High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers and synthetical aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10°longitude×10°latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5% and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center.

Pig farms management is involved in multiple factors such as environmental conditions, animal behavior, weight gaining and others. In all those scenarios, it is fundamental to detect each individual and its development as it grows to reach the shipment phase. Therefore, the objective of this study was to apply an automatic individual pig detection algorithm using Deep Learning Techniques, in frames taken from videos recorded during the weaning phase in real production conditions of small and medium producers in tropical conditions in Colombia. The weaning phase was selected because individual detection in each cage is more difficult due to environmental adaptations that piglets undergo after nursing. Piglets tend to cluster together during this phase, making image processing more challenging compared to the fattening phase, where animals are more isolated. The You Only Look Once (YOLOv7) algorithm and VGG Image Annotator were used to detect individuals in two pens separated by gender. All animal postures, lighting conditions were considered. The Precision, Recall and mAP metrics were used to assess the model performance with different confidence values. A precision of 98.3% in a threshold of 0.9 was reached, Recall of 98.5% in a threshold of 0.85. Data augmentation techniques were important to increase the dataset and to have a more realistic model for individuals’ detection. The method used allowed us to identify all the complete pigs’ bodies under different posture and lighting situations.

Precise monitoring of individual crop growth and health status is crucial for precision agriculture practices. However, traditional manual inspection methods are time-consuming, labor-intensive, and often lack the spatial resolution required for detailed analysis. This research addresses the need for efficient and high-resolution crop monitoring by leveraging Unmanned Aerial Vehicle (UAV) imagery and advanced computational techniques. The primary objective was to develop a methodology for precise identification, extraction, and monitoring of individual corn crops throughout their growth cycle. This was achieved by integrating UAV-derived data with image processing, computational geometry, and machine learning techniques. UAV imagery was ac-quired bi-weekly at altitudes of 40m and 70m, capturing the entire growth cycle of a corn crop from planting to harvest. A time-series Canopy Height Model (CHM) was generated by analyzing the differences between the Digital Terrain Model (DTM) and the Digital Surface Model (DSM) derived from the UAV data. Local spatial analysis and image processing techniques were em-ployed to determine the local maximum height of each crop. Subsequently, a Voronoi data model was developed to delineate individual crop canopies, successfully identifying 13,000 out of 13,050 corn crops in the study area. For enhanced accuracy in canopy size delineation, vegetation indices were incorporated into the Voronoi model segmentation, refining the initial canopy area esti-mates by eliminating interference from soil and shadows. The proposed methodology enables precise estimation and monitoring of crop canopy size, height, biomass reduction, lodging, and stunted growth over time, providing valuable insights for precision agriculture practices. This work contributes to the scientific community by demonstrating the potential of integrating UAV technology, computational geometry, and machine learning for accurate and efficient crop mon-itoring at the individual plant level.

The aim of this study was to examine the oxidation of human serum albumin (HSA) caused by oxidative stress after an exhaustive exercise such as ultra-marathon race. Thus, blood samples from 12 adult runners who underwent a 103 km mountain ultra-marathon race were collected pre- and 24, 48 and 72 h post race. HSA was partially purified using affinity chromatography and then was subjected to Western blot analysis for disulfide dimers determination, indicating oxidation. The results were correlated with those from a previous study in which the same samples were analyzed using different oxidative stress markers and a good correlation with protein carbonyls (PC) at all time points was observed. Moreover there was a significant correlation with static oxidation-reduction potential (sORP) at 24 h, and a negative correlation with capacity oxidation-reduction potential (cORP) at 24 and 48 h. In addition, an individual analysis of albumin dimers exhibited great inter-individual differences. This inter-individual variability in the oxidation of HSA may suggest different interventions (e.g. through diet) in order to confront the effects on athletes’ organism after a strenuous exercise. In conclusion, this study supported the importance of the assessment of albumin dimers as a predictive marker for exercise-induced oxidative stress.

Precise individual tree or sample-based inventories derived from 3D point cloud data of mobile laser scanning can improve our comprehensive understanding of the structure, function, resilience, biodiversity, and ecosystem services of urban forests. This study assessed the performance of a hand-held laser scanning system for the extraction of tree position, diameter at breast height (DBH) and tree height (H) in an urban area. A total of 2083 trees of 13 species from 34 plots were analyzed. The results showed that the registration of tree positions using ground control points (GCPs) demonstrated high accuracy, with errors consistently below 0.4 m, except for a few instances. The extraction accuracy of DBH for all trees and individual species remained consistently high, with a total root mean square error (RMSE) of 2.06 cm (6.89%) and a bias of 0.62 cm (2.07%). Notably, broad-leaved trees outperformed coniferous trees, with RMSE and bias values of 1.86 cm (6%) and 0.76 cm (2.46%) compared to 2.54 cm (9.46%) and 0.23 cm (0.84%). Tree height extraction accuracy varied significantly among different species, with R2 values ranging from 0.65 to 0.92. Generally, both DBH and height were underestimated. Linear mixed effects models (LME) were applied to evaluate factors affecting the performance of HLS with the plot as a random factor. LME analysis revealed that plant type and terrain significantly influenced the accuracy of DBH and H derived from HLS data. Other fixed factors of plot area, tree density and trajectory length didn’t have significance. With a large sample size, we concluded that the HLS demonstrated sufficient accuracy in extracting individual tree parameters in urban forests.

More than 20 years after the discovery of the first anelloviruses (AVs), they still remain a mysterious group of viruses. To date, there is no clear understanding of their impact on the host organism, although information is emerging about their participation in various pathologies. However, it is well known that AVs are an important component of the human virome. In the current study we assessed the abundance of AVs in viromes from four nasal and pharyngeal samples from children with respiratory symptoms using a metagenomic approach. It is worth noting that three patients had known respiratory viruses and one did not have any. Regarding AVs, they were detected in all samples, namely Torque teno mini virus (TTMV). The greatest abundance and diversity of AVs (Torque teno virus (TTV), TTMV and Torque teno midi virus (TTMDV)) were shown in a diseased patient with an absence of respiratory viruses, which may indicate the potential involvement of AVs in the maintenance of respiratory symptoms. An activated immune system to combat the main pathogens, against the background of which the number of AVs decreases, is discussed as a possible reason for the reduced diversity of anellome in other patients. We also compared the results of the metagenomic approach and qPCR for major respiratory viruses, which were in agreement. In addition, metagenomic sequencing made it possible to obtain additional data on viral genomes in order to establish their taxonomic identification and characterize individual viral profiles in patients from the Siberian part of Russia.

AbstractBackground: In Ethiopia, 8.6% of maternal deaths are attributed to abortion. Despite the legalization of abortion and improved accessibility of safe abortion services, almost six in 10 abortions in Ethiopia are performed outside of the health facility. Abortion considered as an indicator for various aspects of reproductive health and healthcare access within a particular region or country. Despite the significance of the problem, there is a limited understanding of the magnitude of abortion and the contributing factors in the study area. Therefore, this study aimed to assess the prevalence of abortion and determinant factors among reproductive-age women in the Sidama regional state of Ethiopia.Methods: A community-based cross-sectional study was conducted from October to November 11, 2022, among 1,130 women of reproductive age. We utilized a multi-stage sampling method to select eligible women. A structured and pretested questionnaire was utilized to collect the data using Open Data Kit (ODK) mobile application. Due to the hierarchical nature of the data, a multilevel logistic regression model was applied. Variables with p-values < 0.25 on bi-variable analysis were included in a multivariable regression model. In the multivariable regression model, variables with a p-value < 0.05 were declared as statistically significant factors of abortion. Results: Nearly one-fifth (19.5%) of the women had a history of abortion. From the individual level determinates; women with formal education (AOR=0.44; 95% CI: 0.24-0.79), and planned pregnancy (AOR=0.41; 95% CI: 0.28-0.61) had lower odds of abortion. While from the community related factors; urban residence increased the odds of abortion (AOR=2.25; 95% CI: 1.20-4.20) as compared to the rural residence.Conclusion: the prevalence of abortion among reproductive age women of Northern Zone of Sidama Region was high. Education and a planned pregnancy serve as protective factors for abortion, while the risk of abortion increased among women reside in urban area. Therefore, to lower the abortion rate, it is better to implement a comprehensive approach, focusing on education, family planning, and urban-specific intervention.

To address the insufficient mechanical properties of calcined phosphogypsum, this research aims to investigate the utilization of basalt fiber and calcium carbonate whiskers as reinforcing agents. The study examines their impact on the flexural and compressive strength, toughness, water resistance, and tensile strength of calcined phosphogypsum. In the individual tests, basalt fibers with different lengths (3 mm, 6 mm, 9 mm, and 18 mm) were added at dosages of 0%, 0.5%, 1.0%, and 1.5% respectively. The findings demonstrate that basalt fiber effectively enhances the flexural and compressive strength, toughness, and tensile strength of calcined phosphogypsum, albeit potentially compromising water resistance. Among the various fiber lengths, the 6 mm fibers exhibit the most advantageous influence on the performance of calcined phosphogypsum. A subsequent test was conducted to investigate the impact of cross-scale fibers on the properties of calcined phosphogypsum by mixing 6 mm basalt fibers and calcium carbonate whiskers. The results illustrate that calcium carbonate whisker refines the pores, thereby improving the flexural strength and toughness of calcined phosphogypsum. Furthermore, it compensates for the water resistance limitations associated with the sole utilization of basalt fiber while further augmenting the tensile strength and strain capacity. However, it should be noted that increasing the dosage of both calcium carbonate whiskers and basalt fibers concurrently leads to increased porosity of phosphogypsum and reduced compressive strength.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

This study examines a case involving a 7-year-old child who developed dengue symptoms following Qdenga vaccination. Despite initial negative diagnostic results, molecular analysis confirmed an infection with DENV4. Next-generation sequencing detected viral RNA from both DENV2 and DENV4 serotypes, which were identified as vaccine-derived strains using specific primers. Phylogenetic analysis further confirmed that these sequences belonged to the Qdenga vaccine rather than circulating wild-type viruses. This case underscores the critical need for precise diagnostic interpretation in vaccinated individuals to avoid misdiagnosis and to strengthen public health surveillance. A comprehensive understanding of vaccine-induced viremia is essential for refining dengue surveillance, improving diagnostic accuracy, and informing public health strategies in endemic regions.

Internal combustion engine (ICE) vehicles contribute significantly to the global warming through their immense quantity of CO2 emissions and are on the way to be replaced by zero emission alternative solutions. Several replacement techniques with scientifically sound performances are proposed for the propulsion equipment including the related supply chains from renewable sources, but they often cannot fulfill the huge demand quantitatively. The paper discusses the quantitative aspects of the real demand with the example of the actual automotive park in Switzerland and analyses different alternatives like conventional EV’s, fuel-cell vehicles or energetic chains based on sustainable fuels like e-methanol or synthetic solar fuels. The analysis comprises energy efficiency considerations.

Herein, we examined the effects of weather parameters and individual clinicodemographic risk factors on hemorrhagic stroke (HS) incidence, severity on admission, and disability at discharge in a harsh desert climate. In a retrospective design we studied patients admitted to a stroke unit in Arab Emirates in 2016-2019. With a distributed lag nonlinear model we explored immediate and delayed effects of weather on stroke incidence. Supervised machine learning was used to build models predictive of scores in NIHSS and mRS scales. We assessed model performance by calculating ROC AUC, F1 scores, specificity, and sensitivity. HS risk increased after a significant change in any weather parameter. The risk was reduced below baseline after 1-week adjustment to environmental changes. Climate input from the previous 3 days yielded reliable classification models. Humidex was a better predictor of severity than air temperature, whereas body mass index, age, and time of day at stroke onset were the strongest clinical predictors. Weather parameters before admission were stronger predictors of disease severity than individual clinical factors. We addressed limitations of previous studies by analyzing a full set of climate parameters: ambient temperature, relative humidity, humidex, atmospheric pressure, and wind speed. Predictive models may help to optimize patient management and develop preventative strategies.

