The coastal zone, situated at the sensitive interface between land and sea, serves as a pivotal area of extensive human economic activities. As one of China's economic special zones, Xiamen exemplifies the comprehensive trajectory of coastal governance in China. This research adopts an interdisciplinary approach grounded in historical geography and political ecology, employing data collection methods encompassing historical literature, field surveys, and interviews. The research findings indicate that:(1) The year 1994 witnessed the pivotal role played by the United Nations Convention on the Law of the Sea (UNCLOS) in connecting Jimei Peninsula from a local context to the international arena, thus signifying a momentous turning point in the process of scale reconstruction. However, the subsequent implementation of the Coastal Exclusion Policy in 2002 had detrimental consequences, leading to the disintegration of the local scale, the erosion of maritime culture, and the disregard for the livelihood security of displaced coastal populations.(2)The Coastal Exclusion Policy serves as an instrumental tool for implementing scale politics, while its functional realignment has had profound implications for the coastal zone, encompassing economic transformation, ecological degradation, and the marginalization of the socio-cultural fabric that intertwines humans and the coastal environment.

The Principle of Indifference (“PI”: the simplest non-informative prior in Bayesian probability) has been shown to lead to paradoxes since Bertrand (1889). Von Mises (1928) introduced the “Wine/Water Paradox” as a resonant example of a “Bertrand paradox”, and which has been presented as demonstrating that the PI must be rejected. We now resolve these paradoxes by a Maximum Entropy (MaxEnt) treatment of the PI that also includes information provided by Benford’s “Law of Anomalous Numbers” (1938). We show that the PI should be understood to represent a family of informationally-identical MaxEnt solutions; each solution being identified with its own explicitly justified boundary condition. In particular, our solution of the Wine/Water Paradox exploits Benford’s Law to construct a non-uniform distribution representing the universal constraint of scale invariance, which is a physical consequence of the Second Law of Thermodynamics.

Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Since it is difficult to obtain multiple spatial resolution remote sensing images of the same area at the same time, the main current method to study the scale effect of land cover classification is to use the same image resampled to different resolutions, however errors in the resampling process lead to uncertainty in the accuracy of land cover classification. To study the land cover classification scale effect of different spatial resolutions of multi-source remote sensing data, we selected 1 m and 4 m of GF-2, 6 m of SPOT-6, 10 m of Sentinel-2 and 30 m of Landsat-8 multi-sensor data, and explored the scale effect of image spatial resolution on land cover classification from two aspects of mixed image element decomposition and spatial heterogeneity. For the study area, we compared the classification obtained from GF-2, SPOT-6, Sentinel-2, and Landsat-8 images at different spatial resolutions based on GBDT and RF. The results show that (1) GF-2 and SPOT-6 had the best classification results, and the optimal scale based on this classification accuracy was 4–6 m; (2) the optimal scale based on linear decomposition depended on the study area; (3) the optimal scale of land cover was related to spatial heterogeneity, i.e., the more fragmented and complex was the space, the smaller the scale needed; and (4) the resampled images were not sensitive to scale and increase the uncertainty of the classification. These findings have implications for land cover classification and optimal scale selection, scale effects and landscape ecology uncertainty studies.

BACKGROUND. The aims of this study was to compare differences in daytime sleepiness between genders and qualification levels in a cohort university Chinese soccer player under 0 Covid policy restrictions in the urban area of Shanghai. METHODS. 491 questionnaires of Epworth Sleepiness Scales (ESS) were compiled online by males and females Soccer Students (SS), Semi-professional players (SP) and professional players (PP) during the ongoing measures of Shanghai lockdown. ANOVA was performed for players levels and gender. RESULTS. Significant differences were found between the 3 levels and between males and females. PP showed a very low score in the ESS (5,97) well below the threshold of 8, while SS and SP showed an ESS score above the threshold. Female showed higher scores than males. CONCLUSIONS. This study present the first data on sleepiness in Chinese soccer players of different level of qualification in a lockdown condition. Professional players has been less affected by lockdown measures than SS and SP. We can hypothesize the reasons resides in the more ordered lifestyle of PP in comparison to SS and SP, which mitigated the effects of the lockdown. Measures to improve sleep in females’ soccer player should be adopted.

Mass transfer is often the rate determining step for solid-liquid chemical reactions. Decrease of the concentration boundary layer thickness is essential to intensify the chemical reaction. Because the concentration boundary layer exists in the velocity boundary layer, force imposition in the concentration boundary layer by superimposing an electrical current and a magnetic field was proposed. Through, flow can be directly excited in the concentration boundary layer. The previous result indicates that by superimposing a DC current and a gradient magnetic field, the development of the concentration boundary layer was suppressed, because of a macro-scale flow excitation in the whole vessel. And by superimposing the gradient magnetic field with a modulate current, the development of the concentration boundary layer was further suppressed. This is because of the macro-scale flow enhancement and the excitation of a micro-scale flow near the solid-liquid interface. However, the mechanism for the micro-scale flow excitation has not been clarified. To clarify this, a uniform magnetic field was superimposed with the DC current or the modulate current. By this means, only the micro-scale flow was excited near the anode surface. The results found that the non-unform electromagnetic force distribution is the main reason for the micro-scale flow excitation.

The level of technological development of any civilization can be gaged in large part by the amount of energy they produce for their use, but also encompasses that civilization’s stewardship of their home world. Following the Kardashev definition, a Type I civilization is able to store and use all the energy available on its planet. In this study, we develop a model based on Carl Sagan’s K formula and use this model to analyze the consumption and energy supply of the three most important energy sources: fossil fuels (e.g., coal, oil, natural gas, crude, NGL and feedstocks), nuclear energy and renewable energy. We also consider environmental limitations suggested by United Nations Framework Convention on Climate Change, the International Energy Agency, and those specific to our calculations to predict when humanity will reach the level of a Kardashev scale Type I civilization.

Carton detection is an important technique in the automatic logistics system and can be applied to many applications such as the stacking and unstacking of cartons, the unloading of cartons in the containers. However, there is no public large-scale carton dataset for the research community to train and evaluate the carton detection models up to now, which hinders the development of carton detection. In this paper, we present a large-scale carton dataset named Stacked Carton Dataset (SCD) with the goal of advancing the state-of-the-art in carton detection. Images are collected from the Internet and several warehouses, and objects are labeled using per-instance segmentation for precise localization. There are total of 250,000 instance masks from 16,136 images. Naturelly, a suite of benchmarks are established with several popular detectors. In addition, we design a carton detector based on RetinaNet by embedding our proposed Offset Prediction between Classification and Localization module (OPCL) and Boundary Guided Supervision module (BGS). OPCL alleviates the imbalance problem between classification and localization quality which boosts AP by 3.1%∼4.7% on SCD at the model level while BGS guides the detector to pay more attention to boundary information of cartons and decouple repeated carton textures at the task level. To demonstrate the generalization of OPCL to other datasets, we conduct extensive experiments on MS COCO and PASCAL VOC. The improvements of AP on MS COCO and PASCAL VOC are 1.8%∼2.2% and 3.4%∼4.3% respectively. Source dataset is available here.

Scale inhibitors are deployed as preventive and rejuvenation operation in oil and gas industry when production operations are under threat or menace of scale blockage. The application of scale inhibitors is carried out through a method known as squeezing. In general, the squeeze process is governed by inhibitor-rock interaction which is described by adsorption/desorption isotherm. Most reservoirs produce loose sand grains or fine sand which float and flow within the pore spaces along with the squeezed scale inhibitors. Hypothetical reports have shown that not all scale inhibitors pumped into the formation adsorb onto the formation rock. A number of factors (irreversible adsorption, pH changes, competing ions, concentration and temperature) have been considered to affect the adsorption and return profile of these scale inhibitors. This review work examines the performances of most common scale inhibitors used in the oil and gas production activities, theoretical application in reservoirs and how loose fine sand grains affect the adsorption and desorption characteristics of squeezed scale inhibitors. Additionally, presented were overviews of previous reports on fine sand production and migration of fine sands through formation pores in reservoirs.

The Mouse Grimace Scale (MGS) was developed 10 years ago to assess pain through characterisation of changes in five facial features or action units. The strength of the technique is that it is proposed to be a measure of spontaneous or non-evoked pain. A comprehensive scoping review of the academic literature was performed. The MGS has been employed mainly in evaluation of acute pain, particularly in the pain and neuroscience research fields. There has however been use of the technique in a wide range of fields, and based on limited study it does appear to have utility for pain assessment across a spectrum of animal models. Use of the method does allow detection of pain of a longer duration, up to a month post-initial insult. There has been less use of the technique using real-time methods and this is an area in need of further research.

Small-scale fishers are considered as one of the most vulnerable communities in Bangladesh but very few studies focused on the livelihood sustainability and vulnerabilities of this professional group. A fieldwork in lower Padma and upper Meghna hilsa sanctuaries identifies different livelihood characters and associated vulnerabilities of the fishers. A conceptual framework known as Sustainable Livelihood Approaches (SLA) has been introduced to analyses the qualitative and quantitative data. The insights of the livelihood strategies provide on small-scale fishers and fisheries management have been explained and explored. Fishers are found solely dependent on fishing, economically insolvent and neglected. In addition, some socio-economic abstractions such as low income, credit insolvency, lack of substitute earning flexibility make them more vulnerable. A number of effective suggestions are elicited from fishers’ perceptions, the implementation of which is crucial to ensure livelihood sustainability of the small-scale fishers.

Friction is an important subject for sustainability due to problems associated with energy loss. Recent years, surface micro- and nanostructures have attracted much attention to reduce friction; however, suitable structures are still under consideration. Many functional surfaces are present in nature, such as the friction reduction surfaces of snake skins. In this study, we focused on firebrats, Thermobia domestica, living in narrow spaces such as under bark, so their surface frequently contacts with surrounding surfaces. We speculate that their body surface would be adapted to reduce friction. To investigate the firebrat surface functions, firebrat surfaces were observed by using a field-emission scanning electron microscope (FE-SEM) and a colloidal probe atomic force microscope (AFM), respectively. Results of surface observations by the FE-SEM revealed that firebrats are entirely covered with scales, whose surfaces have micro groove structures. Scale groove periods around the firebrat's head are almost uniform within a scale but vary between scales. AFM friction force measurements revealed that firebrat scale reduces friction by decreasing contact area between scales and a colloidal probe. The heterogeneity of groove periods of the scales suggest that it is difficult to fix the whole body in particular rough surfaces and that lead to be "fail-safe".

Size-based fungal growth studies have limitations. For example, the growth in size stops in closed systems once it reaches the borders and poorly describes the metabolic status, especially in the stationary phase. This might lead mycotoxin studies to unrealistic results. Color change could be a viable alternative as pigments are results of the mold’s metabolic activity. This study aimed to verify the possibility of using gray values and the RGB system to analyze the growth of Fusarium graminearum. It consisted color and area measurement using the ImageJ software for specimens grown in yeast extract agar (YEA). The results suggest the usability of color and gray values as reliable tools to analyze the growth of F. graminearum.

A growing number of clinical data suggests that the use of antiplatelets and/or statins pre-stroke are associated with reduced severity and better functional outcomes for ischemic stroke. Studies have shown that the long-term use of ACEI/ARB pre-stroke is beneficial in reducing severity at onset and improving functional outcomes. We aimed to compare stroke severity and early functional outcome between patients taking ACEI/ARB and those who were not, and to identify any additional effects to taking ACEI/ARB with antiplatelets, statins, or both. In this retrospective case-control study, we assessed 218 patients who presented with ischemic stroke to the stroke unit in Padeh-Poriyah Hospital between 2019-2020. Of these patients, 119 took ACEI/ARB pre-stroke. A significantly higher percentage of ACEI/ARB-treated patients had a history of hypertension (HTN) and hyperlipidemia and were taking antiplatelets and/or statins, compared to the non-ACEI/ARB group. We observed that pre-stroke treatment with ACEI/ARB is associated with worsened stroke severity and reduced early functional outcomes. No significant benefit to taking ACEI/ARB with antiplatelets and/or statins pre-stroke was observed. Due to the nature of our study, the data should be interpreted as suggestive. Thus, prospective studies of these medications on ischemic stroke severity and early outcomes are warranted.

