(1) Background: This retrospective cohort study aimed to investigate the cephalometric evaluation of facial height ratio (FHR) and growth patterns. (2) Methods: We assessed facial height ratios, Y-axis to SN angle, and growth patterns in 94 participants from Timis county using digital cephalograms. Participants were categorized based on Angle’s classification. Cephalograms were digitally traced and analyzed using WebCeph imaging software. Statistical analysis was conducted using Python version 3.11.9. (3) Results: Significant correlations were observed between FHR and craniofacial development, particularly regarding hypodivergent growth patterns. In a sample of 94, molar classes showed varying patterns: Class I—33.3% hyperdivergent, 61.5% normodivergent, 33.3% hypodivergent. Class II—50% hyperdivergent, 30.8% normodivergent, 52% hypodivergent. Class III—16.7% hyperdivergent, 7.7% normodivergent, 14.7% hypodivergent. Y-axis to SN angle values were within normal limits across groups (Group I: 65.0 (IQR: 61.2-69.0), Group II: 65.0 (IQR: 62.0-69.0), Group III: 67.0 (IQR: 59.7- 69.0). A strong negative correlation was found between Y-axis to SN angle and Jarabak’s ratio (r = -0.72, p < 0.001), highlighting the need for holistic assessment methods in orthodontic practice. (4) Conclusion: Patients from Timis county predominantly exhibit a hypodivergent growth pattern across all malocclusion types. Understanding these patterns is essential for comprehensive orthodontic treatment planning. Further research is needed to explore the implications of these findings on treatment outcomes and patient care.

Despite various interventions in road safety work, fatal and severe road traffic accidents (RTAs) remain a significant challenge leading to human suffering and economic costs. Understanding the multicausal nature of RTAs, where multiple conditions and factors interact, is crucial for developing effective prevention measures in road safety work. This study investigates the multivariate statistical analysis of co-occurring conditions in RTAs, focusing on single-vehicle accidents with single occupancy and personal injury on Austrian roads outside built-up areas from 2012 to 2019. The aim is to detect recurring combinations of accident-related variables, referred to as blackpatterns (BPs), using the Austrian RTA database. The study proposes Fisher’s exact test to estimate the relationship between an accident-related variable and fatal and severe RTAs (severe casualties). In terms of pattern recognition, the study develops the maximum combination value (MCV) of accident-related variables, a procedure to search through all possible combinations of variables to find the one that has the highest frequency. The accident investigation proceeds with the application of pattern recognition methods, including binomial logistic regression and a newly developed method, the PATTERMAX-method, created to accurately detect and analyse variable-specific BPs in RTA data. Findings indicate significant BPs contributing to severe accidents. The combination of binomial logistic regression and the PATTERMAX-method appears to be a promising approach to investigate severe accidents, providing both insights into detailed variable combinations and their impact on accident severity.

Considering the prevalence of cropping pattern in many Saffron cultivation regions, the continuous cropping obstacle caused the decline in growth and development. These effects justify the necessity of studying agronomic strategies to promote plant quality and production. Herein, the mono cropping, intercrop of Paulownia and Saffron, and intercrop of Soybean and Saffron patterns have been performed. The metabolites of Saffron under three cropping patterns were determined and identified using by an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method. Uni and multivariate statistical analysis were applied to examine the difference between groups and select the significant differential accumulated metabolites. The results showed that a total of 315 compounds were significantly changed in three comparison groups. Phenylalanine metabolism, linoleic acid metabolism, and flavonoid biosynthesis pathway has been greatly enriched by the changed metabolites. The phenyl lactate, trans-2-Hydroxy-cinnamate, γ-Linolenate, 9-oxo-octadecadienoic acid, 13-0xo-0ctadecadienoic acid, 9,12,13-TriHOME of those metabolites showed significant differential accumulation in Saffron under three cropping patterns. And the accumulation of safranal and picrocrocin related compounds, such as Crocetin, Crocin showed a similar variation regularity. These indicate that there may be a close internal relationship between the cropping pattern and the biosynthesis of metabolites related to endogenous substances and Saffron quality formation.

Coilia nasus is an important fish resource in the Yangtze River, and the Yangtze River Estuary is a crucial migration pathway for it. In this study, we used otolith microchemistry to analyze the strontium/calcium (Sr/Ca) ratios and Sr contents in the sagitta otolith of C. nasus from the south branch (SB) and north branch (NB) of the Yangtze River Estuary, and obtained the diversity of migration patterns and spawning grounds distribution for C. nasus. The results indicate that C. nasus from both branches include two types of habitat history: freshwater (F)-brackish water (B) (Type I) and F-B-seawater (S) (Type II), with Type I being dominant at 62.50% in both branches. The C. nasus from SB comprises six migration patterns, while that from NB has seven migration patterns. The C. nasus from both branches hatch in F habitats. At the time of capture, the C. nasus from SB predominantly remain in F, accounting for 62.5%, while C. nasus from NB primarily stay in B, accounting for 87.5%. Throughout the migration process, C. nasus from both branches switch between different habitats, with C. nasus from NB exhibiting more frequent transitions between F and B, showing a greater reliance on the estuarine brackish habitat. The radius of the first blue region near the core (Lf) and freshwater coefficient (Fc) of otolith for C. nasus from both branches are divided into three groups: Long-distance freshwater dependence (LD), medium-distance freshwater-dependent (MD), and short-distance freshwater dependence (SD), with the LD only appearing in the SB, while the NB is primarily represented by the MD. There is a correlation between the differences in Lf among different groups of C. nasus and the differences in the distance from the spawning grounds of C. nasus in different sections of the Yangtze River to the Estuary (DYRE), reflecting the distribution pattern of C. nasus spawning grounds in different sections of the Yangtze River. This study provides theoretical guidance for the protection of migration pathway and maintenance of spawning grounds for C. nasus, which has significant practical value in the precise management of C. nasus resources in the Yangtze River Estuary.

The Bax inhibitor-1 (BI-1) gene family, which is required for plant growth, development, and stress tolerance, remains largely unexplored in cauliflower. In this study, we identified and characterized cauliflower BI-1 family genes. On the basis of aligned homologous sequences and collinearity with Arabidopsis genes, we identified nine cauliflower BI-1 genes, which encoded proteins that varied regarding length, molecular weight, isoelectric point, and subcellular localization (i.e., Golgi apparatus, plasma membrane, cell membrane, and chloroplast). Phylogenetic analyses detected evolutionary conservation and divergence among these genes. Ten structural motifs were identified, with Motif 5 crucial for inhibiting apoptosis. According to the cis-regulatory elements in their promoters, these genes likely influence hormone signaling and stress responses. Expression profiles among tissues highlighted the diversity in the functions of these genes, which were significantly expressed in the silique and root. Focusing on BobBIL4, we investigated its role in brassinosteroid (BR)-mediated root development and salt stress tolerance. BobBIL4 expression levels increased in response to BR and salt treatments. The functional characterization of this gene in Arabidopsis revealed it enhances root growth and salinity tolerance. These findings provide insights into BI-1 gene functions in cauliflower, while also highlighting the potential utility of BobBIL4 for improving crop stress resistance.

In the present era, there is no longer a necessity to rely on outdated and laborious methods for attendance management in the field of education. Managing attendance for large groups of students in a classroom can be a challenging and time-consuming task when it comes to recording data. Fortunately, modern technologies offer us the opportunity to streamline attendance management and make it more efficient. One effective approach is Real-Time Face Recognition, which simplifies the process of tracking attendance for numerous students daily. We employ the Haar cascade classifier to identify positive and negative facial attributes, along with the LBPH algorithm for accurate face recognition. These techniques are implemented using Python programming language and the OpenCV library while incorporating a user-friendly Tkinter GUI (Graphical User Interface) for seamless usability. By embracing these advancements, we can revolutionize how attendance is managed in educational environments.

In modern times, technology has become more than just a tool; it is a vital component of our lives, driving society and humanity towards new horizons, better living standards, and solu-tions for complex, global challenges. This article explores the world of dependable systems, specifically focusing on system design, software solutions, and architectural decisions that fa-cilitate collaborative work. It aims to dive into the intricacies of designing robust and effective document collaboration software. Throughout this paper, readers will gain insights into the proposed design process, enabling them to understand, learn from, and critically evaluate the examined methodologies and outcomes. Like everything else in the software technology field, there are multiple solutions to any given problem, and this work is no exception to this rule. The objective of this study is to provide a detailed architectural overview of the microservices pattern in an orchestrated cloud environment based on independent containers. To examine the pros and cons of such a system, the paper will detail how a real-time document collaboration system can benefit from such an architecture regarding availability, elasticity, scaling, and disaster recovery. Moreover, the paper will analyze how cloud-native technologies can be used to create a scalable platform solution, capable of handling traffic, dynamic resource storage, asynchronous com-munication, and application scaling. The intricate nature of this system renders this paper a valuable resource for prospective investigations within the domain of dependable systems, cloud computing, and distributed systems. This paper not only showcases the design and implementation process but also sets a founda-tion for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture.

Understanding the structural intricacies of RNA molecules is essential for deciphering numerous biological processes. Traditionally, scientists have relied on experimental methods to gain insights and draw conclusions. However, the recent advent of advanced computational techniques has significantly accelerated and refined the accuracy of research results in several areas. A particularly challenging aspect of RNA analysis is the prediction of its secondary structure, which is crucial for elucidating its functional role in biological systems. This paper deals with the prediction of pseudoknots in RNA, focusing on two types of pseudoknots: K-type and M-type pseudoknots. Pseudoknots are complex RNA formations in which nucleotides in a loop form base pairs with nucleotides outside the loop and thus contribute to essential biological functions. Accurate prediction of these structures is crucial for understanding RNA dynamics and interactions. Building on our previous work in which we developed a framework for the recognition of H- and L-type pseudoknots, an extended grammar-based framework tailored to the prediction of K- and M-type pseudoknots is proposed. This approach uses syntactic pattern recognition techniques and provides a systematic method to identify and characterize these complex RNA structures. Our framework uses context-free grammars (CFGs) to model RNA sequences and predict the occurrence of pseudoknots. By formulating specific grammatical rules for type K and type M pseudoknots, we enable efficient parsing of RNA sequences to recognize potential pseudoknot configurations. This method ensures an exhaustive exploration of possible pseudoknot structures within a reasonable time frame. In addition, the proposed method incorporates essential concepts of biology, such as base pairing optimization and free energy reduction, to improve the accuracy of pseudoknot prediction. These principles are crucial to ensure that the predicted structures are biologically plausible. By embedding these principles into our grammar-based framework, we aim to predict RNA conformations that are both theoretically sound and biologically relevant.

Before calcification begins, the early embryonic and fetal skeletal development of both mammalian Homo sapiens and the chondrichthyan fish Raja asterias consists exclusively of cartilage. This cartilage is formed and shaped through processes involving tissue segmentation and the frequency, distribution, and orientation of chondrocyte mitoses. In the subsequent developmental phase, mineral deposition in the cartilage matrix conditions the development further. The stiffness and structural layout of the mineralized cartilage have a significant impact on the shape of the anlagen (early formative structures of organs or tissues) and the mechanical properties of the skeletal segments. The fundamental difference between the two studied species lies in how calcified cartilage serves as a scaffold for osteoblasts to deposit bone matrix, which is then remodeled. In contrast, chondrichthyans retain the calcified cartilage as the definitive skeletal structure. This study documents the distinct mineral deposition pattern in the cartilage of the chondrichthyan R. asterias, in which calcification progresses with the formation of focal calcification nuclei or “tesserae”. These are arranged on the flat surface of the endo-skeleton (crustal pattern) or aligned in columns (catenated pattern) in the radials of the appendicular skeleton. This anatomical structure is well adapted to meet the mechanical requirements of locomotion in the water column. Conversely, in terrestrial mammals, endochondral ossification (associated with the remodeling of the calcified matrix) provides limb bones with the necessary stiffness to withstand the strong bending and twisting stresses of terrestrial locomotion. In this study, X-rays of marine mammals (reproduced from previously published studies) document how the endochondral ossification in dolphin’s flipper adapts to the mechanical demands of aquatic locomotion. This adaptation includes the reduction in the length of the stylopodium and zeugopodium and an increase in the number of elements in the autopodium’s central rays.

Dendritic spines are protruding membrane organelles from neuronal dendrites. The quantity of dendritic spines formed seems to be regulated with the -BAR family proteins, as they would initiate the membrane curvature to form the spines; however it is unclear whether the positions of these spines are selected based on spatial information due to the location of pre-existing spines or are selected via random molecular interactions. Through measuring the distance between dendritic spines from the images of Prada et. al (6), a distribution graph was created to determine whether the spine formations followed a random distribution pattern. Two groups of images were measured: dendritic spines when extracellular vesicles (EV) neuron contact was normal (control) and when EV-neuron contact was inhibited (experimental), preventing the transfer of MicroRNA (miRNA). Two randomly generated simulation groups were then created with the same spine density as the control and experimental conditions. Distribution graphs were created for the two randomly generated simulation groups as well. It was found that the randomly generated control simulation and the control group had significantly similar distribution; however, the randomly generated experimental simulation and the experimental simulation showed less of a similar distribution. These findings show that an element of randomness was removed when EV-neuron contact was inhibited.