Single nucleotide polymorphisms in the mitochondrial genome have been investigated in relation to breast cancer. Certain variants could be associated with an increased risk of this malignant disease. These associations underline the importance of mitochondrial function in cancer biology and highlight the potential for mtDNA-based biomarkers and future therapies. The general objective of this research was to develop a model which is capable of identifying nonlinear patterns in breast cancer mitochondrial sequences. Association rules were used to explore mtDNA variant positions. The analysis included 41 breast cancer patients and 28 control samples. An a priori algorithm identified significant association rules with lift > 1 and confidence > 0.5. A total of 5562 rules for cancer and 157,140 for control sequences were refined after redundancy removal. A total of 150 associations were identified, of which only 78 showed significant support and confidence, while 315 and 1438 positions showed strong associations with breast cancer. Association rules analysis revealed significant patterns, especially in sequences associated with the control region and a specific locus around genes coding for tRNAs and NADH dehydrogenase subunits. However, further research is necessary to establish causality, clinical relevance, and to confirm these findings.

Introduction: One of the key strategies to achieve sustainable development goal by reduce preventable maternal deaths below 70 per 100,000 is increasing awareness about major obstetrics danger sign. Mother's awareness of obstetric danger signs in developing country is relatively low regardless of attempts trough many local and national program. It is crucial to increase women’s knowledge of obstetric danger signs through education and awareness-raising efforts. Despite its importance to reduce maternal deaths, Studies are limited only to the Northern Ethiopia. Objective: This study aimed to assess prevalence of knowledge of obstetric danger signs and associated factors among women who delivered in the last 12 months in Sidama region, Ethiopia. Methods: We conducted a community-based cross-sectional study from October to November, 2022. A multi-stage sampling procedure was utilized to select study participants. A structured and pretested questionnaire was utilized to collect data. A multilevel mixed-effects negative binomial regression model was used to control effects of clusters and confounders.Results: Out of 1,140 study participants, only 1,130 study participants took part in the study making a response rate of 99.12%. The overall prevalence of knowledge of obstetrics danger sign was estimated as 22.3% (95%CI: 18.7, 25.9). Government employed women (AIRR = 1.37; 95% CI: 1.2, 1.6), women who had access to mass media (AIRR = 1.16; 95% CI: 1.08, 1.25), women who had received model family training (AIRR = 1.15; 95% CI: 1.1, 1.25), autonomous women (AIRR = 1.15; 95% CI: 1.04, 1.25), women who had faced health problems during pregnancy (APR = 1.21; 95% CI: 1.11, 1.32) and urban women (APR = 1.22; 95% CI: 1.09, 1.62) were factors associated positively with knowledge of obstetrics danger sign. Conclusion: The prevalence of knowledge of obstetrics danger sign is found to be lower compared with the national average. Residence, mass-media exposure, model family planning, problem faced during pregnancy and women autonomy are the main predictors of knowledge of obstetrics danger sign. Public health policy makers should enhance health literacy at for focused on rural community. Awareness creation should be improved through mass media. Health providers should educate women during maternity health services to empower women for decision making process.

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

The study of values at European and global level has gained momentum along with the theory of values launched by Schwartz. Values are dormant, hidden, unobservable and impossible to measure directly. They exist somewhere within the human being, manifested by different attitudes, depending on their degree of generality. The paradigm of basic human values implies shared universal values that are encountered in cultures all over the world. The theory of values designed by Schwartz has refined the pool of 19 basic individual values representing principles in individuals and group, further describing the dynamic relationships among them. This study presents practical evidence of the dynamics between individual values, the dynamics theorized by Schwartz in 2012. Following the development of an online questionnaire made up of 46 items with online responses options on a Lickert scale from 1 to 6, where 1 represents less important and 6 represent very important, 220 young people from Western Romania voluntarily responded. By testing the hypothesis assuming the dynamic relationship between the two values through multiple regression analysis, the results demonstrate that in Model 1, which involves a linear relationship, health explains 42% of the variance in security with a F =161,215 significant at p <.01. In Model 2, which involves a curvilinear relationship, health explains 50% of the variance in security version with a F = 35,336 significant at p <.01. The incremental prediction optimization of 8% added by including the squared security accounts for the curve in the regression line, indicating the existence of a curvilinear relationship between security and health. The dynamic relationship demonstrates that upper limit and lower limit aspects of security, significantly influence the health value in a negative way. Normal levels of security trigger a high level of prioritization of health value. The implications of this type of relationship are discussed in explaining the value phenomenon at individual level. The study shows limits due to the selected sample, focusing exclusively on young people with higher education from the Western region of Romania. This sample was the target group of "The National Identity of Romanian Youth" project which designed this research.

The study tries to find out the impact of investors demographic variables on the return from the stock market. The data has been collected from the brokerage and Marchant banks for individual investors investments, return and demographic characteristics. The research covers the period from 2009 to 2021 and have a decade long enough to identify the trend. The structural break in the data also been adjusted to avoid any kind of endogeneity. The regression results suggest that demographic variables affect the investment pattern and beta return for the investors. the demographic variables such as education, location and experience have positive links with the beta whereas age and income show negative association. The education, income and experience variables are also found to be significant in the empirical analysis.

Objective: To summarize the prevalence of PASC/Long COVID symptoms among the general population reported in published articles. This narrative review examined 21 PASC symptoms. Methods: A PubMed/manual search returned 114 articles on general PASC/Long COVID symptoms. Manuscripts were excluded if they were not research studies, didn’t report symptom prevalence, or used a pediatric population. Ninety-eight studies were selected for review and 59 met criteria for inclusion. Risk of bias was assessed with the Hoy critical appraisal tool. Results: After excluding studies with high risk of bias, meta-analysis of prevalence for 21 symptom categories ranged from 2.6-28.7% in studies based on surveys to 0.3%-7.1% in studies based on EHR data. Conclusions: PASC symptom studies are limited by variability in study design and representation of the general population. Further research is needed to effectively cluster symptoms in meaningful ways that enable focused treatment.

In this article, we present two topics related to mathematical economics. We offer an intriguing proposal for securing cost and production functions in the face of uncertainty and risk. We discuss the relationship between individual and social preferences. This is important because traditional revealed preference theory does not account for such factors.

The goal of our study was to examine the effect of regional characteristics of living environment on individual a priori and a posteriori dietary patterns of the Russian population. For the analysis, we used cross-sectional data from the Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation study of 2013-2014. The sample included 18,054 men and women 25-64 years of age from 12 regions. Based on the frequency of consumption of basic foods, four a posteriori empirical dietary patterns (EDPs), along with an a priori cardioprotective dietary pattern (CPDP) were identified. To describe the regional living environment, 5 regional indices were used. The adherence to the meat-based EDP was directly associated with deterioration of social living conditions and the more northerly location of the region of residence. The probability of CPDP increased with deterioration of social living conditions, an aggravation of demographic crisis, higher industrial development of the region, as well as with a decline in the economic development of the region, income and economic inequality of the population. We detected some gender-dependent differences in associations. The revealed patterns reflect the national dietary preferences of Russians, and regional indices characterize the effect of living environment.

In the contemporary business world, digital transformations have undergone vast and important developments over the last several decades, and they have aided in the development of the virtual team concept, in which geographically dispersed team members work to achieve a common goal. Virtual teams, according to the literature, suffer from process losses more frequently than their face-to-face counterparts. Although just a few studies have looked at the effects of individual differences in virtual teams, this study fills in the gaps by examining the impact of individual differences: Age Disparity (AD), Gender Disparity (GD), Language Competency (LC), and IT Competency (ITC) in management perspective on virtual team adaptation in the Sri Lankan private sector. A survey was used to collect data from a sample of 175 private sector companies in Sri Lanka during the COVID- 19 pandemic, and the data was analyzed using partial least squares path modeling (PLS) to test the study's hypotheses. The results indicated that the hypotheses were statistically significant only in the language competency and IT competency and their effects were in the expected direction. Future research could benefit from perceptions of employees in public sector organizations.

The characteristics of response to stressful situations depend on a complex of factors such as personality traits, emotional regulation, health state, features of the nervous system, motor functions and proprioception. In cases of disruption of the brain's dopamine system due to disease or chemotherapy, hormone discharge due to stress, changes in emotions and proprioception may occur. The aim of our study was to find the relationship of stress resilence in verbal test and individual differences performed in proprioceptive test in onco-patients, sportsmen and group of control; as well as to observe the differences between these groups in the verbal stress resistance and individual differences proprioceptive tests. The results showed that onco-patients were less resistant as per verbal stress resistance outcomes for a major part of variables compared to other groups. The sportsmen were superior in verbal Risk and Control dimensions compared to other groups; but less in Positive Affectiveness. The proprioceptive test perfomance revealed the only statistically significant difference in performance in the dimension related to Mood, showing more Pessimism in the sportsmen group, but more Optimism in the oncopatients at temperamental (or intrisinc) level. The obtained results can be used by psychologists, therapists, coach and healthcare when needed to attend the specific needs of public, being pateints or sportsmen, etc.

Sweetness drives consumption of added sugars, so understanding how individuals differ is important for developing strategies to lower sugar intake. However, methods to assess hedonic response to sweetness vary, making results across studies difficult to integrate. We compared methods to measure optimal sucrose concentration in 21 healthy adults (1) using paired-comparison preference tracking vs. ratings of liking, (2) with participants in the laboratory vs. at home, and (3) using aqueous solutions vs. vanilla milk. Tests were replicated on separate days to assess test-retest reliability. Test-retest reliability was similar between laboratory and home testing, but tended to be better for vanilla milk and preference tracking. Optimal sucrose concentration was virtually identical between laboratory and home, slightly lower when estimated via preference tracking, and about 50% lower in vanilla milk. However, individual optimal sucrose concentration correlated strongly between Methods, test Locations, and Stimuli. More than 50% of the variability in optimal sucrose concentration could be attributed to consistent differences among individuals while much less variability was attributable to differences in Methods, test Locations or Stimuli. These results demonstrate convergent validity between measures of preference and liking, support testing at home to lower participant burden, and suggest that aqueous solutions can be useful proxies for some commonly consumed beverages for measuring individual differences.

The COVID19 coronavirus SARS-CoV2 spreading in Wuhan and now worldwide has been shown to use angiotensin-converting enzyme 2 ACE2 as its host cell receptor, like the severe acute respiratory syndrome coronavirus (SARS-CoV). Epidemiology studies found different sex and age groups have different susceptibility to infection, and very skewed severity and mortality of the virus infection, with male, old age, and comorbidity being the most inflicted. Here by analyzing GTEx and other public data in 30 tissues across thousands of individuals, we found significantly higher expression in Asian females compared to males and other ethnic groups, an age dependent ACE2 expression decrease and a highly significant decrease in type II diabetic patients. Consistently, the most significant expression quantitative loci (eQTLs) contributing to high ACE2 expression are close to 100% in East Asians, >30% higher than other ethnic groups. Together with the shockingly common enrichment of viral infection pathways among ACE2 anti-expressed genes, binding of virus infection-related transcription factors at ACE2 regulatory regions, the repression of ACE2 expression by inflammatory cytokines and by type 2 diabetes, and the induction by estrogen and androgen (both decrease with age) established a negative correlation between ACE2 expression and CovID19 fatality at both population and molecular levels. Our results will be instrumental when designing potential prevention and treatment strategies for ACE2 binding coronaviruses in general.

Smart grids require flexible data driven forecasting methods. We propose clustering tools for bottom-up short-term load forecasting. We focus on individual consumption data analysis which plays a major role for energy management and electricity load forecasting. The two first sections are dedicated to the industrial context and a review of individual electrical data analysis. We are interested in hierarchical time-series for bottom-up forecasting. The idea is to disaggregate the signal in such a way that the sum of disaggregated forecasts improves the direct prediction. The 3-steps strategy defines numerous super-consumers by curve clustering, builds a hierarchy of partitions and selects the best one minimizing a forecast criterion. Using a nonparametric model to handle forecasting, and wavelets to define various notions of similarity between load curves, this disaggregation strategy applied to French individual consumers leads to a gain of 16\% in forecast accuracy. We then explore the upscaling capacity of this strategy facing massive data and implement proposals using R, the free software environment for statistical computing. The proposed solutions to make the algorithm scalable combines data storage, parallel computing and double clustering step to define the super-consumers.

