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.

The research investigated the relationship between burnout syndrome and the variables of mental resilience and quality and enjoyment of life, in Greek private and public sector workers (N=112), with demographic differences. Data were collected through a structured questionnaire which was distributed in the form of an electronic Microsoft forms. The questionnaire contained demographic questions, the psychometric tool Burnout Assessment Tool version 2.0 (Schaufeli et al., 2019), the psychometric tool Brief Resilience Scale (BRS) (Smith et al., 2008), and the psychometric tool Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) (Endicott et al., 1993) which were used to measure the three variables examined by the research. For statistical analysis, Pearson and Spearman correlation coefficients were used to test the relationship between two quantitative variables, while linear regression analysis was used to find independent factors. The main research hypothesis was verified, finding a negative correlation between burnout and the variables of mental resilience and quality of life, while it was identified that employees experienced greater exhaustion and spiritual withdrawal compared to freelancers. Hypotheses regarding age, educational level, and public-private job data were not verified as there were no statistically significant differences in demographic results.

Although the water absorption feature (WAF) at 970 nm is not very well-defined, it may be used alongside other indices to estimate the canopy water content. The individual performance of a number of existing vegetation water content (VWC) indices against the WAF is assessed using linear regression model. We developed a new Combined Vegetation Water Index (CVWI) by merging indices to boost the weak absorption feature. CVWI showed a promise in assessing the vegetation water status derived from the 970 nm absorption wavelength. CVWI was able to differentiate two groups of dataset when regressed against the absorption feature. CVWI could be seen as an easy and robust method for vegetation water content studies using hyperspectral field data.

Socio-demography of statuses reflects the demographic and social roles and achievements of an individual(s) in a population. In the theoretical frameworks, little was known about the theory, analytical measures, and evolutionary mechanism of the socio-demographics of statuses of an individual(s). In this paper, three (3) methodological issues regarding the concept of socio-demographics were proposed, these are: (a) identified the basic features that clarify our understanding about the conception of the socio-demographic statuses of an individual(s) as common, universal, and desirable positions, achievements, and advantages every individual strives and competes to attain, achieve, maintain, update, and upgrade which are determined by biological and social environments, driven and regulated by a continuum of competitions and natural selections; (b) presented a new paradigm of analytical measures of an individual’s socio-demographic statuses and the established hierarchical transitions; (c) proposed theoretical assumptions for the evolution of a socio-demographically unique population. Seven (7) factors (the driving forces) and eight (8) conditions responsible for the evolution of socio-demographically unique populations were identified and explained. The evolutionary transitions were organized into six (6) socio-demographic ranks.

Introduction: Substance-induced psychotic disorder (SIPD) is a mental health condition linked to the use of a psychotropic substance whose pathogenesis has not been totally clarified. The present retrospective observational study has the objective to identify differences in clinical features and peripheral biomarkers in SIPD patients according to the main substance of abuse.Methods: A total sample of 218 patients was divided in 3 groups according to the type of consumed substance: alcohol, cannabis and psychostimulants. The 3 groups were compared for continuous variables by one-way analyses of variance (ANOVAs) and for qualitative variables by χ² tests. After removing alcohol-induced psychotic disorder group, the same analyses were repeated. Statistically significant variables from these latter analyses were included in a binary logistic regression model to confirm their reliability as predictors for cannabis- or psychostimulants-induced psychotic disorders. Results: Psychotic cannabis abusers were younger (p<0.01) and had an earlier age at onset (p<0.01). On the contrary, alcohol consumers resulted to have a longer duration of illness (p<0.01), more previous hospitalizations (p=0.04), more frequent medical comorbidity (p<0.01), higher mean Modified Sad Person Scale scores (p<0.01). Finally, psychostimulant abusers had more frequently a lifetime history of poly-substance use disorders (p<0.01). Binary logistic regression revealed that higher mean Brief Psychiatric Rating Scale scores (p<0.01) higher sodium (p=0.012) and haemoglobin(p=0.040) plasma levels were predictors of cannabis misuse in SIPD patients.Conclusions: Different clinical factors and biochemical parameters con be associated to SIPD according to the main substance of abuse, thus requiring a specific management by clinicians.

Crash prediction of the sharp horizontal curve segment (SHCS) of a freeway is an important tool in analyzing safety of SHCSs and in building a crash prediction model (CPM). The design and crash report data of 88 SHCSs from different institutions were surveyed and three negative binomial (NB) regression models and three generalized negative binomial (GNB) regression models were built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The study demonstrates the effective use of the GNB model in analyzing the interactive influence of explanatory variables and in predicting freeway basic segments. Traffic volume, highway horizontal radius, and curve length have been formulated as explanatory variables. Subsequently, we performed statistical analysis to determine the model parameters and conducted sensitivity analysis. Among the six models, the result of model 6, which considered interactive influence, is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 SHCSs with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than models 1 and 3.

What drives an individual police officer to activate his body-worn camera (BWC)? Some evidence suggests officer attitudes and resistance to the technology contributes to the equivocal results in studies testing for BWCs effect on use-of-force, complaints, and other outcomes of interest. Leveraging a novel survey and administrative dataset, we investigate the predictors of BWC activation among 147 police officers in a single agency. With a test of three nested models, we find job function covariates offer robust predictive power of how often an officer activates her or his BWC. Neither demographic nor attitudinal measures significantly predict BWC activations, except for a negative relationship with how officers perceive BWC impacts on professional discretion. The study furnishes empirical support for understanding officers as Principled Agents: job function, guided by administrative policy is the most explanatory and parsimonious, while models of attitudes and demographics fail to improve upon the job function model.

Different variants of thinning for discrete random variables are studied. The thinning procedure allows to introduce an analog of scale parameter for positive integer-valued random variables. Sufficient and necessary conditions for the existence of such a scale are given.

The worldwide competition to vaccinate against COVID-19 has highlighted the importance of immunization measures in containing the virus. Saudi Arabia, like the rest of the globe, must assess socio-demographic subtleties, chronic illnesses, vaccination effects, and public health policy implications as it navigates this complicated environment. This cross-sectional study examined Saudi COVID-19 vaccine in many ways. It examined the socio-demographic makeup of vaccine recipients, the prevalence of chronic conditions in this population, vaccine administration patterns, post-vaccination side effects, and vaccine-infection rates. A questionnaire-based online survey of 401 participants ensured gender, nationality, age, weight, and educational diversity. We analyzed vaccine manufacturer choice for each dosage, side effects after the first and second doses, and chronic diseases in the sample. Pfizer/BioNTech vaccines are preferred for all three doses, reflecting worldwide vaccination acceptance patterns. Side effects were not significantly different between vaccination kinds. Interestingly, immunization reduced infection rates, demonstrating the efficacy of COVID-19 vaccines. The data fills important information gaps and illuminates Saudi COVID-19 vaccination kinetics. These data support the global preference for mRNA vaccines, demonstrating the faith in this breakthrough technology. They also sponsor COVID-19 vaccine safety and effectiveness studies. The dramatic drop in infection rates among vaccinated people shows how vaccinations suppress the pandemic. These findings inform Saudi Arabia's immunization efforts. As booster doses become more common, long-term vaccination research is crucial. Vaccine reluctance, especially in certain demographics, must be addressed. Due to vaccines' protective potential, equitable vaccine distribution and large immunization programs are essential for herd immunity and pandemic management. This thorough cross-sectional study helps policymakers and healthcare practitioners build successful and inclusive COVID-19 immunization regimens in Saudi Arabia.

In this study, we surveyed over 600 participants to determine: a) major causes to mental stress during the pandemic and its future impacts, and b) diversity in public perception and acceptance (specifically for children) of Covid-19 vaccination. Statistical results and intelligent clustering outcomes indicate significant relationships between sociodemographic diversity, mental stress causes, vaccination perception, and Covid-19 infections. For instance, statistical results indicate significant dependence between mental stress due to Covid-19 and gender (p = 1.7e-05). Over 25% of males indicated work related stress comparing 35% in females however, females indicated more stressed (17%) due to relationships comparing to males (12%). Around 30% of Asian/Arabic participants don’t feel vaccination being safe as compared to 8% of white-British and 22% of white-European indicating significant dependence (p = 1.8e-08) with ethnicity. More specifically, vaccination acceptance for children is significantly dependent to ethnicity (p = 3.7e-05) where only 47% participants show willingness towards children’s vaccination. Primary dataset in this study along with experimental outcomes identifying sociodemographic information diversity with respect to public perception and acceptance of vaccination to children and potential stress factors might be useful for public and policy makers to be better prepared for future epidemics as well as working globally to combat mental health issues and running more effective vaccination campaigns.

The study examines academic burnout syndrome and its relation to personal and academic variables among university students in nursing and early childhood education programs in Spain. A total of 606 university students (Primary Education: 49.7%; Nursing: 49.7%) of both sexes (71.5% female), and average age 20.68 years (SD = 1.65) participated. An ex post facto retrospective single-group design was planned. The instruments used were the Maslach Burnout Inventory-Student Survey (MBI-SS) and the NEO Five Factor Inventory (NEO-FFI). Nursing students, who showed more study hours, less sleep, and lower grades, had higher academic burnout scores. Linear regression models were proposed to analyze the relationship between academic burnout, personality, and sociodemographic variables. Nursing students scored higher in emotional exhaustion and lower in cynicism, and they scored higher in neuroticism and openness. Furthermore, 16.1% of the variance in academic burnout was explained by personality variables as degree, course and study hours. These findings suggest the importance of considering both academic and personality variables in understanding academic burnout in university students.

Land plants have undergone their great diversification and evolution in the past 400 million years. Although appearing complex and hard to grasp, the evolution of plants centers around an invariable core development process, SRC (Sexual Reproductive Cycle). Various modifications have been added sequentially to this core process, and thus creating various novel organs and distinguishing their bearers one from another. Reproductive organs of all land plants, including sporangium, megasporangium, metamegasporangium (= ovule), and various metamegasporangium complexes, are derived from terminal sporangia in the earliest land plants. Throughout the million-year-long evolution, plants sequentially recruit associating accessories to protect their vulnerable core parts (spore and gamete). The occurrence of every single of these novelties is a stair marking land plant reproduction evolution and leads to enhanced offspring development conditioning (ODC).

A random variable X that is base b Benford will not in general be base c Benford when c is not equal to b. This paper builds on two of my earlier papers and is an attempt to cast some light on the issue of base dependence. Following some introductory material, the “Benford spectrum” of a positive random variable is introduced and known analytic results about Benford spectra are summarized. Some standard machinery for a “Benford analysis” is introduced and combined with my method of “seed functions” to yield tools to analyze the base c Benford properties of a base b Benford random variable. Examples are generated by applying these general methods to several families of Benford random variables. Berger and Hill's concept of “base-invariant significant digits” is discussed. Some potential extensions are sketched.

This paper presents the results of quantitative research examining the impacts of demographic and socioeconomic factors on community resilience to disasters. The survey was carried out utilising a questionnaire distributed and subsequently collected online from 321 participants during January 2024. The study employed an adapted version of the '5S' social resilience framework, encompassing five sub-dimensions – social structure (10 variables), social capital (9 variables), social mechanisms (17 variables), social equity and diversity (13 variables), and social belief (13 variables). This customized framework includes 62 indicators, providing a thorough assessment of community (social) disaster resilience in the research context. To explore the relationship between predictors and community (social) disaster resilience in Serbia, their attitudes towards the mentioned five sub-dimensions, as well as their engagement in preventive measures and their perception of resilience to various disasters with a particular focus on demographic and socio-economic impacts, statistical methods including t-tests, one-way ANOVA, Pearson’s correlation, and multivariate linear regression were employed. The results of the multivariate regressions across various community disaster resilience subscales indicate that age emerged as the most significant predictor for the social structure subscale. At the same time, education stood out as the primary predictor for the social capital subscale. Additionally, employment status proved to be the most influential predictor for both social mechanisms and social equity-diversity subscales, with property ownership being the key predictor for the social beliefs sub-scale. Despite being considered in the analyses, gender, marital status, income level, and number of household members did not emerge as the most significant predictors across the investigated community (social) disaster resilience subscales. The determined mean value of the community (social) disaster resilience index is M = 2.62, and the findings reveal that participants assigned the highest ratings to the social beliefs subscale (M = 2.76), while the lowest values were observed in the social structure subscale (M = 2.46). Findings can be used to create strategies and interventions aimed at enhancing the resilience of communities in Serbia by addressing the intricate interplay between demographic characteristics, socio-economic factors, and their ability to withstand, adapt to, and recover from different disasters.

