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Problematic smartphone use is an expanded public health heed that requires more study to clarify the influence elements of different populations. The aim of this study was to investigate the relationship between smartphone use, and sleep quality, self-perceived health, and exercise participation in university students. A total of 1,575 Taiwanese undergraduate students from 7 universities participated in the study. Three questionnaires were completed by the study individuals. The results show the overall PSU rate was 11.8%. Average smartphone users were more (...) likely to feel in good health, better sleep quality and less unsatisfactory exercise participation than those who were problematic smartphone users. Multiplelogisticregression analysis indicated that PSU, low weekly exercise frequency, and poor sleep quality were significant indicators of poor self-perceived health. We concluded that both low physical activity and PSU did have negative impacts on self-perceived health and sleep quality for undergraduate students. (shrink)

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Infertility is a huge problem nowadays, not only from the medical but also from the social point of view. A key step to improve treatment outcomes is the possibility of effective prediction of treatment result. In a situation when a phenomenon with more than 2 states needs to be explained, e.g. pregnancy, miscarriage, non-pregnancy, the use of multinomiallogisticregression is a good solution. The aim of this paper is to select those features that have a significant impact (...) on achieving clinical pregnancy as well as those that determine the occurrence of spontaneous miscarriage. Two multi-factor models were obtained, used in predicting infertility treatment outcomes. One of the models enabled to conclude that the number of follicles and the percentage of retrieved mature oocytes have a significant impact when prediction of treatment outcome is made on the basis of information about oocytes. The other model, built on the basis of information about embryos, showed the significance of the number of fertilized oocytes, the percentage of at least 7-cell embryos on day 3, the percentage of blasts on day 5, and the day of transfer. (shrink)

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Infertility is recognized as a major problem of modern society. Assisted Reproductive Technology is the one of many available treatment options to cure infertility. However, the efficiency of the ART treatment is still inadequate. Therefore, the procedure’s quality is constantly improving and there is a need to determine statistical predictors as well as contributing factors to the successful treatment. There is a concern over the application of adequate statistical analysis to clinical data: should classic statistical methods be used or would (...) it be more appropriate to apply advanced data mining technologies? By comparing two statistical models, MultivariableLogisticRegression analysis and Artificial Neural Network it has been demonstrated that MultivariableLogisticRegression analysis is more suitable for theoretical interest but the Artificial Neural Network method is more useful in clinical prediction. (shrink)

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This paper makes a quantitative analysis of the comprehensive influence of music networks. Firstly, 11 music features are selected from energy, popularity, and other aspects to build a comprehensive evaluation index of music influence, and the PageRank algorithm is used to quantify the music influence. Secondly, the multiobjectivelogisticregression is used to construct the music similarity measurement model and, combined with music influence and music similarity, to judge whether the influence of different musicians is the actual influence. (...) Thirdly, the influence and similarity of the same music genre and different music genres are analyzed by using the two-way cluster analysis method. Finally, the lasso region is used for feature selection to obtain the change factors in the process of music evolution and analyze the dynamic changes in the process of music development. Therefore, this paper uses network science to build a dynamic network to analyze the similarity of music, the evolution process, and the impact of music on culture, which has certain research significance and practical value in the fields of music, history, social science, and practice. (shrink)

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The purpose of this study was to understand the influence mechanism of college students’ entrepreneurial intention in view of the increasing number of college students at present to alleviate college students’ employment competition. The psychological factors that influence the entrepreneurial tendency of art graduates were analyzed and studied. First, venture capital and factors affecting entrepreneurial performance were analyzed. Second, the coefficient calculation is carried out for college students majoring in art through theregression analysis of thelogistic model. (...) Finally, a team entrepreneurial performance questionnaire was designed, and team reward levels were discussed. The results show that thelogistic model can well reflect the real situation of the respondents. The significance level of the entrepreneurial team was 0.02, which was correlated. Additionally, corresponding suggestions were put forward according to the questionnaire results. Clear team goals, assignment of tasks to members, good pressure resistance, and psychological quality of members are necessary qualities for successful entrepreneurship. This conclusion provides a certain theoretical basis for the current college students’ entrepreneurial learning and a reliable inspiration for helping college students to successfully start a business. (shrink)

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Principal Component Analysis is one of the data mining methods that can be used to analyze multidimensional datasets. The main objective of this method is a reduction of the number of studied variables with the mainte- nance of as much information as possible, uncovering the structure of the data, its visualization as well as classification of the objects within the space defined by the newly created components. PCA is very often used as a preliminary step in data preparation through the (...) creation of independent components for further analysis. We used the PCA method as a first step in analyzing data from IVF (in vitro fertilization). The next step and main purpose of the analysis was to create models that predict pregnancy. Therefore, 805 different types of IVF cy- cles were analyzed and pregnancy was correctly classified in 61-80% of cases for different analyzed groups in obtained models. (shrink)

