Miracle-dz/UniFAR-FTUs huggingface dataset:
Online photovoice to engage indigenous Cook Islands youth in the exploration of social and ecological wellbeing amidst a global disruption

Photovoice is a participatory action research method that aims to include the voices of groups by enabling people to record and reflect on their knowledge of issues they consider important. Drawing from critical pedagogy, feminist theory, and community-based approaches to document research, photovoice involves participants as collaborators by using photographs that participants take themselves. Engaging the participants in conversations regarding their photographs facilitates agency in the research process and provides valuable insights into the views, experiences, and knowledge of participants. Originating in the public sector as a method for assessing health needs, the use of photovoice has since gained popularity as a tool for examining perceptions regarding changes in the social and natural environment, and for exploring human-environment interactions. This paper reviews the use of photovoice as a research method to engage indigenous youth in the small island community of Rarotonga, Cook Islands for the exploration of ecological and social wellbeing during disaster times. Amidst the global disruption ensued by the COVID-19 pandemic, indigenous youth participants explored the responses and adaptations of their community to changes in the social and ecological environment of their island home. Given the associated lockdown measures and travel restrictions, photovoice interviews were conducted via Zoom, an online videoconferencing platform. By integrating the photovoice method with advanced online communication systems, the research team based in Auckland, New Zealand was able to collect data remotely while facilitating meaningful engagement with indigenous youth participants across geographic and cultural borders. The use of online photovoice via Zoom was shown to be an empowering and inclusive method for the engagement of indigenous youth and the promotion of collaborative, cross-cultural research partnerships for the exploration of social and ecological wellbeing during a global disruption.
A study of the types and manifestations of physicians' unintended behaviors in the DRG payment system

Introduction In recent years, China has implemented the Diagnosis Related Groups (DRG) payment system as part of its healthcare insurance reimbursement policy. Numerous studies have focused on the effectiveness of DRG payment system in controlling unreasonable growth in medical expenses. However, there has been no systematic report on the types of unintended behaviors exhibited by doctors under the DRG payment system. Methods The study first utilized interrupted time series analysis to analyze medical records and insurance data from eight hospitals. It investigated the data changes in MDC and ADRG groups before and after the implementation of the DRG payment system. Subsequently, a semi-structured interview method was employed to conduct qualitative research on the unintended behaviors of physicians, aiming to gain a more accurate understanding of specific changes in physician behavior after the implementation of the DRG payment system. Results This study discovered that doctors engage in unintended behaviors within the framework of the DRG payment system. Discussion In the early implementation of the DRG payment system in China, the contradictions between the flawed DRG payment methods and supporting systems and the actual diagnostic and treatment work manifested in the form of unintended doctor behaviors. Most of these unintended behaviors can be considered reasonable feedback from doctors to cope with the existing system flaws. They are conducive to identifying the deficiencies in China's DRG payment system and suggesting directions for improvement.
Parental resources and heritability as factors shaping children's health. An analysis of twins' self-rated health using TwinLife

We assess the relative and joint contributions of genetic and environmental factors on health during childhood and assume that parental resources are part of the environmental factors shaping children's health. We discuss theoretical background and empirical evidence concerning the effects of parental resources and heritability on children's health. Based on these findings we formulate six hypotheses guiding our empirical analysis, using data from TwinLife, a nationally representative sample of same sex twin pairs in Germany. We analyze self-rated health of 1,584 twin pairs aged 4–18. We did find strong support for the idea that parental resources influence children's health: household income and fathers' education consistently show positive effects. In contrast to our expectation, we did not find that genetic factors influence the health of well-off children less than the health of children living in families with lower SES. We also did not find that the genetic influence on health increases during childhood and adolescence. On the contrary our results indicate that the role played by genetic factors diminishes whereas environmental factors gain importance for health of children while growing up. This finding is good news for those interested in improving health chances of children from lower SES backgrounds because it demonstrates the malleability of children's health.
Plasma lipidomic profiling of thiopurine-induced leukopenia after NUDT15 genotype-guided dosing in Chinese IBD patients