Active transportation, such as walking, cycling, and micro-mobility modes, has received a lot of attention in recent years due to its potential benefits to urban residents, such as less traffic, better air quality, more opportunities to get exercise, and an overall higher quality of life. In this study, we used Classification and Regression Trees (CART) to compare and contrast three mobility options: shared micro-mobility, individual micro-mobility, and walking. We surveyed 219 people living in Budapest, Hungary, to learn more about their travel habits and investigate the demographic elements that influence people's mode choice, such as age, gender, ownership of micro-mobility modes, education, job, and income. Results showed that ownership of personal micro-mobility modes, and age as important predictors of active travel mode choice. Males seem to prioritize cost and weather conditions when choosing shared micromobility modes, while females value safety and weather conditions. Our findings can guide policy decisions and urban planning initiatives by identifying the most significant predictors of mode choice and evaluating the possible benefits and drawbacks of each mode.

This article investigates whether the weather has any role in terms of spread and vulnerability of COVID-19 and how that knowledge can be used to arrest this fast spreading disease. It highlights that temperature and humidity both are important for transmitting the virus- temperature being the stronger factor. A dry, cool environment is the most favourable state for the spread of the virus. In fact, high temperature environment significantly reduces the risk from the virus. Warm places and countries are likely to be less vulnerable. Only regulating temperature level can provide drastic results to stop and arrest the outbreak. Some urgent solutions are proposed based on that knowledge. The novelty of such approach is- it can be applied overnight and implemented immediately across the globe. It is very cost effective and practically without side effects. No vast amount of funding is required to adopt these solutions. Apart from existing guidelines, these additional measures are likely to reduce the spread of the disease dramatically. Following the scientific discussion, such solutions may be thought of implementing worldwide, especially to vulnerable countries, as an emergency basis.

In this paper, we introduce two discrete degenerate random variables, namely the degenerate binomial and degenerate Poisson random variables. We deduce the expectations of the degenerate binomial random variables. We compute the generating function of the moments of the degenerate Poisson random variables, which leads us to define the new type degenerate Bell polynomials, and hence obtain explicit expressions for the moments of those random variables in terms of such polynomials. We also get the variances of the degenerate Poisson random variables. Finally, we illustrate two examples of the degenerate Poisson random variables.

Background and Objective: In the present study, the purpose was to compare the demographic, clinical and laboratory results of pediatric brucella cases who had liver involvement and who had no specific organ involvement. Material and Methods: The data of 248 patients between 2 and 18 years of age diagnosed with Brucellosis between July 2017 and August 2018 were analyzed retrospectively. The patients who had liver involvement and who did not have other specific organ involvement were compared in terms of presentation, physical examination findings, age, gender, hemogram, AST, ALT, GGT, ALP, bilirubines, sedimentation, CRP, clinical and laboratory findings, and culture and relapse rates. Results: No significant differences were detected between the patients who had liver involvement (n=92) and who did not have specific organ involvement (n=156) in terms of diagnosis age and gender. Loss of appetite, nausea and sensitive stomach were higher in the patients who had hepatic involvement, and weariness was determined to be more in the control group patients. In the patients who had hepatic involvement, the hemoglobin and platelet values were lower, and the sedimentation, CRP and blood culture growth were higher. The relapse rates were lower in patients who had liver involvement. Conclusion: In patients who have liver involvement, in addition to elevated hepatomegaly and transaminase levels, the growth rate of the acute-phase reactants and brucella is higher in blood culture; and the relapse rate is lower after treatment. Brucellosis must be considered in the differential diagnosis of hepatomegaly and transaminase elevation where brucellosis is seen endemically. We believe that early diagnosis of brucellosis is important in treatment response.

Insecticidal toxins from Bacillus thuringiensis (Bt) are valuable tools for pest management worldwide, contributing to the management of human disease insect vectors and phytophagous insect pests of agriculture and forestry. Here, we report the effects of dual and triple Bt toxins expressed in transgenic cotton cultivars on the fitness and demographic performance of Helicoverpa zea (Boddie), a noctuid pest known as cotton bollworm and corn earworm. Life-history traits were determined for individuals of three field populations from a region where H. zea overwintering is likely. Triple-gene Bt cotton cultivars expressing Cry and Vip3Aa toxins killed 100% of the larvae in all populations tested. In contrast, dual-gene Bt cotton expressing Cry1Ac+Cry1F and Cry1Ac+Cry2Ab2 allowed population growth with the intrinsic rate of population growth (rm) 38% lower than on non-Bt cotton. The insects feeding on Bt cotton plants expressing Cry1Ac+Cry2Ab2, Cry1Ac+Cry1F, or Cry1Ab+Cry2Ae exhibited reduced larval weight, survival rate, and increased development time. Additionally, fitness parameters varied significantly among the insect populations, even on non-Bt cotton plants, likely because of their different genetic background and/or previous Bt toxin exposure. This is the first report of the comparative fitness of H. zea field populations on dual-gene Bt cotton after the recent reports of field resistance to certain Bt toxins. These results document the population growth rates of H. zea from an agricultural landscape with 100% Bt cotton cultivars. Our results will help to refine models designed to predict resistance evolution and improve insect resistance management for Bt crops.

A new form of beta coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) causing a recent pandemic outbreak possesses a linear positive ss-RNA genome with a length of 29,903 nt. Here, the genomes of SARS-CoV-2 from 821 samples were characterised for its better understanding of the genomic and evolutionary patterns. The phylogeny of SARS-CoV-2 was reconstructed using concatenated dataset consisting of all peptide encoding sequences under Bayesian Inference (BI) and Maximum Likelihood (ML) approaches. Comparison of all peptide encoding sequences reveals high divergence of amino acid sequences proportional to divergence of nucleotides, indicating that the viral genomic evolution has not been strictly neutral. The most part of the genome was under neutral evolution, however, the specific sites for peptide encoding sequences were evolved under positive selection. As well as providing reliable evidence on transmission routes of the SARS-CoV-2 outbreak, the phylogenetics and network analyses suggest the sample reported from Guangdong province is likely ancestor of the pandemic virus form. The overall substitution rate of SARS-CoV-2 genome was estimated to be 1.65 x 10^-3 per site per year, falling within the range for previously reported RNA viruses. Median estimation of tMRCA from Bayesian coalescent analyses corresponds to 10 September 2019. The exponential growth rate (r), doubling time (Td) and R₀ were estimated to be 47.43 per year, 5.39 days and 2.72, respectively. These findings convincingly emphasise that the use of more comprehensive genome data improves robustness and also enhances understanding of the demographic history of the outbreak.

Free Floating Car Sharing (FFCS) services are a flexible alternative to car ownership. These transportation services show highly dynamic usage both over different hours of the day, and across different city areas. In this work, we study the problem of predicting FFCS demand patterns -- a problem of great importance to an adequate provisioning of the service. We tackle both the prediction of the demand i) over time and ii) over space. We rely on months of real FFCS rides in Vancouver, which constitute our ground truth. We enrich this data with detailed socio-demographic information obtained from large open-data repositories to predict usage patterns. Our aim is to offer a thorough comparison of several machine learning algorithms in terms of accuracy and easiness of training, and to assess the effectiveness of current state-of-art approaches to address the prediction problem. Our results show that it is possible to predict the future usage with relative errors down to 10%, and the spatial prediction can be estimated with relative errors of about 40%. Our study also uncovered the socio-demographic features that most strongly correlate with FFCS usage, providing interesting insights for providers opening service in new regions.

The widespread integration and growing dependence among currency, stock and commodity markets make these markets often very vulnerable to shocks and at risk of collapse at the same time. As a result, these trends threaten the sustainability of the entire financial system. In this study, we explore the spillovers and nonlinear dependences between the seven major foreign ex-change rates, crude oil and gold prices, a global stock price index, and oil and stock implied volatility indices as proxy variables for global risk factors by em-ploying directional spillover network approach. We also use multi-scale de-composition method and nonlinear causality test between these variables to capture multi-level relationships at short and long horizons. Major findings are summarized as follows. First, from the multi-scale decomposition analysis, we identify that Granger causality test results and the direction and strength of return spillovers change with the level of decomposition. Second, the results of nonlinear causality tests show variation in both the significance and direction of Granger causality relationships between the decomposed currency and other series at different timescales, especially for the decomposed oil, gold, and OVX series. Third, the measured directional spillover indices identify the EUR as the largest contributor of connectedness to the other series. The central role of the EUR is a net transmitter of connectedness to gold, oil, the GBP, JPY, and CHF.

Tennis is an individual sport characterised by high intensity action, including sprints and changes of direction (COD). There is a gap in the knowledge of limb asymmetries in adolescent tennis players and their association with performance. This study aimed to examine the relationship between asymmetry in vertical and horizontal jump tests (CMJ and HJ) and COD with lower limb performance variables in adolescent tennis players. Forty-five adolescent tennis players (age: 13.81 ± 1.08 years; height: 167.64 ± 9.9 cm; body mass: 57.48 ± 10.94 kg; body mass index: 20.27 ± 2.18 kg/m2) performed the CMJ test (unilateral and bilateral), horizontal jumps (unilateral and bilateral), 25 m sprint and 180º COD test. The single-leg countermovement jump showed the greatest asymmetries among the different tests (6.62 ± 9.35%). Significant negative relationships were found between CMJ asymmetry and COD asymmetry with unilateral horizontal jump variables (r = -0.30 to -0.53). In addition, CMJ asymmetry showed significant relationships with CMJR (r=0.49) and COD180R (r=0.29), whereas COD asymmetry showed a significant relationship with COD180L (r=0.40). On the other hand, HJ asymmetry showed no significant relationships with any variable. The main findings of this study indicate that greater imbalances in the CMJ and COD tests are associated with a reduced capacity to perform unilateral horizontal jumps. These results suggest the need to incorporate training protocols that reduce interlimb asymmetries in growing athletes to improve their performance.

Although Shannon mutual information has been widely used, its effective calculation is often difficult for many practical problems, including those in neural population coding. Asymptotic formulas based on Fisher information sometimes provide accurate approximations to the mutual information but this approach is restricted to continuous variables because the calculation of Fisher information requires derivatives with respect to the encoded variables. In this paper, we consider information-theoretic bounds and approximations of the mutual information based on Kullback--Leibler divergence and Rényi divergence. We propose several information metrics to approximate Shannon mutual information in the context of neural population coding. While our asymptotic formulas all work for discrete variables, one of them has consistent performance and high accuracy regardless of whether the encoded variables are discrete or continuous. We performed numerical simulations and confirmed that our approximation formulas were highly accurate for approximating the mutual information between the stimuli and the responses of a large neural population. These approximation formulas may potentially bring convenience to the applications of information theory to many practical and theoretical problems.

Internal and mesoscopic variables differ from each other fundamentally: both are state space variables, but mesoscopic variables are additional equipped with a distribution function introducing a statistical item into consideration which is missing in connection with internal variables. Thus, the alignment tensor of liquid crystal theory can be introduced as an internal variable or as one generated by a mesoscopic background using the microscopic director as mesoscopic variable. Because the mesoscopic variable is part of the state space, the corresponding balance equations change into mesoscopic balances, and additionally an evolution equation of the mesoscopic distribution function appears. The flexibility of the mesoscopic concept is not only demonstrated for liquid crystals, but is also discussed for dipolar media and flexible fibers.

There is increasing evidence that the non-cooperative models describe household structures in developing countries more succinctly compared with the unitary model. Domestic violence against women, which is pervasive in Nigeria even though likely to be under-reported, will need to be understood within the framework of non-cooperative relationship between couples. In this study, we identify factors of domestic violence against women within couples who were currently in marital or cohabiting partnerships. Also, we investigate whether domestic violence influences the decision of women to terminate pregnancies. We use data from the 2018 Nigeria Demographic and Health Survey (NDHS). Multivariate logistic regressions were used to model the predictors of domestic violence, and its influence on the decision to terminate pregnancies among married women. Of the 8,910 married women interviewed for domestic violence, 35.33% had ever experienced a form of domestic violence. We discover that women: with higher education, that is not poor, and resides in urban areas have 44%, 18% and 15% reductions in the odds of experience domestic violence respectively. On the other hand, women who are employed, own land, having husbands/partners that are employed in the agricultural sector, and drink alcohol have 1.16, 1.2, 2.07, and 2.8 times increased odds of experiencing domestic violence accordingly. Also, we uncover that currently married women experiencing domestic violence have 1.25 times increased odds of terminating pregnancies compared with their counterparts that are not experiencing domestic violence. Effectively, poverty, low levels of education, residing in rural areas, drinking habit of husbands/partners, employment, marital capital, and land ownership status of women are risk factors of domestic violence against married women in Nigeria but can be affected by policies and programmes. Importantly, public actions to contain domestic violence in order to improve maternal health should be implemented in the context of the dynamics of a non-cooperative relationship existing between married couples.

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes. The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.

