The study of ecological connectivity is a global priority due to the important role it plays in the conservation of diversity. However, few studies in this context have focused on marine benthic ecosystems. To address this issue, the present work determines the ecological connectivity between two sub-Antarctic macrobenthic assemblages through assessment of the α-, β-, and functional diversity indices. Samples were collected using a van Veen grab at stations located in Bahia Inútil and Seno Almirantazgo. The ecological analysis was based on a total of 113 invertebrate taxa. The mean abundance values were lower in Bahia Inútil (888.9 ± 26.8 ind m-2) than in Seno Almirantazgo (1358.6 ± 43.4 ind m-2). While the mean α-diversity values showed significant differences between assemblages, β- and functional diversity indices presented no significant differences. These results indicate that, despite the distance (56 km) separating the two basins from each other, there is a high degree of connectivity at the functional level between the assemblages, due to the high number of shared species and their functional traits. The species most responsible for this observation were the polychaetes Capitela capitata and Aricidia (Acmira) finitima, as well as the bivalves Nucula pisum and Yoldiella sp. 1. In terms of functional biodiversity, species characterized as omnivorous and with lecithotrophic larval development were mostly responsible for connectivity between assemblages. These results suggest the importance of including β- and functional diversity indices as criteria in the future planning of marine protected areas for the maintenance of marine ecosystem integrity.

The control of classical swine fever (CSF) in endemic areas has been attempted with modified live vaccines. However, in some regions, the implementation of imperfect vaccination programs has led to a reduction in the genetic diversity of the circulating strains and a change in their virulence. Porvac® subunit vaccine has been shown to provide a rapid onset of protection against the “Margarita” strain. The aim of this study was to evaluate whether the immune response induced by Porvac® is also effective against autochthonous isolates of low, medium or high virulence. All pigs vaccinated with Porvac® were protected against the disease after the challenge. PR-11/10–3 isolate caused a very mild disease in controls, whilst Holguin_2009 isolate produced mild to moderate signs of CSF and one of the pigs died. Finally, controls inoculated with PR-2016 isolate developed moderate to severe signs of CSF and two of them died. Viral replication was detected in controls, but not in pigs immunized with Porvac®. Finally, anti-Erns antibodies were induced in five out of six control pigs but in any of the vaccinated pigs. These results support the use of Porvac® for the control and elimination of CSF in Cuba and other endemic regions.

Quantum contextuality describes situations where the statistics observed in different measurement contexts cannot be explained by a measurement independent reality of the system. The most simple case is observed in a three-dimensional Hilbert space, with five different measurement contexts related to each other by shared measurement outcomes. The quantum formalism defines the relations between these contexts in terms of well-defined relations between operators, and these relations can be used to reconstruct an unknown quantum state from a finite set of measurement results. Here, I introduce a reconstruction method based on the relations between the five measurement contexts that can violate the bounds of non-contextual statistics. A complete description of an arbitrary quantum state requires only five of the eight elements of a Kirkwood-Dirac quasi probability, but only an overcomplete set of eleven elements provides an unbiased description of all five contexts. A set of five fundamental relations between the eleven elements reveals a deterministic structure that links the five contexts. As illustrated by a number of examples, these relations provide a consistent description of contextual realities for the measurement outcomes of all five contexts.

The benthic matrix acts as a key natural archive where the memory of long-term timescale environmental changes is recorded. Some ecological and chemical features of fjord sediments were explored during the AREX cruise carried out in the Svalbard archipelago in summer 2021. The activity rates of the enzymes leucine aminopeptidase (LAP), beta-glucosidase (GLU) and alkaline phosphatase (AP) and community-level physiological profiles (CLPP) were studied with the aim of determining the functional diversity of the benthic microbial community, while bacterial isolates were screened for their susceptibility to antibiotic molecules in order to explore the role of these extreme environments as potential reservoirs of antibiotic resistance. Enzyme activity rates were obtained by fluorogenic substrates, CLPP by Biolog Ecoplates; antibiotic susceptibility assays were performed through the standard disk diffusion method. Spatial trends observed in the functional profiles of the microbial community suggested the variability in the microbial community composition, presumably related to the patchy distribution of organic substrates. Complex Carbon sources, carbohydrates and amino acids were the organic polymers preferentially metabolized by the microbial community. Multiple resistance to ampicillin, clindamycin and gentamycin was detected in all the sampled sediments, excepting in the southern Hornsund area, stressing the role of sediments as a potential reservoir of chemical wastes ascribable to antibiotic residuals. This study provides new insights on the health status of fjord sediments of West Spitsbergen applying a dual ecological and biochemical approach. Microbial communities in the fjord sediments showed globally a good functional diversity, suggesting their versatility to rapidly react to changing conditions.

Keywords: contamination; bioaccumulation; fish and mollusks tissue; ecosystem components; heavy metals; organochlorine pesticides; polychlorinated biphenyls; polycyclic aromatic hydrocarbons.

This manuscript presents a new two-parameter unit stochastic distribution, obtained by transforming the Laplace distribution, using generalized logistic map, into a unit interval. The distribution thus obtained is named the Laplace-logistic unit (abbreviated LLU) distribution, and its basic stochastic properties are examined in detail. Also, the procedure for estimating parameters based on quantiles is provided, along with the asymptotic properties of the obtained estimates and the appropriate numerical simulation study. Finally, the application of the LLU distribution in dynamic and regression analysis of real-world data with accentuated "peaks" and "fat" tails is also discussed.

This paper outlines the ongoing development of a specialised mobile application to address the mental health needs of vulnerable populations in the European Union (EU). Conducted as a mixed-methods research within two EU Science and Technology Cooperation Actions, the study prioritises stakeholder feedback to identify features for initial testing and strategies to improve application uptake, using critical digital health analysis. With a focus on marginalised groups such as refugees, migrants and socio-economically disadvantaged individuals, the application aims to provide an accessible and culturally sensitive platform for mental health support, integrating evidence-based interventions such as cognitive behavioural techniques and mindfulness exercises. Key features include multilingual support, habit tracking, personalised recommendations for support and services, and real-time crisis intervention. Collaboration with stakeholders and ongoing rigorous usability testing are driving the refinement process to ensure usability, acceptability and effectiveness, underscoring the importance of user engagement in technology-based mental health interventions in the EU context and highlighting the importance of collaborative science and technology for societal benefit.

Graph Neural Networks (GNNs) are powerful models capable of managing intricate connections in non-Euclidean data, such as social networks, physical systems, chemical structures, and communication networks. Despite their effectiveness, the large-scale and complex nature of graph data demands substantial computational resources and high performance during both training and inference stages, presenting significant challenges, particularly in the context of embedded systems. Recent studies on GNNs have investigated both software and hardware solutions to enhance computational efficiency. Earlier studies on Deep Neural Networks (DNNs) have indicated that methods like reconfigurable hardware and quantization are beneficial in addressing these issues. Unlike DNN research, studies on efficient computational methods for GNNs are less developed and require more exploration. This survey reviews the latest developments in quantization and FPGA-based acceleration for GNNs, showcasing the capabilities of reconfigurable systems (often FPGAs) to offer customized solutions in environments marked by significant sparsity and the necessity for dynamic load management. It also emphasizes the role of quantization in reducing both computational and memory demands through the use of fixed-point arithmetic and streamlined vector formats. This paper concentrates on low-power, resource-limited devices over general hardware accelerators and reviews research applicable to embedded systems. Additionally, it provides a detailed discussion of potential research gaps, foundational knowledge, obstacles, and prospective future directions.

Timely and accurate acquisition of information on distribution of the crop planting structure in Loess Plateau of eastern Gansu Province, one of the most important agricultural areas in western China, is crucial for promoting fine management of agriculture and ensuring food security. In this study, the Object-Based Image Classification (OBIC), the Random Forest (RF) and Convolutional Neural Network (CNN) models were employed to classify the crop planting structure of four representative test areas in Qingyang City in a precise manner. Firstly, different optimal segmentation scales for various crops were selected using the Estimation of Scale Parameter 2 (ESP2) tool and the Ratio of Mean Difference to Neighbors(ABS) to Standard Deviation (RMAS)model. The images were then segmented through multiresolution segmentation combined with the Canny Edge Detection algorithm. Secondly, the L1 regularized logistic regression model was utilized to select and optimize 39 spatial feature factors including spectral, textural, geometric, and index features, in conjunction with phenological factors. Lastly, under the multi-level classification framework, the Random Forest (RF) classifier and Convolutional Neural Network (CNN) model, combined with object-based multiresolution segmentation, was used to classify the crop planting structure. The findings show that: Thanks to the Canny Edge Detection algorithm, we can obtain a more complete boundary of the segmented objects and improve the separability. The optimal segmentation scales for corn, vegetables, and buckwheat were found to be 55, 70, and 35, respectively, while wheat and apple had optimal segmentation scales of 65. In addition to phenological characteristics, the number of selected spatial features for corn, vegetables, buckwheat, wheat, and apple were 9, 7, 16, 12, and 10, respectively. The CNN model demonstrated high consistency with the RF model in the classification results, but the accuracy of RF model is higher than that of CNN model on the whole. The overall accuracy of classification using RF model in four test areas registered 91.93%, 94.92%, 89.37% and 90.68%, respectively. This paper introduced crop phenological factors, effectively improving the extraction precision of shattered agricultural planting structure in the Loess Plateau of eastern Gansu Province. Its findings have important application value in crop monitoring, management, food security and other related fields.

This article introduces the Theory of Inverse Discrete Dynamical Systems (TIDDS), a novel methodology for modeling and analyzing discrete dynamical systems via inverse algebraic models. Key concepts such as inverse modeling, structural analysis of inverse algebraic trees, and the establishment of topological equivalences for property transfer between a system and its inverse are elucidated. Central theorems on homeomorphic invariance and topological transport validate the transfer of cardinal attributes between dynamic representations, offering a fresh perspective on complex system analysis. A significant application presented is an alternative proof of the Collatz Conjecture, achieved by constructing an associated inverse model and leveraging analytical property transfers within the inverted tree structure. This work not only demonstrates the theory's capability to address and solve open problems in discrete dynamics but also suggests vast implications for expanding our understanding of such systems.

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler Wind Lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth in a polar sun-synchronous orbit at about 320 km altitude with a repeat cycle of 7 days, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. Exceeding scientific expectations, Aeolus, initially designed for a 3-year lifetime, provided global coverage of wind profiles for almost five years. In this long-term validation study, we assessed the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products by collecting radiosonde data from three stations in the Brazilian Amazon: Cruzeiro do Sul (7.62° S, 72.67° W), Porto Velho (8.76° S, 63.91° W), and Rio Branco (10.00° S, 67.80° W). Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data, launched daily at 12:00 UTC from October 2018 to March 2023. Considering all data collected during the mission period, Pearson’s coefficient (R) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy, revealing a strong correlation between Aeolus and radiosonde winds. No significant biases were detected, with values of -0.14 m/s for Rayleigh-clear and -0.40 m/s for Mie-cloud, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was -0.95 m/s, exceeding the mission requirements.

This paper introduces a three-layer system, proposing a comprehensive model of granular mixture transport over a mobile sloped bed in a steady flow. This system, consisting of the bottom, contact and upper zones, provides complete, continuous sediment velocity and concentration vertical profiles. The model considers gravity’s effect on sediment transport in the bottom (dense) layer, a crucial factor often overlooked in previous studies. The induced movement in the mobile sublayer of the dense layer causes an increase in velocity at the upper boundary of this layer, significantly affecting the vertical distributions of velocity and concentration above this layer. We described the interactions between fractions and an intensive sediment mixing and sorting process in the contact layer. The proposed shear variation, with an increase in its maximum value at the bed, adds to the novelty of our approach. The data sets used for the model’s validation cover various conditions, including slopes, grain diameters, densities and grain mobility conditions, from incipient motion to a fully mobilised bed. This extensive validation process instils confidence in the theoretical description and its applicability to real-world scenarios.

