The topic of the article refers to expressions used to address the psychosocial risk linked to the workplace violence. The article bases on the Polish-French comparison, using analysis of definitions, legal acts and public statistics. The purpose is to show social differences, in the context of mobbing and “harcèlement moral”, that surface from ratified definitions of these phenomena and public statistics. The final conclusions are the effect of a compilation of results of analysis and available literature. The choice of the two European, diverse areas of comparison for the diagnosis - Poland and France - is the result of selection of the method of data content analysis, chosen by the author because of the availability of the scientific resources essential for the article and accessible during an academic stay in Centre d'Etudes de l'Emploi in France.

Regression models are highly popular in empirical research and come in many different forms to fit virtually any distribution, variable, or research question. Usually, these models also compute how much variation in the outcome variable can be explained by all predictors, which is relevant to understanding whether the predictors are, in sum, able to explain the outcome or whether other potentially unobserved factors are more relevant. This aspect is crucial for interventions and policy as even statistically significant regression coefficients can be meaningless if they have little influence on the outcome overall. Besides having a measurement to judge the overall goodness of fit, ranking predictors by their relative importance is also relevant. For such analyses, it is necessary to decompose the total explanatory power of a model and partition it so that each explanatory variable is assigned a share. This enables the computation of a predictor variable's absolute and relative influence. Dominance analysis is a statistical approach to achieve this goal.

The field of domain adaptation, particularly in cross-domain sentiment classification, leverages labeled data from a source domain alongside unlabeled or sparsely labeled data from a target domain. The objective is to enhance performance in the target domain by mitigating the discrepancies in data distributions. Traditional methods in this area have focused on identifying and differentiating between pivotal sentiment words (shared across domains) and domain-specific sentiment words. In our work, we introduce a novel framework called Sentiment Domain Adapter (SDA), which incorporates a Category Attention Network (CAN) alongside a Convolutional Neural Network (CNN). This approach treats pivotal and domain-specific words as part of a collective category of attributes, which SDA learns to discern automatically, thereby enhancing domain adaptation. Additionally, SDA seeks to provide interpretative insights by learning these category attributes. Our model's optimization targets three main goals: (1) supervised classification accuracy, (2) minimizing the disparity in category feature distribution, and (3) maintaining domain invariance. Evaluations on three benchmark datasets for sentiment analysis affirm that SDA surpasses several established baselines.

With the development of the Internet, The content people share contains types of text, images, and videos, and utilizing these multimodal data for sentiment analysis has become an important area of research. Multimodal sentiment analysis aims to understand and perceive emotions or sentiments in different types of data. Currently, the realm of multimodal sentiment analysis faces various challenges, with a major emphasis on addressing two key issues: 1) Inefficiency when modeling the intra-modality and inter-modality dynamics and 2) Inability to effectively fuse multimodal features. In this paper, we proposed the CCDA(Cross-Correlation in Dual-Attention) model, a novel method to explore dynamics between different modalities and fuse multimodal features efficiently. We capture dynamics at intra- and inter-modal levels by using two types of attention mechanisms simultaneously. Meanwhile, the cross-correlation loss is introduced to capture the correlation between attention mechanisms. Moreover, the relevant coefficient is proposed to integrate multimodal features effectively. Extensive experiments were conducted on three publicly available datasets, CMU-MOSI, CMU-MOSEI, and CH-SIMS. The experimental results fully confirm the effectiveness of our proposed method, and compared with the current optimal method (SOTA), our model shows obvious advantages in most of the key metrics, proving its better performance in multimodal sentiment analysis.

Sulfolane, a highly water-soluble industrial solvent, has raised environmental concerns due to its persistence once released into the environment. To assess the extent of contamination effectively, reliable analytical methods are essential. In this review, we delve into the published literature on sulfolane analytical procedures. Existing guidelines for sampling from environmental matrices provide a solid foundation for sul-folane analysis. Notably, there is little variation in the choice of determination method, with GC-MS or GC-FID being favored across studies. However, substantial variability emerges in sample prep-aration methods. Many procedures rely on large quantities of environmentally hazardous solvents, such as dichloromethane, during extraction. Nevertheless, by incorporating extraction enhancement techniques proposed in various studies, it is possible to develop more eco-friendly extraction processes. Overall, this field calls for further re-search to devise efficient and environmentally sustainable analytical methods for sulfolane analysis. Through this review, insights into the challenges at hand and potential solutions can be gained, offering a foundation for the development of novel sulfolane analysis methods applicable to a range of environmental matrices.

By framing the problem of determining the state of Schrodinger’s cat as a problem of searching for Hidden Markov Model (HMM), this work shows that Schrodinger’s cat is dead with stationary probabilities P(Cat = Dead) = 1 and P(Cat = Alive) = 0 consistently in various observation-based modelling of the HMM.

Probabilistic latent semantic analysis is a statistical technique developed for information retrieval and spanned many fields. It yields intuitive and solid results. However, the rigidity of the assumptions and the iterative nature derived from the Expectation-maximization algorithm generate several problems, dividing detractors and enthusiasts. In this manuscript, we first describe the Probabilistic latent semantic analysis. After, we discuss reformulations that attempt to solve these problems. We pay special attention to the works relating Probabilistic latent semantic analysis and the Singular value decomposition Theorem. Also, Probabilistic latent semantic analysis can be the basis for other techniques, such as kernelization or probabilistic transfer learning, and those that extend the descriptive character of the Principal component analysis to an inferential tool and open a window of opportunities.

Analyzing big data poses a great challenge for numerous researchers to explore the data structure. Dimension reduction methods can be used to reduce data dimensionality, taking it from occupying a high-dimensional space to existing in a lower-dimensional space while retaining as much information as possible. Principal Component Analysis is one of the most popular used to reduce the dimensional space. The bootstrap sample is obtained by randomly sampling n times with replacement from the original sample, the method provides easy tool to understand the interactive component and develop the process. There are not enough researches discussed the stability of PCA method using bootstrap method. In this paper, the bootstrap method is used to analyze the stability of PCA results and to estimate the number of PCA in efficient way. The method is used to estimate the number of PCA that needed to classify the data set, and the effectiveness of the discussed techniques is demonstrated through real data sets.

Consistent increment of road traffic in cities is remained a threat to traffic performance and causes confliction. The researcher repeatedly emphasized the connected autonomous vehicles (CAVs) as stronger solution to deal with traffic related issues. While having autonomous system in the dedicated lanes is found to be safe by many investigators because of predictable surrounding maneuvers, in contrast, the mixed lane states remain questionable. Different methodologies are being used to study the effects of autonomous vehicles (AVs) in the mixed traffic. Microscopic simulation tools are popular in such cases as it offers scope to experiment in cheap, robust, and optimistic way. One interesting methodology to deal with CAVs is considering it as conventional human driven vehicles and predict its possible characteristics based on the simulation inputs. One big challenge is, as there is no regular real-world data to calibrate and to validate the simulated model for CAVs. This is where conventional human driven vehicles from real world, come to aid as benchmark to offer the measure of effectiveness (MoE) for the calibration and validation. For the three most common driving modules, a sensitivity analysis of the driving behaviors of autonomous vehicles (AVs) and an effect assessment of CAVs in a mixed traffic environment were done to explore the human alike autonomous technology. The findings show that, up to a point, which is directly related to the quantity of interacting vehicles, the impact of CAVs is typically favorable. This study supports earlier research by demonstrating that CAVs outperform AVs in traffic. In addition, the sensitivity analysis has shown that technical and infrastructural advances are necessary to achieve the greatest benefits.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

Systematic reviews and meta-analyses have become an important way to summarize data. The hierarchy of evidence-based medicine confers a high platform to meta-analyses. Hence, it is imperative that the analytical and reporting strategy associated with a meta-analysis be standardized. The modern tradition of reporting and publishing a meta-analysis is riddled with several methodological flaws. The most common of these flaws involve the choice of the model used to conduct the meta-analysis and the way that the heterogeneity of studies is assessed. The use of the I² statistic as a means of detecting within-study heterogeneity is a common methodological flaw encountered in reporting summary statistics.One of the ways to rectify the above flaws is to arm reviewers with an objective way to scrutinize the manuscript. This narrative review enlists six checklists for reviewers to improve the reporting of meta-analyses. The first two checklists address reporting of the risk of bias and assessment of publication bias with the help of a funnel plot. Checklists 3, 4, and 5 address the choice of model selected for the meta-analysis, the method to assess the confidence interval, and the measures of heterogeneity. The final checklist addresses the question asked in the meta-analysis, binary versus an effect size estimate. Although there are many more aspects which can help improve the assessment of a manuscript, these basic checklists can be employed by reviewers without the need for an external statistical analysis to enhance and improve meta-analyses.

There is increasing evidence that many molecular processes exhibit differences with age 1 and sex. Such differences produces also differences in the insurgence and progression of many 2 complex diseases. For instances, demographic data on insurgence of comorbidities of mellitus 3 diabetes, on lethality of COVID-19, and on some cancers, shows differences between sex and age 4 groups. Therefore, the growing interest on such area requires the management of related data as 5 well as the development of algorithms and tool for the analysis. The availability of omics data 6 annotated with metadata related to age and sex is mandatory for building pipeline of the analysis. 7 The number of databases containing data related to age and sex is hencefort growing. We here show 8 some databases and tools storing such data. Finally, future research direction are highlighte

Heart rate variability (HRV) is commonly intended as the variation in the heart rate (HR) and it is evaluated in the time and frequency domains with various well known methods. In the present paper, we first consider an abstract model in which the HR is the instantaneous frequency of an otherwise periodic signal such as the electrocardiogram (ECG). Thus the ECG is assumed as a frequency modulated signal, or carrier signal, where HRV or HRVt is a supposed time-domain signal which is frequency modulating the carrier ECG signal around its average frequency. Hence we describe an algorithm able to frequency demodulate the ECG signal to extract a continuous signal HRVt with possibly enough time resolution to analyse fast time-domain variations in the instantaneous HR. After exhaustive testing of the method on simulated frequency modulated sinusoidal signals, we have applied the procedure on actual ECG tracings. The purpose of the work is to eventually use the heart as a kind of biological sensor of the fast activity of the autonomic nervous system (ANS) to study the ANS ultra-short-term event-evoked responses. A few preliminary, not clinical, real examples are also given.

The present-day financial system is being influenced by the rapid development of Fintech (financial technologies), which are technologies created to improve and automate traditional forms of finance for businesses and consumers. The topic of Fintech as a financial disruptor is gaining popularity in line with the swift spread of digitalization across the banking industry, whereby this paper contributes to the field by presenting a novel bibliometric analysis of academic literature related to Fintech as a financial disruptor. The analysis is based on metadata extracted from the Scopus database through the VOSviewer and Biblioshiny software. The bibliometric analysis of 363 documents identified the most impactful sources of publication, keywords, authors, and most cited documents on the topic of Fintech as a financial disruptor. As our analysis demonstrates the number of publications on the given topic increases, defining both the interest among academia and potential for future research.

IT auditing quality has been defined by results obtained in the process. Meanwhile, multiple studies have been done to enhance it therefore, it continues to be a topic interest and research so it is worth mentioning that its quality relies on trained competent auditors and experts able to develop a process correctly, adapting to clients and to manage auditing inherent risks According to results from the IT audit, low quality and security levels have been identified in terms of the human, technical and contextual factors, affecting audit quality. The objective of this investigation is to identify metrics and to determine their own corresponding factor applying an exploratory type of research. In order to achieve such aim, a targeted survey was designed and implemented at the Institute of Internal Auditors of Ecuador since they have the knowledge and expertise in the field. A factor analysis statistics technique was applied to data gathered to verify that it relates to the identified factors as dimensions are reduced, thus the most impacting metrics may assess the quality of IT audits. Analysis results yielded a mean score for each one of the assessed metrics, concluding that the technical factor is the most significative since it relates roles and task performance during the auditing process as well as control proce-dures. Finally, most auditing quality-related issues are mainly the outcome of an inferior management auditing process, therefore it is crucial that collegiate groups and professionals in the field validate the auditing process.

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application a more appropriate measure may be necessary. In this paper we introduce a family of divergences we call gamma-divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. We investigate their properties in the context of kernel theory. Finally, we apply our findings to the analysis of simulated and real time series.

Analyses of faculty citation activity usually focus on counts as a function of author characteristics such as rank, gender, previous citation levels, and other factors influencing productivity and career path. Citation analyses of publications consider aspects such as number of authors, author reputation, author order, length of the title, methodology, and impact factors of the publication. While publication topics or discipline are considered to be important factors, they are more difficult to analyze, and therefore performed less frequently. This paper attempts to do that for the field of urban planning. Urban planning is multi-disciplinary and includes consideration of social, economic, technological, environmental, and political systems that shape human settlement patterns. It has been suspected that some topics are more “popular” and have larger audiences, therefore are cited more often. Using nearly 15,000 urban planning publications, this paper presents an analysis of topics to assess which are cited most frequently. The classification of publications was performed using a Support Vector Machine (SVM), a machine learning (ML) approach to text classification, using citation data from Google Scholar. The citation levels for the resulting categories are analyzed and discussed.