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The authenticity of the company’s accounting information is an important guarantee for the effective operation of the capital market. Accounting fraud is the tampering and distortion of the company’s public disclosure information. The continuous outbreak of fraud cases has dealt a heavy blow to the confidence of investors, shaken the credit foundation of the capital market, and hindered the healthy and stable development of the capital market. Therefore, it is of great theoretical and practical significance to carry out the research (...) on the identification and governance of accounting fraud. Traditionally, accounting fraud identification is mostly based on linear thinking to build the fraud identification model. However, more and more studies show that fraud has typical nonlinear characteristics, and the multiobjective of fraud means also determines the limitations of using the linear model for identification. Considering that the traditional identification methods may have the defects of model setting error and insufficient information extraction, this paper constructs the support vector machine andlogisticregression model to identify accounting fraud. The support vector machine is used to improve the learning ability and generalization ability of unknown phenomena, and the explanatory power of each variable to the whole model is identified by thelogisticregression model. This paper breaks through the linear constraint hypothesis and explores the model setting form which is more suitable for the law of corporate fraud behaviour to extract the fraud identification information more fully and provide more powerful support for investors to effectively identify fraud. (shrink)

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Objective The establishment of patient-centered measures capable of empirically determining meaningful cognitive change after surgery can significantly improve the medical care of epilepsy patients. Thus, this study aimed to develop reliable change indices (RCIs) and standardizedregression-based (SRB) change norms for a comprehensive neuropsychological test battery in the German language. Methods Forty-seven consecutive patients with temporal lobe epilepsy underwent neuropsychological assessments, both before and 12 months after surgery. Practice-effect-adjusted RCIs and SRB change norms for each test score were computed. (...) To assess their usefulness, the presented methods were applied to a clinical sample, and binarylogisticregression analyses were conducted to model the odds of achieving improvement in quality of life (QOL) after surgery. Results The determined RCIs at 90% confidence intervals and the SRB equations for each test score included in the test battery are provided. Cohen’s kappa analyses revealed a moderate mean agreement between the two measures, varying from slight to almost perfect agreement across test scores. Using these measures, a negative association between improvement in QOL and decline in verbal memory functions after surgery was detected (adjusted odds ratio = 0.09, p = 0.006). Significance To the best of our knowledge, this study is the first to develop RCIs and SRB change norms necessary for the objective determination of neuropsychological change in a comprehensive test battery in the German language, facilitating the individual monitoring of improvement and decline in each patients’ cognitive functioning and psychosocial situations after epilepsy surgery. The application of the described measures revealed a strong negative association between improvement in QOL and decline in verbal memory functions after surgery. (shrink)

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This study has two objectives – to provide a Korean form of the workaholism analysis questionnaire, and to analyze workaholic tendencies in South Korea by using a nationally representative data. Using 4,242 samples (2,497 men and 1,745 women), exploratory and confirmatory factor analyses were conducted to develop a Korean form (K-WAQ). The four-factor structure of K-WAQ in this study seemed to adequately represent the underlying dimensions of work addiction in Korea. The study also analyzed the prevalence of workaholism among Koreans (...) and its differences according to socio-demographic variables. Both mean difference analyses andlogistic regressions were conducted. The overall result indicated that the prevalence of workaholism in Korea can be estimated to be 39.7% of the employees. The workaholic tendencies in Korea differ significantly according to gender, age, work hours, and voluntariness of choosing employment type. Practical as well as theoretical implications and future research directions are discussed. (shrink)

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Economy is one of the major issues in the United States presidential election campaign. In order to investigate the impact of the US presidential election on the economy, this paper first constructs an analysis model of the economic impact on the United States based on stepwiseregression and principal component analysis to analyze the focus of different candidates’ attention on the economic issues and its possible impact on the US economy in the election year and after the election; secondly, (...) a Chinese economic impact analysis model based on factor analysis and machine learninglogisticregression was constructed to analyze the impact of the US presidential election on the Chinese economy. At the same time, the future economic development of the United States and China based on the time series prediction model is forecast and analyzed, respectively. Finally, the countermeasures and policy suggestions on China’s related economic development are put forward. (shrink)

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An emergent body of literature examined why some firms apply some environmental initiatives while other firms do not take responsibility for their natural environment? Thus, firm environmental orientation (responsiveness and performance) are linked in the literature to several variables. Unfortunately, the relationship between firm environmental orientation and either available resources or firm size showed mixed results and inconclusive evidence. Therefore, the aim of this paper is to show empirically how available resources and firm size can explain differences in firm environmental (...) responsiveness and environmental performance. Econometric results of environmental responsiveness using thelogisticregression model demonstrated that firm size does appear to add something unique in explaining differences in environmental responsiveness while available resource can be safely dropped from the model. However, econometric analysis of environmental performance using the maximum-likelihood random effects model showed strong evidence that available resources and firm size are significant predictors of firm environmental performance. (shrink)