Ticks are one of the most dominant forced ectoparasites of vertebrates, belonging to the arthropods, which transmit pathogens such as bacteria, viruses, and parasites to humans and animals in Iran and worldwide. Given that, sex ratio factors can affect the epidemiology of vector-borne diseases, this study aimed to identify and determine the ticks' sex ratio and host type (camels, sheep, cattle, dogs, chickens, and pigeons) in different areas of Tehran province. This descriptive cross-sectional study took samples from different animal body parts in four seasons from 20 villages in 2019, in which 685 hard ticks and 121 soft ticks were caught from 1623 studied livestock and poultry. Regarding sex segregation among all caught ticks, 42.01% were male, and 57.99% were female. It is noteworthy that in both mountain and plain environments, R. sanguineus species of hard ticks had the most elevated sex ratio. Most ticks were collected from sheep hosts with 60.04% and the lowest from cattle hosts with 0.62% in tick infestation.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in Smart Cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G Smart Cities IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low Round-Trip Time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

Indocyanine Green (ICG) has significantly advanced minimally invasive surgery. It is widely recognized for its ability to visualize blood vessel patency in real-time across various surgical specialties. While its primary use in colorectal surgery is to evaluate anastomoses for leaks, nu-merous other applications have been documented in the literature. In this review, we aim to explore both established and emerging applications of ICG fluorescence in colorectal surgery, with the goal of improving patient outcomes. This includes preoperative tumor marking and the detection of metastatic disease. Some applications, such as lymphatic mapping, require further research to determine their impact on clinical practices. Conversely, oth-ers, like the intraoperative localizations of ureters, necessitate additional procedures and are not yet widely accepted by the surgical community. However, the development of alternative com-pounds could offer better solutions. Future research should focus on areas like quantitative ICG and protocol standardization in prospective multicenter studies.

Layered Ti3C2Tx MXene has been successfully intercalated and exfoliated with the simultaneous generation of a 3D silica network by treating its cationic surfactant intercalation compound (MXene-CTAB) with an alkoxysilane (TMOS) resulting in a MXene-silica nanoarchitecture that exhibits porosity along with the intrinsic properties of MXene (e.g., photothermal response). The ability of these new materials to produce thermal activation reactions of compounds previously adsorbed on MXene-SiO2 is shown here. For this purpose, the pinacol rearrangement reaction has been selected as a first model example, testing the effectiveness of NIR laser-assisted photothermal irradiation in these processes. This work shows that Ti3C2Tx – based nanoarchitectures open new avenues for applications that rely on the combined properties inherent to their integrated nanocomponents that could be extended to the broader MXene family.

Inflorescence architecture underpins sexual reproduction in wild Musa species and productivity in edible banana cultivars. In a functional analysis we identified the apical inflorescence and lateral ‘cushion’ meristems and the change in flower type as the three primary components of inflorescence architecture. Five genotypes of two clone-sets of edible plantains (Musa AAB), were grown for four generations along an elevation gradient (1100 m to 2200 m, 16°C to 24°C) straddling the equator in the humid highlands of East Africa. The data consisted of peduncle length at harvest, fruit per hand (Fh) and hands per bunch (Hb). The activity of the apical inflorescence meristem drives peduncle length and lateral ‘cushion’ meristems determine fruit per hand. However, Hb is determined by a change in flower type – from fruit-forming to non-fruit forming. Site temperature affected Hb more than Fh, while development of the genet (rhizome) changed the allocation of resources between Hb and Fh, independently of the effect of site temperature. Clone-sets differed in their response to genet development. Cooler temperatures reduced the number of fruit-forming flowers in an inflorescence and changed the balance away from female towards male flowers. In banana breeding schemes, manipulating inflorescence components independently raises options for producing genotypes better suited to markets, environments, and cultural practices.

Coastal zones experience increasing climatic and human pressures, which lead to growing risks and tipping points (TPs) under future scenarios and natural resource scarcity. To avoid crossing TPs with irreversible coastal losses, this paper proposes the development of adaptation pathways based on advanced coastal oceanography and engineering knowledge that enables an objective assessment of evolving coastal risks. These pathways feature sequential interventions, combining conventional engineering works with nature-based solutions (NbS), steered by simulations and observations as a function of available coastal resources (space and sediment) and risks for infrastructure and socioeconomic assets. Such an adaptation has been developed for urban and peri-urban Mediterranean beaches, considering conventional coastal engineering together with NbS. Both types of interventions are assessed in terms of key physical variables, which serve to evaluate performance and estimate TPs. This analysis supports the new coastal protection and management plan promoted by the local government and the coastal adaptation plan of the central government. The approach and results illustrate the potential of adaptation pathways for beach sustainability, enhancing the compatibility between short/long-term coastal protection objectives under present/future climate and management scenarios. The adaptation pathways development underpins an increasing stakeholder cooperation to achieve shared decisions for coastal sustainability.

While cycling presents environmental benefits and promotes a healthy lifestyle, the risks associated with overtaking maneuvers by motorized vehicles pose significant hindrances for many potential cyclists. Large-scale analysis of overtaking maneuvers could inform traffic researches and city planners on how to reduce these risks by better understanding these maneuvers. Drawing from the fields of sensor-based cycling research and of LiDAR-based traffic data sets, this paper provides a step towards addressing these safety concerns by introducing the Salzburg Bicycle 3d (SaBi3d) data set, consisting of LiDAR point clouds capturing car-to-bicycle overtaking maneuvers. The data set, collected using a LiDAR-equipped bicycle, facilitates detailed analysis of a large quantity of overtaking maneuvers without the need for manual annotation through enabling automatic labeling by a neural network. Additionally, a benchmark result for 3d object detection using a competitive neural network is provided as a baseline for future research. The SaBi3d data set is structured identically to the nuScenes data set, and therefore offers compatibility with numerous existing object detection systems. This work provides valuable resources for future researchers to better understand cycling infrastructure and mitigate risks, thus promoting cycling as a viable mode of transportation.

A ~3-kb deletion-type DNA copy-number variation (CNV, esv3587290) located at intron 7 of the VANGL1 gene (1p13.1, MIM*610132) has been proposed as a genetic factor for developing lupus nephritis (LN) in adult systemic lupus erythematosus (SLE) patients across European-descent populations, but its replication in other ethnicities has been inconsistent and its association with LN in childhood-onset SLE (cSLE) remains unknown. Here, we performed an exploratory association study in a sample of 66 unrelated cSLE Mexican patients (11 males, 55 females; ages 7.8 to 18.6 years). Two stratified groups were compared: cSLE patients with (N=39) or without (N=27) LN, as diagnosed by renal biopsy (N=17), proteinuria (N=33), urinary protein:creatinine ratio >0.2 (N=34), and erythrocyturia and/or granular casts in urinary sediment (N=16). For esv3587290 CNV genotyping, we performed an end-point PCR assay with breakpoint confirmation by Sanger sequencing. We also determined the allelic frequencies of the esv3587290 CNV in 181 deidentified ethnically-matched individuals (reference group). The obtained genotypes were tested for Hardy-Weinberg equilibrium (HWE) by c2 test. Associations between LN and esv3587290 CNV were tested by calculating the Odds Ratio (OR) and using Pearson's c² tests with a 95% confidence interval and P≤0.05. The esv3587290 CNV allele (OR 0.108, 95% CI 0.034-0.33, P=0.00003) and the heterozygous genotype (OR 0.04, 95% CI 0.119-0.9811, P=0.002) showed a significant protective effect against LN development. Finally, we characterized the precise breakpoint of the esv3587290 CNV as NG_016548.1(NM_138959.3):c.1314+1339_1315-897del (https://databases.lovd.nl/shared/variants/0000918418#00025811) in our population. This report supports the notion that a broad genetic heterogeneity underlies the susceptibility for developing LN.

Background: Our study investigates the prevalence and causes of injuries among undergraduate dental students during clinical sessions. Methods: The study was conducted at the Department of Dentistry, National and Kapodistrian University of Athens, focusing on injuries reported from 2021 to 2024. Data were collected through self-reported questionnaires and clinical records. The primary variables assessed included the type of injury, the instrument involved, the clinical procedure being performed, and the immediate actions taken post-injury. Serological testing was conducted on both students and patients to assess the risk of bloodborne pathogen transmission. Results: The findings revealed a high prevalence of injuries, with needles being the most common cause, followed by burs and dental probes. The most frequent injury type was piercing, primarily affecting the fingers. Periodontal treatments, restorative procedures, and endodontic treatments were the main activities leading to injuries. Despite normal medical records for most patients treated by injured students, serological testing showed significant positivity rates for HCV and HBV. It is noteworthy that most injured students demonstrated their commitment to safety by adhering to recommended post-exposure protocols, including wound cleaning, disinfecting, and serological testing. Our study highlights the critical need for enhanced biosafety awareness and training among dental students to reduce injury risks. Conclusions: These findings underline the necessity for integrated safety protocols and continuous education to improve clinical practices and ensure student safety.

Brain tumor being one of the major health hazards always needs a prompt diagnosis for the early treatment options to improve the chances of the survival of the patients. Traditional manual assessment of MRI (magnetic resonance imaging) to identify these conditions is a common practice. Hence, automation of the diagnosis practices can considerably improve the quality of the treatment procedures. In recent years almost every method for the automated diagnosis of brain tumor detection uses a deep learning technique. Despite decent works current techniques need a significant improvement to produce better results. Along with failure to produce decent results, the current deep learning models present very complex architectures which sometimes require huge computational resources. Therefore, in this paper we present a novel method that uses a lightweight dual-stream model with dual-input to detect brain tumors on MRI images. Both the inputs use different pre-processing mechanisms based on Contrast Limited Adaptive Histogram Equalization (CLAHE) and White Patch Retinex algorithm in order to enhance the feature learning capabilities of the proposed model. In addition, the proposed method uses a two-fold margin loss to boost training process for better feature learning. The proposed method produces state-of-the-art results for the detection of Glioma, Meningioma and Pituitary tumors. The model presents accuracy of 99%, 98% and 99% respectively for Glioma, Meningioma and Pituitary tumor detection.

The genus Amomum encompasses six medicinal species that are extensively utilized and have a significant historical background. Due to their morphological similarities, however, the presence of counterfeit and substandard products remains a challenge. Accurate plant identification is therefore essential to address these issues. This study utilized 11 newly sequenced samples along with extensive data from NCBI to perform molecular identification of these six species. The plastomes of Amomum displayed a typical quadripartite structure with conserved gene content, yet showed independent variations in the SC/IR boundary shifts at both inter- and intra-specific levels. Our approach incorporated ITS, ITS1, ITS2, complete plastomes, matK, rbcL, and psbA-trnH sequences for molecular identification, which effectively differentiated the six medicinal species within the genus Amomum, as confirmed by distance-based and phylogenetic tree analyses. Among these, the ITS, ITS1, and complete plastomes sequences demonstrated the highest identification success rate (3/6), followed by ITS2, matK, and psbA-trnH (1/6). In contrast, rbcL failed to identify any species. This research successfully established a reliable molecular identification method for Amomum plants, to protect wild plant resources and promote the sustainable use of medicinal plants and restrict the exploitation of these resources.

Objective: The Covid-19 pandemic has raised significant concerns about public health, particularly in terms of mental well-being due to heightened fear and uncertainty. The findings of this study are based on a survey conducted to evaluate the mental health status of the general population in Croatia during the Covid-19 pandemic. Methods: A survey conducted randomly and cross-sectionally included 588 respondents from all 21 counties in Croatia. The survey gathered demographic data and assessed various factors related to pandemic response measures and mental health using the Mental Health Continuum-Short Form (MHC-SF) scale. Results: Despite feeling adequately informed about Covid-19 (76.0%), most respondents (60.8%) expressed concerns about their loved ones during the pandemic. There were significant numbers who felt there was no risk of infection (50.9%) or believed they would not get infected (40.2%), while 72.4% were content with government measures. Statistical analysis indicated that mental health was not significantly different between genders, but age-related differences were evident, with those under 21 experiencing the most distress. The lowest level of psychological and social well-being was observed in respondents who were unemployed. Conclusions: The study identifies vulnerable groups in the Croatian population during the pandemic, including younger individuals, those on parental leave, students, and the unemployed, who exhibited worse mental health. The importance of implementing targeted mental health interventions to support these vulnerable groups is highlighted by these findings.

Soil-structure interaction (SSI) leads to a modification of dynamic properties of a structure, but due to the complexity on analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported at the ground, which unavoidably gives potential dangers to seismic performances of the structure. This study focuses on the possibility of the detrimental effects of SSI by comparing the dynamic responses of SSI system to fixed-base structure. The SSI model consists of an oscillator, a three-dimensional foundation and a multilayered half-space. In indirect boundary element method is employed, combined with non-singular Green’s functions of distributed loads to calculate the foundation impedances for substructure method. Although the SSI mechanism dampens peak amplitude of structure response in frequency domain, case studies on four buildings to 42 earthquakes in time history show a possibility of 15%-20% that SSI amplifies the dynamic responses, depending on the frequency component of incident waves. Also, a neural network algorithm is proposed to provide a new idea of involving SSI analysis into the traditional seismic designs, to eliminate potential hazards of SSI.