Next-generation sequencing (NGS) has been a widely-used technology in biomedical research for understanding the role of molecular genetics of cells in health and disease. A variety of computational tools have been developed to analyse the vastly growing NGS data, which often require bioinformatics skills, tedious work and significant amount of time. To facilitate data processing steps minding the gap between biologists and bioinformaticians, we developed CSI NGS Portal, an online platform which gathers established bioinformatics pipelines to provide fully automated NGS data analysis and sharing in a user-friendly website. The portal currently provides 16 standard pipelines for analysing data from DNA, RNA, smallRNA, ChIP, RIP, 4C, SHAPE, circRNA, eCLIP, Bisulfite and scRNA sequencing, and is flexible to expand with new pipelines. The users can upload raw data in fastq format and submit jobs in a few clicks, and the results will be self-accessible via the portal to view/download/share in real-time. The output can be readily used as the final report or as input for other tools depending on the pipeline. Overall, CSI NGS Portal helps researchers rapidly analyse their NGS data and share results with colleagues without the aid of a bioinformatician. The portal is freely available at: https://csibioinfo.nus.edu.sg/csingsportal

The sentiment of a word varies based on its context of usage: the words used around it and the part-of-speech it is used as. This paper proposes a technique to suggest the sentiment of a word by combining its part-of-speech and the semantic similarities of its co-occurrences with both context-specific and pre-trained embeddings to achieve powerful and fast results. A study was conducted across domains and sub-domains to measure variance of sentiment by switching domains and switching context within the same domain. Re-scoring a commonly used polarity lexicon showed that 10% of words changed scores while switching domains and 8% changed scores within domains while switching context. Part of Speech analysis on 65,353 commonly used sentiment lexicons showed that 81% of sentiment bearing (non-neutral) lexicons were of the tags NN (Common Noun), JJ (Adjective) or NNS (Proper Noun).

The oral cavity harbors hundreds of microbial species that are present either as planktonic cells, or incorporated into biofilms. The majority of the oral microbes are commensal organisms. Those that are pathogenic microbes can result in oral infections, and at times initiate systemic diseases. Biofilms that contain pathogens have been challenging to control. Many conventional antimicrobials have proven to be ineffective. Recent advances in science and technology are providing new approaches for pathogen control and containment and methods to characterize biofilms. This perspective provides: 1) A general understanding of biofilm development; 2) A description of emerging chemical and biological methods to control oral biofilms; 3) An overview of high-throughput analytical approaches to analyze biofilms.

The effect of the different dental implants positioning region on the stress performance of the implant-supported prosthesis is not yet clear. This study evaluated the dental treatment with six dental implants in three different models and three different occlusal loading conditions, in terms of the biomechanical response of implants, prosthetic screw and maxilla, using three-dimensional finite element analysis. The finite element models were modelled containing external hexagon implants, as well as a Cobalt-Chromium superstructure. Three types of loads were applied: in the area of ​​the central incisors, first premolar and in the second molars. For the finite element simulations, the von-Mises stress peaks in the implant and in the surrounding cortical bone were analyzed. All recorded results reported higher values ​​for the implant-supported prosthesis in group C compared to the groups A and B. The highest stress values, ​​regardless the evaluated model, was in the prosthesis in group C and in screws, the smallest were in group A.

Global food security for the increasing world population not only requires increased sustainable production of food but a significant reduction in pre- and post-harvest waste. The timing of when a fruit is harvested is critical for reducing waste along the supply chain and increasing fruit quality for consumers. The early in field assessment of fruit ripeness and prediction of the harvest date and yield by non-destructive technologies have the potential to revolutionize farming practices and enable the consumer to eat the tastiest and freshest fruit possible. A variety of non-destructive techniques have been applied to estimate the ripeness or maturity but not all of them are applicable for in situ (field or glasshouse) assessment. This review focuses on the non-destructive methods which are promising, or have already been, applied to the pre-harvest in field measurement including colorimetry, visible imaging, spectroscopy and spectroscopic imaging. Machine learning and regression models used in assessing ripeness are also discussed.

Objective: To identify and characterise genomic and phylogenetically isolated SARS-CoV-2 viral isolates in patients from Lambayeque, Peru. Methods: nasopharyngeal swabs were taken from patients from the Almanzor Aguinaga Asenjo Hospital, Chiclayo, Lambayeque, Peru, which have been considered mild, moderate and severe cases of COVID-19. Patients had to have tested positive for COVID-19, using a positive RT-PCR for SARS-CoV-2. Subsequently, the SARS-CoV-2 complete viral genome sequencing was carried out using Illumina MiSeq®. The sequences obtained from the sequence were analysed in Nextclade V1.10.0 to assign the corresponding clades, identify mutations in the SARS-CoV-2 genes and perform quality control of the sequences obtained. All sequences were aligned using MAFFT v7.471. The SARS-CoV-2 isolate Wuhan NC 045512.2 was used as a reference sequence to analyse mutations at the amino acid level. The construction of the phylogenetic tree model was achieved with IQ-TREE v1.6.12. Results: it was determined that during the period December 2020 and January 2021, the lineages s C.14, C.33, B.1.1.485, B.1.1, B.1.1.1, B.1.111 circulated, lineage C.14 the most predominant with 76.7% (n=23/30), these lineages were classified in clade 20D mainly and also within clade 20B and 20A. On the contrary, the variants found in the second batch of samples of the period September – October 2021 were Delta Variant (72.7%), Gamma (13.6%), Mu (4.6%), Lambda (9.1%), distributed between clades 20J, 21G, 21H, 21J and 21I. Conclusions: This study reveals updated information on the viral genomics of SARS-CoV-2 in the Lambayeque region, Peru, which is crucial to understanding the origins and dispersion of the virus and provides information on viral pathogenicity, transmission and epidemiology.

Avipoxvirus (APV), a linear dsDNA virus belonging to the subfamily Chordopoxvirinae of the family Poxviridae, infects more than 278 species of domestic and wild birds. It is responsible for causing the avian pox disease, which is characterized by its cutaneous and diphtheric forms. With a high transmission capacity, it can cause high economic losses and damage to the ecosys-tem. Several diagnostic methods are available and vaccination of birds can be an effective pre-ventive measure. To update the molecular characterization and phylogenetic analysis of viruses isolated in Portugal between 2017 and 2023, ten APV-positive samples were analyzed. A P4b gene fragment was amplified by PCR and the nucleotide sequence of the amplicons was deter-mined by Sanger sequencing. The sequences obtained were aligned using ClustalW, and a max-imum likelihood phylogenetic tree was constructed. With this study, it was possible to verify that the analyzed sequences are distributed in subclades A1, A2, B1, and B3. Since some of them are quite similar to others from different countries and obtained in different years, it is possible to conclude that there have been several viral introductions in Portugal. Finally, it was possible to successfully update the data on avipoxviruses in Portugal.

Software testing is an integral yet time-consuming component of software development, and even with capable software testing resources (technology and people), it is still regarded as problematic. Test automation is widely being utilised within the software industry to provide increased testing capacity to ensure high product quality and reliability. In this paper, we are specifically addressing automated testing whereby test cases are manually written. Test automation has its benefits, drawbacks, and impacts on different stages of development. Furthermore, there is often a disconnect between non-technical and technical roles, where non-technical roles (e.g., management) predominantly strive to reduce costs and delivery time whereas technical roles are often driven by quality and completeness. Although it is widely understood that there are challenges with adopting and using automated testing, there is a lack of evidence to understand the different attitudes toward automated testing (AtAT), focusing specifically on why it is not adopted. In this paper, the authors have surveyed practitioners within the software industry from different roles to determine common trends and draw conclusions. A two-stage approach is presented, comprising a comprehensive descriptive analysis and the use of Principle Component Analysis. In total, 81 participants were provided with a series of 22 questions and their responses are compared against job role types and experience levels. In summary, 6 key findings are presented covering expertise, time, cost, tools and techniques, utilisation, organisation, and capacity

India is ranked 5th in world in terms of Covid-19 publications accounting for 6.7% of the total. About 60% of the Covid-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometrics analysis of the publi-cation trends and citation structure along with identification of major research clusters. By performing network analysis of authors, citations, institutions, key-words, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by United States, China, UK, Italy, India in Covid-19 research may be attributed to the high prevalence of Covid-19 cases in those countries witnessing the first outbreak and also due to access to Covid-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. Large number of publications and citations from India are due to co-authored publications with countries like United States, UK, China, and Saudi Arabia. Findings show health sciences with highest the number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open access category. With India as focus, by comparing three major pandemics SARS, MERS, Covid-19 from biblio-metrics perspective, we observe much broader involvement of authors from multiple countries for Covid-19 studies as compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable develop-ment-related studies from the Covid-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding on how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in closure of scientific institutions.

Sometimes a pavement deflects only because of seasonal volume change of expansive soils in the pavement subgrade. Engineering practitioners expect an implementable and straightforward analysis method for a geosynthetic-reinforced pavement subjected to the swelling/shrinkage issue of expansive clayey subgrade, in an effort to find the bending moment, shear force and tension force distributions through the reinforced pavement, which are induced from the volumetric changes of subgrade soils. The virtual load method (VLM) was proposed in the past following the Timoshenko beam theory to analyze geosynthetic-reinforced pavement on expansive soils. In the VLM, the unknown virtual distributed load was obtained in the way by applying the inverse theory for the identification of material parameters of the pavement-foundation system. It was seen that the selection of the number of material parameters to obtain virtual load significantly affects the accuracy of the structural properties of the pavement and tensile properties of the geosynthetics if the linear least square method is used. In this paper, a unique numerical scheme was proposed in the hopes of solving the issue. After a forward problem was solved numerically, the Timoshenko beam deflection was taken as a start-up for the inverse problem to back analyze the load applied to the pavement. Solutions from forward/backward examples have explicitly shown the accuracy achieved related to the bending moment in the pavement and tension in the geosynthetic reinforcements. The proposed methodology can be applied for an in-depth understanding of the geosynthetic function for the mitigation of longitudinal cracks on pavements caused by heave/shrinkage of expansive soils.

AYUMI EYE is an accelerometer-based gait analysis device that measures the 3D accelerations of the human trunk. This study investigated the measurement accuracy of the AYUMI EYE as hardware as well as the accuracy of the gait cycle extraction program via simultaneous measurements using AYUMI EYE, a ground reaction force (GRF), and an optical motion capture system called VICON. The study was conducted with four healthy individuals as participants. The gait data were obtained by simulating four different patterns for three trials each: normal walking, anterior-tilt walking, hemiplegic walking, and shuffling walking. The AYUMI EYE and VICON showed good agreement for both the acceleration and displacement data. The durations of subsequent stride cycles calculated using the AYUMI EYE and GRF were in good agreement based on the calculated cross-correlation coefficients (CCs) with an r value of 0.896 and p-value less than 0.05, and their accuracies for these results were sufficient.

This study presents a meta-analysis of studies that investigate the effectiveness of chitosan administration on lifestyle-related disease in murine models. A total of 34 published studies were used to evaluate the effect of chitosan supplementation. The effect sizes for various items after chitosan administration were evaluated using the standardized mean difference. Using Cochran’s Q test, the heterogeneity of effect sizes was assessed, after which a meta-ANOVA and –regression test was conducted to explain the heterogeneity of effect sizes using the mixed-effect model. Publication bias was performed using Egger’s linear regression test. Among the items evaluated, blood triglyceride and HDL-cholesterol showed the highest Q statistics and I2 values, respectively. Other than blood HDL-cholesterol, total cholesterol, and triglyceride in feces, most items evaluated showed a negative effect size with high significance in the fixed- and random-effect model (p<0.0001). In the meta-ANOVA and -regression test, administering chitosan and resistant starch was revealed to be most effective in lowering body weight. In addition, chitosan supplementation proved to be an effective solution for TNF-α inhibition. In conclusion, chitosan has been shown to be somewhat useful in improving symptoms of lifestyle-related disease. Although there are some limitations in the results of this meta-analysis due to the limited number of animal experiments conducted, chitosan administration nevertheless shows promise in enhancing the quality of human life.

