Background: Dental education blends theoretical and practical training to prepare students for independent patient care. This study examines the confidence levels of dental students in Umeå regarding independent performance of general dentistry tasks, and whether this confidence changes after clinical training. Methods: Surveys were conducted before and after a summer clinical internship, with s tudents rating their comfort levels on a scale from 0 to 10 for various procedures. Results: Results from 64 initial surveys and 54 follow-up surveys showed no significant difference in confidence before and after the internship. However, confidence levels varied based on whether students had practiced specific tasks during the internship. Students felt least confident in managing acute dental trauma and treating cavities in young children, while they were most confident in tasks like obtaining radiographic surveys and debriding periodontally compromised dentition. Tooth extraction and dental fillings were the most practiced procedures during the internship. Conclusions: The study concludes that the internship between the ninth and tenth semesters does not notably boost students' confidence in specific dental procedures, possibly due to the short duration of the training. Further exploration, including input from clinical supervisors, is suggested to optimize clinical training in dental education.

This paper explores various methods for inspecting gravity pipes. It emphasizes that understanding the initial process of pipe prioritization is crucial before discussing inspection methods. Given the extensive gravity pipeline systems in use today, inspecting all suspected pipelines without prioritization would be extremely costly and time-consuming, especially in a large country like India. Therefore, the paper highlights the importance of using algorithms and analysis tools to prioritize which pipelines need inspection. It also describes innovative inspection techniques, such as wave and sound analysis, which can improve inspection efficiency. The research provides an overview of the pipe inspection process and discusses cost-saving algorithms that can enhance field efficiency.

There is increasing interest in automating train operations of mainline services, e.g. to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but not implemented on a large scale. Before the general introduction of new or adapted technologies can have a transformative effect on the operation of such a complex system as train operation on mainlines, they have to pass functional, interoperability and performance tests. A virtual preliminary analysis is one way to ensure a smooth as well as safe introduction and implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. To demonstrate the developed approach, a straightforward investigation of a case study is conducted using a microscopic train simulator in combination with an ATO algorithm.

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various meth-ods. In the case of domestic power distribution facilities, there are limitations in performing di-agnostic management on all facilities owing to the large number of facilities; therefore, old fa-cilities are managed by the health index assessment method. The health index assessment com-prises only facility operation data and external environmental data and is managed only for four types of distribution facilities, including overhead/underground transformers and switchgear. In the case of extra high–voltage overhead wires, there is no standard for old replacement, despite the large number of wires, such as transformers and switchgear, and the large ripple effect of power failure in the event of a power outage. Therefore, in this paper, a health index assessment methodology for extra-high voltage overhead cables was developed. In this paper, we devel-oped an economic health index assessment methodology that additionally considers risk cost, which is different from the existing health index assessment method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement criteria. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the per-spective of electric power companies through the replacement of old extra-high voltage over-head cables. In addition, from the perspective of consumers, it is expected to increase power re-liability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

Artificial Intelligence (AI) systems involve diverse components, such as data, models, users and predicted outcomes. To elucidate these different aspects of AI systems, multifaceted explanations that combine diverse explainable AI (XAI) methods are beneficial. However, popularly adopted user-centric XAI evaluation methods do not measure these explanations across the different components of the system. In this position paper, we advocate for an approach tailored to evaluate XAI methods considering the diverse dimensions of explainability within AI systems using a normalised scale. We argue that the prevalent user-centric evaluation methods fall short of facilitating meaningful comparisons across different types of XAI methodologies. Moreover, we discuss the potential advantages of adopting a standardised approach, which would enable comprehensive evaluations of explainability across systems. By considering various dimensions of explainability, such as data, model, predictions, and target users, a standardised evaluation approach promises to facilitate both inter-system and intra-system comparisons for user-centric AI systems.

The study on the sustainable utilization capacity of water resources is of great significance for the realization of sustainable water resources management and development in the water-scarce regions of Northwest China. It provides insights into the potential for sustainable utilization of these resources. To evaluate the sustainable utilization capacity of the Huangshui Basin, a comprehensive evaluation index system was constructed based on three aspects: climate factors, water resources systems, and socio-economic factors. The evaluation was conducted using two methods: the fuzzy comprehensive evaluation model and the ELECTRE III evaluation method. The results indicate that the Huangshui Basin's water resources, as a whole, exhibit a medium sustainable utilization capacity. Climatic factors and socio-economic characteristics are the main factors affecting the sustainable utilization of water resources in the Huangshui Basin. Based on the results, measures such as strengthening the introduction of external water resources, enhancing water resources management, and implementing comprehensive remediation efforts in the basin can improve the level of sustainable use of water resources. The research results can provide a reference for decision-making regarding the evaluation of sustainable utilization capacity of water resources in water-scarce areas and the optimization of water resources management in the Huangshui Basin.

Currently, urban renewal activities in China are booming. And promoting the renovation of public buildings is the key due to its large scale, high cost and significant impact to the nature and social environment. To reduce the ambiguity and uncertainty in evaluating the potential for renewal of existing public buildings, a renewal potential evaluation model combining game theory combination weighting method and cloud model theory is proposed. The paper constructs a comprehensive evaluation index system based on relevant standards and literature. Game theory is used to optimize the weights obtained by AHP and entropy weight methods to obtain a combined weight. MATLAB programming is used to calculate the comprehensive cloud parameters of the evaluation index for the potential renewal of existing public buildings and therefore generate cloud Graphs. Through case study in Nanjing of China, it has been demonstrated that the combination empowerment cloud model can objectively reflect the relationship between the fuzziness and randomness of evaluation indicators for public building renewal potential. The expression of cloud Graphs can intuitively reflect the magnitude of renewal and renovation potential and the degree of uncertainty in evaluation results. The research result provides useful references for the sustainable utilization of building resources in the era of building.

Programming languages drive most if not all of modern problem- solving using computational methods and power. Research into new programming languages and methods is essential to the furthering or improvement of computational problem-solving by making the design, implementation, and application of automation to general or particu- lar problem-solving ever easier, more accessible, and more performant. General-purpose Programming Languages (GPLs) typically are designed to be purely domain agnostic—meaning they can be applied in any field, for any kind of problem. However, this typically also makes them hard and difficult to apply in problems where non-programmers or even ex- perts with little or no GPL programming skills are required to leverage programmatic problem solving capabilities, which is why Domain Specific Languages (DSLs) come into play; they are generally more fine-tuned to- wards improving human productivity and performance than that of the machine, while making solving particular, domain-oriented problems sim- pler. In this paper, we review the literature concerning how to design and then fully implement a new DSL, with special focus on a DSL for generic problem-solving leveraging Text Processing methods—essentially, a Text Processing Language (TPL). We consider leveraging the design research paradigm and philosophy as a systematic framework for guiding research into the development of new TPLs. This work presents for the first time, new unifying theory concerning general, but also TPL-specific language engineering theory and guiding frameworks—UPLT, PLEF & PLEf. We consider quantitative but also qualitative evaluation of programming lan- guages. The SOE framework is re-introduced for this purpose too. Finally, we set the pace for future theoretical and practical research into the field of programming language engineering especially with focus on TPLs.

Transport infrastructure’s asphalt pavement deteriorates under the influence of destructive factors. Damages which have been occurred during its exploitation period are repaired, and when their further rehabilitation is economically and technically irrational, the asphalt pavement is recycled. The material from the asphalt pavement layer that has reached its limit state is milled out or broken and crushed and then is repeatedly used in the production of hot-mix asphalt (HMA) or warm-mix asphalt (WMA) mixtures. In this paper, the dynamics of the percentage recycling ratio (RR) of old asphalt pavement material was investigated. RR represents the quantity of reclaimed asphalt pavement (RAP) used in the production of HMA and WMA mixtures in Europe and the USA, divided by the total amount of RAP prepared in the country. Factors and goals affecting it are analyzed. An original system of 10 criteria that increase the RR country has been created. By applying different multiple criteria decision making (MCDM) methods and using the importance given to these criteria by 14 experts, the normalized subjective weights of the criteria were determined. Analytic Hierarchy Process (AHP), rank correlation, Average Rank Transformation into Weight - Linear (ARTIW-L) and Non-linear (ARTIW-N), Direct Percentage Weight (DPW) methods were used in the study. The results display that the RAP recycle rate is close to 100% in countries with a sustainable economic background. In the Baltic countries, it is mostly increased by the adequacy of regulatory documents, the strategy promoting asphalt recycling in the country, and the homogeneity and classifying of RAP. The number and capacity of RAP stocks, the number and productivity of asphalt milling equipment and the wear and tear of the asphalt pavement have the least influence on the increase of RR. The opinions of experts in assessing the significance of all criteria are consistent. The averages of the weights of criteria determined by four MCDM methods (AHP, ARTIW-L, ARTIW-N, DPW) made it possible to obtain more reliable results. These results can be used to make strategic decisions and to create a plan of practical actions to increase the RAP recycling rate in the developing countries.

Air quality and environmental fairness have always been an area of prime interest across the globe. The significance low-cost air quality sensing and practices spikes during the time of pan-demic and epidemics when the air becomes a threat to living beings especially human beings. The gradual innovation and enrichment in low-cost air quality sensing sensors, nodes or devices, and systems are exponentially increasing for the last three decades. This work reviews the major contributions in a) low-cost scalable air quality assessment; b) low-cost air quality sensors, sensing approaches and technologies; c) low-cost state-of-the-art gas sensors fabrication methods (MEMS and CMOS); d) low-cost gas sensors measurement configurations and assemblies; and e) low-cost air quality sensors calibration and testing systems. A systematic review of past work with a goal to assist end-users, public health facilities, state agencies, researchers, scientists and air quality protection agencies has been rendered in this work. Starting from sensors electrodes to IoT based mobile smart nodes; all have been introduced in this article.

Comparing sonification with visualization is like comparing apples and oranges. While visualizations are ubiquitous to the public and have established names, principles, application areas, and sophisticated designs, sonifications tend to be unique, self-made and completely new to users. In this study we developed a rudimentary visualization that is related closely to the principle of the sonification designs that we want to evaluate. In addition, we implemented a prototypical sonification that uses the most common mapping principles. Experiment results show that participants perform similarly well using the rudimentary visualization and the prototypical sonification, which is much better than chance but significantly worse than using our new sonification results. We therefore argue that both rudimentary visualization and prototypical sonifications can serve as a suitable benchmark to evaluate new sonifications designs against.

SacreBLEU, by incorporating a text normalizing step in the pipeline, has been well-received as an automatic evaluation metric in recent years. With agglutinative languages such as Korean, however, the metric cannot provide a conceivable result without the help of customized pre-tokenization. In this regard, this paper endeavors to examine the influence of diversified pre-tokenization schemes –word, morpheme, character, and subword– on the aforementioned metric by performing a meta-evaluation with manually-constructed into-Korean human evaluation data. Our empirical study demonstrates that the correlation of SacreBLEU (to human judgment) fluctuates consistently by the token type. The reliability of the metric even deteriorates due to some tokenization, and MeCab is not an exception. Guiding through the proper usage of tokenizer for each metric, we stress the significance of a character level and the insignificance of a Jamo level in MT evaluation.