Parkinson-like events are side effects that may persist for an extended period even after drug administration is discontinued. Although these events can be triggered by various drugs, the mechanisms underlying their diverse symptoms remain largely unclear. To investigate this, we used the Japanese Adverse Drug Event Reporting Database, which is maintained by the Phar-maceuticals and Medical Devices Agency, to analyze the risk factors associated with Parkinson-like events along with associated drug trends and characteristics. Our findings indicate that similar to　Parkinson’s disease, age-related differences affect the onset of these events, with older individuals being more susceptible. Hierarchical clustering and principal component analysis revealed that the mechanisms triggering these Parkinson-like events are consistent across reports, suggesting a common underlying cause. However, even with a consistent mechanism, side effects can vary depending on the site of action. These insights underline the importance of swift identification of the drugs suspected of causing these events and implementation of measures to reduce their side effects.

Attention-Deficit/Hyperactivity Disorder (ADHD) exhibits a notable prevalence across diverse populations, with estimates ranging from 4% to 6%. This wide range prompts an investigation into the evolutionary and genetic underpinnings of ADHD, especially considering the markedly different environments faced by ancestral human populations compared to today's structured societies. This study examines the potential adaptive advantages of ADHD-associated traits in hunter-gatherer contexts, where hyperactivity, impulsivity, and novelty-seeking behaviors may have conferred survival benefits. We employ the principles of population genetics, including Hardy-Weinberg equilibrium, selection coefficients, and genetic drift, to model the dynamics of ADHD allele frequencies over time. Additionally, we discuss balancing selection as a mechanism for maintaining genetic diversity and how gene-environment interactions (GxE) contribute to the expression of ADHD in contemporary settings. Our analysis suggests that traits associated with ADHD, while potentially maladaptive in modern structured environments, could have been preserved through evolutionary processes due to their adaptive value in ancestral contexts. Understanding these dynamics provides a comprehensive view of ADHD's prevalence and highlights the significance of genetic and environmental interplay in shaping human behavior.

This study aims to provide an understanding of the preferences of student tourists regarding service attributes related to domestic accommodation. To clarify how lodging firms formulate policies for the student travel market, a “Relative to an Identified Distribution” (RIDIT) analysis in which responses are treated as ordinal data instead of equally spaced data is performed to examine the Likert-scale data obtained from 296 university students in Taiwan. In our RIDIT analytical results, respondents’ preferences are sorted in a descending importance. Of the examined attributes, “Cleanliness of rooms” is the attribute most prioritized by the students, followed by “Located in a safe neighborhood/feeling safe in the room,” and “Close to scenic area for meeting the trip requirement.” The attribute least prioritized by the students is “Interaction with other guests.” This analysis provides conclusions that differ from those obtained through commonly used techniques including the arithmetic average and exploratory factor analysis. The preference rankings indicate that managers should focus on the most prioritized service attributes and implement the necessary measures to enhance their service quality and maximize customer satisfaction.

We propose a neural-network-based watermarking method that introduces the quantized activation function that approximates the quantization of JPEG compression. Many neural-network-based watermarking methods have been proposed. Conventional methods have acquired robustness against various attacks by introducing an attack simulation layer between the embedding network and the extraction network. The quantization process of JPEG compression was replaced by the noise addition process in the attack layer of the conventional methods. In this paper, we propose a quantized activation function that can simulate the JPEG quantization standard as it is in order to improve the robustness against the JPEG compression. Our quantized activation function consists of several hyperbolic tangent functions and is applied as an activation function for neural networks. Our network was introduced in the attack layer of ReDMark proposed by Ahmadi et al. to compare it with their method. That is, the embedding and extraction networks had the same structure. We compared the usual JPEG compressed images and the images applying the quantized activation function. The results showed that a network with quantized activation functions can approximate JPEG compression with high accuracy. We also compared the bit error rate (BER) of estimated watermarks generated by our network with those generated by ReDMark. We found that our network was able to produce estimated watermarks with lower BERs than those of ReDMark. Therefore, our network outperformed the conventional method with respect to image quality and BER.

Total hip arthroplasty (THA) is a preferred treatment for primary osteoarthritis (OA) or secondary due to developmental hip dysplasia (DDH). Gait analysis is considered a golden standard for evaluating post-arthroplasty walking patterns. This study compared post-THA spatiotemporal gait parameters (SGPs) between OA and DDH patients and explored correlations with demographic and clinical variables. Thirty patients (15 per group) were recorded during gait, and their SGPs were analyzed. Functionality was evaluated with the Oxford Hip Score (OHS). The OA patients were significantly older than DDH (pr< 0.51, all p< 0.05). The preoperative gait alterations associated with OA or DDH were improved to similar levels in both groups after THA. Post-arthroplasty SGPs and OHS correlations indicate limitations in certain activities. These find-ings must be correlated with kinetic gait analysis data to fully evaluate gait and functionality dif-ferences among patient groups.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

The use of sustainable energy sources is a feasible alternative for fossil fuel products, which can represent a positive factor to alleviate many current environmental issues. In that sense, not only the sustainable industrial development is important, but also sustainable practices at local level, including households. Specifically, heating and cooking are one of the most important activities that require energy in households, where the role of biomass could be interesting, as it can provide an energy source with lower environmental impact. However, there is room for improvement in biomass stoves, whose adaptability to specific wastes, as well as their improvement in efficiency, should be accomplished. The aim of this work was to assess the improvement of combustion performance of a domestic stove by the implementation of a programmable logic converter for a better adaptation to different biomass samples (holm oak, pear tree, poplar and sugarcane bagasse pellets). Thus, the working regime of the stove was controlled, especially concerning the screw conveyor (to regulate pellet feeding) and flue gas fan (to change oxygen supply). As a result, better combustion performances were obtained, heat capacities from 5.66 to 8.67 kW for the selected samples. On the other hand, different improvements of the combustion stove to avoid blockages, for instance, are proposed as further steps.

As is well known, limiting carbon emissions is an important link in mitigating global climate change. Carbon quotas are a widely used policy tool by governments around the world, without increasing the financial burden on the government. To study the impact of carbon quota policies on the clean transformation of the key carbon emitting industry - the power industry, we established a duopoly model and conducted analysis and numerical simulation. Research has found that the effectiveness of carbon quota policies is closely related to the level of competition within the power supply chain, and is also influenced by the market share of clean energy power generation enterprises.Moreover, in some cases, it may have the opposite effect.

This study investigates the valorization potential of yellowfin tuna tails for the production of high-value commercial products. Muscle and skins were firstly mechanically separated by using a specifically designed device. The muscle was then used as a nitrogen source for the growth of the proteolytic enzymes-producer Bacillus subtilis, whereas the skins were employed for gelatin extrac-tion. The proteases from Bacillus subtilis were partially purified and used to produce antioxidant peptides from gelatin obtained. The gelatin obtained formed a gel upon cooling, with gelling and melting temperatures at 16 ºC and 22 ºC, respectively, and Bloom Strength of ≈ 160. RSM was used to determine the optimal hydrolysis conditions to obtain the highest antioxidant activity (35.96%, measured as DPPH radical scavenging activity), which were 50°C / 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability in the frame of circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhance economic viability of the tuna industry.

This research aims to elucidate the organizational patterns of interregional economic interdependence to enhance our comprehension of the national economy's structure at a regional scale. Employing a multilayer network model, this study represents economic interdependence among Indonesian regions, utilizing the InterRegional Input-Output (IRIO) table. Through the application of various metrics, such as degree and strength distribution, assortativity coefficient, and global and local rich club coefficient, to the multilayer IRIO network, we uncover the organizational patterns of economic exchanges between provinces and economic sectors within Indonesia. Our findings demonstrate that a multilayer network approach reveals the heterogeneous and complex structure of the national economy at the regional level. By analyzing the assortativity pattern and global rich-club coefficient, we illustrate that the IRIO network exhibits a hierarchical organization, where significant provincial-sector nodes are interconnected and form dense rich clubs, extending from a few structural cores to peripheral regions. Additionally, we identify distinct connectivity patterns of non-rich nodes based on their incoming and outgoing relations. The insights gained from this study have implications for the macro-control of regional development.

In Taiwan, remote healthcare was initially limited to telemedicine services, and the systematic development of remote care was relatively delayed. It was not until 2007 that the Department of Health of the Executive Yuan first initiated the 'Remote Care Pilot Program,' followed by the 'Remote Care Service Improvement and Quality Enhancement Plan' in the subsequent year. In 2010, Taiwan officially launched the 'Remote Health Care Services Development Plan' and established a dedicated project office, marking the comprehensive start-up of remote care services. This stage saw significant contributions from artificial intelligence aids and ICT remote transmission technologies, greatly promoting the application of smart healthcare in home care. This study aims to explore the strategic gaps in the application of smart healthcare in home remote care. By analyzing gaps in 'legal regulations,' 'economic factors,' 'user behavior habits,' 'policy and culture,' and 'environment and technology,' this study employs a mixed-methods approach. Particularly, it uses the Analytic Hierarchy Process (AHP) to construct a weighted ranking of these strategic gaps. Through in-depth interviews with doctors and smart healthcare experts and the collection of 16 valid AHP questionnaire samples, which cover both industry and academia with a balanced distribution, the survey results are ensured to be representative and reliable. The findings indicate that 'legal regulations' are considered the most critical strategic gap that needs to be addressed first, followed by 'user behavior habits.' This suggests that when designing smart healthcare applications, greater consideration needs to be given to user acceptance and habits. By systematically analyzing and addressing these strategic gaps, this study not only provides solutions to issues in the application of smart healthcare in home remote care but also offers valuable references for future research and practice, aiming to make home remote care services more comprehensive and efficient.

Objective: To analyze prevalence of tuberculosis among the people who presented PIMS with complaints of fever, cough, difficulty in breathing during COVID pandemic.Study Design: Retrospective/ Cross-sectional study.Place and Duration: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad. 2020-2023. Methods: Total 17121 patients who presented PIMS during COVID pandemic with complaints of high grade fever, cough, difficulty in breathing ,were included in this study. Following the acquisition, the HRCT scans were conducted by a skilled and experienced technician and researcher, utilizing GE Healthcare equipment for HRCT Chest procedures. The scans covered the lung apices to the bases and were executed with maximal inspiration, employing a CT scanner from Toshiba Aquilion. Frequency of TB among all cases was recorded. SPSS 21.0 was used to analyze all data.Results: This study incorporated a total of 17,121 patients, comprising 9,961 (58.1%) males and 7,160 (41.8%) females. The mean age of the enrolled cases was 49.11±7.67 years, demonstrating consistency with the findings of a prior study [33]. This study also examined the prevalence of Tuberculosis in different years based on imaging findings of HRCT chest as follows: in 2020, 582 cases out of 2,450, equivalent to 23.7%; in 2021, 2,377 cases out of 9,584, equivalent to 24.8%; in 2022, 1,099 cases out of 3,913, equivalent to 28.1% and in 2023, 295 cases out of 1,174, equivalent to 25.1%. The average prevalence of TB cases from 2020 to 2023 was determined to be 4,353 cases out of 17,121, which is equal to 25.42%.Conclusion: As per the National Tuberculosis Program (NTP) in Pakistan, the prevalence rate of tuberculosis stands at 340 cases per 100,000 population, equivalent to 0.34%. However, our study reveals an exceptionally high frequency of TB cases. Specifically, the prevalence of Tuberculosis in 2020 was 23.7% (582 out of 2,450), in 2021 it was 24.8% (2,377 out of 9,584), in 2022 it surged to 28.1% (1,099 out of 3,913), and in 2023 it was 25.1% (295 out of 1,174). The average prevalence of TB cases over the period from 2020 to 2023 was calculated at 25.4% (4,353 out of 17,121). Consequently, our findings suggest the presence of a substantial tuberculosis burden in Pakistan, equating to a TB Tsunami in Pakistan.