Antibiotics (ABs) are common medications used for treating infections. In cancer patients treated with immune checkpoint inhibitors (ICIs), concomitant exposure to ABs may impair the efficacy of ICIs and lead to a poorer outcome compared to AB non-users. We report here the results of a meta-analysis evaluating the effects of ABs on the outcome of patients with solid tumors treated with ICIs. PubMed, the Cochrane Library, and Embase were searched from inception until September 2019 for observational or prospective studies reporting prognosis of adult patients with cancer treated with ICIs and with or without ABs. Overall survival (OS) was the primary endpoint, and progression-free survival (PFS) was the secondary endpoint. The effect size was reported as hazard ratios (HRs) with a 95% confidence interval (CI), and an HR > 1 associated with a worse outcome in ABs users compared to no-ABs users. Fifteen publications were retrieved for a total of 2363 patients. In the main analysis (n = 15 studies reporting data), OS was reduced in patients exposed to ABs before or during treatment with ICIs (HR = 2.07, 95%CI 1.51–2.84; P<.01). Similarly, PFS was inferior in ABs users in n = 13 studies with data available (HR = 1.53, 95%CI 1.22–1.93; p<.01). In cancer patients treated with ICIs, AB use significantly reduces OS and PFS. Short duration/course of ABs may be considered in clinical situations in which they are strictly needed.

Recently, selection in pigs has been focused on improving the lean meat content in carcasses; this focus has been most evident in breeds constituting a paternal component in breeding. Such sire-breeds are used to improve the meat quantity of cross-breed pig lines. However, even in one breed, a significant variation in the meatiness level can be observed. In the present study, the comprehensive analysis of genes and microRNA expression profiles in porcine muscle tissue was applied to identify the genetic background of meat content. The comparison was performed between whole gene expression and miRNA profiles of muscle tissue collected from two sire-line pig breeds (Piertain, Hampshire). The RNA-seq approach allowed the identification of 627 and 416 differentially expressed genes (DEGs) between pig groups differing in terms of loin weight between Pietrain and Hampshire breeds, respectively. The comparison of miRNA profiles showed differential expression of 57 microRNAs for Hampshire and 34 miRNAs for Pietrain pigs. Next, 43 genes and 18 miRNAs were selected as differentially expressed in both breeds and potentially related to muscle development. According to Gene Ontology analysis, identified DEGs and microRNAs were involved in the regulation of the cell cycle, fatty acid biosynthesis and regulation of the actin cytoskeleton. The most deregulated pathways dependent on muscle mass were the Hippo signalling pathway connected with the TGF-beta signalling pathway and controlling organ size via the regulation of ubiquitin-mediated proteolysis, cell proliferation and apoptosis. The identified target genes were also involved in pathways such as the FoxO signalling pathway, signalling pathways regulating pluripotency of stem cells and the PI3K-Akt signalling pathway. The obtained results indicate molecular mechanisms controlling porcine muscle growth and development. Identified genes (SOX2, SIRT1, KLF4, PAX6 and genes belonging to the transforming growth factor beta superfamily) could be considered candidate genes for determining muscle mass in pigs.

Gas turbine power plants have important roles in the global power generation market. The examines thermodynamically the impact of steam injection for a combined cycle including a gas turbine cycle with a two-stage turbine and carbon dioxide recompression. The combined cycle is compared with the simple case without steam injection. Steam injection’s impact is observed on important parameters such as energy efficiency, exergy efficiency, and output power. It is revealed that steam injection reduces exergy destruction in components compared to the simple case. The efficiencies for both cases are obtained. The energy and exergy efficiencies respectively are found to be 30.4% and 29.4% for the simple case, and 35.3% and 34.1% for the case with steam injection. Also, incorporating steam injection reduces emissions of carbon dioxide.

Lubricated tribosystems such as main-shaft bearings in gas turbines have been successfully diagnosed by oil sampling for many years. In practice, the interpretation of wear debris analysis results can pose a challenge due to the intricate structure of power transmission systems and the varying degrees of sensitivity among test methods. In this work, oil samples acquired from the fleet of M601T turboprop engines were tested with optical emission spectrometry. Two-way analysis of variance (ANOVA) with interaction analysis and post hoc tests were carried out on measurement data from the whole fleet of the M-601T turboprop engines to study the impact of aluminum and zinc concentration on iron concentration. Finally, the developed model was used to evaluate the oil testing results for two specific engines of this type. Thanks to ANOVA, the assessment of engine health is based on a statistically proven correlation between the values of the dependent variable and the classifying factors.

Topic discovery is finding the main idea of large amounts of textual data. It indicates the recurring topics in the documents, allowing an overview of the texts. Current topic discovery models receive the texts, with or without pre-processing of Natural Language Processing. The processing consists of stopwords removal, text cleaning and normalization (lowercase conversion). A topic discovery model that receives texts with or without processing generates general topics since the input data is many uncategorized texts. The general topics do not offer a detailed overview of the input texts, and manual text categorization is a time-consuming and tedious task. Accordingly, it is necessary to integrate an automatic text classification task in the topic discovery process to obtain specific topics with their top words that contain relevant relationships based on belonging to a class. Text classification performs a word analysis that makes up a document to decide what class or category is being identified; then, integrating the text classification before a topic discovery process will provide latent topics depicted by top words with a high coherence in each topic based on the previously obtained classes. Therefore, this paper exposes a approach that integrates text classification into topic discovery from large amounts of English textual data, such as 20-Newsgroup and Reuters corpora. The text classification is accomplished with a Convolutional Neural Network(CNN) incorporating three embedding models based on semantic relationships. The topic discovery over categorized texts is realized with Latent Dirichlet Analysis(LDA), Probabilistic Latent Semantic Analysis(PLSA), and Latent Semantic Analysis(LSA) algorithms. An evaluation process was performed based on the normalized topic coherence metric. The 20-Newsgroup corpus was classified, and twenty topics with ten top words were discovered for each class, obtaining 0.1723 normalized topic coherence when applying LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters corpus was also classified, obtaining 0.1441 normalized topic coherence when applying the LDA algorithm to obtain 20 topics for each class.

This article addresses the question how the religious narrative identity and subjective religiosity change over the course of 15 years. The cases portrayed are deconverts who have changed their religious affiliations multiple times. It will be carved out what led to their deconversion and what remains as a core of their faith after they have turned away from organized religion for good. Interviews have been conducted at three time points and are analyzed using content analysis. It will become clear that the needs and expectations of the two individuals differ highly, as well as the reasons for turning away from a religious community; yet what is a common core in this joint faithful journey is their need to live their religiosity, now in a private setting.

The economy is a complex system, and the interactions between different agents are still not easy to quickly see-through. This complexity should reflect in a spatial dimension; in this way, tracking the tradeoffs opens a new window to the nexus of place and flow. Due to the fact, the economic systems often go through transitions and end up in another state, and this evolution is embedded in cities as the new motor of paradigm shift. To adequately represent and study these dynamics, we aim to develop an integrated method based on network analysis science and geographic economy synthesis to detect a multiscale navigator to track the transition from regional to the local level. This paper seeks to explore the specialization of regional clusters and their innovative behaviour in a particular lagging region, hence unfolding the innovation ecosystem to the smallest granularity then simulating the emergence phase of this complex system. First, our findings reveal that the local scale is relevant to start a bottom-up planning approach on policy implementation. Second, the global challenges could be addressed on a regional scale if we investigate the local complexity to unfold the innovation flow over its complex ecosystem and lead the knowledge as a critical element for inclusive transition, most probably into cities. Finally, the innovation network is an existing fact which can translate as a host for prosperity; In this line of reasoning, we intend to spatialize the track of the innovation flow to achieve transition hotspots and respond adequately to upcoming world concerns.

The doctoral defense is an important step towards obtaining the doctoral degree. As such, preparing for the event is necessary. Anecdotal evidence highlights that there is a wide variety of ways in which doctoral candidates prepare for the defense. In this work, I want to explore if there is a relation between the way in which a doctoral candidate prepares for the defense and two important aspects of the defense: the outcome of the defense, and the student perception during and after the defense. For this purpose, I first reviewed the literature on the topic of the preparation for the doctoral defense. Then, I carried out an international survey on the doctoral defense and analyzed the data of the 204 completed surveys with respect to the preparation for the defense using quantitative and qualitative methods. The methods I used included the statistical tests of the correlation between on one hand the preparation and on the other hand the defense outcome and student perception. I used inductive thematic analysis of the open-ended survey questions to gain deeper insight in the way candidates prepared for their defense. I found that candidates most often prepare by making their presentation, reading their thesis, and practicing. The most effective measure is the mock defense, followed by a preparatory course. Reading blogs, books, and chapters is a less effective preparation measure. The conclusion of this work is that doctoral candidates need to understand the format of their defense in order to be able to prepare properly, and that universities should explore either individual pathways to the defense or pilots using a mock defense and/or preparatory course to give their doctoral candidates the necessary tools to prepare for their doctoral defense.

In this paper, we present a general version of polygonal fitting problem called Unconstrained Polygonal Fitting (UPF). Our goal is to represent a given 2D shape S with an N-vertex polygonal curve P with a known number of vertices, so that the Intersection over Union (IoU) metric between S and P is maximized without any assumption or prior knowledge of the object structure and the location of the N-vertices of P that can be placed anywhere in the 2D space. The search space of the UPF problem is a superset of the classical polygonal approximation (PA) problem, where the vertices are constrained to belong in the boundary of the given 2D shape. Therefore, the resulting solutions of the UPF may better approximate the given curve than the solutions of the PA problem. For a given number of vertices N, a Particle Swarm Optimization (PSO) method is used to maximize the IoU metric, which yields almost optimal solutions. Furthermore, the proposed method has also been implemented under the equal area principle so that the total area covered by P is equal to the area of the original 2D shape to measure how this constraint affects IoU metric. The quantitative results obtained on more than 2,800 2D shapes included in two standard datasets quantify the performance of the proposed methods and illustrate that their solutions outperform baselines from the literature.

Shape of supracondylar fracture of the humeral of pediatric patients is analysed with Procrustes method. XR–images of fractures are considered both in anterio-posterior (AP) view (66 images) and in a lateral (L) view (24 images). Applying Procrustes method for both views mean images are constructed and compared. Variability of shapes is quantified with a shape principal component analysis. Non-parametric tests (permutational and bootstrap) do not indicate statistical difference between Procrustes mean shapes in anterio-posterior and lateral projections. It is shown, however, that AP and L shapes of humeral fractures differ in their variability quantified by shape principal components.

Biofilm is a complex community of microorganisms that are attached to surfaces and encased in a self-produced extracellular matrix. Machine learning (ML) techniques have been applied to various aspects of biofilm research, such as predicting biofilm formation, identifying key genes, and designing new therapeutic strategies. In this study, we conducted a bibliometric analysis of machine learning in biofilm research to provide a comprehensive overview of the current state of the field. We searched the Web of Science database for articles published included "machine learning biofilm". A total of 126 articles were identified and analysed. Our results showed that the number of publications on machine learning in biofilm has been increasing rapidly over the past decade, indicating a growing interest in the application of ML techniques to biofilm research. The analysis also revealed that the most common research topics in this area were related to biofilm formation, prediction, and control. Furthermore, the most frequently used ML techniques in biofilm research were artificial neural networks and support vector machines. Overall, our study provides valuable insights into the current trends and future directions of machine learning in biofilm research. It also highlights the importance of interdisciplinary collaboration between biofilm researchers and ML experts to drive innovation in this field.

In order to evaluate the economy of superhighway, on the basis of the analysis of the cost of the ordinary expressway and high speed railway, the cost of superhighway is estimated. On this basis, the standard of the toll of superhighway at all levels is determined by reference to the standard of the construction cost and the toll collection standard of the ordinary expressway. According to the toll collection standard of superhighway and the fuel consumption cost of superhighway at all levels, the cost of single car and the single person cost of superhighway are calculated. Based on the analysis of highway passenger transport, railway passenger transport and civil aviation ticket price, the single person cost per kilometer of the above travel modes is calculated and compared with the single person travel cost per kilometer of superhighway. The results show that the single person cost of superhighway is between 0.29 and 0.47 yuan /km, which is 0.28 yuan /km higher than the highway bus, 0.18 yuan /km higher than the ordinary expressway self driving and 0.23 yuan /km higher than the express train, but 0.78 yuan/km lower than that of the first class seat of high-speed train, and is 0.92 yuan/km far lower than that of civil aviation flight economy class and 2.42 yuan/km lower than the business class. Therefore, the superhighway trip has certain advantages in economy.

The practice of voluntary depigmentation is still prevalent in Africa, with a wide range of lightening cosmetics used. Our objective was to research and quantify three regulated and/or prohibited depigmenting ingredients present in lightening cosmetics sold in Ouagadougou. Twenty-nine lightening cosmetic samples were collected from vendors and HPLC analysis was subsequently conducted to identify and measure the concentrations of hydroquinone, clobetasol propionate, and kojic acid. The presence of hydroquinone was indicated on the label of 13.79% of the products, while 51.72% contained it after analysis. Furthermore, none of the products mentioned a concentration of hydroquinone exceeding 2.00%, even though 27.58% of them contained high concentrations. For clobetasol propionate, its presence was stated on the labels of 13.79% of the products, while 31.03% contained it. One sample had a clobetasol content exceeding 0.05%, although none mentioned a concentration higher than this value. Finally, while 24.13% of the samples claimed to contain kojic acid, only 17.24% did. We also observed that 41.38% of the samples contained combinations of two depigmenting ingredients investigated, with a predominance of the hydroquinone + clobetasol propionate (27.38%). These results demonstrate that manufacturers' declarations regarding the compositions of active ingredients in lightening cosmetics can sometimes be deceptive.