Introduction Thiopurines, azathiopurine (AZA) and mercaptopurine (6-MP) have been regularly used in the treatment of inflammatory bowel disease (IBD). Despite optimized dosage adjustment based on the NUDT15 genotypes, some patients still discontinue or change treatment regimens due to thiopurine-induced leukopenia. Methods We proposed a prospective observational study of lipidomics to reveal the lipids perturbations associated with thiopurine-induced leukopenia. One hundred and twenty-seven IBD participants treated with thiopurine were enrolled, twenty-seven of which have developed thiopurine-induced leucopenia. Plasma lipid profiles were measured using Ultra-High-Performance Liquid Chromatography-Tandem Q-Exactive. Lipidomic alterations were validated with an independent validation cohort (leukopenia n = 26, non-leukopenia n = 74). Results Using univariate and multivariate analysis, there were 16 lipid species from four lipid classes, triglyceride (n = 11), sphingomyelin (n = 1), phosphatidylcholine (n = 1) and lactosylceramide (n = 3) identified. Based on machine learning feature reduction and variable screening strategies, the random forest algorithm established by six lipids showed an excellent performance to distinguish the leukopenia group from the normal group, with a model accuracy of 95.28% (discovery cohort), 79.00% (validation cohort) and an area under the receiver operating characteristic (ROC) curve (ROC-AUC) of 0.9989 (discovery cohort), 0.8098 (validation cohort). Discussion Our novel findings suggested that lipidomic provided unique insights into formulating individualized medication strategies for thiopurines in IBD patients.
Triple-hurdle model analysis of aquaculture farmers’ multi-stage willingness to participate in green and healthy aquaculture actions in China: based on ecological cognition and environmental regulation perspectives

Implementing the action of green and healthy aquaculture is an important measure to ensure the stable and secure supply of crucial agricultural products and promote the green and high-quality development of the fishing industry in China. This article divides the willingness to participate in the green and healthy aquaculture actions (GHAAs) into three stages: whether to participate, mode of participation, and degree of participation based on the dynamic decision-making process of the farmers. Based on micro survey data of aquaculture households in Zhejiang Province, this paper applies the Triple-Hurdle model to analyze the effect of ecological cognition and environmental regulation on multi-stage participation willingness, with a particular emphasis on exploring the differences in participation willingness between two types of green aquaculture methods, traditional and emerging technologies. The results show that ecological cognition has a positive promoting effect on the willingness to participate in actions and the degree of willingness to participate in both types of technological methods, the constrained environmental regulation policies significantly positively affects the degree of willingness to participate in traditional technological methods, and the incentive environmental regulation policies significantly positively affects the willingness to choose emerging technological methods and its degree of willingness to participate. The analysis of the regulatory effect of environmental regulation shows that constrained regulation policies can enhance the willingness of high ecological cognition farmers to participate in actions, while incentive policies are helpful for high ecological cognition farmers’ adoption willingness of emerging green production technology. In addition, there are scale and intergenerational differences in the effects of ecological cognition and environmental regulation on farmers’ willingness to participate in actions.
AATF/Che-1 RNA polymerase II binding protein overexpression reduces the anti-tumor NK-cell cytotoxicity through activating receptors modulation

Introduction AATF/Che-1 over-expression in different tumors is well known and its effect on tumorigenicity is mainly due to its central role demonstrated in the oncogenic pathways of solid tumors, where it controls proliferation and viability. The effect exerted by tumors overexpressing Che-1 on the immune response has not yet been investigated. Methods Starting from ChIP-sequencing data we confirmed Che-1 enrichment on Nectin-1 promoter. Several co-cultures experiments between NK-cells and tumor cells transduced by lentiviral vectors carrying Che-1-interfering sequence, analyzed by flow-cytometry have allowed a detailed characterization of NK receptors and tumor ligands expression. Results Here, we show that Che-1 is able to modulate the expression of Nectin-1 ligand at the transcriptional level, leading to the impairment of killing activity of NK-cells. Nectin-1 down-modulation induces a modification in NK-cell ligands expression able to interact with activating receptors and to stimulate NK-cell function. In addition, NK-cells from Che-1 transgenic mice, confirming a reduced expression of activating receptors, exhibit impaired activation and a preferential immature status. Discussion The critical equilibrium between NK-cell ligand expression on tumor cells and the interaction with NK cell receptors is affected by Che-1 over-expression and partially restored by Che-1 interference. The evidence of a new role for Che-1 as regulator of anti-tumor immunity supports the necessity to develop approaches able to target this molecule which shows a dual tumorigenic function as cancer promoter and immune response modulator.
Emotional abuse and depressive symptoms among the adolescents: the mediation effect of social anxiety and the moderation effect of physical activity