Elevated levels of homocysteine (Hcy) and related metabolites are associated with Alzheimer’s disease (AD). Severe hyperhomocysteinemia causes neurological deficits and worsens behavioral and biochemical traits associated with AD. Although Hcy is precluded from entering the Genetic Code by proofreading mechanisms of aminoacyl-tRNA synthetases, and thus is a non-protein amino acid, it can be attached to proteins via an N-homocysteinylation reaction mediated by Hcy-thiolactone. Because N-homocysteinylation is detrimental to protein’s function and biological integrity, Hcy-thiolactone detoxifying enzymes – PON1, BLMH, BPHL – have evolved. This review provides an account of the biological function of these enzymes and of consequences of their impairments leading to phenotypes characteristic of AD.

Exploring new approaches to innovating higher vocational education is a worldwide pursuit driven by the increasing demand for graduates equipped with competencies. This study investigated how Outcomes-Based Education (OBE) influences the attainment of graduate competence (AGC) in China’s higher vocational education, using the theory of Constructive Alignment (CA) as its foundation. The OBE framework incorporates intended learning outcomes (ILOs), project-based learning (PjBL), assessment strategies (ASs), and AGC. The study tested the model by assessing the impact of ILOs, PjBL, and ASs on AGC, respectively and sequentially. Surveys were administered to 320 CBEC learners in April 2024, resulting in 301 usable responses. Data were analyzed using structural equation modeling (SEM) with SPSS 23.0 and AMOS 24.0. Results indicated that PjBL and ASs were directly and positively related to graduate competency attainment, while ILOs were indirectly associated with graduate competence through the mediating roles of PjBL and ASs. The most substantial mediating effect between ILOs and graduate competence was ASs, followed by PjBL, and then, the chain mediating effect of PjBL and ASs. These findings enhance the theoretical understanding of OBE and provide detailed procedures for tracking and enhancing sustainability in higher vocational education. Beneficiaries include educators, policymakers, and accreditation bodies.

Background: Patterns of humoral immune responses represent a major hurdle in terms of pig-to-human xenotransplantation approaches. The best-known xenogeneic glycan antigens pre-sent in pigs are the αGal (Galili-antigen) and the non-human sialic acid Neu5Gc. As there are further differences between porcine and human cellular surface glycosylation, a much broader range of glycan epitopes with xeno-reactive relevance can be anticipated. Therefore, we set-out to chemically modify porcine cellular surface glycans in a global approach by applying sodium peri-odate (NaIO4) oxidation. Methods: Porcine endothelial cells were exposed to oxidation with 1 to 5 mM NaIO4 for different time periods at 37°C or 4°C and under static or dynamic conditions. The impact on cellular sur-vival was determined applying live/dead-assays. Oxidation of αGal-epitopes was assessed by flu-orescence microscopy-based quantification of isolectin-B4 (IL-B4) staining. Overall immunogenic-ity of porcine cells was determined by human serum antibody binding. Results: Treatment of porcine endothelial cells and tissues with NaIO4 led to a reduced binding of the αGal-specific IL-B4 and/or human serum antibodies. NaIO4 revealed to be cytotoxic when performed at elevated temperature and for prolonged time. However, by applying 2 mM NaIO4 for 60 min at 4°C a high extent of cellular viability and a relevant reduction of detectable αGal epitope were observed. No differences were detected irrespectively on whether the cells were oxi-dized under static or flow conditions. Conclusion: Glycan epitopes on living cells can be oxidized with NaIO4 while maintaining their viability. Accordingly, this strategy holds promise to prevent immune reactions mediated by pre-formed anti-glycan antibodies.

The growing importance of edge and fog computing in the modern IT infrastructure is driven by the rise of decentralized applications. However, resource allocation within these frameworks is challenging due to varying device capabilities and dynamic network conditions. Conventional approaches often result in poor resource use and slowed advancements. This study presents a novel strategy for enhancing resource allocation in edge and fog computing by integrating machine learning with blockchain for reliable trust management. Our proposed framework, called CyberGuard, leverages blockchain’s inherent immutability and decentralization to establish a trustworthy and transparent network for monitoring and verifying edge and fog computing transactions. CyberGuard combines the Trust2Vec model with conventional machine learning models like SVM, KNN, and Random Forests, creating a robust mechanism for assessing trust and security risks. Through detailed optimization and case studies, CyberGuard demonstrates significant improvements in resource allocation efficiency and overall system performance in real-world scenarios. Our results highlight CyberGuard’s effectiveness, evidenced by a remarkable accuracy, precision, recall, and F1-Score of 98.18%, showcasing the transformative potential of our comprehensive approach in edge and fog computing environments.

Grape pomace (GP) is considered a natural source of bioactive compounds. To improve the ex-tractability of bioactive compounds, in this work GP was biologically treated for 15 days with the white-rot fungus Trametes versicolor in laboratory jars and a tray bioreactor under solid-state fermentation (SSF) conditions. During SSF, the activity of lignolytic (laccase, manganese peroxi-dase) and hydrolytic (xylanase, cellulase, β-glucosidase and invertase) enzymes was measured, with the activity of laccase (2.66 U/gdb in jars and 0.96 U/gdb in the bioreactor) and xylanase (346.04 U/gdb in jars and 200.65 U/gdb in the bioreactor) being the highest. The effect of the com-plex enzyme system was reflected in the changes in the chemical composition of GP with in-creasing ash, crude protein and free fat content: 28%, 10% and 17% in the laboratory jars and 29%, 11% and 7% in the bioreactor, respectively. In addition, the biological treatment had a positive effect on the extractability of 13 individual phenolic compounds. Therefore, the applied SSF technique represents an effective strategy to improve the profile of phenolic compounds and the nutritional composition of GP, promoting their valorization and opening the door for potential application in the food industry and other sectors.

This paper presents a comprehensive analytical-numerical algorithm constructed for proprotor performance evaluation, focusing on accommodating large inflow angles. The algorithm’s design, range, and analytical features are clarified, indicating its potential to improve performance analysis, particularly for blades with substantial pitch variations. The Stahlhut model has not been validated against the conventional BEMT small-inflow angle methodology. This paper implements a modified Stahlhut model, coupled with the conventional BEMT theory. Preliminary validations of the model demonstrate promising results, with deviations reduced to -3% to 4% compared to conventional BEMT methods exhibiting deviations as high as 20% to 88% against experimental data for a highly twisted proprotor. The reconsideration of the computational module carries considerable implications for the design and refinement of proprotors, providing alternative analysis methods that could improve operational effectiveness across a range of flight scenarios. Drawing upon the theoretical framework presented by Stahlhut, the algorithm enables a more complex understanding of proprotor dynamics, facilitating accurate predictions of the loads at each blade section. The introduced algorithm emerges as a valuable asset for evaluating proprotor performance during the early stages of design and certification, offering both low computational cost and medium to high reliability.

In this study, a cholera infection model with the bilinear infection rate is developed by considering the perturbation of the infection rate by the mean-reverting process. First of all, we give the existence of a globally unique positive solution for a stochastic system at arbitrary initial value. On this basis, the sufficient condition for the model to have an ergodic stationary distribution is given by constructing proper Lyapunov functions and tight sets. This indicates in a biological sense the long-term persistence of cholera infection. Furthermore, after transforming the stochastic model to an relevant linearised system, an accurate expression for the probability density function of the stochastic model around a quasi-endemic equilibrium is derived. Subsequently, the sufficient condition to make the disease extinct is also derived. Eventually, the theoretical findings are shown by numerical simulations. Numerical simulations show that the impact of regression speed and fluctuation intensity on stochastic systems.

A modification to the conventional spark plasma sintering (SPS) process was undertaken to allow edge-free deformation of grains longitudinally to the loading axis in a process termed spark plasma texturing (SPT). The resulting Al7075 SPT compact was compared to SPSed Al7075 in terms of densification behaviour, microstructural evolution, and mechanical properties. The result reported herein highlights the unique benefits of the SPT technique and potential application in the manufacturing of advanced materials.

Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.

This research explores the application of Support Vector Machine (SVM) and Digital Surface Models (DSM) derived from Unmanned Aerial Vehicle (UAV) data for a vertical-horizontal classification of mangrove ecosystems in Tongke-tongke and Samataring Village. The study focuses on integrating high-resolution DSM subtracted from Digital Terrain Models (DTM) to classify mangrove vegetation into sixteen distinct vertical-horizontal classes based on vegetation type and elevation. The analysis revealed that older mangroves, particularly those within the 25-35 meters elevation range, dominate the landscape, accounting for 43.40% of the total classified area. This dominance suggests a mature and ecologically stable mangrove ecosystem, which is crucial for biodiversity conservation and carbon storage. The study demonstrates the effectiveness of SVM and UAV technologies in providing detailed and accurate ecological assessments of mangrove forests. The classification results contribute valuable insights into the structural diversity and health of mangrove ecosystems, facilitating targeted conservation and management strategies. Additionally, the research highlights the utility of advanced remote sensing and machine learning techniques in enhancing the precision of environmental monitoring and the assessment of carbon sequestration capabilities within mangrove ecosystems. The findings underscore the potential of UAV-based remote sensing for ecological studies, offering a replicable method for similar assessments in other regions, thereby supporting global environmental management and climate action initiatives.

Fragile X syndrome (FXS) is an intellectual developmental disorder characterized, inter alia, by deficits in short-term processing of neural information such as sensory processing and working memory. The primary cause of FXS is the loss of fragile X messenger ribonucleoprotein (FMRP), which is profoundly involved in synaptic function and plasticity. Short-term synaptic plasticity (STSP) may play important roles in functions that are affected by FXS. Recent evidence points to a crucial involvement of presynaptic calcium sensor synaptotagmin-7 in STSP. However, how the loss of FMRP affects STSP and synaptotagmin-7 have been insufficiently studied. Further-more, males and females are affected differently by FXS, but the underlying mechanisms remain elusive. The aim of the present study is to investigate possible changes in STSP and the expres-sion of synaptotagmin-7 along the hippocampus of adult males and females in the Fmr1 knock-out (KO) rat model of FXS. We found that paired-pulse ratio and frequency facilita-tion/depression, two forms of STSP, as well as the expression of synaptotagmin-7, are normal in adult KO males, but paired-pulse ratio is increased in the ventral hippocampus of KO females. Furthermore, we found no gender-related but robust region-dependent difference in STSP. AM-PA receptors are similarly expressed in the two hippocampal segments of the two genotypes and in both genders. Also, basal excitatory synaptic transmission is higher in males compared with females. Interestingly, we found more than twofold higher levels of synaptotagmin-7, not syn-aptotagmin-1, in the dorsal compared with the ventral hippocampus in males of both genotypes and in wild type females. These results point to the susceptibility of the female ventral hippo-campus to FMRP loss. Importantly, the different levels of synaptotagmin-7 that parallel the higher score of synaptic facilitation in the dorsal vs ventral hippocampus suggest that synapto-tagmin-7 may play a pivotal role in defining the striking difference in STSP along the long axis of the hippocampus.

This the term "Bubungan Tinggi" (High Roof) in this study refers to the banjarese traditional house. A significant artifact in South Kalimantan is called Bubungan Tinggi. With its unique typology and anatomy, this particular building has evolved into an iconic structure that symbolizes the collective memory of the Banjarese people.This research aims to showcase the versatility of the Bubungan Tinggi design in modern architecture by exploring different transformation models. By applying various techniques and approaches, the study provides insights into how this traditional Banjarese character can be adapted for new house designs.The Bubungan Tinggi's transformation process reveals characteristics in its fundamental components, which are distinguished by their geometric objects. Experimental design is the methodology employed in this study. This methodology shows that a variety of transformation models may be carried out by introducing and identifying the Bubungan Tinggi, observing objects in case studies, using transformation techniques and their application, and creating transformation models.This research produced a variety of modeling results that illustrated new interpretations of bubungan tinggi's in modern house design. The incorporation of traditional elements like the bubungan tinggi in modern house design can help preserve cultural heritage while also creating unique and innovative architectural solutions.

Particles are considered temporarily identical if the interchange of these particles does not cause any observable physical effects within a time interval Δt. An indistinguishability hypothesis is proposed for such particles, suggesting that two particles (or systems) with nearly the same degree of internal freedom will actually interchange under certain circumstances, thereby affecting the subsequent dynamics. This indistinguishability implies that, theoretically, it is possible to capture an elementary particle with extraordinarily large internal freedom by trading it for an isolated composite system of ordinary matter particles with almost the same total internal freedom as the large-freedom particle. Following this, the ordinary particles will instantly disperse into the environment, while the large-freedom particle will initially be captured and then gradually delocalized into the environment, an observable phenomenon. If this hypothesis is proven true in the future, it might provide a novel strategy for detecting dark matter particles.