The Water-Cooled Lead Lithium (WCLL) Breeding Blanket (BB) is one of the two BB concepts candidate to be selected as driver blanket for the EU-DEMO fusion reactor. In this regards, the development of a sound architecture of the WCLL Central Outboard Blanket (COB) Segment, ensuring the fulfilment of the thermal and structural design requirements, is one of the main goals of the EUROfusion consortium. To this purpose, an exploratory research campaign has been launched to preliminarily investigate the thermo-mechanical performances of the Bottom Cap (BC) region of the WCLL COB segment, because of its peculiarities making its design different from the other regions. The assessment has been carried out considering the nominal BB operating conditions, the Normal Operation (NO) scenario, as well as a steady-state scenario derived from the in-box LOCA accident, the Over-Pressurization (OP) scenario. Starting from the reference geometric layout of the WCLL COB BC region, a first set of analysis has been launched in order to evaluate its structural performances under a previously calculated thermal field and to select potential geometric improvements. Then, the analysis of a more complete BC region has been conducted from both the thermal and structural standpoints, evaluating its structural behaviour in compliance with the RCC-MRx code. Finally, after some iterations and geometric updates, a promising geometric layout of the BC region has been obtained even though some criticalities still persist in the internal Stiffening Plates and First Wall. However, the obtained results clearly showed that the proposed layout is worthy to be further assessed to achieve a robust enough configuration. The work has been performed following a theoretical-numerical approach based on the Finite Element Method (FEM) and adopting the quoted Ansys commercial FEM code.

Diabetes mellitus leads to cardiovascular complications including impaired cardiac β-adrenoceptor (β-AR) function. Sodium-glucose cotransporter-2 (SGLT2) inhibitors, such as empagliflozin (EMPA) improve outcomes in heart failure patients and animal models thereof. Therefore, we have investigated the effects of EMPA on in vivo cardiac function (pressure-volume loop analysis) and β-AR-mediated contractile responses (papillary strips) in streptozotocin (STZ; 40 mg/kg, i.p.)-induced diabes in male Sprague Dawley rats (control, EMPA-treated control, diabetic, EMPA-treated diabetic) in a design reflecting late-onset treatment. 13-16 weeks after STZ injection treatment with a low dose of EMPA (10 mg/kg/day, daily oral gavage) or vehicle was administered for another 8 weeks. EMPA did not change cardiac function in control rats. Diabetic rats had a reduced heart rate, cardiac output, stroke work, rate of contration and rate of relaxation and increased isovolumic relaxation, whereas in vitro responses were not markedly attenuated. Treatment with EMPA showed a trend for improvement of some but not all parameters. Our results indicate that low dose EMPA treatment had limited effects on cardiac impairment despite reducing blood glucose when initiated after diabetes is manifest. Future studies with a higher dose and greater sample sizes could help to clarify the possible benefits of EMPA on the diabetic heart.

This paper proposes a curved link-slab (CLS) structure, simplified into a hingeless-arch model, to address the current cracking phenomenon of CLS concrete. The stress formula of the hingeless arch under various loads is derived based on the classical mechanic's method. Based on an actual bridge example, the mechanical properties of CLS are analyzed under different loads and load combinations. The results show that: (1) the CLS stress is significantly lower than that of the flat link-slab structure (FLS), (2) its stress values are less than the concrete tensile limit, and (3) the CLS can effectively solve the concrete cracking phenomenon on the link-slab. The rationality of the stress formula derived from the simplified model of the hingeless arch is verified using the finite element method (FEM). The parametric sensitivity analysis shows that variation of the reinforcement ratio of the CLS has a limited impact on it. Considering both the concrete tensile and compressive limit, the thickness of the CLS should be 15 cm to 20 cm, and its design span should be about 5% to7.5% of the main beam length.

Polydimethylsiloxane with hydroxy groups was functionalized to form functionalized polydimethylsiloxane, which subsequently underwent an addition reaction with isophorone diisocyanate to form the prepolymer. Next, 3-aminopropyltriethoxysilane (APTS) reacted with 3-glycidoxypropyltrimethoxysilane (GPTS) to produce bridged polysilsesquioxanes, and the sol–gel technology was employed to form hyperbranched polysiloxane nanoparticles with hydroxy groups, which was used as the additive. The hyperbranched polysiloxane and the prepolymer containing NCO functional groups then underwent an addition reaction to produce the hybrid materials. Fourier-transform infrared spectroscopy and 29Si nuclear magnetic resonance were used to characterize the structure of the polyurethane hybrid. Regarding thermal stability, after the hyperbranched polysiloxane nanoparticles was introduced, the integral procedural decomposition temperature increased from 348 ºC for polyurethane matrix to 859 ºC for the hybrid material. The results revealed that the thermal stability of the hybrid material substantially increased by approximately 247%.

The underperforming state of agricultural sector especially in Sub Saharan Africa, Nigeria inclusive is largely due to gender inequities in opportunities which undermine the sustainable and inclusive agricultural development. Agricultural value chain development requires equity in opportunities among men and women along the value chain, and this can only be done through interventions recommended by gender equity studies. The study analyzed gender equity opportunities, and youth engagement in rice value chains in southeast Nigeria. The multistage sampling technique was used in selecting the sample. The sample size consists of 476 youth rice value chain actors randomly selected from 48 villages across three states in South-East Nigeria. The data were analyzed using Modified Gender Equity Index (MGEI), and value addition models. The results from MGEI show that the level of gender equity opportunities for youth rice producers, processors and marketers were -0.21, -0.21 and -0.04 respectively, indicating inequity against the female youth. The overall value-added per ton by the male youth actors was ₦52,281 and ₦52,229 for female youth actors. The share of the value-added by male youth producers, processors and marketers were 51.65%, 49.41% and 47.78% while the share for female youth were 48.38%, 50.59% and 52.22%, respectively. The major constraints to youth engagement in rice value chain include lack of capital to start up, lack of access to credit, drought, lack of access to better technology, high cost of hiring machines, lack of technical skills, and stressful nature of rice value chain. It was recommended that Policies and interventions that ensure equal access to resources, opportunities, and decision-making power for both male and female youth actors should be implemented through targeted training programmes, awareness campaigns and capacity-building initiatives that promote gender equality.

In this work, we report a series of undoped and 1% Ga or Y doped lanthanum manganite compounds which have been synthesized via sol-gel technique. The obtained materials were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM/EDX). The XRD results confirmed a good crystallinity for all the studied samples and a change in the crystal structure of Ga or Y doped lanthanum manganite (Pm-3m space group) is observed compared to pristine sample (R-3c space group). Thermal analysis highlighted a different behavior of the doped samples compared to the undoped sample observed by the different mass loss in the analyzed temperature range. For these materials, it is shown for the first time that the static electrical conductivity, σDC of Ga or Y doped LaMnO3 compounds increases compared to the σDC pristine sample, and the thermal activation energy of the conduction EA,cond increases linearly with the temperature, for all three studied sample.

Aims: The aims of this meta-analysis were to assess: the prevalence of Post-Acute COVID-19 sequalae in HIV positive patients; average time of diagnosis; and meta-regress for possible moderators of PACS.Methods: A standard search strategy was used in PubMed, and then later modified according to each specific database to get the best relevant results. These included Medline indexed journals; PubMed Central; NCBI Bookshelf and publishers' Web sites in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “long COVID-19 or post-acute COVID-19 syndrome/sequalae”, “persons living with HIV or HIV. The criteria for inclusion were published clinical articles reporting HIV in association with long COVID-19, further, the average time to an event of post-acute COVID-19 sequelae among primary infected patients with COVID-19. Random-effects model was used. Rank Correlation and Egger's tests were used to ascertain publication bias. Sub-group, sensitivity and meta-regression analysis were conducted. A 95% confidence intervals were presented and a p-value < 0.05 was considered statistically significant. Review Manager 5.4 and comprehensive meta-analysis version 4 (CMA V4) were used for the analysis. The review/trial was PROSPERO registered (CRD42022328509).Results: A total of 43 studies reported post-acute COVID-19 syndrome. Of those, five reported post-acute COVID-19 sequalae in PLHIV. Prevalence of post-acute COVID-19 sequalae was 43.1% (95% CI 20.5% to 68.9%) in persons living with HIV (PLWH). The average time to PACS diagnosis was 4 months at 64% [0.64 (95% CI 0.230, 0.913) (P < 0.0000), I²= 93%] and at one year to PACS diagnosis was at 70 %, however with non-significant correlation (P > 0.05). On comorbidities, asthenia was associated with PACS at 17.6 % [0.176 (95% CI 0.067, 0.385) (P = 0.008), I²= 86%] while fatigue at 82%, however not related with PACS event incidence (P < 0.05). Americas, Asian and European regions showed PACS events rates of 82%, 43% and 19 % respectively (P<0.05) relative to HIV infection. Conclusion: PACS prevalence in PLWH was 43% occurring at an average time of 4 months at 64% and 70 % at 12 months however non-significant with PACS. Asthenia was significantly associated with PACS at 17.6 % while fatigue at 82%, however not related with PACS event incidence. Americas recorded the highest PACS event rates in PLWH.

Currently, an interactive environmental planning analysis system platform based on " Three Lines One Permit " (TLOP) is being developed to support environmental planning, construction project approval, and the application of TLOP outcome data in Guangzhou. The main objective is to provide governments, businesses and the public with environmental planning analysis tools to determine the site of construction projects. The platform is using the system architecture of the browser and server. Its core functions are interactive environmental planning analysis tool for construction project and the results display tool supporting map viewing. It provides users with a large number of detailed geospatial data and TLOP results data access and environmental planning analysis functions. This article describes the system architecture and implementation of the system platform and has a case study illustrating the system functionality. At present, the platform has been deployed and trial-operated. The content of the analysis framework is constantly expanding. This promotes the matching of environmental planning and analysis with local conditions. This will implement the application of TLOP and improve the efficiency of project construction and the level of ecological environment planning and management.

This study investigates the efficiency of a biogas-powered cooling system through the utilization of energy and exergy calculations. Biogas, which can be generated and stored in small-scale plants as needed, serves as a viable fuel source for absorption cooling systems. The present research focuses on the biogas consumption of a triple-effect absorption cooling system, specifically designed to supply a fixed cooling load of 100 kW under varying operational conditions. The study highlights the COP (Coefficient of Performance) and ECOP (Exergetic Coefficient of Performance) values of the system, along with the exergy destruction rates of its individual components, at the optimal temperatures of operation. Furthermore, to determine the necessary biogas consumption, the study explores the establishment of dedicated farms for various animal species, ensuring an adequate number of animals for biogas production. The findings reveal a COP of 1.78 and an ECOP of 35.4% at the optimized operating temperatures. The minimum mass flow rate of biogas is determined to be 0.0034 kg/s, facilitating the operation of the boiler with a methane content of 65%. The study concludes that a total of 290 head of cattle is required to generate the annual biogas consumption necessary for the cooling system. Also, number of the cattle is enough to establish 284 biogas plants in Bursa province in Türkiye.

The onset and progression of the salivary and gut microbiota, the transmission and the impact of the salivary microbiota on the development of early fecal microbial communities was herein explored. We characterized the microbiota of 82 faecal and 80 salivary samples, collected from 82 healty newborns at birth, 7, 15, 30, 90 and 180 days of life, by 16S rRNA targeted-metagenomics approach. Correlation heat-maps and co-occurrence networks were used to investigate microbial taxa relationship in saliva, gut and between the two ecosystems. In saliva microbiota, Streptococcus and Staphylococcus appeared as early commensals, dominating this ecosystem through the time, while Fusobacterium, Prevotella, Porphyromonas, Granulicatella and Veillonella were late colonizers. anaerobes as Enterobacteriace, Staphylococcus and Streptococcus, were gut microbiota pioneers, followed by the anaerobic Bifidobacterium, Veillonella, Eggerthella and Bacteroides. Streptococcus, Staphylococcus and Veillonella were shared by gut and saliva ecosystems (core microbiota). Early saliva and gut microbiota seem to evolve independently driven by local adaptation strategies, with the only exception for the oral Streptococcus and Veillonella genera, involved in gut microbiota development as seeding species. A more comprehensive knowledge of how oral microbiota may impact pathophysiological conditions of gut microbiota may open new avenues on the design of postbiotics.