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Recent works in Explainable AI mostly address the transparency issue of black-box models or create explanations for any kind of models (i.e., they are model-agnostic), while leaving explanations of interpretable models largely underexplored. In this paper, we fill this gap by focusing on explanations for a specific interpretable model, namely pattern-basedlogisticregression (PLR) for binary text classification. We do so because, albeit interpretable, PLR is challenging when it comes to explanations. In particular, we found that a standard (...) way to extract explanations from this model does not consider relations among the features, making the explanations hardly plausible to humans. Hence, we propose AXPLR, a novel explanation method using (forms of) computational argumentation to generate explanations (for outputs computed by PLR) which unearth model agreements and disagreements among the features. Specifically, we use computational argumentation as follows: we see features (patterns) in PLR as arguments in a form of quantified bipolar argumentation frameworks (QBAFs) and extract attacks and supports between arguments based on specificity of the arguments; we understandlogisticregression as a gradual semantics for these QBAFs, used to determine the arguments’ dialectic strength; and we study standard properties of gradual semantics for QBAFs in the context of our argumentative re-interpretation of PLR, sanctioning its suitability for explanatory purposes. We then show how to extract intuitive explanations (for outputs computed by PLR) from the constructed QBAFs. Finally, we conduct an empirical evaluation and two experiments in the context of human-AI collaboration to demonstrate the advantages of our resulting AXPLR method. (shrink)

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This paper investigates the effects of 10 factors on the choice between alternative ba sentences and SVO sentences in Mandarin Chinese. These factors are givenness, definiteness, animacy and pronominality of NP2s, NP2 length, VP length, verb sense, syntactic parallelism, dependency distance, and surprisal. Using corpus data and mixed-effectslogisticregression modeling, we find that on the one hand, givenness, syntactic parallelism, and the log-transformed ratio of NP2 length and VP length are significant predictors of the choice between ba (...) sentences and SVO sentences. A new NP2, a large length ratio and a parallel construction predict an SVO sentence rather than a ba sentence. On the other hand, dependency distance and surprisal estimated by the trigram model are effective in predicting the choice between naturally occurring ba/svo sentences and their alternatives. Naturally occurring sentences are more likely to have shorter dependency distances and smaller surprisal values than the converted sentences. The effects of these five factors on syntactic choice are congruent with results of previous studies, which suggests that some determinants of syntactic choice are shared among languages. (shrink)

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We investigate what drives responsible investment of European pension funds. Pension funds are institutional investors who assure the income of part of the population for a long period of time. Increasingly, stakeholders hold pension funds accountable for the non-financial consequences of their investments and many funds have engaged in responsible investing. However, it appears that there is a wide difference between pension funds in this respect. We investigate what determines pension funds’ responsible investments on the basis of a survey of (...) more than 250 pension funds in 15 European countries in 2010. We use multinomiallogisticregression and find that especially legal origin of the country, ownership of the pension fund and fund size-related variables are to be associated with pension funds′ responsible investment. For fund size, we establish a curvilinear relationship; especially the smallest and largest pension funds in the sample tend to engage with responsible investing. (shrink)

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The motive of this study is to identify the factors influencing the willingness to pay (WTP) a premium price for socially responsible food products (SRFPs) in India. This study is based on primary survey of 398 respondents. Descriptive statistics and factor analysis have been used for data analysis. Further,logisticregression was used to examine the factors affecting the WTP a premium price for SRFPs. Results demonstrate that respondents of higher age are more likely to pay premium prices (...) for SRFPs. Male consumers are two times more likely to have higher WTP for SRFPs. WTP a premium price is significantly influenced by the consumers' reference group, pro‐environmental intention, and concern for the animals. Gender, age, consumers' reference group, pro‐environmental intention, and concern for the animals determine WTP premium prices for SRFPs. There are relatively very limited researches on this topic in emerging economies including India, where the adoption of socially responsible products is in early stage. The practical implications of this study are to help in increasing the sales of the SRFPs and producers to develop appropriate policy design. (shrink)

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The University of Tehran English Proficiency Test (UTEPT) is a high-stakes entrance examination taken by more than 10,000 master’s degree holders annually. The examinees’ scores have a significant influence on the final decisions concerning admission to the University of Tehran Ph.D. programs. As a test validation investigation, the present study, which is a bias detection research in nature, utilized multisteplogisticregression (LR) procedure to examine the presence of gender differential item functioning (DIF) in the UTEPT with a (...) sample of 6,555 examinees who took the test in November 2006. Specifically, the LR DIF two-degree of freedom Chi-squared test of significance was employed to test the significance of DIF. Following what has been recently suggested in the literature, the test of significance for DIF was accompanied by a measure of magnitude, namely the R-squared effect size for LR DIF, for the interpretation of which the two widely accepted classification schemes were used comparatively. The results reveal that 39 of the 100 items in the test display significant gender differences. However, these group differences are viewed as “negligible” based on both of the schemes. Accordingly, it could be argued that the UTEPT is a gender DIF-free test, though the Reading Comprehension section of the test remains in need of further analysis as it seems that the general trend of DIF indices at the item level may hint at an inclination towards males. (shrink)

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In this article thelogisticregression results in Table 4Logisticregression results were unfortunately misinterpreted with respect to one hypothesis. The original article states that H5 Levels of observed unethical behavior by accounting students are lower for students who self-identify as politically liberal, than for students who self-identify as politically conservative. While the variable “Self-identified Political Ideology” is statistically significant, the negative sign on the coefficient indicates the result is hypothesized in the opposite direction. Thus (...) the correct interpretation is that accounting students who self-identify as conservative have lower levels of observed unethical behavior than accounting students who self-identify as politically liberal. We regret any inconveniences this may have caused. (shrink)