Tungsten balls with sub-100-μm diameter can function as probe tips for micro-coordinate measuring machines (CMMs) to measure ultraprecise workpieces such as ceramic bearings with a high aspect ratio. A high-precision measuring system was proposed to evaluate the roundness error of the self-made tungsten ball tips. The principles and mathematical models of the measuring system are illustrated, and the fabrication principle of tungsten balls is introduced. An analysis was conducted on the maximum allowable contact force and bending strength of the tungsten ball tips, and the elastic mechanism was designed based on the analysis. A ruby probe with a sphericity error of 130 nm (A-5003-0577, Renishaw Corporation) used as a reference sphere was measured to verify the system's effectiveness. Repeated measurement experiments were performed for two tungsten ball tips. The results show the roundness error of the tungsten ball-A is between 568.3 and 586.2 nm with a standard deviation of 6.6 nm while the tungsten ball-B’s roundness error is between 898.5 and 958.0 nm with a standard deviation of 19.7 nm. The uncertainty is calculated as 125.8 nm. The developed system can stably measure the roundness of the tungsten ball tips.

Fears of negative evaluation (FNE) and fears of positive evaluation (FPE) comprise a bivalent model of evaluation that can explain the etiology and maintenance of Social Anxiety Disorder (SAD). In this study we examined an extended version of this model developed by Cook et al. [1] which incorporates two related cognitive processes (concerns about reprisal and discounting of positive outcomes) as partial mediators of the effects of FNE and FPE. We built on earlier work by including a broader measure of social anxiety and comparing models for groups of participants with and without probable SAD. Structural equation modelling was utilized to test the model in a sample of 890 university students (74.8% female, mean age 29.49). We replicated the findings of Cook et al. in the overall sample and in the group with probable SAD. FNE and FPE predicted social anxiety directly and were serially mediated by concerns about reprisal and discounting positive outcomes. The model was also a good fit for those without SAD, however, in that model, FNE was no longer a direct predictor of social anxiety. The findings confirm the utility of the extended bivalent model and have implications for psychoevolutionary accounts of social anxiety.

This study delves into the realm of heuristic evaluation within usability testing, focusing on refining and applying a tailored algorithm that simplifies the implementation of the Analytic Hierarchy Process for heuristic prioritization. Addressing the prevalent challenge of disparate evaluation methodologies and the absence of a standardized process in usability testing, our research introduces a novel method that leverages the Analytic Hierarchy Process alongside a bespoke algorithm. This algorithm utilizes transitive properties for pairwise comparisons, significantly reducing the evaluative workload. This innovative approach facilitates the estimation of heuristic relevance irrespective of the number of items per heuristic or the item scale and streamlines the overall evaluation process. In addition to rigorous simulation testing of the tailored algorithm, we applied our method in a practical scenario, engaging seven usability experts in evaluating a web interface. This empirical application underscored our method’s capacity to diminish the requisite comparison count and spotlight areas of improvement for critically weighted yet underperforming heuristics. The outcomes of this study underscore the efficacy of our approach in enhancing the efficiency and organization of heuristic evaluations, paving the way for more structured and effective usability testing methodologies in future research endeavors.

Urban areas are centres of business and innovation. Freight transport is indispensable for the proper functioning of any modern urban society. Urban areas can’t function without an appropriate freight transport system, due to the need to replenish stocks of food and other goods in retail shops. The complexity of the decisions concerning implementation of measures to improve the movement of goods in the city requires tools designed to support this process. The purpose of this article is to introduce the possibility of applying the Analytic Hierarchy Process (AHP) as well as the Decision Making Trial and Evaluation Laboratory Method (DEMATEL) in choosing a set of measures and in analysing in the field of distribution logistics, which will help to solve the delivery problems and streamline the cargo flows in Szczecin, in the context of sustainable development.

Distributional word vector representation orword embedding has become an essential ingredient in many natural language processing (NLP) tasks such as machine translation, document classification, information retrieval andquestion answering. Investigation of embedding model helps to reduce the feature space and improves textual semantic as well as syntactic relations.This paper presents three embedding techniques (such as Word2Vec, GloVe, and FastText) with different hyperparameters implemented on a Bengali corpusconsists of180 million words. The performance of the embedding techniques is evaluated with extrinsic and intrinsic ways. Extrinsic performance evaluated by text classification, which achieved a maximum of 96.48% accuracy. Intrinsic performance evaluatedby word similarity (e.g., semantic, syntactic and relatedness) and analogy tasks. The maximum Pearson (ˆr) correlation accuracy of 60.66% (Ssˆr) achieved for semantic similarities and 71.64% (Syˆr) for syntactic similarities whereas the relatedness obtained 79.80% (Rsˆr). The semantic word analogy tasks achieved 44.00% of accuracy while syntactic word analogy tasks obtained 36.00%

This article is about school evaluation. The objective was to explain critically the mediating relationships between educational evaluation and the production of school knowledge from the perspective of the Dialectical Historical Materialism. With this interest, a documentary analysis was made, obtaining as result four explanatory categories: production, subsumption, distribution and exchange of knowledge, which form a concrete totality with distinctions and antagonistic relationships between them, limited by their opposite. It is concluded that the evaluation as a mediating form lacks antagonistic pair and consequently of control by opposition, emerging from the school daily as autonomous and sovereign entity, oppressive of school subjects.

Recent advances in technology have propelled Artificial Intelligence (AI) into a crucial role in everyday life, enhancing human performance through sophisticated models and algorithms. However, the focus on predictive accuracy has often resulted in opaque, black box models that lack transparency in decision-making. To address this issue, significant efforts have been made to develop explainable AI (XAI) systems that make outcomes comprehensible to users. Various approaches, including new concepts, models, and user interfaces, aim to improve explainability, build user trust, enhance satisfaction, and increase task performance. Evaluation research has emerged to define and measure the quality of these explanations, differentiating between formal evaluation methods and empirical approaches that utilize techniques from psychology and human-computer interaction. Despite the importance of empirical studies, evaluations remain underutilized, with literature reviews indicating a lack of rigorous evaluations from the user perspective. This review aims to guide researchers and practitioners in conducting effective empirical user-centered evaluations by analyzing several studies, categorizing their objectives, scope, and evaluation metrics, and offering an orientation map for research design and metric measurement.

This study aims to develop an auditory experience evaluation questionnaire to improve the presence of metaverse environments, and to derive evaluation components considering auditory presence and auditory user experience (AUX) through a survey. After conducting a survey with a total of 232 participants, five evaluation components were extracted from auditory presence and AUX evaluation factors through principal component analysis (PCA) and reliability analysis (RA): 'realistic auditory background', 'acoustic aesthetics', 'consideration of acoustic control and accessibility', 'auditory utility and minimalist design', and 'auditory consistency'. In particular, although AUX evaluation factors such as 'ease of access to sound control' have limitations in improving the sense of presence, negative factors of presence such as 'distraction due to sound' can be improved by utilizing AUX evaluation factors, so it is judged that the sense of presence in the metaverse environments can be improved by enhancing the auditory sense of presence and AUX evaluation factors according to the composition of the five evaluation components derived in this study. This study can be used as a basis for developing an auditory experience evaluation questionnaire for the metaverse platform, creating sound design guidelines, and identifying sound development priorities.

Introduction: Pre-Exposure Prophylaxis (PrEP) for HIV prevention has been implemented in several countries. Previous literature has shown that its cost-effectiveness (and, under some specifications, cost-saving character) is dependent on the reduction in price due to generics, the time-horizon and its effectiveness. The intervention has never been studied in Catalonia, a territory with extensive implementation. Methods: Economic evaluation of the implementation of HIV pre-exposition prophylaxis using administrative data from Men who have Sex with Men (MSM) who receive the treatment (at the generic price). A deterministic compartmental model and a social perspective with a micro-costing approach over the time horizon 2022-2062 are used. A baseline 86% effectiveness of PrEP is assumed. Results: Daily oral PrEP is found to be cost-saving: discounted savings in costs are attained after 16 years, and after 40 years they reach 81 million euros. In terms of health indicators, 10,322 additional discounted QALYs are generated by the intervention. Results are sensitive to sexual behavioral patterns among MSM, the price of PrEP (reduced if offered on-demand), its effectiveness and the discount rate. Conclusions: The use and promotion of PrEP in Catalonia is predicted to result in substantial health and monetary benefits because of reductions in HIV infections. Short-term investments in the promotion of PrEP will result in important cost-savings in the long term.

Establishing an effective evaluation model to analyze the actual environmental level of the multi-indicator systems is an urgent challenge. However, due to the complexity of the environmental system, the factors that determine the practical system are usually interrelated. To solve this problem, many methods have been proposed and verified. However, the disadvantage of unreasonable weight determination and only single-indicator assessment limits the practical application of these analysis methods. Here, we established an optimized entropy weight model and integrate it with the fuzzy comprehensive evaluation (FCE) method to quantify the complex environmental system. By introducing the linear programming method into the entropy weight solution, we can obtain high accuracy weight values and strong resistance to extreme data. Theoretical and simulation results demonstrate that our method can enhance the precision of weight calculation and evaluation results for multi-factor systems. Our work develops an effective method to quantify the complex environment system comprehensively and is significant to real applications of evaluation method.

Background: Physical-sports habits in adulthood constitute one of the predictors of physical, psychological and social health within healthy lifestyles. Methods: The Acquired Healthy Lifestyle Assessment Scale was applied to a sample of 788 subjects between the ages of 22 and 72 and the dimension that makes up physical-sports practice habits was analyzed. Results: 74.4% of adults have habits of physical sports practice that are not healthy or unhealthy, 18.8% tend towards health and only 6.9% are healthy. Pearson's 2 tests show a significant association between men and healthy habits, without observing changes associated with the age variable. The t-student and one-factor ANOVA tests confirm the relationship between the level of health and physical-sports practice habits depending on sex and age. Conclusions: It is necessary to promote preventive programs to increase participation in the practice of physical and sports exercise in the adult population that has unhealthy or unhealthy levels of lifestyle.

Residential burns camp programmes provide help and support to children with burn injuries by providing activities designed to build their confidence and self-esteem. Our regional burns service has been running camps for over 20 years and evaluation is an important part of assessing their effectiveness. In this study we report both qualitative and quantitative data from 10 consecutive years of burns camps. Qualitative feedback was gathered using Likert scales and free response questionnaires at the end of camp and six weeks post-camp. Three quantitative outcome measures, the Paediatric Quality of Life Inventory v4, the Children’s Revised Impact of Event Scale (CRIES8) and the Satisfaction with Appearance Scale (SWAP) were completed before and six weeks after camp. Children and their parents/carers both reported attending burns camp was helpful for them/their child; the themes of meeting other children with burn injuries and developing confidence and self-esteem were cited as reasons. Parents/carers also reported significant improvements in their child’s physical and psychological functioning post-camp in some years. These findings confirm the importance of providing burns camp programmes for children with burn injuries as part of their post burn rehabilitation.

With the advent of Neural Machine Translation, the more the achievement of human-machine parity is claimed at WMT, the more we come to ask ourselves if their evaluation environment can be trusted. In this paper, we argue that the low quality of the source test set of the news track at WMT may lead to an overrated human parity claim. First of all, we report nine types of so-called technical contaminants in the data set, originated from an absence of meticulous inspection after web-crawling. Our empirical findings show that when they are corrected, about 5% of the segments that have previously achieved a human parity claim turn out to be statistically invalid. Such a tendency gets evident when the contaminated sentences are solely concerned. To the best of our knowledge, it is the first attempt to question the “source” side of the test set as a potential cause of the overclaim of human parity. We cast evidence for such phenomenon that according to sentence-level TER scores, those trivial errors change a good part of system translations. We conclude that to overlook it would be a mistake, especially when it comes to an NMT evaluation.