Lagerstroemia is a genus of deciduous and evergreen shrubs and trees belonging to the family Lythraceae. Due to the attention paid to environmental and health issues, Lagerstroemia has become increasingly important in ecological environment protection, drug development, genetic resource protection, and application research. In order to gain an in-depth understanding of the current status and cutting-edge trends of Lagerstroemia research in the world, and objectively reflect the scientific capabilities and influence of relevant research countries, institutions, authors, and journals in this field. Using the visual analysis software VOSviewer and CiteSpace, a statistical analysis of the literature on Lagerstroemia in the Web of Science database was performed from 2002 to 2022. The results showed that the number of articles published on Lagerstromia in the world was increasing. Four of the five articles with the highest citation frequency were from the United States, and the number of articles published in Hortscience was the highest. In terms of subject distribution, the most frequently published subjects were plant sciences, pharmacology and pharmacy. These two disciplines focused on the cultivation of Lagerstroemia species and medicinal research on Lagerstroemia extracts. In terms of categories, science accounted for 41% of the top 10 subjects. Technical science accounted for a relatively large proportion. However, the amount of relevant literature in engineering science needs to be improved. India, the United States, and China were the main research forces in this field. In terms of international cooperation, China had close collaborations with many countries such as the United States, Japan, India, Russia, and the United Kingdom. Beijing Forestry University ranked first in terms of total number of publications, and the Chinese Academy of Sciences had the highest total citations and average citations. Meanwhile, most of the authors at the top of the list were Chinese scholars. Cluster analysis showed that the research of keywords such as “oxidative stress”, “protein” and “corosolic acid” were the research hotspots in recent years. Research on the chemical components and pharmacological effects of Lagerstroemia will be the focus of the research on Lagerstroemia.

This experimental study investigates the effect of scarf geometry in restoring the impact response of scarf patched 3 mm thick glass-fibre reinforced polymer (GFRP) matrix composite laminates. Traditional circular along with rounded rectangular scarf patch configurations considered as repair patches. Experimental measurements revealed that the temporal variations of force and energy response of the pristine specimen are close to that of circular repaired specimens. The predominant failure modes were witnessed only in repair patch which include the matrix cracking, fibre fracture, delamination and no discontinuity in adhesive interface was witnessed. When compared with the pristine samples, the top ply damage size of the of the circular repaired specimens is larger by 9.91 %, while that of the rounded rectangular repaired specimens is larger by 434.23 %. The results show that circular scarf repair is more suitable choice of repair approach under the condition of 37J low-velocity impact event even though the global force-time response is similar.

In order to reconstruct the origin and pathways of variola virus (VARV) dispersion, we analyzed 47 VARV isolates available in public databases and their SNPs. The mean substitution rate of the whole genomes was 9.41x10-6 (95%HPD:8.5-11.3x10-6) substitutions/site/year. The time of the tree root was estimated to be a mean 68 years (95%HPD:60.5–75.9). The phylogeographical analysis showed that the Far East and India were the most probable locations of the tree root and of the inner nodes, respectively, whereas for the outer nodes it corresponded to the sampling locations. The Bayesian Skyline plot showed that the effective number of infections started to grow exponentially in 1915-1920, peaked in the 1940s, and then decreased to zero. Our results suggests that the VARV major strains circulating between 1940s-1970s probably shared a common ancestor originated in the Far East; subsequently moved to India, which became the center of its dispersion to eastern and southern Africa, and then to central Africa and the Middle East, probably following the movements of people between south-eastern Asia and the other places with a common colonial history. These findings may help to explain the controversial reconstructions of the history of VARV obtained using long- and short- term calibrations.

Several specialized terpenoids that are used as phytoalexins are produced in the plant of tobacco. They play a key role in plant defense against pests and pathogens. Here, we performed genome-wide identification, classification, and expression profiling of the terpene synthase (TPS) genes in the tobacco genome. A total of 186 TPS genes were identified, which is significantly higher than that in wild Nicotiana, Capsicum and Solanum species. Phylogenetic analysis of these TPS genes in tobacco and Solanaceous relatives as well as Arabidopsis showed that a few tobacco-exclusive TPS clades occurred recently through gene duplication events. These clades are likely to be responsible for a range of compounds that separate N. tabacum cultivars from its wild relatives. Transcriptome sequencing of two cultivars of N. tabacum at several developmental stages revealed that some TPS genes from the TPS-a and TPS-b lineages are constitutively expressed and a few duplicated TPS genes are only expressed post anthesis at the time of harvest. Additionally, some TPS genes underwent alternative splicing, further diversifying the gene products of the TPS genes. Our findings provide an important candidate genes for further understanding of the diversity and evolution as well as functionality of TPS genes in the plant of tobacco.

In this paper, we study the black hole solution of self-similar gravitational collapse in the Einstein-axion-dilaton system for the elliptic class in four dimensions. The solution is invariant under space-time dilation, which is combined with internal SL(2,R) transformations. Due to the complex and highly nonlinear pattern of the equations of motion in the physics of black holes, researchers typically have to use various numerical techniques to make the equations tractable to estimate the parameters and the critical solutions. To this end, they have to ignore the numerical measurement errors in estimating the parameters. To our knowledge, for the first time in the literature on axion-dilation systems, we propose to estimate the critical collapse functions in a Bayesian framework. We develop a novel methodology to translate the modelling of the complexity of the elliptic black hole to a sampling problem using Hamiltonian Monte Carlo with stacked neural networks. Unlike methods in the literature, this probabilistic approach enables us not only to recover the available deterministic solution but also to explore possibly all physically distinguishable self-similar solutions that may occur due to numerical measurement errors.

Microstructured optical fibres (MOFs) are a new type of optical fibres that possess a wide range of optical properties and many advantages over common optical fibres. Those are provided by unique structures defined by a pattern of periodic or quasi-periodic arrangement of air holes that run through the fibre length. In recent years, MOFs have opened up new possibilities in the field of optics and photonics, enabling the development of advanced devices and novel optical systems for different applications. The key application areas of PCFs vary from telecommunications and high-power energy transmission to quantum optics and sensing. The stack-and-draw method is a standard manufacturing technique for MOFs, where a preform is first manually created and then drawn in a high-tech furnace into a fibre with the required final dimensions and position of the air holes. Since in the manufacturing process experimenters can control only a few parameters, mathematical models and numerical simulations of the drawing process are highly requested. They not only allow to deepen the understanding of physical phenomena occurring during the drawing process, but they also accurately predict the final cross-section shape and size of the fibre. In this manuscript, we assume thermal equilibrium between the furnace and the fibre and propose a functional form of the fibre temperature distribution. We utilise it with asymptotic mass, momentum, and evolution equations for free surfaces already available in the literature to describe the process of fibre drawing. By doing so, the complex heat exchange problem between the fibre and the furnace need not be solved. The numerical results of the whole asymptotic model overall agree well with experimental data available in the literature, both for the case of annular capillaries and for the case of holey fibres.

Crystallization often occurs in the laser welding of amorphous alloys, reducing the amorphous alloys’ properties. So, it is necessary to simulate the temperature field curve of the welding area by computer and then determine the power and laser moving speed of laser welding. In this paper, the temperature field curve of Zr41.2Ti13.8Cu12.5Ni10Be22.5(Vit1) amorphous alloy in laser welding is obtained by finite element analysis. The continuous heating curve (CHT) of Vit1 is fitted by the Vogel-Fulcher-Tammann (VFT) equation and the Kissinger equation. If the temperature field curve intersects with the CHT curve, crystallization occurs. The experiment results show that the VFT equation can be used to predict the crystallization of Vit1 better in laser welding. The tem-perature and welding time are increased by using low welding speed. Therefore, the temperature of the weld zone cannot fall in time, resulting intersection of the temperature field curve and the CHT curve. So, crystallization can be avoided if the welding speed is controlled within a rea-sonable range, and the highest temperature is kept under the CHT curve.

Spike shape and morphometric characteristics are among the key characteristics of cultivated cereals associated with their productivity. Identification of the genes controlling these traits requires morphometric data harvesting and analysis for numerous plants, which is automatable using technologies of digital image analysis. A method for wheat spike morphometry utilizing 2D image analysis is proposed. Digital images are acquired in two variants: a spike on a table (one projection) or fixed with a clip (four projections). The method identifies spike and awns in the image and estimates their quantitative characteristics (area in image, length, width, circularity, etc.). Models of sections, quadrilaterals, and radial model are proposed for describing spike shape. Parameters of these models are used to predict spike shape type (spelt, normal, or compact) by machine learning. The mean error in spike density prediction for the images in one projection is 4.61 (~18%) versus 3.33 (~13%) for the parameters obtained using four projections. F1 measure in automated spike classification into three types is 0.78 using logistic regression (one projection) and 0.85 using random forest method (four projections). The proposed method is implemented in Java; examples of images and user guide are available at http://wheatdb.org/werecognizer.

Colostrum is a natural product, issued by both mammals and humans in first week of lactation. Among different species, donkey colostrum is considered as having, besides a valuable composition in nutrients and immune factors, an outstanding similitude with human colostrum. In this context, and taking into account the scarcity of available data concerning the interaction between climate factors and colostrum quality, a trial was conducted aiming to identify the possible influence of environmental factors on donkey colostrum nutritional traits. A stock of 16 jennies from 2 farms located in the County of Cluj, during a 7 days postpartum period was analyzed. During experimental period the daily temperature, humidity, and wind velocity data were collected. Strong positive correlations may be reported between fat and lactose, and fat and protein respectively, while moderate to strong correlation is emphasized between lactose and protein content of donkey colostrum. Testing the influence of environmental temperature, relative humidity, and wind velocity influence upon nutritional content of donkey colostrum, results the neglectable influence of the wind velocity, the negative influence of the heat stress upon all studied colostrum components, and complex influence of relative humidity, which has positive influence on fat and lactose increase when it increases, while its increase has negative influence on protein content of donkey colostrum.

Pumpo is a Simmental breed and an essential livestock resource in the nucleus genetic cattle of Peru. This study provides a draft genome sequence of a top bull using a de novo assembly approach on the Illumina Novaseq X platform, yielding 208 GB of raw sequencing data with 150 bp paired-end reads. The final genome assembly resulted in a size of 2.06 Gb with an N50 contig length of 108 Mb and a completeness of 95.7% according to BUSCO analysis. A total of 973,925 simple sequence repeats (SSRs) were identified, with a predominance of mononucleotide repeats. The genome showed low heterozygosity (0.568%) and moderate repeatability (11.5%), aligning with other Bos taurus genomes. Reference-guided scaffolding improved the assembly quality significantly, producing an N50 scaffold value of 108 Mb. The SSR analysis of the Pumpo genome identified 973,925 SSRs with a frequency of 2,808 SSRs per kilobase, predominantly mononucleotide repeats, and 85,453 found in compound formations. Obtaining knowledge of the genome of a breeding Simmental bull is essential to optimize breeding programs and improve productivity.

Abstract: Background: Pain management is one of the main parts of treatments for Temporomandibular Disorders (TMDs). However, there is still a lack of high-quality evidence that compare the overall effects of these non-surgical treatments. The objective of this systematic review is to identify the most potential treatment protocol in dealing with pain caused by TMDs through a mixed comparison of interventions based on network meta-analysis. Methods: A systematic review and network meta-analysis of studies identified by searching PubMed, Embase, Medline, Ovid, and CINAHL. All the included studies should have characteristics that: (1) participants with TMDs of any age; (2) non-surgical treatments; (3) score of Visual Analog Scale (VAS) as the outcome measure; (4) randomized controlled trials. The Cochrane Bias Assessment Toll was used to assess the bias, the CINeMA website was applied to rate the confidence of evidence, and ADDIS software was used to conduct the network meta-analysis. Results: 46 studies were included in this review. The agreement between authors reached a kappa value of 0.78. The results of the network meta-analysis showed that wearable therapy devices are more likely to be the best choice for reducing the pain of patients with myogenic TMDs, whereas a combination of platelet-rich plasma injection and wearable therapy devices is more likely to be the best choice for reducing the pain in a long term after treatment for patients with mix-type TMDs. Moreover, the application of therapy equipment has the most potential in reducing pain in a long term after treatment for patients with articular TMDs. Discussion: Wearable devices have a great potential for pain syndrome caused by TMDs, the mechanism might come from a biomechanical perspective. However, the overall confidence rating of evidence is low. Studies with high quality are still needed in the future. Other: The PROSPERO Registration Number of this systematic review is CRD42021253442.

The problem of limited water supply in the Vhembe District (Limpopo Province, South Africa) is exacerbated by a preponderance of dissolved salts, which cause disagreeable taste and odour in the water as reported by the communities using this water for drinking. The water treatment plant that supplies the treated water to the communities in the District sources this raw water from the Nandoni Dam at the Livhuvu river catchment. However, there are no scientific studies that have been reported in the literature which focused on determining the levels of water salinity from various water sources in the municipalities of the District. Water samples from various sites across the Nandoni Dam, a primary source of domestic water supply in the region, were collected during all the seasons basis over a period of twelve months in order to ascertain the concentrations of dissolved salts in the dam. Onsite analyses of the water samples were conducted using the YSI ProDSS multimeter, while the laboratory water analyses were conducted using the spectroquant and atomic absorption spectrometers. Although salinity tests seem to indicate that the water sampled across most of the Nandoni Dam is brackish during all seasons of the year with the highest being 750 mg/L, water samples from the dam mid-outlet and the treatment plant are slightly below the WHO brackish water bracket of 500 mg/L with unfavourable taste for drinking. Results from this study indicate that the water sourced from the Nandoni Dam is not suitable for human consumption and therefore requires integrated water resource management, as well as robust and cost-effective water desalination treatment.