In this paper, we present a full coverage path planning (CPP) algorithm for the marine surveys conducted in the convex polygon shaped search area. The survey is supposed to carry out by torpedo-type AUVs (autonomous underwater vehicles). Due to their nonholonomic mechanical characteristics, these vehicles have nonzero minimum turning radius. For any given polygon shaped search area, it can always be partitioned into one or more convex polygons. With this in mind, this paper proposes a novel search algorithm called CbSPSA (Calculation based Shortest Path Search Algorithm) for full coverage of any given convex polygon shaped search area. By aligning the search inter-tracks alongside the edge with the minimum height, we can guarantee the minimum number of the vehicle’s turns. In addition, the proposed method can guarantee the planned path is strictly located inside the polygon area without overlapped or crossed path lines, and also has the total path length as short as possible. Considering the vehicle’s nonzero minimum turning radius, we also propose a sort of smoothing algorithm to smooth the waypoint path searched by CbSPSA so as for the vehicle to exactly follow it. The smoothed path is also guaranteed to be strictly located inside the polygon. Numerical simulation analyses are also carried out to verify the effectiveness of the proposed schemes.

China's implementation of public-private partnerships projects has been quite effective, involving infrastructure and other livelihood projects, a total of 19 industries, and an investment of nearly 1.5 trillion yuan. The characteristics of PPP projects such as long construction period and large investment amount determine the risks of PPP projects are also great, and the PPP projects of comprehensive environmental governance are also the same. The government and social capital use the PPP model to cooperate, and use the principal component analysis method to assess the risks of the entire life cycle of the comprehensive environmental governance PPP project. Therefore, it plays an important role in ensuring the smooth implementation of projects and reducing the losses caused by risks. According to the risk factors of the whole life cycle of the comprehensive environmental governance PPP project, an indicator system of 5 first-level indicators, 18 second-level indicators, and 43 third-level indicators has been established. Principal component analysis is used to analyze the influence weight of risk factors at each stage. The analysis shows that among the four stages, environmental pollution risk, project approval delay risk, completion risk, interest rate and financial fluctuation risk, and franchise life risk are the most influential risks in the implementation of PPP projects. Therefore, suggestions are made through the risk factors of each stage in the comprehensive environmental governance PPP project. For example, strengthen the response to the external environment risks of the comprehensive environmental governance PPP project, standardize the bidding and procurement of the comprehensive environmental governance PPP project, and strengthen the subsequent management of the transfer of the comprehensive environmental governance PPP project. In this way, the ability to resist risks of comprehensive environmental governance PPP projects is improved; the smooth implementation of the project is guaranteed, and the long-term development of comprehensive environmental governance PPP projects is promoted.

Rotavirus species H (RVH) has been detected in pigs, humans and bats. Moreover, porcine RVHs have been recently identified in several swine-producing countries. Despite their zoonotic impact, genome information of RVHs is still limited. This study aimed to establish a tentative complete genome-based genotyping system for RVHs, by appending genomic sequences from 12 porcine RVHs identified in Japan between 2013 and 2015 to those from human and other porcine RVHs reported in previous studies. Phylogenetic analysis of 11 RNA segments indicated that porcine RVHs could be classified into multiple genotypes. Consequently, the genotype classification for RVHs revealed the existence of genotypes 10G, 6P, 6I, 3R, 4C, 7M, 6A, 2N, 4T, 6E, 3H for the genes VP7, VP4, VP6, VP1, VP2, VP3, NSP1, NSP2, NSP3, NSP4 and NSP5, respectively. Surprisingly, two distinctive types in NSP1 and NSP3 genes were identified from among the twelve porcine RVHs. Our data suggest a potentially novel gene rearrangement event between porcine RVH and rotavirus species C in the NSP3 gene. These findings would provide a new insight in understanding for evolution of RV.

Although the spanwise periodicity within the gap between two tandem circular cylinders has been observed by some researchers, there is a lack of systematic study on the properties of this pe-riodicity. For the spanwise periodicity within the gap, this study aims to ascertain its characteris-tics, its influences on the flow field, and its variation trend with increasing spacing ratio. By nu-merically simulating the flow around two tandem circular cylinders with a diameter ratio of d/D=0.6 and seventeen spacing ratios (L/D=1.00~6.00) at Re=3900, this study shows four flow re-gimes: Reattachment Flow (L/D=1.00~3.15), Bi-stable Flow (L/D=3.24), Intermittent Lock-in Co-shedding (L/D= 3.30~3.50) and Subharmonic Lock-in Co-shedding (L/D=4.00~6.00). Further, de-pending on the spanwise periodicity length of the time-averaged flow structures (i.e. Pz) within the gap, Reattachment Flow is, for the first time, subdivided into three new sub-flow regimes: Small-scale Periodic Reattachment (L/D=1.00~1.50, Pz/D=(0, 4]), Large-scale Periodic Reattachment (L/D=2.00~2.25, Pz/D>4) and Non-periodic Reattachment (L/D=2.50~3.15, no spanwise periodicity). The formation mechanisms are elaborated by analyzing the combined effect of both the L/D value and the spanwise-averaged time-averaged reattachment angle of the downstream cylinder. Moreover, this study proves that the newly-defined Small-scale Periodic Reattachment and Large-scale Periodic Reattachment are responsible for the pronounced asymmetry of the flow along the transverse direction within the gap. In addition, detailed flow properties and statistical pa-rameters are provided for each flow regime, such as velocity, vorticity, force coefficient, separa-tion/reattachment angle, Strouhal number and Q-criterion.

A little-known thermomechanical relation between entropy and action, originally discovered by Boltzmann in the classical domain, was later reconsidered by de Broglie in relation to the wave-particle duality in the free propagation of single particles. In this paper we present a version adapted to the phenomenological description of the hadronization process. The substantial difference with respect to the original de Broglie scheme is represented by the universality of the temperature at which the process occurs; this in fact coincides with the Hagedorn temperature. The main results are: 1) a clear connection between the universality of the temperature and the existence of a confinement radius of the color forces; 2) a lower bound on the hadronic mass, represented by the universal temperature, in agreement with experimental data; 3) a scale invariance which allows the reproduction of the well-known hadronic mass spectrum solution of the statistical bootstrap model. The approach therefore presents a heuristic interest connected to the study of the strong interaction.

In this paper we introduce the Adomian decomposition method for a class of first order fuzzy dynamic equations on arbitrary time scales for existence of solutions. The results are provided with suitable numerical examples.

This paper presents an enhanced Fully Connected Neural Network (FCNN) framework that incorporates manifold learning and Renormalization Group (RG) methods. By integrating Christoffel symbols, the model adapts to the curvature and topology of the data manifold, improving learning from geometrically complex data. Additionally, RG methods enable effective multi-scale data processing. We demonstrate the enhanced model’s performance on synthetic and real-world datasets, showing improved accuracy compared to standard FCNNs, particularly in complex systems simulation.

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

Metabolites are at the end of the gene-transcript-protein-metabolism cascade. As such, metabo-lomics is the omic approach that offers the most direct correlation with phenotype. This allows that, where genomics, transcriptomics and proteomics fail to explain a trait, metabolomics might give an answer. Complex phenotypes, which are determined by the influence of multiple small effect alleles, are an example of these situations. Consequently, the interest in metabolomics has increased ex-ponentially in the last years. As a newer discipline, the metabolomics bioinformatics analysis pipe-lines are not as standardized as in the other omic approaches. In this review we synthesized the different steps that need to be carried out to obtain biological insight from the annotated metabolite abundance raw data. These steps were grouped in three different modules: preprocessing, statistical analyses and metabolic pathway enrichment. We included within each one of them the different state-of-the art procedures and tools that can be used depending on the characteristics of the study, providing details about the characteristics of each method has, as well as the issues the reader might encounter. Finally, we introduce genome scale metabolic modeling as a tool for obtaining pseu-do-metabolomic data in situations where its acquisition is difficult, being possible to analyze the resulting data with the modules of the described workflow.

Vulnerabilities in smart contracts may trigger serious security events, and the detection of smart contract vulnerabilities has become a significant problem. In this paper, by using the multi-scale cascade encoder architecture as the backbone, we propose a novel Multi-scale Encoder Vulnerability Detection (MEVD) approach to detect well-known high-risk vulnerabilities in smart contracts. Firstly, we use the gating mechanism to design a unique Surface Feature Encoder (SFE) to enrich the semantic information of code features. Then, by combining a Base Transformer Encoder (BTE) and a Detail CNN Encoder (DCE), we introduce a dual-branch encoder to capture the global structure and local detail features of the smart contract code, respectively. Finally, to focus the model's attention on vulnerability-related characteristics, we employ the Deep Residual Shrinkage Network (DRSN). Experimental results on three types of high-risk vulnerability datasets demonstrate performance compared to state-of-the-art methods, and our method achieves an average detection accuracy of 90%.

This paper deals with the analysis of the cognitive functions of the cerebral cortex or cortex in the evolutionary context. The triune brain model is presented given its notorious popularity in fields that are not strictly neuroscientific, and its limitations and inaccuracies are also shown. Although it is an outdated theory, this one represented the passage to a new era, because it really was the model of the movement towards understanding the brain in evolutionary terms. Next, the paper illustrates the different areas of the cortex and their functions, as well as the evolution of the brain and the cortex in vertebrates. To date, the expansion of the cortex with the amniotes was placed 300 million years ago, although recent studies place it in the lampreys more than 500 million years ago. Evolutionary changes in mammalian brain and cortex size are discussed, showing the evolution from three to six cell layers and trends in different groups of mammals. Finally, the most recent contributions in the field of research are illustrated, such as the role of neurogenesis and the evolution of the connectivity of the cortex.

Background: Patients with allergic rhinitis (AR) have bothersome symptoms that may assess using the visual analog scale (VAS). Asthma frequently is associated with AR. The present study investigated the role of VAS in children with newly-diagnosed AR. Methods: Parameters were VAS for nasal and asthma symptoms, and doctor’s perception of these diseases, medication use, and asthma comorbidity. Results: 67% of AR children had asthma. Severity of perceived nasal symptoms was associated with more intense asthma symptoms and doctor’s perception of disease severity (p<0.001 and p=0.02, re-spectively. Conclusions: Allergic rhinitis frequently is associated with asthma in child-hood. Symptom perception assessment using VAS is a simple tool for assessing their intensity. Moreover, the severity of nasal symptoms is associated with asthma symptom severity. Therefore, asthma should be carefully considered in AR children and require appropriate symptom perception assessment.

We carry out in a thin heterogeneous porous layer, the multiscale analysis of Smoluchowski's discrete diffusion-coagulation equations describing the evolution density of diffusing particles that are subject to coagulate in pairs. Assuming that the thin heterogeneous layer is made of microstructures that are uniformly distributed inside, we obtain in the limit an upscaled model in lower space dimension. We also prove a corrector-type result very useful in numerical computations. In view of the thin structure of the domain, we appeal to a concept of two-scale convergence adapted to thin heterogeneous media to achieve our goal.