Recent climatic disasters (dzudzs) and uncontrolled massive breeding endangered valuable ge-netic resources of Mongolian goats labored by five thousand years of evolution in extremes of Al-tai mountains and Gobi deserts. Meanwhile, Mongolian goats has never been characterized by genomic data. We used Illumina Goat SNP50 to investigate phylogenic relationships and genetic risks in 5 local Mongolian populations: Erchim (N=37) from geographically remote Darkhat Valley in the northern mountains, Ulgii Red (N=35) and Dorgon (N=28) from the western mountain region, Buural (N=34) from the western steppe and mountain areas and Gobi Gurvan Saikhan (N=33) from semi-arid steppe area in the South Gobi region. ROH analyses, estimated populations sizes and Fst values showed South Gobi and Darkhat Valley goats to be of a high risk of inbreed-ing that however appear to be of distinct origin (artificial selection vs geographical isolation). In-dices of genetic differentiations between Mongolian goats were relatively low compared to Euro-pean breeds. Meanwhile, we suggest direct comparison is not fully appropriate given that Mongo-lian breeds were not subjected to intense selection. Darkhat Valley goats were clearly differentiat-ed from other Mongolian breeds according to various types of analyses. Phylogenetic relationships within XXX breeds of the rest of the world plotted Mongolian goats between some Russian (Altai, Orenburg) and Chinese populations (Nanjiang and Qinggeli). Thus, present study (i) highlights demographic history Mongolian goats and (ii)provides unified SNP-data called for support deci-sions in conservational genetics. Finally, our work (iii) raises a question of how exactly these data should be compared to make objective choices.

Background. Predisposition to HIV+ is influenced by a wide range of correlated economic, environmental, demographic, social, and behavioral factors. While evidence among a candidate handful have strong evidence, there is lack of a consensus among the vast array of variables measured in large surveys. Methods. We performed a comprehensive data-driven search for correlates of HIV positivity in >600,000 participants of the Demographic and Health Survey (DHS) across 29 sub-Saharan African countries from 2003 to 2017. We associated a total of 7,251 and of 6,288 unique variables with HIV+ in females and males respectively in each of the 50 surveys. We performed a meta-analysis within countries to attain 29 country-specific associations. Results. We identified 344 (5.4% out possible) and 373 (5.1%) associations with HIV+ in males and females, respectively, with robust statistical support. The identified associations are consistent in directionality across countries and sexes. The association sizes among individual correlates and their predictive capability was low to modest, but comparable to established factors. Among the identified associations, variables identifying being head of household among females was identified in 17 countries with a mean odds ratio (OR) of 2.5 (OR range: 1.1-3.5, R² = 0.01). Other common associations were identified with marital status, education, age, and ownership of land or livestock. Conclusions. Our continent-wide search for variables has identified under-recognized variables associated with HIV+ that are consistent across the continent and sex. Many of the association sizes are as high as established risk factors for HIV+, including male circumcision.

Food intake plays a pivotal role of human growth, which necessarily contributes 45% of global economy and wellbeing in general. Consumption of balanced food is elementary for overall good health while a shift of equilibrium can lead to malnutrition, prenatal death, obesity, osteoporosis and bone fractures, coronary heart diseases (CHD), idiopathic hypercalciuria, diabetes and many more. Though CHD, osteoporosis, malnutrition, obesity are being classified thoroughly in the literature, there are fragmented findings in the regime of kidney stone diseases (KSD) and the correlation with food intake therein. KSD associated with hematuria and renal failure poses an increasing threat to the healthcare and global economy while its emergence of Indian populations is being affected with multi-factorial urological disorder resulting from several factors. In this realm, epidemiological, biochemical, macroeconomic situations been portrayed when food intake is also a paramount importance which rarely been forecasted. Hence, in this article we will be reviewing the corollary connotation with diverse food consumption and the efficacy it plays in KSD extrapolating in Indian context.

Objective: To determine demographic predictors and comorbidities in hospitalized children with conduct disorder. Methods: A retrospective analysis was performed using Nationwide Inpatient Sample (2012–2014). All patients were ≤18 years and cases with primary diagnosis of conduct disorder (N = 32345) and a comparison group with another psychiatric diagnosis (N = 410,479) were identified using ICD-9-CM diagnosis codes. A logistic regression model was used to generate the Odds Ratio (OR) between both groups. Results: Children <11 years old have five times greater chances of admission for conduct disorder than adolescent (OR 5.339). African American males are more likely to be admitted for conduct disorder. Children with conduct disorder from low-income families have a 1.5 times higher likelihood for inpatient admission compared to high-income families. These children have about eleven times higher odds of comorbid psychosis (OR 11.810) and seven times for depression (OR 7.093) compared to the comparison group. Conclusion: Conduct disorders are more debilitating for children and families than many providers realize. African American male under 11 years is at the highest risk for inpatient management for conduct disorder. These patients have a higher risk of comorbid psychosis and depression which may further deteriorate the severity of illness and require acute inpatient care.

Background: Despite the abundant scientific literature on entrepreneurship, there is still only limited information on young students’ entrepreneurial intentions. The reasons may be generally found in the different conceptual approaches to entrepreneurial intention and particularly in the variables that regulate and act as antecedents to such intentions. This bias has generated different lines of investigation into the factors relating to entrepreneurial intention among students: one is centered on the variables that influence entrepreneurial intention, in particular, relational, educational, and psychological variables; and the other is centered on the antecedents of entrepreneurial intention, among which is entrepreneurial interest. Methods: In the present paper, we seek to analyze the relationship between the entrepreneurial interest of Spanish youth and a set of socio-educational, psychological, and health-related variables using principal component analysis. A previously validated ad hoc questionnaire was administered to 1764 students (15–18 years old). Results: Notably, few Spanish youth expressed significantly high entrepreneurial interest; those who did were mostly men with a family tradition of entrepreneurial parents, who held high perceptions of their health and quality of life and considered it important in business to detect opportunities beforehand and to create employment. Conclusions: Their principal motives were to improve their professional development, to put their ideas into practice, and to achieve economic independence. This paper proposes the early detection of entrepreneurial interests in young people in order to reinforce these interests as potential long-term initiatives.

With the widespread use of electric machines there is a growing need to extract information from the machines to optimize their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of an squirrel cage induction motor rotor physical variables. The system comprises: circuit to acquire desirable rotor variable(s) value(s) and send it to the computer; a rectifier and power storage circuit that besides converting an alternating current in continuous also store energy for a certain amount of time to wait the motor engine shutdown; and magnetic generator that harvest energy from rotating field to power the circuits mentioned above. The embedded system is set on the rotor, making it difficult to power the system because it is rotating, problem solved with the construction of the magnetic generator eliminating the need of using batteries or collector rings and send data to the computer using a wireless NRF24L01 module. For the proposed system validation a temperature sensor (DS18b20) was used, variable known as the most important when identifying the need for maintenance and control systems. Tests were made getting satisfactory results proving the viability of using sensors on the rotor.

Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. Controlling and curing diabetes in its early stages is the most significant technique to avoid its effects of diabetes. However, lack of awareness and expensive clinical tests are the primary reasons to skip clinical diagnosis and take preventive methods in lower-income countries like Bangladesh, Pakistan, and India. From this perspective, the study aims to build an automated machine learning (ML) model, which will predict diabetes at an early stage using socio-demographic characteristics rather than clinical attributes. Because clinical features are not always known to all people from lower-income countries. To find the best fit supervised ML classifier of the model, we applied six classification algorithms and found that RF outperformed with an accuracy of 99.36%. In addition, the most significant risk factors were found based on the SHAP value by all the applied classifiers. The study reveals that polyuria, polydipsia, and delayed healing are the most significant risk factors for growing diabetes. The findings indicate that the proposed model is highly capable of predicting diabetes in the early stages.

The doctoral defense, which is an essential requirement for the doctoral degree, is considered to have three dimensions: the scholarly dimension, the emotional (affective) dimension, and the cultural dimension. In this work, I explore the link between sociodemographic factors and students’ perception of the doctoral defense. In particular, I focus on gender, ethnicity, and age at time of defense, as well as current position, and field of study. To address the influence of these aspects on the affective dimension of the doctoral defense, I first reviewed the literature on these socio-demographic aspects as well as the affective dimension of the defense. I then carried out an international survey on doctoral defenses, defense formats, and students’ perceptions and analyzed the 204 completed surveys for this study using quantitative and qualitative methods. The analysis included cross-correlations between students’ perceptions and the studied sociodemographic aspects. The main results of these analyses are that gender affects various aspects of the students’ perception of the doctoral defense and long-term perception, and that female candidates experience more issues with their committee. Ethnicity is important as well, although the participations of non-white respondents in this survey was limited. The influence of age at the defense is limited, and only for the youngest and oldest age groups I observe some differences in perception. There is no relation between current position and perception of the candidates during the defense. Finally, field of study is correlated for various aspects of student perception, committee issues, and long-term perception. The conclusion of this work is that socio-demographic aspects, and in particular gender, ethnicity, and field of study, influence how doctoral candidates experience their defense.

The purpose of this work is to define optimal growth conditions for batch culture of the cyanobacterium Arthrospira maxima and the microalgae Chlorella vulgaris, Isochrysis galbana and Nannochloropsis gaditana. Thus, we study the effect of three variables on algae growth: i.e., inoculum:culture medium ratio, light:darkness photoperiod and type of culture medium, including both synthetic media and wastewaters. The results showed that the initial inoculum volume did not affect the amount of biomass at the end of the growth (14 days), whereas an excess (18 h) or defect (6 h) in the number of hours of light is determinant for its development. The contribution of nutrients from different culture media modified the growth of the different species. A. maxima was favoured in seawater enriched with Guillard's F/2 as well as C. vulgaris and N. gaditana but in fresh water medium. I. galbana had the greatest growth in the marine environment enriched with Walne’s media. Nitrate was the limiting growth reagent at the end of the exponential phase of growth for C. vulgaris and N. gaditana, while iron was for A. maxima and I. galbana. All species demonstrated their capability to grow in effluents from a wastewater treatment plant and they efficiently consume nitrogen, especially the three microalgae species.

A nation's vitality, dynamism and economic strength will always be related to its demographic component, and a healthy and vigorous population will ensure its long-term future. However, the current realities demonstrate the existence of an obvious population decrement at the level of the entire country particularly triggered by the birth rate decrease and the high demographic aging to which other factors add ap specific to local communities, which in their turn determined a particular type of demographic behaviour. Therefore we aim to analyze those elements with a major population dynamics impact such as family stability and demographic potential that can generate a specific demographic behaviour, as a result of the major changes that have occurred in the last period of time. These elements are translated through several demographic indicators that characterize the family, such as the nuptiality index and the divorce index whose evolution was registered and analyzed for the period 1992-2021. Their evolution indicates the demographic potential of Romania, as well as of Bihor county.

Gradients of smooth functions with non-independent variables are relevant for exploring complex models and for the optimization of functions subjected to constraints. In this paper, we investigate new and simple approximations and computations of such gradients by making use of independent, central and symmetric variables. Such approximations are well-suited for applications in which the computations of the gradients are too expansive or impossible. The derived upper-bounds of the biases of our approximations do not suffer from the curse of dimensionality for any $2$-smooth function, and theoretically improve the known results. Also, our estimators of such gradients reach the optimal (mean squared error) rate of convergence (i.e., $\mathcal{O}(N^{-1})$) for the same class of functions. Numerical comparisons based on a test case and a high-dimensional PDE model show the efficiency of our approach.

The choice of holiday destinations is highly depended on climate considerations. Nowadays, since the effects of climate crisis are being increasingly felt, the need of accurate weather and climate services for hotels is crucial. Such a service could be beneficial for both the future planning of tourists’ activities and destinations and for hotel managers as it could help in decision making about the planning and expansion of the touristic season, due to a prediction of higher temperatures for a longer time span, thus causing increased revenue for companies in the local touristic sector. The aim of this work is to calculate predictions on climatic variables using statistical techniques as well as Artificial Intelligence (AI) for a specific area of interest utilising data from in situ meteorological station, and produce valuable and reliable localised predictions with the most cost-effective method possible. This investigation will answer the question of the most suitable prediction method for time series data from a single meteorological station that is deployed in a specific location. As a result, an accurate representation of the microclimate in a specific are is achieved. To achieve this high accuracy in situ measurements and prediction techniques are used. As prediction techniques, Seasonal Auto Regressive Integrated Moving Average (SARIMA), AI techniques like the Long-Short-Term-Memory (LSTM) Neural Network and hybrid combinations of the two are used. Variables of interest are divided in the easier to predict temperature and humidity that are more periodic and less chaotic, and the wind speed as an example of a more stochastic variable with no known seasonality and patterns. Our results show that the examined Hybrid methodology performs the best at temperature and wind speed forecasts, closely followed by the SARIMA whereas LSTM perform better overall at the humidity forecast, even after the correction of the Hybrid to the SARIMA model.