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This paper investigates three morphosyntactic alternations in Estonian – those between the exterior locative cases allative, adessive and ablative and the corresponding postpositionspeale‘onto’,peal‘on’ andpealt‘off’. Based on the Complexity Principle (e.g., Rohdenburg, Günter. 2002. Processing complexity and the variable use of prepositions in English. In Hubert Cuyckens & Günter Radden (eds.),Perspectives on prepositions, 79–100. Tübingen: Niemeyer), we expect cognitively more complex constructions to use more explicit (i.e., morphologically more substantial) marking by means of a postposition. Further, we expect variation to be (...) conditioned similarly in all three semantic categories. For each of the three alternations, a random sample of the two outcomes (case vs. postposition) from the Estonian National Corpus is used, resulting in 3,000 data points. Using properties of the Landmark phrase as independent variables in Bayesian mixed-effectslogisticregression models, we predict the choice of postpositions over case-marked realisations. Of the patterns found, only the frequency-related one supports our complexity-related hypothesis. We conclude that the Complexity Principle, in its general form, has little explanatory power for the Estonian constructions at hand and, in particular, that the derived principle of ‘analytic support’ is not generally applicable. We show, however, that the grammatical knowledge of Estonian exterior locative cases and the corresponding postpositions is regulated by our three factors in a relatively uniform way. (shrink)

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Artificial intelligence, including Digital AI Humans (DHs) and Voice Assistants (VAs), offers new opportunities for healthcare delivery but may widen inequalities. This cross-sectional online survey examined factors influencing the acceptability of these technologies among 472 UK adults, considering demographics, digital literacy, healthcare access, familiarity with DHs and VAs, personality traits, and attitudes. VA acceptability was assessed usinglogisticregression, with willingness to use VAs as the outcome variable. Lower acceptance was found among women, ethnic minorities, those with lower (...) education levels, and individuals who infrequently searched for health information online. Conversely, higher acceptance was associated with engagement in online health discussions, greater awareness and use of VAs, perceived usefulness, fewer perceived barriers, and openness. DH acceptability was analysed through multipleregression, with attitudes toward DHs as the outcome variable. More positive attitudes were linked to White/Irish/European ethnicity, a greater perceived need for in-person care, participation in online health discussions, higher conscientiousness, and lower neuroticism, explaining 27.8% of the variance. Although 85.8% had used VAs and 82.2% owned one, only 25.8% reported daily use. Awareness of DHs was reported by 70.3% of participants, with attitudes generally positive (median score: 2.17/5, where lower scores indicate greater favourability). Institutional endorsement was a key factor, with 71.2% stating they would use VAs for healthcare if approved by the NHS. These findings support technology acceptance models, highlighting the roles of perceived usefulness, ease of use, and awareness. Culturally responsive design principles that address these factors may enhance adoption across diverse groups. Distinct personality traits influenced acceptance, with openness predicting VA acceptability, while conscientiousness and low neuroticism were associated with more positive attitudes toward DHs. While offering novel insights into human factors influencing AI adoption in healthcare, the study is limited by its reliance on proxy measures for acceptance. (shrink)

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A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms (...) of variable selection and multicollinearity, respectively. Alogisticregression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective. (shrink)

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Proper utilization of antenatal and postnatal care services plays an important role in reducing the maternal mortality ratio and infant mortality rate. This paper assesses the utilization of health care services during pregnancy, delivery and post-delivery among rural women in Uttar Pradesh and examines its determinants. Data from a baseline survey of UP Community Mobilization project was utilized. A cross-sectional sample of currently married women who delivered a baby 15 months prior to the survey was included. Information was collected from (...) 2208 women spread over five districts of UP. Information on socio-demography characteristics, utilization of antenatal care, delivery and postnatal care services was collected. To examine the determinants of utilization of maternal health services, the variables included were three ANC visits, institutional delivery and PNC within 42 days of delivery. Separate multilevel random interceptlogistic regressions were used to account for clustering at a block and gram panchayat level after adjusting for covariates. Eighty-three percent of women had any ANC. Of them, 61% reported three or more ANC visits. Although 68% of women delivered in a health facility, 29% stayed for at least 48 h. Any PNC within 42 days after delivery was reported by 26% of women. In the adjusted analysis, women with increasing number of contacts with the health worker during the antenatal period, women exposed to mass-media and non-marginalized women were more likely to have at least three ANC visits during pregnancy. Non-marginalized women and women with at least three ANC visits were more likely than their counterparts to deliver in an institution. Contacts with health worker during pregnancy, marginalization, at least three ANC visits and institutional delivery were the strong determinants for utilization of PNC services. Self-help group membership had no association with the utilization of maternal health services. Utilization of maternal health services was low. Contact with the health worker and marginalization emerged as important factors for utilization of services. Although not associated with the utilization, SHGs can be used for delivering health care messages within and beyond the group. (shrink)