Universal Stress Protein (USP) plays an important regulatory role in the response to abiotic stress. Most of the research related to USP so far has been conducted on plant models such as Arabidopsis, rice, and cotton. The potato is one of the four major food crops in the world. Therefore, it is of great significance to study the expression pattern of the potato StUSP gene family under abiotic stress conditions. In this study, a total of 108 USP genes were identified from the genome of the Atlantic potato, divided into four subgroups. And based on the genetic structure, the physical and chemical properties of proteins and other aspects of their biological characteristics are comprehensively analyzed. Collinear analysis showed that the homologous genes of StUSPs and four other representative species (Arabidopsis, rice, coyote tobacco, and tomato) were highly conserved. The cis-regulatory elements of the StUSPs promoter are involved in plant hormones, environmental stress, mechanical damage, and light response. RNA-seq analysis showed that under different abiotic stresses, there are differences in the expression patterns of members of each subgroup. WGCNA co-expression analysis of the central gene showed that the differential co-expression gene is mainly involved in the plant-pathogen response process, plant hormone signal transduction, and the biosynthesis process of secondary metabolites. Through qRT-PCR analysis, it was confirmed that StUSP13, StUSP14, StUSP15, and StUSP41 may be important candidate genes involved in the response to adversity stress in potatoes. The results of this study provide the basis for further research on the functional analysis of StUSPs in the potato response to adversity stress.

The field of financial literacy is intricate and developing. This systematic review of the literature provides a thorough overview of financial literacy. It examines the sample of 3182 papers of the period 1990 to 2023 from different databases such as Scopus, Web of Science, IEEE, Science Direct, and JSTOR and identifies important publications, knowledge gaps, and rising themes. The four major topics that emerged are the degree of financial literacy among various groups of people, gender disparity in financial literacy, the influence of financial literacy on financial behavior and planning, and the impact of financial education on day-to-day decisions. Groups with lower levels of financial literacy include adults, women, people in the lower-income band, rural people, etc. Financial planning and financial behavior are positively associated with financial literacy. Financial literacy could be enhanced with financial education; however, output depends upon program design and experimental group. The review also discusses financial literacy in the context of gender disparity, including its definition, difficulties encountered, and possible solutions. This systematic study will help researchers, practitioners, and policymakers by providing insightful information on financial literacy and its ramifications.

Paper is a material whose mechanical properties are highly dependent on humidity and temperature. Which naturally also builds the relationship between the stiffness and strength of corrugated board and changing weather conditions. In this paper, attention is focused on the dependence of the physical properties of the cardboard on changes in humidity and temperature, which undergo dynamic fluctuations both during the production of corrugated board and during its storage. Two techniques were used to test this effect, namely numerical homogenization and global sensitivity analysis. Both methods were implemented to determine the theoretical relationships between the change in humidity and/or temperature in each layer of corrugated board and its global bending, compression and shear stiffness. The procedure was used to analyze different types of 5-ply and 3-ply cardboard. The obtained results allowed to build a complete map of the relationship between the change in humidity of selected layers and the strength characteristics of the full assembly.

Student retention is one indicator of accountability in the implementation of educational programs. Achievement of student retention rates indicates the performance of the quality objectives of an institution or college. To get an accurate picture of the factors related to retention, we need to do modeling. The retention variable is the time response variable measured in semester units. One of the statistical analyzes that can be used to analyze response data in time is survival analysis. The selection of an accurate analytical method in modeling will produce valid conclusions and impact making policies that are right and on target. This paper presents alternative modeling of student retention in distance education using survival analysis. The method used is a literature review. This paper also briefly describes distance education, open and distance education, distance education students' characteristics, distance education student retention, and survival models for modeling student retention in distance education.

Due to the demands of personal travels and entertainments, light airplanes and small business aircrafts are developing rapidly. Light airplane structure is simple; however, it lacks crashworthiness design, especially the considerations on the impact of energy absorption. Therefore, in an event of accident, significant damage to passengers will be usually incurred. Airplanes made of composite materials structurally have high specific strength and good aerodynamic configuration. These materials have become the primary choice for new airplane development. This study mainly explores the topology optimization analysis of the light aircraft’s cockpit made of carbon fiber reinforced composites. This paper compares the compression amounts in the original models of composite material and aluminum alloy fuselages with the models after optimization during the crash-landing, in order to investigate the safety of fuselages made of different materials after structural optimization under the dynamic crashing. This study found that the energy absorbed by the aluminum alloy fuselage during crash-landing is still higher than that by the carbon fiber reinforced composites fuselage. On the other hand, the aluminum alloy fuselage after topology optimization could have an energy absorption capability enhanced by 40%, as compared to the that of the original model of aluminum alloy fuselage.

The global COVID-19 pandemic claiming global spread continues to evolve, now to the verge of a third wave of outbreak possibly caused by the novel variants of concern of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2). The test positivity rate (TPR) and case fatal-ity rate (CFR) have increased steeply in the second wave of COVID-19 compared to the first. From the example of Kerala, a state in southern India, positivity increased from 1.33% at the peak of wave one in 10th June 2020 to 13.45% during 10th June 2021 in the second wave of pandemic. SARS-CoV-2 is an enveloped single-stranded RNA virus. Angiotensin-Converting Enzyme-2 (ACE-2) is a trans membrane surface protein present on multiple types of cells in the human body to which the viral spike protein attaches. Genetic variations in the SARS-CoV-2 and ACE2 receptor can affect the transmission, clinical manifestations, mortality and the efficacy of drugs and vaccines for COVID-19. Mutations are the primary cause of genetic variations. Given the high TPR and CFR, it is necessary to understand the variations of SARS-CoV-2 and cellular receptors of SARS-CoV-2 at the molecular level. In this review, we summarize the impact of genetic and ep-igenetic variations in determining COVID-19 pathogenesis and disease outcome.

This paper presents the findings of an exploratory study on the continuously generating Big Data on Twitter related to the sharing of information, news, views, opinions, ideas, knowledge, feedback, and experiences about the COVID-19 pandemic, with a specific focus on the Omicron variant, which is the globally dominant variant of SARS-CoV-2 at this time. A total of 12028 tweets about the Omicron variant were studied, and the specific characteristics of tweets that were analyzed include - sentiment, language, source, type, and embedded URLs. The findings of this study are manifold. First, from sentiment analysis, it was observed that 50.5% of tweets had the ‘neutral’ emotion. The other emotions - ‘bad’, ‘good’, ‘terrible’, and ‘great’ were found in 15.6%, 14.0%, 12.5%, and 7.5% of the tweets, respectively. Second, the findings of language interpretation showed that 65.9% of the tweets were posted in English. It was followed by Spanish or Castillian, French, Italian, Japanese, and other languages, which were found in 10.5%, 5.1%, 3.3%, 2.5%, and <2% of the tweets, respectively. Third, the findings from source tracking showed that “Twitter for Android” was associated with 35.2% of tweets. It was followed by “Twitter Web App”, “Twitter for iPhone”, “Twitter for iPad”, “TweetDeck”, and all other sources that accounted for 29.2%, 25.8%, 3.8%, 1.6%, and <1% of the tweets, respectively. Fourth, studying the type of tweets revealed that retweets accounted for 60.8% of the tweets, it was followed by original tweets and replies that accounted for 19.8% and 19.4% of the tweets, respectively. Fifth, in terms of embedded URL analysis, the most common domains embedded in the tweets were found to be twitter.com, which was followed by biorxiv.org, nature.com, wapo.st, nzherald.co.nz, recvprofits.com, science.org, and other URLs. Finally, to support similar research and development in this field centered around the analysis of tweets, we have developed an open-access Twitter dataset that comprises tweets about the SARS-CoV-2 omicron variant since the first detected case of this variant on November 24, 2021.

Multi-cropping is becoming an increasingly popular approach in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility losses, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensive assessment of the impact of multi-cropping intensity on the agroecosystem is a new and still under-researched approach that provides a better understanding of the impact of the individual indicators studied on the overall functioning of the biodiversed agroecosystems. Data from a stationary field experiment with multi-cropping at the Vytautas Magnus University, Experimental Station between 2020 and 2022 were used to achieve this objective. The study included maize, hemp and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these diversified crops on the agroecosystem, the interrelationships between the main indicators and the strength of their effects. It was found that the most positive effect on agroecosystem had ternary maize-hemp-faba bean crop. The effectiveness of other crops was from 2 to 35% less. The lowest one was calculated for the maize-faba bean crop.

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management, by measuring heart rate, heart rate variability (HRV), and various matrices related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and Biofeedback using smartwatches and finger monitor/sensor pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. we apply various algorithms and methodologies employed for HRV analysis and stress detection is discussed, including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers use smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions. Keywords: smartwatch; stress; wearable device; heart rate variability; comparative analysis

Osteoarthritis (OA) is the degeneration of cartilage in joints that results in bones rubbing against each other, it causes uncomfortable symptoms such as pain, swelling, stiffness, and can lead to disability. It usually occurs in the elderly and causes a large medical burden. The aim of this study is to evaluate cost-effectiveness between the standard treatment for osteoarthritis and the standard treatment with added crystalline glucosamine sulfate at various stages. The Markov analysis modelling was applied to evaluate the effect of both adding glucosamine compared to standard treatment from a societal perspective during whole patients’ lifetimes. Data input was collected by review in previous studies. The outcome was measured in quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) from a societal perspective was ap-plied with 3%-discounted for all cost and outcome. One-way analysis via Tornado diagram was performed to investigate the change of factors in model. In general, the adding glucosamine into the standard treatment proved to be more cost-effectiveness compared to the standard treatment. Particularly, early stage adding glucosamine in the treatment was cost-effectiveness then post-stage adding glucosamine. The addition of supplementing crystalline glucosamine sulfate to whole regimen at any stage was cost-effectiveness at willingness-to-pay (WTP) threshold

One of the challenges posed by renewable energies is the stabilization of parameters related to the quality of electrical energy. This study demonstrates the existence of a relationship between input blocks of hydropower and the variation of the fundamental frequency of the electricity grid. By mapping production data provided by Spanish Electric Network with frequency measured in the laboratory, it is shown that gradients of hydropower are correlated with frequency fluctuations for certain characteristic times. Considering hourly instances of energy input, the study compares two methods for calculating hydropower gradients (linear regression and pseudo-linear regression); and two methods for calculating local frequency extremes (the "specular inertia" method and analysis by comparison with the moving average), in order to corroborate the results.

Social media giants like Facebook are struggling to keep up with fake news, in the light of the fact that disinformation diffuses at lightning speed. For example, the COVID-19 (i.e. Coronavirus) pandemic is testing the citizens' ability to distinguish real news from falsifying facts (i.e. disinformation). Cyber-criminals take advantage of the inability to cope with fake news diffusion on social media platforms. Fake news, created as a means to manipulate readers to perform various malicious IT activities such as clicking on fraudulent links associated with the fake news/posts. However, no previous study has investigated the strategies used to create fake news on social media. Therefore, we have analysed five data-sets using Machine Learning (ML) that contain online news articles (i.e. both fake and legitimate news) to investigate strategies of creating fake news on social media platforms. Our study findings revealed a threat model understanding strategies of crafting fake news which may highly likely diffuse on social media platforms.

This study focuses on traffic condition analysis, especially in under developing country India and makes more visible of traffic flow by using traffic flow theory in order to understand real traffic condition. India is one of rapid economic growing countries and large market with second largest population 1.3 billion in 2018. On the other hand, there are social issues such as environment air pollution and global warming by traffic CO2 emission of transportation. This kind of condition is not only in India, but in other South East Asia and Africa in future. From recent more than one-month traffic observation in a typical major city Ahmedabad in Gujarat state, which has about 8 million population and industrialized city. In terms of traffic data collection, 14 CCTV cameras are used in the city. Based on multiple traffic cameras monitoring, author found the unique traffic flow characteristics and compares traffic flow theory. In this study, it is described what is key parameters to show real traffic congestion condition and how these congestion occurs.