An entrepreneur is a business-able physical person who performs activities to gain the profit and who is registered according to law. Starting from the national and theoretical and legal solutions and court practice from comparative law, the authors analyze the concept and the legal position of an individual entrepreneur noticing the problems and inconsistencies in legal regulations. The authors of the work make a few conclusions and suggestions: 1) terminology is not coordinated with legal terminology from comparative law. In our law, the legal term is “entrepreneur”, which is a too wide and unspecified term because in economic profession this term represents the genus term for individual and collective entrepreneurship; 2) analyze all forbidden activities for entrepreneurs, judge the reasons pro et contra and work on eliminating prohibitions and favouring legal entities; 3) set by law the bankruptcy of an individual entrepreneur i.e. the individual bankruptcy of a physical person; 4) work on passing a separate legislation in the field of the individual entrepreneurship, especially on passing and changing the laws which would regulate handicrafts (including old crafts and jobs of home industry), free professions as well as agricultural activity.

Fragile X syndrome (FXS) is the most frequent monogenic form of autism spectrum disorder (ASD). Autistic FXS is caused by loss of the fmr1 gene product, the fragile X mental retardation protein (FMRP), triggering physiological and behavioral abnormalities. It is correlated with clock components for behavioral circadian rhythm. Mutation of this gene causes the disturbances in sleep patterns and circadian behavior commonly observed in patients with autistic FXS, accompanied by frequent dysregulation of melatonin synthesis and melatonin-dependent signaling. These changes impair vigilance, learning and memory, and are also linked to autistic behavior including the abnormal anxiety response. However, although several possible causes, symptoms, and clinical features of ASD have been investigated, the correlation between an altered circadian rhythm and autistic FXS has not been extensively studied. Recent works have highlighted the impact of melatonin on the nervous, immune, and metabolic systems. Even though utilization of melatonin for sleep disorder in ASD has been considered in clinical research, further studies should be aimed at its neuroprotective role in ASD during developmental period. In this review, we focus on the regulatory circuits involved in melatonin dysregulation and circadian system disruption in those with autistic FXS. Additionally, we discuss the neuroprotective effect of melatonin intervention. This may improve neuroplasticity and physical capability. We also review the underlying molecular mechanisms, and suggest that melatonin may be a useful novel treatment for autistic FXS, countering the adverse effects of circadian variation.

The mutton sheep breeding industry has transformed significantly in recent years, from traditional grassland free-range farming to a more intelligent approach. As a result, automated sheep face recognition systems have become vital to modern breeding practices and have gradually replaced ear tagging and other manual tracking techniques. Although sheep face datasets have been introduced in previous studies, they have often involved pose or background restrictions (e.g., fixing of the subject’s head, cleaning of the face), which restrict data collection and have limited the size of available sample sets. As a result, a comprehensive benchmark designed exclusively for the evaluation of individual sheep recognition algorithms is lacking. To address this issue, this study develops a large-scale benchmark dataset, Sheepface-107, comprised of 5,350 images acquired from 107 different subjects. Images were collected from each sheep at multiple angles, including front and back views, in a diverse collection that provides a more comprehensive representation of facial features. In addition to the dataset, an assessment protocol is developed by applying multiple evaluation metrics to the results produced by three different deep learning models: VGG16, GoogLeNet, and ResNet50, which achieved F1-scores of 83.79%, 89.11%, and 93.44%, respectively. A statistical analysis of each algorithm suggested that accuracy and the number of parameters were the most informative metrics for use in evaluating recognition performance.

The aim of this work was to study age-related changes in the behaviour of adult Wistar rats using the open field (OF) and elevated plus maze (EPM) tests. Behavioural changes related to motor activity and anxiety were of particular interest. Results showed that as male and female rats progressed from 2 to 5 months of age there was a decrease in the level of motor and exploratory activities, and an increase in the level of anxiety. Age-related changes were dependent upon initial individual characteristics of behaviour. For example, animals that demonstrated high motor activity at 2 months become significantly less active by 5 months, and animals that showed a low level of anxiety at 2 months become more anxious by 5 months. Low-activity and high-anxiety rats did not show any significant age-related changes in OF and EPM tests from 2 to 5 months of age, except for a decrease in the number of rearings in EPM. Significant individual differences in the behaviour of rats in OF and EPM tests observed at 2 months were not apparent by 5 months.

Cochlear implantation (CI) allows rehabilitation for patients with severe to profound hearing impairment. Although the use of a robotic assistant provides technical assistance to the surgeon, the assessment of the impact of its use on auditory outcomes remains uncertain. We aim to com-pare the hearing results of patients who underwent bilateral cochlear implantation, one side was performed with manual insertion and the other side with robot-assisted insertion. The electrode array intrascalar positioning and the surgery duration were also studied. This retrospective intra-individual study involved 10 patients who underwent bilateral cochlear implantation. The study included 2 infants and 8 adults. The unique composition of this cohort enabled us to utilize each patient as their own control. Regarding speech disyllabic recognition, pure tone average, ECAP, ratio of array translocation, basilar membrane rupture, percentage of translocated electrodes there was no difference between manual and robot-assisted CI groups. This study is the first to compare intra-individual hearing performance after cochlear implantation either manually or robot-assisted. The number of patients and the time delay between manual and robotic implantation may have led to a lack of power, but there was no apparent difference in hearing performance between manual and robotic implantation.

Domestic cats (Felis catus) are widespread worldwide as the most popular pets. This medium-sized carnivore have well-known negative effects on biodiversity, but there is still need to better understand the proximate causes of its predation. Based on a citizen science project, we assessed the role of spatiotemporal (i.e., latitude, longitude and seasons), climatic (i.e., rainfall), anthropogenic (i.e., human footprint, HFI) and individual (i.e., sex and age) variables on the number of preys returned home by cats in metropolitan France. Over the 5 048 cats monitored between 2015 and 2022, prey from 12 different classes (n= 36 568) were returned, being 68% mammals, 21% birds and 8% squamates. Shrews brought home by cats peaked during summer, while rodents were recorded during summer-autumn. Birds brought home by cats peaked in spring-summer and in autumn, and lizards in spring and in late summer. Lower HFI was associated with more voles and mice brought home and the opposite trend was observed for lizards and birds. Younger cats were more prone to bring home shrews, birds and reptiles. Although environmental factors play a minor role in prey brought home by cats, some geographical characteristics of prey species distribution partly explains the hunting behaviour of cats.

In this paper, we define the consumer preference relation from scratch. We study algebraic and topological properties for the preference magma that reflects the consumer. We also consider the influence of society on an individual's preference.

A new clothing resistance model is described and applied to characterize the human thermal and moisture climates. The climate was described by the thermal (rcl,t) and evap-orative (rcl,e) resistances of comfortable, imaginary clothing. The key input variable of the model is the rate of sweating (λEsw). Since sweating is an individual-specific process, the model applies to the individual. The observations were carried out by a single individual in Martonvásár (Hungarian lowland, Central Europe) in the summer of 2023 and the winter of 2024. During the observations, the observer walked at a speed of 1.1-1.7 ms-1 in weather-appropriate clothing. Among the results, we would highlight the following: Dur-ing large environmental heat surpluses, the rcl,t values were found to be between 0.1-0.5 clo-t (clo-t = 0.155 m2·℃·W-1), while the rcl,e values fell between 0.4-0.8 clo-e (clo-e = 0.155 m2·hPa·W-1). The values of the parameters close to 0 were caused by intense sweating (λEsw > 200 Wm-2). The applicability of the model is limited and largely depends on the rela-tionship between λEsw and the metabolic heat flux density.

Effective development of digital twins of real-world objects requires sophisticated data collection techniques and algorithms for automated modeling of individual objects. In City Information Modeling (CIM) systems, individual buildings can be modeled automatically at the second Level Of Detail or LOD 2. Similarly, automated solutions for 3D modeling of individual trees at different levels of details are required for Tree Information Modeling (TIM) and building Forest Digital Twins (FDT). The existing algorithms support the automated modeling of trees by generating models of the canopy and the lower part of the trunk. Our work in this paper is based on the assumption that, similar to the canopy shape, the structure of tree trunk and branches is also an important consideration. An algorithm for automated modeling of tree trunks is proposed. Aiming to generate 3D models of tree trunks, the suggested approach starts by extracting the trunk point cloud, which is then segmented into single stems. Finally, the individual stems are modeled by dividing them into slices. The geometry of the developed tree models is represented in a matrix format. This solution enables automatic comparisons of tree elements over time, which is necessary for monitoring changes in forest stands and promoting sustainable forest management. Despite the huge variation of trunk geometric forms, the proposed modeling approach can gain an accuracy of better than 4 cm in the constructed tree trunk models.

Introduction: This study aims to elucidate the clinical diagnostic value of S100 Calcium Binding Protein beta (S100B) in epilepsy, a topic of ongoing debate among European and Asian epilepsy research centres.Methods and analysis: A structured long-term research plan was developed, comprising three phases. Phase one involves observational studies investigating the correlation between S100B levels in serum or cerebrospinal fluid and epilepsy. Phase two integrates observational and randomised controlled data to establish baseline S100B levels across diverse epilepsy demographics, underpinning the predictive value of S100B for epilepsy. Phase three focuses on randomised controlled trials to evaluate the diagnostic accuracy of S100B as an epilepsy biomarker.Ethics and dissemination: All enrolled patients will provide written consent. The ethics committee of the Second People’s Hospital of Gansu Province, Affiliated Hospital of Northwest Minzu University, China, approved the study (GSSEY2022-KY009-01).Registration: The study is registered with PROSPERO (CRD42023425431).

The goal of our article was to systematize studies that investigated the impact of living conditions in large national regions on individual alcohol consumption. We sought publications on the research topic in PubMed, Google Scholar, OpenGrey, Crossref and eLibrary databases from the moment they were created until December 31, 2021. After removal of duplicates and unsuitable publications, and full-text review of remaining published sources, the final sample included 81 publications. The majority of ultimately selected papers were published after 2010, represented the United States of America, and considered samples of children and youths, either the younger population or the general adult population. High quality was characteristic for 19 studies, while satisfactory quality was exhibited by 46 publications. The most consistent associations with individual alcohol consumption were revealed for the legislative environment (especially for integral scales and indices), alcohol pricing policy, the prevalence of alcohol consumption and binge drinking in the population, and unemployment rate. Among the shortcomings of the reviewed articles, we should mention the prevailing assessment of the impact of only one type of regional characteristics, as well as the lack of studies analyzing the interaction of environmental influence at the territorial level of different scales. Protocol PROSPERO CRD42021234874.

This study analyses 749 drawings of five female Bornean orang-utans (Pongo pygmaeus) at Tama Zoological Park in Japan. We searched for differences between individuals but also tried to identify possible temporal changes among the drawings of one individual, Molly, who drew almost 1,300 drawings from 2006 to 2016. An analysis of the drawings was carried out after collecting quantitative and qualitative variables. Our findings reveal evidence of differences in the drawing style of the five individuals as well as creative changes in Molly’s drawing style throughout her lifetime. Individuals differed in terms of the colours used, the space they filled but also the shapes (fan patterns, circles or loops) they drew. Molly drew less and less as she grew older, and we found a significant difference between drawings produced in winter, when orang-utans were kept inside and had less activity, and those produced during other seasons. Our results suggest that the drawing behaviour of these five orang-utans is not random and that differences among individuals might reflect differences of styles, states of mind but also motivation to draw.

Shelter-in-place aimed at slowing COVID-19 transmission has altered nature accessibility patterns, creating quasi-experimental conditions to assess if retracted nature contact and perceived nature deprivation influences physical and emotional wellbeing. We measure through survey methods how pandemic mandates limiting personal movement and outdoor nature access effect self-assessed nature exposure, perceived nature deprivation, and subsequent flourishing as measured by the Harvard Flourishing Index. Results indicate that perceived nature deprivation strongly associates with neighborhood nature contact, time in nature and access to municipal nature during the pandemic, after controlling for shelter-in-place mandates, job status, household composition, and sociodemographic variables. Our hypothesis that individuals with strong perceived nature deprivation under COVID-19 leads to diminished wellbeing proved true. Interaction models of flourishing showed positive modification of nature affinity with age and qualitative modification of nature deprivation with race. Our results demonstrate the potential of local nature contact to support individual wellbeing in a background context of emotional distress and social isolation, important in guiding public health policies beyond pandemics.