The Coronavirus outbreak that began in December, 2019 became a worldwide pandemic by March, 2020. The education industry had to adapt to this new change in a speedy and most feasible way by shifting to virtual classes over the internet and other available resources. WhatsApp has turned out to be a boon in academic’s section where in all the teachers have their own subject-wise groups on the said application. This not only helps them to share the necessary information resources but also to have discussion regarding the subject matter. On the other side, this application allows easy access for the students to all the resources shared by the teacher, and they can share their assignments without much difficulty with their subject teachers. Therefore, it has become a primary tool for conducting teaching, learning and evaluation online. The researchers have tried to analyze impact of online classes and the efforts required by the students to learn online with the help of survey conducted with the sample size of 514. The survey questionnaire was grouped into 4 categories namely; Opinion on Information and Communications Technology (ICT) based Teaching, Changes in communication behavior due to ICT using WhatsApp, the main hindrance for integration of ICT (Information Communication Technology) in the teaching-learning process and disadvantages of using ICT for teaching and learning.

Obesity is associated with increased morbidity and mortality and impaired quality of life. Weight losse is associated with improvement or even cure of cardiovascular risk factors with cardiometabolic benefit. nonsurgical measures for weight loss is rarely successful in the long term. Bariatric surgery has achieved clear success in reversing the abnormal metabolic profile associated with obesity. Pre surgical evaluation is important to rule out any medical or psychological problems that increased the surgical mortality or adversely affect the outcome.

Ethics is a research field that is obtaining more and more attention in Computer Science due to the proliferation of artificial intelligence software, machine learning algorithms, robot agents (like chatbot), and so on. Indeed, ethics research has produced till now a set of guidelines, such as ethical codes, to be followed by people involved in Computer Science. However, a little effort has been spent for producing formal requirements to be included in the design process of software able to act ethically with users. In the paper, we investigate those issues that make a software product ethical and propose a set of metrics devoted to quantitatively evaluate if a software product can be considered ethical or not.

In most world’s countries, scholarship evaluation for tenure and promotion continues to rely on conventional criteria of publications in journals of high impact factor and grant funding. Continuing to hire and promote scholars for their achievements in research and in securing research funds exposes universities at risk because students, directly and indirectly through government funds, are the main source of revenues for academic institutions, whereas talented young researchers are those who actually carry out most of the published research. Purposeful scholarship evaluation needs to include all three areas of scholarly activity: research, teaching and mentoring, and service to society. Young scholars seeking tenure and promotion benefit from the practice of open science because it provides better and more impactful results with respect to each of the three areas of scholarship.

This research centers on the Mulberry-Dyke and Fish-Pond System in Digang Village, Huzhou, exem-plifying the traditional cyclic agricultural models of China. The study's objective is to evaluate its integral value concerning agricultural production, ecological environment, and heritage conservation. Employing the Analytical Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methodologies, we developed a comprehensive evaluation framework comprising 8 dimensions and 29 factors, aimed at assessing the provisioning, regulating, and cultural services of this ecosystem. The findings indicate a robust performance of the ecosystem services in Digang Village's Mulberry-Dyke and Fish-Pond System, with cultural services significantly standing out. In contrast, the regulating services appeared relatively weaker, pinpointing shortcomings in mulberry land management, while the provisioning services demonstrated substantial strength. These insights are pivotal for comprehending the system's ecosystem service values, highlighting areas for managerial improvements, and guiding future assessment and management strategies. This study contributes theoretical insights and empirical experiences for future evaluations of the Mulberry-Dyke and Fish-Pond System's ecosystem services.

With the spread of compulsory education emerged school management problems continued, and the quality of school management in compulsory education has attracted a great deal of attention in China. However, the application of information technology in the field is not yet detailed and wide, resulting in problems of heavy workload and high difficulty in the whole evaluation process. Accordingly, we use big data technologies such as Apache Spark, Apache Hive, and SPSS to carry out data cleaning, correlation analysis, dynamic factor analysis, principal component analysis, and visual display on 1760 sample data from 40 primary and secondary schools in Q Province in China, and constructs a model school management of quality evaluation in the compulsory education stage, which reduces the 22 management tasks required for previous evaluation to 5, greatly reducing the workload and difficulty of evaluation. It has improved the efficiency and accuracy of evaluation, and further promoted the simultaneous development of education of five domains and education equity in the compulsory education stage.

Member states of regional intergovernmental organisations exert institutional discursive power by influencing regional narratives and policy frameworks. This influence operates through formal communications that validate specific viewpoints. The effectiveness of such discursive practices is predicated on the organisation's credibility, structure, and regional geopolitics. The interaction between institutional rhetoric and national interests often yields nuanced discursive outcomes, reflecting a synthesis of supranational and state-level priorities. At the centre of interstate dynamics is the pursuit of institutional discursive power, which has become a crucial avenue for states to participate in the creation of international governance guidelines. We consider the institutional discursive power of nations within Regional Fisheries Management Organisations (RFMOs) to see how it impacts the establishment of global fisheries governance systems and order. As intergovernmental organisations, RFMOs have significant influence on global fisheries governance. In order to evaluate and compare the institutional discursive power of different countries within RFMO, this study has developed an evaluation framework and model that includes competitiveness, constructiveness, and influence as its three main dimensions. It does this by drawing on a thorough understanding of the institutional discursive power within RFMO and its formation mechanisms, as well as by integrating theoretical principles from evaluation science.

Pipelines are regularly trenched and then forgotten, just allowed to run till failure and producing an overall incredibly poorly run system that is ripe for improvements. One of the most needed areas for improvement are proactive methods for condition assessment of existing pipelines. This can be divided into two main categories: proactive condition assessment technologies and nonstructural proactive condition improvement technologies. The objective of this paper is to identify the best option available on the market for both these areas of proactive condition assessment for existing pipelines. The compared proactive condition assessment technologies include Acoustic Resonance Testing, Ultrasonic Thickness Measurement Testing, Phased Array Ultrasonic Testing, Pulsed Eddy Current Testing, and the Multisensor ROV. The technologies compared for nonstructural proactive condition improvement were Jetting, Pigging and also included the main requirements for a proper catalog of pipe information that can be used to produce a ranked system for assessing which pipes are at highest risk for failure and can be used to efficiently direct resources for pipe maintenance. The final conclusion was that Acoustic Resonance Testing and the Multisensor ROV are the two best products available for the proactive condition assessment of existing pipelines available on the market from their versatility of application and amount of information gathered during pipe inspection. The best option available in the group of nonstructural proactive condition improvement technologies was pigging for its incredibly low risk and low social impact as well as potential for improvement in the near future. It was also concluded that every agency would be better off with a catalog of the pipe material, age, length, diameter, and burial depth to know the location of every pipe an agency owns as well as to rank every pipe in terms of risk of failure and impact of said failure to most efficiently direct resources.

Background and Objectives: Down syndrome (DS) is the most common chromosomal disorder in the world. It is caused by the imbalance of the chromosomal constitution of 21, by free trisomy, translocation or mosaicism. Children and adolescents with Down syndrome have immune dysregulation and are more susceptible to infections. This study aims to evaluate hospitalizations of children and adolescents with DS in the pediatric ward of Botucatu Clinics Hospital (HCFMB), to classify the population of children included in the study regarding age, diagnosis, outpatient follow-up, length of stay and need for Intensive Care Unit (ICU). Thus, it will be possible to improve care for these children, aiming to reduce these hospitalizations. Materials and Methods: It was an observational, cross-sectional study, with retrospective data collection from the last 10 years of hospitalization, from January 2013 to December 2021, of children and adolescents with DS, in the pediatric ward, emergency room and ICU of HCFMB. Children hospitalized in this period in the pediatric ward and ICU, in the age range of 30 days to 15 years (age of acceptance for admission to this service) were included in this study. Those who at some point had the exclusion of the diagnosis of DS were excluded. The evaluation of comorbidities that culminated in the need for hospitalization in this population can be the focus of actions to improve diagnoses and conducts for this population, to prevent worsening and hospitalizations in future populations. Results: The statistical analysis of the data was performed. In this analysis, 80 children with DS were evaluated, with a total of 283 hospitalizations and it was noticed that 46 of them had more than one hospitalization in this period. The most prevalent age group was 1 to 3 years, and the main cause was due to problems in respiratory system (99 cases). Among respiratory causes, the main cause of hospitalization was due to pneumonia, in 50% of cases, followed by acute respiratory failure, in 14%. The average hospitalization time was 8 days and in 49 hospitalizations the children required the ICU. The main cause of hospitalization in the ICU was due to respiratory causes (36%), followed by cardiac malformations (14%). During the ICU hospitalizations, there were 13 deaths, and we observed a higher prevalence of heart conditions and, in some cases, positive urine cultures in these children. Conclusions: preventive actions, such as vaccinations and improved monitoring of these children, without outpatient follow-up or during hospitalization, should be carried out. Thus, it has been developed a proposal for a risk score for mortality in children and adolescents with DS admitted to the ICU, and those patients with five or more points should be monitored more closely. A meeting will be held with the genetics, cardiology, and pediatric ICU teams to discuss this score and propose a surveillance plan for these patients at the HCFMB and potentially for the pediatric community in the future.

Although numerous citrus varieties have recently been developed to enhance their quality, information on their quality characteristics is limited. We assessed the quality characteristics of Yellowball, a novel citrus variety, by evaluating its appearance, storability, sensory properties, functionality, and metabolite profiles and comparing these characteristics with those of its parent varieties: Haruka and Kiyomi. The metabolite profiles between the citrus varieties differed significantly, resulting in distinct physicochemical and functional qualities. The storability of Yellowball was significantly increased compared with that of its parent varieties owing to its strong antifungal activity and unique peel morphology, including the stoma and albedo layers. While we did not investigate the volatile compounds, overall functional activities, and detailed characteristics of each metabolite, our data provide valuable insights into the relationship between citrus metabolites, peel morphology, physicochemical properties, and storability and demonstrate the potential of Yellowball as a promising variety in the citrus industry.

Root crops grow in the soil deeply and bond with soil closely, which results in that the process of the separation between soil and root becomes the most difficult during the harvesting processes. In order to harvest root crops efficiently, the mechanical harvesting has become the main developing trend. However, high power and high damage rate are still occurred when mechanical harvester gets in touch with the roots. In this paper, we review the research of the development and evaluation of the mechanical harvesting of root crops and its performance optimization on the past years. The process of soil separation mainly consists in the initial separation between root and the ground and further separation between root and adhered soil. In general, the soil-cutting operation in the initial separation and the sieving mechanism in the further separation require high draught and power. And the dramatic friction, impact, pressure and so on, which happen in the components and soil-roots, are the key reasons to lead to root damage. The optimization of harvesting methods and parameters, including the digging shovel shape, working conditions, vibration, and screening way, is more significant in improving the harvesting performance. But there are still some limitations in the research and application of the mechanical harvester for root crops. Future research is suggested to focus on the development of the soil break-up when the digging shovel cutting soil, the insight into the interaction between soil and roots by different external compression loads, and the long-term studies to verify the high-efficiency and low-damage performances of mechanical harvester in practical application.

With the branding development of the international exhibition industry and the increase in the number of mergers and acquisitions of exhibitions, the assessment of the brand value of exhibitions has gradually come into the view of governments, investment and financing institutions and researchers. Compared with the brand value assessment of consumer goods and industrial sectors, the brand value assessment of exhibitions, especially B2B exhibitions, has special characteristics. A model for brand value assessment of B2B exhibitions is proposed, which can not only provide a reference for decision-making on M&A behaviour of exhibitions, but also provide a decision-making tool for government exhibition brand promotion. The aim of this paper is to explore the feasibility of constructing an AHP-based conceptual model for brand value assessment of exhibitions in Shanghai through a hybrid study. The applicability of the conceptual model for exhibition brand value assessment is empirically demonstrated by analysing six steps, including establishing pairwise comparison matrices, calculating the maximum eigenvalues and normalised eigenvectors of each comparison matrix, conducting consistency checks, group decision matrix synthesis and weight allocation of exhibition brand value assessment indicators. On this basis, the three values of the model in practice and theory are explored separately. The research results can provide better brand value assessment and development support for exhibition stakeholders and improve the sustainability of exhibition brands.