Interspecific competition between herbivorous insects is a major selection pressure affecting the distribution, abundance, and structure of their populations. Facilitator-mediated interactions, such as mutualism, can influence competition. Furthermore, the temporal dynamics of competitive relationships affect the interaction’s outcome. Here, we re-evaluated the data on the competition for space between two herbivorous insects commonly known as scales (Toumeyella martinezae and Opuntiaspis philococcus) in either the presence or absence of Liometopum apiculatum (a mutualistic species of T. martinezae) and its variations over time. We selected 27 Myrtillocactus geometrizans plants on which the studied insects were present; the plants were classified into one of five different conditions: either of the scale species were present on the plant, without its competitor; T. martinezae with neither its mutualistic species nor the competitor; and both scale species competing in either presence or absence of the mutualistic species. We kept a photographic record of each condition, measured the size of (as an indicator of the development stage) and area occupied by the individual scales, estimated the total coverage of each scale species, and assessed their relative occupation of space and their competitive intensity. We found temporal variations in competitive intensity. T. martinezae occupied more space during the first months, whereas O. philococcus did so towards the end of the study period. The population structure changed over time and between species, affecting the competitive interactions. In conclusion, the dynamics of competition change over time, and the mutualistic species has a positive effect on T. martinezae when the scales are in competition. However, temporal variations resulting from changes in the life cycle of the scales allow the two competitors to coexist in the same place at the same time.

Background: The adoption of self-care behaviors among patients with arterial hypertension (AH) plays an important role in the management of their health condition. However, a lack of scales assessing self-care is observed. We aimed to develop and validate the Hippocratic hypertension self-care scale. Methods: From a pool of questions derived from a literature review, 18 items were included in the scale and reviewed by a committee of experts. Participants indicate the frequency at which they follow the self-behavior prescribed in each statement on a five-point Likert scale. Data were collected between April 2019 and December 2019. Re-sults: 202 consecutive adult patients with AH were enrolled in the study. The internal consistency of the scale was found to be 0.807, using Cronbach’s alpha coefficient. An exploratory factor analysis identified two do-mains that accounted for 92.94% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test- retest of the scale showed a significant strong correlation (r=0.0095, p<0.001). Conclusion: Our data indicate that the scale is a reliable and valid tool for assessing self-behaviors in patients with AH. Health professionals can use it in their clinical practice to improve the management of patients’ health condition.

Introduction: Lack of certainty or knowledge in health professions generates uncertainty, affecting clinical practice in decision-making (diagnostic or therapeutic), intervention design and therapeutic communication. In nursing, the lack of information to predict prognosis and outcome of interventions generates uncertainty: recognizing and managing it is essential for individualized, safe, and effective care. Objective: to assess uncertainty and the perception of a debriefing within the same shift ("intrathoracic pass") as a proposal for improvement. Method: ad-hoc survey of nursing professionals and Auxiliary Nursing Care Technicians (ANC). Variables: age, work experience, PRU scale (Physisicians' Reactions to Uncertainty) and additional question on intrathoracic pass. Results: Sample: 61 nurses and 10 TCAE (90.14 % female, 9.86 % male; mean age 35.18, standard deviation SD=13.04). Mean professional experience 11.74 years (SD=12.21); 56.33% had ≤4 years of experience. Origin: 49.30% Intensive Care Units (ICU), 11.27% Hospitalization, 7.04% Emergency, 1.41% Primary Care and 30.99% Other Services. The mean level of uncertainty was 27.99 points (max. possible 75; SD=7.50), with stress (mean=25.55, max. possible: 40; SD=5.24) and anxiety (mean=15.80, max. possible: 25; SD=3.05) as major manifestations. The association uncertainty-age (r=0.339; p=0.004) and uncertainty-experience (r=0.391; p=0.001) correlated negatively (the older and more experienced, the less uncertainty), with no significant differences between degrees or services. 91.55% stated that the intra-day pass was useful to reduce uncertainty during the working day. Conclusion: Uncertainty is frequent in nursing, and implementing the intrashift pass is perceived as a competent strategy.

AbstractPurpose: This study aimed to perform a psychometric evaluation of the preliminary preterm birth risk assessment scale (PBRAS-K) of 32-item. Method(s): There were 299 subjects, 167 in the exploratory factor analysis (EFA) group and 132 in the confirmatory factor analysis (CFA) group, who delivered before 37⁺⁰ weeks after having preterm symptoms and were admitted to high-risk pregnancy maternal-fetal intensive care units (MFICU). After an item reduction process in EFA, the psychometric property scales were assessed using SPSS 26, and CFA was accomplished using AMOS 27. Results: The Kaiser-Meyer-Olkin measure (KMO) and Bartlett’s χ² test of sphericity confirmed the adequacy of the sample for factor analysis (KMO = .81 (> .80), χ² = 1841.38, p < .001). The final version of the PBRAS-K was comprised of 23 items within seven dimensions. Factor analysis identified items explaining 65.9% of the total variance. The PBRAS-K had a mean score of 35.58 (±10.35) and showed a high internal consistency and satisfactory reliability with a Cronbach’s alpha of .85. The PBRAS-K had a low correlation with risk scoring of preterm delivery (RPD) for discriminant validity (r = .45, p < .001), a positive, high correlation with the Somatic Awareness Scale with Spontaneous Preterm Labor (SPL-SAS) for criterion validity (r = .65, p < .001), and with pregnant stress for convergent validity (r = .57, p < .001). RPD and SPL-SAS were moderately correlated (r = .53, p < .001). Conclusion(s): The PBRAS-23-K is a valid and reliable instrument for assessing pregnant women’s risk of preterm birth. Clinical nurses are encouraged to apply and obtain information for effective interventions in MFICU. This scale has meaningful results and reflects the voices of women who had a preterm birth. The scale should be evaluated for standardization and cut-off scores using larger subject sizes in the future.

The paper shows an analysis of the large-scale distribution of galaxy spin directions of 739,286 galaxies imaged by DES. The distribution of the spin directions of the galaxies exhibits a large-scale dipole axis. Comparison of the location of the dipole axis to a similar analysis with data from SDSS, Pan-STARRS, and DESI Legacy Survey shows that all sky surveys exhibit dipole axes well within 1$\sigma$ error from each other. While non-random distribution is unexpected, the findings are consistent across all sky surveys, regardless of the telescope or whether the data were annotated manually or automatically. Possible errors that can lead to the observation are discussed. The paper also discusses previous studies showing opposite conclusions, and analyzes the decisions that led to these results. Although the observation is provocative, and further research will be required, the existing evidence justifies to consider the contention that galaxy spin directions as observed from Earth are not necessarily randomly distributed. Possible explanations can be related to mature cosmological theories, but also to the internal structure of galaxies.

The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always a subjective, intangible, and often hard to quantify with precision due to the lack of quantitative models dealing with. The main goal of the present paper is thus to propose a mathematical, quantitative model for the measurement of a quality of life index. The main novelty is firstly the construction of a wavelet dynamic multiscale model to quantify and investigate the effect of time scale on the quality of life index measuring. The proposed procedure is acted empirically on a sample corresponding to Saudi Arabia as a case of study during the period from 2003 to 2020 as part of the 2030-vision plan. Saudi Arabia has implemented the so-called 2030-vision plan where the quality of life improvement is one of the main goals to be attempted. The findings show that wavelets are capable to localize the time-wise behavior of the index contrarily to classical studies which estimate a global view of the index. Moreover, the study shows the link between the quality of life behavior and many other indices.

A robust hydrological assessment is challenging in regions where human interference, within all aspects of the hydrological system, significantly alters the flow regime of rivers. The challenge was to extend a large-scale water resources model, GWAVA, to better represent water resources without increasing the model complexity. A groundwater and a regulated reservoir routine were incorporated into GWAVA using modifications of the existing AMBHAS-1D and Hanasaki methodologies, respectively. The groundwater routine can be varied in complexity when sufficient input data is available but fundamentally is driven by three input parameters. The reservoir routine was extended to account for the presence of large, regulated reservoirs using two calibratable parameters. The additional groundwater processes and reservoir regulation was tested in two highly anthropogenically influenced basins in India: the Cauvery and Narmada. The inclusion of the revised groundwater routine improved the simulation of streamflow in the headwater catchments and was successful in improving the representation of the baseflow component. In addition, the model was able to produce a time series of daily groundwater levels, recharge to groundwater and groundwater abstraction. The regulated reservoir routine improved the simulation of streamflow in catchments downstream of major reservoirs, where the streamflow was largely reflective of reservoir releases, when calibrated using downstream observed streamflow records. The model was able to provide a more robust representation of the annual volume and daily outflow released from the major reservoirs and simulate the major reservoir storages adequately. The addition of one-dimensional groundwater processes and a regulated reservoir routine proved successful in improving the model performance and traceability of water balance components, without excessively increasing the model complexity and input data requirements.

An accurate understanding of jointed rock mass behavior is important in many applications ranging from deep geological disposal of nuclear waste to deep mining to urban geoengineering projects. The roughness of rock fractures and the matching of the fracture surfaces are the key contributors to the shear strength of rock fractures. In this research, push shear tests with three normal stress levels of 3.6, 6.0, and 8.5 kPa were conducted with two granite samples with artificially induced well-matching tensile fractures with sizes of 500 mm × 250 mm and 1000 mm × 500 mm. The large sample reached on average a -60 % weaker peak shear stress than the medium-sized sample, and a strong negative scale effect was observed in the peak shear strength. The roughness of the surfaces was measured using a profilometer and photogrammetry. The scale-corrected profilometer-based method (JRC) underestimates the peak friction angle for the medium-sized slabs by -27 % for the medium sample and -9 % for the large sample. The photogrammetry-based (Z’2) method produces an estimate with -7% (medium) and +12 % (large) errors. The photogrammetry-based Z’2 is an objective method that consistently produces usable estimates for the JRC and peak friction angle.

Shrinking farm size and fragile farm resources pose a significant challenge to the sustainability of small-scale farms. Efficient resource utilization in small-scale farms is crucial to achieving farm sustainability through endogenous mechanisms. However, the precise mechanisms to integrate physical resources to achieve farm sustainability are not very clear yet. By capturing the interaction among farm resources as a network phenomenon, we identify the discrete resource interactions (RIs) in different types of small-scale farms of Indian Sundarbans, which are associated with higher farm sustainability. Thirty-two linkages, 11 reciprocal linkages, 22 triads, and three ‘core elements’ that occurred and cooccurred on highly sustainable farms are found to be critical in achieving farm sustainability. Using the properties of resource interaction networks as explanators of farm sustainability, we anticipate that sustainability in small-scale farms can be achieved by strategically creating new RIs on the farm. However, there may be limitations to such achievement depending on the nature of RI and type of farm. The analytical approach helps to understand the structural basis of sustainability in small-scale farms, and this approach can be used to achieve farm sustainability through the strategic integration of existing farm resources in the smallholder systems.

Perovskite based solar cells have achieved tremendous progress reaching record efficiency in the past 5 years. Numerous new processes and chemistry have been reported and contribute to the perovskite rapid progress. Continuous efficiency improvements are still necessary for perovskite solar cells, and an exploratory data analysis on devices performance over multiple studies could boost the technology development. Such analysis could identify patterns or provide insights that are not obvious in a single study. Here we present a high quality dataset containing only independently certified Pb-based perovskite solar cells summarizing their efficiency, relevant I-V metrics, manufacturing processes and materials used. Analysis over the dataset provides insights on how aperture size, perovskite deposition methods and materials used in each functional layer affect the final solar cell efficiency and I-V metrics. Future directions are also suggested for efficiency improvements.

From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded in the very environment we live in. We still do not fully understand how information takes the form of cities, and how our minds deal with it in order to learn about the world, make daily decisions, and take part in the complex system of interactions we create as we live together. This paper addresses three related problems that need to be solved if we are to understand the role of environmental information: (1) the physical problem: how can we preserve information in the built environment? (2) The semantic problem: how do we make environmental information meaningful? And (3) the pragmatic problem: how do we enact environmental information in our daily lives? Attempting to devise a solution to these problems, we introduce a three-layered model of information in cities, namely environmental information in physical space, environmental information in semantic space, and the information enacted by interacting agents. We propose forms of calculating entropy in these different layers, and apply these measures to archetypal urban cases and simulated scenarios. Our results suggest that ordered spatial structures and diverse land use patterns encode information, and that aspects of physical and semantic information affect coordination in interaction systems.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

Auricular keloids pose significant aesthetic and functional challenges, and traditional treatments often fall short in ad-dressing these. Our study presents an innovative combined approach of ablative CO2 and dye laser therapy for improved keloid management. This treatment protocol was applied to 15 patients with auricular keloids after an initial multispec-tral analysis to assess keloid composition. The laser sequence was tailored per patient based on this analysis. Evalua-tions using the Vancouver Scar Scale and Patient and Observer Scar Assessment Scale were carried out at baseline and at 3-week intervals post-treatment. The results showed a significant reduction in these scores at the final follow-up (p<0.05), suggesting improvements in keloid color, texture, and pliability, with minimal adverse events. Additionally, no recur-rence of keloids was observed. Our findings indicate that this novel methodology of multispectral analysis followed by tailored laser therapy may offer a safe and effective solution for auricular keloids, promising enhanced keloid treatment and prevention of recurrence. However, further investigations, including randomized controlled trials, are needed to confirm and optimize this treatment protocol.