The individual and combined effects of extracellular products (ECP) from Arthrobotrys oligospora (Ao) and A. musiformis (Am) growth in liquid media against Haemonchus contortus L3 (HcL3) were assessed. The following methodological steps were established: isolation, morphological (MI) and molecular identification (Mol-I), assessment of nematocidal activity (NA) of fungal liq-uid culture filtrates (LCF) produced in two liquid media alone and in combination and finally, the myco-compound profile identification (MCP). The MI of both isolates suggested that the fungi corresponded to the species Ao and Am. This result was confirmed by PCR analysis followed by sequencing, alignment and obtaining coverage and similarity with respect to isolates reported in the NCBI database. Likewise, the highest Hc mortalities were 91.4% with individual LCF of Am and 86.2% with those of Ao at the highest concentration (100 mg/mL) in Czapek-Dox Broth. The combination of both LCF resulted in a similarly high larval mortality with no statistical differ-ences in relation to individual activity (P>0.05). The MCP showed the presence of alkaloids in both fungi. Coumarins, triterpenes and saponins were found only in Ao. Both fungi produced ECP with a high NA that could be identified and assessed in future studies as potential natural an-thelmintic compounds.

The Individual Work Performance Questionnaire (IWPQ) can be defined as the individual be-haviour capable of generating value and competitive advantage for the organization. It is a mul-ti-dimensional construct, consisting of task performance, contextual performance and counter-productive work behavior. Albeit important, a comprehensive measure of individual job per-formance is still lacking in the Italian context. This paper describes the validation of an Italian adaptation of the IWPQ. A back translation procedure was used. To investigate the psychometric properties of the 18-item Italian IWPQ, 1053 participants (502 men, 47.7%; 551 women, 52.3%) were enrolled; the age of participants ranged between 19 and 69 (Mage=34.6, SD= 11.8), and for the oc-cupation, the sample is classified in blue collar 32.5%, pink collar 33% and white collar 34.5%. Exploratory and confirmatory factor analyses and multigroup confirmatory factor analyses were performed to test the structural factor of the IWPQ. The results supported the goodness of the IWPQ in the Italian context and the scales were found consistent with the original structure. One item was omitted due to a low factor loading, resulting in a final 17-item structure. Multigroup confirmatory factor analysis showed that the factor solution was invariant across both gender and occupational category and found evidence of metric invariance, uniqueness and scalar invariance, and structural invariance. Convergent and discriminant validity were also tested and showed.

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

With the growing size and use of night lights time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night lights data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g. airports, prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20% of the mean. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances, and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.

This study investigated the breakdown trend in an automated production with an aim to recommend the application of Reliability-centered maintenance (RCM) for an improved productivity via a new preventive maintenance (PM) program. Individual Section-forming machine (ISM): a glass blowing machine for making glass bottles was used as the case study of an automated production system. The machine parts and the working mechanisms were analysed with a special focus on methods of processes and procedures that will enable the ISM maintenance department run more effective and achieve its essential goal of ensuring effective machine operation and reducing machine downtime. In this work, information is provided on the steps and procedures to identify critical components of the ISM using Failure Modes and Effect Analysis (FMEA) as a tool to develop an optimal maintenance program based on the reliability data of the equipment’s functional components. A relationship was established between the failure rate of the machine components and the maintenance costs such that using the recommended PM program, an evidence of improvement in the machine’s availability, safety and cost-effectiveness will result into an increase in the company’s profit margin.

The use of individual protective covers (IPCs) to protect newly planted citrus trees from HLB infection is being widely adopted in Florida, an HLB endemic citrus producing area. It is known that IPCs positively influence most horticultural traits, increasing tree growth, flush expansion, and leaf size enabling trees to sustain a balanced carbohydrate metabolism by preventing CLas infection and induced higher leaf chlorophyll levels. This may result in more productive trees. However, as the tree grows IPCs eventually are removed, typically between 2 and 3 years after initial installation. Once IPCs are removed, trees become exposed to the ACPs and ultimately become infected. In this work we covered trees from Valencia sweet orange with IPCs for 30 months, until the trees entered fruit bearing age. We investigated how IPC protection of newly planted trees for 30 months influenced fruit quality and yield of ‘Valencia’ trees for three consecutive seasons after IPC removal compared to non-covered trees. The use of IPCs kick-started the newly planted citrus trees, resulting in more yield and fruits with better internal and external quality. After 30 months of IPC protection, tree canopies were larger and denser supporting more fruit per tree than in non-protected trees for three consecutive seasons even though by the end of the first season after IPC removal trees were HLB positive. Tree height, scion diameter, canopy volume, and leaf area were significantly improved as compared to non-covered trees. Additionally, fruit quality was significantly improved in the three seasons following IPC removal as compared to non-covered trees. However, a decline in quality was measurable in fruit from IPC trees after the second harvesting season, with trees affected by HLB. Based on the results from this study, we conclude that benefits from IPC protection may last for at least three consecutive seasons once trees enter the productive age despite CLas-infection within 12 months after IPC removal.

The location and number data of individual fruit trees are critical for planting area investigation, fruit yield prediction, and smart orchard management and planning. These data are conventionally obtained through manual investigation and statistics with time-consuming and laborious effort. Object detection models in deep learning used widely in computer vision could provide an opportunity for accurate detection of individual fruit trees, which is essential for rapidly obtaining the data and reducing human operations errors. This study proposes an approach to detecting individual fruit trees and mapping their spatial distribution by integrating deep learning with unmanned aerial vehicle (UAV) remote sensing. UAV remote sensing collected high-resolution true-color images of fruit trees in the experimental pomelo tree orchards in Meizhou city, South China. An image dataset of deep learning samples of individual pomelo trees (IPTs) was constructed through visual interpretation and field investigation based on the fruit tree images captured by UAV remote sensing. Four different scales of YOLOv5 (YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) for object detection were selected to train, validate, and test on the image dataset of pomelo trees. The results show that the average precision ([email protected]) of the four YOLOv5 models for validation reach 87.8%, 88.5%, 89.1%, and 90.7%, respectively. The larger the model scale, the higher the average accuracy of the detection result of validation. It suggests that YOLOv5x is a preferred high-accuracy model among the YOLOv5 family and is suitable to realize the detection of IPTs. The number of the IPTs in the study area was counted using YOLOv5x, and their spatial distribution map was made using the non-maximum suppression method and ArcGIS software. This study will provide primary data and technical support for smart orchard management in Meizhou city and other fruit-producing areas.

Complex diseases are prevalent medical conditions which are characterized by strong inter-patient differences in symptom profiles, disease trajectory and treatment response. The challenges in understanding and managing these diseases are due to their complex pathophysiology, comprising of a combination of genetic and environmental factors. The traditional model of disease assumes a clear distinction between health and disease, as well as between different diagnoses, but recent findings with regards to diseasomes and network pleiotrophy suggest that this dogma is not useful in understanding complex diseases. This paper presents a novel model, in which the individual disease burden is determined as a function of molecular, physiological and pathological factors simultaneously: disease(symptoms(traits(genes AND environment))). From this a high-dimensional space is defined which includes all individual disease burdens, ranging from healthy (i.e. low disease burden) to multi-morbidity (i.e. high disease burden), termed the disease landscape. This model provides a novel way to conceptualize human physiology and pathophysiology in the context of complex diseases and may present a useful concept to simultaneously address the strong interindividual heterogeneity of diagnose cohorts as well as the lack of clear distinction between diagnoses and health and disease, thus facilitating the progression towards personalized medicine.

Autosselecionar a intensidade do treinamento aeróbico é uma perspectiva que permite aos praticantes desenvolver autonomia (escolha do ritmo), melhorar a aptidão física e alcançar a perda de peso. Comparar o efeito de quatro protocolos de treinamento aeróbico nas respostas cardiometabólicas e psicofisiológicas em homens e mulheres adultos fisicamente inativos. A amostra foi composta por 11 indivíduos com idade entre 56 ± 10 anos e IMC 29,2 ± 2,4 kg/m2 que realizaram quatro diferentes protocolos de treinamento aeróbio em esteira, sendo: 1-indivíduo com intensidade autosselecionada (ISS), 2-indivíduo com intensidade prescrita (IPI) (64-76% da FC máx), grupo 3 pequeno com autosseleção. intensidade selecionada (SGS) e intensidade prescrita em 4 pequenos grupos (SGP) (64-76% da FC máx). Foram analisados ​​frequência cardíaca, lactato, percepção subjetiva de esforço, resposta afetiva, escala de ativação, prazer, intenção de repetir a sessão, velocidade da esteira e distância total do protocolo. A análise estatística utilizou ANOVA com teste post hoc de Tukey (p<0,05). As análises de frequência cardíaca, lactato, percepção subjetiva de esforço, escala de ativação, prazer, velocidade média e distância total não apresentaram diferenças significativas entre os protocolos. A resposta afetiva apresentou menor declínio no protocolo ISS (p<0,05), e a intenção de repetir a sessão de treinamento foi maior no protocolo ISS (p<0,05). Conclusão: Os dados permitem concluir que o protocolo de treino ISS produziu resultados superiores na resposta afetiva e na intenção de repetir a sessão.

Self-selecting the intensity of aerobic training is a perspective that allows practitioners to develop autonomy (choice of pace), improve physical fitness and achieve weight loss. To compare the effect of four aerobic training protocols on cardiometabolic and psychophysiological responses in physically inactive adult men and women. The sample consisted of 11 individuals aged 56 ± 10 years and BMI 29.2 ± 2.4 kg/m2 performed four different treadmill aerobic training protocols, including: 1-individual with self-selected intensity (ISS), 2-individual with prescribed intensity (IPI) (64-76% of HR max), 3-small group with self-select. selected intensity (SGS) and 4-small group prescribed intensity (SGP) (64-76% of HR max). Heart rate, lactate, perceived exertion, affective response, activation scale, enjoyment, intention to repeat the session, treadmill speed and total distance from the protocol were analyzed. Statistical analysis used ANOVA with Tukey's post hoc test (p<0.05). Heart rate, lactate, perceived exertion, activation scale, enjoyment, average speed and total distance analyzes did not show significant differences between protocols. The response affective showed a smaller decline in the ISS protocol (p<0.05), and the intention to repeat the training session was greater in the ISS protocol (p<0.05). Conclusion: The data allow us to conclude that the ISS training protocol produced superior results in affective response and intention to repeat the session.

Despite the technological advancements of 3-D city models, the 3-D shape abstraction methods for urban vegetation are recent and still limited to support spatial analysis of individual or groups of trees and forest patches. In this paper, a scheme for individual urban tree abstraction, which retains the semantic complexity of the object, is proposed. Our contribution is three-fold. First, an initial tree structure based on a new 3-D aggregation operator is proposed. Second, we developed Gestalt rules for 3-D urban vegetation mapping. Third, current state-of-the-art deep learning is adapted for the abstraction of individual urban trees. Quantitative and qualitative results show the effectiveness of our proposed approach in accurately reducing the spatial density of trees and the degree of fragmentation of the total green area, which can access information about the location, size, and spatial distribution of mapped urban trees.

We extend Ziv and Lempel's model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless finite-state encoder that compresses the reconstruction codeword with no additional distortion. We first derive two different lower bounds to the compression ratio that depend on the number of states of the lossless encoder. Both bounds are asymptotically achievable by conceptually simple coding schemes. We then show that when the number of states of the lossless encoder is large enough in terms of the reconstruction block-length, the performance can be improved, sometimes significantly so. In particular, the improved performance is achievable using a random-coding ensemble that is universal, not only in terms of the source sequence, but also in terms of the distortion measure.

Combination treatment, i.e., the use of two or more drugs for the same condition, is frequent in medicine if monotherapy yields an insufficient therapeutic response. We here review and challenge clinical study designs and formats of reporting outcomes for the evaluation of the benefit/risk ratio of combination treatment over monotherapy. We demonstrate that benefits of combination treatment at the group level over-estimate the probability of benefit at the single patient level based on outcome simulations under almost any imaginable setting. Based on these findings we propose that studies testing combination treatment should always report on percentages of responders to monotherapy and combination treatment. We provide equations that allow calculation of the percentage of patients truly benefitting from combination (responders to both monotherapies) and that of patients exposed to risk of harm from adverse effects without a reasonable expectation of individual benefit. These considerations are explained based on real clinical data, mostly from the field of functional urology (male lower urinary tract symptoms).