Objectives: Few studies in literature evaluate the "mean measure" of root divergence. Most of them are linear measurements, they hardly describe the dental furcation conformation. It is left to the subjectivity of the operator deciding whether a furcation is convergent or divergent. The goal of this study is to create a visual evaluation method to overcome these problems giving a conformation of the entire interradicular space. Material and methods: A user-friendly software (Paint®, Windows10®) was used to measure endo-oral radiographs of upper and lower molars. Three kinds of measurements were taken. Three operators used the software to measure 20 radiographs, then the technique was repeated on 250 radiographic images to identify an average measurement. The ratio of these three measurements allowed to develop a new visual evaluation method of the interradicular space. Results: Intra and inter-operator reproducibility was statistically assessed on a sample of 20 anonymous endo-oral radiographs measured by 3 blind operators. Then, a sample of 250 anonymous endo-oral radiographs were measured by a blind operator and were statistically evaluated to identify an average value to define a main conformation of the interradicular space. Measurements made by the 3 operators on the 20 radiographic images showed that the technique is reproducible, and a mean value of the interradicular space was obtained. Conclusions: A new anatomical evaluation of the interradicular space in its entirety, which could help the clinicians in the therapy of furcated molars, can be obtained.

Chess is an interesting game for artificial intelligence research and an entertaining hobby and sport for a growing number of people. However, humans differ greatly in their ability to play. Typically, the Elo rating is used to determine a player's skill and to predict who will win. When differences in Elo are too great the weaker player is almost guaranteed to lose. While on one hand, the Elo rating allows players to be matched to equally well-playing opponents, it also to some degree restricts the games to be played between equally strong opponents since otherwise the result is known beforehand. Here a handicap system where stronger players remove pieces at the start of the game is evaluated. Specifically, the effect each removed piece or combination of pieces have on a player. Interestingly, pieces do not always reduce the Elo of a player by a predefined amount, but their effect depends strongly on the player's current Elo. The results presented here are from playing the computer engine Stockfish because data about humans playing this scheme is limited. However, the results make direct predictions about the effect of piece removal on Elo.

The number of artificially ripened pineapples is outnumbered than the naturally ripened pineapples. However, there is a lack of understanding between artificially ripened and naturally ripened pineapples. Thus the inquiry was anticipated to explore the physicochemical changes and organoleptic acceptability of the naturally ripened and artificially ripened pineapples. Farmers used different chemicals such as calcium carbide, ethylene, besides growth hormones to reduce production loss. Here we evaluated the content of moisture, ash, protein, fat, crude fiber, reducing sugar, total sugar, titratable acidity, sucrose, and vitamin C in both naturally ripened and artificially ripened pineapples. Artificially ripened pineapples showed a significantly lower vitamin C than naturally ripened ones, but arsenic content was nil in both samples. In the case of color and appearance, there was no significant difference between the two samples, but in case of the other organoleptic properties, such as flavor, sweetness, sourness, the natural one was more acceptable. Thus naturally ripened pineapples are more beneficial to consumers than artificially ripened ones.

Background: Transposable elements (TEs) constitute the vast majority of all eukaryotic DNA, and display extreme diversity, with thousands of families. Given their abundance and diversity, TEs discovery and annotation becomes challengeable. At present, tools and databases have built libraries to mask TEs in genomes based on de novo- and homology-based identification strategies, but no consensus criteria about which tools should be used have been proposed. Results: In the de novo-based strategy, we compared performances of TE libraries developed by four commonly used tools, including RepeatModeler, LTR_FINDER, LTRharvest, and MITE_Hunter, by using a simulated genome as a standard control. The results showed that the performance of RepeatModeler decreased as it was combined with either LTR_FINDER or LTRharvest. Combination of RepeatModeler and MITE_Hunter showed better performance than RepeatModeler and MITE_Hunter alone. In the homology-based strategy, we evaluated different sources from a taxonomic point of view to build an accurate TE library. When we selected a library from databases to identify TEs for Arabidopsis thaliana genome, the library from a genus genetically closer to Arabidopsis achieved better performance than other genera with further genetic distance. Without the Arabidopsis, combination of top three genera closer to Arabidopsis showed better performance than combination of all genera. Conclusion: This study proposes a series of recommendations to perform an accurate TE annotation: 1) For de novo-based strategy, RepeatModeler and MITE_Hunter are suggested to build a TE library; 2) For homology-based strategy, it is recommended to use library of genus genetically close to the species rather than use combined library from all genera.

In recent years, there have been concerns raised about construction industrialization in China, which have initiated a wave of policy change in both governmental and industrial organizations in order to change the mode of conventional construction. However, the current development level of regional construction industrialization (RCI) in China has not been well-characterized. This study screened preliminary index systems in five dimensions: technical, economic, sustainable, enterprise development and development environment. Based on the data gathered from the questionnaire surveys and subsequently analyzed, twenty-two critical evaluation indicators were identified. Analytic Hierarchy Process (AHP) was then employed to determine the weighting of each indicator. The evaluation method of the development level was formulated on the basis of the evaluation criteria. Jiangsu Province was used as an example in this study, with the development level of this province being comprehensively examined using a combination of the index system and evaluation method. The results show that Jiangsu has a relatively high RCI development level. The data from analysis scores of five dimensions and twenty-two indicators show that the index system is feasible, with evaluation results being consistent with actual practice. These findings provide a good practical reference for making decisions about how best to guide the development of RCI.

Embryonic and larval Danio rerio is increasingly used as a toxicological model to conduct rapid in vivo tests and developmental toxicity assays; the zebrafish features as high genetic homology to mammals; robust phenotypes; and its value in high-throughput genetic and chemical screening have made it a powerful tool to evaluate in vivo toxicity. New methodologies of genome editing as CRISPR/Cas9; ZFN or Talen make it a suitable model to perform studies to pair human genetic diseases as well. This review surveys recent studies; employing zebrafish as experimental model; comparing it with other in vivo and in vitro models; presenting zebrafish as a potent vertebrate tool to evaluate drug toxicity to facilitate more extensive; easy and comprehensive knowledge of new generation drugs.

In the rapidly evolving landscape of the AI era, the measurement of Computational Thinking ability among Computer Science (CS) University students is of paramount importance. This study introduces UniCTCheck, a novel method designed to assess the main components of Computational Thinking in CS students. Utilizing two key instruments, namely the web application CTScore and the psychometric scale CTProg, this research aims to precisely evaluate seven core components of Computational Thinking and six programming concepts skills essential for CS students. The study, conducted at Rey Juan Carlos University and Atlantic Technological University Galway, involved a diverse sample of students from different year levels and program specializations. Through a rigorous research design, including sampling strategies and data collection tools, this study seeks to address critical research questions related to measurement of variations in students' Computational Thinking and programming skills by gender, university level, and location. By shedding light on the significance of Computational Thinking and programming in the educational realm, this research contributes to the existing literature and underscores the essential role of computational skills in the modern era.

The focus of this article is the evaluation of the quality and the degree of community engagement in an expert-based, public-health communicative intervention for Alcohol Use Disorder (AUD). In 2023 the Canadian Alcohol Use Disorder Society collaborated with a grass-roots community health group, a regional health authority, and an academic participatory researcher to organize a working group to mount a social-marketing campaign to increase community support for AUD medical treatment in family-practice settings in a rural community in British Columbia. The partnership working group conducted a series of activities in the school system, the town council, and the community. This article covers the formative evaluation and the summative evaluation of the working group's effectiveness. The formative evaluation ("lessons learned" and "recommendations") consists of consensus evaluations of the quality of each activity using a variety of data sources. The formative evaluation followed improvement science methods and used consensus meetings to provide and reflect on formal and informal feedback. Formative results reflect the consensus of the participants in the working group and they record the reactions in the community. The summative evaluation measures evidence of community engagement found in transcribed text from meeting minutes. The summative evaluation used theory-based frameworks and text data visualization to assess the engagement dynamics of the working group. The summative evaluation helps to put the formative evaluation into perspective as communicative action. The summative evaluation validates the formative evaluation by revealing the communicative dynamics of engagement which resulted in the community’s increased capacity to understand and support Alcohol Use Disorder Treatment options. The working group and the entire intervention was seen by the participants and the public as a success and capable of replication. In a small community, it instilled new understandings and attitudes, bringing an emerging awareness of medication as an optional health mitigation strategy for Alcohol Use Disorder. Our study furthers this overall assessment by using theoretical constructs and analysis of communicative records to trace engagement characteristics of interest to researchers, societies, and community groups contemplating similar interventions in the future. The study also validates the effectiveness of communicative analysis as a measure of social-marketing for expert-based public health interventions.

Amazona amazonica, popularly known as the mangrove parrot, belongs to the order Psittaciformes and is widely distributed across South America, occurring in all regions of Brazil. Although this species is commonly admitted to veterinary care, detailed hematological data are scarce. These data are crucial for guiding clinical interventions, monitoring specimens in human care environments, and providing research references. Hematological reference intervals were established for man-grove parrots kept in a fauna management establishment located in the Amazon biome in the state of Pará, Brazil. The study included 32 Amazona amazonica parrots. Average values for the analyzed analytes in the complete blood count (CBC) were: red blood cells (RBC) 2.42 million/µL; hemoglobin 15.92 g/dL; hematocrit 50.31%; MCV 205.47 fL; MCHC 31.7%; MCH 66.73 pg; white blood cells (WBC) 6,281.4 cells/µL; heterophils 2,671.1 cells/µL; lymphocytes 3,452.27 cells/µL; eosinophils 0 cells/µL; basophils 22.63 cells/µL; monocytes 106.41 cells/µL; thrombocytes 29.44; PPT 6.71 g/dL. Morphological characteristics of the cells were similar to those of other parrots. This research is pioneering in deter-mining hematological reference intervals for mangrove parrots under human care in a holding facility in the Amazon biome. These data can be used as a reference for animals of the species raised under similar conditions.

The pursuit of materials that offer both wear comfort and protection for functional and protective clothing has led to the exploration of weft-knitted spacer structures. Traditional cushioning materials such as spacer fabrics and laminated foam often suffer from deformation under compression stresses, thus compromising their protective properties. This study investigates the enhancement of the force absorption, stress-strain and thermal properties of weft-knitted spacer fabrics with inlays. Surface yarns with optimal stretchability and thermal properties are used and combined with elastic yarns in various patterns to fabricate nine different inlay samples. The mechanical and thermal properties of these samples are systematically analyzed, including their compression, stretchability, thermal comfort and surface properties. The results show that the inlay spacer fabric exhibits superior compression properties and thermal conductivity compared to traditional laminated foam and spacer fabrics, while maintaining stretchability, thus providing a better performance than traditional fabrics for protective clothing and wearable cushioning products. This study further confirms that the type of inlay yarn and inlay structure are crucial factors that significantly influence the thermal, tensile and compressive properties of fabric. This research provides valuable insights into the design and development of advanced textile structures to improve wear comfort and protection in functional garment applications.