The management of skin cancer presents challenges in reconstructive surgery to achieve the best patient outcome and rapid wound healing. The most used antiseptic in pre and post operative care is Povidone Iodine solution. However, valid antiseptic alternatives should be considered. The primary endpoint of our study was to achieve the best healing in patients receiving fluorescein solution versus two comparator arms (Eosin and Povidone-Iodine).182 patients were enrolled and divided into three randomized groups according to the type of antiseptic solution received: Fluorescein (n = 63), Eosin (n= 60), and Povidone-Iodine (n = 59). To assess the endpoint of our study the ASEPSIS score was used to objectively evaluate graft healing. Results of the ASEPSIS score for each group were analyzed. The comparison demonstrated that there was no statistically significant difference among the three groups regarding the endpoint of our study, thus between fluorescein and povidone-iodine (p = 0.89), eosin and fluorescein (p = 0.54), and eosin and povidone-iodine (p = 0.81). Patients responded positively to the use of the Fluorescein antiseptic solution, although no more than the others. This study suggests that this type of antiseptic can be successfully used in skin graft management.

Introduction: Lumbar radiculopathy, frequently triggered by disc herniation, affects around one in 50 young adults (30-55 ages), leading to significant impacts on quality of life. When conservative treatments fail to alleviate symptoms, surgical intervention such as discectomy is often pursued. Technological advancements have led to various minimally invasive techniques, promising improved outcomes. Our aim was to compare clinical outcomes of different techniques. Methods: We conducted a systematic search in PubMed using "lumbar disc hernia" and the meta-analysis filter. Inclusion criteria comprised meta-analyses focusing on lumbar disc herniation treatments, published in English. A rigorous selection process adhering to PRISMA guidelines ensured high-quality evidence extraction. Results: From 28,171 initial records, 31 meta-analyses involving 87,852 patients were included. Heterogeneity across the literature presented challenges, notably in study populations, surgical techniques, and research designs. Among the techniques evaluated, full-endoscopic lumbar discectomy (FELD) emerged as superior in various perioperative parameters, including Visual Analog Scale (VAS) scores, Oswestry Disability Index (ODI), operation time, and complications. Conversely, automated percutaneous discectomy (AUTD) consistently exhibited poorer outcomes, suggesting limited effectiveness compared to other techniques. Conclusion: Despite advancements, the heterogeneity observed in the literature underscores the need for standardized approaches in minimally invasive spinal surgery research. FELD stands out as a preferred technique, offering favorable outcomes across multiple parameters. Conversely, techniques like AUTD raise concerns regarding efficacy. Future research should aim for uniformity in methodologies to facilitate accurate comparisons and guide clinical decision-making.

A system of simultaneous multi-variable nonlinear equations can be solved by the Newton’s method with local q-quadratic convergence if the Jacobian is analytically available. If this is not the case, then quasi-Newton methods with local q-superlinear convergence give solutions by approximating the Jacobian in some way. Unfortunately, the quasi-Newton condition (secant equation) doesn’t completely specify the Jacobian approximate in multi-dimensional case, so its full-rank update is not possible with classic variants of methods. The suggested new iteration strategy (“T-Secant”) allows full-rank update of the Jacobian approximate in each iteration by determining two independent approximates for the solution. They are used to generate a set of new independent trial approximates, then the Jacobian approximate can fully be updated. It is shown, that the T-Secant approximate is in the vicinity of the classic quasi-Newton approximate, providing that the solution is evenly surrounded by the new trial approximates. The suggested procedure increases the super-linear convergence of the secant method (φS = 1.618...) to super-quadratic (φT = φS + 1 = 2.618...) and the quadratic convergence of the Newton-method (φN = 2) to cubic (φT = φN + 1 = 3) in one dimensional case. The Broyden-type efficiency (mean convergence rate) of the suggested method in multi-dimensional case is an order higher than the efficiency of other classic low-rank update quasi-Newton methods as shown by numerical examples on a Rosenbrock-type test-function with up to 1000 variables. The geometrical representation (hyperbolic approximation) in single variable case helps explaining the basic operations and a vector-space description is also given in multi-variable case.

Full waveform (FW) LiDAR holds great potential for retrieving vegetation structure parameters at a high level of detail, but this prospect is constrained by practical factors such as lack of available handy processing tools and technical intricacy of waveform processing. This study introduces a new product, named the Hyper Point Cloud (HPC) derived from FW LiDAR data, and explore its potential applications such as tree crown delineation using the HPC-based intensity and percentile height (PH) surfaces, which show a promising solution to the constraints of using FW LiDAR data. Results of the HPC present a new direction to handle FW LiDAR data and offer prospects for studying the mid-story and understory of vegetation with high point density (~ 182 points/m2). The intensity-derived digital surface model (DSM) generated from the HPC shows that the ground region has larger maximum intensity (MAXI) and mean intensity (MI) than the vegetation region while having smaller total intensity (TI) and number of intensities (NI) at the given grid cell. Our analysis of intensity distribution contours at individual tree level exhibit similar patterns, indicating that the MAXI and MI are decreasing from the tree crown center to tree boundary while a rising trend is observed for TI and NI. These intensity variable contours provide a theoretical justification for using HPC-based intensity surfaces to segment tree crowns and exploit their potential for extracting tree attributes. The HPC-based intensity surfaces and the HPC-based PH Canopy Height Models (CHM) demonstrate promising tree segmentation results comparable to the LiDAR derived CHM for estimating tree attributes such as tree locations, crown widths and tree heights. We envision that products such as the HPC and the HPC-based intensity and height surfaces introduced in this study can open new perspectives to use FW LiDAR data and alleviate the technical barrier of exploring FW LiDAR data for detailed vegetation structure characterization.

It was recently studied how to achieve the optimal degrees of freedom (DoF) in a multi-antenna full-duplex system with partial channel state information (CSI). In this paper, we revisit the DoF of a multiple-antenna full-duplex system using opportunistic transmission under the partial CSI, in which a full-duplex base station having M transmit antennas and M receive antennas supports a set of half-duplex mobile stations (MSs) having a single antenna each. Assuming no self-interference, we present a new hybrid opportunistic scheduling method that achieves the optimal sum DoF under an improved user scaling law. It is shown that the optimal sum DoF of 2M is asymptotically achievable provided that the number of MSs scales faster than SNR^M, where SNR denotes the signal-to-noise ratio. This result reveals that in our full-duplex system, better performance on the user scaling law can be obtained without extra CSI, compared to the prior work that showed the required user scaling condition (i.e., the minimum number of MSs for guaranteeing the optimal DoF) of SNR^2M−1.

Light pollution of the night sky is a phenomenon increasingly observed around the world and reported in the form of thematic maps. The major contributor to light pollution is ill-adjusted or inappropriately designed artificial lighting by outdoor light sources. The phenomenon occurs mainly over urban areas, but affects both the urban environment and the areas adjacent to it. The problem of excessive artificial light emission at night and the negative effects it causes has already become so serious and global in its impact that effective and comprehensible methods of cartographic presentation of this phenomenon have been explored. The literature on the subject provides examples of how to present the results of measurements of light pollution of the night sky, but these have been developed using different colour scales, often in discretionary ranges and units of measurement. This paper presents an overview of the measurement scales and units found in the literature to describe the phenomenon of light pollution that obscures the night sky. A proposal of the author’s color scale for the presentation of the phenomenon was proposed and shown by example. The differences between measurement scales and how they affect interpretation of results are discussed. Furthermore, a recommendation is made for a standardised method of cartographic visualisation of the spatial distribution and presentation of light smog measurement results.

This study investigated whether positive self-talk (ST) over 4 weeks would improve standing long jump (SLJ) performance in men and women in their 20s. The participants of this study were 36 men and 28 women, selected through interviews with male and female students. The test subjects’ performance was measured 10 times over a 4-week period, 2-3 sessions per week. In the experimental group, participants performed SLJ while reciting positive ST; the control group performed SLJ without any specific conditions. A pre-and post-intervention survey was conducted using the Rosenberg Self-Esteem Scale (RSE). The results revealed a significant difference in the performance of experimental group (p < 0.05), while no significant difference was observed in the control group. RSE survey results also showed a significant difference only in the experimental group (p < 0.05). These findings indicate that self-affirmation yields positive effects on SLJ performance.

Weak signal spectral detection is a serious problem in many applications, especially the target possesses certain frequency band and under low signal-to-noise ratio (SNR). A kind of novel technique based on pre-whitening scale-transformation symmetric bistable parallel stochastic resonance (SR) is proposed to solve the problem. Firstly, the pre-whitening can ensure the even distribution of the receiving signal to fit the requirement of SR processing. Secondly, the scale- transformation can help to utilize the weak signal improvement property especially under low frequency band more effectively. Thirdly, the symmetric bistable parallel SR can try to reduce the variance of the clutter and additive noise fluently. Fourthly, by subtracting the steady state re-sponse of the selected symmetric bistable SR system from the parallel SR output, the weak signal spectral detection objective can be realized successfully. Simulation results based on the real sea clutter radar data guarantee the effectiveness and applicability of the proposed symmetric bistable PSR processing approach.

Involving local people in natural area management is very important to address the complexity of environmental management issues for sustainable use of local resources. Participatory methods require the contribution of local stakeholders in decision making. Mapping the environmental views of local communities allows for detecting aspects that could facilitate management efforts. This research – in the frame of the Skyros LIFE project and the PAMNATURA project - measures local acceptability of the conservation actions proposed by the LIFE project in Skyros Island (Greece) in relation with recording local people’s environmental orientation using the 15-item revised New Ecological Paradigm (NEP) scale. The research was carried out by means of questionnaires. The LIFE project proposed actions were grouped into three categories according to their theme, i.e. promoting (a) Nature protection, (b) Agro-pastoralism and (c) Ecotourism. The sample seems to largely agree with the LIFE project proposals, while the results showed high scores for most of the NEP scale items, implying pro-environmental beliefs, though there appears disagreement or neutrality regarding a few items. Local acceptability of the proposed actions was found to correlate to local people’s environmental concern measured through the NEP scale. Drawing on the results, implementation of actions related directly or indirectly to economic activities, preservation of traditional activities, as well as environmental education, interactive informing and consultation could enhance local participation. Skyros island seems to offer an appropriate social background for applying participatory and adaptive management and implementing conservation programs.

The study focused on the technical and scale efficiency of smallholder pineapple farmers in the Central Region of Ghana. The input-oriented Data Envelopment Analysis (DEA) was used to estimate technical, pure and scale efficiencies of the smallholder pineapple farmers, of which a random sampling procedure was used to select 320 respondents. The study revealed that the farmers were technically inefficient with mean technical efficiency under Constant Returns to Scale (CRS), pure efficiency under Variable Returns to Scale (VRS) and the Scale Efficiency levels of 0.505, 0.641 and 0.772, respectively, due to farmers’ inability to exploit fully the available technology while experiencing evident post-harvest losses resulting from low adoption of post-harvest technologies. Such findings are meaningful and could help the farming communities and relevant policymakers to understand the issues in farming production and hence undertake necessary actions to potentially improve farmers’ technical and scale efficiencies in the study area.