Youth is the essential entrepreneurial force for every country's social, political, and economic development. Urban youth make up about 34.27 percent of the population in Ethiopia. The youth unemployment crisis is one of the serious challenges that Ethiopia is facing nowadays, and it should be mentioned in the nation's public discourse. Therefore, the main objective of this study is to specify the socioeconomic and demographic factors that influence urban youth unemployment in the Somali Regional State, specifically in Jigjiga, Degahbour, Kebridahar, Gode, and Dollo Ado towns. Both primary and secondary data sources were employed. A multi-stage sampling technique has been used to select 385 sample respondents from the total population of the study. This study found that almost 63% of youth in the study area were unemployed, and a large number of unemployed youths live in Jigjiga and Dollo Ado Towns as compared to other city administrations. The econometric model's findings indicate that factors like gender, education level, work experience, access to credit, access to information, time applied for job vacancy, active job seeker, social network (network with clan elders, government officials, businessmen, and other friends), and residence in Jigjiga and Gode town have a significant association with the likelihood of youth unemployment in the Somali regional state. Therefore, this study recommends that the regional government and local city administration should develop effective policies and strategies to address the underlying causes of gender inequality, improving access and quality of education, supporting freshman graduates to find jobs, providing access to credit and job vacancies, ensuring fair and free job competition, and managing youth migration for job seeking.

We present a new penalized method for estimation in sparse logistic regression models with group structure. Group sparsity suggests us to consider the Group Lasso penalty. Being different from penalized log-likelihood estimation, our method can be viewed as a penalized weighted score function method. Under some mild conditions, we provide non-asymptotic oracle inequalities promoting group sparsity of predictors. A modified block coordinate descent algorithm based on a weighted score function is also employed. The net advantage of our algorithm over the existing Group Lasso-type procedures is that the tuning parameter can be pre-specified. The simulations show that this algorithm is considerably faster and more stable than competing methods. Finally, we illustrate our methodology with two real data sets.

The technique of superposition of motions in the space of Lagrange variables is described, which allows us to obtain the equations of combined motion by replacing the Lagrange variables of superimposed (external) motion with Euler variables of nested (internal) motion. The components of velocity and acceleration in the combined motion obtained as a result of differentiating the equations of motion in time coincide with the results of vector addition of the velocities and accelerations of the particles involved in the superimposed motions at each moment of time. Examples of motion and superposition descriptions for absolutely solid and deformable bodies with equations for the main kinematic characteristics of motion, including for robot manipulators with three independent drives, pressing with torsion, bending with tension, and cross– helical rolling, are given. For example, given the fragment of calculation of forces in the kinematic pairs shown the advantages of the description of motion in Lagrangian form for the dynamic analysis of lever mechanisms, allows to determine the required external exposure when performing the energy conservation law at any time in any part of the mechanism.

The study examined key socio-economic characteristics of smallholder farmers identified for their contribution to market participation. These variables include gender, age, marital status, level of education, household size, additional income, membership of cooperative, herd size and use of ICTs. Using a structured questionnaire, primary data was collected from a total of 129 respondents which was analysed with the Statistical Package for the Social Sciences, and presented using cross-tabulations, percentages and count data. The result indicates that age, additional income, cooperative membership and use of ICTs were important variables which contributed to market participation among respondents. The study also made applicable recommendations as the findings may have relevance for future research, policy and practice for commercializing smallholder farmers.

We studied generalization of a method for extending configurational studies to variables that are not exclusively geographical, in order to allow investigation of generic relationships in the built environment. We observed a number of limitations of the classical approach of configurational studies and we considered how a complex analytical method could be implemented in the study of non-topological variables, such as land use, noise pollution and financial or property rents. In order to do this we established a system of relationships based on a labeled primary graph. Categorization of the labels of the links was performed on a generic variable, specifically, the predominant use of roads. The graph was then contracted using an optimization algorithm, which we describe. The algorithm allows the network to be reduced to a more streamlined system that can better analyze the relationships between the different categories. Application of the method showed that it is faster to identify weaknesses in urban networks, and then take measures to resolve them. The case study concerns the pedestrianization of the Colosseum area in Rome.

This study assessed the hydrological performance and runoff water quality of 12 green roof (GR) modular systems located at the Universidad de los Andes campus (Bogotá, Colombia). Based on 223 rainfall events spanning a 3-year period, average rainfall retention was 85% (SD = 25%). T-tests, Welch Test, multiple linear regressions and correlation analysis were performed in order to assess the potential effect of air temperature, substrate type, vegetation cover, relative humidity, antecedent dry weather period (ADWP), rainfall duration and rainfall maximum intensity. In some cases, GR design variables (i.e. growing media and type of vegetation) were found to be significant for describing rainfall retention efficiencies and, depending on the GR type, some hydrological variables were also correlated with the rainfall retention. Rainfall and GR runoff were monitored for Total Kjeldahl Nitrogen (TKN), Nitrates, Nitrites, Ammonia, Total Phosphorus (TP), Phosphates, pH, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Color, Turbidity, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Coliforms, metals and Poliaromatic Hydrocarbons (PAHs). The results obtained confirmed that GR systems have the ability to neutralize pH, but are source of the rest of the aforementioned parameters, excluding PAHs (with concentrations below detection limits), Ammonia, TSS, Se and Li, where differences with reference values (rainfall and plastic panel runoff) were not statistically significant. Substrate type, event size and rainfall regime are relevant variables for explaining runoff water quality.

Background: This study delves into the examination of racial and ethnic disparities in the distribution of the Monkeypox (MPOX) virus vaccine within the United States, offering a critical healthcare perspective on an emerging public health concern. It particularly focuses on the demographic patterns associated with MPOX transmission and the allocation of vaccines. Methods: A comprehensive analysis was conducted, drawing on a wide array of data sources to understand the vaccine distribution and demographic trends in the United States. The study scrutinized three main aspects: MPOX cases by race and ethnicity, vaccine administration across different racial and gender categories, and the potential disparities therein. Results: The findings reveal significant disparities in the distribution of vaccine doses, with males, particularly gay, bisexual, and other Men who have sex with men (MSM), receiving the majority of doses. Moreover, substantial variations in MPOX cases are observed among different racial and ethnic groups, emphasizing the need for culturally sensitive public health strategies. Conclusions: The study underscores the urgent need for targeted public health interventions to address disparities and safeguard the well-being of those at higher risk, particularly MSM. It highlights the importance of equity in vaccine distribution and culturally sensitive approaches, and serves as a foundation for shaping effective public health policies and strategies to mitigate the spread of MPOX. This research advances our understanding of healthcare disparities in the context of an emerging viral infection, providing valuable insights for future public health initiatives.

COVID-19 emerged in Wuhan and is later declared as a pandemic by World Health Organization. Different-aged people have varying gender-wise immunity control properties that necessitates understanding COVID-19 impact on age and gender which does not exist, currently. In this paper, COVID-19 surveillance variables are extensively studied along with hospitalization, tests-performed, and recovery data. Dataset is curated from three sources; however, age and gender data belong to Belgium, particularly. Visualizations, frequencies, Pearson’s and polyserial correlation, student’s t-test, and Cramer’s V are used for enhanced analysis. Results show higher mortality rate in males and need of more ventilators to combat severe symptoms.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

Around the world, every year, about 17 million people death cause happen due to CardioVascular Diseases (CVD). As per clinical records, primarily sufferers exhibit myocardial infarctions and Heart Failures (HF). Creatinine is a Musculo - skeletal waste product. The kidneys filter creatinine from the blood and excrete it through the urine in a healthy body. High creatinine levels can suggest renal problems. Elevated Serum Creatinine (SC) has been well established in the HF. Patients’ electronic medical records can be used to quantify symptoms and other related clinical laboratory test values, which would then be utilized to direct biostatistics exploration to uncover patterns and associations that doctors would otherwise miss. The latest American Heart Association guidelines for 1500 mg/d sodium tend to be sufficiently relevant for patients with stage A and B with HF. In this article, we used a dataset of the year 2015 of heart patients records of 299 patients. The present paper used the data analytic and statistical tools to verify the significant differences between alive and dead patients’ SC and Serum Sodium (SS). It also demonstrates the impact of significant features on abnormal SC and SS on the Survival-Status levels. The Age-Group feature, which is derived from age attribute and, Ejection Fraction (EF), anemia, platelets, Creatinine Phosphokinase (CPK), Blood-Pressure (BP), gender, diabetes, and smoking-status were utilized to determine the potential contributing features to mortality with Cox regression model. The Kaplan Meier plot was used to investigate the overall pattern of survival concerning age-group. During pre-processing of the dataset, Age and SS were removed due to multicollinear features during performing machine learning algorithms experiments. This paper also predicted patients’ survival, age group, and gender using supervised machine learning classifiers. Detection of significant features would help in making informed decisions to balance the lifestyle of heart patients. The author revealed that the patient’s follow-up months, as well as SC, EF, CPK, and platelets, are sufficient key features to predict heart patient survival using Random Forest (RF) stratified 10-fold CV method with accuracy (96%) with 5% Standard Deviation (SD) from medical records dataset. We identified the age-group and gender of the patient, and the RF model outperformed others with the best accuracy 96% and 94% in both cases having 11% SD. Also, prominent features such as CPK, SC, follow-up month, platelets, and ejection were found to be significant factors in predicting the patient’s age-group. Smoking habits, CPK, platelets, follow-up month, and SC of each patient were discovered to be significant predictors of patient gender. The hypothetical study proved that SC and SS making substantial differences in the survival of patients (p &lt; 0.05) and failed to reject that anemia, diabetes, and BP making a significant impact on the creatinine and sodium of each patient (p &gt; 0.05). With χ2(1) = 8.565, the Kaplan Meier plot revealed that mortality was high in the extremely elder age-group. The finding has possible effects on clinical practice and becomes a new medical support system when predicting whether a patient can survive a heart attack or not. The doctor should primarily concentrate on follow-up month, SC and EF, CPK, and platelet count since the aim is to understand whether a patient survives after HF.

The use of risk measures such as the Value at Risk (VaR) or Tail Conditional Expectation (TCE) is required by the Basel Committee on Banking Supervision in determining a bank’s risk profile. However, both measures can be shown to have shortcomings in the information that they provide to regulators and investors. In this paper we present an introduction to risk measure calculations before demonstrating the weaknesses of these measures. Through the exploration of specific cases we show how familiar yet differing risk profiles have identical values for combinations of these measures. From this evidence we recommend that a sequence of several risk measures should be used to give a more accurate representation of the risk contained on banking balance sheet.

The gut microbiome offers numerous advantages to the hosts, through a variety of physiological mechanisms like firming up gut integrity or shaping the intestinal epithelium. Studies showed 2172 species are identified and isolated from human beings, ordered into twelve different phyla, of which 93.5% belonged to Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria. Out of the 12, three phyla are identified. Human microbial communities are affected by the host external factors like dietary patterns, lifestyle factors, antibiotic usage, internal factors gender, host genotype, age and race. To analyze the dysbiosis and bacterial variation in different areas of District Faisalabad 10,000 individuals of age 25–35 years were recruited from the two different rural and urban localities. The oral swab and fecal sample were collected according to prescribed manner. The collected samples from demographically and geographically distinct regions of District Faisalabad were subjected to DNA extraction and quantification. The amplification of 16s rRNA was carried out by PCR and visualized through a transilluminator. The results revealed significant elevated, % abundance of fecal microbial profile Blautia spp, Firmicutes, Ruminococcaceae, in rural population however non-significant difference % abundance of total Bifido, E. coli, Faecali bacteria, total Lactobacillus were identified in both demographically distinct regions. The pathogenic Gamma Protebacteria, Fusobacterium, Campylobacter coli were not detected in both study areas. Out of five orally detected microbial profiles, elevated % abundance of Firmicutes was detected in rural population however non-significant difference was observed in % abundance of total Bifido and E. coli in both populations. Total Lactobacillus and Fusobacterium were not detected in oral sample of both urban and rural population. Conclusively, this research accomplished the potential effects of demographic and geographical induced dysbiosis in the normal microbiome of the oral cavity and intestine that might cause dysbiosis associated disorders.

Hepatitis is the eighth highest cause of mortality globally and second-highest in Pakistan. The purpose of this study was to determine frequency of Hepatitis B and C and related lifestyle and socio-demographic risk factors among adults. The data were collected though questionnaire from Hepatitis B and C patients from Mayo and Jinnah hospital Lahore. The data was analyzed using SPSS version 18. There were 5095 patients with Hepatitis B and C out of which 146 patients (67 males and 79 females) filled questionnaire. The frequency of hepatitis C was higher than hepatitis B. The significant risk factors associated with hepatitis B and C were education, marital status, family history, household income, and type of food consumed. Therefore, socio-demographic and lifestyle risk factors related interventions are needed to reduce frequency of Hepatitis B and C.