Childsmile is Scotland’s national child oral health improvement programme designed to reduce inequalities in oral health and ensuring universal access to NHS dental services by working closely with children and their families. Research has shown that parents with more dental concerns are less likely to bring their children for regular preventive dental check-ups. Therefore, a communication toolkit named ‘Chatterbox’ was created to help families access dental care services. This study aimed to evaluate the acceptability of Chatterbox from the perspective of parents with young children and from staff who work with them. Thirty parents of young children, volunteers, and staff affiliated with three third-sector family support organisations in Dundee participated in in-depth interviews, focus groups, and observations to assess the objectives of Chatterbox. Framework analysis was conducted to capture the themes, patterns, and findings triangulated using observations and field notes. Chatterbox was found to promote effective communication, identify barriers to dental attendance, provide a platform for reflection, convey the complexities of daily life, and boost parents' confidence to seek assistance. Chatterbox has the potential to help parents in accessing preventive dental care for their young children, when used with trained support workers.

This paper thoroughly assesses the ARM and RISC-V architectures in the context of High-Performance Computing (HPC). It includes an analysis of Docker, Kubernetes, and KVM virtualization integration. Our study aims to evaluate and compare these systems' performance, scalability, and practicality in a general context and then assess the impact that might have on special use cases, like HPC. ARM-based systems exhibited better performance and seamless integration with Docker and Kubernetes, underscoring their advanced development and effectiveness in managing high-performance computing workloads. On the other hand, despite their open-source architecture, RISC-V platforms presented considerable intricacy and difficulties in coordinating with Kubernetes, which hurt their overall effectiveness and ease of management. The results of our study offer valuable insights into the practical consequences of implementing these architectures for HPC, highlighting ARM's preparedness and the potential of RISC-V while acknowledging the increased complexity involved and significant trade-offs at this point.

Competent authorities of many countries, including Belgium, impose control measures (preventing wild bird access to feeders and water facilities, indoor confinement of captive birds, or fencing off outdoor ranges with nets) to professional and non-professional keepers of birds to prevent the spread of avian influenza (AI). Flemish laying hen farmers (FAR, n = 33) and private keepers of captive birds (PRI, n = 263) were surveyed about their opinion on, and compliance with, AI-measures legally imposed during the most recent high-risk period before this survey in 2021. Participants answered questions on a 5-point Likert scale (1 = the worst, 3 = neutral, and 5 = the best). FAR indicated better compliance with the AI-measures compared to PRI, except for confinement with nets. PRI and FAR perceived the level of compliance with AI-measures by other private bird keepers to be lower compared to themselves. FAR regarded the AI-measures as more effective than PRI. To prevent the spread of AI more effectively, national authorities could focus on information campaigns explaining to private bird keepers, in particular, the need for the various control measures that they impose, implement alternative control measures that have broader support or implement stricter enforcement of the control measures.

The objective of this study is to analyze the assessment practices in primary education and how they relate to the valuation of the learning process. It seeks to understand the perceptions of teachers and students regarding assessment and to observe classroom activities, as well as to analyze the assessment instruments used. The method used is a mixed approach that combines qualitative interpretations of the participants’ realities with a phenomenological analysis to reflect on the evaluative practices. The results indicate a contradiction between what is said and what is done in terms of evaluation, with a tendency to use written tests and traditional exams instead of a combination of techniques that allow for a significant evaluation of student learning. In addition, significant differences are observed among teachers regarding the importance they give to evaluation within their practices and evaluative models.

Background: With the rapid improvement of the healthcare technologies, security and privacy of the most sensitive data, health data is at risk. Protecting patient privacy has many components, even though the data are in electronic format. Although patient privacy is thoroughly discussed in the literature, there is no study presenting all components of patient privacy protection. Methods: In this study, a complete evaluation framework is presented, as an evaluation tool, an inventory is developed, reliability and validity of the inventory is examined. Study is conducted in three phases: Conceptual framework development, inventory development and an evaluation case study. In the evaluation, fuzzy conjoint analysis is employed to handle the subjectivity and am-biguity. As the result of the evaluation, the institution is given a patient privacy protection ma-turity grade, between 1 and 5, where 1 is the worst and 5 is the best grade. Results: In the case study, XXX’s biggest hospital, employing 800 nurses, is evaluated. Half of the nurses, 400, have partici-pated in the study. Literature tells healthcare institutions do not invest enough to protect patient privacy, and the study results support this finding. Institution’s maturity grade resulted as level 2, which is bad. Conclusion: The study measures he privacy maturity with many evaluation com-ponents. Result of the evaluation explains to the patients and the public if their data is safe or not. With this maturity grade, patients have an idea about which institution to choose, public can conclude the institutions’ reliability in terms of patient privacy.

Protected areas serve as an effective mechanism usually supported by a statute to conserve and protect wildlife-rich areas worldwide. Such extensive external management needs elaborate planning, regular monitoring, and periodic assessment of results. Thus, management effective evaluation (MEE) has emerged as one of the major tools for quantifying the performance of any protected area, globally since 2006. India has successfully conducted a complete round of management effectiveness evaluation of all its terrestrial protected areas (except conservation reserves and community reserves), with 25 such areas already undergoing a repeat assessment. Simultaneously, India biennially carries out a country-wide status of forest cover in all its states and union territories. This study has correlated the trend in change of forest cover for the states that contain those 25 repeat evaluated protected areas with their change in MEE scores over the same period. Our study found a positive correlation between the change in forest cover and the change in management effectiveness score from 2005-06 to 2018-19. Owing to increased protection regimes in the PAs including the degraded areas if they make part of such areas, the habitat often shows recovery. Effective habitat conservation is thus intertwined with the monitoring and preserving the wildlife populations in the protected areas, thereby, reduction in forest cover equally impacts the management scores. However, in states where the loss in forest cover has been reported, more protected areas need to be assessed to plan complementary strategies for both habitat and species conservation.

The advancement of sequencing technology and molecular breeding methods have provided technical support and assurance for accurate breeding. Genomic Selection (GS) utilizes genomic information to improve livestock breeding and, it is more accurate and more efficient than traditional selection methods. GS has been widely applied in domestic animals breeding, especially in cattle. However, there is still limited study on the application and research of GS in sheep and goat. In this paper, we outlined the principle, analysis methods, the influential factors of GS, and elaborated on the research progress, challenges, and prospects of applying GS in sheep and goat breeding. Through the review of these aspects this paper is expected to provide valuable references for the implementation of GS in the field of sheep and goat breeding.

Introduction: The World Health Organization (WHO) recommends visual inspection with acetic acid (VIA) for cervical cancer screening (CCS) in lower-resource settings; however, quality varies widely, and it is difficult to maintain a well-trained cadre of providers. The Smartphone-Enhanced Visual Inspection with Acetic acid (SEVIA) program was designed to offer secure sharing of cervical images and real-time supportive supervision to health care workers providing screening in semirural Tanzania, in order to improve quality and accuracy of visual assessment of the cervix for treatment. The purpose of this evaluation was to document early learnings from patients, providers, and higher-level program stakeholders, on barriers and enablers to program implementation. Methods: From September 9th to December 8th, 2016, observational activities and open-ended interviews were conducted with image reviewers (n= 5), providers (n=17), community mobilizers (n=14), patients (n=21), supervisors (n=4) and implementation partners (n=5) involved with SEVIA. Sixty-six interviews were conducted at 14 facilities, in all 5 of the program regions. Results SEVIA was found to be a highly regarded tool for the enhancement of CCS services in Northern Tanzania. Acceptability, adoption, appropriateness, feasibility, and coverage of the intervention were highly recognized. It appeared to be an effective means of improving good clinical practice among providers and fit seamlessly into existing roles and processes. Barriers to implementation included network connectivity issues, and community misconceptions and adoption of CCS more generally. Conclusion: SEVIA is a practical and feasible mobile health intervention and tool that easily integrated into the National CCS program to enhance quality of care. With the introduction of HPV DNA testing as a primary screening strategy for cervical cancer prevention in settings such as Tanzania, the role of a mobile health platform for program surveillance, tracking follow-up care, and quality assurance of visual assessment of the cervix for treatment (in women who test positive for high-risk HPV) further supports the importance of programs, such as SEVIA, in low resource contexts. Further expansion of the program, especially to rural areas where screening providers can benefit from virtual support for screening services through the use of the mobile App, could strengthen the delivery of services within the national cervical cancer prevention program.

This study aims to assess the operational capabilities of disaster and emergency management re-sources (DEMRs), which are pivotal in mitigating risks and minimizing losses amid the increas-ing frequency of disasters. The research constructs an effective operational capability evaluation system for DEMRs, encompassing four key aspects: resource planning, organizational manage-ment capability, resource support capability, and information processing capability. It focuses on identifying the factors that influence the effective operational capability of DEMRs in China and Korea, comparing and analyzing the relative importance and priority of each evaluation domain and indicator within these countries to enhance DEMRs' operational effectiveness. The method-ology involves calculating and ranking the weight of the four domains, with findings indicating that organizational management capability is most significant in China, whereas resource sup-port capability is prioritized in Korea. A comparative analysis of the local weight of indicators within each domain revealed the largest discrepancy between China and Korea in the infor-mation processing capability domain. The study concludes by calculating global weights, identi-fying fast response capability and resource allocation capability as the most impactful factors on DEMRs' operational capability, highlighting their critical role in disaster and emergency man-agement.

The high genetic diversity of the tomato and its high micronutrient content make this fruit very interesting from an economic and nutritional point of view. The genetic erosion suffered by this crop, due to breeding objectives based on yield and marketing, makes it necessary to return to the origins in search of the nutritional and organoleptic quality lost in traditional varieties. In this study, the agronomic, physical, organoleptic and nutritional characteristics of eighteen F1 hybrids obtained by crossing fourteen traditional varieties, previously selected for their quality, were studied to select genotypes of superior quality that could be candidates for new. All parameters studied were strongly influenced by genotype, showing a wide range between cultivars. Principal Component Analysis revealed the characteristics of each hybrid that made it stand out from the others. Some hybrids (H3, H4, and H6) stand out because of their high concentration of active compounds, others (H16, H15, H10, H17, H9, and H11) because of agronomic performance and high content of β-carotene, and H5 was the only one to contain chlorophyll in their ripe fruits. Finally, the evaluation index allowed the selection of five hybrids with interesting characteristics, combining good yield performance and high quality

Interactions of different factors in differently tilled faba bean agrosystem is still insufficiently studied and evaluated. For these reasons we studied the results of long-term field experiment, which was carried out in the Research Station of Vytautas Magnus University, Agriculture Academy (Lithuania). The aim of this study is comprehensively evaluating the effect of the deep and shallow ploughing, deep cultivation-chiseling, shallow cultivation-disking, and no-tillage systems for faba bean cultivation on the much-interacted factors, relations between them and strength of impact by the integrated evaluation method using complex evaluation index (CEI). Calculations showed that the influence of the no-tillage system was the greatest on the faba bean agrosystem than other system used. Shallow cultivation was more efficient than deep and shallow ploughing and deep cultivation systems. In the deep ploughing system, there were calculated more minimal, i.e. close to 1 as the CEI value, which showed DP ineffectiveness.

European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills skills gap and/or enables acquisition of new ones related to the planning and implementation of such solutions can empower local/ regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents.

A series of pyrazolopyrimidines derivatives 4– 11 were synthesized using 1-(6-(3-methoxyphenyl)-4-methylpyridazin-3-yl)-1H-pyrazolo [3,4-d] pyrimidin-4-amine 3 as a starting material. The detailed synthesis, structure assignments of the novel compounds based on chemical and spectroscopic evidence, spectroscopic data, pharmacological properties and molecular docking are reported. The pharmacological evaluation illustrated that many of these compounds have good analgesic, anti-inflammatory and antimicrobial activities.