During tensile testing of materials, strain measurement is conducted using either contact or non-contact methods. Contact methods offer high accuracy and precision but are limited by the specimen's thickness and dimensions, whereas non-contact methods minimize damage to thin specimens and allow measurements in various environments, though they require longer prep-aration and calculation times. This paper proposes a circular grid marking pattern and a strain prediction algorithm using artificial intelligence (AI), which simplifies the preparation process and allows strain prediction without additional equipment. The circular grid pattern can be ar-ranged in various configurations from 1×5 to 5×7, and a laser marker, which requires minimal time, was used to engrave the pattern on the specimen to shorten the preparation time. The AI model, trained on image-based data, enables strain calculation regardless of the specimen's gauge length and size, and allows measurement of local strain as well as gauge-length strain. The reliability of this concept was verified by applying it to tensile testing.

Single nucleotide polymorphisms in the mitochondrial genome have been investigated in relation to breast cancer. Certain variants could be associated with an increased risk of this malignant disease. These associations underline the importance of mitochondrial function in cancer biology and highlight the potential for mtDNA-based biomarkers and future therapies. The general objective of this research was to develop a model which is capable of identifying nonlinear patterns in breast cancer mitochondrial sequences. Association rules were used to explore mtDNA variant positions. The analysis included 41 breast cancer patients and 28 control samples. An a priori algorithm identified significant association rules with lift > 1 and confidence > 0.5. A total of 5562 rules for cancer and 157,140 for control sequences were refined after redundancy removal. A total of 150 associations were identified, of which only 78 showed significant support and confidence, while 315 and 1438 positions showed strong associations with breast cancer. Association rules analysis revealed significant patterns, especially in sequences associated with the control region and a specific locus around genes coding for tRNAs and NADH dehydrogenase subunits. However, further research is necessary to establish causality, clinical relevance, and to confirm these findings.

Quality of life (QoL) focuses on a person’s ability to live a fulfilling life. In the elderly population, it helps in determining successful aging. Because of a scarcity of information regarding predictors of QoL in the elderly population in developing countries, this study was undertaken to assess the overall QoL and its predictors in the elderly population in an urban setting of Bangladesh. In this cross-sectional study, 275 participants were enrolled by systematic sampling at the outpatient department of a tertiary care hospital in Dhaka, Bangladesh. Data were collected by using a pretested semi-structured standard questionnaire for QoL (OPQOL-35). Pearson’s correlation was used to assess the association between QoL and sociodemographic factors. The Chi-square test was done for assessing the statistical significance between categorical variables. Multivariate linear regression was conducted to identify predictors of QoL, after controlling for potential confounders. The median age of the participants (n = 275) was 65 years (range, 60 to 85; 25th and 75th percentile, 60 and 68, respectively). The majority (78%) of them were married and 20% were widowed or divorced. The median score of QoL was 113 (25th and 75th percentile, 101 and 124, respectively). Most of the participants had a very poor (bad as can be) or poor (bad) QoL. Only 7.3% were observed to have “good” QoL (scores 140 or more). Females had significantly poorer QoL scores compared to males (p = 0.01). Educational status, marital status, body mass index and sleep duration significantly predicted QoL in a multiple regression analysis. In conclusion, the QoL of the elderly individuals in Bangladesh was very poor or poor. Future research should focus on service-oriented interventions, especially targeting women. Counseling of elderly people for enhancing their quality of life may include improving sleep patterns, healthy diets, regular exercise, and caring for their mental health.

This work reports a characterization of crystallographic phases and chemical composition of hercynite-spinel (FeAl2O4) natural long crystals and their powders using X-ray Diffraction, Scanning Electron Microscopy, Inductively Coupled Plasma mass spectrometry, and mineralographic/petrographic analysis. The samples studied show a high content of hercynite with Neumann bands/Widmanstätten patterns, coexisting with other crystallographic phases such as corundum, spinel (MgAl2O4), esseneite, kamacite, hedenbergite, pseudobrookite, and ulvospinel. The diffractograms of two of the samples examined exhibit an extraordinary sharpness of the diffraction peaks that determines a high degree of crystallinity, which is hard to obtain in hercynite synthesized by artificial methods. In addition, the hercynite natural samples are less porous than the artificially synthesized hercynite. The x-ray diffraction pattern of one of the pulverized crystalline samples allowed us to estimate the percentage of the main phases present. The crystallographic existent phases with the highest participation in one of the spinel samples were hercynite (43.4%), corundum (18.7%), spinel (18.4%), esseneite (17.2%), and kamacite with a 2.3 %. These results contribute to the structural characterization of this unique material widely used in many technological applications.

Evaluation ecosystem service value (ESV) is critical for “lucid waters and lush mountains are invaluable assets”. However, the ESV estimation and spatial-temporal analysis for mountainous soil erosion area is rare, e.g., Changting county, China. In this study, we developed a remote sensing driven mountainous equivalent factor (RS-MEF) method to estimate the ESV of soil erosion area in subtropical mountain. It is a hybrid of a conventional equivalent factor framework and the remote sensing techniques for mountains, and achieves several highlights of spatial adjustment using carbon sink with vegetation canopy, improvement spatial resolution, and removal topographic effect. Using the RS-MEF method, we estimated that the ESV of Changting county was about 15.80 billion CNY in 2010 and 34.83 billion CNY in 2022. Specifically, the ESV per unit area of major soil erosion area (MSEA) in the county was less than that of non-major soil erosion area (n-MSEA), however, the ESV growth rate of MSEA from 2010 to 2022 was faster than that of n-MSEA. Therefore, the ESV gap between two areas was shortened from 28.99% in 2010 to 15.83% in 2022. Topographic gradient effect analysis illustrates that the area with high elevation and small slope is one control focus in the next step. Our study indicates that the ecological restoration in the county has made great achievements in the ESV perspective, with low ESV area shrank evidently in MSEA; and the achieved knowledge of the ESV growth and inherent factors is valuable and instructive for the next soil and water conservation.

This article explores the efficiency of various clustering methods for image segmentation under different luminosity conditions. Image segmentation plays a crucial role in computer vision appli-cations, and clustering algorithms are commonly used for this purpose. The search for an adaptive clustering mechanism aims to ensure maximum symmetry of real objects with objects/segments in their digital representations. However, clustering methods performance can fluctuate with varying lighting conditions during image capture. Therefore, we assess the performance of several clustering algorithms — including k-means, K-Medoids, fuzzy c-means, Possibilistic C-Means, Gus-tafson-Kessel, Entropy-based Fuzzy, Riddler-Calvard, Kohonen Self-Organizing Maps, and Meanshift — across images captured under different illumination conditions. Additionally, we develop an adaptive image segmentation system utilizing empirical data. Conducted experiments highlight varied performance among clustering methods under different luminosity conditions. This research enhance better understanding of luminosity's impact on image segmentation and aiding in method selection for diverse lighting scenarios.

Pipelines extend thousands of kilometers to transport and distribute oil and gas. Given the challenges often faced with corrosion, fatigue, and other issues on steel pipes, the demand for glass fiber reinforced plastics (GFRP) pipes is increasing in the oil and gas gathering and transmission systems. However, the medium transported through these pipelines contains multiple acid gases such as CO2 and H2S, as well as ions including Cl-、Ca2+、Mg2+、SO42-、CO32- and HCO3-. These substances can cause a series of problems, such as aging, debonding, delamination, and fracture. In this study, a series of aging damage experiments were conducted on V-shaped GFRP pipes with depths of 2mm and 5mm. The aging and failure of GFRP were studied under the combined effects of external force and acidic solution using acoustic emission (AE) techniques. It was found that the acidic aging solution promoted matrix damage, fiber/matrix desorption, and delamination damage in GFRP pipes over a short period. However, the overall aging effect was relatively weak. Based on the experimental data, the SSA-LSSVM algorithm was proposed and applied to the damage pattern recognition of GFRP. An average recognition rate of up to 90% was achieved, indicating that this method is highly suitable for analyzing AE signals related to GFRP damage.

This study involves the development of a hybrid forecasting framework that integrates two different models in a framework to improve prediction capability. Although the concept of hybridization is not a new issue in forecasting, our approach presents a new structure that combines two standard simple forecasting models uniquely for superior performance. Hybridization is significant for complex data sets with multiple patterns. Such data sets do not respond well to simple models, and hybrid models based on the integration of various forecasting tools often lead to better forecasting performance. The proposed architecture includes serially connected ARIMA and ANN models. The original data set is first processed by ARIMA. The error (i.e., residuals) of the ARIMA is sent to the ANN for secondary processing. Between these two models, there is a classification mechanism where the raw output of the ARIMA is categorized into three groups before they are sent to the secondary model. The algorithm is tested on well-known forecasting cases from the literature. The proposed model performs better than existing methods in most cases.

A new data processing method based on Machine Learning (ML) algorithms has been developed and tested in clinical environments during COVID-19 trials at the Medical University of South Carolina (MUSC). Breath samples have been collected in 2020–2021 from 100 participants using gas chromatography combined with ion mobility spectrometry (GC-IMS, G.A.S. mbH). Polymerase chain reaction (PCR) tests combined with clinical diagnostics were used as a reference method. Once the ML training-testing cycle is completed, the diagnostics of a single data set may be completed in as little as a few seconds. A convincing difference in the Volatile Organic Compounds (VOS) breath biomarker signature with COVID-19 positive and negative participants has been found. This approach is a generic method that can be applied to data sets collected with other types of hardware, e.g., different settings of GC, GC-MS, GC-GC, or other methods providing high information density in 2-dimensional data sets.

Background: Blood pressure (BP) is characterized by a circadian rhythm (Circr), with lower nighttime values, called dipping. Non-dipping is associated with higher CVD risk. The Circr of urinary sodium excretion (NaCle), peaking during the day, is linked to BP patterns. Physical ac-tivity (PA) is known to improve BP control and enhance the dipping phenomenon, but its possi-ble effect on NaCle remains unclarified. Objectives: This study aimed to investigate the correla-tion between PA and the Circr of NaCle and to determine if the relationship is independent of age, sex, BP values, dipping pattern, and salt intake. Methods: A cross-sectional analysis was conducted using data from the Ticino Epidemiological Stiffness Study, involving 953 participants in Switzerland. Data collection included standardized questionnaires, blood samples, 24-hour urine collections, and ambulatory BP monitoring. Participants were categorized into sedentary, partially active, and active. The effect of PA, NaCl intake, and dipping on the day/night NaCle ratio, was assessed with multivariable linear regressions. Results: Participants median age 49 years, with 78% having normal BP values and 47% exhibiting a dipping pattern. 51% were classi-fied as sedentary and 22% as partially active. The median NaCl intake was 7.9 g/day. The youngest subjects had a higher hourly NaCle ratio compared to older subjects. Higher NaCl in-take correlated with increased BP, phenomenon more pronounced in men and younger subjects. The hourly day/night NaCle ratio positively correlates with dipping; however, PA did not show a significant correlation with the NaCle ratio. Conclusion: This study indicates that while the day/night NaCle ratio correlates with the dipping pattern, PA is unrelated to the circadian rhythm of renal sodium handling. The beneficial effects of PA on BP and cardiovascular health thus appear to be mediated through mechanisms other than NaCle. These are explorative find-ings only, but relativize the need for further investigations on the topic.

In this letter, we propose a pattern-diversity antenna with different radiation patterns at two different frequency bands (f1 and f2) (f1: broadside radiation pattern, f2: conical radiation pattern). The proposed structure consists of a central circular antenna and two annular ring antennas; each of the three antennas has individual ports. Two of the ports exhibit orthogonal broadside radiation patterns; the other two ports exhibit orthogonal conical radiation patterns. Thus, they have polarization diversity characteristics. To improve isolation between ports, the inner part of the annular ring antennas is shorted via array, and the outermost port is positioned orthogonal to the other ports. Using this configuration, the isolation between ports was measured as -26.7 dB and -30.1 dB at the two frequency bands, respectively. Experimental results based on the fabricated prototype show that the proposed antenna achieves -10 dB bandwidths of 240 MHz (5.71~5.95 GHz) and 210 MHz (7.69~7.9 GHz) at f1 and f2, respectively.

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentanglement (PDD) model, developed in our earlier work. Applied to the large data, the eICU Collaborative Research Database for sepsis risk assessment, the proposed algorithm can effectively discover statistically significant association patterns, generate an interpretable knowledge base for interpretability, cluster samples in an unsupervised learning manner, and detect abnormal samples from the dataset. As shown in the experimental result, our method outperformed K-Means by 38% on the full dataset and 47% on the reduced dataset for unsupervised clustering. Multiple supervised classifiers improve accuracy by an average of 4% after removing abnormal samples by the proposed error detection approach. Therefore, the proposed algorithm provides a robust and practical solution for unsupervised clustering and error detection in healthcare data.