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The psychological problems and employment problems of college students have always been the focus of attention of all sectors of society. The COVID-19 epidemic has a great impact on the mental health and employment of Chinese college students. Under this background, this study discusses how epidemic anxiety affects the employment confidence and perception of employment situation of Chinese college students. Through the online questionnaire survey of 1,132 college students nationwide, and the ordinallogisticregression analysis of the survey (...) data using Stata 16.0 software, the results show that: Epidemic anxiety negatively affects Chinese college students' employment confidence and employment situation perception, and has a significant impact on employment confidence. The three control variables of employment guidance, older age and higher education have a significant positive impact on college students' employment confidence and employment situation perception. College students in the eastern region have stronger employment confidence and more optimistic employment situation perception. But the expected monthly salary is negatively correlated with employment confidence. Male college students and Science and Engineering students' epidemic anxiety have a stronger negative impact on employment confidence and employment situation perception. Employment guidance has a moderating effect on the relationship between epidemic anxiety, employment confidence and employment situation perception. Employment guidance can enhance college students' employment confidence and reduce their sense of employment crisis by alleviating epidemic anxiety. Combined with the research conclusions, it is proposed that the state and schools should pay attention to the psychological counseling of college students, strengthen the employment guidance of colleges and universities, vigorously support the development of small, medium-sized and micro enterprises, and improve the employment and entrepreneurship service system of college students, so as to promote the employment of college students. (shrink)

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BackgroundThe psychological burden possibly deriving from not immediately undergoing radical treatment for prostate cancer could be a potential disadvantage of active surveillance, especially in the eve of some relevant clinical exams [i.e., re-biopsy, prostate-specific antigen test, and medical examination]. Even if it is known from the literature that the majority of PCa men in AS do not report heightened anxiety, there is a minority of patients who show clinically significant levels of anxiety after diagnosis. The present study aimed to investigate (...) if demographic, clinical, and psychological variables at the entrance in AS were associated with the risk of developing clinically significant PCa-related anxiety 2 months before the first re-biopsy and to offer psychological support to improve quality of life.Materials and MethodsA total of 236 patients participated in the PCa Research International: AS protocol and in PRIAS-QoL study. Demographic/clinical features, health-related QoL domains, coping with cancer, PCa-related anxiety [Memorial Anxiety Scale for PCa ], personality traits, and decision-making-related factors were assessed at T0. MAX-PC was also administered at T1. PCa-related anxiety at T1 was considered to be of clinical significance if the MAX-PC score was ≥1.5. Multivariablelogisticregression coupled to bootstrap was used to detect factors associated with high levels of anxiety.ResultsThe median age was 64.4 years. Fifty-six patients reported MAX-PC total score above the cutoff. Three factors were associated with a high level of PCa anxiety at T1: anxious preoccupation [odds ratio = 4.36], extraversion, and prostate-related symptoms. Physical well-being was associated with a low PCa anxiety subscale ; neuroticism and functional well-being were associated with PSA anxiety. Neuroticism and helplessness/hopelessness were associated with fear of progression.ConclusionOnly a partial portion of the sample experienced significant levels of anxiety after 10 months. Psychological assessment should be routinely conducted to detect risk factors for increased anxiety, offering tailored psychological interventions aimed at promoting interpersonal awareness and emotional well-being. (shrink)

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The effects of grandparent survival on child survival and mean interbirth interval, both independent of and relative to parent survival, were investigated in a historical population. Families for the data set were reconstituted from the parish and census records of Cambridgeshire, 1770–1861. In alogisticregression analysis, only the mother’s and the maternal grandmother’s survival were found to be significant predictors of child survival. Maternal grandmother’s survival was found to influence child survival both via maternal survival and independent (...) of maternal survival. Grandparent survival was not found to influence mean interbirth interval. These findings are reviewed with respect to other studies of grandmothering, the Grandmother Hypothesis, and the evolutionary significance of human female postreproductive lifespan. (shrink)

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In this article we apply one of the key concepts in cognitive linguistics, the radial category, to inflectional morphology. We advance the Paradigm Structure Hypothesis, arguing that inflectional paradigms are radial categories with internal structure primarily motivated by semantic relationships of markedness and prototypicality. It is possible to construct an expected structure for a verbal paradigm, facilitating an empirical test for our hypothesis. Data tracking an on-going morphological change in Russian documents the distribution of conservative vs. innovative forms across the (...) cells of the verbal paradigm. Alogisticregression model that takes into account the sources of variation (the frequencies of individual verbs and paradigm slots, and individual verb preferences) shows that the language change is implemented differently across the paradigm forms, confirming the expected structure. In addition to markedness and prototypicality, we investigate the impact of frequency and show that there is a good, albeit not perfect match between the expected hierarchy and frequency. We conclude that the diachronic change analyzed in this article gives evidence for the structure of paradigms modeled on the radial category. (shrink)