Post-evaluation of ecological redevelopment is a good method for its achievements. The eco-engineering technologies and achievements of landscape water reconstructed from aquaculture ponds in Shanghai Chenshan Botanical Garden have been introduced in this study. The sediments and water quality were also sampled and tested for basic physicochemical parameters and heavy metal concentration. The ecological redevelopment of landscape water reconstructed from aquaculture ponds was evaluated using the Nemero comprehensive pollution index method. The results shown that nutrients including organic matter, organic nitrogen and their ratio of sediment were found to be in a state of moderate pollution, while their ecological risk of heavy metals was low. Although total nitrogen and total phosphorus of water quality was really higher than that of other indexes, the decline trends of ammonia nitrogen, total nitrogen and total phosphorus was obvious presented over time. In general, this is a good example that redevelopment of water ecosystems from aquaculture ponds using eco-engineering technologies.

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. Identification and surveillance of viruses rely on understanding their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. Use of virus databases is integral to gain new insights into the biology, evolution, and transmission of viruses, and develop new strategies to manage virus outbreaks and preserve global health.

The paper addresses the problem of a statistically significant numerical evaluation of the biomechanics of respiration using the motion of the ribcage through the identification of the kinematics of the sixth rib. We report the results of an experimental campaign conducted using a RESPIRholter device prototype for efficient, comfortable, and numerical monitoring on two groups of volunteers, namely with healthy people and with chest operated patients. The results are reported in terms of statistical processing of the data extracted from the monitoring which are represented in plots of acquired motion characteristics with movement graphs in terms of angles and accelerations. This experimental campaign can be considered a first result for the construction of a database useful for a reference of diagnostics as reported by the discussed example case study.

Voice cloning, an emerging field in the speech processing area, aims to generate synthetic utterances that closely resemble the voices of specific individuals. In this study, we investigate the impact of various techniques on improving the quality of voice cloning, specifically focusing on a low-quality dataset. To contrast our findings, we also use two high-quality corpora for comparative analysis. We conduct exhaustive evaluations of the quality of the gathered corpora in order to select the most suitable audios for the training of a Voice Cloning system. Following these measurements, we conduct a series of ablations by removing audios with lower SNR and higher variability in utterance speed from the corpora in order to decrease their heterogeneity. Furthermore, we introduce a novel algorithm that calculates the fraction of aligned input characters by exploiting the attention matrix of the Tacotron 2 Text-to-Speech (TTS) system. This algorithm provides a valuable metric for evaluating the alignment quality during the voice cloning process. We present the results of our experiments, demonstrating that the performed ablations significantly increase the quality of synthesised audios for the challenging low-quality corpus. Notably, our findings indicate that models trained on a 3-hour corpus from a pre-trained model exhibit comparable audio quality to models trained from scratch using significantly larger amounts of data.

The AUC-ROC is a widespread measure to assess the performance of a binary classification model across various discrimination thresholds. Yet, it is not apt for unbalanced class problems and is misleading for early retrieval. For instance, link prediction in complex networks is an unbalanced early retrieval problem, whose goal is to offer a ranking of the nonobserved network links, prioritizing a small cohort of positive links (for which we are sure the labels are reliable) on top of a list largely populated by unlabeled links (for which the labels are uncertain). Differently from binary classification, here the evaluation focuses on how the predictor prioritizes the positive class, because the negative class does not exist and is replaced by an unlabeled class. For decades, scholars have been investigating the necessity to correct and to generalize the AUC-ROC to work for both unbalanced classification and early retrieval evaluation, this is requested in many applied domains of computational science. Here we propose the area under the magnified ROC (AUC-mROC), a new measure that adjusts the standard AUC-ROC to work for unbalanced early retrieval problems such as link prediction. Finally, we introduce the area under the generalized ROC (AUC-gROC), which unifies both AUC-mROC and AUC-ROC to provide a universal and reliable evaluation measure that can work for both classification and early retrieval problems, regardless of class proportion.This discovery represents a critical achievement, culminating in success after decades of contentious research. Its solution promises to significantly impact various domains within applied computational science.

Despite their enormous potential the use of Indoor Localization Systems (ILS) remains seldom. One reason is the lack of market transparency and stakeholders’ trust in the systems’ performance as a consequence of insufficient use of Test and Evaluation (T&E) methodologies. The heterogeneous nature of ILS, their influences, and their applications pose various challenges for the design of a methodology that provides meaningful results. Methodologies for building-wide testing exist, but their use is mostly limited to associated indoor localization competitions. In this work, the T&E 4iLoc Framework is proposed - a methodology for T&E of indoor localization systems in semi-controlled environments based on a system-level and black-box approach. In contrast to building-wide testing, T&E in semi-controlled environments, such as test halls is characterized by lower costs, higher reproducibility, and better comparability of the results. The limitation of low transferability to real world applications is addressed by an application-driven design approach. The empirical validation of the T&E 4iLoc Framework, based on the examination of a contour-based Light Detection and Ranging ILS, an Ultra Wideband ILS, and a camera-based ILS for the application of Automated Guided Vehicles in warehouse operation, demonstrates the benefits of T&E with the T&E 4iLoc Framework.

North American Whites tend to evaluate members of their own race more positively than members of other races. One exception may be White Liberals, who appear politically motivated to evaluate members of (disadvantaged) racial outgroups more positively than members of their own racial group. We confirmed this claim presently, where 75 White Liberals, 95 White Conservatives, 49 Black Liberals and 71 Black Conservatives evaluated biracial faces using explicit and implicit evaluation tests. We instrumentally ‘frustrated’ half our participants to note whether incidental anger influenced ideologically-motivated racial attitudes. Evaluations towards racial outgroups were largely unaffected by negative mood induction -White Liberals were pro-Black relative to White Conservatives, and Black Conservatives were pro-White relative to Black Liberals, independent of mood. Negative mood induction selectively influenced own-race evaluations. Black Liberals and White Conservatives became respectively more pro-Black and pro-White when frustrated.Conversely, Black Conservatives and White Liberals became respectively less pro-Black and pro-White. Frustration significantly amplified negative own-race attitudes across explicit and implicit evaluation measures for White Liberals. We speculate on some social consequences that may follow from frustration-amplified ‘anti-White’ bias across White Liberals.

The aim of this paper is the evaluation of the success of graduating with distinction in higher education (SGDHE) using the fuzzy DEMATEL method. The observation has been done using cause and effect criteria. 11 cause and 14 effect clusters have been used in this study. The study result of this work shows that all the effects are connected to the given causes and a cause-effect graph has been generated for each connection. This proposed approach is demonstrated with the empirical case of Dire Dawa University students in Dire Dawa Ethiopia.

This paper proposed a new evaluation model based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchical process model is a combination of qualitative and quantitative analysis of systematic decision analysis method. According to the objective of the remote sensing cooperative observation mission, we decompose the complex problem into several levels and a number of factors, compare and calculate various factors in pairs, and obtain the combination weights of different schemes. The model can be used to evaluate the observation capability of resource satellites. Taking the optical remote sensing satellites such as China’s resource satellite series and GF-4 as examples, this paper verifies and evaluates the model for three typical tasks: point target observation, regional target observation and moving target continuous observation. The results show that the model can provide quantitative reference and model support for comprehensive evaluation of the collaborative observation capability of remote sensing satellites.

This paper presents an analysis of precipitation extremes over the East African region. The study employs six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) to evaluate possible climate change. Observed datasets and CMIP6 simulations and projections are employed to assess the changes during the two main rainfall seasons of March to May (MAM) and October to December (OND). The study evaluated the capability of CMIP6 simulations in reproducing the observed extreme events during the period 1995 – 2014. Our results show that the multi-model ensemble (herein referred to as MME) of CMIP6 models can depict the observed spatial distribution of precipitation extremes for both seasons, albeit with some noticeable exceptions in some indices. Overall, MME's assessment yields considerable confidence in CMIP6 to be employed for the projection of extreme events over the study area. Analysis of extreme estimations shows an increase (decrease) in CDD (CWD) during 2081 – 2100 relative to the baseline period in both seasons. Moreover, SDII, R95p, R20mm, and PRCPTOT demonstrate significant OND estimates compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while reduction is observed over the Tanzania region. The increase in projected extremes during two main rainfall seasons poses a significant threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are encouraged to examine the underlying physical features modulating the occurrence of extremes incidences projected for relevant policies.

As a consequence of the global sanitary crisis in early 2020, universities had to tackle with a sudden shift in their teaching-learning strategies so that the preset competences could be fulfilled. This study presents the learning outcomes of the tasks implemented, student experiences and feedback, as well as some reflections from the instructors with a holistic perspective of the courses due to the measures and adaptations adopted. Six courses taught at Civil Engineering degrees of three universities, two from Spain and one from Peru, are analyzed. The teaching and evaluation strategies are described and some reflections are made by comparing the student’s performance with the previous course. Although the shift to online learning had to be made from day to day, with no time for preparation, the experience has proved that online learning can be beneficial in some aspects and have probably come to stay, although some others are difficult to replace with respect to face-to-face learning, especially students’ engagement and motivation.

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated COVID-19 disease has become a global pandemic causing significant mortality and morbidity. In the absence of vaccines and effective therapeutics, reliable serological testing can be a key element of public health policy to control further spread of the disease and gradually ease quarantine measures. However, prior to launch of large-scale seroprevalence studies to assess herd immunity, it is critical to understand the limits and potential of current SARS-CoV-2 serological tests on the market. In this study, we provide an overview of serological testing and conduct a systematic review of independent evaluations of SARS-CoV-2 serological tests performance. Our findings show significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid diagnostic tests with high performance level in detecting SRAS-CoV-2 specific antibodies. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.

The contribution deals with the joining of various types of materials by technology of thermal drilling. In various branches of industries, also in the automotive industry must be joining operations, service, repairing, substitution or protection workpieces, components with various types of materials. Equally, the important role as joint, is also used material, and a product preparation by assembly and disassembly operations. By utilization of new friction hybrid joining technologies we can shortage the production time, provide automation in operations, increase the quality of joints, spare of economical expenses and also we can protect the environment. In this paper authors have investigated the effect of friction drilling on the tested material, aluminium alloy AlMgSi, which was used for material testing. The created joints were evaluated visually and by microscopy methods. The errors of tested joining were documented and described, too. This contribution was made with cooperation of Technical University of Kosice and with U. S. Steel Kosice, s.r.o.

Injuries of repetitive efforts constitute one of the prime causes of absenteeism in the workplace, have bear a considerable cost for the public health system and can cast doubt on the sustainability of a company. The objective of this paper is to build, in the researchers, the needed knowledge to choose a set of relevant scientific articles about repetitive strain injuries in the poultry meat industry, aiming identify characteristics in those scientific publications that have the potential to contribute on the topic of this paper. The research is characterized as exploratory-descriptive, draws on primary and secondary data sources. The study involves the application of a method for selection and analysis of the selected articles. To this end, the method utilized was the Knowledge Development Process – Constructivist (Proknow-C) as theoretical intervention instrument. Within the process development, it was obtained a portfolio of 16 articles aligned to the research and scientifically recognized with the main periodicals, papers, authors and keywords. The ProKnow-C process allowed identify opportunities in the literature about injuries in the poultry meat industry and showed opportunities for research future. This paper, under the constructivist perspective, presents a structured process to build, in the researcher, the necessary knowledge to identification, selection and analysis of relevant scientific articles relating to research context and, for these articles, find prominences and opportunities for a research theme without similar publications.