Background Childhood maltreatment has been identified as a risk factor for depressive symptoms. Social anxiety is closely associated with depression. Physical activity has been regarded as an underlying protective factor. Little is known about the complex relations among these factors in Chinese middle school students. This study aimed to explore whether social anxiety mediated the association between childhood maltreatment and depressive symptoms and investigate whether physical activity moderated the indirect or direct effect of the mediation model. Methods A total of 1,570 middle school students were recruited and measured for childhood maltreatment (measured by Childhood Trauma Questionnaire—Short Form Chinese version), social anxiety (as the mediator, measured by the Chinese simplified version of Social Anxiety Scale for Adolescents), depressive symptoms (measured by the Chinese version of Depression Anxiety Stress Scales-21), physical activity (as the moderator), and covariates such as age, sex, and nationality. The proposed relationships were tested using mediation and moderated mediation models. Results Emotional abuse was directly associated with depression, and the association between emotional abuse and depression was partially mediated by social anxiety. The associations between emotional abuse with depression and with social anxiety were moderated by physical activity. Conclusion This study revealed the mediating role of social anxiety and the moderating role of physical activity between emotional abuse and depression, which emphasizes the potential benefits of sufficient physical activity to reduce social anxiety and depressive symptoms, and more intervention studies should be conducted to explore the direct influence of sufficient physical activity in the future.
Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers

In this study, we demonstrate how freely available satellite images can be used to understand large-scale coastline developments along the coast of Mecklenburg-Western Pomerania (MWP). By validating the resulting dataset with an independent Light Detection and Ranging (LIDAR) dataset, we achieved a high level of accuracy for the calculation of rates of change (ROC) with a root mean square error (RMSE) of up to 0.91 m, highlighting the reliability of Earth observation data for this purpose. The study assessed the coastal system’s natural evolution from 1984 to 1990, prior to significant human interventions, and examined the period from 1996 to 2022, which was characterized by regular sand nourishments amounting to approximately 16 million m³. The results reveal notable changes in the study area, with a significant decline in erosive trends and an increase in the number of stable and accreting transects. However, it is important to note that the regular sand nourishments may be masking the true ROC along the coastline. Furthermore, the future supply of sand raises concerns about the sustainability of coastal developments, particularly in the context of future sea level rise (SLR). The study provides valuable insights for coastal authorities and policymakers, informing decisions on sand resource allocation and highlighting the need for appropriate adaptation strategies to address future SLR and ensure long-term coastal resilience.
Algorithm 971

Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis and the calculation of truncated singular value decompositions. The present article presents an essentially black-box, foolproof implementation for Mathworks’ MATLAB, a popular software platform for numerical computation. As illustrated via several tests, the randomized algorithms for low-rank approximation outperform or at least match the classical deterministic techniques (such as Lanczos iterations run to convergence) in basically all respects: accuracy, computational efficiency (both speed and memory usage), ease-of-use, parallelizability, and reliability. However, the classical procedures remain the methods of choice for estimating spectral norms and are far superior for calculating the least singular values and corresponding singular vectors (or singular subspaces).
Methods of Capturing and Tracking Objects in Video Sequences with Subsequent Identification by Artificial Intelligence (short paper)

In video surveillance systems, the task of capturing an object and following it is relevant. An even more urgent task is the process of identification with subsequent authentication of the person. This makes it possible to organize the appropriate security of a private person or property, as well as the security of particularly important objects. A method of capturing the object has been developed. The use of the best among the considered methods in automated video surveillance systems will allow increasing the efficiency of intelligent video surveillance systems with a sufficient level of reliability. Footage from capturing the object is recorded in files. Implemented object capture using the MediaPipe Face Mesh library. In the future, it is planned to carry out the identification of a person using machine learning.
Health Recommender System for Smart Cities

Recommender systems are a key element in transforming cities into smart cities, improving the quality of life of citizens, reducing costs, solving complex problems and provide quality services through personalized solutions. Nowadays, tourism is valuable for smart cities through its contributions to improve business, employment and economy. Smart city tourism can be enhanced by various services to improve citizen's life quality of. In this paper, we survey the existing literature on health recommender systems for smart cities and propose a novel approach to help tourists finding the appropriate doctor. The experiments showed that the built recommendation system has great effective promise to improve the efficiency of smart city tourism services.
Relationship between bacteria and nitrogen dynamics in