Although there has been research regarding the response of horses to human behaviour, there is still a gap concerning the knowledge about the interaction of horses and humans in showing individual responses to different human behaviour in the same situation. In this work, the horses´ individual responses to different humans were examined to close this research gap and to identify whether or not horses actually respond differently to different people. To this end, 29 interactions between horses and humans, where the humans were supposed to lead the horse through a training course (including two identical exercises in each situation) were videoed and then transcribed in the style of the action-oriented system of notations HANOS (Handlungsorientiertes Notationssystem). The qualitative content analysis was appropriated on the basis of Mayring. Just nonverbal interactions between each person and one horse were focused. In total, just under 600 interactions were analyzed and categorized. The categories were then put into a chi-square-test (quantitative analyses). Based on these analyses, it can be assumed that each human individual received an individual, different feedback from the horses.

Traditionally understood in reference to distance education, cognitive presence may be defined as "the extent to which the participants in any particular configuration of a community of inquiry can construct meaning through sustained communication. The purpose of this paper was to create a blueprint for the reflective ePortfolio as the capstone project for my graduate degree. The blueprint was accomplished by adapting for use cognitive presence as a tool for both analysis and framing, which has never been done to the best of my knowledge. I considered myself to be a participant in a “community of inquiry” model and substituted the result of my interaction with each of the required instructor-course content pairings I took to serve as fellow participants in this community model. The result of my participation was understood to be the knowledge and experience that I have gained, which was reflected in eight of my academic research papers. These selected papers were the artifacts around which my ePortfolio was ultimately developed and demonstrated my participation as an active member in this community of inquiry constructing meaning through sustained communication.

Nowadays, the development of civilization requires a vision of balancing the interests of employees and employers in the sphere of work as never before. Work-life balance is directly linked to social sustainability. The aim of this article is to analyse various dimensions of mutual enrichment of the professional and private life of an individual and to describe how positive experiences in professional and non-professional life influence the improvement of satisfaction, health and achievements, thus enabling the sustainable development of the individual. The conducted research was of a qualitative nature. Thematic exploration was used to analyse the findings of 34 in-depth interviews with experienced HR managers and employees at various levels of enterprises in Poland. The research shows that the work and personal life of the respondents interact, complement, and enrich in different ways, depending on the stage of the employee’s life. Habits developed by practicing a specific sport discipline or other type of hobby are helpful in the effective implementation of professional tasks. Also, non-professional interests, including communing with culture and art have a positive impact on professional activities. On the other hand, the respondents emphasized that thanks to their professional activities, specific to the type of work they perform, they are sometimes more extroverted, meticulous, organized and consistent when performing activities outside of work and in other aspects of private life.

The study examines the risk and protective factors in childhood for boys and girls who engage in unlawful behavior, through the lens of developmental criminology. This field explores the elements contributing to the emergence of antisocial and prosocial behaviors in childhood, which are linked to the increase or desistance of delinquency in later years. To enhance understanding in this domain, the study analyzes risk and protective factors associated with criminality in children across various levels: individual, family, and community. Utilizing a systematic review grounded in the PRISMA method, the study identifies and categorizes a range of factors, including conduct problems, socio-emotional competencies, biological determinants, social exclusion, interpersonal relationships, institutional governance, family adversity, caregiver characteristics, and family composition. This review underscores the significance of recognizing risk and protective factors in child development to design interventions at multiple levels, aiming to prevent antisocial behavior proactively.

The expansion of unconventional oil and gas development (UD) across the US continues to be at the center of debates regarding safety to health and the environment. This study evaluated the water quality of private water wells in the Eagle Ford Shale within the context of community members’ perceptions. Community members (n=75) were surveyed regarding health status and perceptions of drinking water quality. Water samples from respondent volunteers (n=19) were collected from private wells and tested for a variety of water quality parameters. Of the private wells sampled, 8 had exceedances of MCLs for drinking water standards. Geospatial descriptive analysis illustrates the distributions of the well exceedance as well as the well owners’ overall health status. Surveys showed that the majority of respondents received their water from a municipal source and were significantly more distrustful of their water source than of those on private wells. In many cases, there are statistically significant differences between self-reported, provider undiagnosed conditions and self-reported, provider diagnosed conditions. Attitudes and perceptions of water quality may play an important role in the overall perceived health status of community members in high fracking regions.

Ground level ozone is an abiotic stress estimated to reduce mean global annual wheat yields by nearly 10%. This study in solardomes exposed an elite cultivar, and multiple lines of synthetic wheat (primary and F2) to four levels of ozone (30 ppb, 55 ppb, 80 ppb, 110 ppb) for three months, with two lines (cv Paragon and an F2 line, BC1) selected for X-ray microcomputed tomography. The uCT imaging revealed ozone’s effect on individual grain formation, both spatially within the spike and on grain shape. Reductions in grain number occurred primarily across the middle of the spike. Grain volume reductions were driven more by reduced width and depth than reduced length. Based on yield data, both lines demonstrated relative tolerance to ozone. Links between ozone’s effects on grain morphology and grain quality are also explored. These data provide information that could be utilised in wheat breeding programmes to increase tolerance to ozone of this staple food crop.

Current methods for assessing individual well-being in team collaboration at the workplace rely often on manually collected surveys. This limits continuous real-world data collection and proactive measures to improve team member workplace satisfaction. We propose a method to automatically derive social signals related to individual well-being in team collaboration from raw audio and video data collected in teamwork contexts. The goal is to develop computational methods and measurements to facilitate the mirroring of individuals’ well-being to themselves. We are focusing on how speech behavior is perceived by team members to improve their well-being. Our main contribution is the assembly of an integrated toolchain to perform multi-modal extraction of robust speech features in noisy field settings and to find which features are predictors of self-reported satisfaction scores. We apply the toolchain to a case study where we collected videos of 22 teams with 56 participants collaborating over a four-day period in a team project. Our audiovisual speaker diarization extracts individual speech features in a noisy environment. As the dependent variable team members filled out a daily PERMA (positive emotion, engagement, relationships, meaning, and accomplishment) survey. These well-being scores have been predicted with speech features extracted from the videos using machine learning. The results suggest that the proposed toolchain is able to automatically predict individual well-being in teams, leading to better teamwork and happier team members.

In the context of partial autonomy, where autonomous vehicles and humans share control of the vehicle, bringing out-of-the-loop drivers back into the loop is a significant challenge. While warning signal design guidelines are commonly used to provide alerts, few studies have examined each signal in depth with an emphasis on the autonomous environment. This study aims to fill this gap by investigating visual, auditory, and tactile stimuli and modifying their sub-attributes to explore variations related to age, gender, and other individual backgrounds. A driving simulator was utilized to create a realistic driving environment and measure participants' reaction times in takeover request situations. Analysis of the data revealed correlations between age and reaction times for auditory and tactile signals, with interaction effects observed between age and sub-attribute intensity. Additionally, participants exhibited varying reaction time patterns in response to different sub-attribute intensities. By evaluating individual differences in perception based on modality characteristics, often overlooked in prior research, this study serves as a foundational contribution to future research in the field.

Between 25 and 30% of the nearly one million military personnel who participated in the 1991 Persian Gulf War became ill with chronic symptoms ranging from gastrointestinal to nervous system dysfunction. This disorder is now referred to as Gulf War Illness (GWI) and the underlying pathophysiology has been linked to exposure-based neuroinflammation caused by organophosphorous (OP) compounds coupled with high circulating glucocorticoids. In a mouse model of GWI we developed, corticosterone was shown to act synergistically with an OP (diisopropylflurophosphate) to dramatically increase proinflammatory cytokine gene expression in the brain. Because not all Gulf War participants became sick, the question arises as to whether differential genetic constitution might underlie individual differences in susceptibility. To address this question of genetic liability, we tested the impact of OP and glucocorticoid exposure in a genetic reference population of 30 inbred mouse strains. We also studied both sexes. The results showed wide differences among strains and overall that females were less sensitive to the combined treatment than males. Furthermore, we identified one OP-glucocorticoid locus and nominated a candidate gene—Spon1—that may underlie the marked differences in response.

As distinct human societies, three unique intentional communities are investigated regarding their preferred consensus decision-making practices. It is Identified that each has adopted a different form of consensus decision-making to solve potential group-wide interpersonal conflict. The individual attributes of these three consensus decision-making practices are considered, both from the perspective of maintaining group stability and in relation to individual member's mental health. The communities are a Canadian self-directed public senior elementary and secondary school, an annual English conference for those self-identifying as on the autistic spectrum, and a self-producing Korean popular music (K-pop) group. It is found that the intentional community and participants’ mental health are sustained regarding each of the three consensus decision-making practices. Nevertheless, the resulting decisions generate various stresses within the communities, both as a whole and concerning the individual members. To retain group cohesion and maintain individual mental health, these stresses must be recognized and understood by participants. The novel finding of this research is that, dependent on the time available for decision-making, and the members’ perspective adopted, intentional communities might practice more than one form of consensus decision-making and still support both group cohesion and individual mental health, maintaining the democracy of these distinct societies.

The structure and phenomena arising from charge transfer in cold field emission modus in a single closed carbon nanotube under cold field emission conditions were studied. By studying microphotographs in various microscopes - AFM, SEM, TEM it was found inhomogeneities in the form of two types of superlattices. The conductivity of the emitter section of a nanodiode circuit with an emitter made of an individual closed carbon nanotube (CNT) and arrays of closed CNTs was studied. High values of cold field emission were observed, as well as nonlinearity and anomalies of the current-voltage characteristic (I-V characteristics), which manifested themselves in the form of peaks at low and high current values. Peaks in the CVC have distinct areas of negative differential conductivity. It is argued, that the anomalously high currents in the I–V characteristics of cold field emission of electrons from a nanoemitter made of closed CNTs can be associated with a sharp increase in the density of electron states at energies near the van Hove singularity.

There is scientific consensus that organismal aging did not evolve by natural selection (NS) because it lacks individual benefit. Nonetheless it exists, leading to much speculation about its origins, and when the diminishing force of selection begins. Both concepts are based upon two misconceptions; that aging occurs in and of itself and is caused by the declining strength of NS during the reproductive lifespan. Although lacking individual benefit, aging evolved by NS as a tradeoff of survival for reproduction. Based upon regulatory dynamics that participate in this tradeoff, aging begins once reproductive success has been achieved through offspring nurturing. Thereafter, the strength of NS wanes to exponentially accelerate aging, leading to death. Assumptions of the theory are that: (1) a life-long, “holistic” regulatory mechanism whose genic expression is modified epigenetically, originates in ontogenesis; (2) the regulatory mechanism of the last developmental stage becomes redundantly expressed during “morphostasis”, a non-aging, life interval of peak vitality to ensure completion of reproduction through nurturing, and (3) thereafter, loss of regulatory redundancy causes aging which reduces the strength of natural selection and allows accumulation of randomly occurring somatic damage.

The object of this work is to determine the correlation on the Nusselt number on the individual rows of a four-row tubular finned heat exchanger with continuous fins with a staggered tube arrangement using CFD modelling. Correlations for calculating Darcy-Weisbach friction factors on individual tube rows were also determined. Relationships for the Nusselt number and friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature determined using experimental data. The maximum relative differences between the Nusselt number for a four-row exchanger determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube's outside diameter of 1,000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the friction factor for a four-row exchanger determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1,000 to 10% for a Reynolds number of 13,000. The CFD modeling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1,400, the Nusselt number for the first row in a four-row finned heat exchanger is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2,800 to 6,000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations on Nusselt numbers and friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.