Conversational spoken dialogue systems that interact with the user rather than merely reading text can be equipped with hesitations to manage the dialogue flow and the users' attention. Based on a series of empirical studies, we built an elaborated hesitation synthesis strategy for dialogue systems that inserts hesitations of scalable extent wherever needed in the ongoing utterance. So far, evaluations of hesitating systems have shown that synthesis quality is affected negatively by hesitations, but that there is improvement in interaction quality. We argue that due to its conversational nature, hesitation synthesis needs interactive evaluation rather than traditional MOS-based questionnaires. To prove this point, we dually evaluate our system’s speech synthesis component: on the one hand, linked to the dialogue system evaluation, on the other hand, in the traditional MOS way. This way we are able to analyze and discuss differences that arise due to the evaluation methodology. Our results suggest that MOS scales are not sufficient to assess speech synthesis quality, which has implications for future research that are discussed in this paper. Furthermore, our results indicate that hesitations work well to increase task performance and that an elaborated strategy is necessary to avoid likability issues.

Oil has become the object of global exploits and fierce competition among the major world powers as it is a key strategic non-renewable resource. Transnational petroleum investment is therefore an important mechanism available to countries and international corporations to control oil resources even though there are numerous inherent uncertainties and risks. A new risk assessment index system is proposed in this paper based on use of the Delphi expert scoring system and fuzzy comprehensive evaluation that aims to minimize the potential risks inherent to multinational petroleum investment. This approach encapsulates political, legal, socioeconomic, and infrastructural factors to develop a technical method that can be used for transnational petroleum investment risk assessment. An evaluation of oil investment risk within a case study area is also presented; results provide reference data that can be applied by national and international oil companies to mitigate risks of transnational oil investment.

Background: Differentiating essential tremor (ET) and functional tremor (FT) remains challenging due to their overlapping clinical presentations. Objective: In this study, we aimed to elucidate the demographic and psychometric differences between the aforementioned tremor types to enhance the diagnostic accuracy and therapeutic strategies. Methods: In this prospective study, we included 96 patients diagnosed with ET or FT and analysed their related demographic data, clinical symptoms, and psychometric evaluation scores. Our statistical analysis involved Pearson’s chi-square tests, Fisher’s exact tests, and logistic regression to assess how the different variables impact tremor diagnosis. Results: Our study demonstrated a higher ET prevalence in males (p = 0.015). Furthermore, we demonstrated that patients with ET displayed a significantly lower body mass index and a lower age of onset compared to those with FT (p = 0.050 and p = 0.023, respectively). Our psychometric assessments revealed higher cognitive and body image scores in patients with ET, whereas those with FT scored higher on depression and anxiety scales. The misdiagnosis rate was 14.5%, emphasising the need for improved diagnostic criteria. Conclusions: We established specific demographic and psychometric distinctions between ET and FT, which could potentially benefit clinicians in making accurate diagnoses and tailoring treatment approaches. These findings support the inclusion of comprehensive psychometric evaluations into standard diagnostic procedures to better differentiate tremor types.

Using a sample of 103 surviving and non-surviving global bond funds over a long sample period of 1998 to 2022, we perform a comprehensive analysis of the funds under our modified Sharpe’s (1992) style analysis model. We find that dynamic style analysis is useful in explaining time-series and cross-sectional and in predicting future returns of global bond funds. The dynamic style analysis also allows us to examine asset allocation over time. The results show that, during 2001 to 2014, funds shift their allocations from intermediate-term bonds to world corporate bonds and from world corporate bonds to emerging market bonds in search of higher returns at the price of credit quality.

Given the many approaches to and definitions of gender responsive monitoring and evaluation (M&E) for health programs and interventions there is a lack of clarity on how to operationalize it including what to measure and how to measure it. We conducted a scoping review to understand what makes M&E gender responsive. We included 31 studies and conducted two rounds of extraction to delineate ways in which gender was integrated into M&E. Twelve articles described the use of theory to guide M&E though most were not related to gender. Twelve articles employed a gender score in data collection, most of which measured Likert scale responses related to gender equity. Even though most studies did not use a specific gender framework, most incorporated gender domains in their analysis. Seven studies used participatory methods in the design and implementation of M&E. Most studies conducted M&E on programs or interventions that were designed to be gender intentional and related to gender issues. Gender responsive M&E intentionally integrates gender into the M&E process, regardless of how gender-intentional the program or intervention is. Gender dimensions can be identified through gender theories, models, scores, and frameworks to inform tool development, data collection, analysis, and stakeholder engagement processes.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

Machine Learning is increasingly and ubiquitously being used in the medical domain. Evaluation metrics like accuracy, precision, and recall may indicate the performance of the models but not necessarily the reliability of their outcomes. This paper assesses the effectiveness of a number of machine learning algorithms applied to an important dataset in the medical domain, specifically, mental health, by employing explainability methodologies. Using multiple machine learning algorithms and model explainability techniques, the project provides insights into the model workings to help determine the reliability of the machine learning algorithm predictions. The results are not intuitive. It was found that the models were focusing significantly on less relevant features and at times, unsound ranking of the features to make the predictions. The paper therefore argues that it is important for research in applied machine learning to provide insights into explainability of the models in addition to other performance metrics like accuracy. This is particularly important for applications in critical domains such as healthcare. A future direction is to investigate methods to quantify the effectiveness of the machine learning models in terms of the insights from their explainability.

The evaluation of tourism sustainability has become of paramount importance for researchers and decision-makers to better protect tourist destinations, especially with the continuous increase in the number of tourists and visitors that alter the natural components of the environment and degrade ecosystems. Therefore, the use of geographical data is of great significance, particularly in environmental monitoring and land management, due to its ease of use and availability. However, calculating composite indices for sustainability involves several steps and requires a basic understanding of existing models. This article describes the development and design of a package of plugins in QGIS that serves as an easy-to-use tool for processing and automatically calculating economic, environmental, social indices, and the overall index of tourist sustainability. These plugins have been built in Python and designed as QGIS software plugins.

Ethics values for public officers are important for enhancing cultural ethical levels and keeping society free from low-level barbarian ethical values. Barbarian ethics values are reflected in animal behavior, as in some countries security agencies, and a culture based on strength is dominant, especially in political and military parties. This study gave insight into the change in security agency duties from fighting criminal activities to managing criminal activities. Keeping high-level ethical values is essential for enhancing the behavior of public officers and stakeholders in any official institution at a standard level. This study provides stakeholders with a clear vision of the different defects in public institutions and how to improve and avoid negative ethical issues. By identifying all aspects of public officers and deviations from ideal ethical values for public officers,the negative ethical values in security agency officers have been noticed for a long time due to feelings of injustice or unfairness in native citizens of any country, generating mafia-based institutions instead of police departments or security agencies in any country.

The recent introduction of foot-and-mouth disease virus serotype O (O/EA-2 topotype) in Southern Africa region has changed virus dynamics and the FMD vaccine requirements. This study describes an assessment of the heterologous antibody responses induced by O Manisa vaccine (three PD50/dose) against a representative O/EA-2 virus collected from an FMD outbreak in Zambia. Commercial and subsistence cattle herds were monitored following vaccination, where the benefits of employing a double vaccination schedule were compared to single-dose vaccination. Testing using virus neutralisation showed cattle that received two vaccine doses had a mean reciprocal log virus neutralisation titre of 2.02 (standard error [SE] = 0.16, n = 9) for commercial herds and 1.65 (SE = 0.17, n = 5) for subsistence herds , 56 days after first vaccination (dpv). Significantly lower mean titres were observed for single-dosed commercial herds (0.90, SE = 0.08, n = 9) and subsistence herds (1.15, SE = 0.18, n = 3), 56 dpv. Comparison of these results and those generated by solid-phase competitive ELISA by cohen’s kappa coefficient observed a statistically significant (ρ = 0.598 for 1:10 dilution, and ρ = 0.562 for 1:30 dilution of SPCE % inhibition results, p < 0.001 for both dilutions) positive correlation.

This study aims to explore the utilization of deep learning models, specifically the innovative Multi-Modal Contextual Fusion Convolutional Neural Network (MSHA), for the detection and diagnosis of Adrenocortical Carcinoma (ACC) using computed tomography (CT) images. The objective is to develop an accurate and reliable model that can assist in the effective detection and classification of ACC. The study utilizes a dataset comprising contrast-enhanced CT images from 53 confirmed ACC patients. The MSHA model is employed, which incorporates a combination of mixed-scale dense convolution, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information techniques. Evaluation metrics are used to assess the performance of the MSHA model, and a comparison is made with other established models, including ResNet50, VGG16, VGG19, and InceptionV3. The evaluation of the MSHA model demonstrates high performance, with an accuracy of 96.65% and precision, sensitivity, specificity, and F1 score of 96.0%. These results highlight the MSHA model's capability in accurately detecting and classifying ACC. Furthermore, compared to other models, the MSHA model outperforms ResNet50, VGG16, VGG19, and InceptionV3, indicating its superior performance in ACC detection and diagnosis. The findings of this study suggest that the MSHA model holds significant potential in assisting healthcare professionals with the detection and diagnosis of ACC. With its advanced features and contextual fusion techniques, the MSHA model achieves high accuracy and performance. The results highlight the clinical significance of this novel model and its potential to improve patient management and outcomes in the detection and diagnosis of ACC using CT images.

This work deals with a systematic review of literature data concerning the theme of the integrated approach to occupational health and safety management, with particular reference to the programming of assistance plans, which guide the company's organizational choices also by aiming at the principles of the Total Worker Health. In the current regulatory framework on this issue, the UNI ISO 45001: 2018 standard assumes particular relevance, which defines the dynamic approach to occupational health and safety management systems, paying particular attention to external contextual factors that may influence corporate organizational decisions. The adoption of these systems is not mandatory, but allows companies to fulfill their duties in terms of health and safety at work, through an organizational approach aimed at awareness, involvement and participation of all subjects of the company prevention system, overcoming the phase of the mere technological and prescriptive approach, towards a holistic vision of prevention, which places the person at the center of preventive actions. In this context, the role of institutional networks and socio-economic partnerships assumes particular importance, in the activation of territorial assistance interventions to support companies for the improvement of risk management levels. To this end, the importance of verifying the effectiveness of assistance interventions emerges from the scientific debate, through the use of indicators such as quantitative ones for measuring the performance of all phases of the intervention with particular attention to the effects in terms of improved solutions developed.

The osteoarthritis (OA), the main cause of disability, is a chronic condition that most frequently affects older adults. As the population ages, the cost of treatment is placing pressure on the healthcare budget. As a result, it is imperative to evaluate the medicines' cost-effectiveness and the influence they have on health resource allocation. Hence, our study aims to summarize the cost and outcome of utilizing glucosamine in OA treatment. Authentic databases like Medline, Cochrane, and Scopus were adopted for the identification process up until July 2023. Our primary inclusion criteria centered on the economic evaluation of Glucosamine in OA treatments with provided the incremental cost-effectiveness ratio (ICER) at least. The Quality of Health Economic Studies (QHES) instrument was applied to grade the quality of the studies. A total of 7 qualified studies were selected and discussed the cost-effectiveness of glucosamine with or without other formulations. All of them demonstrated that glucosamine was cost-effective. There was an in-creasement of QALY when incorporating Glucosamine into conventional care. Moreover, Crystalline Glucosamine Sulfate (pCGS) was more cost-effective than the Other Formulations of Glucosamine (OFG). In overall, utilizing pCGS was more beneficial than OFG in terms both of cost and quality of life.