This paper presents a comprehensive comparative analysis of four different computational vision algorithms for implementing an unpalleting system in a factory environment, under typical edge computing constraints. The primary objective is to automate the process of detecting and locating specific variable-shaped objects on a pallet, enabling a robotic system to accurately unstack them. The four algorithms evaluated are Pattern Matching, Scale-Invariant Feature Transform, Oriented FAST and Rotated BRIEF, and Haar cascade classifiers. Each technique is described in detail in this paper, and their implementations are outlined. Experimental results are thoroughly analyzed, assessing the algorithms’ performance based on accuracy, robustness to variability, computational speed, detection sensitivity, and resource consumption. The findings reveal the strengths and limitations of each algorithm, providing valuable insights for selecting the most appropriate technique based on the specific requirements of the unpalleting system. This research contributes to the advancement of automated object detection and localization in industrial environments, paving the way for more efficient and reliable unpalleting systems.

With the galaxy J101652.52 as a model galaxy, this paper studied on the temporal duration of optically observed spiral patterns in disc galaxies is based on the finite reservoir of hydrogen available without replenishment following the initial formation of these well-isolated galaxies. The galaxy J101652.52 exhibits a grand design spiral pattern of two wide open spiral arms with perfect central symmetry, has only rear side trail effect, which clearly indicates that there is no corotation circle, therefore, the Density wave theory proposed for the spiral arm formation may not be applicable in this galaxy. The results reveal a gradual decline in observable spiral arms regardless of any spiral arm formation mechanism. This reduction occurs after half-loop rotation (as defined in the paper) as hydrogen reserves deplete, hindering new star formation. Ultimately, spiral patterns may possibly become optically invisible at normal conditions after a full-loop rotation (as defined in the paper) with hydrogen depletion, even if the formation mechanism remains active. The spiral galaxies with spiral arms decoupled from galactic bars or having soft spiral structures shall have similar results as long as that the spiral pattern rotation speed is significant different from the galactic matter rotation speed. Most of observed spiral galaxies have soft spiral structures, their spiral patterns dynamically change constantly. The results of this study support the idea of short-lived spiral patterns compared to the lifespan of the spiral galaxies. The spiral arm formation may occur once like the onetime firework show in a galaxy’s life based on the limited availability of hydrogens. A concise, universally applicable mechanism for spiral arm formation across various galaxies should exist which provides a single mathematical formula to describe the broad range of morphologies of the spiral arms with few adjustable parameters. Some exceptions may be explained within this framework. Furthermore, the observed data on spiral pattern and galactic bar rotation speeds in the Milky Way require rigorous verification, particularly concerning the winding problem.

Tori are bony growths in the mouth caused in general by genetic and environmental factors. Oral tori may grow over time and interfere with oral hygiene, speech, mastication and the application of dentures. The aim of this study is to evaluate the prevalence and patterns of torus mandibularis and torus palatinus according age and gender among patients attending the Diamond Dental Hospital in Tirana. Methodology. A case-series study conducted at DDH from February 1-30 April 2024. Written consent was taken from each participant and the questionnaire comprises some variables. The patients were examined intraoral only by one examiner and were taken photos from participants having positive findings. Results. The prevalence of oral tori in Albania was very high 48.4% and the peak incidence was 18-29 age group (54.2%). The most common type was TM 39.3%. The most prevalent form for TP was flat (71.4%) and for TM was solitary bilateral (47.9%). Conclusions. The prevalence of oral tori was found to be very high and not related to gender or bruxism. Dental professionals should be aware of the high occurrence of oral tori and their importance in dental practice. Nevertheless, further assessment of the prevalence of tori in a larger sample is required.

The once near-extinct Russell’s viper has recently come back to the area beyond its historical range. A couple of decades ago, its distribution was confined to 11 districts of Bangladesh. Hence, the study aims to update the distributional map of Russell’s Viper (Daboia russelii) across the country and find out the surges' causal factors. Both primary and secondary data were utilized in this study. It revealed that the distributional range of this snake was expanded from 22 to 33 districts in 2024. The respondents noted that climatic stressors like high humidity accompanied by hot weather, increased salinity, and increased frequency of flooding facilitated the spreading of the viper across the country. The cropping pattern and crop diversification were another major contributing factor. The shifting of the single-cropped area to a multi-cropped area in the Barind tract increased its main prey rats. Contrarily, the killing of natural predators such as foxes, monitor lizards and mongoose led to the rise in the snake population. The destruction of vegetation coverage in the upper part of the Padma Basin facilitated the movement of Russell's vipers downstream.

The thermal conditions of transitional (ranging from warm to cold) coldwater streams impact the ranges and resource availabilities for biota inhabiting these lotic systems. With ongoing climate change and increasing land modifications, thermal boundaries may shift, altering thermal transition zones and their biotic communities. The objective of this study was to investigate the condition of trout across three forks of the Whitewater River catchment and to investigate factors influencing fish community composition and distribution. Each fork was characterized into three separate sections: headwater (coolwater), middle (warmwater), and lower (coldwater). Springs were identified throughout each fork, with greatest concentrations in the lower sections of each fork. Using single-pass electrofishing, we sampled 61 sites across the three forks in the Whitewater River system (North = 21 sites, Middle = 19, South = 21), and catch statistics were used to calculate diversity, trout abundance, and trout condition. In general, diversity increased, and trout were healthier but less abundant in middle and headwater sections, whereas diversity decreased slightly, trout condition decreased, and trout abundance increased in lower reaches, with changes differing somewhat among forks. Canonical correlation analysis had strong significant correlations showing simpson diversity and condition increase going upstream with high non trout abundance and catch rates while trout catch rates and reach width decrease. The Whitewater River is a catchment exhibiting transitional temperature-pattern characteristics with generally low fish community diversity and trout conditions that range from thin, normal, and robust. Dominated by a changing landscape (agriculture) and intensifying climate change, we may begin to see stream temperatures increase along with species diversity. Understanding how spring temperature influences species composition and distribution can bring potential stressors to light increasing our understanding of thermal conditions and to help mitigate the negative impacts from land use and climate change.

Although promoting healthy eating is a policy objective, the controllability of dietary habits remains uncertain. The personal dietary patterns reflect many factors, of which some are relatively controllable for individual, and others are not. In this article, assuming that some sort of information about controllability of dietary habits is contained in the observed pattern of food consumptions, we focused on dietary pattern on its own. We introduced a statistical descriptive model for data on food frequency questionnaire, estimated strength of pairwise linkage between foodstuffs, and grouped foodstuffs by applying community detection to the networks of the estimated inter-food linkages. Those linkages represent co-movement of pairs of foods consumption. Furthermore, we demonstrated an analysis on the relationship between health of mind and dietary habits considering the aspect of controllability of dietary habits. Using an observational study in Japan, we obtained the following results: 115 foodstuffs were divided into 3 groups for both of genders, but the compositions were different by gender; in the analysis of mental health, some stress response items were associated with the dependence on some of those food groupings. As the grouping of foodstuffs based on our estimation depicted the internal structure of dietary habit that a healthy eating policy should regard as constraint, it follows that we should design the policy along the line with that grouping.

Inflammation is the body’s response to infection, injury, or other stimuli. Acute inflammation is a crucial component of the immune system’s defense, aimed at eliminating infected or damaged cells and halting disease progression. A subtle interaction between pro- and anti-inflammatory processes determines its progression to inflammation resolution or to chronic inflammation. In this study, we propose a generic model of inflammation through a system of reaction-diffusion equations involving various inflammatory and anti-inflammatory cells and cytokines. We investigate the formation of patterns, determined by the emergence of Turing structures, through linear stability analysis and numerical simulations. These theoretical findings are further supported by observations of similar patterns in skin diseases.

Biological nitrogen fixation (BNF) by symbiotic bacteria plays a vital role in sustainable agriculture. However, current quantification methods are often expensive and impractical. This study explores the potential of Raman spectroscopy, a non-invasive technique, for rapid assessment of BNF activity in soybeans. Raman spectra were obtained from soybean plants grown with and without rhizobia bacteria to identify spectral signatures associated with BNF. δN15 isotope ratio mass spectrometry (IRMS) was used to determine actual BNF percentages. Partial least squares regression (PLSR) was employed to develop a model for BNF quantification based on Raman spectra. The model explained 80% of the variation in BNF activity. To enhance the model's specificity for BNF detection regardless of nitrogen availability, a subsequent elastic net (Enet) regularization strategy was implemented. This approach provided insights into key wavenumbers and biochemicals associated with BNF in soybeans.

This paper experimentally reveals some of the resources offered by the evolution of the instantaneous active electric power in describing the state of three-phase AC induction asynchronous electric motors (with squirrel-cage rotor) operating under no-load conditions. A mechanical power is required to rotate the rotor at no-load and this mechanical power is satisfactorily reflected in the constant and variable part of instantaneous active electric power. The variable part of this electrical power should necessarily have a periodic component with the same period as the period of rotation of the rotor. The paper proposes a procedure for extracting this periodic component description (as a pattern, by means of a selective averaging of instantaneous active electrical power) and analysis. The time origin of this pattern is defined by the time of a selected first passage through the origin of an angular marker placed on the rotor, detectable by a proximity sensor (e.g. a laser sensor). The usefulness of the pattern in describing the state of the motor rotor has been demonstrated by several simple experiments which show that a slight change in the no-load running conditions of the motor (e.g. by placing a dynamically unbalanced mass on the rotor) has clear effects in changing the shape of the pattern.

Previous reviews have investigated machine learning (ML) models used to predict the risk of developing preeclampsia but have not described how the ML models are intended to be deployed throughout pregnancy or feature performance. The aim of this study is to provide an overview of the existing ML models and their intended deployment patterns and performance along with identified features of high importance. This review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. PubMed, Engineering Village, and the Association for Computing Machinery were searched between January and February 2024. A total of 86 studies were found of which 14 were included. Out of 12 studies, eight showed the intent to use the ML model as a single-use, two intended a dual-use, and two intended multiple-use. A total of seven studies listed the features of the highest importance. Systolic and diastolic blood pressure were listed along with mean arterial pressure to be of high importance. Out of four studies intending to use the ML model more than a single-use, three of them were conducted in the years 2023 and 2024, whereas the remaining study is from 2011. No ML model emerged as superior across the subgroups of PE. Utilizing body mass index and either mean arterial pressure or diastolic blood pressure and systolic blood pressure may benefit the performance. The deployment patterns are mainly single use being within the gestation weeks 11+0 to 14+1.

Inducer of C-Repeat Binding Factor (CBF) expression (ICE), a well-known MYC-type bHLH transcription factor, plays a crucial role in the ICE-CBF-cold regulated (COR) cold signaling pathway. Brassica rapa (B. rapa), an important oilseed and vegetable crop, exhibits strong chilling and freezing tolerance. However, the exact molecular mechanisms by which ICE1 functions in B. rapa remain unclear. Here, 41 ICE1 homologous genes were identified from six widely cultivated Brassica species using a bioinformatics approach. These genes exhibit high conservation but reveal evolutionary complexity between diploid and allotetraploid species. Low-temperature stress induced ICE1 homolog expression, with patterns differing between strong and weak cold-tolerant varieties. Two novel ICE1 paralogs, BrICE1 and BrICE2, were cloned from Longyou 6. They positively regulate cold tolerance in B. rapa via a CBF-dependent pathway, contributing to reactive oxygen species (ROS) scavenfging and osmotic adjustment. Immunoblot analysis revealed that low temperatures induce BrICE1 and BrICE2 degradation via the 26S-proteasome pathway. In summary, ICE1 exhibits complex evolutionary relationships in Brassica species. BrICE1 and BrICE2 positively regulate cold tolerance via the CBF-dependent pathway and ROS scavenging mechanism and are also responsible for balancing the development and cold defense of B. rapa.

Monitoring the status and dynamics of desertification is one of the most important parts of combating desertification. In this study, 30m high-resolution information on land desertification and restoration in the HRB was extracted from the land cover database. The results indicate that land desertification coexists with land restoration in the HRB. At different periods, the area of land restoration is much larger than the area of land desertification in the HRB, and the HRB has been in a process of land restoration. Upstream of the HRB, there is a continuing trend of increasing land desertification associated with overgrazing in a context where climate change favors desertification reversal. In the middle and lower reaches, although both climate variability and human activities favor land desertification, the process of land desertification in the middle and lower reaches is still being reversed and land restoration dominates. The implementation of the Eco-Environmental Protection Project and desertification control measures, especially the EWDP, is contributing to the reversal of desertification in the middle and lower reaches of the HRB. However, the EWDP has indirectly led to the lowering of the water table in the middle reaches, resulting in local vegetation degradation. Therefore, there is therefore an urgent need to transform the economic structure of the middle reaches to cope with water scarcity and land desertification.