Predicting trip purpose from comprehensive and continuous smart card data is beneficial for transport and city planners in investigating travel behaviours and urban mobility. Here we propose a framework, ActivityNET, using machine learning (ML) algorithms to predict passengers’ trip purpose from smart card data and Points-of-Interest (POIs) data. The feasibility of the framework is demonstrated in two phases. Phase I focuses on extracting activities from individuals’ daily travel patterns from smart card data and combining them with POIs using the proposed ‘activity-POIs consolidation algorithm’. Phase II feeds the extracted features into an artificial neural network (ANN) with multiple scenarios and predicts trip purpose under primary activities (home and work) and secondary activities (entertainment, eating, shopping, child drop-offs/pick-ups and part-time work) with high accuracy. As a case study, the proposed ActivityNET framework is applied in Greater London and illustrates a robust competence to predict trip purpose. The promising outcomes demonstrate that the cost-effective framework offers high predictive accuracy and valuable insights into transport planning.

This paper provides a framework for the assessment of household-level risk, incorporating both a individual social risk perspective and a location-based perspective. We use this framework as a heuristic to explore the effect of social reintegration choices individuals face, which are not be addressed by current policies. For example, we explore how integrating extended family households during COVID-19 without social distancing may affect household and community risk. The goal is to aid individual decision makers, who are seeking to maintain quality-of-life while navigating local policy, with nuance relating to location-specific behavior and disease prevalence.

Soil CO2 efflux (FCO2) plays a dominant role in the terrestrial carbon (C) cycle but interpreting constraints on local observations is impeded by challenges in disentangling belowground CO2 sources. Trees contribute most C to forest soils, so linking aboveground properties to FCO2 could open new avenues to study plant-soil feedbacks and facilitate scaling; furthermore, FCO2 responds dynamically to meteorological conditions, complicating predictions of total FCO2 and forest C balance. We tested for proximity effects of individual Acer saccharum Marsh. trees on FCO2, comparing FCO2 within 1 m of mature stems to background fluxes before and after an intense rainfall event. Wetting significantly increased background FCO2 (6.4±0.3 vs. 8.6±0.6 s.e. μmol CO2 m-2s-1), with a much larger enhancement near tree stems (6.3±0.3 vs. 10.8±0.4 μmol CO2 m-2s-1). FCO2 varied significantly among individual trees and post-rain values increased with tree diameter (with a slope of 0.058 μmol CO2 m-2s-1 cm-1). Post-wetting amplification of FCO2 (the ‘Birch effect’) in root zones often results from the improved mobility of labile carbohydrates and further metabolization of recalcitrant organic matter, which may both occur at higher densities near larger trees. Our results indicate that plant-soil feedbacks change through tree ontogeny and provide evidence for a novel link between whole-system carbon fluxes and forest structure.

The transport sector in Germany causes one-quarter of energy-related greenhouse gas emissions. One potential solution to reduce these emissions is the use of battery electric vehicles. Although a number of life cycle assessments have been conducted for these vehicles, the influence of a transport system wide transition has not been researched sufficiently. Therefore, we developed a method which combines life cycle assessment with an agent-based transport simulation and synthetic electric, diesel and gasoline powered vehicle models. We use the transport simulation to obtain the number of vehicles, their lifetime mileage and road-specific consumption. Subsequently we analyze the product systems’ vehicle production, use phase and End-of-Life. The results are scaled depending on the covered distance, the vehicle weight and the consumption for the whole life cycle. The results indicate that the sole transition of drive trains is insufficient to significantly lower the greenhouse gas emissions. However, sensitivity analyses demonstrate that there is a considerable potential to reduce greenhouse gas emissions with higher shares of renewable energies, a different vehicle distribution and a higher lifetime mileage. The method facilitates the assessment of the ecological impacts of the complete car based transportation in urban agglomerations and is able to analyze different transport sectors.

The basic constitutional freedoms and rights of a person and citizen are in principle unlimited: the full scope of their exercise is the rule, and the restriction determined by law can only be an exception based on explicit constitutional authority and the legitimate aim of the restriction determined by the Constitution. That being so, the restrictions - in addition to being based on constitutional authority and pursuing constitutional objectives - should be commensurate with the needs to achieve these objectives. This means that restrictive legal rules must be suitable for achieving the legitimate aim pursued, must not be stricter than necessary and must be balanced between the constitutionally guaranteed subjective right of the individual and the interests of society. In this scholar paper, the authors point out the economic and legal consequences of the violation of individual privacy and data protection rights caused by the public disclosure of personal data of people who, at a certain time, were obliged to self-isolate due to suspicion of Covid-19 virus infection.

Computer vision is a powerful technology that has enabled solutions in various fields by analyzing visual attributes in images. One field that has taken advantage of computer vision is agricultural automation, which promotes high-quality crop production. The nutritional status of a crop is a crucial factor in determining its productivity. This status is mediated by approximately 14 chemical elements acquired by the plant, and their determination plays a pivotal role in farm management. To address the timely identification of nutritional disorders, this study focuses on the classification of three levels of phosphorus deficiencies through individual leaf analysis. The methodological steps include: (1) generating a database with laboratory-grown maize plants that were induced to total phosphorus deficiency, medium deficiency, and total nutrition, using different capture devices; (2) processing the images with state-of-the-art transfer learning architectures (i.e. VGG16, ResNet50, GoogLeNet, DenseNet201, and MobileNetV2); and (3) evaluating the classification performance of the models using the created database. The results show that the VGG16 model achieves superior performance, with 98% classification accuracy. However, the other studied architectures also demonstrate competitive performance and are considered state-of-the-art automatic leaf deficiency detection tools. The proposed method can be a starting point to fine-tune machine vision-based solutions tailored for real-time monitoring of crop nutritional status.

The patient was a 44-year-old woman with suspected Stevens-Johnson syndrome due to Baktar® (sulfamethoxazole trimethoprim) medication received at our outpatient dermatology clinic. Histopathological examination of the epidermis, dermis, and subcutaneous adipose tissue samples showed numerous necrotic keratinocytes in the epidermis. Apoptotic nuclei were visualized as diaminobenzidine brown deposits with immunoperoxidase staining for cleaved caspase-3. Cleaved-caspase3-positive findings were consistent with eosinophilic material that appeared to be necrotic cells within the epidermis. Therefore, these eosinophilic materials must be apoptotic bodies. Generally speaking, and especially in Japan, these materials are considered necrotic keratinocytes. To our best knowledge, no studies have used apoptotic immunohistochemical markers to examine whether these structures are apoptotic.

Allylbenzenes (apiol, dillapiol, myristicin and allyltetramethoxybenzene) are individual components of plant essential oils that demonstrate antitumor activity, as well as enhancing effect on cytotoxic drugs such as paclitaxel, doxorubicin, cisplatin, etc. Triphenylphosphine (PPh3) derivatives of allylbenzenes are 2-3 orders of magnitude more potent than allylbenzenes in terms of IC50. Inhibition of efflux pumps has been reported for allylbenzenes, and PPh3 moiety is deemed to be responsible for preferential mitochondrial accumulation and depolarization of mitochondrial membranes. However, due to poor solubility the practical use of these substances has never been an option. Cyclodextrin-based (CD) molecular containers suggested here provided solubilization of allylbenzenes and its PPh3-derivatives. So, in this study we have observed an increase antitumor activity of paclitaxel in the presence of PPh3-derivatives adjuvants by an order of magnitude (in terms of IC50) against adenocarcinomic human alveolar basal epithelial cells A549. At the same time, they are quite powerful cytostatics themselves against A549 cells. On the other hand, the cytotoxic formulations developed show pronounced selectivity of the antiproliferation activity: high against tumor cells line (A549) and low toxicity of these composition was demonstrated on normal cells HEK293T, red blood cells, and sea urchin embryos (a model close to the human genome). On non-cancer HEK293T cells, it was shown that PPh3-derivatives of allylbenzenes at a concentration of 100 µM cause the death of about 20% of cells, while on A549 cancer cells, 85% of cells die. PPh3 derivatives of allylbenzenes, when solubilized in CD molecular containers, show remarkable potential as adjuvants to some of the widely used cytotoxic drugs.

From the perspective of individual resource and social capital, this paper aims to explain how employees’ political skill affect their job satisfaction and turnover intention, through the mediating role of popularity. Using a sample of 237 dyad surveys from supervisors and employees in the Yangtze River Delta of China, we found that: 1) political skill is positively correlated with job satisfaction and negatively correlated with turnover intention, and that these correlations are partially mediated by individual popularity; 2) positive affect (PA) moderates the relationship between political skill and job satisfaction, and negative affect (NA) moderates the relationship between political skill and turnover intention. The implications of our findings and future research directions are discussed.

Introduction: In the year 2022, 4.9 million children died worldwide before five years of age. United Nations General Assembly has set the target of bringing down under-five child mortality to 25 deaths per 1000 live births by 2030. However, the United Nations Inter-Agency Group for Child Mortality Estimation highlights, that without rapid action many low and Lower Middle-Income Countries (LMICs) will not be able to achieve this target and 35 million under-five children will die before 2030. In such a scenario understanding the determinants that bring down preventable deaths in children is important. Design: Anonymized, publicly available data from the India National Family Health Survey (NFHS-5) is collected. The sample consisted of 724,115 women in the age group of 15-49 years has been sub-grouped as urban and rural women. Data on the number of Anganwadi centers per state has been collected from the Ministry of Women and Child Development. For better analysis of data, the country is divided into regions. Union territories are grouped in these regions as per their geographical locations. Descriptive statistical analysis, correlation coefficient analysis, and linear regression analysis were done. Results: Results of the Pearson correlation indicated that there is a significantly large positive relationship between operational AWCs (%) and U5MR (r = 0.542, p < .001) whereas there is a significantly large negative relationship between women with Internet access (%) and U5MR, (r = -0.738, p < .001). For our data, the multiple regression equation for y is U5MR (per 1000 live births) = 0.77266. AWCs (%) - 0.58788. women with Internet access (%) + 53.68073. Conclusion: Compared to NFHS-4 (2015-16) U5MR has reduced in almost all states of the country. The study shows more urban women have access to the Internet as compared to rural women. Child mortality is higher in rural areas in every state as compared to urban areas. Urban women have more access to health information because of internet access which may be the reason for lesser child mortality in urban areas compared to rural areas. Internet access for women (individual level) is far more effective in bringing down U5MR if compared to the community-level approach of Daycare centers.

Headspace solid phase microextraction (HS-SPME) coupled to gas chromatography-mass spectrometry is widely employed for volatile analyses of plants, including mapping populations used in plant breeding research. Studies often employ a single internal surrogate standard, even when multiple analytes are measured, with the assumption that any relative changes in matrix effects among individuals would be similar for all compounds, i.e. matrix effects do not show Compound × Individual interactions. We tested this assumption using individuals from two plant populations, an interspecific grape (Vitis spp.) mapping population (n = 140) and a tomato (Solanum spp.) recombinant inbred line (RIL) population (n = 148). Individual plants from the two populations were spiked with a cocktail of internal standards (n = 6, 9, respectively) prior to HS-SPME-GC-MS. Variation in the relative responses of internal standards indicated that Compound × Individual interactions exist but were different between the two populations. For the grape population, relative responses among pairs of internal standards varied considerably among individuals, with a maximum of 249% relative standard deviation (RSD) for the pair of [U13C]hexanal and [U13C]hexanol. However, in the tomato population, relative responses of internal standard pairs varied much less, with pairwise RSDs ranged from 8% to 56%. The approach described in this paper could be used to evaluate the suitability of using surrogate standards for HS-SPME-GC-MS studies in other plant populations.

Heavy metals toxicity is a grave environmental issue in contemporary times. Phytoremediation is economic, effective and ecofriendly approach to decontaminate and remediate metal contaminated areas. Phenolic and Flavonoid content are important abiotic stress markers. The individual and combined impacts of toxiferous metals Arsenic (As), Cadmium (Cd) and (Copper) Cu were employed in recent studies to investigate their effect on Total flavonoids content (TFC) and total phenolic content (TPC) in various parts of Hydrocotyle umbellata L. to explore the role of plant in abating metal contamination. Folin- ciocalteu and AlCl 3 methods were used for investigating TPC and TFC respectively. Two-way ANOVA and CART model were employed for statistical analysis. Highest TPC was examined in decreasing order as leaf &amp; gt; stem &amp; gt; root in case of all the metals. Whereas highest TFC was found in all plant parts when subjected to As toxicity, and the lowest TFC was found in stem of the plant in respect to Cu toxicity. There was significant effect on TPC on plant part when subjected to Cu and As stress, but so significance was observed in plant part in case of Cd and combined metal stress. Treatment concentration had no significant effect on TPC when subjected to unique impact of all the three metals but had significant effect in case of combined metal stress. Similarly, in case of TFC no significant effect was recorded in case of plant part in all the stress types. But treatment amount has significant impact on Cd and combined metal stress. Metal type has significant effect on TPC and TFC. Whereas plant part has significant impact on TPC but non-significant values were observed on TFC in this case. This study epitomizes TPC and TFC in plants as effective and viable tool to pertain their role in phytoremediation against metal contamination. Therefore H. umbellata L. can be exerted for successful assemblage and decontamination of Cd, Cu and As in different plant parts.