The research question in this article concerns how a competitive environment affects the learner (officer cadet's) personal leadership development and their relationship to their team and with future civilian foundations. More specifically, what are the possible learning effects of the “hidden” curriculum? This article investigates how a more than 250 years of leadership education provides new army officers with new skills and how such an environment may affect the cadets' leadership training. The paper builds on ethnographic data gathered during the three-year education program in most of the relevant practical locations and contexts. Findings regarding trust in their learning environment, cadets have reported scores of (Mean 2.83) on a 1 (low trust) to 5 (high trust) Likert scale, underpinning interviewdata regarding the lack trust in the academy and in their fellow cadets. Cadets also point out that competition has hindered their learning (Mean 2.50). These findings are interpreted in relation to possible negative effects stemming from internal competition and the evaluation system as a whole. The overall output of this system is a zero–sum game, and thus effects evaluative practices and learning processes. This study is of relevance to higher education officers responsible for designing learning environments.

Pulsed thermography is a vital technique in the nondestructive evaluation field. However, its data analysis can be complex and requires skilled experts. Advances in deep learning have yielded exceptional results, including image segmentation. Therefore, many efforts have been made to apply deep learning methods to data processing for nondestructive evaluation. Despite this, there is currently no public Pulsed thermographic dataset available for evaluating various spatial-temporal deep methods of segmenting pulsed thermographic data. This article aims to provide such a dataset and assess the performance of commonly used deep learning-based instance segmentation models on it. Additionally, the impact of the number of frames and data transformations on model performance is examined. The findings suggest that suitable preprocessing methods can effectively reduce the data size without compromising the deep models’ performance.

The world is facing a great technological transformation towards full autonomous vehicles, where optimists predict that by 2030, autonomous vehicles will be sufficiently reliable, affordable and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all the surroundings, being light detection and ranging (LiDAR) sensors a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely in accurate measurements of the environment. Thus, sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors with the main goal of testing not only commercially available sensors, but also sensor prototypes currently under development in Bosch Automotive Electronics division. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment to which such devices are normally subjected. To characterize and validate the sensor under test, the platform evaluates several parameters such as the field of view (FoV), angular resolution, sensor’s range, etc. This project results from a partnership between the University of Minho and Bosch Car Multimedia Portugal, S.A.

Infectious bursal disease (IBD) is one of the most endemic diseases of commercial poultry in Ethiopia. Vaccination has been practiced as the major means of IBD prevention and control. A study was conducted to determine and compare the immunogenicity of two commercially available IBD vaccines in broiler chicken with maternally derived antibody (MDA). Day-old chickens of 270 were randomly assigned to three groups, group 1 vaccinated with brand 1 vaccine at 7^th and 19^th days and group 2 with brand 2 vaccine at 15^th and 22^nd days while group 3 were kept as control. Six chickens were also randomly selected and bled on day 1 for differential leukocyte count (DLC) and determination of MDA. Representative chickens from each group were bled at 24^th and 42^nd days of age for antibody titration using the indirect ELISA test. DLC scores were determined in the 1^st and 24^th days. The result revealed highly significant differences (P = 0.001) between group 1 and group 2 in DLC at 24^th days of age. Antibody titers against IBD were differed significantly (P = 0.02) at 24^th and 42^nd days of age in broilers vaccinated with brand 1 and brand 2 vaccines. It is concluded that although both brands of vaccine induce an adequate immunological response at the end of the experiment, brand 1 vaccine has shown significantly high antibody titers against the IBDV and DLC than brand 2.

Efficient quality evaluation provides support for the timely and good maintenance of the lane line marking. This paper searches and optimizes the back propagation(BP) network model which referred to the analytic hierarchy process(AHP) model structure, as well as the number of nodes in the middle layer network. Based on this, a comprehensive evaluation method of multi-dimensional lane line quality such as shape, color and contrast is established. The experimental results show that the parameters of the model are more simplified, and the scoring and classification results of lane lines are more accurate.

Body-Esteem Scale is an assessment tool for adolescents and adults that evaluate three dimensions of self-evaluations of one’s body. Body-Esteem Scale has been translated and validated in some countries since America down to Europe. Lack of translation and reliability evidence in Portugal was detected. This study aimed to translate and test the validity and reliability of the Body Esteem Scale for Adolescents and Adults (BESAA) in students in the context of Portuguese higher educa-tion. A total of 173 students (60.7% are female) with a mean age of 19.7 (standard deviation = 2.2) years participated. Categorical Principal Component Analysis was used to assess the underlying dimensions of BESAA. Construct validity was evaluated through correlation with the Appearance Schemas Inventory – Revised and a three-factor model (“Appearance”, ‘‘Weight’’ and “Attribu-tion’’) was established. Confirmatory factor analysis was performed to verify the construct validity of the instrument. Items that had factor weights (λ)<.40 were removed, as well as those that were considered redundant by the modification indices estimated by the Lagrange Multipliers (LM) method (LM>11, p<.001). We observed high correlations between theoretically similar factors, and low correlations between different factors. The Portuguese BESAA showed adequate validity and reliability.

Cereals and their derivatives are the basis of human nutrition. However, cereals also contribute to the dietary exposure to toxic metals that may pose a risk. Strengthening food security and nutrition information is a high priority challenge for the Cape Verde Government. The toxic metals content (Cr, Ni, Sr, Al, Cd, Pb) has been determined in 126 samples of cereals and derivatives (rice, corn gofio, corn flour, wheat flour, corn, wheat) consumed in Cape Verde. Wheat flour samples stand out for registering the highest Sr (1.60 mg/kg), Ni (0.25 mg/kg) and Cr (0.13 mg/kg). The results show relevant Al levels (1.17 – 13.4 mg/kg) with its highest levels in corn gofio. The mean Pb average content in the cereals is 0.03 – 0.08 mg/kg with the highest level observed in corn gofio. The Al and Pb levels are lower in cereals without husks. A consumption of 100 g/day of corn gofio provide an intake of 1.34 mg Al/day (13.7% of the tolerable weekly intake established at 1 mg/kg bw/week) and 8 µg Pb/day (20% of the BMDL set at 0.63 µg/kg bw/day for nephrotoxic effects). The minimization of the dietary exposure of the Cape Verdean population to toxic metals is through the importation of higher quality cereals.

This study examines the improvement in coupled intercomparison project phase six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS dataset using robust statistical techniques for 1981 – 2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6-MME shows improved performance in the local annual mean cycle simulation with a better representation of two peaks, especially the MAM rainfall relative to its predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to its predecessor. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating SDII, CDD, and R20mm over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). A few CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depicts robust performance in reproducing the observed indices across all analyses. Conversely, OND season shows the overestimation of some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance due to the cancellation of some systematic errors in the individual models. Generally, the CMIP6 depicts improved performance in the simulation of MAM season akin CMIP5 models. However, the new model generation is still marred with uncertainty, thereby depicting substandard performance over the East Africa domain. This calls for further investigation of attribution studies into the sources of persistent systematic biases and a prerequisite for identifying individual models with robust features that can accurately simulate observed patterns for future usage.

The fast and flexible characteristics of badminton determine the necessity of its lunge, and fast lunge will have an important impact on the results of the game in actual combat. In lunge evaluation, the contact time to the ground is a key indicator. This article selects two middle-aged male badminton amateurs with similar body shape and age， but different skill levels as the research objects to carry out comparative experiments. The microseismic equipment is used to record the floor vibration which is caused by the running of badminton amateurs in sports. The microseismic signals of lunge are processed and analyzed by MATLAB software. And we evaluate the pro and cons of various time to touch the ground from amateurs with different skill levels. The research found that 1. Microseismic technology can detect the contact time to the ground. 2. High-level badminton amateurs have obvious advantages in the footwork contact time. Microseismic technology has a certain feasibility as a tool for evaluating the footwork contact time of badminton.

This study evaluates the historical mean surface temperature (hereafter T2m) and examines how T2m changes over East Africa (EA) in the 21^st century using CMIP6 models. An evaluation was conducted based on mean state, trends, and statistical metrics (Bias, Correlation Coefficient, Root Mean Square Difference, and Taylor skill score). For future projections over EA, five best performing CMIP6 models (based on their performance ranking in historical mean temperature simulations) under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 scenarios were employed. The historical simulations reveal an overestimation of the mean annual T2m cycle over the study region with fewer models depicting underestimations. Further, CMIP6 models reproduce the spatial and temporal trends within the observed range proximity. Overall, the best performing models are as follows: FGOALS-g3, HadGEM-GC31-LL, MPI-ESM2-LR, CNRM-CM6-1, and IPSL-CM6A-LR. During the three-time slice under consideration, the Multi Model Ensemble (MME) project many changes during the late period (2080 – 2100) with expected mean changes at 2.4 °C for SSP2-4.5 and 4.4 °C for the SSP5-8.5 scenario. The magnitude of change based on Sen’s slope estimator and Mann-Kendall test reveal significant increasing tendencies with projections of 0.24°C decade-1 (0.65°C decade-1) under SSP2-4.5 (SSP5-8.5) scenarios. The findings from this study illustrate higher warming in the latest model outputs of CMIP6 relative to its predecessor, despite identical instantaneous radiative forcing.

Opening gated-communities (GCs) has been widely discussed for urban inclusion and revitalization. With the policies of opening GCs being promoted in China, quantitative and comprehensive evaluation of the potential benefits is heavily needed. Taking Shanghai as an example, this study quantifies and analyzes the accessibility benefits and risks of opening GCs with factors including GC types, opening levels, travel modes, and travel destinations considered. We found that (1) opening GCs can bring 50m+ accessibility gains to 17% and 52% of the residents in Moderately Opening (MO) and Completely Opening (CO) scenarios, respectively. (2) Cycling benefits more than walking in all cases and scenarios. (3) For different GCs, conventional GCs have fewer benefits in MO but more in CO than the newly-established one. For different facilities, trips to bus stations demonstrate the largest accessibility gains. (4) The accessibility benefit of a residential building is highly determined by its closeness to the gates and relative location in the block. (5) Only 1% and 5-7% of external trips may penetrate the opened communities in MO and CO scenarios, respectively, which are far less than both expectation and the benefits. These findings precipitate at least two policy implications in China.

The popularity of functional gummies has increased, which is evident from the growing line of functional gummies from almost every nutraceutical companies. Sensory evaluation serves the purpose of determining which brand of functional gummy would capture the largest market share. Texture profile analysis was used to determine the mechanical properties of functional gummies. The brands of functional gummies that came under the scope of this study were denoted as Brand A, B, C, D, E, F and G. Fourier Transform Infrared Spectroscopy was utilised to detect organic material and functional groups in the functional gummies. Texture profile analysis gave valuable insights into the gummies’ mechanical properties which are cohesiveness, springiness, hardness, gumminess, and chewiness. Amongst the gummies that were studied, Brand F gummy has the highest value of cohesiveness of 0.92. Brand A gummy has a high springiness value of 1.0. Brand B gummy possesses the highest value of hardness, gumminess and chewiness of 12 532.2 g, 7617.6 N, and 6256.8 J, respectively. Qualitative sensory evaluation reveals that Brand G gummy has the best aesthetic qualities in terms of colour and appearance. Brand B gummy tastes the best while brand A gummy claims the top spot for gumminess and chewiness. Overall, the respondents in this study preferred brand A gummy over other brands.

We report on an exploratory study conducted at a graduate school in Sweden with a humanoid robot, Baxter. First, we describe a list of potentially useful capabilities for a robot teaching assistant derived from brainstorming and interviews with faculty members, teachers, and students. These selected capabilities consist of reading, greeting, alerting, remote operation, clarification, and motion. Second, we present feedback on how the robot's capabilities, demonstrated in part with the Wizard of Oz approach, were perceived, and iteratively adapted over the course of several lectures, using the \EP tool. Third, we discuss observations and findings regarding the capabilities and the development process. Our findings suggest that using a social robot as a teaching assistant is promising using the chosen capabilities. We find that personalizing the capabilities and the role of embodiment are important topics to be considered in future work.