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A positive connection has been established between personality traits and suicidal ideation. However, the possible mediation of resilience within this association has never been thoroughly discussed. In this study, we aimed to investigate this topic by using population-based cross-sectional survey data of 4,489 Chinese children and adolescents. A self-administered questionnaire was used to collect information from the participants. Univariate and multivariatelogisticregression models were adopted to measure the crude and adjusted associations between personality traits, SI, and resilience. (...) Path analysis was performed to evaluate the mediation of resilience in the association between personality traits and SI. For 4,489 study subjects, the mean age was 13.4 years, ethnic minorities accounted for 71.8%, and over a half were middle school students. The reported prevalence rates for 1-week, 1-year, and lifetime SI were 27.6%, 35.5%, and 56.7%, respectively. Girls reported a significantly higher prevalence of SI than boys. Path analysis results revealed a prominent mediation of resilience; moreover, for different dimensions of personality traits, the proportion of mediation by resilience varied. Our major findings suggest that resilience-based intervention measures could be considered in preventing personality traits related to suicidal risk among youngsters. For children and adolescents, the measuring of personality dimensions may also be helpful in targeting key subpopulations of intervention priority. (shrink)

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This paper presents a novel perspective on an evolving policy area. The UK’s withdrawal from the EU has led to the creation of a new Agriculture Act and proposals for significant changes to the way farming subsidies are structured in England. Underpinned by a ‘public money for public goods’ approach, where public goods are those outputs from the farm system which are not rewarded by markets, yet which provide benefits to many members of society. New schemes include the Animal Health (...) and Welfare Pathway, where certain aspects of farm animal health and welfare (FAHW) will be subsidised through government support, raising a much-debated issue in the literature regarding the representation of FAHW as a public good. For policy to be responsive to societal demands and accountable to citizens, understanding public attitudes and preferences towards FAHW as a public good, and how the public might prioritise this in relation to a wider suite of environmental public goods from farming, is important. An online survey of 521 members of the UK public was conducted and analysed with descriptive statistics and orderedlogisticregression. Findings reveal low awareness of the changing agricultural policy context, but strong support for public money being used to provide public goods, particularly for FAHW. Findings also indicate a need for more effective public communication of farming and FAHW issues from farming stakeholders to ensure public policy in this domain is responsive and accountable to its citizens. Further work is needed to inform future debates and engagement surrounding FAHW, including through which combination of funding mechanisms (public or private) it is provided. (shrink)

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Relevance deprivation syndrome refers to feelings of incompetence among retired people caused by them leaving their high status or influential jobs. The question then arises: do people in positions of power, like Danwei leaders in China, have a lower life satisfaction post-retirement compared to other groups? This study investigated the influence of serving as a Danwei leader before retirement on retirees’ life satisfaction, as well as differences in this influence and the channels through which they are affected. Based on the (...) data of 5,873 respondents of the 2018 China Longitudinal Aging Social Survey, ordinary least-squares, orderedlogisticregression, and propensity score matching models were used to investigate the influence, differences, and influential mechanisms of serving as a Danwei leader before retirement on retirees’ life satisfaction. We found that Danwei leaders experience a significantly positive impact on their life satisfaction post-retirement. Second, the positive impact of having served in this role on peoples’ post-retirement life satisfaction is related to the resulting higher income, social status, and better living habits. In contrast to the perspective of relevance deprivation syndrome, in China, having been a Danwei leader before retirement has a significantly positive impact on peoples’ life satisfaction post-retirement, with there being a significant difference observed among different types of retired Danwei leaders. (shrink)

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Little is known about research misconduct within industry and how it compares to universities, even though a lot of biomedical research is performed by–or in collaboration with–commercial entities. Therefore, we sent an e-mail invitation to participate in an anonymous computer-based survey to all university researchers having received a biomedical research grant or scholarship from one of the two national academic research funders of Belgium between 2010 and 2014, and to researchers working in large biomedical companies or spin-offs in Belgium. The (...) validated survey included questions about various types of research misconduct committed by respondents themselves and observed among their colleagues in the last three years. Prevalences of misconduct were compared between university and industry respondents using binarylogisticregression models, with adjustments for relevant personal characteristics, and with significance being accepted for p< 0.01. The survey was sent to 1766 people within universities and an estimated 255 people from industry. Response rates were 43 and 48%, and usable information was available for 617 and 100 respondents, respectively. In general, research misconduct was less likely to be reported by industry respondents compared to university respondents. Significant differences were apparent for one admitted action and three observed actions, always with lower prevalences for industry compared to universities, except for plagiarism. This survey, based on anonymous self-report, shows that research misconduct occurs to a substantial degree among biomedical researchers from both industry and universities. (shrink)

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Weights of evidence andlogisticregression are two loglinear methods for mineral potential mapping. Both models are limited by their respective basic assumptions in application. Ideally, WofE indicator patterns have the property of conditional independence with respect to the point pattern of mineral deposits to be predicted; in LR, there supposedly are no interactions between the point pattern and two or more of the indicator patterns. If the CI assumption is satisfied, estimated LR coefficients become approximately equal to (...) WofE contrasts and the two methods produce similar results; additionally, bias then is avoided in that the sum of all estimated posterior probabilities becomes approximately equal to the number of observed discrete events. WofE allows construction of input layers that have missing data as a separate category in addition to known presence-absence type input, whilelogisticregression as such is not capable of handling missing data. As an improved WofE model based on LR, modified weights of evidence inherit the advantages of both LR and WofE, i.e., eliminates bias due to lack of CI and can handle missing data as well. Pixel or unit area input for MWofE consists of positive and negative weights for presence and absence of a pattern plus zeros for missing data. MWofE first is illustrated by application to simple examples. Next, it is applied to a study area with 20 known gold occurrences in southwestern Nova Scotia in relation to four input layers based on geological and lake geochemical data. Assuming that geochemical data were missing for the northern part of the study area, MWofE, like WofE but unlike LR, provides posterior probabilities for the entire area. (shrink)