This paper delves into the concept of information within the context of conscious systems, emphasizing the pivotal role of entropy as a fundamental aspect in comprehending consciousness. Drawing on insights from Integrated Information Theory (IIT) and information theory, the argument posits that consciousness entails dynamic information processing, distinct from the static storage and retrieval model employed by modern computers. The intrinsic dynamics of neural systems are explored, illuminating how they integrate incoming stimuli into a unified state of subjective experience, thereby shaping conscious awareness. By considering entropy as a temporal and qualitative value, its significance in reducing uncertainty and facilitating adaptability in conscious systems is underscored. Through a series of principles, the intricate relationship between entropy, neural dynamics, and consciousness is elucidated. This analysis suggests the necessity of rethinking traditional notions of information when applied to conscious systems, highlighting the dynamic nature of consciousness and its interaction with the environment.

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances and the therapeutic effects of metabolic ketogenic therapy remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

In this study, we present a novel method for fabricating semi-transparent electrodes by combining silver nanowires (AgNW) with titanium nitride (TiN) layers, resulting in conductive nano-composite coatings with exceptional electro-mechanical properties. These nano-composites were deposited on cellulose nanopaper (CNP) using a plasma-enhanced pulsed laser deposition (PE-PLD) technique at low temperatures (below 200°C). Repetitive bending tests demonstrate that incorporating AgNW into TiN coatings significantly enhances the microstructure, increasing the electrodes electro-mechanical robustness by up to four orders of magnitude compared to commercial PET/ITO substrates. Furthermore, the optical and electrical conductivities can be optimized by adjusting the AgNW network density and TiN synthesis temperature. Our results also indicate that the nanocomposite electrodes exhibit improved stability in air and superior adhesion compared to bare AgNW coatings. These findings are crucial for advancing bio-compatible flexible electronics and could lead to the development of new wearable and implantable medical devices.

Data integrity and security are among the most essential things in this digital era performance. Digital certificates can be one solution to this problem. This research will develop the architecture of digital certificate verification and validation using blockchain. The blockchain concept for digital certificates uses three stages: requirements planning, workshop design, and implementation. Digital certificate files will be tested based on a scenario in which there could be any changes to those files, such as compressing files, changing data of files, inserting images in the file, and rotating files. This system architecture will detect any changes that could occur to the digital certificate file by using a digital signature, Keccak256 hash algorithm, and blockchain. This research shows that change detection accuracy for digital certificate files is 100%. However, there is a digital signature nature that could reduce the accuracy of change detection, and several solutions can be resolved. The average time to generate a signature using blockchain technology is 2.11 seconds, faster than 3.23 seconds when it does not use blockchain. The average time to validate a signature is 2.11 seconds without using blockchain, which is reduced to 0.22 seconds using blockchain technology. This research concludes that the architecture for digital certificate verification and validation using blockchain technology has successfully improved the security of digital certificates. Testing showed that even minor changes to a digital certificate could affect the signature, ensuring the certificate's integrity. For further research, evaluating the performance of various hash algorithms within the blockchain network is recommended.

Let $\{\tau_n\}_{n=1}^\infty$ and $\{\omega_m\}_{m=1}^\infty$ be two modular Parseval frames for a Hilbert C*-module $\mathcal{E}$. Then for every $x \in \mathcal{E}\setminus\{0\}$, we show that \begin{align}\label{UE} \|\theta_\tau x \|_0 \|\theta_\omega x \|_0 \geq \frac{1}{\sup_{n, m \in \mathbb{N}} \|\langle \tau_n, \omega_m\rangle \|^2}. \end{align} We call Inequality (\ref{UE}) as \textbf{Noncommutative Donoho-Stark-Elad-Bruckstein-Ricaud-Torr\'{e}sani Uncertainty Principle}. Inequality (\ref{UE}) is the noncommutative analogue of breakthrough Ricaud-Torr\'{e}sani uncertainty principle \textit{[IEEE Trans. Inform. Theory, 2013]}. In particular, Inequality (\ref{UE}) extends Elad-Bruckstein uncertainty principle \textit{[IEEE Trans. Inform. Theory, 2002]} and Donoho-Stark uncertainty principle \textit{[SIAM J. Appl. Math., 1989]}.

Poultry farming in Slovakia has a tradition and an irreplaceable position to ensure rational nutrition for the population. In terms of a nutritional value, poultrymeat (Galliformes) contains a high amount of proteins, essential amino acids, essential unsaturated fatty acids, minerals, vitamins and a low fat content. Poultrymeat production has a relatively short reproductive cycle and thus allows regulating the demand and supply. The poultry market also influences the development of domestic consumption. According to the Statistical Office of the Slovak Republic, the consumption of meat has witnessed a persistent increase over the last 10 years. [1] According to the 2023 AVEC (The Voice of European Meat Sector) annual report, the consumption of poultrymeat in Slovakia was 20.0 kg per person per year. The average consumption in the EU-27 (2021) was 23.4 kg, with the countries with the highest consumption being Portugal (37.8 kg), Ireland (36.0 kg), Hungary (33.5 kg) and Spain (29.9 kg). On the other hand, the countries with the lowest consumption of poultrymeat, apart from Slovakia, also include Austria and Greece with a consumption of 21.5, resp. 21.0 kg [2]. The breeding of broiler chickens, as well as the production and placing on the market of poultrymeat must comply with the requirements laid down by legislation, while the compliance is regularly checked by the competent authorities.

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Demand for environmentally friendly types of energy is growing all over the world, which naturally increases the intensity of work on the production of hydrogen-containing fuel mixtures. Steam reforming of methanol is one of the most effective areas of research, as it is a process with low energy consumption. The results of steam reforming of methanol on the catalysts prepared by solution combustion synthesis (SCS) and impregnation by moisture capacity are presented. Investigation of the activity of Cu-Ce-Al catalysts of different composition was carried out for production of hydrogen and comparison of SCS with traditional impregnation method. Methanol conversion reaches 99%, while the selectivity of H2 was 88%, at 500 °C. It was found that CuAl2O4 spinel formation is due to substitution of Al3+ with Cu2+ Ce3+ cations. A consequence CuAl2O4 and CeAlO3 lattice parameters increase because of difference in ionic radius of Al3+ (0.53 Å) and Cu2+ (0.73 Å), Ce3+ (1.07 Å). Advantages of SCS catalysts in steam reforming of methanol were shown. The aim of this research is to develop a new catalyst for conversion of methanol into hydrogen containing fuel mixtures, which will further promote the organization of a new era of environmentally friendly energy-saving production methods.

This qualitative research study explores the multifaceted impacts of digital transformation on supply chain processes within contemporary business environments. Through in-depth interviews with industry professionals, the study investigates the implications of digitalization for visibility, collaboration, resilience, and innovation within supply chains. The findings highlight the opportunities presented by digital technologies for enhancing operational efficiency, mitigating risks, and creating value across supply chain networks. However, the study also underscores the challenges and barriers that organizations face in their digital transformation journey, including integration complexity, data security, and organizational culture. The research emphasizes the importance of strategic investments in digital capabilities, change management, and organizational culture to capitalize on the opportunities presented by digital transformation while addressing the associated challenges. By doing so, organizations can build agile, resilient, and competitive supply chains capable of thriving in an increasingly digitalized and interconnected world.

The objective of this study was to identify genomic regions and genes associated with resistance to gastrointestinal nematodes in Australian Merino sheep in Uruguay, using the single-step GWAS methodology (ssGWAS), which is based on genomic estimated breeding values (GEBVs) obtained from a combination of pedigree, genomic and phenotypic data. This methodology converts GEBVs into SNP effects. Analysis included 26,638 animals with fecal egg count (FEC) records obtained in two independent parasitic cycles (FEC1 and FEC2), and 1,700 50K SNP genotypes. Comparison of genomic regions was based on genetic variances (gVar(%)) explained by non-overlapping regions of 20 SNPs. For FEC1 and FEC2, 18 and 22 genomic windows exceeded the significance threshold (gVar(%) ≥ 0.22%), respectively. The genomic regions with strong associations with FEC1 were located on chromosomes OAR 2, 6, 11, 21 and 25, and for FEC2 on OAR 5, 6 and 11. The proportion of genetic variance attributed to the top windows was 0.83% and 1.9% for FEC1 and FEC2, respectively. The 33 candidate genes shared between the two traits were subjected to enrichment analysis, revealing a marked enrichment in biological processes related to immune system functions. These results contribute to the understanding of the genetics underlying gastrointestinal parasite resistance and its implications for other productive and welfare traits in animal breeding programs.

Areca palm sheath leaves were an incredibly noble food packaging system. In ancient times, naturally available wood, leaves, stems, and barks were used to store food materials. But all these were turned down upon the rise of civilization. Today, many modern food packaging systems are used; paper and paperboard packaging materials are used mainly as a replacement for plastic materials. But somehow, paper-based materials have major drawbacks when temperature-dependent products are stored; leaching out components poses a higher threat to health. To alleviate it, bio-based components were used in the manufacturing of paper materials, but the migration of those components was still risky. This study focuses on how the areca palm sheath leaves can be effectively used to prevent this migration of components.

: Background: Low birth weight (LBW) is a major public health problem in low-income countries. Infants born with LBW are at increased risk of neonatal mortality, have poorer school performance, and are more likely to develop respiratory and cardiovascular diseases in adulthood. Methods: An unmatched case–control study was conducted in five maternity wards in the Kenge Health Zone, involving 159 mother–newborn pairs. Data analysis was performed using STATA 18.0 software. Bivariate and multivariate analyses were used to determine the associations between independent variables and LBW. Results: Determinants of low birth weight were maternal short stature (height &lt; 155 cm) (adjusted odds ratio (AOR): 3.90; 95% confidence interval (CI): 1.66–9.13), maternal non-indigenous Yaka ethnic group (AOR: 2.39; 95% CI: 1.01–5.66), having attended fewer antenatal care (ANC) sessions (AOR: 0.73; 95% CI: 0.53–0.99), and inadequate maternal dietary diversity (AOR: 3.97; 95% CI: 1.25–12.62). Conclusions: Increased education and awareness of dietary diversity as an indicator of dietary quality in women of childbearing age, especially during pregnancy, along with regular follow-up of antenatal care visits and behavior change communication targeting pregnant women, can help health professionals address dietary taboos and reduce the incidence of LBW.

Traditional concrete pavements have poor water permeability, while the strength of pervious concrete pavements is low. To solve these problems, this study designed Innovative recycled aggregate pervious concrete (I-RAPC) with controllable water permeability and high strength by using response surface methodology, and investigated the effects of different pore parameters (number, diameter, material, distribution form, etc.) on the performance of I-RAPC. And the strength discount factor method was proposed to construct the theoretical calculation model of compressive strength and pipe pore parameters, and the calculation model of water permeability coefficient was established at the same time. The results show that the fewer the number of holes and the smaller the pipe diameter of I-RAPC, the higher its compressive strength and the smaller the water permeability coefficient. The theoretical model of compressive strength can accurately evaluate the discounting effect of the pore parameters on the compressive strength of I-RAPC, and the maximum relative error is only 7.52%, and the maximum relative error of the calculation model of water permeability coefficient is only 4.42%. I-RAPC has the advantages of high strength and permeability with controllable performance, which overcomes the problems of random distribution of pore space, uncertainty of water permeability, and strength of ordinary pervious concrete.

CAR-T cell therapy has emerged as a groundbreaking approach in cancer treatment, leveraging the immune system to target and eliminate cancer cells. While currently focused on hematologic malignancies, the future holds promise for expanding CAR-T cell therapy to diverse cancers, enhancing its efficacy, and improving safety profiles. Recent advances in tumor immunology have propelled CAR-T cell therapy as a game-changer in treating diseases such as relapsed/refractory B-cell acute lymphocytic leukemia (B-ALL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM). Six CAR-T cell products have received FDA approval for treating R/R B cell malignancies. However, challenges persist, including complications like cytokine release syndrome (CRS), coagulopathy, and cytopenias. Strategies to mitigate these complications involve targeting distinct antigens with dual- or multi-targeted CAR-T cells and enhancing immunogenicity. Additionally, γδ CAR-T cells show promise in recognizing antigen- negative leukemia cells in an MHC-independent manner while reducing the risk of inducing graft-versus-host disease (GVHD). As CAR-T cell therapy continues to evolve through innovation and discovery, it holds the potential to revolutionize cancer treatment, offering new hope to patients and reshaping the landscape of oncology with its precision and efficacy.