Hope is important in the rehabilitation of persons with schizophrenia, through scales to measure hope are not appropriate for this population. The purpose of this cross-sectional study was to identify the psychometric properties of the Schizophrenia Hope Scale-9 (SHS-9) using data from 83 people with schizophrenia in four mental health centers and 762 healthy persons from two universities in South Korea. The mean (standard deviation) SHS-9 score of the participants with schizophrenia and healthy participants was 11.24 (4.90) and 14.83 (3.10), respectively. Lower scores indicate a lower level of hope. The internal consistency alpha coefficient was 0.92 with a 4-week test-retest reliability of 0.89. Criterion-related construct validity was established by examining the correlation between the SHS-9 and the State-Trait Hope Inventory scores. Divergent validity was identified through a negative relationship of SHS-9 with the Beck Hopelessness Scale. The construct validity of the SHS-9 was confirmed through principal component analysis with extraction methods, which resulted in a one-factor solution, accounting for 49–60% of the total item variance.. This study provided evidence for the validity and reliability of the SHS-9; therefore, it could be used to measure hope in people with schizophrenia.

The COVID19 pandemic tested the performance of hospitals and intensive care units around the world. Health care workers (HCWs) have been used to develop mental symptoms, but this was especially true during the COVID19 pandemic when HCWs must deal with many other sources of stress and anxiety that can usually be avoided, and long-term shifts and unprecedented population restrictions have weakened people's ability to cope with stress. The research aims to observe the dynamic interplay between burnout, depression, distress, and anxiety in HCWs working in various settings, with specific a focus on Emotional exhaustion, depersonalization, and a diminished sense of personal achievement in mediating a worst mental health status during the first wave of the COVID19 pandemic in Italy. To analyze that we performed a mediation analysis, from which resulted a strong correlation among depression, psychological distress, health perception and anxiety, and the impact of job burnout on anxiety, depression, and distress. Gender seemed to have a strong correlation with burnout, anxiety, and distress; the impact of COVID19 pandemic on Quality of Life seemed to affect anxiety and depression; the changing of mansion influenced depression and job burnout. Encouraging supportive and educational strategies would certainly be recommended to policy makers.

Research background – Effective management of modern business is impossible without the systematic development and implementation of solutions aimed at changing it, due not only to market demands and competitive conditions, but also to the requirements of various social groups. Corporate governance should be focused on ensuring that all stakeholders perform their functions in the best possible way and satisfy their needs while maintaining a balance of interests between them.Purpose – This article is devoted to the consideration of the possibility of using the integrated business analysis developed by its author, based on a balanced scorecard, in the process of studying the strategic aspects of a company's activities.Design/methodology/approach – The methodological basis of the study was the concept of business analysis as such and the concept of a balanced scorecard by R. Kaplan and D. Norton.Findings – It is shown that an integrated business analysis based on a balanced scorecard involves a comparison with the target value, identifying the causes of deviations and predicting the company's strategic rating. It includes a comprehensive analysis of financial performance, customer performance, internal business process performance, and learning and development performance of a company's balanced system. Integrated business analysis based on a balanced scorecard begins with the analysis of the indicators of training and development of the company's personnel and ends with the forecasting of its strategic rating. His methodological tools are expert- score rating, comparison method, graphical and tabular methods, factor analysis techniques and various forecasting methods. Development of an integrated business analysis based on a balanced scorecard is the result of further development of the concepts of business analysis and a balanced scorecard and is aimed at further improving the information support of the strategic management of the company, ensuring its sustainable development in the long term.Originality/value – The author comes to the conclusion that integrated business analysis based on a balanced scorecard is a new and quite effective tool for studying the strategic aspects of a company's activities, forming the analytical support for its strategic management in modern conditions. Its results can be used in the development of management decisions not only long-term, but also medium-term and short-term, providing a sufficient degree of stability of the company from the point of view of its main stakeholders.

Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The second scenario examined driver responses to phantom braking caused by the AEBS. As a result, the first scenario shows that none of the subjects could control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 seconds. In the second scenario, we found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.

Biosensors and wearable sensor systems with transmitting capabilities are currently developed and used for the monitoring of health data, exercise activities, and other performance data. Unlike conventional approaches, these devices enable convenient, continuous, and unobtrusive monitoring of a user’s behavioral signals in real time. Examples include signals relative to hand an finger movement/pressure control reflected by individual grip force data. As will be shown here, these directly translate into task, skill and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. On the basis of thousands of sensor data from multiple sensor locations, individual grip force profiles of an task expert, a trained user and a highly proficient user (expert) performing an image-guided and robot-assisted precision task with the dominant or the non-dominant hand are analyzed in several steps following Tukey’s “detective work” approach. Correlation analyses (Person’s Product Moment) reveal skill-specific differences in individual grip force profiles across multiple sources of variation, functionally mapped to the somatosensory brain networks which ensure grip force control and its evolution with control expertise. Implications for the real-time monitoring of individual grip force profiles and their evolution with training in complex task-user systems are brought forward.

Abstract: Long-term rainfall, temperature and solar radiation time series data are required to simulate crop yield and yield variability. A field experiment conducted at Mount Makulu was used to simulate the interactive effect of planting dates (SD1, SD2, SD3), maize varieties (PIO30G19, PIO30B50, ZMS606), and nitrogen fertilizer application levels (N1 = 66; N2 = 132; N3 = 198 kg N ha-1) on strategic and economic assessment. Statistical downscaled climate datasets from three GCMs from 1971-2000, 2010-2039, 2040-2069, and 2070-2099 using Representative Concentration Pathways (RCP4.5, RCP8.5) were utilized as DSSAT v4.7 inputs. The Seasonal analysis Program of the DSSAT model was used to simulate the impacts of climate change on maize yield. Results show increasing trends in temperature while there is variability in rainfall. The biophysical analysis showed varied grain yield responses to sowing date, maize cultivars and N application rates. The Mean-Gini analysis showed that PIO30B50 had an efficient late sowing data (SD3) with an application of 132 and 168 kg N ha-1 under both scenarios. Further, PIO30G19 at SD3 with 198 kg N ha-1 would be the most dominant management option for maize grain yield under future climate scenarios from 2010-2099. This research emphasizes the urgency for tailored adaptation actions and collaborative efforts along the maize value chain to mitigate future yield losses and sustain food security. Increasing maize grain yield requires implementing adaptation strategies such as varying sowing dates, adopting late-maturing varieties with high thermal heat requirements under future climate scenarios.

To assess the impact of tourism on the incidence of HIV and AIDS using Malaysian epidemiological data over the period of 1986-2011 with additional consideration for newborns infected with HIV. A population-level mathematical model was used to investigate: i) the role of tourism in the spread of HIV and measures used to reduce HIV spread in Malaysia; ii) whether the stability of infectious disease transmission is dependent on the flow of visiting tourists. We first derived an equation for the reproduction number (R0) threshold to quantify the contagiousness of HIV in Malaysia. Sensitivity analyses were used to determine the effect of various parameters on HIV transmission with respect to the increase in tourism. Our findings suggest that a stable disease-free state is sustainable based on the low value of R0 was 0.0017. This result is encouraging from a public health perspective. Approximately 14% of outbound tourists who leave the country return infected with HIV and the difference between the rate at which tourists move to the susceptible category and the rate at which tourists leave the susceptible is category is 12%. Estimated parameters for the influx of tourist rates, δ=1.1540x10-3[1.1477x10-3 - 1.15954x10-3], δ1=7.7901x10-4[7.7867x10-4 - 7.79418x10-4], and δ2=1.4030x10-8[-7.2287x10-7-7.5096x10-7], significantly impacted the spread of HIV in Malaysia. Some significant adjustments were made to the expected parameters. The methods used are helpful to public health analyses and provide a framework for epidemiological modeling of HIV spread among tourists. The trend and magnitude of tourist inflows may be determinants in the incidence of HIV and AIDS in Malaysia.

Heavy metals are toxic, persistent and non-degradable. After sedimentation and adsorption, they accumulate in water sediments. The aim of this study was to understand the heavy metal pollution of Qinjiang River sediments on the ecological environment and apportioning sources. The mean total concentrations of Mn, Zn, Cr, Cu, and Pb are 3.14, 2.33, 1.39, 5.79, and 1.33 times higher than the background values, respectively, except for the Co, Ni, and Cd, which are lower than the background values; Fe, Co, Ni, Cd, Cr, Cu, and Pb are all primarily in the residual state, while Mn and Zn are primarily in the acid-soluble and oxidizable states, respectively. Igeo, RI, SQGs and RAC together indicate that the pollution status and ecological risk of heavy metals in Qinjiang River sediments are generally moderate; among them, Fe, Co, Ni, Cd, Cr, and Pb are not harmful to the ecological environment of the Qinjiang River. Cu is not readily released because of its higher residual composition, depicting that Cu is less harmful to the ecological environment. Mn and Zn, as the primary pollution factors of the Qinjiang River, are harmful to the ecological environment. This heavy metal pollution in surface sediments of the Qinjiang River primarily comes from manganese and zinc ore mining. Manganese carbonate and its weathered secondary manganese oxide are frequently associated with a significant amount of residual copper and Cd, as a higher pH is suitable for the deposition and enrichment of these heavy metals. Lead-zinc ore and its weathering products form organic compounds with residual Fe, Co, Cr, and Ni, and their content is related to salinity. The risk assessment results of heavy metals in sediments provide an important theoretical basis for the prevention and control of heavy metal pollution in Qinjiang River.

: The purpose of this research was to verify the importance and performance of crisis management in Korean fitness center using Importance-Performance Analysis (IPA). For this study, 304 fitness center executives and managers in Seoul and Gyeonggi region were selected as from March 21 to May 17, 2020. Frequency analysis was performed using SPSS 24.0 and exploratory factor analysis was conducted to verify the validity and reliability. Priority analysis and IPA analysis were performed to compare the mean values, and the following results were obtained. First, in the first quadrant, there were 6 attributes besides keep social distancing between employees and customers. Second, in the second quadrant, there were four attributes in addition to regular disinfection of the gymnasium. Third, in the third quadrant, there were 6 attributes besides maintain furniture clean. Third, there were 6 attributes other than maintaining furniture clean in the third quadrant. Fourth, in the fourth quadrant, there are three attributes in addition to the restriction of face-to-face meetings. The conclusion is as follows. First, equip supplies for prevention of covid19, keep social distance, and check government support policies. Second, analyze of economic support policies, and research on their application methods. Third, Prepare various non-face-to-face communication methods and Untact(non-contact) marketing strategies. Fourth, make a checklist for factors with relatively little importance.

This research work is concerned in the exergy analysis of the continuous-convection drying of onion. The influence of temperature and air flow rate was studied in terms of exergy parameters. The energy and exergy balances were carried out taking into account the onion drying chamber. Its behaviour was analysed based on exergy efficiency, exergy loss rate, exergetic improvement potential rate and sustainability index. The exergy loss rates increase with the temperature and air flow rate augmentation. Exergy loss rate is augmented at higher drying air temperatures and flow rates because the overall heat transfer coefficient increase. On the other hand, the exergy efficiency increases with the air flow rate augmentation. This behavior is due to the energy utilization was improved because the most amount of supplied energy was utilized for the moisture evaporation. However, the exergy efficiency decreases with the temperature augmentation due to the free moisture is less, then, the moisture begins diffusing from the internal structure to the surface. The exergetic improvement potential rate values show that the onion drying process presents a high potential to improve the exergy efficiency. The sustainability index of the drying chamber varied from 1.9 to 5.1. To reduce the environmental impact of the process, the parameters must be modified in order to ameliorate the exergy efficiency of the process.

Objective To investigate the functional and biological significance of telomere-related active genes in cholangiocarcinoma (CCA) using single-cell sequencing and cell communication analysis. Methods First, we identified and annotated different cell types in CCA samples using single-cell sequencing data. Pseudotime analysis revealed the transcriptional status and differentiation process of CCA cells. We then explored interactions between CCA cells and their regulatory pathways through cell communication analysis. 47 key genes related to telomere activity were identified, and GO and KEGG pathway enrichment analysis was performed. Additionally, we constructed a prognostic model and verified the model's predictive efficacy. Finally, we identified genes associated with drug sensitivity in CCA patients and identified pathways associated with CCA prognosis through tumor TMB analysis. Results We identified 452 active telomere-associated cells. Then, we assessed telomere associated gene activity, obtaining 47 differentially expressed telomere genes by intersecting with CCA differentially expressed genes. Major up-regulated signaling pathways, including MIF-(CD74+CXCR4) and HLA-A-CD8A, were identified through pseudotime analysis. Three telomere-associated prognostic genes were identified using LASSO analysis, and prognostic-related models were built. In addition, PBRM1 mutation load was found to be highest in the high-risk group, making it a potential diagnostic target. Finally, drug sensitivity analysis revealed higher sensitivity to certain therapeutic drugs in the high-risk group, providing guidance for tailored CCA treatment. Conclusion The MIF-(CD74+CXCR4) and HLA-A-CD8A signaling pathways appear to be major pathways for CCA cell proliferation. Prognostic models based on telomere-associated genes show promise for application, indicating the biological and clinical significance of telomere activity genes in CCA.