Background and Objectives: Pulmonary Hypertension (PH) is a clinical condition with high mortality rates, particularly in patients over 65. Current guidelines recommend assessing the Probability of Pulmonary Hypertension (PHP) using advanced echocardiography, before pro-ceeding to right heart catheterization. This study proposes using the common femoral vein (CFV), an accessible vein that reflects right atrial pressure, as an alternative method to assess the like-lihood of severe PHP. Materials and Methods: This prospective observational study included 175 emergency patients from three hospitals. Ultrasound assessed the Pulsed Wave Doppler (PW-Doppler) morphology of the CFV. This diagnostic yield for high PHP was evaluated along-side traditional ultrasound parameters (right-to-left ventricular basal diameter ratio greater than 1 (RV>LV), septal flattening, right ventricular outflow acceleration time of less than 105 ms and/or mesosystolic notching, pulmonary artery diameter greater than the aortic root diameter or over 25 mm, early pulmonary regurgitation maximum velocity >2.2 m/s, TAPSE/PASP less than 0.55, in-ferior vena cava (IVC) diameter over 21 mm with decreased inspiratory collapse, and right atrial (RA) area over 18 cm²). Results: The CFV's PW-Doppler cardiac pattern correlated strongly with high PHP, showing a sensitivity (Sn) of 72% and a specificity (Sp) of 96%. RA dilation and TAPSE/PASP < 0.55 also played significant diagnostic roles. Conclusions: The CFV's PW-Doppler cardiac pattern is an effective indicator of high PHP, allowing reliable exclusion of this condition when absent. This approach could simplify initial PHP evaluation in emergency settings or where echocardiographic resources are limited.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7-3.8 GHz (76.4%). For a traditional 4G dipole antenna which covers the band 1.71 GHz- 2.69 GHz, it’s difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3-3.8 GHz, which mainly due to the fixed antenna height is no longer a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7-3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7-4.0 GHz). It has an average measured in-band realized gain of 7.0±1.0 dBi and a stable 70∘±5∘ half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1710-2690 MHz and 3300-3800 MHz.

Simple summary This reassessment of the findings from our Phase I/II study seeks to evaluate the effectiveness of SBRT for treating local intermediate-high risk prostate cancer in the absence of androgen-deprivation therapy due to patient’s refusal, with a median follow-up of 6.5 years. Our primary focus is on analysing the treated areas compared to recurrence patterns in the seven patients who experienced local relapse. Additionally, we provide updated data on late toxicities of grade 2 or higher, both genitourinary and gastrointestinal. Abstract Objectives: We investigated spatial patterns between primary and recurrent tumor sites and assessed long-term toxicity after dose escalation stereotactic body radiation therapy (SBRT) to the dominant intraprostatic nodule (DIN). Materials and methods: In 33 patients with intermediate-high risk prostate cancer (PCa), doses up to 50 Gy were administered to the DIN. Recurrence sites were determined and compared to the original tumor development sites through multiparametric MRI and 68Ga-labelled prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (68Ga-PSMA-PET/CT) images. Overlap rates, categorized as 75% or higher for full overlap, and 25-74% for partial overlap, were assessed. Long-term toxicity is reported. Results: All patients completed treatment, with only one receiving concomitant androgen deprivation therapy (ADT). Recurrences were diagnosed after a median of 33 months (range: 17-76 months), affecting 13 out of 33 patients (39.4%). Intraprostatic recurrences occurred in 7 patients (21%), with ≥ 75% overlap in two, a partial overlap in another two, and no overlap in the remaining three patient. Notably, 5 patients with intra-prostatic recurrences had synchronous bone and/or lymph node metastases, while six patients had isolated bone or lymph node metastasis without intraprostatic recurrences. Extended follow-up revealed grade 2 or higher late GU and GI toxicity in 18% (n=6) and 6% (n=2) of the patients. Conclusions: Among patients with intermediate-high risk PCa undergoing focal dose-escalated SBRT without ADT, DIN recurrences were infrequent. When present, these recurrences were typically located at the original site or adjacent to the initial tumor. Conversely, relapses beyond the DIN and in extra-prostatic (metastatic) sites were prevalent, underscoring the significance of systemic ADT in managing this patient population. Advances in knowledge: focal dose escalated prostate SBRT prevented recurrences in the dominant nodule, however extra-prostatic recurrence sites were frequent.

Trichoderma has been widely studied for its potential as a biocontrol agent against plant pathogenic organisms. Trichoderma's biological control mechanisms include competition, modification of environmental conditions, antibiosis, induction of plant defensive mechanisms, and mycoparasitism. Trichoderma species are known to produce a variety of secondary metabolites that have antifungal activity. These metabolites include peptaibols, gliotoxin, and trichokonins. Trichoderma also produces chitinases and β-1,3-glucanases that can degrade the cell walls of fungal pathogens. In addition to direct antagonism against fungal pathogens, Trichoderma can also induce systemic or localised resistance in plants, which is achieved through the production of elicitors such as chitin oligosaccharides and β-glucans that activate plant defence responses. Trichoderma can also form mutualistic associations with plants. In these associations, Trichoderma colonises the roots of plants and promotes plant growth by increasing nutrient uptake and inducing systemic resistance. Using Trichoderma as a biocontrol agent has several advantages over conventional crop protection techniques based on applying synthetic pesticides.

Examining contemporary developments and cutting-edge approaches in the field, this literature review explores how antenna design for transmission lines is changing. Review findings are compiled from a variety of academic sources, including pertinent technical reports published as recently as 2018, conference papers, journal articles, and reports. A variety of antenna topologies suited for transmission lines are evaluated in this paper, including microstrip, slot, and patch antennas, with a focus on theoretical frameworks and practical implementations. This overview clarifies the complex relationship between antenna design and transmission line characteristics by looking at important factors like impedance matching, bandwidth, and radiation pattern management. Notable developments in materials, fabrication methods, and numerical simulations are also examined and their effects on antenna performance explained. Through a comprehensive analysis of the literature, this review offers valuable insights into the state-of-the-art antenna design practices for transmission lines, facilitating informed decision-making and inspiring future research endeavors in this field.

Object-Oriented Programming (OOP) has long been a dominant paradigm in software development, but it's not without its challenges. One major issue is the problem of tight coupling between objects, which can hinder flexibility and make it difficult to modify or extend code. Additionally, the complexity of managing inheritance hierarchies can lead to rigid and fragile designs, making it hard to maintain and evolve the software over time. This paper introduces a software development pattern that seeks to offer a renewed approach to writing code in Object-Oriented (OO) environments. Addressing some of the limitations of the traditional approach, the Puzzle Pattern focuses on extreme modularity, favoring writing code exclusively in interfaces. Concrete classes are subsequently assembled through the implementation of those interfaces, reducing coupling and introducing a new level of flexibility and adaptability in software construction. The highlighted pattern offers significant benefits in software development, promoting extreme modularity through interface-based coding, enhancing adaptability via multiple inheritance, and upholding the SOLID principles, though it may pose challenges such as complexity and a learning curve for teams.

Purpose: To examine the effectiveness of patterned laser trabeculoplasty (PSLT) as an additional treatment for patients of open-angle glaucoma (OAG) receiving maximized ocular hypotensive medications (OHM). Methods: Forty eyes of 33 patients (average age 72.7±10.7 years) who had not previously undergone open glaucoma surgery or laser trabeculoplasty and were treated with maximized OHM between June 2018 and March 2022 were included. A 360-degree PSLT was conducted and postoperative intraocular pressure (IOP) and survival curves at 1, 3, 6, 9, and 12 months were evaluated. Results: According to the Kaplan-Meier survival analysis, the average survival time was 8.1 months with death defined as postoperative IOP reduction of less than 10% or requiring additional treatment. The average survival time was 4.9 months with death defined as postoperative IOP reduction of less than 20% or requiring additional treatment. In the 31 eyes which received no additional treatment after PSLT, the mean preoperative IOP was 18.5±3.9 mmHg, which reduced to 15.3±4.1 mmHg (p=1.62 x 10-6)), 15.5±3.4 mmHg (p=1.51 x 10-5), 15.7±4.0 mmHg (p=1.75 x 10-5), 14.7±4.38 (p=2.89 x 10-6), and 15.0±4.0 mmHg (p=5.74 x 10-9) at 1, 3, 6, 9 and 12 months after PSLT, respectively. The IOP reduction rate one year after PSLT was 18.7%. Thirteen of the 31 eyes (42%) achieved a 20% reduction in IOP compared to the baseline. Conclusion: Adjunctive treatment with PSLT in OAG patients receiving maximized OHM may be effective over 12-months of follow-up.

Adherence to the Mediterranean diet has been shown to lower the risk of developing chronic non-communicable diseases like cardiovascular and neurodegenerative diseases and cancer. Improvements in depression, participation in daily activities in older individuals, weight loss and reduction in adverse pregnancy outcomes are associated with adherence to the Mediterranean diet. The number of studies that have evaluated barriers to the adherence of the Mediterranean diet in the US and in particular, in racial and ethnic minority populations within the US are few. Among Native American and Alaskan Native populations, studies evaluating traditional or alternative Mediterranean diet adherence for chronic non-infectious diseases is unavailable. Mediterranean diet scoring instruments used in studies in European and Mediterranean countries and among white participants in the US fail to capture the dietary patterns of racial and ethnic minority populations. In this narrative review the food components of the traditional Mediterranean diet are discussed, adherence to the Mediterranean diet is examined in Mediterranean and non-Mediterranean countries and barriers preventing adherence to the Mediterranean diet in the US and among racial and ethnic minority populations is reviewed. Recommendations for improving nutrition education and intervention, and increasing adherence and cultural adaptions to the Mediterranean diet are provided.

Present study on land use land cover analysis and taluka wise combination of cropped area, carried out in Beed district of Maharashtra state in India and studied 11 talukas of the district. Secondary data on land use land cover and area in various crops has been collected, compiled and analyzed from various secondary sources. Simple descriptive statistics used to examine the agricultural land use land cover and J.C. Weaver’s crop combination technique was used for taluka wise analysis of crop combinations and on the basis of highest to smallest area engaged in particular crop, crops have been ranked. The study showed that, in the district as a whole, percentage of uncultivated land other than fallow was about 46 percent as compare to net sown area is only 35 percent in total geographical area (1063855ha) of Beed district. The study further revealed that about 42 percent area engaged in food crops and about 58 percent area occupied by nonfood crops, which includes cereals (25%), cotton (19%), pulses (13%), oilseed (12%), sugarcane (5%) and fruits and vegetables (3%). Results of Weaver’s crop combination technique showed that the Wadwani taluka demarcated as most diversified taluka by means of maximum number (sixteen) of crops combinations with the lowest variance value (14) found in the present investigation. Further, the study revealed that the high crop diversity found in Dharur taluka with eighteen crop combinations and the taluka has given first rank amongst others. To derive the crop diversity ranking, taluka wise maximum to minimum number of crop combinations derived in different talukas and given ranks accordingly. The study concluded that, agricultural land use analysis is essential for solving and optimizing the land use problem, maintaining socio-ecological balance, best utilization of scarce resources. The authors enlightened that the rational use of agricultural land has important for food security and biodiversity which increase the productivity and profitability of the agriculture sector and it indicates the decision making ability of farmers in study area.

Recent climate change and water pollution has affected algal diversity resulting in emergence of more tolerant species. They can be the indicators of water quality, pollution and seasonal changes. Present study revealed the green algal diversity and distribution pattern according to water parameters and season in the Lucknow City, India. The water sample were collected from seven sites within Lucknow and outskirts. The occurrence of a total of 36 taxa of green algae belonging to 11 genera are recorded. It has been observed that less polluted water is dominated by Spirogyra; where conductivity, TDS and salinity of water were low. Whereas the more polluted water was dominated by desmids. Dominance index was found highest in site 4 (0.61), where only three taxa were identified; whereas the lowest (0.13) was measured in site 1, where nine taxa were identified. This study also recorded several algal taxa for the first time from Lucknow.

During the high-speed flight of a vehicle in the atmosphere, surface friction with the air generates aerodynamic heating. The aerodynamic heating phenomenon can create extremely high temperatures near the surface. These high temperatures impact material properties and the structure of the aircraft, so thermal deformation measurement is essential in aerospace engineering. This paper revisits high-temperature deformation measurement using the digital image correlation (DIC) technique under high-intensity blackbody radiation with a precise speckle pattern fabrication and a heat haze reduction method. The effect of speckle pattern on the DIC measurement has been thoroughly studied at room temperature, but high-temperature measurement studies have not reported such effects so far. We found that the commonly used methods to reduce the heat haze effect could produce incorrect results. Hence, we propose a new method to mitigate heat haze effects. An infrared radiation heater was employed to make an experimental setup that could heat a specimen up to 950 ℃. First, we mitigated image saturation using a short-wavelength bandpass filter with blue light illumination, a standard procedure for high-temperature DIC deformation measurement. Second, we studied how to determine the proper size of the speckle pattern under a high-temperature environment. Third, we devised a reduction method for the heat haze effect. As proof of the effectiveness of our developed experimental method, we successfully measured the deformation of stainless steel 304 specimens from 25 ℃ to 800 ℃. The results confirmed that this method can be applied to the research and development of thermal protection systems in the aerospace field.