This paper examines the moral community thesis in the secular context of China. Using multilevel logistic regression, we test (1) whether both individual- (measured by affiliation with institutional religion) and aggregate-level religiosity (measured by the number of religious sites per 10,000 people in province) are inversely related to law and rule violations at the individual level and (2) whether the province-level religiosity enhances the inverse relationship between individual religiosity and the deviant behaviors. Results from analyzing data from the 2010 China General Social Survey and the Spatial Explorer of Religions show that both individual- and aggregate-level religiosity are inversely related to the odds of violating the law and various rules of government, transportation, workplace, and other organizations. However, the cross-level interactions are not significant across models, indicating that the contextual religiosity does not increase the effect of individual-level religiosity on deviance. Implications of findings for the moral community thesis are discussed.

Background: As cancer progresses, cells acquire traits that allow them to disperse and disseminate to distant locations in the body – a process known as metastasis. While in the vasculature, these cells are referred to as circulating tumour cells (CTCs) and can manifest either as single cells or clusters of cells (i.e., CTC clusters), with the latter being the most aggressive. The increased metastatic potential of CTC clusters is generally associated with cooperative group benefits in terms of survival, such as increased resistance to shear stress, anoikis, immune attacks and drugs. However, the adoption of a group phenotype poses a challenge when exiting the vasculature (extravasation) as the large size can hinder the passage through vessel walls. Despite their significant role in the metastatic process, the mechanisms through which CTC clusters extravasate remain largely unknown. Based on the observed in vivo association between CTC clusters and platelets, we hypothesized that cancer cells take advantage of the platelet-derived Transforming Growth Factor Beta 1 (TGF-β1) – a signalling factor that has been widely implicated in many aspects of cancer, to facilitate their own dissemination. To address this possibility, we evaluated the effect of exogenous TGF-β1 on an experimentally evolved non-small lung cancer cell line that we previously developed and used to investigate the biology of CTC clusters. Results: We found that exogenous TGF-β1 induced the dissociation of clusters into adherent single cells. Once adhered, cells released their own TGF-β1 and were able to individually migrate and invade in the absence of exogenous TGF-β1. Based on these findings we developed a model that involves a TGF-β1-mediated plastic switch between a cooperative phenotype and a single-celled stage that enables the extravasation of CTC clusters. Conclusions: This model allows for the possibility that therapies can be developed against TGF-β1 signalling components and/or TGF-β1 target genes to suppress the metastatic potential of CTC clusters. Considering the negative impact that metastasis has on cancer prognosis and the lack of therapies against this process, interfering with the ability of CTC clusters to switch between cooperative and individual behaviours could provide new strategies to improve patient survival.

A novel concept of ion separation Anisotropic Diffusion Mobility Analyser (ADMA) with Individual Ion Counter (IIC) was shown by numerical modelling to be able to separate ions with high resolution and ultra-high sensitivity. An ADMA-IIC device has been developed and tested at sheath flow rates below 40 l/min with a number of chemicals relevant to airport security and military applications. The resolving power of the ADMA was observed to be in the range of 40 to 80. These data were close to the resolution obtained in numerical modelling predictions. It is greater than or comparable with the RP of currently available on-the-market devices for airport security and other applications. It was also confirmed that the ADMA technology enables very fast detection of analytes, at least 100 times faster than ion mobility spectrometers. It was shown that Brownian diffusion can be controlled and even overpowered by generating highly anisotropic diffusion in the ADMA device. The ultimate sensitivity of single-ion detection below the ppq range has been demonstrated.

The global SARS-Cov-2 which caused the coronavirus disease 2019 (COVID-19) pandemic has had a significant impact over the last 3.5 years, especially among healthcare workers (HCWs) who were constantly in the forefront of the pandemic. Due to the nature of their work, HCWs faced a potential risk of exposure. Therefore, this study investigated the individual-level factors associated with perceived COVID-19 risk among South African HCWs. We used an analytical cross-sectional study design to analyse data from the South African Health Care workers’ response to the Coronavirus (COVID-19) pandemic online survey conducted by the Human Sciences Research Council across the nine provinces in South Africa, from 11th April to 7th May 2020. In this study, only data (n= 5 579) with non-missing values for COVID-19 risk and individual-level factors (age, gender, educational level, occupational category, and race) was analysed. Univariate and Multivariate binomial logistic regression analyses were conducted. The crude and adjusted odds ratio and p-value ≤ 0.05, were used to describe the association between the individual-level factors and perceived COVID-19 risk, from low-medium to high. The binomial logistic regression was used to assess the factors associated with high perceived risk. Perceived COVID-19 risk among HCWs in South Africa was significantly associated with age, race, educational level and occupational category. Being 60 years and older, being “White”, having a Master’s and Doctorate degrees and being a healthcare worker other than a nurse practitioner and medical practitioner, all had higher odds of having high perceived COVID-19 risk. The findings may be used to guide policies and programs aimed at mitigating the impacts of COVID-19 and other similar pandemics.

This paper presents a novel approach for individual design perception modeling using the YUKI-trained Fuzzy Inference System. The study focuses on understanding how individuals perceive design based on personality traits, particularly openness to experience. The proposed YUKI algorithm optimizes the FCM clustering algorithm, enhancing its ability to handle uncertain and imprecise data. The YUKI-trained FIS generates several Sugeno-type FIS models to predict design perception, to minimize the Root Mean Squared Error between the model prediction and the actual design perception of participants. The results demonstrate that the YUKI-trained FIS offers more accurate predictions compared to the traditional FCM-trained FIS, and the RMSE values for individual design perceptions fall within a satisfactory range of 0.84 to 1.32. The YUKI-trained FIS proves effective in clustering individuals based on their level of openness, providing insights into how personality traits influence design perception.

A multiscale mathematical model is proposed seeking to study the propagation dynamics of the Human Immunodeficiency Virus (HIV) in a group of young people between 15 and 24 years of age, through sexual contact without protection, considering the use of antiretroviral therapy (ART) and therapeutic failure. The model consists in a scale-free complex network that follows a power law, coupled with the immunological dynamics of each individual, that is, it considers the infection by the virus in the immune system of each HIV carrier, through a system of non-linear differential equations that govern the infection’s behavior in the immune system. Propagation of the virus in the network is modelled by taking into account information from the immunological status of each person. The study found that for a population to have high HIV prevalence, it is not necessary at the beginning of the simulation time for the virus to propagate rapidly. In addition, the study proves that with a higher number of sexual partners, there will be greater prevalence of HIV in the population and that the use of ART helps to control the propagation of the infection in the population. As an interesting result, it was also found that there is a higher number of HIV carriers who abandon ART than those who have access to it.

We present a case of Capnocytophaga canimorsus septic shock after a dog bite in an immunocompetent individual, where real-time nanopore metagenomic sequencing characterized the microbial agent within 19 hours, with subsequent confirmation using droplet digital PCR. Oral swabs from the dog demonstrated a nearly-identical C. canimorsus isolate by sequencing.

The new Post Accelerating Data and Knowledge Online Society, or ‘Padkos’ requires a new model of decision making. This introductory paper proposes a model where decision making and learning are a single symbiotic process, incorporating man and machine, as well as the AADD (ánthrōpos, apparatus, decider, doctrina) diamond model of individual and organizational decision-making and learning processes. The learning is incorporated by using a newly proposed quadruple loop learning model. This model allows for controlled changes of identity, the process of creating and the sense making of new mental models and assumption, and reflections. The model also incorporates the recently proposed model of quantum decision-making, where time collapse of the opted past and the anticipated future (explicitly including its time horizon) into the present play a key role in the process, leveraging decision-making and learning by human as well as Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The paper closes with conclusions.

To follow the growth and development of each tree (N = 1200) Pinus sylvestris L., var. Negorelskaya starting from the seed and continuing at the juvenile (or even generative) stage is the goal of an ambitious project to create a plant passport if possible. Five datasets of replenished empirical (tab-ular and file) and systematic data reflect the early results of a unique ongoing experiment conducted with families moved along a climatic gradient from the collection area (1731 degree days, 722 mm) to the experimental area (2326 degree days; 786 mm). Datasets of morphometric, VIS-spectrometric, and germination seed data, combined with the first results of biometric data (including the Dickson quality index) of seedlings produced from these seeds, will allow scientists in the future to conduct correlation and other statistical analysis, or train a neural network to determine the presence of connections between a seed and a plant. These data contribute to the early non-destructive diag-nosis and grading of seeds according to VIS-spectrometric properties. This dataset structure can complement the FLR-Library. In the future, by tracing seedlings in their early growth (for example, over three growing seasons at the site being restored), it will be possible to determine the degree of intensification of FRM production depending on the initial properties of the seed.

Background/Purpose: Over the last two decades, malaria has remained a major worldwide public health concern, especially in the developing countries leading to high morbidity and mortality among children. Nigeria is the world most burdened malaria endemic nation, contributing more than a quarter of global malaria cases. This study determined the prevalence of malaria among children 6-59 months in Nigeria, and the effects of individual and contextual factors. Methods: The study utilized data from 2018 Nigeria Demographic and Health Survey (NDHS) involving a weighted sample size of 10,185 children who were tested for malaria using rapid diagnostic test (RDT). Given the hierarchical structure of the data set, such that children at level-1 are nested in community at level-2, and nested in states and Federal Capital Territory (FCT) at level-3, multilevel mixed effect logistic regression models were used for the analysis. Results: The proportion of children 6-59 months of age in Nigeria that had malaria fever positive as assessed by RDTs was 35.5% (3,418/10185), (CI: 33.9-37.1). Kebbi State had the highest proportion of children 6-59 months who were malaria positive, 77.6%, (CI: 70.2-83.5), followed by Katsina State, 55.5%, (CI: 47.7-63.1). The Federal Capital Territory (FCT), Abuja had the proportion of 29.6%, (CI: 21.6-39.0), malaria positive children of 6-59 months of age. Children between the age of 48 and 59 months were 2.68 times more likely to have malaria fever than children 6-11 months of age (AOR=2.68, 95% CI: 2.03-3.54). Also, children from the rural area (AOR= 2.12, 95% CI: 1.75-2.57), were more likely to suffer from malaria infection compare with children from urban area. Conclusion: The study identified some individual and contextual predictors of malaria among children in Nigeria. These factors are areas that need to be considered for policy designs and implementations toward control and total elimination of malaria-related morbidity and mortality among children in Nigeria.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

Considering the impact of religiosity on the perceptions regarding life quality, in this paper we focus on the effects of the appurtenance to a religion on the standard of living in several economically developing countries (Turkey, Ukraine, Senegal and Morocco). The data have been collected using a survey carried out in 2012 and the empirical analysis was based on non-parametric tests and multinomial logistic regression. The results indicate there are differences between religious persons and atheists regarding gender, marital status, perceptions of daily life and standards of living. Females and officially married people or single people tend to be more religious. A person claiming to belong to a religion has 2-4-fold more chances to achieve a considerable improvement in the standards of living as compared to an atheist. Moreover, religious people from the analyzed countries are more optimistic about their life overall. Taking into account the sample’s characteristics and the countries chosen, we can claim that the results obtained are truly cross-cultural in nature. Moreover, most of the conclusions reached would be to some extent relevant to other developing economies of Eastern Europe, North Africa and Middle East.