Background: The adoption of self-care behaviors among patients with congestive heart failure (CHF) is essential for the management of their health condition. However, there is a lack of tools for estimating self-care in CHF patients. We aim to develop and validate the Hippocratic heart failure self-care scale (HHFSCS). Methods: the scale includes 22 items which are reviewed by a committee of experts. Individuals indicate the frequency at which they follow each self-behavior on a five-point Likert scale. Adult patients with CHF (n=250) from a General Hospital, in Athens, were participated in the study from June 2020 to March 2021. Reliability coefficients and Explanatory Factor Analysis (EFA), using a Varimax rotation and the Principal Components Method were used to assess the psychometric measurements. Results: The Cronbach’s alpha coefficient of the HHFSCS was 0.807. The exploratory factor analysis identified two domains that accounted for 88.44% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test-retest showed a significant strong correlation (r=0.973, p&lt;0.001). Conclusions: The HHFSCS is a reliable and valid tool for assessing self-behaviors in CHF patients. Health professionals can use it in their clinical practice to improve the management of patient’s health conditions.

Small scale carp polyculture plays a key role for food supply in Bangladesh, however, factors including water pollution, limited infrastructure and inadequate disease management hinder its sustainability. This paper reports on a survey of 231 farmers across the 6 major carp producing regions in Bangladesh, analyzing factors including, farmers’ social aspects, farm characteristics, information on disease and approaches adopted to combat them, and biosecurity practices. Almost half (46.8%) of the farms surveyed experienced disease in carp species, with clear regional variations. Eighty four percent of farms reported carp mortalities during disease outbreak, with an average mortality level 10.23±11.81%. Clinical signs during outbreaks lasted between a week and a month, and there was a peak in disease outbreaks in two seasonal periods between June to July and October to December. Disease incidence was related to a range of factors including the farmer experience, ponds/farm type, stocked species, and biosecurity practice. A combination of disinfecting measures during pond preparation and measures during stocking, including discarding fingerling transport water off-farm, fingerling disinfection and check the health of fingerlings before stocking significantly reduced disease occurrence. Treatments involving the antibiotics, ciprofloxacin, erythromycin, and azithromycin were reported as ineffective, raising concerns about non-prudent use, inadequate dosing (perhaps without appropriate veterinary guidance) and the potential for further driving antimicrobial resistance in the environment. The research unveils a concerning pattern of disease high disease incidence across small-scale carp farms in Bangladesh and the significant potential for disease spread highlights the need for responsible disposal practices. The study emphasizes the need for improving training and awareness programs are vital for addressing biosecurity and disease management challenges, ensuring sustainable aquaculture and community well-being.

One of the current challenges in Higher Education is the development of students’ emotional competencies, and consequently, how these competencies can be trained. Moreover, this must be addressed within the UN framework of inclusive, equitable, quality education (United Nations Agenda 2030) (SDG 4). To address this challenge, the present study set the following objectives: (1) to analyze pre-service teachers’ level of interest in EI and their perceived level of general EI knowledge, (2) to examine their self-perception of certain variables of emotional knowledge, according to their degree program and year of studies, (3) to analyze the relationship between these emotional knowledge variables and perceived emotional intelligence (EI); and (4) to study the predictive capacity of the study variables on future teachers' emotional knowledge variables. The study sample contained a total of 434 university students from three degree programs at two universities in Spain, of which 82.70% were women, and the mean age was 20.91 years. Two instruments were used: an ad hoc questionnaire, which assessed perceived emotional knowledge according to three variables (General knowledge of EI, where level of training in EI is considered; Intrapersonal knowledge of EI; and Theoretical-practical knowledge related to teaching), and the Trait Meta-Mood Scale (TMMS-24), which assesses metaknowledge of emotional states across three variables (Attention, Clarity, and Repair). Results of the study suggest that there are differences in perceived EI knowledge according to students' year of studies and according to their degree, and indicate that students present high interest, while their perceived level of knowledge is low. In addition, emotional clarity is the EI variable that was identified as being important in the emotional knowledge of future teachers. This study shows evidence of the importance of social-emotional competencies in initial teacher training.

The grinding process by friction at the micro-scale in a mill with stones is considered a variable combination of contacts: with two-body (the asperities of lower millstone in direct contact with the asperities of upper millstone) and the three-body (micro-particles of ground seeds trapped between the asperities of lower and the upper stones of the mill). Three elements are described: (1) the mechanic contact of the asperities of the lower and upper millstone, to predict pressures on asperities, by modeling; (2) tests on a millstone sample covered with grinding particles, and (3) tests on a wafer sample formed by the millstones with the grinding particles between them. The paper highlights the combined effects of the micro-scale friction by individual measurements and to sum these effects an analytical model was used, and to validate the model, several experiments were performed. A suitable grind by friction assumes the grain’s movement and the interaction between the seeds and solid surfaces and is highlighted through theoretical and experimental studies. Topography analysis of the surface of the millstones revealed the model of microscopic frictional force. Endpoint measurements (the traces of the surface topography evolution), enable model verification in the grinding process.

Thanks to its valuable assessment possibilities (subjective complaints and changes in nasal patency in the course of the examination), nasal provocation test may serve as an alternative tool for oral food challenges in the future. However, this test requires successive attempts to regulate its methodology in order to develop a standardized lyophilisate form and determine the threshold dose for a positive result. The study objective was to present the methodological foundation for nasal food allergen provocation tests induced by freeze-dried powdered chicken egg white. A control group of 25 individuals with no history of allergy to chicken eggs or any other allergy was included in the study. Optical rhinometry and visual analog scale were used to assess the response of nasal mucosa to local allergen challenge. Minor variations in nasal flows as measured by optical rhinometry were observed in the provocation tests. The mean optical density measurements (as measured regardless of the allergen dose used) varied from positive to negative values and vice versa; e.g., amounting to 0.018 OD (standard deviation 0,095) at 15 minutes and −0.011 OD (standard deviation 0,090) at 30 minutes. No significant differences were observed with regard to the perceived nasal discomfort using the visual analog scale. Due to the absence of nasal mucosal reactivity, nasal challenge is an excellent methodological tool for implementing food allergen tests.

Pain is a complex multidimensional feeling combined with sensorial and emotional features. The majority of patients undergoing orthodontic treatment reported various degrees of pain, which is perceived as widely variable between individuals, even when the stimulus is the same. Orthodontic pain is considered the main cause of poor-quality outcomes, patients' dissatisfaction, and lack of collaboration up to the interruption of the therapy. A deep understanding of pain and how it influences the patient’s daily life is fundamental to establishing proper therapeutic procedures and obtaining the correct collaboration. Because of its multifaced and subjective nature, pain is a difficult dimension to measure. The use of questionnaires and their relative rating scales is actually considered the gold standard for pain assessment. Depending on the patient’s age and cognitive abilities is possible to choose the most appropriate instrument for self-reported pain records. Although several scales have been proposed and a lot of them are applied, it remains uncertain which of these tools represents the standard and performs the most precise, universal, and predictable task. This review aims to give an overview of the aspects which describe pain, specifically the pain experienced during orthodontic treatment, the main tool to assess self-perceived pain in a better and more efficient way, the different indications for each of them, and their correlated advantages or disadvantages.

Innovation and technology are important tools of minerals sector efficiency and productivity im-provement. The uptake of technologies has proven important levelrs to improve the productivity of mining sector. This paper provides a comprehensive analysis of mine-level productivity by using a global data of copper, gold, and platinum from 1991-2020. Various drivers of proioductivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in technical efficiency and productivity across mines and regions. A further decomposition of TFP into its different components suggest that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities. The findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in productivity in different commodities (e.g., South Africa vs. Zimbabwe) give policymakers with insights into how to support production scale and productivity through appropriate input mixtures.

Although the Geriatric Depression Scale (GDS) is a well-established instrument for the assessment of depressive symptoms in older adults, this has not been validated specifically for Portuguese cognitively impaired persons. The objective of this study was to analyze the psychometric properties of two Portuguese versions of the GDS (GDS-27 and GDS-15) in a Portuguese mild-to-moderate cognitively impaired sample. Clinicians assessed for major depressive disorder and cognitive functioning in 117 participants with mild to moderate cognitive decline (76.9% female, Mage = 83.66 years). The internal consistency of GDS-27 and GDS-15 were 0.874 and 0.812, respectively. There was a significant correlation between GDS-27 and GDS-15 with Beck Depression Inventory-II GDS-27: rho = 0.738, p < 0.001; GDS-15: rho = 0.760, p < 0.001), suggesting good validity. A cutoff point of 15/16 in GDS-27 and 8/9 in GDS-15 resulted in identification of persons with depression (GDS-27: sensitivity 100%, specificity 63%; GDS-15: sensitivity 90%, specificity 62%). Overall, the GDS-27 and GDS-15 are reliable and valid instruments for the assessment of depression in Portuguese-speaking cognitively impaired persons.

Considering the differences between the European and African continents concerning the management of the mining production sector, we decided to carry out this study with the main objective of demonstrating that, in Africa, mining can positively change the quality of life of the populations where it develops and, at the same time, it is possible to respect the environment, which is our main wealth. To achieve these objectives, it is necessary to present the mining activity of the continent, emphasizing both the negative aspects and its strong points. The most important thing is to make a good diagnosis of the situation, which will allow us to cure our "patient", that is, African mining production.

Marketing is the manner of how to make our sales the best in the market, our prices the most accessible, our clients satisfactory, and thus our brand is the largest distributed. This needs sophisticated and advanced understanding of the total network related. Indeed, marketing data may be seen in different forms such as qualitative and quantitative. However, in the literature, it is easily noticed that large bibliography may be collected about qualitative studies, against few studies on the quantitative point of view. This is a major drawback that makes the marketing science still focusing on the design, although the market is strongly depending on quantities such as money and time. Indeed, marketing data may be a time series such as brand sales per specified periods, brand related-prices over specified periods, market shares, ..., etc. The purpose of the present work is to investigate some marketing models based on time series due to brands. We will precisely study the effect of the time scale on the persistence of brands sales in the market and on the forecasting of such a persistence according to the characteristics of the brand and the related market competition or competitors. Our study is acted on a sample of Saudi brands during the period November 22, 2017 to December 30, 2021.

Background This paper draws learnings and successes based on field implementation experience spanning four years (2016–2019) of implementing CLTS by Prince of Peace Orphans and Widows Vision, a community-based organization located in Kaberamaido district in eastern Uganda. Methods The study aimed to document, disseminate and inform from an evidence-based point of view how adaptation and collaborative engagements triggers learning from mistakes to inform iterative changes from improvements and success.This is a descriptive paper that used project documents review based on field implementation experience. Existing project reports were synthesised, collated and curated for evidence. Data were drawn from project reports and records to inform narratives in writing. Implementation of the project was executed in homogenous rural communities occupied by people of the same dialect, cultural and social settings. Results We note that success in CLTS implementation can hardly be achieved by merely following prescriptions in handbooks and guidelines but rather by devising innovative community engagement and other participatory and community-driven techniques that foster adaptive management, promote ownership, and buy-in.Having learned from our failures, we used data to inform decisions and transformatively deviated from traditional CLTS implementation and introduced high impact and innovative approaches such as the use of CLTS helpdesks and Situation room, the Pamoja approach, learning labs and iterative feedback loops, innovatively tackling slippage and carefully introducing the follow-up mandona approach. These enhanced experiential learning and ultimately resulted in sustained sanitation behaviour. Conclusions The CLTS approach as outlined in the handbook needs to be flexibly adapted to address contextual needs. Reflective and learning sessions reinforced with routine feedback loops from implementers and beneficiaries yields tremendous results, propagates experiential learning, and ultimately results in a transformative deviation from undesirable to desired sanitation behaviours. These innovative approaches once carefully blended have proved to be sustainable, are adaptable and can work in an even larger scale and in a variety of contexts.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

Eco-friendly and low-cost water-based nanolubricants containing rutile TiO2 nanoparticles (NPs) were developed for accelerating their applications in industrial-scale hot steel rolling. The lubrication performance of developed nanolubricants was evaluated in a 2-high Hille 100 experimental rolling mill at a rolling temperature of 850 ℃ in comparison to that of pure water. The results indicate that the use of nanolubricant enables to decrease the rolling force, reduce the surface roughness and the oxide scale thickness, and enhance the surface hardness. In particular, the nanolubricant consisting of 4 wt% TiO2, 10 wt% glycerol, 0.2 wt% sodium dodecyl benzene sulfonate (SDBS) and 1 wt% Snailcool exhibits the best lubrication performance by lowering the rolling force, surface roughness and oxide scale thickness up to 8.1%, 53.7% and 50%, respectively. The surface hardness is increased by 4.4%. The corresponding lubrication mechanisms are attributed to its superior wettability and thermal conductivity associated with the synergistic effect of rolling, mending and laminae forming that are contributed by TiO2 NPs.