The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.

With recent advancements in network technology and spread of Internet, use of social network services and Internet of Things devices has flourished, leading to a continuous generation of large volumes of graph stream data, where changes, such as additions or deletions of vertices and edges occur over time. Additionally, owing to the need for efficient use of storage space and security requirements, graph stream data compression has become essential in various applications. Even though various studies on graph compression methods have been conducted, most of them do not fully reflect the dynamic characteristics of graph streams and complexity of large graphs. In this paper, we propose a compression scheme using provenance data to efficiently process and analyze large graph stream data. It obtains provenance data by analyzing graph stream data and builds a pattern dictionary based on this to perform dictionary-based compression. By improving the existing dictionary-based graph compression methods, it enables more efficient dictionary management through tracking pattern changes and evaluating their importance using provenance. Furthermore, it considers the relationships among sub-patterns using an FP-tree and performs pattern dictionary management that updates pattern scores based on time. Our experiments show that the proposed scheme outperforms existing graph compression methods in key performance metrics, such as compression rate and processing time.

The article presents an innovative method for synthesizing radiation patterns efficiently by 1 combining the Taguchi method and neural networks, while validating the results on a 10-element 2 antenna array. The Taguchi method aims to minimize product and process variability, while neural 3 networks are used to model the relationship between antenna design parameters and radiation 4 pattern characteristics. This approach utilizes Taguchi parameters as inputs for the neural network, 5 which is then trained on a dataset generated by the Taguchi method. After training, the network is 6 validated using a real 10-element antenna array. Analytical results demonstrate that this method 7 enables efficient synthesis of radiation patterns with a significant reduction in computation time 8 compared to traditional approaches. Furthermore, validation on the antenna array confirms the 9 accuracy and robustness of the approach, showing a high correlation between predicted performances 10 by the neural network model and actual measurements on the antenna array.In summary, our article 11 highlights that the combined use of the Taguchi method and neural networks, with validation on a 12 real antenna array, offers a promising approach for efficient synthesis of antenna radiation patterns. 13 This approach combines speed, accuracy, and reliability in antenna system design.

This study delves into a unique binary pattern found within the wellknown 3n+1 problem, or Collatz conjecture. Through careful analysis of the steps in the 3n+1 sequence, we have discovered a special binary representation that captures the behavior of all positive integers undergoing this transformation. With this new understanding, we have provided a solid proof confirming the validity of the 3n+1 problem for all positive integers. Our method goes beyond the need for extensive computational confirmation, providing a simple and elegant resolution to a long-standing mathematical mystery.

The number of diabetic patients worldwide is increasing rapidly. Prevention of diabetic reti-nopathy (DR), a leading cause of blindness, is a serious issue. We examined the effects of prophy-lactic pattern scanning laser retinal photocoagulation on DR development in 16 Spontaneously Diabetic Torii (SDT) fatty rats. Photocoagulation was applied to the right eyes of 8-week SDT fatty rats, and the left eyes served as the untreated controls. Electroretinography at 9 and 39 weeks of age and pathological examination of the retinal thickness and number of retinal folds, and immunohistochemistry of vascular endothelial growth factor and glial fibrillary acidic pro-tein at 24 and 40 weeks of age were performed bilaterally. No significant differences were seen between the left and right eyes in the apex latency and the amplitude of the oscillatory potential wave in the SDT fatty rats at 9 and 39 weeks of age and in the pathology and immunohistochem-istry in the SDT fatty rats at 24 and 40 weeks of age. Prophylactic pattern scanning retinal laser photocoagulation did not affect the development of DR in SDT fatty rats.

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

Arboviruses are infections caused by arboviruses that may be either symptomatic or asymptomatic, according to individuals' resistance and immune response, which dietary patterns can influence. Thus, this study aimed to investigate the possible association between the occurrence of clinical manifestations of arboviruses and the dietary pattern of the population studied. The study was conducted in a rural population in the metropolitan area of Belém, Pará State, Brazil. The sampling consisted of 95 individuals during a febrile outbreak. Two investigations were conducted: clinical-epidemiological-dietary and laboratory investigation based on blood samples taken for arbovirus analysis. Out of the 95 individuals studied, more than half (57.89%) showed clinical manifestations. Following the laboratory serology (HI and IgM ELISA) analyses, viral isolation in C6/36 cells, and viral genome detection (RT-qPCR), the final diagnosis of the cases was 47.37% Oropouche Fever, 2.11% Oropouche Fever and Chikungunya Fever, and 1.05% Mayaro Fever. Regarding dietary pattern, as for the comparison analyses, statistical significance was observed between dietary pattern and classification regarding the presence of symptoms (p<0.05); after the correspondence analysis, symptomatic cases were more associated with a bad dietary pattern, while asymptomatic cases were more associated with a good dietary pattern.

The term `motor control´ encompasses a wide range of mechanisms thought to be implicated in the organization of movements. Their study, like that of any other scientific field, must use specific notions to get to grips with them. This review is therefore organized along a series of notions that are frequently used in motor control, and we will discuss them with particular emphasis on neurological conditions, which may disrupt normal motor functioning. We will start with a short description of the roles of space and time, in which movements take place. Subsequently we will deal with kinematics and kinetics (dynamics) of movements. Then, we will list the inputs to motoneurons (MNs), which, in different forms, convey signals from the central nervous system (CNS) to skeletal muscles and muscle spindles, including central pattern generators (CPGs), sensory inputs and supraspinal descending fiber systems. Some helpers in movement organization will be introduced, such as internal models and neuronal network models. A relatively brief section on sensory-motor learning will follow because learning abilities are required to endow the sensory-motor system with flexibility and adaptability. The major emphasis is placed on neurological processes, which result from genetic modifications, autoimmune diseases, neurodegenerative diseases, infections in the nervous system as well as vascular and traumatic lesions. These neurological diseases lead to a variety of impairments and symptoms, particularly movement derangements including cerebellar ataxia, spasticity, and (other) movement disorders such as Parkinson’s syndromes. The conclusion is that there is no unique top controller that controls ´motor control`.

Two strongly curved areas of the Carpathians in Romania are earthquake-prone: Vrancea - in the South-Eastern Carpathians, and Danubian – in the western edge of the Southern Carpathians. By far the highest seismicity episode in 2023 was recorded in the Southern Carpathians, near Targu Jiu city, of more than 4000 earthquakes. A first ML 5.2 mainshock was recorded on 13 February, followed by a second one, ML 5.7, on 14 February. Our purpose is to provide a first analysis of this sequence in order to explain its extent and unusual development, in time. The possible role of fluids in the middle crust, is discussed in connection with the rather unusual character of the space-time distribution of aftershocks. A large and high-quality dataset is provided by the dense array of seismic stations which has been gradually improved by adding new stations in the epicentral area. The thorough revision of the phase picking and location reveals a few interesting and intriguing features of seismicity that still remain worthy to be further investigated. The database built within this paper provides excellent information not only for Targu Jiu area, but for any other investigation in intra-continental regions characterized by diffuse and sporadic seismic activity.

Oncolytic virotherapy is a promising immunotherapy approach for cancer treatment, utilizing viruses to preferentially infect and eliminate cancer cells while stimulating immune responses. In this review we synthesize current literature on the molecular circuits of immune sensing and response to oncolytic virotherapy; focusing on viral DNA or RNA sensing by infected cells, cytokine and danger-associated signal sensing by neighboring cells, and subsequent downstream activation of immune pathways. The sequential sense-and-response mechanisms involve the triggering of molecular sensors by viruses or infected cells to activate transcription factors and related genes for a breadth of immune responses. We describe how molecular signals induced in the tumor upon virotherapy can trigger diverse immune signaling pathways, activating both antigen-presenting cell-based innate and T cell-based adaptive immune responses. Insights into these complex mechanisms provide valuable knowledge for enhancing oncolytic virotherapy strategies.

This systematic review provides a comprehensive neuropsychological analysis of psychotic spectrum disorders, including schizophrenia, bipolar disorder, and depression. It explores cognitive impairments in memory, attention, and executive function, and the relation between brain abnormalities and these deficits. The paper emphasizes the use of neuropsychological tests in diagnosis and early psychosis management, while also discussing interventions, the impact of dementia on psychosis, and the neurobiological patterns associated with these conditions. Additionally, it underlines the importance of childhood trauma in the development of psychosis and examines the effects of substance abuse and brain injury. Neuropsychological evaluations and targeted therapies are highlighted as crucial for the understanding, diagnosis, and treatment of psychotic disorders. The research further includes evidence of neurocognitive dysfunction in individuals with a high risk of psychosis and emphasizes the advanced brain aging in schizophrenia and bipolar disorder. The necessity of comprehensive clinical evaluations and targeted therapies for cognitive impairments is underscored throughout the research. The potential effects of dementia on individuals with psychosis, neurobiological patterns, the role of childhood trauma, the impact of psychosis in dementia patients, and proposed treatments are also explored in depth. Overall, the paper underscores the integral role neuropsychological knowledge plays in understanding, diagnosing, managing, and treating psychotic spectrum disorders.

Diacylglycerol kinase (DGK) is a lipid kinase that phosphorylates diacylglycerol (DAG) to generate phosphatidic acid (PA). Based on converting one important signaling molecule (DAG) to another (PA), DGK plays an important role in plant responses to abiotic stress including waterlogging stress. However, no studies have been reported on the characterization of the DGK gene family in the waterlogging-tolerant kiwifruit germplasm, Actinidia valvata Dunn. Here, we identified 18 AvDGK genes in the A. valvata genome. The phylogenetic analysis showed that AvDGKs can be classified into three clusters, and members within the same cluster have similar domain distribution, exon-intron structures and conserved motif compositions. Chromosome localization analysis revealed that all the AvDGK genes are located across 18 different chromosomes. There were 29 duplicated gene pairs in kiwifruit and all had undergone purifying selection during evolution. Promoter cis-element analysis revealed that the cis-elements within AvDGK genes are associated with multiple functions, including phytohormone signal transduction, stress response, and plant growth and development. The expression pattern analyses indicated that AvDGK play an important role in the fruit development and plant response to waterlogging stress. AvDGKs gene family in the tetraploid A. valvata genome might promote PA synthesis and subsequent signal transduction both under short-term and long-term waterlogging stress. These results provide information regarding the structural characteristics and potential function of DGK genes within kiwifruit and lay a fundamental basis for further research into breeding for enhancing the kiwifruit’s tolerance to waterlogging stress.

Pedestrian Dead Reckoning (PDR) is a promising algorithm for indoor positioning. However, the accuracy of PDR degrades due to the accumulated error, especially in multi-floor buildings. This paper introduces a three-dimensional (3D) positioning method based on terrain feature matching to reduce the influence of accumulated error in multi-floor scene. The proposed method involves two steps: motion pattern recognition and position matching calibration. The motion pattern recognition aims to detect different motion states, i.e., taking the stairs or horizontal walking, from the streaming data. Then, stair entrances and corridor corners are matched with transition points of motion states and pedestrian turning points, respectively. After matching, calibration is performed to eliminate the accumulated errors. By carrying out experiments on a two-floor closed-loop path with a walking distance about 145 m, it is shown that this method can effectively reduce the accumulated error of PDR , achieving accurate 3D positioning . The average error is reduced from 6.60 m to 1.83 m.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

: Human settlements have historically thrived near rivers for navigation, trade, and availability of water supply and resources. Night light data, representing economic activities provide a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000-2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tribu-taries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river signifying denser settlements, such as towns and cities which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool to constrain the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest this data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method to classify spatiotemporal processes based on entropy measurements. To test and validate the method, we selected four classes of similar processes related to the evolution of random patterns: dynamic colored noises ((i)~white and (ii)~red); (iii)~weak turbulence from reaction-diffusion; (iv)~hydrodynamic fully developed turbulence, and (v)~plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon Permutation Entropy ($S^p_H$) and a new approach based on Tsallis Spectral Permutation Entropy ($S^s_q$). Notably, our observations reveal the segregation of reaction terms in this $S^p_H \times S^s_q$ space, a result that identifies specific sectors for each class of dynamic process, and can be used to train machine learning models for automatic classification of complex spatiotemporal patterns.