More than 20 lines of independent evidence from clinical observations, studies in laboratory animal models, pharmacokinetic considerations, and numerous temporal and spatial associations previously indicate that numerous genetic and environmental factors leading to inflammation and oxidative stress confer vulnerability to aberrant metabolism of acetaminophen during early development, leading to autism spectrum disorder (ASD). Contrary to this conclusion, multivariate analyses of cohort data adjusting for inflammation-associated factors have tended to show little to no risk of acetaminophen use for neurodevelopment. To resolve this discrepancy, here we use in-silico methods to create an ideal (virtual) population of 120000 individuals in which 50% of all cases of virtual ASD are induced by oxidative stress-associated cofactors and acetaminophen use. We demonstrate that Cox regression analysis of this ideal data set shows little to no risk of acetaminophen use if cofactors which create aberrant metabolism of acetaminophen are adjusted for in the analysis. Further, under-reporting of acetaminophen use is shown to be a considerable problem for this analysis, leading to large and erroneously low calculated risks of acetaminophen use. In addition, we argue that factors which impart susceptibility to acetaminophen-induced injury, and propensity for acetaminophen use itself, can be shared between the prepartum, peripartum, and postpartum periods, creating additional difficulty in analysis of existing datasets to determine risks of acetaminophen exposure for neurodevelopment during a specific time frame. It is concluded that risks of acetaminophen use for neurodevelopment obtained from multivariate analysis of cohort data depend on underlying assumptions in the analyses, and that other evidence, both abundant and robust, demonstrate the critical role of acetaminophen in the etiology of ASD.

Previous research demonstrates that the interruption of immersive experiences may lead to a bias in the results of questionnaires. Thus, the traditional way of presenting questionnaires, paper-based or web-based, may not be compatible with evaluating VR experiences. Recent research has shown the positive impact of embedding questionnaires contextually into the virtual environment. However, a comprehensive overview of the available VR questionnaire solutions is currently missing. Furthermore, no clear taxonomy exists for these different solutions in the literature. To address this, we present a literature review of VR questionnaire user interfaces (UI) following PRISMA guidelines. Our search returned 1.109 initial results, which were screened for eligibility, resulting in a corpus of 25 papers. This paper contributes to HCI and games research with a literature review of embedded questionnaires in VR, discussing the advantages and disadvantages and introducing a taxonomy of in-VR questionnaire UIs.

Global stress is widespread in todays post-pandemic world of political and economic uncertainty. Vibroacoustic technology is a vibrotactile intervention with multiple uses, and its impact on stress lacks interpretation. This research assessed if the vibroacoustic technology of a Vibroacoustic Sound Massage (VSM) can reduce psychological, physiological and cognitive stress. The Perceived Stress Scale (PSS-10), and electrocardiogram (ECG) and electroencephalogram (EEG) biosignals were used to quantify results. Participants were divided into Low Stress and High Stress groups. ECG results show VSM increased parasympathetic activity for all participants, with the Low Stress group more effected. EEG results indicate increased concentration (TBR), reduced arousal and increased relaxation (BAR), and non-significant effects on participant well-being (FAA), though variability in this metric was homogenised after VSM. Together, these results validate VSM as an effective support tool for stress management and further research is required.

The paper presents the problem of damage detection in steel girders. Static displacements at the selected point of the structure play the role of measured variables. Structural response signal decomposition is performed according to the Mallat pyramid algorithm, which is used to perform the discrete wavelet transform (DWT). This procedure allows us to quite well determine the location of structural damage. The geometry and the placement of any defective part of the structure may have a random character. It can be assumed that the random processes occurring in the broadly understood structure mechanics are Gaussian in nature. The first four probabilistic moments are estimated using three approaches independent: semi-analytical (SAM), perturbative (SPT), and Monte-Carlo simulations (MCS). The semi-analytical random approach seems to be the most optimal due to the necessary computation time. The incorporation of the mathematical stochastic apparatus into the classical (deterministic) analysis of the statics of the structure makes it possible to estimate the reliability measures of the analyzed girder.

Background: Older adults with bipolar disorder (OABD) are individuals aged 50 years and older with bipolar disorder (BD). People with BD may have fewer coping strategies or resilience. A long course of the disease, such as in OABD, could impact the development of resilience strategies, but this remains under-researched in OABD. Therefore, this study aims to assess resilience levels within the OABD and explore associated factors, hypothesizing that resilience could improve psychosocial functioning, wellbeing and quality of life of OABD patients. Methods: This study sampled 33 OABD patients from the OABD cohort at the Bipolar and Depressive Disorders Unit of Hospital Clinic of Barcelona. This was an observational, descriptive and cross-sectional study. Demographic and clinical variables as well as psychosocial functioning, resilience and cognitive reserve were analyzed. Resilience was measured using the CD-RISC-10. Non-parametric tests were used for statistical analysis. Results: The average CD-RISC-10 score was 25.67 points (SD 7.87). Resilience negatively correlated with the total number of episodes (p = 0.034), depressive episodes (p = 0.001), and the FAST (p < 0.001). Participants with normal resilience had a lower FAST (p = 0.046), a higher CRASH (p = 0.026), and more EOBD (p = 0.037) compared to those with low resilience. Conclusions: OABD individuals may exhibit lower resilience levels which correlate with more psychiatric episodes, particularly the number of depressions and worse psychosocial functioning and cognitive reserve. Better understanding and characterization of resilience could aid in early identification of patients requiring additional support to foster resilience and enhance OABD management.

A typical halogen-free flame-retardant (HFFR) formulation for electric cables may contain polymers, various additives, and fire-retardant fillers. In this study, composites are prepared by mixing natural magnesium hydroxide (n-MDH) with linear low-density polyethylene (LLDPE) and a few types of ethylene-octene copolymers (C₈-POE). Depending on the content of LLDPE and C₈-POE, we obtained composites with different crystallinity that affected the final mechanical properties. The nucleation effect of the n-MDH and the variations in crystallinity caused by the blending of C₈-POE/LLDPE/n-MDH were investigated. In the C₈-POE/LLDPE blend, we found a decrease in the crystallization temperature of LLPDE compared to pure LLDPE and an increase in the crystallization temperature of C₈-POE compared to pure C₈-POE. On the contrary, the addition of n-MDH led to an increase in the crystallization temperature of LLDPE. As expected, the increase in the crystallinity of the polyolefin matrix of composites led to higher elastic modulus, higher tensile strength, and lower elongation at break. Overall, these results show how to obtain the required mechanical features for halogen-free flame-retardant compounds for electric cable applications depending on the quantities of the two miscible components in the final blend.

Photoreceptor degeneration is a major cause of untreatable blindness worldwide and has recently been targeted by emerging technologies, including cell- and gene-based therapies. Cell types of neural lineage have shown promise for replacing either photoreceptors or retinal pigment epithelial cells following delivery to the subretinal space, while cells of bone marrow lineage have been tested for retinal trophic effects following delivery to the vitreous cavity. Here we explore an alternate approach in which cells from the immature neural retinal are delivered to the vitreous cavity with the goal of providing trophic support for degenerating photoreceptors. Rat and human retinal progenitor cells were transplanted to the vitreous of rats with a well-studied photoreceptor dystrophy, resulting in substantial anatomical preservation and functional rescue of vision. This work provides scientific proof-of-principle for a novel therapeutic approach to photoreceptor degeneration that is currently being evaluated in clinical trials.

With the advancing energy transition, ice is a growing problem in wind turbine sector. The development of systems to detect and mitigate icing makes it necessary to understand its basic behavior and characteristics. This paper proposes a method for the continuous and full field measurement of the icing process of rotating blades, using a single line laser profile scanner. Inside of a climate chamber, a rotor is driven by a motor, while a system of nozzles provides a fine water dust, which leads to ice accumulating on simple NACA blades, that in turn is measured by a triangulation laser. The measurement data is cleared from outliers and presented as a surface in 3D space. An alpha shape is used to reconstruct and extract the volume of the ice between a reference and a measurement surface, using the corresponding Matlab function. Appropriate input parameters for the function and offsetting of the reference surface to improve the results are compared and discussed. The resulting system is able to detect thin changes in the ice layer in the range of sub millimeter thickness.

In today's globalized business environment, multinational corporations (MNCs) face significant challenges in achieving and sustaining effective supply chain integration across diverse cultural contexts. This qualitative research explores the influence of cultural factors on supply chain integration within MNCs, employing in-depth interviews and thematic analysis to uncover key insights. Findings reveal the complex interplay between culture and supply chain practices, highlighting challenges related to cross-cultural communication, trust-building, decision-making, and organizational culture alignment. However, the study also identifies opportunities for leveraging cultural diversity as a source of competitive advantage, emphasizing the importance of cultural intelligence and cross-cultural competence for supply chain professionals. The implications of the research extend to managerial practice, suggesting the development of culturally sensitive strategies for supply chain integration and investment in cultural training and development programs. Moreover, the study underscores the need for a holistic approach to supply chain integration that considers not only technical and operational aspects but also cultural and social dimensions. While the research offers valuable insights, limitations such as the qualitative nature of the study and the focus on supply chain managers' perspectives should be considered. Future research could address these limitations and explore the interdependencies among various contextual factors to enhance our understanding of cultural influences on supply chain integration in MNCs.

The presence of exogenous auxins such as indole-3-acetic acid (IAA), has been reported in organic materials such as vermicompost. The objectives of this work were to quantify the concentration of IAA in sand-based substrates with vermicompost (S-VC), to establish the relationship between the concentration of exogenous IAA and the amount of vermicompost (VC), as well as determine its influence on the development of tomato plants. S-VC substrates with different percentages based on volume (0, 20, 40 and 50% VC) placed in pots were used to transplant tomato seedlings. In each substrate, the concentration of IAA was determined at the beginning and at the end of a culture cycle, as well as the bacterial load. In addition, some performance components were measured in the plants. The results show that by increasing 1 kg of VC in a sand-based substrate, the concentration of exogenous IAA increases both at the beginning and at the end of the experiment (0.0470 and 0.0642 mg g^-1, respectively); a result that, in turn, was related to the colony-forming units of gram-positive bacteria (Bacillus spp., mainly). Behavior that is reflected in tomato plants; for example, the root had its maximum development (371.33 cm^-3) when the amount of VC in the substrate was 4.12 kg.

Transient receptor potential canonical (TRPC) channels are calcium channels with diverse expression profiles and physiological implications in the retina. Neurons and glial cells of rat retinas with photoreceptor degeneration caused by retinitis pigmentosa (RP) exhibit basal calcium levels that are above those detected in healthy retinas. Inner retinal cells are the last to degenerate and are responsible for maintaining the activity of the visual cortex even after complete loss of photoreceptors. We considered the possibility that TRPC1 and TRPC5 channels might be associated with both the high calcium levels and the delay in inner retinal degeneration. TRPC1 is known to mediate protective effects in neurodegenerative processes, while TRPC5 promotes cell death. In order to comprehend the implications of these channels in RP, the co-localization and subsequent physical interaction between TRPC1 and TRPC5 in healthy retina (Sprague-Dawley rats) and degenerating (P23H-1, a model of RP) retina were detected by immunofluorescence and proximity ligation assays. There was an overlapping signal in the innermost retina of all animals where TRPC1 and TRPC5 physically interacted. This interaction increased significantly as photoreceptor loss progressed. Both channels function as TRPC1/5 heteromers in the healthy and damaged retina, with a marked function of TRPC1 in response to retinal degenerative mechanisms. Furthermore, our findings support that TRPC5 channels also function in partnership with STIM1 in Müller and retinal ganglion cells. These results suggest that increase in TRPC1/5 heteromers may contribute to slowing of the degeneration of the inner retina during the outer retinal degeneration.

An innovative concrete that incorporates the advantages of self-compacting concrete with geopolymer is called self-compacting geopolymer concrete. The objective of this study was the Manufacturing of M30-grade self-compacting geopolymer concrete by adding industrial materials like fly ash (FA), ultrafine ground granulated blast furnace slag (UFGGBS), and silica fume (SF) as minerals. The disposal of these industrial wastes can be substantially overcome, as they lead to land pollution. The fixed powder content was 500 kg/m³. A mixture of sodium silicate (Na₂SiO₃) and sodium hydroxide (NaOH) created an alkaline solution that activated the cementitious binders. In this study, slump flow, L-box, V Funnel, T50 V Funnel, and J ring tests were carried out to determine the fresh qualities of the concrete. These tests were conducted under the regulations for self-compacting concrete provided by EFNARC (2005). To improve the flexural strength of the SCGC, 1.5 % glass fibre was added. This study illustrates how an artificial neural network (ANN) model can determine the concrete mix proportion. The characteristics of SCGC, both fresh and hardened properties test were investigated for molarities of 8, 10, and 12. The microstructural outcomes were determined using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and X-ray diffraction (XRD).