Biological gels (bio-gels) are hydrated polymer networks that serve diverse biological functions, which often lead to intentional or unintentional exposure to particulate matter. In this work, we derive a microscopically motivated framework that enables the investigation of penetration mechanisms into bio-gels. We distinguish between two types of mechanisms: spontaneous (unforced) penetration and forced penetration. Using experimental data available in literature, we exploit the proposed model to characterize and compare between the micro-structures of respiratory, intestinal, and cervicovaginal mucus and two types of biofilms. Next, we investigate the forced penetration process of spherical and ellipsoidal particles into a locally quadrilateral network. The proposed framework can be used to improve and complement the analysis of experimental findings in vitro, ex vivo, and in vivo. Additionally, the insights from this work pave the way towards enhanced designs of nano-medicines and allow to assess risk factors related to the nano-pollutants exposure.

Huge filaments with scales from several hundred megaparsecs to gigaparsecs are detected in the distribution of galaxies and clusters, quasars, gamma-bursters. The hypothesis on the nature of the huge filaments as regions of space-time deformation is proposed. An anisotropic deformation of the local region is described by the strain tensor, it depends on the velocities of matter. Galaxies get an extra velocity in the region, which leads to the formation of filamentary structures. The class of exact solution of the GR equations is constructed by introducing the special definition of the Christoffel symbols as function of the velocity of matter. With a definition of these symbols, the motion matter equation turns into identity. For the sake of simplicity, an ideal fluid is considered.

Severe postoperative pain affects most patients after thoracotomy and is a risk factor for post-thoracotomy pain syndrome (PTPS). This randomized controlled trial compared preemptively administered ketamine versus paravertebral block (PVB) versus control in patients undergoing posterolateral thoracotomy. The primary outcome was acute pain intensity on the visual analog scale (VAS) on the first postoperative day. Secondary outcomes included morphine consumption, patient satisfaction, and PTPS assessment with Neuropathic Pain Syndrome Inventory (NPSI). Acute pain intensity was significantly lower with PVB compared to other groups at four out of six time points. Patients in the PVB group used significantly less morphine via a patient-controlled analgesia pump than participants in other groups. Moreover, patients were more satisfied with postoperative pain management after PVB. PVB, but not ketamine, decreased PTPS intensity at 1, 3, and 6 months after posterolateral thoracotomy. Acute pain intensity at hour 8 and PTPS intensity at month 3 correlated positively with PTPS at month 6. Bodyweight was negatively associated with chronic pain at month 6. Thus, PVB but not preemptively administered ketamine decreases both acute and chronic pain intensity following posterolateral thoracotomies. The trial was prospectively registered at the Australian New Zealand Clinical Trial Registry (https://www.anzctr.org.au/; ACTRN12616000900415; 07 July 2016).

In this work a modified version of the well-known Simple Water Balance (SWB) model, comprising here three parameters instead of one, was used. Although simple, the model was tested in large-scale river basins in east-central Greece, upstream two hydrometric stations. The available historic runoff records comprised 19 hydrologic years each, on a monthly basis. Thirteen among them were used for calibrating the model, whereas the six subsequent, for validating it. Two different efficiency criteria were used as a measure of performance of the modified model. Their values, calculated for both calibration and validation stages, were close and relatively high. Thus, keeping in mind both the size and complexity of the river basins studied, one can conclude that the modified model, despite its simplistic concept and lumped form, fits satisfactorily the historic runoff series.

Mill scale is the by-product of iron and steel industry. It can be recycled via sinter plant or solid as sinter feed materials. 85 to 90% of the constituent particles are more than 0.008 inches. The iron content is near around 70 %, with a very small amount of alkaline compounds and non-ferrous metals. Mill scale is polluted and contaminated with lubricants, oils and greases from the equipment. In this experiment for recovering of oil from mill scale, it is treated with three different methods. Then all methods were compared according to the ability of oil elimination and iron recovered. After washing and boiling with surfactants, large amount of polluted waste water becomes a problem for environment so this wastewater was utilized for making of Microbial Fuel Cells (MFCs), production of electricity in MFC depends on the biodegradation of organic materials, so different waste were added in wastewater for making MFC. The remaining of MFC was converted in bioethanol, biodiesel and biofertilizer. So this research is economical and environmentally friendly and fulfilled the important aspect of green environment with zero waste. It will be a mile stone in the research of metallurgy, environmental engineering, recycling technology and zero waste management.

While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.

The thermal lubrication of an entangled polymeric liquid in wall-driven shear flows between parallel plates is investigated by using a multiscale hybrid method coupling molecular dynamics and the hydrodynamics (i.e., the synchronized molecular dynamics method). The temperature of the polymeric liquid rapidly increases due to viscous heating once the drive force exceeds a certain threshold value. The rheological properties of the polymeric liquid drastically change at around the critical drive force. In the weak viscous-heating regime, the conformation of polymer chains is dominated by the local shear flow so that the anisotropy of the bond orientation tensor grows as the drive force increases. However, in the large viscous-heating regime, the conformation dynamics is dominated by the thermal agitation of polymer chains so that the bond orientation tensor recovers more uniform and random structures as the drive force increases, even though the local shear flows are further enhanced. Remarkably, these counter-intuitive transitional behaviors give an interesting re-entrant transition in the stress--optical relation, where a linear formalism in the stress--optical relation approximately holds even though each of the macroscopic quantities behaves nonlinearly. The robustness of the linear stress--optical relation is also confirmed in the spatiotemporal evolution at the hydrodynamic level.

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

We focus on macromolecules which are modelled as sequentially growing dual scale-free networks. The dual networks are built by replacing star-like units of the primal treelike scale-free networks through rings, which are then transformed in a small-world manner up to the complete graphs. In this respect, the parameter γ describing the degree distribution in the primal treelike scale-free networks regulates the size of the dual units. The transition towards the networks of complete graphs is controlled by the probability p of adding link between non-neighbouring nodes of the same initial ring. The relaxation dynamics of the polymer networks is studied in the framework of generalized Gaussian structures by using the full eigenvalue spectrum of the Laplacian matrix. The dynamical quantities on which we focus here are the averaged monomer displacement and the mechanical relaxation moduli. For several intermediate values of the parameter’s set (γ, p) we encounter for these dynamical properties regions of constant in-between slope.

It is important to realize the transformation behavior of wüstite because it greatly affects the final structure of the oxide layer and the surface quality of the steel products. In the present study, the transformation behaviors of the wüstite layer are examined under nearly-oxygen-free conditions, to simulate the cooling processes after the hot rolled strip is coiled. As the single phase wüstite was prepared at 950˚C, the 460˚C transformed oxide layer was composed of a mixture of iron and magnetite formed through eutectoid reactions. For the 750˚C-fabricated wüstite, only magnetite was observed after transformation, without iron precipitates and residual wüstite. It is speculated that the unusual transformation behavior of the low-temperature-made wüstite results from the pseudo-structural intermediate phase transformation between wüstite and magnetite. This pseudo-structure is a pre-transformed wüstite and of various concentration of ferrous ion, which is determined by the fabrication conditions. During the hot strip mill process, the so-called wet scale, wüstite, is produced continuously from finish mill to laminar flow sections and ended at 570˚C. Consequently, the final eutectoid transformation below 570˚C is dominantly controlled by the surface temperature ranged from 750˚C to 950˚C for low carbon steel.

TThe following three objectives were tested in this study: (1) investigate the utility of low-altitude remote sensing using UAS technology to compare the effects of different N application systems in rice production; (2) use spatial extrapolation to scale up plot-level generated to farmer field rice yield data based on crop spectral signatures, and (3) predict and map out rice productivity as a function of N placement systems. Images were captured on a UAV platform at midseason of the rice crop. Orthomosaics were developed for selected fields in rice-producing zones. Grain yields were assessed from low, medium, and high crop health plots delineated based on NDVI values. On the plot scale, UDP outyielded non-UDP by 0.84%. Individual plot yield data were scaled up to the farmer field level through Jenks natural breaks classification and es-tablishing an empirical relationship between OSAVI and plot yields. Assessment of the scaled-up field levelfield-level data also confirmed the superiority of UDP N man-agement over the non-UDP systems in promoting rice yields. Scaling up plot scale da-ta to whole field levels also facilitated generating and mapping expected yield maps for individual farmer fields in the three zones studied. This study has established a tangible simple but tangible protocol protocol for predicting and mapping rice yields in small-scale farmer fields using UAS data.

This comprehensive study looks at how operational conditions affect the performance of a novel seven-channel titania ceramic ultrafiltration membrane for the treatment of produced water. A Full factorial design experiment (23) was conducted to study the effect of the cross-flow operating factors on the membrane permeate flux decline and the overall permeate volume. Eleven experimental runs were performed for three important process operating variables: Transmembrane Pressure (TMP), Crossflow Velocity (CFV), and Filtration Time (FT). Steady final membrane fluxes and permeate volumes were recorded for each experimental run. Under the optimized conditions (1.5 bar, 1 m/s, and 2 hours), the membrane performance index demonstrated an oil rejection rate of 99%, a flux of 297 liters/m2·hr (LMH), a 38% overall initial flux decline, and a total permeate volume of 8.14 L. The regression models used for the steady-state membrane permeate flux decline and overall permeate volume led to the highest goodness of fit to the experimental data with a correlation coefficient of 0.999. A Multiple Linear Regression method and an Artificial Neural Network approach were also employed to model the experimental membrane permeate flux decline and analyze the impact of the operating conditions on membrane performance. The predictions of the Gaussian regression and the Levenberg-Marquardt backpropagation method were validated with a determination coefficient of 99 % and a mean square error of 0.07.

Objective: This study aims to investigate the effects of acupuncture therapy on the quality of life, early recurrence rate, and heart rate variability in patients following radiofrequency ablation for atrial fibrillation, as well as to assess its safety. Methods: Seventy patients were enrolled in this study. Of these, 35 patients received acupuncture treatment post-radiofrequency ablation, forming the experimental group, while the remaining 35 patients received sham acupuncture treatment, constituting the control group. The acupuncture group targeted the Xinju (BL15), Neiguan (PC6), and Shenmen (HT07) points, whereas the sham acupuncture group received sham interventions at three non-meridian and non-acupoints. Both groups underwent acupuncture treatment twice weekly for a total of 24 consecutive sessions. After three months, the total scores on the Atrial Fibrillation Specific Quality of Life Scale (AFEQT)—including symptom scores, daily activity scores, treatment anxiety scores, atrial fibrillation control scores, and symptom improvement satisfaction scores—along with atrial fibrillation burden and satisfaction scores, were compared between the two patient groups. Additionally, the recurrence rate of atrial fibrillation, frequency of hospitalizations due to arrhythmia, and incidence of adverse events occurring three months post-catheter ablation were also assessed. No significant differences were observed in the general baseline characteristics between the two groups. Results: The total AFEQT scores—including symptom scores, daily activity scores, treatment anxiety scores, atrial fibrillation control scores, and symptom improvement satisfaction scores—were significantly higher in both groups post-treatment compared to pre-treatment. Notably, patients in the experimental group exhibited statistically significant improvements in daily activity scores, treatment anxiety scores, and symptom improvement satisfaction scores compared to those in the control group (P<0.05). There were no statistically significant differences between the two groups regarding other measured outcomes. Conclusion: Acupuncture-assisted treatment of atrial fibrillation can improve the clinical efficacy of drugs and catheter ablation, help maintain sinus rhythm, increase sinus rhythm conversion rate, reduce ventricular rate, and shorten conversion time, and is safe and reliable.