The purpose of the study was to identify factors characterizing a decrease in LV global systolic function in patients with ST-segment elevation myocardial infarction (STEMI) after revascularization using cardiac magnetic resonance imaging (MRI)-based ischemic injury pattern and laboratory parameters sensu left ventricular global systolic function. A total of 109 STEMI patients were examined. The patients underwent contrast-enhanced cardiac MRI with a 1.5 Tesla GE SIGNA Voyager (GE HealthCare, USA) on the 7th-10th days from the onset of the disease. According to cardiac MRI analysis, the patients were divided into the following groups with regard to left ventricular ejection fraction (LVEF) values: group 1 – patients with LVEF ≥50%; group 2 – patients with mildly reduced LVEF 40-49%; group 3 – patients with low LVEF <40%. A predominance of most parameters of the ischemic injury pattern was noted in patients with mildly reduced and low LVEF versus patient group with LVEF ≥50%. Some risk factors for a decrease in LVEF <50% systolic function in STEMI patients after revascularization were revealed: male gender; time from the onset of the anginal attack to revascularization; coronary artery status; several LV parameters; ischemic injury characteristics; natriuretic peptide and troponin I levels.

The purpose of this study is to analyze how global research cooperation patterns in the secondary battery industry have changed over recent years and to identify the evolution in the focus of research. To this end, network analysis was performed using the nationality information of the authors of a 10-year multinational joint research paper related to lithium-ion batteries. Furthermore, keyword analysis and topic modeling were performed using the abstract data from the study. The results of this study confirm that some countries that are not well-known in the field, such as Australia, Spain, and France, showed high centrality, compared with the level of cooperation scale. Additionally, six research topics were identified. According to a comparison over the first half of the decade, no difference was observed in the appearance of keywords indicating high energy density and conductivity with lithium, a key mineral. Keyword distribution was high for topics like battery charging and discharging in the first half of the decade, and for next-generation battery materials, such as solid electrolytes, lithium metal anodes, and lithium-sulfur batteries in the second. These results provide insights into the establishment of R&D cooperation strategies by countries and pre-planning by companies in the battery industry.

In general sound waves propagate radially outwards from a point source. These waves will continue in the same direction, decreasing in intensity, unless a boundary condition is met. To arrive at a universal understanding of the relation between frequency and wave propagation within spatial boundaries, an analysis and comparison is made between the results of Chladni plate experiments and Chladni plate simulations. We consider a finite range of frequencies and plate geometries and present a model that has been shown to successfully recreate the nodal line patterns to a first approximation. We discuss the benefits of such a model and the future work necessary to develop the model to its full predictive capacity.

As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable for intrusion detection systems (IDS) requirements. Over the years, many studies have proposed various solutions in this regard including signature-based and machine-learning (ML) based systems. More recently, researchers are considering deep learning (DL) based anomaly detection approaches. Most proposed works in this research field aimed to achieve either one or a combination of high accuracy, considerably low false alarm rates (FARs), high classification specificity and detection sensitivity, achieving lightweight DL models, or other ML and DL-related performance measurement metrics. In this study, we propose a novel method to convert a raw dataset to an image dataset to magnify patterns. Based on this we devise an anomaly detection for IDS using a lightweight convolutional neural network (CNN) that classifies denial of service and distributed denial of service. The proposed methods were evaluated using a modern dataset, CSE-CIC-IDS2018, and a legacy dataset, NSL-KDD. We have also applied a combined dataset to assess the generalization of the proposed model across various datasets. Our experimental results have demonstrated that the proposed methods achieved high accuracy and considerably low FARs with high specificity and sensitivity. The resulting loss and accuracy curves have also demonstrated the excellent generalization of the proposed lightweight CNN model, effectively avoiding overfitting. This holds for both the modern and legacy datasets, including their mixed version.

The scattering pattern from a narrow absorbing/amplifying grating is investigated. A simple model of a narrow amplifying grating is solved exactly numerically and approximately analytically for the regime where the beam’s wavelength is much shorter than the grating’s wavelength. The main results are: The incident angle divides the scattering pattern into two regimes: below and above the incident angles. The former regime has a weak dependence on the incident angle but has a strong dependence on the scattering one. In this regime, a new grating formula is derived. The opposite occurs in the latter regime, which is very sensitive to the incident angle, but has only weak dependence on the scattering angle. Consequently, at certain incident angles, all the scattering is concentrated in the first regime, i.e., all scattering angles are lower than the incident angle.

Any malocclusion can be associated with various face development patterns, including hyper, neutral and hypodivergent growth patterns. We measured face height ratios, angle formed by Y axis to SN and growth patterns in various malocclusions in a group of patients from Timis county. The pretreatment digital cephalograms of 350 participants were split into three groups based on Angle's classification of dentoalveolar malocclusion. Every cephalogram was digitally traced and analyzed using a composite cephalometric method analysis utilizing the WebCeph imaging cephalometric program, which included two linear and one angular. In general, patients from Timis county have a hypodivergent development pattern. Hypodivergent development pattern predominated in group I, II, and III. Group I hyperdivergent 5.14%, normodivergent 16.01%, hypodivergent 78.85%. Group II hyperdivergent 2.78%, normodivergent 14.44%, hypodivergent 82.78%. Group III hyperdivergent 10.53%, normodivergent 10.53%, hypodivergent 78.94%. In all three groups, the value of the angle formed by Y axis to SN is within normal limits group I 65.4 ±4.34°, group II 63.87± 3.86° and group III 64.66 ±5.28°. A strong negative correlation was found between angle: Y axis to SN and facial height ratio (r= -0,766; p &lt;0.001). In all kinds of malocclusion, patients from Timis county show primarily a hypodivergent development pattern.

Chemical instability of liquid-repellent surfaces is one of the nontrivial hurdles that hinders their real-world applications. Although much efforts have been made to prepare chemically durable liquid-repellent surfaces, few attentions have been paid to exploit the instability for versatile use. Herein, we propose to create hydrophilic patterns on superhydrophobic surface by taking advantage of its chemical instability induced by acid solution treatment. Superhydrophobic Cu(OH)2 nanoneedles covered Cu plate that shows poor stability towards HCl solution (1.0 M) is taken as an example. Results show that 2.5 min of HCl solution exposure leads to the etching of Cu(OH)2 nanoneedles and partial removal of self-assembled fluoroalkyl silane molecular layer, resulting in the wettability transition from superhydrophobocity to hydrophilicity, and the water contact angle decreases from ~160° to ~30°. Hydrophilic dimples with different diameters are then created on the superhydrophobic surfaces by depositing HCl droplets with different volumes. Afterwards, the hydrophilic dimple patterned superhydrophobic surfaces are used for water droplet manipulations, including controlled transfer, merging and nanoliter droplets deposition. The results thereby verify the feasibility of creating wettability patterns on superhydrophobic surfaces by using their chemical instability towards corrosive solutions, which broadens the fabrication methods and applications of functional liquid-repellent surfaces.

With the increase of global human activities, a large number of technogenic magnetic particles (TMPs) generated by industrial activities such as coal combustion, traffic and so on enter sediments on continental shelves. However, there is currently a lack of understanding of the spatiotemporal distribution of TMPs on continental shelves, as well as the sedimentary effects they cause. This review work comprehensively analyzes the source, morphology, composition, and spatiotemporal distribution characteristics of TMPs. Then it elucidates their magnetic contribution to sedimentary environments in continental shelf seas, as well as the influence of heavy metals and active iron. At the same time, the existing problems and future development directions of TMPs on continental shelves are summarized.

This paper focuses on the impact that urban traffic has on the environment. The study characterizes the global effect of GHG emissions, including the ecologic evaluation and the characterization, normalization, and evaluation factor. The work makes a detailed survey of the different modes of driving and their influence on engine performance as one of the principal causes of gas emissions during the combustion process. The article analyzes six types of vehicles equipped with different engine configurations: diesel and gasoline, GLP and GNC, hybrid electric, and plug-in hybrid electric. Simulation of the driving mode under various operational conditions for every type of engine results in energy consumption, thus, in GHG emissions, carbon dioxide and monoxide, nitrogen oxides, and Sulphur dioxide. The study concludes that a reduction in vehicle speed, thus in the engine revolutions, has positive effects on engine combustion and gasses emissions, which is reduced by 27.5%. The study also concludes that the limitation in driving mode, avoiding sharp and sudden acceleration, may reduce up to 45% of GHG emissions. The changes applied in the driving mode improve the air quality in the urban environment, reducing the content of GHG from 39% to 61%.

Currently, Pythagorean fuzzy sets (PFSs) have been widely applied in various fields due to their substantial advantages in expressing and dealing with uncertainty. However, measuring the similarity and difference between PFSs effectively remains an unresolved issue. Inspired by Tanimoto similarity, we propose a novel set of similarity and distance measures for PFSs. We delve into the theoretical properties of the proposed measures and compare it with existing PFSs measures. Numerous numerical examples validate their rationality and effectiveness. Furthermore, our experimental findings suggest that in contrast to existing measures, the introduced measures successfully circumvent various counter-intuitive issues encountered by current measures, and yield more pronounced outcomes in the discrimination of different fuzzy sets. This enhances the uniqueness and superiority of our measures. Finally, we developed two decision models based on the proposed measures and validated their applicability in three applications.

Mountain ecosystems are crucial for global biodiversity conservation. However, their landscape features are constantly changing owing to urban expansion. Understanding the relationships between biotic communities and landscape features is essential for biodiversity conservation. This study aimed to examine the effect of land-cover type on avian communities in Lishui, a mountainous urban area in eastern China. Avian surveys were conducted using a total of 168 line transects across different land-cover types once per season from December 2019 to January 2021. We assessed the diversity of bird communities by calculating various metrics at both taxonomic and functional levels. Among the land-cover types measured, woodland, built-up land, cultivated land, and water bodies significantly influenced bird community diversity and composition. Species richness, species abundance, and functional richness were negatively correlated with the proportion of woodland but positively correlated with the proportion of non-natural land cover, such as built-up and cultivated land. In contrast, functional evenness was positively correlated with the proportion of woodland and grassland but negatively correlated with the proportion of non-natural land cover. Land-cover type also exhibited significant correlations with avian functional characteristics such as diet, foraging strata, and body mass, thereby influencing the overall community structure. Our results indicated that mountainous landscape patterns substantially affect avian communities. Different land-cover types possess varying resource endowments that affect the distribution of avian species. Therefore, urban landscape planning in mountainous areas should carefully consider the various functions provided to organisms by different types of land cover to promote biodiversity.

This research delves into the realm of predictive modeling within artificial intelligence (AI) and introduces an innovative ensemble approach designed to enhance prognostic precision. The proposed methodology, characterized by its ebullient nature, leverages the collective wisdom of diverse predictive models, synthesizing a comprehensive and robust framework. The pursuit of parsimony are paramount, underscoring the need for efficient model architectures that balance predictive acuracy and computational efficiency. Our study meticulously explores the amalgamation of diverse algorithms, encapsulating the intrinsic complexity of real-world phenomena. We navigate the intricate landscape of feature selection, algorithmic diversity, and model combination, fostering a holistic understanding of the prognostic process. The ebullient ensemble emerges as a dynamic solution, harnessing the synergy of constituent models while mitigating the risk of overfitting. To validate the efficacy of our approach, extensive experiments are conducted on diverse datasets, spanning domains such as healthcare, finance, and natural language processing. Comparative analyses demonstrate the superior predictive performance of our ensemble model in comparison to individual algorithms and traditional ensemble methods. Additionally, we delve into interpretability aspects, elucidating the underlying mechanisms that contribute to the model's prognostic prowess. Our research advances the frontier of predictive modeling in AI, offering a nuanced and sophisticated paradigm for prognostication. The ebullient ensemble approach stands as a testament to the synergy achievable through the amalgamation of diverse predictive models, providing a pragmatic and parsimonious avenue for enhanced prognostic acuracy in artificial intelligence applications.

The field of nephrology has recently directed a considerable amount of attention towards the stimulator of interferon genes (STING) molecule since it appears to be a potent driver of chronic kidney disease (CKD). STING and its activator, the cyclic GMP-AMP synthase (cGAS) are among the most relevant inducers that promote the expression of type I interferons (IFN-Is). These cytokines have been long recognized as part of the mechanism used by the innate immune system to battle viral infections; however, their involvement in sterile inflammation remains unclear. Mounting evidence pointing to the involvement of the IFN-I pathway in sterile kidney inflammation provides potential insights into the complex interplay between the innate immune system and damage to the most sensitive segment of the nephron, the glomerulus. The STING pathway is often cited as the cause of renal disease originating from non-infection related caused by the induction of IFN-I expression. However, other receptors have been implicated in this process, mainly by recognizing host-derived nucleic acids. This review explores the main endogenous inducers of IFN-I in glomerular cells, discusses what exposure to the main autocrine and paracrine cytokines has on these cells, and identifies the pathways that are implicated in the development of glomerular damage.