High-temperature cooking process like frying, baking, smoking, or drying can induce chemical transformations in conventional food ingredients, causing deteriorative modifications. These reactions, including hydrolytic, oxidative, and thermal changes, are a common occurrence and can result in alterations to the food's chemical composition. In this study, a combination of sucrose and histidine (Su-Hi) was transformed through a process of charring or pyrolysis. The GC-MS profiling study showed that when sucrose and histidine (Su-Hi) are exposed to high temperatures (≈240°C), they produce carbonyl and aromatic compounds including beta-D-Glucopyranose, 1,6-anhydro (10.11 %), 2-Butanone, 4,4-dimethoxy- (12.89 %), 2(1H)-Quinolinone-hydrazine (5.73%), Benzenamine (6.35%), 2,5-Pyrrolidinedione, 1-[(3,4-dimethylbenzoyl)oxy]- (5.82%), Benzene-(1-ethyl-1-propenyl) (5.62%), and 4-Pyridinamine-2,6-dimethyl (5.52%). The compounds mentioned have the ability to permeate the cell membrane and contribute to the development of cell death by necrosis in human immune cells. The evidence available suggests that a specific set of pyrolytic compounds may pose a risk to immune cells. This investigation reveals the complex relationship between high-temperature cooking-induced transformations, compound permeation inside the cells, and downstream cellular responses, emphasizing the significance of considering the broader health implications of food chemical contaminants.

(1) Background: tuberculosis (TB) is considered one of the leading causes of death by a single in-fectious agent worldwide. This study aimed to identify hotspots of people diagnosed with tu-berculosis and abusive use of alcohol, tobacco and other drugs in communities through a geo-spatial intelligence application; (2) Methods: ecological study with a spatio-temporal approach. We considered tuberculosis cases diagnosed and registered in the Notifiable Diseases Information System, which presented information on alcoholism, smoking, and other drugs. Spatial Variations in Temporal Trends (SVTT) and scan statistics were applied for the identification of Hotspots; (3) Results: of 29.499 cases of tuberculosis were identified. And when we applied the STTT for al-coholism, three Hotspots were detected, one of which was protective (RR: 0.08 – CI95%: 0.02 – 0.32) and two at risk (RR:1.42 – CI95%: 1.11 – 1.73; RR: 1.39 - CI95%: 1.28 – 1.50). Regarding smoking, two risk clusters were identified (RR: 1.15 - CI95%: 1.01 – 1.30; RR: 1.68 - CI95%: 1.54 – 1.83). For other drugs, a risk cluster was found (RR: 1.13 - CI95%: 0.99 – 1.29) and two protections (RR: 0.70 - CI95%: 0.63 – 0.77; RR: 0.76 – CI95%: 0.65 – 0.89); (4) Conclusions: it was evidenced in the communities a problem of TB and drug addiction. Use disorder perhaps in a person's brain and behavior and leads to an inability to continue their treatment, putting the community at risk for TB.

Black yeasts are a highly specified group of fungi, which are characterized by a high resistance against stress factors. There are several factors enabling the cells to survive harsh environmental conditions. One aspect is the pigmentation, besides the melanin black yeasts often display a highly diverse carotenoid spectrum. Determination and characterization of carotenoids depend on an efficient extraction and separation, therefore especially for black yeast, characterized by thick cell walls specific protocols are needed to ensure analyses regarding stress responses in these fungi. Here we present both, a method to extract and analyze carotenoids and the unusual carotenoid composition of the black yeast Knufia petriola A95. Mechanical treatment combined with an acetonitrile extraction gave us very good extraction rates with a high reproducibility. The presented extraction and elution protocol allows the separation of the main carotenoids (7) in K. petricola A95 and should be suitable for the detection of additional carotenoids in other species. K. petricola A95 displays an unusual carotenoid composition, with mainly didehydrolycopene, torulene and lycopene. The pigment composition varied in dependency to oxidative stress but remained relatively constant if the cells were cultivated under low temperature. Black yeasts are a promising source for carotenoid production and other substances. To unravel the potential of these fungi new methods and studies are needed. The established protocol allows the determination carotenoid composition in black yeasts. Oxidative stress results in an adaptation in pigment composition in K. petricola A95. Future experiments have to be carried out to determine if didehydrolycopene functions as a protective agent itself or if it serves as a precursor for antioxidative pigments like torulene and torularhodin, which could be produced after induction under stress conditions.

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, we selected and analyzed 199 SCI and SSCI papers on HEI published from 2000 to 2023 by VOSviewer and CiteSpace software. The results indicate that the publication volume of HEI research has grown significantly in recent years, with China and the US being the most productive and influential countries. The author network shows the collaboration and contribution of different researchers and institutions, while the journal network reveals the multidisciplinary nature and scope of the field. The keyword network and the burst keyword analysis identify the main research themes and the emerging hot topics in HEI, such as online learning, big data, and artificial intelligence. The co-citation network of sources illustrates the theoretical and methodological foundations and influences of the field. The paper concludes with some implications and suggestions for future HEI research.

Digitized counter-diabatic (CD) optimization algorithms have been proposed and extensively studied to enhance performance in quantum computing by accelerating adiabatic processes while minimizing energy transitions. While adding approximate counter-diabatic terms can initially introduce adiabatic errors that decrease over time, Trotter errors from decomposition approximation persist. On the other hand, increasing the high-order nested commutators for CD terms may improve adiabatic errors but could also introduce additional Trotter errors. In this article, we examine the two-qubit model to explore the interplay between approximate CD, adiabatic errors, Trotter errors, coefficients and commutators. Through these analysis, we aim to gain insights into optimizing these factors for better fidelity, shallower circuit depth, and reduced gate number in near-term gate-based quantum computing.

New detailed geological/structural mapping as well as field-based structural analysis were carried out to investigate the deformation pattern of well-preserved high-pressure rocks of the Blueschist Unit exposed on SE Syros (Cyclades, Greece). Our new geological mapping revealed the occurrence of a metasedimentary sequence underlain by a meta-igneous sequence. The contact between these two sequences displays typically interfingering patterns in map-scale due to folding. The earlier ductile deformation phase recognized in the mapped area, is associated with the development of a penetrative foliation, which was formed under eclogite/blueschist facies conditions at peak conditions. The subsequent main deformation phase occurred at blueschist facies conditions synchronous with the early stages of exhumation of the high-pressure rocks. This phase is mainly associated with the formation of map-scale WNW-trending folds and a pervasive axial planar foliation linked with ESE-directed shearing. The main deformation ceased within blueschist facies conditions and exhumation of the rocks to greenschist facies conditions took place under very weak deformation. Greenschist retrogression observed in the southwestern part of the mapped area seems to be controlled by fluids rather than by intense deformation. Our results indicate that the high-pressure rocks of the Blueschist Unit exposed on Syros Island represent a large-scale pod of low deformation under blueschist to greenschist facies conditions, likely occupying the core of an extrusion wedge.

Considering that consumers are more willing to buy products online, companies are increasingly selling remanufactured products online through e-commerce platforms. Notwithstanding the high attention it elicits from researchers and companies, the study about the remanufacturing trading platform is in its infancy. Thus, we investigate 20 remanufacturing trading platforms related nowadays and make a gap analysis among them in terms of: (i) business model, (ii) product display, (iii) delivery products, (iv) quality assurance and after-sales service, (v) product review and star rate and (vi) transaction and payment. On this basis, we analyze features and trends for the development of remanufacturing trading platforms and propose six key applications aimed at filling the identified gaps. The consortium blockchain has the characteristics of security and transparency, high credibility, traceability and unfalsifiability, low cost, and strong scalability, which can provide effective support for the six key applications. Then, we construct the technical framework and the model of a consortium blockchain-supported remanufacturing trading platform. Further, we analyze the coupling mechanism between consortium blockchain and remanufacturing trading platform to explain how the remanufacturing trading platform supported by consortium blockchain achieves development characteristics. This study provides important guidance for the development, construction, and operation management of remanufacturing trading platforms.

We are living in a business context characterized by change, which today behaves with an unprecedented intensity, driven by the technological revolution and increased competition. As a result, increasingly large and complex companies are facing profound transformation processes in which the role of the human factor and of managers in particular, due to their high capacity to impact the organization, is essential. In response to this reality, the literature has developed a large number of approaches from different areas of knowledge: from business economics to psychology, including technical disciplines. This article offers a classification of these approaches that provides an overview of research on the role of managers in change management.

Emergent physics education research (PER) literatures have been disseminated through academic publications within the community. The growing body of literatures over years challenge Indonesian PER scholars to understand how the research community has been progressed and what possible future work that should be emphasized. Nevertheless, previous traditional method of thematic analysis performed serious limitation when the number of PER literatures exponentially increased. Dealing with this large volume of publications, one of the machine learning studies namely natural language processing (NLP) was employed in this study to automate our thematic analysis among Indonesian PER literatures that are still limited to be explored. One of the well-known NLP algorithm, latent Dirichlet allocation (LDA), has been performed to extract Indonesian PER topics and their associated development between 2014 and 2021. A total of 852 papers (~ 4 to 8 pages each) were collectively downloaded from five international conference proceedings organized by Indonesian PER researchers. Before their topics were modeled through LDA algorithm, our data corpus should be previously preprocessed through several common procedures of established NLP studies. Findings revealed that LDA has thematically quantified Indonesian PER topics and described their distinct development over certain period. The identified topics from this study demonstrated that Indonesian PER community has established robust development in eight distinctive topics to the present. They begin with initial interest in focusing research on physics laboratory and following the research based instruction in the late 2015. Indonesian PER scholars sustained to study continuous topic on 21st century skill until 2019 which gave way to a focus on developing relevant educational technology to address several forms of students’ performance including scientific literacy and problem solving. There is still lack of Indonesian PER literatures that have been attempted to address qualitative aspects of physics teaching and learning.

This paper presents a robust method based on graph topology to find the topologically correct and consistent subset of inter-robot relative pose measurements for multi-robot map fusion. However, the absence of good prior gives a severe challenge to distinguish the inliers and outliers, and wrong loop closures can seriously corrupt the fused global map. Existing works mainly rely on the consistency of spatial dimension to select inter-robot measurements, which does not always hold. In this paper, we propose a fast inter-robot loop closure selection method that integrates the consistency and topology relationship of measurements, which both conform to the continuity characteristics of similar scenes and spatiotemporal consistency. The traditional high-dimensional consistency matrix is decomposed into the sub-matrix blocks corresponding to the overlapping trajectory area. Building on this logic, a clustering method involving topology correctness of inter-robot loop closures is introduced to split the entire measurement set into multiple clusters. We define the weight function to find the maximum cardinality subset with topologically correct and consistent, then convert the weight function to a maximum clique problem in the graph and solve it. We evaluate the performance of our method in a simulation and in a real-world experiment. Compared to state-of-the-art methods, the results show that our method can achieve competitive performance in accuracy while reducing computation time by 75%.

Around 14% of the global population does not have access to electricity. About 95% of those are living in rural Sub-Saharan Africa. Often in these regions, diesel generators are the only source of electricity. The operating cost of these diesel generators is high. However, solar and wind energy are available in most of African countries. This study presents the analysis of designing an off-grid hybrid system with a wind turbine, PV, diesel generator, and battery to power a hospital, school, and 200 household village in four locations across Somalia. The research investigated the availability of wind-solar resources in selected locations. Designing of the system and economic-technical calculations were performed using HOMER. The selection of the optimum design was based on the Cost of Electricity and Net Present Cost. The results show that for Kabaal and Ceel Buur, a WT-PV-DG-Battery is the optimal system as the wind resource in these regions is high. For Saakov and Baki, a PV-DG-Battery system proves to be optimum as the wind resource is limited here. The study also evaluated the control strategy and proved that combined dispatch was the most cost-effective for these locations. The study concluded that hybrid systems are more economical than diesel systems.

La minería es una industria intensiva en energía que requiere una fuente estable de electricidad. Con el aumento de la demanda de minerales y la disminución de las leyes, se espera que la demanda de energía aumente en un 36% para el 2035. Este aumento de la demanda depende del uso de combustibles fósiles ya que la electricidad producida y comprada en las empresas mineras se basan principalmente en el caso de los combustibles fósiles, los costos de los sistemas de almacenamiento de energía solar y eólica han caído a una escala sin precedentes, lo que alienta a las empresas mineras a probar estas tecnologías.Entre los factores que influyen en el uso de energía renovable, se encuentra el beneficio a la comunidad en la etapa de operación y cierre o post-cierre de un proyecto minero, el siguiente factor es el perfil de consumo eléctrico o demanda es importante para el cálculo de su almacenamiento o no, de las energías renovables a utilizar. Como tercer factor está el cálculo del consumo en los procesos. Los rangos de penetración determinarán si es posible su almacenamiento de energía, y si es posible utilizar control híbrido (solar - eólico), para ello es importante el uso de herramientas digitales como el programa Holmer, es una herramienta importante que técnica y económica.El gobierno debe tener una perspectiva que ayude en los temas regulatorios necesarios para impulsar proyectos de energía renovable con diferentes incentivos e intereses según el contexto minero.