Background: Given that VR is applied in multiple domains, understanding the effects of cybersickness on human cognition and motor skills and the factors contributing to cybersickness gains urgency. This study aimed to explore the predictors of cybersickness and its interplay with cognitive and motor skills. Methods: 30 participants, 20-45 years old, completed the MSSQ and the CSQ-VR, and were immersed in VR. During immersion, they were exposed to a roller coaster ride. Before and after the ride, participants responded to CSQ-VR and performed VR-based cognitive and psychomotor tasks. Post VR session, participants completed the CSQ-VR again. Results: Motion sickness susceptibility, during adulthood, was the most prominent predictor of cybersickness. Pupil dilation emerged as a significant predictor of cybersickness. Experience in videogaming was a significant predictor of both cybersickness and cognitive/motor functions. Cybersickness negatively affected visuospatial working memory and psychomotor skills. Overall cybersickness’, nausea and vestibular symptoms’ intensities significantly decreased after removing the VR headset. Conclusions: In order of importance, motion sickness susceptibility and gaming experience are significant predictors of cybersickness. Pupil dilation appears as a cybersickness’ biomarker. Cybersickness negatively affects visuospatial working memory and psychomotor skills. Cybersickness and its effects on performance should be examined during and not after immersion.

Parkinson’s disease (PD) is a slowly progressing neurodegenerative disorder that is coupled to both widespread protein aggregation and to loss of substantia nigra dopamine (DA) neurons, resulting in a wide variety of motor and non-motor signs and symptoms. Recent findings suggest that the PD process is triggered several years before there is sufficient degeneration of DA neurons to cause onset of overt motor symptoms. According to this concept, the number of DA neurons present in the substantia nigra at birth could influence the time from the molecular triggering event until the clinical diagnosis with lower number of neurons at birth increasing the risk to develop the disease. Conversely, the risk for diagnosis would be reduced if the number of DA neurons is high at birth. In this commentary, we discuss the genetic and epigenetic factors that might influence the number of nigral DA neurons that each individual is born with and how these may be linked to PD risk.

In T. gondii, as well as in other model organisms, gene knock-out using CRISPR-Cas9 is a suitable tool to identify the role of specific genes. The general consensus implies that only the gene of interest is affected by the knock-out. Is this really the case? In a previous study, we have generated knock-out (KO) clones of TgRH88_077450 (SRS29B; SAG1) which differed in the numbers of integrated dihydrofolate-reductase-thymidylate-synthase (MDHFR-TS) drug-selectable marker. Clones 18 and 33 had a single insertion of MDHFR-TS within SRS29B. Clone 6 was disrupted by the insertion of a short unrelated DNA-sequence, but the marker was integrated elsewhere. In clone 30, the marker was inserted into SRS29B and several other MDHFR-TS copies were found in the genome. KO and wild-type (WT) tachyzoites had similar shape, dimensions and vitality. This prompted us to investigate the impact of the genetic engineering as such on the overall proteome patterns of the four clones as compared to the respective WT. Comparative shotgun proteomics of the five strains was performed. Overall, 3236 proteins were identified. Principal component analysis of the proteomes revealed five distinct clusters corresponding to the five strains by both iTop3 and iLFQ algorithms. Detailed analysis of the differentially expressed proteins revealed that the target of the KO, srs29B, was lacking in all KO clones. Besides this protein, twenty other proteins were differentially expressed between KO clones and WT or between different KO clones. The protein exhibiting the highest variation between the five strains was srs36D encoded by TgRH_016110. The deregulated expression of SRS36D was further validated by quantitative PCR. Moreover, the transcript levels of three other selected SRS genes, namely SRS36B, SRS46, and SRS57 exhibited significant differences between individual strains. These results indicate that knocking out a given gene may affect the expression of other genes. Therefore, care must be taken when specific phenotypes are regarded as a direct consequence of the KO of a given gene.

A key step in providing management/treatment options to men with suspected prostate cancer (PCa) is categorizing the risk for the presence of benign, low risk, intermediate risk, or high-risk disease. Our novel modality brings new evidence, based on the long-known hallmark characteristic of PCa – decreased Zinc (Zn), which is the most direct metabolic sign of malignancy and its aggressiveness. To date, this approach has not been adopted for clinical use for a number of reasons that are described in this article and which have been addressed by our approach: Zn has to be measured on fresh samples, prior to fixating in formalin, therefore samples have to be scanned during the biopsy session; as Zn depletion occurs in the glands, where the tumors develop, estimation of the glands’ levels in the scanned tissue along with their compactness, are essential for accurate diagnosis. Combined with the Zn depletion, this facilitates a reliable assessment of the disease aggressiveness. Data gathered in the clinical study described here indicate that in addition to improving the biopsy quality by real-time interactive guidance, a malignancy score can now be established for the entire prostate, allowing higher granularity personalized risk stratification and more decisive treatment decisions for all PCa patients.

Objective: We tested a model of individual health literacy information sharing with family members, personal preventive behaviours and family well-being during the Coronavirus Disease 2019 (COVID-19) pandemic in Hong Kong. Methods: We analysed data of 1501 randomly selected Chinese adults from a cross-sectional survey in Hong Kong from 9 to 23 April, 2020. Individual health literacy about COVID-19 with the items extracted from the questionnaire in World Health Organization Risk Communication and Community Engagement (RCCE) Action Plan Guidance for COVID-19 preparedness and response, COVID-19 information sharing with family members, preventive behaviours against COVID-19 and family well-being were measured. Structural equation modelling analysis tested the proposed model. Findings: COVID-19 information sharing with family members partially mediated the association between individual health literacy and personal preventive behaviours. The direct effect of 0.24 was shown, and the indirect effect through COVID-19 information sharing with family members was small at 0.03 (Z = 3.66, p < 0.001). Family well-being was associated with personal preventive behaviours against COVID-19. The model was adjusted for sex, age, and socioeconomic status factors and had good fit with RMSEA = 0.04, CFI = 0.98, TLI = 0.96, and SRMR = 0.02. Conclusion: COVID-19 information sharing with family members was a partial mediator between individual health literacy and personal preventive behaviours against COVID-19. Strategies for enhancing health literacy and preventive measures against COVID-19 are needed to promote family well-being in the pandemic.

Many metabolic processes at the molecular level support both viral attack strategies and human defenses during Covid-19. This knowledge is of vital importance in the design of antiviral drugs. In this study, we extracted 18 articles (2021-2023) from PubMed reporting the discovery of hub-nodes specific for the liver during covid-19, identifying 142 hub-nodes. They are highly connected proteins from which to get deep functional information on viral strategies when used as functional seeds. Therefore, we evaluated the functional and structural significance of each of them to endorse their reliable use as seeds. After filtering, the remaining 111 hubs were used to get by STRING an enriched interactome of 1111 nodes (13,494 interactions). It shows the viral strategy in the liver is to attack the entire cytoplasmic translational system, including ribosomes, to take control of protein bio-synthesis. We used the SARS2-Human-Proteome Interaction Database (33,791 interactions), de-signed by us with BioGRID data to implement a reverse-engineering process that identified human proteins actively interacting with viral proteins. The results show 57% of human liver proteins di-rectly involved in Covid, a strong impairment of the ribosome and spliceosome, an antiviral defense mechanism against cellular stress of the p53 system, and, surprisingly, a viral capacity for multiple protein attacks against single human proteins that reveal underlying evolutionary-topological molecular mechanisms. Viral behavior over time suggests different molecular strategies for different organs.

Stock bubbles are characterized by unpredictable price surges and subsequent declines, causing significant losses for investors. The study aimed to detect mildly explosive patterns in S&P 500-listed stocks in real-time using the GSADF test. This study focused on the length, the normality of the stock bubble episode and compared the effectiveness of SADF and GSADF tests in bubble detection, consistently finding GSADF's superiority. The duration of breakouts exhibited non-normality, suggesting unusually long bubble durations.

Aim of this research paper is to introduce a novel method of hybrid orthodontic tooth-borne distalizer treatment of class II malocclusion by using 3D printed biocompatible personalized distalizer. Explains 3D designing, printing and clinical application of individualized biocompatible medical device dedicated for orthodontic teeth distalization. Compares such distalizer manufactured from two different biocompatible photopolymers (white and transparent). Evaluates their clinical performance and also patients’ aesthetical perception. Clinical part includes comparison of treatment debonding on the set of 12 complete orthodontic treatments with uni-lateral class II malocclusion managed with hybrid approach (CAT-Invisalign with 3D printed distalizer). Paper offers an evaluation of the personalized distalizer functioning in regard to current publications and comparison to conventional prefabricated alternatives like Carriere® Distalizer™ appliance. Results showed no significance of material differences on clinical performance of such individualized distalizers. Research showed preference of patients towards transparent biocompatible photopolymer instead of white A2 shade.

Objective: To examine variations in end-of-life care for breast cancer, heart failure, and dementia patients. Data and methods: Data from four Norwegian health registries were linked using a personal identification number. Longitudinal trends over 365 days and the type of care on the final day of life were analyzed using descriptive techniques and logistic regression analysis. Results: Patients with dementia were most commonly placed in nursing homes, while patients with heart failure and breast cancer were more frequently hospitalized. Breast cancer and heart failure patients had a higher likelihood of dying at home. The presence of general practitioners increased the probability of home-based end-of-life care for cancer patients, while non-physician healthcare workers increased the likelihood of home-based care for the other patient groups. Conclusion: Diagnoses, individual characteristics, and service availability are all associated with the place of death in end-of-life care.

Abstract: The population issue has been increasingly urgent in China in recent years. Fertility desire is an essential component of fertility research. Studies on fertility desire mainly contain two aspects: socio-economic structure and individual family[1]. The psychological structure of individuals in individual families is the primary factor of fertility desire. Based on the parasocial relationship theory, this study analyzed the changes in real behavioral intention achieved by players through the identification and attachment to avatars while constructing parasocial relationships[2]. The results indicate that character attachment can significantly enhance the variables of game concentration and player self-identity, actively mediates parasocial emotions and parasocial cognition, and ultimately increases fertility desire. As a theoretical contribution, this study provides a comprehensive interpretation of the psychology of Chinese players in a Simulation Game and explores the theoretical connections among role attachment, role identity, and parasocial relationships in virtual game players.

The fact that individuals are spatially close to each other in the urban environment increases the potential number of encounters between them. Thus, theoretically speaking, the probability of interaction and social intercourse among people increases as they get closer to each other spatially. This reduction in spatial distance and propensity for larger networks can offer advantages in lower communication and transaction costs. However, there is also the possibility of entropy in a single (organizational) urban subsystem, characterized by reduced spatial distances between individuals that can lead to more toxic outcomes and the possibility of generalized deconstruction in an urban system as a whole. The current paper considers, through a theoretical model and secondary data analysis, how reductions in spatial distance between individuals in urban business organizations can lead to withdrawals of energy through toxic forms of entropic citizenship behavior, and lead to the development of toxic organizations. Such toxic organizations can ‘infect’ the urban system and lead to systematic entropic urban deconstruction. Practical, implications for management of the theoretical explanatory heuristic of toxic forms of organizational entropy and toxic organizations are briefly discussed in the paper.

Micronutrient deficiencies remain a public health burden among non-pregnant women in developing countries, including Nepal. Hence, this study examined micronutrient deficiencies among non-pregnant Nepalese women aged 15-49 using the 2016 Nepal National Micronutrient Status Survey (NNMSS). Data on 2143 non-pregnant women was extracted from the 2016 NNMSS. The study analysed ferritin, soluble transferrin receptor (sTfR), red blood cell (RBC) folate and zinc. Multivariable logistic analysis was carried out to assess factors associated with micronutrient deficiencies. Prevalence of ferritin, sTfR, folate, and zinc were 19%, 13%, 16% and 21%, respectively. Non-pregnant women from the Janajati region were significantly less prone to ferritin [adjusted odds ratio (AOR): 0.45; 95% confidence interval (CI): 0.25, 0.80], and those who had body mass index (BMI) of 25 kg/m2 or higher had significantly higher odds of ferritin [AOR: 2.69; 95% CI: 1.01, 7.17]. Non-pregnant women aged 35-49 years were significantly less predisposed to folate deficiency [AOR: 0.58; 95% CI: 0.40, 0.83], and the likelihood of zinc deficiency was significantly lower among non-pregnant women from richer households [AOR: 0.48; 95% CI: 0.31, 0.76]. The study provides further insight into screening high-risk subgroups and instituting public health interventions to address the prevailing micronutrient deficiencies among non-pregnant Nepalese women.