The escape and establishment of Iberian wild goats, Capra pyrenaica, from an enclosure in the 1990s marked the beginning of the recovery of the species in the Pyrenees. This population has occupied part of the Prepyrenees and has contacted another population reintroduced in France since 2014. It coexists with other wild ungulates, including the feral and domestic goats Capra hircus that has been living free since the 1960s. Today it’s the largest Iberian wild goat Pyrenean population. Between 2006 and 2022 we monitored the population and its expansion based on vantage points, itineraries and testimonies. The results indicate: (i) a population, of uncertain genetic origin, in numerical (15% average annual growth) and areal expansion, with the capacity to connect with other populations; (ii) an estimate of at least 500 individuals; (iii) in the process of expansion in contact with Iberian wild goats from France; (iv) sympatry with feral and domestic goat population in its main nucleus whose estimate exceeds 2000 specimens and (v) hybridization with feral and domestic goats. In 2022 sustainable hunt started with a hunting quota of 20 individuals. Genetic characterization and the establishment of an international coordinated monitoring are two of the current priorities.

News recommendation schemes utilize features of the news itself and information about users to suggest and recommend relevant news items to the users towards the interest they have. However, the effectiveness of the existing news recommendation scheme is limited in the occurrence of new user cold start problems. Therefore, we designed a news recommender system using hybrid approaches to address new user cold start problems to ease and suggest more related news articles for new users. To achieve the objective mentioned above, user demographic data with a hybrid recommendation system that contains the scheme of both content-based and collaborative filtering approaches is proposed. To evaluate the effectiveness of the proposed model, an extensive experiment is conducted using a dataset of news articles with user rating value and user demographic data. The performance of the proposed model is done by two ways of experiment. So, the performance of the proposed model performs around 68.05% of Precision, 42.46% of Recall and 52.1% of the average F1 score for the experiment based on individual user similarity in the system. And also performs around 93.75% of precision, 40.25% of recall and 56.31% F1-score for the similarity of users based on the similarity of users within the same category which is better than the first experiment.

Demographic processes directly affect patterns of genetic variation within contemporary populations as well as future generations, allowing for demographic inference from patterns of both present day and past genetic variation. Advances in laboratory procedures and sequencing and genotyping technologies in the last decades have resulted in massive increases in high quality genome-wide genetic data from present day populations and allowed retrieving genetic data from archaeological material, also known as ancient DNA. This has resulted in an explosion of work exploring past changes in population size, structure, continuity and movement. However, as genetic processes are highly stochastic, patterns of genetic variation only indirectly reflect demographic histories. As a result, past demographic processes need to be reconstructed using an inferential approach. This usually involves comparing observed patterns of variation with model expectations from theoretical population genetics. A large number of approaches have been developed based on different population genetic models that each come with assumptions about the data and underlying demography. In this article I review some of the key models and assumptions underlying the most commonly used approaches for past demographic inference and their consequences for our ability to link the inferred demographic processes to the archaeological and climate records.

The importance of various markers such as sclerostin, Dickkopf-1 (DKK-1), Irisin, receptor activator of NF-kB ligand (RANKL), and Vitamin D have been well studied in bone metabolism. Additionally, inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and Interleukine-6 (IL-6) have been identified to hinder muscle protein synthesis, leading to the loss of muscle and strength. However, a research gap exists in the understanding their role in muscle function and physical activity. Therefore, this study aims to explore the serum levels of sclerostin, DKK-1, irisin, IL-6, RANKL, Vitamin D, and TNF-α and assess their relationships with upper and lower body strength in young adults. In this study, 38 college-aged students 18-23 years participated and completed the protocols. The participants’ lower and upper body strength were assessed by the vertical jump test (Just Jump, Probotic, AL) with a Tendo FitroDyne (Tendo Sports Machines, Trencin, Slovak Republic) and handgrip (HG) dynamometry (Takei Scientific Instruments, Yashiroda, Japan), respectively. Fasting morning blood samples were analyzed for serum levels of the biomarkers by ELISA. The results indicate significant sex differences in sclerostin, DKK-1, irisin, and vitamin D levels (p<0.05). Furthermore, a positive association was observed between sclerostin, DKK-1, and vitamin D, with lower body muscle performance variables (p<0.05). Conversely, a significant negative correlation was observed between TNF-α and upper-body muscle performance variables (p<0.05). The results suggest that these markers may have a distinct effect on muscle performance, underscoring the need for further investigation to elucidate the concept of muscle-bone crosstalk.

This study utilizes data from the fourth National Health Survey conducted in 2019. in the Republic of Serbia, aiming to contribute to a deeper understanding of the factors influencing the mobility of the elderly population. It examines the sociodemographic and psychosocial factors associated with functional limitations in older adults. By analyzing variables such as age, gender, marital status, education, income, social support, and mental health, the study seeks to explain their impact on the prevalence of walking limitations.Questionnaires were employed as a research instrument in line with the methodology of the European Health Survey (EHIS). The analysis is based on a sample of 3,705 participants aged 65 and above. Statistical significance between variables was assessed using the Chi-square test. Post-hoc comparisons were performed using pairwise z-tests. Univariate logistic regression was employed to identify predictors of walking difficulties. Additionally, multivariable logistic regression was conducted to further explore predictors while adjusting for potential confounding variables, with odds ratios and corresponding 95% confidence intervals estimated.Women exhibit significantly higher prevalence of walking difficulties compared to men (p < 0.001). There is a significant variation in the prevalence of walking difficulties among different age groups. Individuals aged 75-84 show the highest prevalence in all categories of walking difficulties, with particular significance in the categories of "no difficulty," "some difficulty," and "unable to walk at all" (p < 0.001). Higher levels of education generally correlate with lower prevalence of walking difficulties. Married or partnered individuals have 0.522 times lower odds of reporting difficulties in walking compared to singles (p < 0.05). Individuals with lower wealth index (1-Least affluent) have significantly higher prevalence of walking difficulties.This knowledge can inform targeted interventions to enhance mobility and improve the overall well-being of older individuals.

The commercialization of historic streets constitutes a pivotal aspect of urban cultural heritage, and the comprehension of their visual perception serves as a valuable asset to urban planning and cultural conservation efforts. However, current research concerning the disparities in visual perception among diverse demographics within historic streets, as well as their spatiotemporal dynamics, remains insufficient. This study aims to utilize mobile eye-tracking technology to delve deeply into the visual perception characteristics of diverse demographics within commercialized historic streets, while also analyzing their spatiotemporal dynamics. We explore the disparities in visual perception of historic streets among groups with varying degrees of architectural knowledge and professional literacy. Through meticulous observation using mobile eye-tracking technology, we elucidate the visual perception patterns of different demographic characteristics through statistical analysis and spatiotemporal modeling. The findings reveal significant discrepancies in visual attention and perception among various groups. Participants with a higher understanding of architecture tend to focus more on architectural details and structures within the streetscape compared to those with a lower understanding, who exhibit greater interest in elements such as shops and signage. Moreover, during the process of perceiving the streetscape, participants’ eye movements transition from surrounding landscapes and historical edifices upon initial entry to the district, gradually shifting towards the commercial activities and distinctive architecture within the district. This study delves deeply into the visual perception characteristics and spatiotemporal dynamics of commercialized historic streets, providing invaluable insights for urban planning and cultural preservation endeavors. By revealing the impact of different demographic characteristics on the visual perception of historic streets, it offers new insights for urban planning and cultural heritage conservation.

Abstract: Spinal disorders are some of the most prevalent health concerns, especially among stu-dents. Based on student demographics, this cross-sectional study evaluated the correlation be-tween functional tests (FT) and spinal range of motion (ROM). This study included 206 students from Vasile Alecsandri University of Bacău. Participants' assessments were conducted using the following tests: (i) Ott, (ii) Schober, (iii) Stibor, (iv) finger-to-floor distance, (v) lateral flexion of the cervical and lumbar spine, and (vi) flexion of the cervical spine. Correlation analyses were evaluated using Spearman correlation coefficient analysis. The results indicated a very strong re-lationship between lateral flexion of the lumbar spine on the left (LFLSL) and right (LFSR) for all departments (r = 0.85 to 0.97, p < 0.05). There was a stronger relationship between FT results and spinal ROM of physical education department students compared to students from other de-partments (n = 17, r = -0.38 to 0.93, p < 0.05). There was no statistically significant correlation be-tween FT and spinal ROM based on age (p > 0.05). The study results provide evidence of the pri-mary risk factors that predispose students to postural deviations. Practitioners and physiothera-pists can utilize these values as a reference for potential therapeutic interventions.

Microvascular complications are one of the key causes of mortality among type-2 diabetic patients. This study was sought to investigate the use of a novel machine learning approach for predicting these complications from patient demographic, clinical, and laboratory profiles only. A total of 96 Bangladeshi participants having type-2 diabetes were recruited during their routine hospital visits. All patient profiles were assessed by using a Chi-squared (2) test to statistically determine the most important markers in predicting four microvascular complications; namely cardiac autonomic neuropathy (CAN), diabetic peripheral neuropathy (DPN), diabetic nephropathy (NEP), and diabetic retinopathy (RET). A machine learning approach based on random forest (RF) and support vector machine (SVM) was then developed to ensure automated clinical testing for microvascular complication in diabetic patients. The highest prediction accuracies were obtained by RF using diastolic blood pressure, Albumin-Creatinine ratio, and gender for CAN testing (98.67%), Microalbuminuria, smoking history, and hemoglobin A1C for DPN testing (67.78%), Albumin-Creatinine ratio for NEP testing (100%), and hemoglobin A1C, Microalbuminuria, and smoking history for RET testing (84.38%). This study suggests machine learning as a promising automated tool for predicting microvascular complications in diabetic patients using their profiles, which could help prvent those patients from further microvascular complications leading to early death.

The study investigated determinants of open defecation among rural women in Ghana. The study extracted data from the female’s file of the 2003, 2008 and 2014 Ghana Demographic and Health Survey (GDHS). A total of 4,284 pooled sample size of rural women aged 15-49 with complete information about the variables analyzed in the study. The outcome variable was “open defecation” (i.e., defecating in an open space rather than a toilet facility) whilst fourteen (14) key explanatory variables were used. Two regression models were built, and output reported in odds ratio. Descriptively, 42 in every 100 women aged 15-49 practised open defecation (n=1811, 95’CI=49-52). Open defecation significantly correlated with educational attainment, wealth status, religion, access to mass media, partner's education, and zone of residence. The likelihood to practice open defecation reduced among those with formal education [aOR=0.69, CI=0.56-0.85], those whose partners had formal education [aOR=0.64, CI=0.52-0.80], women in the rich wealth quintile [aOR=0.12, CI=0.07-0.20], the traditionalist [aOR=0.33, CI=0.19-0.57], and those who had access to mass media [aOR=0.70, CI=0.57-0.85]. Residents in the Savannah zone were over 21-fold higher to defecate openly [aOR=21.06, CI=15.97-27.77]. The prevalence of open defecation is disproportionately pro-poor indicating that impoverished rural women are more likely to perform it.

After approximately 6 months of age, term breastfed infants are increasingly depending on other sources of iron to avoid iron deficiency anemia. The appropriate complementary feeding must include a balance composition of foods containing an adequate amount of macro- and micronutrients to reduce the risk of iron deficiency anemia. This study aims to compare the anemia and growth status of infants receiving commercial fortified infant cereals (FIC) with infants not receiving them. We use all complete multiple Demographic Health Surveys (DHS) from 2005 to 2018 to understand global infant feeding patterns. To better control for the strong household wealth effect in nutritional choices and possibly health awareness, we use propensity score technique as applied in outcome research to better control the effect of covariates. After matching and controlling for confounders, we did find a significant association between reduced risk of anemia and consumption of FIC. After matching and adjusting for confounders the small but positive effects of consumption of FIC on Height for age z-score and Weight for Height Z-score are no longer statistically significant.

Using a theorem of Ulam and Hyers, we will prove the Hyers-Ulam stability of two-dimensional Lagrange's mean value points $(\eta, \xi)$ which satisfy the equation, $f(u, v) - f(p, q) = (u-p) f_x(\eta, \xi) + (v-q) f_y(\eta, \xi)$, where $(p, q)$ and $(u, v)$ are distinct points in the plane. Moreover, we introduce an efficient algorithm for applying our main result in practical use.

We investigated 328 SARS-CoV-2 cases in Barwon South West Victoria, Australia, in the 2020 pre-vaccination period, comparing infections with symptoms to those that remained asymptomatic. De-identified self-reported data from three sequential questionnaires on case characteristics and symptom progression were examined. Multivariable logistic regression were used to model associations between demographic profile and symptoms. Asymptomatic cases were more than three times as likely to be from ethnic minority groups [OR 3.2, 95% CI 1.5 – 6.7, p&lt;0.01], and approximately seven times more likely to be seniors (≥ 65 years) [OR 7.3, 95% CI 1.0 – 50.1] after adjusting for sex and occupation. The overrepresentation of ethnic minority groups among asymptomatic infections is suggestive of genetic haplotype variability by ethnic group, conferring greater cross protection from other coronaviruses in the early stages of the COVID-19 pandemic. This research should be repeated post-vaccination to reassess symptom expression according to ethnicity, and better comprehend case ascertainment impacts of cultural biases in testing and infection reporting, and the reliance on symptoms to trigger testing. These findings may in part reflect differences in testing patterns by ethnicity and true differences in disease expression, both important for appropriate transmission prevention strategies, and tailoring testing messaging towards ethnic minority communities.