The global centenarian population is expected to reach 3 million by 2050, yet little is known about the health status of centenarians in Sub-Saharan Africa. A case study examined the health conditions and functionality of nine Ethiopian centenarians. In-depth interviews revealed that all nine were Orthodox-Christians and lived with extended family; eight were male. Aside from minor health complaints, centenarians in rural Ethiopia perceived that their sensory/cognitive functionality was normal until their late 90s. Despite a lack of medical care, the centenarians included 2 survivors, 4 delayers, and 3 escapers. Centenarians in rural Ethiopia were embedded in closely-knit, religious, multigenerational households and communities and aspired to live resiliently. Findings call for consideration of the unique health status of centenarians in Global South nations in their own cultural context.

Magnesium monofluoride is a polar molecule amenable to laser cooling which has caused renewed interest in its spectroscopy. In this work we consider the case of three low-lying electronic excitations, namely $\rm X \, {}^{2}\Sigma \to A \, {}^{2}\Pi, \ \to B \, {}^{2}\Sigma, \ \to C \,{}^{2}\Sigma$, using well developed quantum chemistry approaches, i.e., without reference to the spin-orbit splitting of the $\rm A \, {}^{2}\Pi$ states. Accurate experimental data for these transitions have been available for over 50 years. Here we explore the linear response method at the level of CC2 theory, as well as equation of motion methods at the level of CCSD and CC3, using two families of basis sets. Excellent agreement is obtained for the first three transitions when using the correlation-consistent basis sets and extrapolation to the complete basis limit within EOM-CC3 (at a relative precision of $10^{-4}$), and qualitative agreement for the other two methods. The purpose of this paper is to serve as a guide in how to approach the accurate calculation of excitations in polar diatomic molecules.

Connexins (Cxs) are transmembrane proteins that assemble into gap junction channels (GJCs) and hemichannels (HCs). Previous research supports the involvement of Rho GTPases and actin microfilaments in the trafficking of Cxs, formation of GJCs plaques, and regulation of channel activity. Nonetheless, it remains uncertain whether distinct types of Cxs HCs and GJCs respond differently to Rho GTPases or changes in actin polymerization/depolymerization dynamics. Our investigation revealed that inhibiting RhoA, a small GTPase that controls actin polymerization, or disrupting actin microfilaments with cytochalasin B (Cyto-B), resulted in reduced GJCs plaque size at appositional membranes and increased transport of HCs to non-appositional plasma membrane regions. Notably, these effects were consistent across different Cx types, since Cx26 and Cx43 exhibited similar responses despite having distinct trafficking routes to the plasma membrane. Functional assessments showed that RhoA inhibition and actin depolymerization decreased the activity of Cx43 GJCs while significantly increasing HCs activity. However, the functional status of GJCs and HCs composed of Cx26 remained unaffected. This study supports the hypothesis that RhoA, through its control of the actin cytoskeleton, facilitates the transport of HCs to appositional cell membranes for GJCs formation while simultaneously limiting the positioning of free HCs at non-appositional cell membranes, independently of Cx type. This dynamic regulation promotes intercellular communication and reduces non-selective plasma membrane permeability through a Cx-type dependent mechanism, whereby Cx43 HCs and GJCs are affected, but Cx26 channels are not.

We analyze a time-delayed SIQR model that considers the transportation-related infections and entry-exit screening. This model aims to determine the measures for preventing and controlling major emergent infectious diseases and the associated costs. We calculate the basic reproduction number (R0), apply the linearization method, and construct an appropriate Lyapunov function to determine the stability of the disease-free equilibrium in the local and global. We collect COVID-19 infection data from two regions in the United States in 2020 for data fitting, obtain a set of optimal parameter values, and show that the model is suitable for simulating the outbreak and spread of emerging infectious diseases. We find that transportation-related infections increase the basic reproduction number, enhancing the impact on disease spread. Entry-exit screening effectively suppress the spread of disease by reducing the basic reproduction number. Furthermore, we investigate the influence of the incubation period on disease and find that a shorter incubation period results in a shorter duration but a larger scale of infection, and the peaks are reduced. We conduct a sensitivity analysis of the R0 and propose three measures to prevent the spread of new infectious diseases based on the most sensitive parameters: wearing masks, implementing urban closures, and administering medication to sick but not yet hospitalized patients promptly. In the case of COVID-19, we use Pontryagin’s minimum principle to get time-varying control measures to control the spread of the outbreak. Optimal control effectively controls the development and deterioration of the disease. Finally, several control measures are compared through cost-effectiveness analysis, and the results show that wearing masks is the most cost-effective measure. Our study provides some practical guidance for controlling the spread of major emerging infectious diseases.

The steady rheological behavior of suspensions of solid particles thickened by cellulose nanocrystals is investigated. Two different types and sizes of particles are used in the preparation of suspensions, namely TG hollow spheres of Sauter mean diameter of 69 µm and Solospheres S-32 of Sauter mean diameter of 14 µm. The nanocrystal concentration varies from 0 to 3.5 wt% and the particle concentration varies from 0 to 57.2 vol%. The influence of salt (NaCl) concentration and pH on the rheology of suspensions is also investigated. The suspensions generally exhibit shear-thinning behavior. The degree of shear-thinning is stronger in suspensions of smaller size particles. The experimental viscosity data are adequately described by a power-law model. The variations of power-law parameters (consistency index and flow behavior index) under different conditions are determined and discussed in detail.

Nowadays, the most advanced micromachined microphones on the market are based on a capacitive coupling principle. Capacitive micro-electro-mechanical systems-based (MEMS) microphones resemble their millimetric counterparts, both in function and in performances. The most advanced MEMS microphones reached a competitive level compared to commonly used measuring microphones in most of the key performance parameters except the acoustic overload point (AOP). In an effort to find a solution for measurement of high-level acoustic fields, microphones with piezoelectric coupling principle have been proposed. Such novel microphones exploit the piezoelectric effect of a thin layer of aluminum nitride, which is incorporated in their diaphragm structure. In these microphones fabricated with micromachining technology, no fixed electrode is necessary, in contrast to capacitive microphones. This specificity significantly simplifies both the design and the fabrication and opens the door for a new improvement of the acoustic overload point as well as harsh environmental applications. Several variations of piezoelectric structures together with an idea leading to electrically controlled sensitivity of MEMS piezoelectric microphone are discussed in the paper.

The relationship between metabolic changes occurring in the developing internodes of sugarcane and the final yield and sugar characteristics is poorly understood. This is due to the lack of integration between phenotypic and metabolic data. To address this issue, a study was conducted where sugarcane metabolism was modelled based on the measurement of cellular components in the top internodes at two stages of crop development. The study also looked at the effects of Trinexapac-ethyl (Moddus®) on growth inhibition. The metabolome was measured using GC-analysis while LC-MS/MS was used to measure proteome changes in the developing internodes. The data was then integrated with the metabolic rates. The study revealed that the duration of internode growth is independent of the growth rate and is probably controlled by the accumulation of heat units (degree days). In contrast, sucrose and lignin accumulation is sensitive to the growth rate. Sucrose accumulation only occurs once the cell wall synthesis slow down. The data suggest that sucrose accumulation is controlled a reduction in sucrose breakdown for metabolic activity and a reduction in demand for carbon for cell wall polysaccharide synthesis. This study also found that nucleotide sugar metabolism appears to be a key regulator in regulating carbon flow during internode development.

Cultural heritage is a fundamental part of the society’s identity, and its conservation is of great relevance as it transcends time and memory. To minimize its deterioration, cultural heritage has traditionally undergone diverse preservation and maintenance treatments and the attention of researchers to develop new and innovative methods for state diagnosis and protection treatments has been increasing in the recent decades. Therefore, in this study, a literature review using a bibliometric analysis and LDA methodology was conducted to systematically map scientific research outputs on cultural heritage conservation and protection. Data was retrieved from the Scopus database and the annual publications, countries, most-cited publications, authors, institutions, and keywords have been comprehensively analyzed, leading to the detection of research trends. Findings show an increasing number of studies in this field in the last decades, particularly since 2010. Italy, home to the largest number of UNESCO heritage sites, is the most prolific country. Most of the studies are related to metal, paper and stone as substrate to be protected. Significant progress has been made in understanding the deterioration processes through precise diagnosis and the development of innovative treatments for protection. In this sense, latest trends have been detected such as the use of non-invasive techniques for diagnosis and the use of nanotechnology and nature-based treatments for the conservation treatments.

The design and integration of intelligent energy management systems in hybrid Electric Vehicle (EV) charging stations, leveraging Industry 4.0 and renewable energy sources, is crucial for advancing sustainability, efficiency, and technological development. This paper introduces a pioneering hybrid EV charging station that employs hybrid power sources, combining photovoltaic panels, a battery, and a fuel cell, each operating at 240V and 14A. Utilizing wireless power transfer technology, the system comprises five integral blocks: a power source, a boost converter, a High-Frequency (HF) inverter, transfer coils, and EV batteries. The optimization process involves two key stages: i) maximum power point tracking optimization of the boost converter, ensuring maximum power generation by varying the duty cycle between 10% and 90%, and ii) the HF phase employing a class-ϕ2 inverter at 30 MHz, synchronized with the resonant frequency of wireless power transfer coils. Control is executed through a digital signal processor card utilizing zero-voltage switching for efficient operations. This design enhances sustainability in EV charging solutions by optimizing power transfer through the use of hybrid sources.

The installation of electric vehicle supply equipment (EVSE) increases demand and peak loads, potentially straining existing energy distribution infrastructure. Dispersed and inadequately planned placement of charging points (CPs) can disrupt the electrical grid, surpass contracted demand thresholds, and require infrastructure upgrades, thereby incurring unfeasible costs for Distribution System Operators (DSOs). In this context, it is necessary to recognize the role of business models in enabling effective electrification of the transportation sector. In response to these challenges, this paper introduces a novel e-mobility hub management strategy, tailored for implementation in the Brazilian context. The proposed strategy revolves around a microgrid configuration encompassing dispatchable and photovoltaic generation, a battery energy storage system (BESS), EVSE infrastructure, and local loads. Moreover, this centralized controller facilitates the implementation of dynamic pricing and demand-response mechanisms, integral to business models seeking to integrate EVSE into the distribution grid. To validate the efficacy of the proposed solution, hardware-in-the-loop (HIL) simulations of the microgrid system are conducted. These simulations, incorporating the centralized controller, serve as a tool for assessing system performance and viability before on-site equipment deployment. Finally, this paper concludes with the insights gleaned from test analysis and its discussion through a selection of the most expressive scenarios, including islanded and connected operation modes.

Causal language can be a powerful tool for media outlets to subtly influence public perception and reinforce specific narratives. Therefore, identifying these linguistic patterns can be helpful in assessing the level of bias present in media content. In this paper, we directly compare the prevalence of causal language in headlines pertaining to the coverage of the Israel-Palestine conflict and the Russia-Ukraine war. We specifically look at the BBC and AlJazeera headlines covering the assault on Gaza since October 7, 2023. We use UniCausal, a model for causal text mining, in order to automatically extract the cause and effect of each headline. Our findings reveal that BBC headlines tend to avoid directly attributing causality to Israel for the violence in Gaza, whereas Al Jazeera headlines explicitly identify Israel as the responsible party. This differential use of causal language suggests a potential bias in media reporting.

This study investigates the impact of real-time emotional feedback on the quality of teamwork conducted over videoconferencing. We developed a framework that provides real-time feedback through a virtual mirror based on facial and voice emotion recognition. In an experiment with 28 teams (84 participants), teams collaborated over Zoom to set up a virtual Mars station using custom simulation software. Participants were divided into 14 experimental teams which were shown the virtual mirror, and 14 control teams without it. Team performance was measured by the improvement in the Mars simulation output quality. Our analysis using correlation, multilevel regression, and machine learning revealed that fewer interruptions but an increasing number over time correlated with higher performance. Higher vocal arousal and happiness also enhanced performance. We confirmed that female presence in teams boosts performance. SHAP values indicated that high variability in happiness, head movement, and positive facial valence—an “emotional rollercoaster”—positively predicted team performance. The experimental group outperformed the control group, suggesting that virtual mirroring improves virtual teamwork and that interrupting each other more, while speaking less, leads to better results.