Fermatean fuzzy sets (FFSs) are a versatile tool for handling uncertain problems and have shown great effectiveness in practical applications. However, many existing Fermatean fuzzy similarity measures exhibit counter-intuitive situations, making it challenging to accurately measure the similarity or difference between FFSs. To address this issue, several similarity and distance measures for FFSs are proposed, inspired by the Tanimoto similarity measure. The properties of the proposed measures are also explored, along with several comparative examples with existing measures for FFSs, which illustrate their superior performance in processing fuzzy information from FFSs. The proposed measures have effectively overcome the counter-intuitive challenges posed by many existing measures and significantly outperforms existing measures in differentiating different FFSs. Furthermore, we demonstrate the practical applicability of the proposed measures in solving pattern recognition, medical diagnosis and multiple-attribute decision-making problems.

A stable match, an intercuspated maxilla-mandible relation is the universally accepted goal for dental restorative interventions, yet the underlying sensorimotor mechanisms to achieve this goal in the natural jaw closure remains to be elucidated. Dentists have intuitively regarded peripheral sensory innervation from tooth contacts as a significant control element for jaw muscle actions, both in the state of health and in cases of pathological dysfunction. However, therapeutical interventions for reshaping the dental arch anatomy and jaw relations have not always been successful. Repetitive masticatory chewing cycles, swallowing, talking, as well as volitional jaw-opening and -closing involve stereotyped neural commands from the central nervous system that are modulated in reaction to the sensory afferent feedback from the peripheral neurons and their sensor organs. The aim of this article is to describe, on a fraction of a second time-scale, the minuscule tilts and kinematic events of mandible during the making of a stable match with maxilla. Evidence of the importance of tooth contacts as the sensorimotor motivation of each of the successive kinematic steps of the “mandible-meets-maxilla-narrative” are discussed.

In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff to patient assistance in caregiving and to gain insights into workload management. However, improving accuracy is challenging when there is a limited amount of sensor data available for training. In this paper, we propose a data augmentation method to reuse the Received Signal Strength (RSS) from different sensors by relabeling to the sensors with less samples resolving data imbalance. Standard deviation and Kullback-Leibler divergence between minority and majority class are used to measure signal pattern to find matching sensors to relabel. By matching sensors between classes, two variation of relabeling are implemented specifically full and partial matching. The performance is evaluated using real world dataset we collected for five days in a nursing care facility installed with 25 BLE beacons. Random Forest model is utilized for location recognition, and performance is compared using the weighted F1-score to account for class imbalance. By increasing the sensor data with our proposed relabeling method for data augmentation, we achieved higher minority class F1-score as compared to augmentation with Random Sampling, Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADASYN). Our proposed method utilizes collected sensor data by leveraging majority class samples. Full matching demonstrated a 6 to 8% improvement from the original baseline overall weighted F1-score.

In order to analyze the spatial distribution characteristics of the cultural landscape of the Yangtze River (Nanjing section) and show the role of the Yangtze River culture in promoting regional economic development and cultural radiation, Based on the Knowledge graph technology and 3S technology, this paper conducts geographical positioning and spatial analysis of the Yangtze River cultural landscape in Nanjing, and analyzes the surrounding environment by combining remote sensing images and topographic data. Researches show that: The Yangtze River cultural landscape in Nanjing includes 74 landscape points of seven landscape types, and the distribution of landscape points shows a clustering trend, but the spatial distribution and aggregation degree of different types of cultural landscapes are different. Due to the influence of climate environment and water resources distribution, the surrounding cultural landscape has a low altitude and high vegetation coverage, showing obvious distribution characteristics along the river. This study is helpful to improve the coordination degree between cultural landscape protection and planning management, and can provide useful reference for the protection of cultural landscape of the Yangtze River.

Membrane filtration is a popular choice in the treatment of wastewater for reuse. However, when used to produce clean water, these devices are subject to concentration polarization and fouling, which inhibit their ability to operate efficiently and provide high-quality permeate streams. Patterned membrane surfaces offer a hydrodynamic approach to mitigating concentration polarization and the surface fouling that follows. However, when subject to a steady feed flow rate, surface patterns generally produce stagnant zones in cavity-like spaces where particulate from the bulk flow recirculates in stationary vortices. To prevent aggregation in these recirculation zones, and therefore the onset of surface fouling, we study a rapidly pulsed feed flow. When combined with cavity-like geometries, such as the valleys present in membrane surface patterns, a rapidly pulsed flow generates mixing mechanisms (i.e., the deep sweep and the vortex ejection) that disrupt otherwise stagnant regions. First, we confirm the existence of these mechanisms, which are typically induced in impermeable cavities at relatively low Reynolds numbers, for near transitional feed Reynolds numbers in permeable cavity spaces via numerical simulation of the flow field. Following this confirmation, we demonstrate the ability of these mechanisms to remove particles trapped in recirculation zones via massless particle tracking studies. The results of this work suggest that when combined with a rapidly pulsed inlet flow, patterned membrane surfaces can not only alleviate concentration polarization and the surface fouling that follows but also reduce the need for traditional cleaning methods, which require operational downtime and often involve the use of abrasive chemical agents.

(1) Background: During physical exercise, ventilation (VE) adapts to the intensity and characteris-tics of the effort. The breathing pattern is defined as the relationship between the tidal volume (VT) and breathing frequency (BF) for a given VE. The aim of this study was to evaluate whether inspiratory muscle training influenced the response of the breathing pattern during an incremen-tal effort in amateur cyclists. (2) Methods: 18 amateur cyclists completed an incremental test to exhaustion with gas analysis on a cycle ergometer and spirometry. Cyclists were randomly as-signed to two groups (IMTG=9; CON=9). The IMT group completed 6 weeks of inspiratory muscle training (IMT) using a PowerBreathe K3® device at 50% of the maximum inspiratory pressure (Pimax). The workload was adjusted weekly. After the 6-week intervention, the cyclists repeated the incremental exercise test with gas analysis and spirometry. The response of the breathing pat-tern was evaluated during the incremental exercise test. (3) Results: Pimax increased in the IMTG (p<0.05; +19.62%). Variables related to the breathing pattern response showed no differences be-tween groups after the intervention (EXPvsCON; p>0.05). Likewise, no differences were found in the IMTG after training (PREvsPOST; p>0.05). (4) Conclusions: IMT improved the strength of in-spiratory muscles and sports performance in amateur cyclists. These changes were not attributed to alterations in the response of the breathing pattern.

The aim of this study was to examine the relationship of the distance between the apex tip of the upper central tooth (U1A) and the anterior nasal spine (ANS) and the nasal floor (NF) with the vertical cephalometric values using cone-beam computerized tomography (CBCT). A total of 122 patients who applied to Department of Orthodontics between January 2011-June 2019 were included. On the CBCT’s, distances between the U1A and the NF and ANS were measured. Statistical significance was considered as p&lt;0.05. Of 122 individuals 73.8% (n=90) were female and 26.2% (n=32) were male with an mean age of 22,8±3,3 years. A statistically significant moderate positive correlation was found between the NF-U1A mean values and the measurements of N-Me, ANS-Me and ANS-Gn, S-Go, and N-ANS measurements (p &lt;0.01). A statistically significant positive correlation was found between the ANS-U1A mean values and Ar-Go-Me, total posterior angles, N-Me, SN/GoGn and Y-axis angle, ANS-Me and ANS-Gn (p &lt;0.01). In this study, we found that the distance of U1A from ANS and NF points was related to orthodontic vertical direction parameters. It was demonstrated that the ANS-U1A and NF-U1A points can serve as reference points for identifying the orthodontic vertical growth pattern on CBCT scans.

Forest-grass intercropping patterns of protected cultivation has been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry (L. barbarum) intercropping and it is cultivated mostly by clean tillage. This paper takes 10 kinds of wolfberry-forage intercropping patterns, compares the effects of different planting modes on the growth, yield, photosynthetic characteristics, nutritional quality, and the degree of occurrence of diseases and pests, which aims to make clear the effects of wolfberry-forage intercropping patterns on wolfberry. The results showed that different intercropping combinations had different effects on wolfberry. The overall effect of Wolfberry-forage intercropping patterns on the growth of wolfberry were promote the photosynthetic characteristics. Ryegrass could increase the branch number, Lvyuan 5 and mangel increase branch length; Mangel, clover, sweet sorghum, ryegrass and stipas could reduce the damage of powdery mildew by 69%, and alfalfa, stipa and ryegrass could reduce the occurrence of aphids by 67% (P<0.05). Intercropping could increase carotenoids, flavonoids and ascorbic acid contents to improve wolfberry quality by 21%, 53% and 127%, respectively (P<0.05). Among all the performances, wolfberry-mangel intercropping has absolute advantages in promoting wolfberry yield and quality increase. Therefore the best patterns of wolfberry-mangel, wolfberry-ryegrass, wolfberry-alfalfa and wolfberry-clover were chosen.

Background: Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. The lack of or inadequate information about the circumstances, substances and populations at risk are considered barriers to the actual prevention of poisoning and effective intervention strategies in Saudi Arabia. The aim of the current study was to describe the pattern and determinants of chemical and drug overdose poisoning in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the Environmental Health and Occupational Safety Department in Makkah over two years (2018-2019) were reviewed.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions of Saudi Arabia. Further in-depth studies are needed to elaborate other social and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning.

The understanding of structural alteration mechanisms due to relative humidity impact on organic supports of paintings is of crucial significance for the preventive conservation strategies in order to ensure the long-term preservation of important cultural identity artworks. The effort in this paper is to simulate Museum realistic relative humidity condition in a climate chamber while monitoring the structural responses through a quantitative interferometric method allowing the quantitative correlation between the physical values of deformation and mass alteration relevant to relative humidity fluctuations.

In Poland, the mountainous and hilly regions until recently were territories with unbalanced and poor diet quality, especially in early spring. Wild edible plants were or still are influential in supplementing a human diet. One of the earliest wild edible plants to appear in the growing season, characteristic of a broad swath of Europe from Ukraine to Germany, remains wild (bear) garlic (Allium ursinum L.). This paper assesses the impact of the vegetation site and preservation methods on selected parameters of the chemical composition of bear garlic. In addition, the connection between its genome pattern and chemical composition was assessed. The plants were collected in three locations in the Carpathian foothills, and the reference sample was plants collected in the lowlands. The site from which the raw material was harvested has a statistically significant effect on the chemical composition of the preserved leaves of bear garlic. The profiles of the analysed components differed in the material from a different site. Bear garlic leaves from mountainous areas had more analyzed components than those obtained from the lowland sites. Moreover, the material from the lowlands had a different genetic pattern from the leaves from the mountainous areas..

This work introduces an innovative approach that unites a PIDND2N2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND2N2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system's response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing impressive performance. These important results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

This article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it can’t get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like), solving a given cognitive problem. DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, it is shown that DBC-1 can solve the following cognitive problems: “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” Smart manufacturing-based systems (digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and, thereby, can enhance its biologicalization.

The water resources carrying capacity (WRCC) system comprises multiple complex and nonlinear interactions related to society, economy, water resources and the water environment. A full understanding of its internal mechanism is conducive to the further improvement of the regional WRCC. This article focuses on the temporal and spatial variability of WRCC to explore a method of dynamic successive assessment. Firstly, the Pressure-State-Response (PSR)framework is used to develop a systematic and causal indicator system. Then, The Variable Fuzzy Pattern Recognition (VFPR) model and an analytic hierarchy process-entropy (AHP-E) model are combined to successively and dynamically assess WRCC. The proposed method is applied to the dynamic successive assessment of WRCC in Hebei Province, and it is obtained that the poor water resources carrying capacity in Hebei Province is mainly due to the basic attribute of the decision of the water resources shortage, but Hebei Province actively adopts a variety of measures to save water and pressurize mining, which makes the province's water resources carrying capacity have a tendency to become better gradually. At the same time, the system dynamics model (SD) of water resources carrying capacity based on the analysis of the model structure was established. Moreover, three scenarios were designed, including existing continuation, high-efficiency water-saving, cross-regional water transfer and coordinated development, each scenario divided into high and low-speed economic development and population growth schemes, then total 6 schemes between 2023 and 2030 were simulated and predicted respectively. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to maintain low levels. It was concluded that the high-speed development of economy and population, the efficient water conservation and inter-basin transfer scenario (scenario 2 with high-speed) is the best choice for sustainable development of water resources and social economy in Hebei.