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Twitter integrates with streaming data technologies and machine learning to add new value to healthcare. This paper presented a real-time system to predict breast cancer based on streaming patient’s health data from Twitter. The proposed system consists of two major components: developing an offline building model and an online prediction pipeline. For the first component, we made a correlation between the features to determine the correlation between features and reduce the number of features from the Breast Cancer Wisconsin Diagnostic dataset. (...) Two feature selection algorithms are recursive feature elimination and univariate feature selection algorithms which are applied to features after correlation to select the essential features. Four decision trees,logisticregression, support vector machine, and random forest classifier have been used on features after correlation and feature selection. Also, hyperparameter tuning and cross-validation have been applied with machine learning to optimize models and enhance accuracy. Apache Spark, Apache Kafka, and Twitter Streaming API are used to develop the second component. The best model with the highest accuracy obtained from the first component predicts breast cancer in real time from tweets’ streaming. The results showed that the best model is the random forest classifier which achieved the best accuracy. (shrink)

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Domestic violence is one of the most common forms of violence against women. Domestic violence during pregnancy is associated with adverse perinatal and maternal outcomes. We aimed to assess whether domestic violence was associated with mode of delivery, low birthweight and preterm birth in two sites in Nepal. In this prospective cohort study we consecutively recruited 2004 pregnant women during antenatal care at two hospitals between June 2015 and September 2016. The Abuse Assessment Screen was used to assess fear and (...) violence. Having ever experienced either fear or violence was defined as any domestic violence. Obstetric outcomes were obtained from hospital records for 1381 women, selecting singleton pregnancies only. Mode of delivery was assessed as birth by cesarean section or not. A birthweight of less than 2500 g was defined as low birthweight and preterm birth as birth before completion of 37 weeks gestation. Descriptive and multiplelogisticregression analyses were performed to assess associations. Twenty percent of the women reported any domestic violence. Among all 1381 women, 37.6% gave birth by cesarean section. Of those women who delivered by cesarean section, 84.7% had an emergency cesarean section. Less than 10% of the babies were born prematurely and 13.5% were born with low birthweight. We found no significant association between exposure to any domestic violence during pregnancy and risk of a low birthweight baby or birth by cesarean section. However, having experienced both violence and fear was significantly associated with giving birth to a preterm infant [aOR 2.33 ]. Domestic violence is common in Nepal. This is a potential risk factor for severe morbidity and mortality in newborns. We found that the risk of having a preterm baby was higher for pregnant women who experienced both fear and violence. This should be recognized by the health sector. In this study, no significant differences were found in the rate of cesarean section nor low birthweight for women who had experienced any domestic violence compared to those who did not. (shrink)

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Background: The purpose of the current study was to assess the prevalence of sleep disturbances among Chinese people during the COVID-19 pandemic in a large national survey, analyze the relationship between sleep disturbances and mental health status, and explore the influencing factors of the relationship between sleep disturbances and mental health status.Methods: An online survey was accessed by 19,740 people throughout China from February 14 to 21, 2020. The survey included the Depression Anxiety Stress Scale-21 to measure psychological distress and (...) two questions about sleep disturbances.Logisticregression analyses and moderation analysis were performed.Results: Among the 14,505 respondents included in analyses, 3,783 reported sleep disturbances at least 3 days during the past week. Sleep disturbances increased the risk of depression, anxiety, and stress. Gender, age, education, occupation, frequency of attending to epidemic information, nervousness about supplies, receiving provisions of living necessities from the service department during the outbreak, number of correct responses to questions about the epidemic, and isolation/quarantine affected the risk of mental health problems among participants experiencing sleep disturbances. A moderation analysis found that sleep problems were more likely to affect depression, anxiety, and stress scores in men than women during the COVID-19 outbreak.Conclusion: During the COVID-19 outbreak, 26.08% people surveyed experienced sleep disturbances, and the presence of sleep disturbances was positively related to depression, anxiety, and stress, especially among front-line anti-epidemic workers, younger people, people living in isolation/quarantine, people with a college or greater education, and males. (shrink)

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Background Studies show that people bereaved by suicide often feel a strong need for professional help. It is hypothesized that aspects related to suicide bereavement, such as stigmatization, shame or guilt, hinder help-seeking process of the bereaved. However, little is known about help-seeking behaviors of people who has lost someone due to suicide. Aims This study was conducted to attain a better understanding of the contributing factors, including the specific features of grief following suicide, to help-seeking behaviors of the bereaved (...) by suicide. Methods The sample consisted of 82 adults bereaved by suicide (64 female; average age 37.79, SD = 14.33). Instruments assessing stigmatization, shame, guilt levels, well-being, tendency to disclose emotional distress and attitudes toward seeking professional psychological help were used. The participants were also asked an open-ended question what professional help-seeking barriers they had encountered. Comparisons between the groups,logisticregression analysis and thematic analysis of the qualitative data were performed. Results The findings revealed that bereaved participants who sought professional psychological help reported experiencing stigmatization and feeling guilty after the loss significantly more often. Also the results showed that attitudes toward mental health specialists had the highest prognostic value in predicting help-seeking behaviors of the bereaved. The participants themselves identified the gaps in the health care system as main barriers to seeking help. Conclusion The results challenge previously spread notion that stigmatization, guilt and shame after suicide can act only as help-seeking barriers. (shrink)