Prionace glauca, blue shark is a cosmopolitan species. Together with Carcharhinus falciformis, it co-dominated the landings of carcharhinidae sharks at the Artisanal Fishing Port of Cotonou. The objective of this study is to determine the demographic parameters of the blue shark in Gulf of Guinea marine waters. The different routines of the FISAT II v 1.2 software associated with the empirical equations of Froese and Nohland, allowed the evaluation of the different demographic parameters of the blue shark in Benin's marine waters. From August to December 2015, 244 individuals shark sizes; ranging from 175cm to 325cm were sampled. The total asymptotic length obtained was 341.25cm with a growth rate of 0.35/year, which indicates that the species is growing rapidly and the optimal total length of the species is 232.01cm. The age of first maturity of the species is 3 years with a longevity of 10 years. The exploitation rate is E= 0.74 with total mortality being 2.4; natural mortality is 0.6 and fishing mortality is 1.8. The sex ratio remains in favour of males throughout the study period. Monitoring programme were suggested with effective management measures established and executed for sustainability of the blue shark’s stock in the Gulf of Guinea.

BACKGROUND G6PD deficiency is an inherited an X-linked recessive condition leading to insufficient levels of glucose-6-phosphate dehydrogenase, thus causing hemolytic anaemia under certain conditions. METHODS Our study is explorative for cases admitted to Jordan University Hospital. The studied parameters include demographics, clinical manifestations, biochemical markers including Hb level, WBC count, liver enzymes, and blood grouping. RESULTS Most of the patients were admitted to the emergency unit (53.13%). Individuals who were Rh-positive represented 57.81%, while patients of AB blood group accounted for 75%. The mean values were 4.81 years (age), 29.06 hours (time-to-hospital admission), 38.10 degree Celsius (temperature), 6.11 gm/dl (Hb), 13242.19 (WBC count), 343.20 U/L (S. ALP), and 50.98 IU/L (S. ALT). There was no significant difference between males and females or between favism-induced versus drug-induced hemolytic episodes. AB and Rh positive blood groups are of protective effect in relation to liver enzymes. Patients who were admitted to the hospital within 24 hours from having clinical manifestations had a better prognosis. CONCLUSION This study is the first inferential research on G6PD deficiency from the Middle East to explore cases from one of the largest healthcare centres in Jordan. The role of blood grouping should be investigated prospectively.

This research investigates the application of Fused Filament Fabrication (FFF) in producing WC-10Co hardmetals, focusing binder formulations and understanding its influence on extrusion force and the influence of printing variables on green density of the samples. By examining the interplay between different binder compositions and backbone contents, the study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggested that formulated feedstocks influenced the hardness of the sintered hardmetal, not due to microstructural changes but to macrostructural responses like macro defects introduced during printing, debinding and sintering of the samples. The results demonstrate the critical role of PP-MA content in improving part density and sintered hardness, suggesting the need for specific thermal debinding protocols tailored to each feedstock. The study provides insights into the formulation of feedstocks for hardmetal FFF, proposing a path toward refining manufacturing processes for better quality and performance of 3D printed hardmetal components.

Conifer bark beetles (Coleoptera: Curculionidae: Scolytinae) are major agents of natural disturbance in temperate forests of the northern hemisphere, capable of killing billions of trees in native forests. The dynamics of these insect populations are influenced by climatic variability. To understand such a relationship, it is necessary to monitor the population fluctuation of the species present over time. In this regard, the objective of the present study was to determine the species community of the genus Dendroctonus, the population fluctuation throughout the months of the year, and the effects of relative humidity, temperature, and precipitation on the fluctuation, at three sites of mixed forests in the Municipality of Bocoyna, Chihuahua, in northern Mexico. For insect monitoring, we used Lindgren funnel traps (with 8 funnels each) baited with semiochemicals. Every two weeks, and during 2 years, we collected, identified, and counted the insects. The identification of the species was based on the external morphology and characteristics of the male seminal rod. Temperature and relative humidity were measured using climate data loggers (HOBOs). We found six Dendroctonus species. We also determined the population fluctuation patterns of D. mexicanus Hopkins, D. frontalis Zimmermann, and D. brevicomis LeConte, species with the highest number of captures at each site. Additionally, the relationship between species abundance and climatic variables was determined. The variable that significantly influenced (P&lt;0.05) abundance was temperature. Relative humidity and precipitation variables did not show a significant relationship (P&gt;0.05).

With the intensification of population aging in rural areas, it becomes increasingly important to analyze the post-retirement migration intention of rural residents and the variables influencing these intentions. In this study, we focus on rural residents aged 45 to 60 and investigate the main variables that influence the post-retirement migration intention of rural residents, using survey data collected from 164 households in three different rural areas and the logistic regression model. From the result of this study, we found that gender, part-time employment, savings level, children's residence and occupation stability, and interest in urban living positively affect migration intention. In contrast, the number of rural companions, relationships with others in rural areas, and evaluation of rural living have a negative effect. In addition, we employ age and the proportion of mobile income as control variables to examine the variables that influence the post-retirement migration intention in different age groups and mobile income groups. The analysis reveals that, the variables influencing post-retirement migration intention varied across age groups and mobile income groups, and this variation can be attributed to the differences between groups' characteristics.

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machine and Random Forest, are compared with Multivariate Linear Regression, TVX and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using four different statistics on a daily basis allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest with residual kriging produces the best results (R$^2$=0.612 $\pm$ 0.019, NSE=0.578 $\pm$ 0.025, RMSE=1.068 $\pm$ 0.027, PBIAS=-0.172 $\pm$ 0.046), whereas TVX produces the least accurate results. The environmental conditions in the study area are not really suited to TVX, moreover this method only takes into account satellite data. On the other hand, regression methods (Support Vector Machine, Random Forest and Multivariate Linear Regression) use several parameters that are easily calculated from a Digital Elevation Model, adding very little difficulty to the use of satellite data alone. The most important variables in the Random Forest Model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day.

Associating the most influential parameters with the product distribution is of uttermost importance in complex catalytic processes such as fluid catalytic cracking (FCC). These correlations can lead to the information-driven catalyst screening, kinetic modeling and reactor design. In this work, a dataset of 104 uncorrelated experiments, with 64 variables, has been obtained in an FCC simulator using 6 types of feedstock (vacuum gasoil, polyethylene pyrolysis waxes, scrap tire pyrolysis oil, dissolved polyethylene and blends of the previous), 36 possible sets of conditions (varying contact time, temperature and catalyst/oil ratio) and 3 industrial catalysts. Principal component analysis (PCA) has been applied over the dataset, showing that the main components are associated with feed composition (27.41% variance); operational conditions (19.09%) and catalyst properties (12.72%). The variables of each component have been correlated with the indexes and yields of the products: conversion, octane number, aromatics, olefins (propylene) or coke, among others.

The critical changes in physical appearance during adolescence can considerably influence the self-appraisal of body image. The purpose of this study is to analyze body self-image gender differences in Mediterranean adolescents, and his relationships to the anthropometric characteristics of this population in different phases of the adolescence. Participants were 809 Mediterranean teenagers (396 females) aged 11 to 17. A relative low prevalence of dissatisfaction with body image was observed among healthy urban Mediterranean adolescents (boys 17.3%; girls 22.7%). Girls showed statistically significantly higher mean BSQ scores than boys (M = 61.7, SD = 26.6 versus M = 56.3, SD = 27.1; p < 0.001). Girls in the late adolescence were more often classified as being dissatisfied (31%) in comparison to those in the early adolescent group (19.1%; p < 0.05). There was a good correlation of BSQ scores with all the anthropometric variables in males but not in females.

Introduction: Over decades, much have been said and done regarding under-five mortality in Ethiopia. The country has been following the lead of sustainable development goals and UNICEF with its transformation plan targets. However, unless the efforts supported by status assessing studies, it might be difficult for the country to progress. Thus, the current study was directed to identify the prevalence and associated factors of under-five mortality in 2019. Methods: According to the study criteria, we extract and cleaned data in STATA v. 15.0. The data then weighted as per the sampling weight, primary sampling unit, and strata before analyzing in STATA 15.0. Data management consisted of descriptive (mean, standard deviation, and proportion or percent) and association statistics. We deliberated binary logistic regression for this analysis and we checked each variable at 0.25 p-values to include in the model. The final p-value to declare association was p <0.05 and AOR with 95% CI was also applied to describe the results. The data source was the Ethiopian Mini Demographic Health Survey (EMDHS) 2019. EMDHS collected the data from 8,885 in a face-to-face manner with a 99% response rate. Results: From 5,527 numbers of weighted women with under-five analysed in this study, the proportion of under-five mortality was 277.23(5.02%). Factors like 2nd birth order 0.52(0.35, 0.79), 3rd-4th 0.49(0.28, 0.84), 1-2 ANC visits 0.24(0.12, 0.49, ANC visit three’ 0.14(0.07, 0.28), ANC visit four and above 0.22(0.14, 0.36), in marriage mother 0.43(0.19, 0.96), ‘1-2 under-five children 0.02(0.011, 0.03), and greater than three under-five children 0.007(0.0007, 0.004) were all negatively associated with under-five mortality rate. Conclusion: To obtain the exalted outcome out of this study, the government might need to increase antenatal care, women education, institutional delivery, and the modern contraceptive methods use through enhanced community mobilization, health education using community health workers, increasing access to essential cares of mothers and children, and the policy commitment for the issues related to family size, birth order, and birth interval.

Access to healthcare services is an essential component of promoting public health and sustainable development. Our aim was to assess socio-demographic correlates of barriers to access healthcare services among children in Albania, a post-communist country in Europe. An online survey was conducted in September 2022, including a nationwide representative sample of 7831 schoolchildren (≈54% girls) pertinent to grades 6-9 from all regions of Albania. A structured and anonymous questionnaire was administered to all children inquiring about a range of potential barriers to access healthcare services. Overall, about 42% of the children reported that they had barriers to access healthcare services. There were no gender differences, but significant: ethnic differences (51% among Roma/Egyptian children vs. 42% among the general sample of the children); urban/rural differences (46% rural vs. 39% urban); and socioeconomic differences (52% among children with a lower maternal education vs. 31% among children with a higher maternal education; 66% among children from poor families vs. 35% among children with a higher family income). In transitional Albania, children residing in rural areas, children from Roma and/or Egyptian communities and especially those pertinent to low socioeconomic families report considerably more barriers to access healthcare services, which is a cause of concern.

he Grassmann variables are used to formally transform a system with constraints into an unconstraint system. As a result, the Schr\"{o}dinger equation arises instead of the Wheeler-DeWitt one. The Schrodinger equation describes a system's evolution, but a definition of the scalar product is needed to calculate the mean values of the operators. We suggest an explicit formula for the scalar product related to the Klein-Gordon scalar product. The calculation of the mean values is compared with an etalon method, in which a redundant degree of freedom is excluded. Nevertheless, we could note that a complete correspondence with the etalon picture is not found. Apparently, the picture with the Grassmann variables requires a further understanding of the underlying Hilbert space.

Noisy data is always encountered in real applications, such as bioinformatics, neuroimage and remote sensing. Existing methods mainly consider linear or generalized linear errors-in-variables regression, while relatively little attention is paid for the multivariate response case, and how to evaluate the estimation performance under perturbed covariates is still an open question. In this paper, we consider the information-theoretic limitations of estimating a low-rank matrix in the multi-response errors-in-variables regression model. By application of the information theory and statistical techniques on concentration inequalities, the minimax lower bound is provided in terms of the squared Frobenius loss, which recaptures the rate provided under the clean covariate assumption in previous literatures. Hence our result further indicates that though under the more realistic errors-in-variables situation, no more samples are required so as to achieve a rate-optimal estimation.

In this study, we investigate the performance of the saddlepoint approximation of the probability mass function and the cumulative distribution function for the weighted sum of independent Poisson random variables. The goal is to approximate the hazard rate function for this complicated model. The better performance of this method is shown by numerical simulations and comparison with a performance of other approximation methods.

The work is devoted to the study of a family of linear initial value problems of partial differential equations in the complex domain, dealing with two complex time variables. The use of a truncated Laplace-like transformation in the construction of the analytic solution allows to overcome a small divisor phenomenon arising from the geometry of the problem and represents an alternative approach to the one proposed in a recent work by the first two authors. The result leans on the application of a fixed point argument and the classical Ramis-Sibuya theorem.