Rapid urbanization has led to many ecological problems such as landscape fragmentation, decreased landscape connectivity, and decreased biodiversity. Building an ecological security pattern is an important way to ensure ecological security and maintain sustainable urban development. Harbin is an important large-scale city in northeastern China, and the urban central district of Harbin is used as the study area. Ecological sensitivity assessment, MSPA, gravity model, landscape connectivity assessment and MCR model were used to extract ecological source areas, ecological corridors and ecological nodes in the study area to construct and optimize the ecological security pattern. Research shows that: A total of 23 ecological source areas were identified, mainly located along the Songhua River in the central part of the study area and in the mountain forest areas within the A-cheng District in the southeastern part of the study area. 48 ecological corridors were extracted, mainly in Daowai District, A-cheng District and the eastern part of Xiangfang District. There are 8 important ecological corridors and 10 important connecting corridors. 61 ecological nodes of the first level and 65 ecological nodes of the second level were extracted. High, higher, medium, lower and low security areas were classified based on the minimum cumulative resistance surface, with the highest proportion of high ecological security areas accounting for 45.75% of the study area. 65 ecological breakpoints were extracted and restoration measures were proposed. Finally, The structure of the ecological security pattern optimization of "two axes, two belts and four areas" is proposed, and corresponding ecological management measures are put forward. The experimental system of this study can provide new ideas for the construction of ecological security patterns in other regions and provide scientific support for the ecological sustainable development of similar urban areas.

Ship wave is of great interest for wave drag, coastal erosion and ship detection. In this paper, a highly-paralleled numerical scheme is proposed for simulating three-dimensional (3-D) nonlinear Kelvin ship waves effectively. First, a numerical model for nonlinear ship waves is established based on potential flow theory, boundary integral method and Jacobian-free Newton-Krylov (JFNK) method. In order to improve computational efficiency and reduce data storage of JFNK method, a banded preconditioner method is then developed by formulating the optimal bandwidth selection rule. After that, a Graphics Process Unit (GPU) based parallel computing framework is designed, and a GPU solver is developed by using Compute Unified Device Architecture (CUDA) language. Finally, numerical simulations of 3-D nonlinear ship waves under multiple scales are performed by using the GPU and CPU solvers. Simulation results show that the proposed GPU solver is more efficient than the CPU solver with the same accuracy. More than 66% GPU memory can be saved and the computational speed can be accelerated up to 20 times. Hence, the computation time for Kelvin ship waves simulation can be significantly reduced by applying the GPU parallel numerical scheme, which lays a solid foundation for practical ocean engineering.

Anthropogenic chemicals are fundamental to our standard of living in modern society. Unfortunately, some chemicals are persistent and can enter waste streams and ultimately the environment. Commonly used household products including pharmaceuticals and personal care products are an important source of contaminants. The aim of this study was to develop an “Up-the-pipe Solutions” framework to raise awareness about the presence and potential risks of chemicals found in household products to reduce their levels in waste streams or substitute them with less harmful alternatives. This approach based on The Natural Step framework and the concept of essentiality recognises the importance of engaging the community to raise awareness around the consequences of our daily activities and behavioural patterns that can lead to the release of persistent contaminants in main waste streams from the kitchen and bathroom and green wastes we generate.

A drinking strategy aiming to replace a given percentage of the sweat losses incurred during exercise should result in reproducible fluid intake volume and, hence, fluid balance from one exercise session to the other performed under similar scenarios. Whether this may also be the case with ad libitum drinking during exercise is unclear. We characterized the repeatability of ad libitum fluid intake during repeated 1 h exercise sessions and examine its effect over time on fluid balance and selected physiological functions and perceptual sensations. Twelve (3 women) healthy individuals participated in this study. At weekly intervals, they completed 4, 2 x 30 min walking/jogging exercise bouts (55% VO2max, 40°C, 20-30% relative humidity) interspersed by a 3 min recovery period. During exercise, participants replaced water (20°C) ad libitum. There were no significant differences among the 4 exercise sessions for absolute fluid intake volume (~ 1000 mL · h-1), percent body mass loss (~ 0.4%), sweat rate (~ 1300 mL · h-1) and percent of sweat loss replaced by fluid intake (~ 80%). Heart rate, rectal temperature and perceived thirst and heat stress did not differ significantly between the first and fourth exercise session. Perceived exertion was significantly lower during the fourth vs. the first exercise session, but the difference was trivial, &lt; 1 arbitrary unit. In conclusion, ad libitum fluid intake during 4 successive identical 1 h walking/jogging sessions conducted in the heat will result in similar fluid intake volumes and perturbations in fluid balance, heart rate, rectal temperature and perceived thirst, heat stress and exertion.

Recanalization poses challenge in coil embolization for cerebral aneurysms. Establishing predictive models for post-embolization recanalization is important for clinical decision-making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process. In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their inherent 3D features. Further feature analysis was conducted utilizing saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress (WSS) in both pre- and post-coiling models derived from computational fluid dynamic (CFD) simulations for 59 aneurysms. Velocity was identified as the most pivotal parameter, supported by the lowest P-value from statistical analysis and the highest area under the curves (AUROC)/precision-recall curves (AUPRC) values from DNN model. Moreover, visual XAI analysis revealed robust injection flow zones with notable impingement points in pre-coiling models, as well as pronounced interplay between flow dynamics and the coiling plane were important 3D features in identifying the recanalized aneurysms. The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting post-embolization recanalization but also at discovering unknown features in the future.

The Silk Road pattern (SRP) and Circumglobal teleconnection pattern (CGT) are two well-known teleconnection patterns along the Eurasian westerly jet during boreal summer, which are often regarded as one teleconnection pattern. In view of the distinct features of the SRP/CGT on the interannual (IA) and interdecadal (ID) timescales, the present study investigates the linkages and differences between the SRP and CGT on the two timescales. On the IA timescale, the SRP and CGT feature a similar circumglobal wave train structure with strong and significant centers over Eurasia, but show clear independences. Specifically, the SRP and CGT illustrates largely the mid-/high-latitude-related and tropics-related parts of the Northern Hemisphere upper-tropospheric circulation variations, respectively. Also, the CGT shows a stronger connection to the Indian summer monsoon (ISM) heating and El Niño–Southern Oscillation than the SRP, which makes the CGT more like a tropical-forcing-driven atmospheric mode but the SRP more like an internal atmospheric mode. The linkages and differences between them are associated with their asymmetry relationship during their positive and negative phases, which are attributed mainly to the asymmetry impact of the ISM heating/cooling on the Eurasian circulations. On the ID timescale, the SRP and CGT are characterized by a coherent two-wave train structure over Eurasia, and feature more like the same teleconnection pattern, which are associated with the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation. The present findings on the linkages and differences between the SRP and CGT are helpful to understand the variability and prediction of the SRP and CGT.

Pregestational and gestational diabetes mellitus are relevant complications of pregnancy and antidiabetic drugs are prescribed to obtain glycemic control and improve perinatal outcomes. The objective of this study was to highlight the prescription pattern of antidiabetics before, during and after pregnancy in Italy and to evaluate its appropriateness. A multi-database cross sectional population study using a Common Data Model was performed. In a cohort of about 450,000 women, the prescribing profile of antidiabetics seemed to be in line with the Italian standards for the treatment of GDM which currently do not recommend the use of oral antidiabetics and non-insulin injection, even if a small share of new users (up to 3.8% in the third trimester) used oral antidiabetics. A substantial variability in the prescription pattern was observed among the Italian regions considered: the highest increase was registered in Tuscany (4.2%), Umbria (3.5%) and Emilia-Romagna (2.6%) while the lowest in Lombardy (1.5%), Veneto (1.7%) and Apulia (1.7%). Analysing the prevalence of use of antidiabetics between foreign women we observed that the consumption during pregnancy was higher than Italians (second trimester: 1,8% vs 0,9%, third trimester: 3,6% vs 1,8%).

Different bone bruise patterns observed on magnetic resonance imaging (MRI) after non-contact anterior cruciate ligament (ACL) rupture and lateral patellar dislocation may indicate different injury mechanism of knee. In order to investigate the typical bone bruising patterns after ACL rupture and patellar dislocation. In this study, 77 ACL rupture and 77 patellar dislocation patients’ knee MR images with bone bruises between August 2020 and March 2022at our institution were selected and analyzed, respectively. Sagittal and transverse planes images were used to determine the bone bruise location in the lateral-medial and superior-inferior directions of the MR images. The presence, location, and intensity of the bone bruises within specific compartments of the femur and tibial after ACL rupture and patellar dislocation were recorded. Relative bone bruise patterns of the ACL rupture and patellar dislocation were classified and analyzed. Results showed that there were 4 kinds of bone bruise (1-,2-,3-,4- bone bruises) patterns after ACL rupture. The most common two patterns after ACL rupture were 3- bone bruises (including lateral side of femur and both lateral and medial side of tibia, LF+BT; both lateral and medial side of femur and lateral side of tibia, BF+LT, medial side of femur and both lateral and medial side of tibia, MF+BT) followed by 4- bone bruises (both lateral and medial side of femur and tibia, BF+BT), 2- bone bruises (LF+LT, lateral side of femur and tibia; MF+LT, medial side of femur and lateral side of tibia; LF+MT, lateral side of femur and medial side of tibia; MF+MT, medial side of femur and tibia; 0+BT, both lateral and medial side of tibia;), and 1- bone bruise (0+LT, only lateral side of tibia). There was only 1 pattern bone bruise (latera femur and medial patella bone bruise) of patellar dislocation, the most common pattern of patellar dislocation was in the inferior medial patella and lateral anterior inferior femur. The results suggest that the pattern of bone bruise after ACL rupture and patellar dislocation is completely different. There were 4 kinds of bone bruise patterns after non-contact ACL rupture while there was only 1 kind of bone bruise pattern after patellar dislocation bone bruise patients which was in the inferior medial patella and lateral anterior inferior femur.

The goal of this paper is to fabricate innovative diaphragm headphones using graphene oxide paper (GOP) and GOP/epoxy nanocomposites (GOPC). Initially, graphene oxide suspension is fabricated, and the vacuum filtration method is adopted to make GOP. Then vacuum bag molding is used to fabricate GOPC from GOP. Hot pressing and associated molds are adopted to fabricate line-indented (GOPC-L) or curve-indented patterns (GOPC-C) on the GOPC. The performance of one kind of GOP and three kinds of GOPC diaphragm headphones is analyzed based on their sound pressure level (SPL) curves achieved by the Soundcheck measurement system. There are four important processing parameters that will influence the performance of the diaphragm, including material type GOP versus GOPC, indented pattern type, sonication time on suspension, and graphene weight fraction in suspension. Compliances of various diaphragms are measured by the Klippel LPM laser measurement system. The results indicate that effects of sonication time and graphene weight fraction on SPL of GOP and GOPC headphones are in reverse, and this is associated with their difference on compliance (modulus), mass, damping ratio, and microstructure uniformity. Either GOPC-L or GOPC-C seems to improve the microstructure of the GOPC, and leads to better SPL performance. The correlation between the previous four factors and SPLs of four kinds of diaphragm headphones is proposed by using scanning electron microscope (SEM) to examine the microstructure of these diaphragms.

Since there are no morphological clues capable of making a pathologist suspect a possible mammary origin of a metastatic lesion without adequate clinical information, the histologic diagnosis of brain metastasis from BC is still based on the immunohistochemical expression of mammary gland markers such as GATA-3, ERs, PgRs and HER-2. The present retrospective study aimed to select purely morphological features capable to suggest the mammary origin of a metastatic carcinoma to the brain. The following histological features were collected on a series of 30 cases of brain metastases from breast cancer:(i) solid growth pattern; (ii) presence of comedonecrosis; (iii) glandular differentiation. Our results showed that most cases histologically exhibited solid growth pattern with at least focal comedonecrosis, producing an overall morphology closely reminiscent of mammary high-grade ductal carcinoma in situ. Although the above-mentioned morphological parameters are not strictly specific to a mammary origin, they may have an important diagnostic utility in leading pathologists to suspect a possible breast primary tumor and to include GATA-3, ERs, PgRs and HER-2 to the immunohistochemical panel.

Land use and land cover (LULC) datasets for Jinan in 1992, 1998, 2002, 2006, 2011, 2017, and 2022 were developed from Landsat images using the Random Forest (RF) classification approach. The relationships between social-economic, political factors and time-series LULC data were exam-ined for the periods between 1992 and 2022. The results showed the effectiveness of using the RF classification method for LULC classification with time series of Landsat images. Combined with driving forces analysis, our research can effectively explain the detailed LULC change tra-jectories corresponding to different stages and give new insights into Jinan LULC change pat-terns. The results show a significant increase in impervious surface which opposite change to bare land which experienced a huge decline declined by 95%, due to urbanization and rapid in-crease of population. The driving forces behind these changes are related to population growth, economic development, and climate change. Moreover, the present research employed Principal Components Analysis (PCA) methodology in order to understand the relative significance of disparate driving factors. The analysis results prove that the economy (population, GDP) and climate change were the primary factors that have an obvious impact on land use/land cover changes and that the driving factors for impervious surface, bare land, woodland, farmland, and water were distinct. Government policies also have a substantial impact on LULC change as well, such as the Construction of Harmonious Jinan (COHJ). The results were helpful for better understanding the mechanisms of LULC change and can provide useful knowledge for effective land resource management and planning.