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Malware is a sophisticated, malicious, and sometimes unidentifiable application on the network. The classifying network traffic method using machine learning shows to perform well in detecting malware. In the literature, it is reported that this good performance can depend on a reduced set of network features. This study presents an empirical evaluation of two statistical methods of reduction and selection of features in an Android network traffic dataset using six supervised algorithms: Naïve Bayes, support vector machine, multilayer perceptron neural network, (...) decision tree, random forest, and K-nearest neighbors. The principal component analysis andlogisticregression methods with p value were applied to select the most representative features related to the time properties of flows and features of bidirectional packets. The selected features were used to train the algorithms using binary and multiclass classification. For performance evaluation and comparison metrics, precision, recall, F-measure, accuracy, and area under the curve were used. The empirical results show that random forest obtains an average accuracy of 96% and an AUC-ROC of 0.98 in binary classification. For the case of multiclass classification, again random forest achieves an average accuracy of 87% and an AUC-ROC over 95%, exhibiting better performance than the other machine learning algorithms. In both experiments, the 13 most representative features of a mixed set of flow time properties and bidirectional network packets selected by LR were used. In the case of the other five classifiers, their results in terms of precision, recall, and accuracy, are competitive with those obtained in related works, which used a greater number of input features. Therefore, it is empirically evidenced that the proposed method for the selection of features, based on statistical techniques of reduction and extraction of attributes, allows improving the identification performance of malware traffic, discriminating it from the benign traffic of Android applications. (shrink)

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In this paper, we argue that corruption research can benefit from studying corrupt transactions as a particular form of social interaction. We showcase the usefulness of a theoretical focus on social interaction by investigating online user reports on the website Frontdesktip.com. Through this focus, we can observe users sharing experiences and tips on the best ways of bribing hotel clerks in Las Vegas for attaining room upgrades and other complimentary extras. We employ alogisticregression analysis to examine (...) what factors influence the “successful” performance of this bribery practice. Our study makes a twofold contribution to existing research on corruption. First, on the theoretical level, we show that the typified and scripted character of social interactions can help explain the occurrence of corrupt transactions. Second, on a methodological level, our study showcases online self-reports as a useful data source to study corrupt transactions in an unobtrusive way. (shrink)

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Interactional competence has attracted increasing attention due to its significance for language users. Previous studies concerning interactional competence mainly focus on synchronous interaction tasks, while the utilization of asynchronous interaction tasks is relatively under-explored despite the importance of asynchronous interaction in real life. Taking the “Responding To Forum Posts” task used in the International Undergraduate English Entrance Examination at Shanghai Jiao Tong University as an example, the study aims to validate the use of asynchronous interaction tasks in the assessment of (...) learner’s interactional competence. 49 students’ performances on the RTFP task were collected through a prototype test of the IUEEE in 2021. The data were analyzed through content analysis, analysis of variance, and ordinallogisticregression. The results showed that the task elicited a wide range of interactional features and test-takers at different proficiency levels differed significantly in the variety of features and the amount of emotion-based interaction. The study also found significant correlations between some of the features and test takers’ overall performance on interactional competence. The study has provided validity evidence for the RTFP task in the assessment of interactional competence and thrown light on the construct of asynchronous written interactional competence. (shrink)

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Sex ratios have widely been recognized as an important link between demographic contexts and behavior because changes in the ratio shift sex-specific bargaining power in the partner market. Implicitly, the literature considers individual partner market experiences to be a function of local sex ratios. However, empirical evidence on the correspondence between subjective partner availability and local sex ratios is lacking so far. In this paper, we analyzed how closely a set of different local sex ratio measures correlates with subjective partner (...) market experiences. Linking a longitudinal German survey to population data for different entities, we used multilevellogisticregression models to explore associations between singles’ subjective partner market experiences and various operationalizations of local sex ratios. Results suggest that local sex ratios correlated only weakly with subjective partner market experiences. Adult sex ratios based on broad age brackets, including those for lower-level entities, did not significantly predict whether individuals predominantly met individuals of their own sex. More fine-grained, age-specific sex ratios prove to be better predictors of subjective partner market experiences, in particular when age hypergamy patterns were incorporated. Nevertheless, the respective associations were only significant for selected measures. In a complementary analysis, we illustrate the validity of the subjective indicator as a predictor of relationship formation. In sum, our results suggest that subjective partner availability is not adequately represented by the broad adult sex ratio measures that are frequently used in the literature. Future research should be careful not to equate local sex ratios and conscious partner market experiences. (shrink)

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