Soil conditions is a major aspect of interest for farmers due to the knowing of the physicochemical properties of the same can help with any necessary restoration of soil that guarantees the quality and the production of their crop. However, technology and analysis of the soil become of difficult access mainly in developing countries, by which the present paper shows the development of a system thought to estimate physicochemical variables of soils growing sugar cane through studies of spectroscopy. Its characteristic is that it is a portable system, with low cost, easy to use and can estimate physicochemical variables in-situ with the objective of knowing the degree of degradation present in the soil and through this help the farmers define possible strategies to restore it. The device uses the frequency response of the soil determining values of magnitude and phase, which are used by algorithms of artificial intelligence capable of getting an estimation of the physicochemical properties. The obtained results show errors below 8% in the estimation of the variables compared to the analysis results of the soil at laboratories.

This article objective was to identify a centenary trend in the growth and development of girls in the metropolis of Moscow. Material and methods — The physical development (body length and weight, chest circumference, right hand muscle strength, and menstrual function development) of Moscow girls was studied during the period from 1920 to 2020. The amount of own observations was 4581 girls aged 8-17 years. Results – A comparative analysis of the physical development of Moscow school girls of different decades revealed a statistically significant increase in body length by 3-5 cm and a significant increase in chest circumference in all age groups of girls of the beginning of the XXI century, compared with their peers in the 1960s and 1980s, which indicates the completion of the gracialization processes that have been observed since the 1980s. However, in all age groups, a decrease in the muscle strength of the right hand is still being noticed. Earlier terms of menarshe onset in modern Moscow school girls (12 years 9 months) and a shift in growth jumps to earlier terms were established. It is shown that the age of menstruation depends on the level of family wealth. Conclusions. In Moscow girls in the centenary dynamics, a tendency to increase the total body size and shift the terms of biological maturation to earlier terms was revealed.

Sample size using prevalence has been one of the most important medical research methodologies and has been used in original articles more often than any other statistical tool available. The simple formula consists of variables interdependent and it is as important to understand how they influence each other as it is to learn to use the formula to calculate the sample size. With the choice of different amounts of precision and levels of confidence available to a medical researcher, it should be of paramount importance to understand what a slight change in choosing the parameter would mean at the end of the research. Understanding of different Z values, Levels of precision, and ranging Prevalence is required to understand the effect on the sample size and subsequently on the research. Topological representation using parameter ranges can be used to demonstrate this relationship.

contaminated sites located in each school district. Previous studies showed that various environmental factors, such as exposure to toxic substances negatively impacts human health depending on their concentration and occurrence. Therefore, the study aims to use Geographical Information System (GIS) technology and secondary data on IEP numbers of each school district, chemical occurrence in contaminated sites, and demographic data to conduct a correlational analysis. The secondary data obtained from school districts and contaminated sites from Iowa Department of Natural Resources Facility Explorer were populated in ArcMap 10.5 (a GIS software) for generating maps and data to conduct statistical analysis. The contaminants were categorized into metals, polyaromatic hydrocarbons (PAH), and solvents with weighing factors as 1, 0.5, and 0.25. A total of 1 Superfund site and 39 CERCLA sites were identified as contaminated sites for this study. The majority of contaminants were heavy metals such as lead, arsenic, mercury, and cadmium. The mean toxic score of all contaminated sites combined was 13.4 (sd 14.4). The correlational analysis between the IEP numbers from each school districts and toxic scores from the contaminated sites was positive indicting that increased toxic score increased the number of students enrolled in the IEP program (F=23.7, p<0.0001). The correlational analysis between toxic score and demographics indicated some interesting results. Children under the age of 10 were living in areas with high toxic score and the showed mild correlation (p<0.00052). Similarly, higher number of black population resided in areas with high toxic score (p=0.0032) than the white population (p<0.0001). The result also indicated that children enrolled in IEP were predominantly among the black population (p<0.0001). The correlational analysis between household income and poverty percentage of people residing near the contaminated area indicated that people had low average household income (p=0.0002) and high poverty percentage (p=0.0203) residing in areas with higher toxic score. Regarding the educational status, less number of people with post graduate degree (p<0.0001) resided in areas with high toxic score and more number of people with no degree (p<0.0001) resided in areas with high toxic score. Finally, the study showed the increasing trend of eligible children enrolling in free and reduced lunch programs with increasing toxic scores (p=0.0012) and IEP levels (p=0.0416). This study emphasize on developing multiple exposure to correlate environmental factors contributing to the negative health outcome on people.

Social and academic integration variables have shown to be relevant for the understanding of university dropout. However, there is less evidence regarding the influence of these variables on dropout intention, as well as predictive models that explain their relationships. Improvements in this topic become relevant considering that dropout intention stands as a useful measure to anticipate and intervene on this phenomenon. The objective of the present study was to evaluate a predictive model for the university dropout intention that considers the relationships between social and academic variables, during the first university semester of 2020. The research was carried out using a cross-sectional associative-predictive design, with a convenience sampling (n=711) due the restrictions of pandemic period. The results showed a good fit of the proposed hypothetical model that explains 38.7% of dropout intention. Both social support and perceived social isolation predicted the sense of belonging, and through it, engagement. Previous academic performance predicted early academic performance, and through it, engagement. The set of variables predicted the intention to quit, through engagement. These results are a contribution both to the understanding of the phenomenon and to guide potential interventions in the early stages of the university experience.

Background: Pre-pregnancy overweight and obesity of women of childbearing ages, has alarmingly a growing trend in developed countries. This study aimed to evaluate potential associations between maternal pre-pregnancy excess body weight and childhood demographic and anthropometric characteristics, as well as perinatal and postnatal outcomes. Methods: This is a cross-sectional study conducted on 5198 pre-school children aged 2-5 years old and their matched mothers that were enrolled from nine different Greek regions. Maternal and childhood anthropometric and demographic data, perinatal and postnatal outcomes were collected from medical history records or validated questionnaires. Results: A prevalence of 24.4% and 30.6% of overweight/obesity was recorded for the enrolled children and their mothers 2-5 years postpartum. In multivariate analysis, childhood overweight and obesity was significantly more frequently observed when maternal pre-pregnancy BMI status was overweight or obese [OR: 2.11 (1.80-2.42) p=0.0001]. A high prevalence of caesarean section delivery and childhood diabetes type I was also significantly associated with maternal pre-pregnancy overweight/obesity [OR:1.71 (1.33-2.19) p=0.0175) and OR: 1.27 (1.04-1.53) p=0.0014, respectively]. Conclusions: Maternal pre-pregnancy overweight and obesity rates were related with increased childhood weight status at birth and 2-5 years postpartum, highlighting the necessity of encouraging healthy lifestyle promotion, including healthier nutritional habits, and focusing on obesity population policies and nutritional interventions among women of reproducible age.

The aims of this study were: (1) to analyze the level of agreement of a sample of Italian people with the rights of people with physical and psychical disabilities (PwPHDs and PwPSYDs) to have satisfying sexuality, to marry, to adopt a child; (2) to inquire if PwPSYDs were subject to less recognition than PwPHDs; (3) to verify if socio-demographic characteristics, such as age, sex, education, occupation, geographical origin, relational status, sexual orientation, and religiosity, associated with being against these sexual and parenting rights (SPRs). An online anonymous questionnaire inquired the level of agreement or disagreement with statements regarding the SPRs of PwPHDs and PwPSYDs. 973 participants, aged 18 – 84 years (71.1% females) were considered for analyses; At least 7 out of 10 participants declared in favor of the SPRs of PwPHDs, while the SPRs of PwPSYDs were always subjected to higher underrecognition. Religiosity almost invariably associated to being against the SPRs of PwDs. Being male, of higher age and lower education also associated with lower recognition. A better identification of the less tolerant respondents and of the less recognized categories may allow for specific strategies for promoting the recognition of the SPRs for PwDs.

Background: Poisoning constitutes an important part of morbidity and mortality among environmental emergencies that can be prevented, frequent in childhood, requiring rapid diagnosis and treatment. This study aimed was to examine the epidemiological, clinical and therapeutic characteristics of drug and corrosive poisonings in terms of children. Materials and Methods: Between January 2010 and December 2018, 1678 patients between the ages of 1-16 who applied to the emergency department with drug and corrosive poisoning were included in the study. The patients were divided into three groups as 1-5, 6-11 and over 12 years of age, and the substances with known pharmacological agents were divided into 10 groups. The Zargar Classification (7) was used to determine the degree of damage caused by corrosive substances in the esophagus. Results: The mean age of the patients was 8.32 ± 3.23 years (1-15 years). The girl/boy ratio of the cases was 1.18 / 1 and 54.3% were girls. 18.9% of the cases were under five years of age, 61% were between 6-11 years and 20% were older than 12 years. 94.6% of the patients were poisoned by drugs and 5.4% of them were poisoned due to non-drug reasons. Accidental poisoning was most commonly seen in children aged 6-11 and suicides were seen in children older than 12 years. It was found that 62.2% of the poisonings were accidental and 37.8% were suicidal. The most common causes of poisoning were analgesics and paracetamol exposure as a pharmacological agent. Mortality was found to be most common in 1-5 years age group and accidental poisonings. Accidental poisoning was common in girls and suicidal poisoning was common in boys. Grade 3 damage was found endoscopically in all of the mortalities due to corrosive substances. Conclusion: It was found that accidental poisoning was observed in children under five years of age, suicides were observed in children older than 12 years and the most important cause of mortality was due to corrosive substances. Cause-specific rapid diagnosis and treatment will contribute to the reduction of morbidity and mortality.

In many previous studies, the conclusions for the effects of disturbance and environmental gradients on the diversity was remain controversial due to exclusions of trait-based diversity in their methodology. This study hypothesized trait-based indices are more likely to show monotonic and predictable relations than traditional based species diversity to guide effective restoration of tree species diversity against environmental change and anthropogenic factors. This study therefore, was initiated to access trait based functional diversity of Yayu Coffee Forest Biosphere Reserve (YCFBR), Southwest Ethiopia. Data was collected from 90 proportionally distributed plots along disturbance levels from core, buffer and transitional zones. For functional trait diversity estimation, traits relevant to plant-life strategy, competition and response to disturbances and climate change were selected. Multiple regression model was used to test the response of species diversity and functional diversity to disturbance and environmental gradients. The result revealed that, anthropogenic disturbance and elevational gradients are the most important factors influencing functional diversity in the YCFBR. Overall this study demonstrates that, trait based functional diversity is useful to predict adaptation potentials of species in heterogeneous environments. Species with low specific leaf area &amp; selective seed mass is recommended for the restoration of disturbed ecosystem.

Multiple myeloma (MM) is an incurable hematological cancer. It is preceded by monoclonal gammopathy of uncertain significance (MGUS), an asymptomatic phase. It has been demonstrated that early detection increases the 5-year survival rate. However, blood-based biomarkers that enable early disease detection are lacking. Metabolomic and lipoprotein subfraction variable profiling is gaining traction to expand our understanding of disease states and, more specifically, for identifying diagnostic markers in patients with hematological cancers. This study aims to enhance our understanding of multiple myeloma (MM) and identify candidate metabolites, allowing for more effective preventative treatment. Serum was collected from 25 healthy controls, 20 patients with MGUS, and 30 patients with MM. 1H-NMR (nuclear magnetic resonance) spectroscopy was utilized to evaluate serum samples. The metabolite concentrations were examined using multivariate, univariate, and pathway analysis. Metabolic profiles of the MGUS patients revealed lower levels of alanine (F.C. = 0.8, p = 0.002), lysine (FC = 0.8, p &lt; 0.001), leucine (FC=0.7, p &lt; 0.001) but higher levels of formic acid (FC=1.6, p ≤ 0.001) when compared to controls. However, metabolic profiling of MM patients compared to controls exhibited decreased levels of total Apolipoprotein-A1 (FC =0.6, p&lt;0.001), HDL-4 Apolipoprotein-A1 (FC = 0.5, p ≤ 0.001), HDL-4 Apolipoprotein-A2 (FC = 0.6, p &lt; 0.001), HDL Free Cholesterol (FC = 0.7, p &lt; 0.001), HDL-3 Cholesterol (FC = 0.5, p ≤ 0.001) and HDL-4 Cholesterol (FC = 0.5, p ≤ 0.001). Lastly, metabolic comparison between MGUS to MM patients primarily indicated alterations in lipoproteins levels: Total Cholesterol (FC = 0.6, p ≤ 0.001), HDL Cholesterol (FC = 0.7, p ≤ 0.001), HDL Free Cholesterol (FC = 0.4, p ≤ 0.001), Total Apolipoprotein-A1 (FC = 0.7, p ≤ 0.001), HDL Apolipoprotein-A1 (FC = 0.7, p ≤ 0.001), HDL-4 Apolipoprotein-A1 (FC = 0.6, p ≤ 0.001) and HDL-4 Phospholipids (FC = 0.6, p ≤ 0.001). This study provides novel insights into the serum metabolic and lipoprotein subfraction changes in patients as they progress from a healthy state to MGUS to MM, which may allow for earlier clinical detection and treatment.