BACKGROUND AND OBJECTIVES: The bacterial community plays a crucial role in the nitrogen cycle. Oxidation ponds act as a natural treatment system for wastewater and are designed to promote the growth and activity of certain bacterial species that remove contaminants from the water. The nitrogen cycle in these ponds involves the conversion of nitrogen compounds through biological processes by bacteria. The presence or absence of certain bacterial species can greatly influence the efficiency of the nitrogen cycle in these ponds. This research investigates the relationship between bacteria and nitrogen dynamics, the key components of wastewater treatment, in oxidation ponds. This work aims to identify the bacterial community composition in oxidation ponds, investigate the role of bacteria in the transformation and removal of nitrogen compounds from wastewater in oxidation ponds, and evaluate the impact of environmental factors on the microbial communities and nitrogen dynamics in oxidation ponds. This study was carried out in the oxidation wastewater treatment at the King’s Royally Initiated Laem Phak Bia Environmental Research and Development or LERD Project, in Phetchaburi, Thailand. METHODS: Wastewater samples were collected from the 1st–5th oxidation ponds at a depth of 30 centimeter from the water surface and analyzed for various quality parameters including temperature, dissolved oxygen, potential of hydrogen, biochemical oxygen demand, nitrates, ammonia, and total kjeldahl nitrogen. Next-generation sequencing by Illumina Miseq was used to examine the 16S ribosomal ribonucleic acid of bacteria in the collected samples. Correlation test was used for statistical analysis. FINDINGS: The temperature, potential of hydrogen (1st to 5th ponds), and dissolved oxygen (2nd to 5th ponds) in the oxidation ponds were within the standard value. Fifteen bacterial phyla were identified in the five oxidation ponds, with phylum Proteobacteria accounting for the highest population comprising 47.56% of the total bacterial population. CONCLUSION: Genera Novosphingobium (phylum Proteobacteria), Ammonia-11 (phylum Verrucomicrobiota), and Vicinamibacteraceae (phylum Acidobacteriota) have the strongest relationships with ammonia, nitrate, and total kjeldahl nitrogen (R2 = 0.9710, 0.986, 0.8124). The bacterial population is a crucial factor in nitrogen nutrient and water quality. Novosphingobium is involved in the removal of ammoniafrom wastewater, Verrucomicrobiota act as denitrifiers, and Vicinamibacteraceae increases the total kjeldahl nitrogen levels. ARTICLE INFO
Integration of Database Management Systems and Video Game Engines for Optimal and Sub-Optimal Pathfinding

This study will examine the feasibility of more closely integrating databases with video games, with motivations being to take advantage of increased data locality, optimizations already implemented in database management systems, and preexisting solutions to a number of problems encountered by modern video games. Using O’Grady’s “Bringing Database Management Systems and Video Game Engines Together” as a base, this study will investigate how his approach can be both extended to the use of Weighted A* for sub-optimal pathfinding and applied to pathfinding problems derived from commercial games.
Aspect-based sentiment analysis of online peer re 鄄 views and prediction of paper acceptance results

Peer�reviews�of�academic�articles�contain�reviewers'�overall�impressions�and�specific�comments� on� the� contributed� articles,� which� have� a� lot� of� sentimental� information. � By� exploring� the� fine-grained sentiments� in� peer� reviews,� we� can� discover� critical� aspects� of� interest� to� the� reviewers. �The�results�can�also�assist�editors�and�chairmen�in�making�final�decisions. �However,� currentresearchontheaspectsofpeerreviewsiscoarse-grained,� and� mostly� focuses� on� the� overall� evaluation� of� the� review� objects. � Therefore,� this� paper� constructs� a� multi-level fine-grainedaspectsetofpeerreviews for� further� study. � First,� this� paper� uses� the� multi-level aspect�extraction�method�to�extract�the�aspects�from�peer�reviews�of�ICLR�conference�papers. � Comparative�experiments�confirm�the�validity�of�the�method. �Secondly,�various�Deep�Learning� models�are�used�to�classify�aspects'�sentiments�automatically,withLCFS-BERTperformingbest. � By� calculating� the� correlation� between� sentimental� scores� of� the� review� aspects� and� the� acceptance�result�of�papers,�we�can�find�the�important�aspects�affecting�acceptance. �Finally,�this� paper�predicts�acceptance�results�of�papers�(accepted/rejected)�according�to�the�peer�reviews. � The�optimal�acceptance�prediction�model�is�XGboost,�achieving�a�Macro_F 1 �score�of�87.43%.
Analysis of approximations of the gas compressibility factor derived from genetic algorithms

Hydraulic calculations are the primary tool for rational technical decisions related to the design and operation of pipeline systems. The compressibility factor is introduced into the gas equation of state to account for its real properties and depends on the pressure, temperature, and gas component composition. At present, the search for an accurate and computationally efficient approximation for the compressibility factor remains an urgent problem. This paper presents a methodology for constructing an approximation based on symbolic regression, and the proposed dependencies analysis provided. The average relative error of the presented models is 0.03%.