Due to the inherent limitations of a single viewpoint, reconstructing 3D human meshes 1 from a single image has long been a challenging task. While deep learning networks enable us to 2 approximate the shape of unseen sides, capturing the texture details of the non-visible side remains 3 difficult with just one image. Traditional methods utilize Generative Adversarial Networks (GANs) 4 to predict the normal maps of the non-visible side, thereby inferring detailed textures and wrinkles 5 on the model’s surface. However, we have identified challenges with existing normal prediction 6 networks when dealing with complex scenes, such as a lack of focus on local features and insufficient 7 modeling of spatial relationships.To address these challenges, we introduce EMAR—Enhanced 8 Multi-scale Attention-driven Single Image 3D Human Reconstruction. This approach incorporates 9 a novel Enhanced Multi-Scale Attention (EMSA) mechanism, which excels at capturing intricate 10 features and global relationships in complex scenes. EMSA surpasses traditional single-scale attention 11 mechanisms by adaptively adjusting the weights between features, enabling the network to more 12 effectively leverage information across various scales.Furthermore, we have improved the feature 13 fusion method to better integrate representations from different scales. This enhanced feature fusion 14 allows the network to more comprehensively understand both fine details and global structures 15 within the image. Finally, we have designed a hybrid loss function tailored to the introduced attention 16 mechanism and feature fusion method, optimizing the network’s training process and enhancing the 17 quality of reconstruction results.Our network demonstrates significant improvements in performance 18 for 3D human model reconstruction. Experimental results show that our method exhibits greater 19 robustness to challenging poses compared to traditional single-scale approaches.

We investigate the cosmological evolution of the universe for a spatially flat FLRW background space within the context of $f(T,B)$ gravity, which is a recently formulated teleparallel theory that connects both $f(T)$ and $f(R)$ gravity under suitable limits. The analysis has been done by focusing on four different $f(T,B)$ cosmological models corresponding to various choices of scale factor, namely emergent, logamediate, and intermediate. In addition to this, we also assume a power-law-like function of $f(T,B)$ gravity. The reconstruction of $f(T,B)$ gravity has been done by considering the Holographic Ricci Dark Energy(HRDE) (a particular case of a highly generalized holographic dark energy given in Nojiri et al. in General Relativity and Gravitation, 38, pp.1285-1304,2006) as the background fluid. We analyze the equation of state parameters and the squared speed of sound for the reconstructed models. Finally, we conducted the thermodynamical analysis for each reconstructed model. The generalised second law of thermodynamics(GSLT) is valid for the four different $f(T,B)$ cosmological models.

This cross-sectional survey assessed the resilient coping levels and their relationship with the socio-demographic characteristics of nursing professionals in Saudi Arabia. Adult (≥18 years) registered nurses and practicing for ≥1 year were included. Resilient coping levels (as assessed via a 4-item Brief Resilience Coping Scale; BRCS) and socio-demographic and other characteristics data were collected. Descriptive analysis and ordinal logistic regressions were used to analyze the data. Further, the psychometric properties of the BRCS were reported. A total of 216 nursing professionals were included. The mean BRCS score was 14.6 (standard deviation=3.6), with most nursing professionals (62.5%) reporting medium to high resilience coping levels. The ordinal logistic regression model demonstrated that increasing age (p=0.002), best overall health (p=0.001), and nurses posted in the outpatient department (p=0.049) and intensive care unit (p=0.032) had significantly high resilient coping levels. The internal consistency of the BRCS was good (Cronbach’s alpha=0.80). In summary, nursing professionals in Saudi Arabia showed medium resilient coping levels. Moreover, this study suggests that BRCS is a psychometrically reliable and adequate tool for assessing resilience coping levels and provides valuable insights into the relationship between resilient coping levels and socio-demographic characteristics of the nursing professionals in Saudi Arabia.

Agriculture is the largest sector of Nepalese economy among the south-Asian developing countries that contributed 26.98 % share of Gross Domestic Product (GDP) in the year 2018/19. The capacity to derive maximum output by per unit of resource is resource use efficiency. Resource use efficiency of a producer explains the comparison between inputs and output value. Potato is staple vegetable in every parts of Nepal. Cobb-Douglas production function is used to predict the significance of inputs in income from cash crops. Due to lack of optimum utilization of available resources in cultivation of vegetable like lack of technical knowledge, low education level, and extensive service the productivity and production is low in Nepalese economy. It ensures vegetable security in Nepal. Though, there are extensive researches on the resource use efficiency and productivity issues on agriculture, very few papers explored in the case of Sudurpaschim province of Nepal OBJECTIVE: This study had the specific purposes: (1) To identify the factors affecting in resource use efficiency and productivity of potato production (2) to utilize the resource use efficiency and productivity in potato production and (3) to show the type of returns to scale in potato production. METHODS: Applying post-positivist paradigm and quantitative causal survey research design, it explored the resource use efficiency and productivity through the semi-structured questionnaire from 140 households by random sampling. Data analysis was carried out by multiple regression model using Cobb-Douglas production function. SPSS software was used to find quantitative results. From the analysis of data using mean, and SD, t-test, analysis of variance, Durbin-Waston test, Marginal Value Product and marginal Factor cost, findings of this research was emerged. RESULTS AND DISCUSSION: The major findings: education level, extension service, farm size and pesticide cost were significant variables in potato production; seed, hired labor, Family Yard Manure and pesticide cost were overused and needed to decrease their cost for optimum allocation and there was decreasing returns to scale in production. This study emphasized on increasing education level, extensive service and farm size for optimum utilization of resources and increasing returns to scale. SIGNIFICANCE: Barriers to Indian potatoes and increasing returns to scale are only possible through protection policy of government. For optimum use of resources and increasing returns to scale, government can introduce capital intensive technique. This study can be implied in policy making and improving existing situation of agriculture, and allocating budget.

Undernutrition is a significant public health issue in Colombia and globally, influenced by multiple factors. The relationship between food insecurity and acute undernutrition in children has been insufficiently explored. To address this, a descriptive, observational, cross-sectional study was conducted involving 70 children under the age of 5, who presented with moderate to severe acute malnutrition. The study assessed family and child food security using the Latin American and Caribbean Food Security Scale (ELCSA). Analysis of the data revealed that when households face challenges in meeting their basic needs, children are generally the least affected. Caregivers tend to prioritize children's diets, opting to reduce food intake among adults over 18 years of age instead. The causes of malnutrition were explored through the perceptions of guardians, who reported that in 30.2% of cases, malnutrition is linked to inadequate feeding and parenting practices. Specific issues noted by parents included children being too lazy to chew, preferring ultra-processed foods, or refusing to eat altogether. The study found that not all children with acute malnutrition experience food insecurity; in fact, the proportion of children suffering from hunger was very low. The findings suggest that malnutrition in children under 5 years of age is not solely determined by food insecurity but also by other factors such as parenting practices and poor feeding habits. Further research is needed to evaluate food access and quality, particularly in terms of dietary diversity, to better understand the needs of each population. Such studies will be essential in guiding public health interventions aimed at preventing, managing, and addressing malnutrition in children.

The Axillary Seabream Pagellus acarne is of economic importance for recreational and commercial fisheries in the Atlantic and the Mediterranean, but a decline in total landings has been observed and raised some concern. Although biological information on the species has been provided for the Atlantic and Mediterranean, in the Portuguese continental slope data is restricted to the southern part of the country, which points to the relevance of the present work. A total of 520 individuals, between 7.8 cm and 39.9 cm TL, were monthly collected from September 2020 to August 2022 from commercial landings of fishing vessels operating off mainland Portugal, and used to study age and growth, the reproductive strategy and the annual sexual cycle. Age varied between 0 years (7.8 cm TL) and 15 years (34.2 cm TL) and the von Bertalanffy growth parameters were estimated from whole-otolith readings (L∞ = 35.2 cm, k = 0.133 yr–1 and t 0 = –2.78 yr). Pagellus acarne proved to be a protandric hermaphrodite species with males prevailing until 28.0 cm TL and females between 28.0 cm and 34.0 cm TL with a brief sex change phase. Females presented asynchronous oocyte development with a batch spawning pattern. The spawning season occurred from April to October with a spawning peak between June and August aas shown by histological analysis of the gonads and high levels of GSI during the period.

The mental health impact of the environmental crisis, particularly eco-anxiety, is a growing research topic whose measurement still lacks consensus. In this article, we use item response theory (IRT) to better un-derstand what existing questionnaires measure. To conduct this review, we used open-access data from the short French version of the Climate Change Anxiety Questionnaire (Mouguiama-Daouda et al. 2022, Heeren et al., 2023). Our results suggest that, of the different models tested, the unidimensional model seems to be the most appropriate for measuring eco-anxiety. The item difficulty parameter extracted from the IRT enabled us to discuss the level of severity of the items making up this tool. The Climate Change Anxiety Questionnaire is more appropriate for measuring severe to moderately severe eco-anxiety. Ave-nues for improving this questionnaire and the measurement of eco-anxiety in general are then discussed.

In this work, we introduce a new and generalized concept (herein referred to as Caputo fractional delta derivative and Caputo fractional delta dini derivative of order $\alpha\in(0,1)$) for Caputo fractional derivatives on an arbitrary time domain $\mathbb{T}$ which is a closed subset of $\mathbb{R}$. Combining the continuous and discrete time domains, we create a unified framework for stability analysis on time scales. Comparison results and stability criteria for the considered Caputo fractional dynamic equations are presented based on a new definition for Caputo fractional delta derivative of a Lyapunov function, contributing to the broader understanding of fractional calculus on time scales. The work also incorporates an illustrative example to demonstrate the relevance, effectiveness and applicability of the established stability results over that of the integer order.

This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. The Ukraine War has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. This investigation outlines the development of a MATLAB optimisation code, based on minimum induced loss propeller theory, which calculates the optimal chord and twist distribution for a chosen propeller operating in known flight conditions. The MATLAB code includes a minimum Reynolds number functionality, which provides the option to alter the chord distribution to ensure the entire propeller is operating above a set threshold value of Reynolds (&gt;100,000), as this has been found to be a transition point between low and high section lift-to-drag ratios. Additional functions allow plotting of torque and thrust distributions along the blade. The results have been validated on experimental data taken from an APC ‘Thin Electric’ 10” x 7” propeller, where it was found that both the chord and twist distributions were accurately modelled. The MATLAB code resulted in a 16% increase in the maximum propulsive efficiency. Further work will investigate a direct interface to SolidWorks to aid rapid propeller manufacturing capability.