This study explores the relationship between job satisfaction, employee loyalty and two types of flexible employment arrangements; teleworking and flexi-time. The analysis relies on data derived by the Workplace Employee Relations Survey (WERS) in 2004 and 2011. A propensity score matching and least squares regressions are applied. Furthermore, Bayesian Networks (BN) and Directed Acyclic Graphs (DAGs) are employed in order to confirm the causality between employment types explored and the outcomes of interest. Finally, an instrumental variables (IV) approach based on the BN framework is proposed and applied in this study. The results support that there is a positive causal effect from these employment arrangements on job satisfaction and employee loyalty.

The paper's main goal is to introduce a novel type of interpolative convex contraction and build up some fresh findings for it using the interpolative convex contractions' progressive approach. We have established certain conclusions using orbitally S-complete and Suzuki type contractions in F-metric spaces. My research aims to examine the fixed point method's efficacy in solving fractional differential equation with boundary conditions.

This paper examines how housing prices are determined by macroeconomic factors in Saudi Arabia, namely, Gross Domestic Product Per capita (GDPP), Consumer Prices Index (CPI), and Unemployment Rate (UNEMP). Quarterly data for a period (2014q1 – 2019q4) were collected from publications of Saudi Arabian Monetary Authority (SAMA). Vector Autoregression Analysis (VAR) is employed to capture the dynamic effect of the variables on housing prices. Granger Causality, Variance Decomposition and Impulse response function are also used. The results show that housing prices are insignificantly and positively related to GDPP, whereas it is negatively related to both (CPI & UNEMP). Only CPI has a significant relationship. The three variables, jointly, have Granger causality on HPI. Variance decompositions show that CPI is the variable with the highest explanatory power over the variation of housing prices, followed by GDPP and the UNEMP respectively indicating that CPI is the most influential determinants for housing prices.

Soil hydraulic properties are often derived indirectly, i.e. computed from easily available soil properties with pedotransfer functions (PTFs), when those are needed for catchment, regional or continental scale applications. When predicted soil hydraulic parameters are used for the modelling of the state and flux of water in soils, uncertainty of the computed values can provide more detailed information when drawing conclusions. The aim of this study was to update the previously published European PTFs (Tóth et al., 2015, euptf v1.4.0) by providing prediction uncertainty calculation built into the transfer functions. The new set of algorithms was derived for point predictions of soil water content at saturation (0 cm matric potential head), field capacity (both -100 and -330 cm matric potential head), wilting point (-15.000 cm matric potential head), plant available water, and saturated hydraulic conductivity, as well as the Mualem-van Genuchten model parameters of the moisture retention and hydraulic conductivity curve. The minimum set of input properties for the prediction is soil depth and sand, silt and clay content. The effect of including additional information like soil organic carbon content, bulk density, calcium carbonate content, pH and cation exchange capacity were extensively analysed. The PTFs were derived adopting the random forest method. The advantage of the new PTFs is that they i) provide information about prediction uncertainty, ii) are significantly more accurate than the euptfv1, iii) can be applied for more predictor variable combinations than the euptfv1, 32 instead of 5, and iv) are now also derived for the prediction of water content at -100 cm matric potential head and plant available water content.

Drug delivery through Liposomes has shown tremendous potential in terms of the therapeutic application of nanoparticles. There are several drug-loaded liposomal formulations approved for clinical use that help mitigate harmful effects of life-threatening diseases. Developments in the field of liposomal formulations and drug delivery have made it possible for clinicians and researchers to find therapeutic solutions for complicated medical conditions. A key aspect in the development of drug-loaded liposomes is a careful review of optimization techniques to improve the overall formulation stability and efficacy. Optimization studies help in improving/modulating the various properties of drug-loaded liposomes and are vital for the development of this class of delivery systems. A comprehensive overview of the various process variables and factors involved in the optimization of drug-loaded liposomes is presented in this review. The influence of different independent variables on drug release and loading properties with the application of a statistical experimental design is also explained in this article.

Human disturbances can have severe environmental impacts on freshwater ecosystems. The main aim of this study was to detect the influences of physiochemical variables, land-cover characteristics, and river connectivity on fish assemblages in Lake Chaohu Basin, China. A cluster analysis of the river connectivity variables identified four groups of sites that characterized by significantly different connectivity gradients in local scale. These four groups of sites showed increasing connectivity from the upper reaches to the lower reaches. At the same time, among the four groups, the values of the environmental variables generally increased from the upper reaches with less human activity towards the lower reaches with more human activities. For instance, some main physiochemical variables (e.g., river width, water depth, nitrate, phosphate) significantly increased among the four groups. In contrast, fish taxa richness and diversity indices were not significantly different among the four connectivity groups. However, fish assemblages showed significant variation among the connectivity groups (p=0.026). In addition, the study determined that upper riparian land uses (e.g., woodland and grassland), flow velocity, and elevation were environmental variables regulating the variance in the fish communities, and for the connectivity variables, only river order and number of branches along a path to the left of the main stem affected the variance in the fish communities. Therefore, new practices aimed at maintaining and even increasing the riparian canopy coverage and the flow velocity of rivers should be integrated into local conservation planning for freshwater ecosystems, especially in the upper reaches of the basin.

Abstract: Background: Of the many side effects suffered by cancer patients, those related to cognitive performance have become increasingly prominent in clinical practice. We know that chemotherapy generates a series of side effects, such as nausea and vomiting, alopecia, and so on, which can be counteracted by complementary medication. However, in the case of post-chemotherapy cognitive impairment, or chemo brain, these cannot be controlled with drug therapies. However, before any intervention can be considered, it is necessary to know exactly what cognitive impairment is being triggered. For this reason, we decided to study the cognitive status of breast cancer patients. Methods: analytical, prospective, three-measure longitudinal, intrasubject unifactorial, non-probabilistic and accidental assignment study. The sample came from the Medical Oncology Department at Hospital de Salamanca, in Spain. Cognitive function (Trail Making Test and Stroop Test) was established as the primary variable; the presence of sleep disorders (Insomnia Severity Index, ISI) and anaemia (haemoglobin levels in blood) were analysed as secondary variables, in addition to sociodemographic variables (age, stage, type of carcinoma, radiotherapy, menopause, social support network, marital status, years of schooling and employment status). Results: We recruited 151 individuals according to the selection criteria. We can confirm that factors including anaemia, menopause, patient support network and marital status, years of schooling, and employment status did affect the cognitive performance of the patients in active chemotherapy treatment in the study. In contrast, sleep disorders, age, radiotherapy treatment, stage of disease, and type of carcinoma did not affect the cognitive performance of the cancer patients. Conclusions: Chemotherapy does impact the cognitive performance of breast cancer patients.

Background: Of the many side effects suffered by cancer patients, those related to cognitive performance have become increasingly prominent in clinical practice. We know that chemotherapy generates a series of side effects, such as nausea and vomiting, alopecia, and so on, which can be counteracted by complementary medication. However, in the case of post-chemotherapy cognitive impairment, or chemo brain, these cannot be controlled with drug therapies. However, before any intervention can be considered, it is necessary to know exactly what cognitive impairment is being triggered. For this reason, we decided to study the cognitive status of breast cancer patients. Methods: analytical, prospective, three-measure longitudinal, intrasubject unifactorial, non-probabilistic and accidental assignment study. The sample came from the Medical Oncology Department at Hospital de Salamanca, in Spain. Cognitive function (Trail Making Test and Stroop Test) was established as the primary variable; the presence of sleep disorders (Insomnia Severity Index, ISI) and anaemia (haemoglobin levels in blood) were analysed as secondary variables, in addition to intervening variables (age, stage, type of carcinoma, radiotherapy, menopause, social support network, marital status, years of schooling and employment status). Results: We recruited 151 individuals according to the selection criteria. We can confirm that factors including anaemia, menopause, patient support network and marital status, years of schooling, and employment status did affect the cognitive performance of the patients in the study. In contrast, sleep disorders, age, radiotherapy treatment, stage of disease, and type of carcinoma did not affect the cognitive performance of the cancer patients. Conclusions: Chemotherapy does impact the cognitive performance of breast cancer patients.

Background: Of the many side effects suffered by cancer patients, those related to cognitive performance have become increasingly prominent in clinical practice. We know that chemotherapy generates a series of side effects, such as nausea and vomiting, alopecia, and so on, which can be counteracted by complementary medication. However, in the case of post-chemotherapy cognitive impairment, or chemo brain, these cannot be controlled with drug therapies. However, before any intervention can be considered, it is necessary to know exactly what cognitive impairment is being triggered. For this reason, we decided to study the cognitive status of breast cancer patients. Methods: analytical, prospective, three-measure longitudinal, intrasubject unifactorial, non-probabilistic and accidental assignment study. The sample came from the Medical Oncology Department at Hospital de Salamanca, in Spain. Cognitive function (Trail Making Test and Stroop Test) was established as the primary variable; the presence of sleep disorders (Insomnia Severity Index, ISI) and anaemia (haemoglobin levels in blood) were analysed as secondary variables, in addition to intervening variables (age, stage, type of carcinoma, radiotherapy, menopause, social support network, marital status, years of schooling and employment status). Results: We recruited 151 individuals according to the selection criteria. We can confirm that factors including anaemia, menopause, patient support network and marital status, years of schooling, and employment status did affect the cognitive performance of the patients in the study. In contrast, sleep disorders, age, radiotherapy treatment, stage of disease, and type of carcinoma did not affect the cognitive performance of the cancer patients. Conclusions: Chemotherapy does impact the cognitive performance of breast cancer patients.

The aim of this study was to examine pathologic complete response (pCR) and overall survival (OS) of patients diagnosed with non-metastatic inflammatory breast cancer (IBC). A total of N=8,550 cases undergoing surgery were identified between 2004-2013, using the National Cancer Database (NCDB). Patients were grouped into 4 biologic subtypes (HR+/HER2-, HR+/HER2+, HR-/HER2+, HR-/HER2-). The median age at diagnosis was 56 years. On average, women were followed for 3.7 years [interquartile range=3.0]. The majority were white (80%), had private health insurance (50%), and presented with poorly differentiated tumors (57%). Approximately 46% of the cancers were >5cm. Most patients underwent mastectomy (94%) and received radiotherapy (71%). Differences by biologic subtypes were observed for grade, lymph node invasion, race, and tumor size (p<.0001). Compared with non-pCR (54%), patients experiencing pCR had superior 5-year survival (77%) (p<.0001). Survival was poor for triple-negative (TN) tumors (37%) vs. other biologic subtypes (60%) (p<.0001). On multivariable analysis, TN-IBC, positive margins, and not receiving either chemotherapy, hormonal therapy or radiotherapy were independently associated with poor 5-year survival (p<.0001). In this large multicentric analysis of IBC, categorized by biologic subtypes, we observed significant differential tumor, patient and treatment characteristics, and OS.

Carotenoids are essential pigments that play a vital role in the photosynthetic process of algae and are important for human health and nutrition. Despite their potential value, algal carotenoids are being neglected by biofuel industries. Recent research is aimed at producing microalgal lipids and carotenoids simultaneously under abiotic stresses. In this study, the effect of different abiotic stress factors such as Nitrogen (N), Potassium (K), Phosphorous (P), Sulphur (S), light intensity, and photoperiod on biomass, lipid, and carotenoids synthesis in Monoraphidium sp. (MP) were explored utilizing a statistical method. In addition, 2, 7-dichlorofluorescein diacetate (DCF-DA) mediated spectrofluorimetry was employed to detect the ele-vation in ROS level. The results revealed that variations in nutrients and light con-ditions are the key factors in the up-regulation of biomolecules lipids and carote-noids in the algae. The carotenoids profiling was done by Ultra Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectroscopy (UPLC-Q-ToF-MS). Among consisting carotenoids violaxanthin, astaxanthin, and beta-carotene were enhanced by 1.3 folds, 1.19 folds, 1.08 folds, while lutein was declined by 1.32 folds under stressed condition compared to control. The identified carotenoids are rec-ognized for their importance in the pharmaceutical and nutraceutical industries, highlighting the significant role of MP in these sectors.

Background: It has been reported that general adiposity in adulthood and early adulthood, and greater height may increase the risk of almost all types of lympho-haematopoietic cancers while a study done in MD Anderson found that obesity and adult weight gain are independent risk factors for CML however no study evaluated the role of obesity in the disease progression while more studies investigate the impact of translocation types. Method: We conducted a retrospective analysis of the files of 37 patients being treated in our center for CML in chronic phase (CMP-CP) with known BCR-ABL1 breakpoints, Results: patients’ management and response assessment was done based on ELN 2013 guidelines. Analysis is done based on two main groups, obese vs normal BMI, and then based on BCR-ABL1 transcripts: e13a2 vs e14a2. Although the number of cases is limited, in the patient-cohort studied an e14a2 BCR-ABL1 transcript type / normal body weight was associated with an inferior outcome when compared to e13a2 transcript / obesity groups Conclusion: our finding suggest the need to enlarge the series to better evaluate a potential role of altered metabolism and/or specific transcripts in the response to TKI in CML.