A better understanding of high temperature processes in slags contributes to facilitate knowledge based design of the solidified product. Here, a slag analogue with a nominal composition of 17 wt% LiMnO2 and 83 wt% Ca2SiO4 was synthesized encountering fairly high cooling rates. The Mn species from 1223 K to 1773 K was simulated using a thermodynamic model assuming a homogeneous melt. The micro-composition including the Mn species of the solidified slag was determined experimentally and was used as basis for molecular dynamics (MD) simulation. The MD simulation provides information on structure and viscosity at high temperatures, otherwise difficult to access. These parameters significantly influence oxidation state of redox-active elements and the solidified product. The micro-composition analyzed by electron probe micro analysis (EPMA) and synchrotron based micro-X-ray fluorescence (micro-XRF) showed that Mn-rich and Ca-Si-rich phases are separated. While the Mn-O phases did not contain noticeable Ca, the Ca2SiO4 phase had incorporated 0.6 wt% of Mn. The slag solidified into round shaped and droplet shaped grains of a Li-Mn-oxide, some Mn3O4 and Ca2SiO4. The powder X-ray diffraction (PXRD) confirmed the formation of larnite, the identity of the Li-Mn-oxide however remained inconclusive. The Mn oxidation state (OS) was identified using synchrotron based micro-X-ray absorption near edge spectroscopy (micro-XANES). The Mn-O grains, matched well with Li-Mn-oxides and a Mn OS: +3 e.g. LiMn3+O2. Small areas matching Hausmannite (Mn2+Mn23+O4) were also identified. The OS of Mn in the silicate phase could not be identified. For comparison a slowly cooled slag analogue with similar composition however higher Si content, was also subjected to micro-XANES. The slowly cooled slag formed long Mn-rich needles in a matrix of large calcium silicate crystals. The Mn-rich crystals matched well with the XANES spectrum of a Mn3+ Li-oxide like LiMn3+O2. At the rim of the needles the Mn-spectra matched well the Hausmannite (Mn2+Mn23+O4) reference. In the silicate phases Mn had a OS: +2, unambiguously. The melt structure at different temperatures of two compositions i.e. LiMn3+O2 and Ca2SiO4 was simulated using molecular dynamics (MD). They serve as model compositions assuming a heterogeneous melt. The results show significant different degrees of polymerization and viscosity. Information from MD simulations can support the identification of potentially different oxygen permeability and with that prediction of oxidation states. The bulk composition was identified by inductively coupled plasma optical emission spectrometry (ICP-OES), bulk structure by PXRD and bulk species by lab-XANES. The synchrotron micro analysis including micro-XRD were performed at the microfocus beamline I18 at the Diamond Light Source. Pure reference compounds were prepared and characterized with the same multi-modal approach.

The present study seeks to assess the Brand Equity in the network of new fashion designers in the Canary Islands. To this end, we have adapted the Brand Equity model to an online context and proposed a set of metrics for four dimensions: estimate, relevance, awareness, and differen-tiation. The multidimensional approach to online Brand Equity was employed to measure the online Brand Equity of 129 fashion designers from the Canary Islands. The study's findings re-vealed that the number of social media profiles significantly impacts brand awareness and dif-ferentiation. Moreover, the digital maturity level influences brand relevance and overall Brand Equity . Our study highlights the practical value of web data-driven metrics for measuring online Brand Equity , which can be utilised for diagnostic, evaluative, or predictive purposes. The study's outcomes have substantial implications for marketers in the fashion industry aimed at improving online Brand Equity

This study aims to evaluate how the operational procedure adopted for the pellets placement and the exposure to subsurface conditions influences the mechanical integrity of bentonite plugs used as barrier elements in the abandonment of petroleum wells. To this end, two methodologies were used to obtain the plugs: from the first methodology, the pellets were immersed in diesel or olefin, which are proposed as displacement fluids in offshore operations, and then, hydrated in deionized water; in the second methodology, representative of onshore operations, the pellets were directly hydrated in deionized water. After that, the plugs were tested by compression and adhesion tests. These mechanical tests were also carried out for test specimens obtained from plugs exposed to four formulations of synthetic formation waters. The results obtained demonstrated that the previous contact with olefin adversely affects the mechanical stability of bentonite plugs, while plugs formed from pellets immersed in diesel presented satisfactory mechanical properties. The mechanical properties of onshore plugs attested the highly successful performance of these elements, once its compressive strength was minimally impacted by exposure to formation waters and more pronounced reductions were observed only in the adhesion properties after the contact with higher salinity formation waters.

Swimming with Sharks: Can Small Investors Compete with Buffett? Pankaj Topiwala. FastVDO LLC, 3097 Cortona Dr., Melbourne, FL 32940 Abstract: Millions of small investors fare poorly in the financial markets. For them, the markets are like turbulent seas. Braving them in a mere skiff, a major storm can spell financial doom at any time. But the reality is that most investment funds also underperform the market. Against this backdrop, there are some savvy investors who have consistently beat the market, for decades! Names such Benjamin Graham, John Templeton, Peter Lynch, or Jim Simons come to mind. But no investor has beat the market as decisively or for as long as Warren Buffett, getting an annual return of nearly 20% since 1965! Is there a way that the small investor can swim with these sharks? These legendary investors developed a refined sense for valuing companies through fundamental analysis (hard work), investing in solid companies that are deep in value. The untrained small investor cannot hope to replicate their method. To enter these waters, she needs a new boat: algorithmic trading. Not the kind that trades in microseconds (high frequency trading), which is again out of her reach, but the type that trades only a few times a year (very low frequency). Using an approach developed and tested in previous papers, we go head-to-head with Buffett's famous BRK-A fund and compare performance over the 44-year period 1980-2024. Buffett's BRK-A earned 19% annual return over the 44 years. We also test a 50-year period, the historical limit for Nasdaq. By using simple algorithmic trading methods, we show that the small investor can indeed keep pace with Buffett, without the hard work. Our simple methods allow us to obtain both strong gains, and reduced drawdowns, helping us to survive the major market downturns known as Black Swan events. This win-win is good news for small investors worldwide.

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.

Lipids have not traditionally been considered likely candidates for catalyzing reactions in biological systems. However, there is significant evidence that aggregates of amphiphilic compounds are capable of catalyzing reactions in synthetic organic chemistry. Here we demonstrate the potential for the hydrophobic region of a lipid bilayer to provide an environment suitable for catalysis by means of a lipozyme, or lipid aggregate capable of speeding up a chemical reaction. By bringing organic molecules into the non-polar or hydrophobic region of a lipid bilayer, reactions can be catalyzed by collections of small, nonpolar or amphiphilic molecules. We demonstrate this concept by the ester hydrolysis of calcein-AM to produce a fluorescent product, which is a widely used assay for esterase activity in cells. The reaction was first carried out in a two phase octanol-water system with the organic phase containing the cationic amphiphiles cetyltrimethylammonium bromide (CTAB) or octadecylamine. The octanol was then replaced with DOPC added to the water in the form of vesicles, where the reaction was also found to be carried out. The reaction was monitored using quantitative fluorescence which revealed catalytic turnover numbers on a scale of 10−4s−1 for each system, which is comparable to some slow enzymes. The reaction product was characterized by 1H-NMR measurements which were consistent with ester hydrolysis. The implications of thinking about lipid aggregates as catalytic entities are discussed in the context of biochemistry, pharmacology and synthetic biology.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

Since the turn of the 21^st Century Chian has enacted a range of policies to improve its water ecosystem. Some of these measures include (but are not limited to) the creation of Seven River Conservancy Commissions to engage in river basin management and the development (combination and recombination) of series of ministries and departments to address environmental pollution and degradation. The most recent attempt to address the nations polluted waterways and lakes occurred in December 2016, when the General Office of the Chinese Central Committee and the State Council issued The Options on Full Implementation of the River Chief System (RCS) Across the Country. The intent behind Options was not only to fully implemented he river chief system but to bring the nations drinking water supply quality to no worse than category III. Based on the Options Erik Solheim, UN Under Secretary General and Executive Director of the UN Environment Programme, commented ‘I'm convinced that what I have seen in Pujiang County and Anji County will be the future of China, even the future of the world’ (cited in Xianqiang 2021, 435; emphasis added). It is to this observation that the reminder of this article will be directed.

This research investigates the challenges and opportunities associated with supply chain transparency and traceability in the renewable energy sector. Using a qualitative methodology, the study involved semi-structured interviews with key stakeholders, including industry experts, supply chain managers, regulatory officials, and NGO representatives. The findings reveal that the complexity and global span of renewable energy supply chains pose significant hurdles for ensuring transparency and traceability. Variability in the maturity of traceability systems across companies further complicates the landscape, with some companies benefiting from advanced systems while others struggle with cost and technical barriers. Technological advancements, especially blockchain, offer promising solutions but require standardization and scalability to be effective. Regulatory frameworks play a crucial role, yet inconsistencies across jurisdictions create compliance challenges, underscoring the need for harmonized standards. Collaboration and partnerships are essential, providing platforms for sharing best practices and developing common standards. Enhanced transparency can lead to operational efficiencies, improved consumer trust, and stronger market positioning. Integrating sustainability into supply chain practices is fundamental, aligning with the increasing emphasis on ESG criteria among investors and stakeholders. Education and capacity-building, particularly for suppliers in developing countries, are vital for promoting transparency. Leadership and corporate culture are critical in driving these efforts, with strong commitment from the top necessary to implement effective practices. This study contributes valuable insights for stakeholders in the renewable energy sector, offering a foundation for future research and policy development aimed at advancing sustainable and ethical supply chain practices. The findings highlight the need for a holistic approach that integrates transparency and traceability into broader sustainability and business strategies.

Wound healing is a complex, dynamic process involving the coordinated interaction of diverse cell types, growth factors, cytokines, and extracellular matrix components. Despite emerging evidence highlighting their importance, dermal sheath cells remain a largely overlooked aspect of wound healing research. This review explores the multifunctional roles of dermal sheath cells in various phases of wound healing, including modulating inflammation, aiding in proliferation, and contributing to extracellular matrix remodeling. Special attention is devoted to the paracrine effects of dermal sheath cells and their role in fibrosis, highlighting their potential in improving healing outcomes, especially in differentiating between hairy and non-hairy skin sites. By drawing connections between dermal sheath cells activity and wound healing outcomes, this work proposes new insights into the mechanisms of tissue regeneration and repair, marking a step forward in our understanding of wound healing processes.

Objective: Meningococcal meningitis (MM) is an acute, severe respiratory infectious disease caused by Neisseria meningitidis and remains an important cause of morbidity/mortality in children. Immunization with meningococcal vaccine (MV) is the most effective measure to control and prevent the transmission of MM. In this study, in order to support the appropriate use of various MVs in the prevention of MM, the effects of MVs, especially single-dose and inter-booster administered, on inflammatory parameters in

Climate change and over-exploitation are imposing unprecedented threats to the groundwater resource. Globally, groundwater reserves have depleted to the extent that well yield have decreased, pumping cost have risen, and land have irreversibly subsided. In Malawi, groundwater quantity is a national problem, specifically in Mzimba district due to severe droughts. In this study, the spatial and temporal trends of groundwater depletion was assessed using Gravity Recovery and Climate Experiment (GRACE) data and Land Surface Models (LSM) from Global Land Data Assimilation System (GLDAS) and Global Surface Water Explorer (GSWE). The results show that 1. Groundwater storage is depleting at an average rate of-1.0 ± 0.06 cm yr-1(0.1043 km3yr-1) in the study area with high rate of up to -1.2 cm yr-1(0.12516 km3 yr-1) in the western side and as low as –0.4 cm yr-1(0.04172 km3 yr-1) in the eastern part. 2. Groundwater storage increases from -13 cm in November up to 15 cm between May and April. 3. Drought is the primary cause of such depletion trends with correlation between active evapotranspiration and groundwater depletion, and downward surface shortwave radiation and groundwater depletion, at -0.577 and -0.678 respectively. The results from the study reveals the need for the scientific community and the general public to consider groundwater recharge strategies specifically by mitigating climate change to reduce prolonged droughts. The study suggests the need to establish a stand-alone groundwater assessment and monitoring authority for enhanced conservation efforts of the water resource in the country.