The conversion of native habitats into anthropogenic ones compromises the original composition and configuration of the landscapes, influencing ecological dynamics and affecting biodiversity. Increasingly, landscape ecology has shown that these effects can only be understood if accessed at adequate spatial scales, as the scale which landscape structure is evaluated influences species responses. Here, we investigated how three variables of landscape composition (proportion of forest, coffee crop and pasture) and two of configuration (number of fragments and mean nearest neighbor distance) interfere in the richness and composition of medium and large-sized mammals considering a multiscale approach. We recorded medium and large-sized mammal species in 13 landscapes with predominantly matrices of coffee and pasture in Minas Gerais, Brazil. Then, we built distance-based linear models to identify the scale of effect of each landscape variable for both response variables considering eight scales (from 250 m to 2000 m). Finally, we verified the influence of the landscape on the richness and composition of mammals, considering the landscape variables in their respective scales of effect. We found 67% of the probable species occurring in the region. The scales of effect varied among landscape variables probably due to the different variables affect different aspects of organisms' ecological requirements. The proportion of pasture in the landscape explained the variation in species richness, while the proportion of forest explained the variation in species composition. In addition, the proportion of pasture in the landscape had a positive influence on species richness, indicating that this matrix may favor the presence of generalist species of habitat and/or this result is due to the higher concentration of species in the fragments immersed in this matrix. These results suggest that considering different responses to biodiversity is important to understand different aspects of the landscape's influence on biodiversity. In addition, the composition of the landscape is fundamental for the perpetuation of species and, therefore, both forest cover and types of matrices in the landscape must be considered to improve species conservation strategies. Finally, generalizing a spatial scale can lead to misinterpretations about the influence of the landscape on biodiversity.

Previous high throughput screening studies indicated trans-eQTLs tend to be tissue specific. In this study, I probed if this feature can be used to identify tissue-specific gene regulatory networks. eQTL data (P<5e-8) for 16,259 genes were identified and their summary association statistics were obtained from the eQTLGen database. Next, eQTLs that display both cis and trans regulatory effects were selected and the association between their corresponding genes were examined by Mendelian randomization. 253 genes that exerted trans-regulatory impacts on 1,439 genes were identified. Majority of the identified gene-pairs aggregated into a gene regulatory network significantly enriched in hemo-immune processes. The robustness of finding was confirmed through simulation. Genes with higher gene expression heritabilities displayed broader regulatory impact in the network. The network displayed the scale-free topology, this provided the reason to examine the association of the network’s hub genes with the phenome. The outcome of analyses revealed GSDMB and ORMDL3 impact several disorders of immune origin and higher expression of HHEX is associated with lower triglycerides and risk of type 2 diabetes. This study reports trans-eQTLs can be used to identify tissue-specific gene regulatory networks and describes a workflow to achieve this purpose. The identified network displayed scale-free topology indicating the hub genes of a tissue-specific network could be targeted to prevent disease outcomes.

Dynamic crossflow filtration (DCF) is the state-of-the-art technology for solid-liquid separation from viscous and sensitive feed streams in the food and biopharma industry. Up to now, the potential of industrial processes is often not fully exploited because fixed recipes are usually applied to run the processes. Therefore, a digital twin has been developed to optimize an industrial brownfield DCF plant. The core of the digital twin is a mechanistic-empirical process model combining fundamental filtration laws with process expert knowledge. The effect of variation of selected process and model parameters on plant productivity has been assessed using a model-based design-of-experiments approach and a regression metamodel has been trained with the data. A cyclic program that bidirectionally communicates with the DCF asset serves as frame of the digital twin. It monitors the process dynamics membrane torque and transmembrane pressure and feeds back the optimum permeate flow rate setpoint to the physical asset in almost real-time during process runs. The presented digital twin framework is a simple example how an industrial established process can be controlled by a hybrid model-based algorithm. With a digital process dynamics model at hand, the presented metamodel optimization approach can be easily transferred to other (bio)chemical processes.

In this study, the distribution patterns of southern horse mackerel are examined using commercial fine-scale resolution data. Using landings by size category and VMS data from the Portuguese commercial bottom trawl fishery, which consistently targets horse mackerel, this study provides a comprehensive analysis of horse mackerel age distributions spanning a decade (2010-2020). Importantly, the study addresses potential biases in commercial effort data and establishes the usefulness of commercial bottom-trawl gear as a suitable method for sampling and evaluate southern horse mackerel stock dynamics. Ordered regression models were applied to allow for the modelling of the distribution of multiple age categories and investigate spatio-temporal migrations off the Portuguese coast. Southern horse mackerel shows a widespread age distribution range and stable abundance with indications of seasonal and spatial patterns in the distribution of specific age groups. The insights derived from this research contribute valuable knowledge for understanding the dynamics and distribution patterns of fish populations.

Climate change is unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems and the fisheries sector. This study documented the past occurrence of extreme climate change impacts, such as supertyphoon Pablo (ST: Bopha), which severely affected Baganga, Davao Oriental, about ten years ago. A mixed-methods data collection was used, combining semi-structured interviews with small-scale fishers (N=120) in four fishing villages and focus group discussions (N=4, participated by about 4 focus groups) on assessing the impacts and their adaptation after climatic events occurred. Our findings indicate that the four selected fishing villages were exposed to common factors of climate change events that destroyed many lives and their livelihood. Including a decrease in catch per trip and the fishing operations disruption (98%). However, due to the impact of the supertyphoon, small-scale fishers in Baganga developed psychological distress (emotional 44% and physical 24%) due to the extreme event or disaster and economic losses (32%). In order to survive, their adaptation strategies relied on government and non-government-provided provisions and projects, e.g., planting trees, constructing a sea wall with wave breakers, cash for work, and tourism as an alternative livelihood. Despite this, our study revealed that the community had limited knowledge on the impacts of climate change, lack clear management goals especially for fishers, and the widespread use of illegal fishing gears. The local government must strongly implement rules, policies, and adaptation measures that will contribute to better and more resilient communities. This can help them to withstand future shocks and provide sustainable fisheries resources that will benefit all the fishers. The study will be useful to policymakers, disaster management group and organization that will help assist affected communities highly affected by climatic events.

Semiconductors play a very important role in modern society. The improvement in performance of semiconductors is what has enabled the world to grow at such a fast pace. For decades scaling has been done through Moore’s law i.e performance improvements have been obtained due to transistor scaling where the number of transistors per unit area increase is what has contributed to the increase in performance. However, with transistor scaling reaching its limitations we need to find alternate methods to enhance silicon design to suit the computational need of modern society. To address this problem we will be looking into a few methods that enable performance scaling with a focus on analysing the most popular implementation of each in the industry.

As smoke toxicity is unregulated outside of the mass transport industry, there is no set methodology for assessing smoke toxicity of construction products, like OSB, on a large-scale. This research aims to assess the novel design of a modified ISO 9705 room corner test designed for smoke toxicity quantification. Three tests conditions will be assessed to determine if restriction of ventilation is enough to force a fire to transition to under-ventilated flaming, or if the fuel loading is much more important in affecting the fire severity and fire condition. The research found that fuel loading and test geometry has more significant impact on the fire condition than restricting the ventilation. While imposing restrictions on the test rooms ventilation did increase the equivalence ratio, it was not sufficient enough to force the transition into under-ventilated flaming. The addition of a door to the test room did not force the fire to transition to under-ventilated flaming. When doubling the fuel loading, there was sufficient fuel for the fire to transition to under-ventilated flaming. This research has provided the experimental methodologies to assess smoke toxicity at a range of ventilation conditions on a large-scale.

The contemporary landscape of education is witnessing a paradigm shift towards innovative instructional methods, with the flipped learning approach gaining considerable attention. The purpose of this research was to investigate the impact of the flipped learning approach on students' perception and acceptance throughout an entire semester in the 'Introduction to Programming with Java' course, using a research design with a quantitative approach, ultimately aiming to inform educational practice and advance our knowledge of innovative teaching methods in higher education. This study was conducted at a university with 174 students involved, divided into two groups, 87 students in the experimental group and 87 students in the control group. The data collected through the scales were analyzed by using descriptive and inferential statistical analysis techniques in statistical software. At the end of the measurements, the technology acceptance level and self-directed learning perceptions of engineering students who received education with flipped learning were high. The results suggest that educators should consider students' readiness for self-directed learning when implementing the flipped learning approach and focus on creating an environment that supports their autonomy and engagement. This research offers valuable guidance for instructors, curriculum designers, and educational policymakers seeking to enhance the effectiveness of flipped learning in higher education courses.

Sensation seeking (SS) is a psychobiological personality trait characterized by an individual’s propensity to engage in various forms of risk-taking behavior. The Brief Sensation Seeking Scale (BSSS-8) is a widely used instrument for assessing SS that has been translated into several languages. However, only outdated and non-validated questionnaires have been used to measure SS in the Slovenian population. The aim of this study was to translate and psychometrically validate the Slovenian version of the BSSS-8. A total of 363 participants aged between 14 and 65 years completed the translated BSSS-8 and the questionnaire on drug abuse. The scale demonstrated good reliability (Cronbach’s α=0.81) and a unidimensional factorial structure, as revealed by confirmatory factor analysis (CFA). The multigroup CFA showed gender-specific measurement invariance. In the nomological network, SS was positively associated with drug-related variables. The Slovenian version of the BSSS-8 scale is a short and simple instrument to assess SS for research and epidemiological purposes.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

Deep networks-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structural information that contains important semantic details crucial for effective hash learning. To address this limitation and improve image retrieval accuracy, we propose a novel deep hashing method called Deep Supervised Hashing by Fusing Multiscale Deep Features (DSHFMDF). Our approach involves extracting multiscale features from multiple convolutional layers and fusing them to generate more robust representations for efficient image retrieval. Experimental results on CIFAR10 and NUS-WIDE datasets demonstrate that our method surpasses the performance of state-of-the-art hashing techniques.

The work presents a mathematical model of a thermogravimetric curve for the growth and simultaneous sublimation of scale on a metal or alloy surface. Reduction of the reaction area as a result of the formation of oxides of alloying elements (for obtaining the basic oxide) is considered for the alloy. For metals, the case where this area is increased as a result of powder metal crushing is also considered. The equations that were obtained are employed to explain the kinetic curves of the mass change of the samples.

The sustainability of agroecological systems, biodiversity protection, animal welfare and consumer demand for higher-quality products from alternative and extensive farming methods, have reinforced interest in local breeds that are well adapted to low-input environments. However, food safety needs to be safeguarded to reinforce consumer confidence. The aim of this study was to conduct a preliminary investigation on the occurrence of Salmonella spp. in eggshells, hen’s cloaca and litter materials from autochthonous Portuguese laying hens raised in a semi-extensive system for small-scale production. A total of 279 samples were obtained, with 63 samples from the “Preta Lusitânica” breed, and 72 samples each from the remaining autochthonous breeds, namely “Branca”, “Amarela” and “Pedrês Portuguesa”. None (0%) of the samples analyzed were positive for Salmonella spp.. To the best of our knowledge, these are the first results of Salmonella evaluation from hen’s cloaca, eggshells, and litter materials in autochthonous Portuguese chickens, suggesting that a semi-extensive production system can contribute to better food security and a lower risk to public health and the environment.

Mindfulness interventions have been implemented in many countries. This study aimed to examine the psychometric properties of English and Thai-version of the 15-item mindfulness attention awareness scale (MAAS) across five samples. A descriptive correlation research was conducted in the Philippines and Thailand, and five data sets were generated using self-reported and online questionnaires. Exploratory factor analyses were used to explore the factorial structure of the MAAS. Confirmatory factor analyses were performed to test measurement invariance across samples. Concurrent validity was tested by examining relationships between the MAAS and psychological well-being (PWB). A unidimensional structure of the MAAS was documented across the five samples. The MAAS demonstrated measurement invariance across samples for both English and Thai versions. Concurrent validity was displayed through significant correlations with PWB. This study produced evidence to support the construct validity, concurrent validity, and reliability of the English and Thai versions of MAAS. This study was not registered.

The reagents and raw materials used, as well as the products obtained (bio-oil, reaction condensates, polyols and sugar phases) were characterized by elemental analysis, infrared spectroscopy, thermogravimetry and high performance liquid chromatography with mass spectrometry. The heating value of the bio-oils is higher than that of the original biomass (higher heating value of Eucalyptus sawdust bio-oil 29 MJ/kg versus 19.5 MJ/kg of the original Eucalyptus sawdust). The analyses of the bio-oils allowed to identify the presence of high added-value compounds, such as levulinic acid and furfural. Finally, a study of the accelerated aging of the liquefied biomass showed that the biofuel density increases with the storage time due to the occurrence of repolymerization reactions.