Search results for: ordered logistic regression

Authors: Cathal Merz, Gareth O’Donnell

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Coil reinforced thin-walled (CRTW) tubes are used in medicine to treat problems affecting blood vessels within the body through minimally invasive procedures. The CRTW tube considered in this research makes up part of such a device and is inserted into the patient via their femoral or brachial arteries and manually navigated to the site in need of treatment. This procedure replaces the requirement to perform open surgery but is limited by reduction of blood vessel lumen diameter and increase in tortuosity of blood vessels deep in the brain. In order to maximize the capability of these procedures, CRTW tube devices are being manufactured with decreasing wall thicknesses in order to deliver treatment deeper into the body and to allow passage of other devices through its inner diameter. This introduces significant stresses to the device materials which have resulted in an observed increase in the breaking of the proximal segment of the device into two separate pieces after it has failed by buckling. As there is currently no international standard for measuring the mechanical properties of these CRTW tube devices, it is difficult to accurately analyze this problem. The aim of the current work is to address this discrepancy in the biomedical device industry by developing a measurement system that can be used to quantify the effect of process and design changes on CRTW tube performance, aiding in the development of better performing, next generation devices. Using materials testing frames, micro-computed tomography (micro-CT) imaging, experiment planning, analysis of variance (ANOVA), T-tests and regression analysis, test methods have been developed for assessing the impact of process and design changes on the device. The major findings of this study have been an insight into the suitability of buckle and three-point bend tests for the measurement of the effect of varying processing factors on the device’s performance, and guidelines for interpreting the output data from the test methods. The findings of this study are of significant interest with respect to verifying and validating key process and design changes associated with the device structure and material condition. Test method integrity evaluation is explored throughout.

Keywords: neurovascular catheter, coil reinforced tube, buckling, three-point bend, tensile

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Authors: Klea Ramaj

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Objectives: There have recently been increasing calls to better understand the intergenerational transmission of adverse childhood experiences (ACEs). In particular, little is known about the links between maternal (ACEs), maternal stress, maternal depression, and child abuse against toddlers in countries in South-East Europe. This paper, therefore, aims to present new descriptive data on the epidemiology of maternal mental well-being and maternal ACEs in the capital of Albania, Tirana. It also aims to advance our understanding of the overlap between maternal stress, maternal depression, maternal exposure to ACEs, and child abuse toward two-to-three-year-old. Methods: This is a cross-sectional study conducted with a representative sample of 328 mothers of two-to-three-year-olds, recruited through public nurseries located in 8 diverse socio-economic and geographical areas in Tirana, Albania. Maternal stress was measured through the perceived stress scale (α = 0.78); maternal depression was measured via the patient health questionnaire (α = 0.77); maternal exposure to ACEs was captured via the ACEs international questionnaire (α = 0.77); and child maltreatment was captured via ISPCAN ICAST-P (α = 0.66). The main outcome examined here will be child maltreatment. The paper will first present estimates of maternal stress, depression, and child maltreatment by demographic groups. It will then use multiple regression to examine associations between child maltreatment and risk factors in the domains of maternal stress, maternal depression, and maternal ACEs. Results: Mothers' mean age was 32.3 (SD = 4.24), 87.5% were married, 51% had one child, and 83.5% had completed higher education. Analyses show high levels of stress and exposure to childhood adversity among mothers in Tirana. 97.5% of mothers perceived stress during the last month, and 89% had experienced at least one childhood adversity as measured by the ACE questionnaire, with 20.2% having experienced 4+ ACEs. Analyses show significant positive associations between maternal ACEs and maternal stress r(325) = 0.25, p = 0.00. Mothers with a high number of ACEs were more likely to abuse their children r(327) = .43, p = 0.00. 32% of mothers have used physical discipline with their 2–3-year-old, 84% have used psychological discipline, and 35% have neglected their toddler at least once or twice. The mothers’ depression levels were also positively and significantly associated with child maltreatment r(327) = .34, p = 0.00. Conclusions: This study provides cross-sectional data on the link between maternal exposure to early adversity, maternal mental well-being, and child maltreatment within the context of Tirana, Albania. The results highlight the importance of establishing policies that encourage maternal support, positive parenting, and family well-being in order to help break the cycle of transgenerational violence.

Keywords: child maltreatment, maternal mental well-being, intergenerational abuse, Tirana, Albania

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Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

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Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

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Authors: Zeynep Altinkaya, Ugur Dal, Figen Dag, Dilan D. Koyuncu, Merve Turkegun

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Obesity is defined as abnormal fat-tissue accumulation as a result of imbalance between energy intake and expenditure. Since 50-70% daily energy expenditure of sedantary individuals is consumed as resting energy expenditure (REE), it takes an important place in the evaluation of new methods for obesity treatment. Also, it is known that walking is a prevalent activity in the prevention of obesity. The primary purpose of this study is to evaluate and compare the resting and walking energy expenditures of individuals with different body mass index (BMI). In this research, 4 groups are formed as underweight (BMI < 18,5 kg/m2), normal (BMI=18,5-24,9 kg/m2), overweight (BMI=25-29,9 kg/m2), and obese (BMI ≥ 30) according to BMI of individuals. 64 healthy young adults (8 man and 8 woman per group, age 18-30 years) with no known gait disabilities were recruited in this study. The body compositions of all participants were measured via bioelectric empedance analysis method. The energy expenditure of individuals was measured with indirect calorimeter method as inspired and expired gas samples are collected breath-by-breath through a special facemask. The preferred walking speed (PWS) of each subject was determined by using infrared sensors placed in 2nd and 12th meters of 14 m walkway. The REE was measured for 15 min while subjects were lying, and walking energy expenditure was measured during subjects walk in their PWS on treadmill. The gross REE was significantly higher in obese subjects compared to underweight and normal subjects (p < 0,0001). When REE was normalized to body weight, it was higher in underweight and normal groups than overweight and obese groups (p < 0,0001). However, when REE was normalized to fat-free mass, it did not differ significantly between groups. The gross walking energy expenditure in PWS was higher in obese and overweight groups than underweight and normal groups (p < 0,0001). The regression coefficient between gross walking energy expenditure and body weight was significiant among normal and obese groups (p < 0.05). It accounted for 70,5% of gross walking energy expenditure in normal group, and 57,9% of gross walking energy expenditure in obese group. It is known that obese individuals have more metabolically inactive fat-tissue compared to other groups. While excess fat-tissue increases total body weight, it does not contribute much to REE. Therefore, REE results normalized to body weight could lead to misleading results. In order to eliminate fat-mass effect on REE of obese individuals, REE normalized to fat-free mass should be used to acquire more accurate results. On the other hand, the fat-mass increasement raises energy requirement while walking to retain the body balance. Thus, gross walking energy expenditure should be taken into consideration for the evaluating energy expenditure of walking.

Keywords: body composition, obesity, resting energy expenditure, walking energy expenditure

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: Krisztina Bohacs, Klaudia Markus

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To author’s best knowledge we are in absence of studies on cognitive program evaluation and we are certainly short of programs that prove to have high effect sizes with strong retention results. The purpose of our study was to investigate the effectiveness of a comprehensive cognitive training program, namely BrainRx. This cognitive rehabilitation program target and remediate seven core cognitive skills and related systems of sub-skills through repeated engagement in game-like mental procedures delivered one-on-one by a clinician, supplemented by digital training. A larger sample of children with learning disability were given pretest and post-test cognitive assessments. The experimental group completed a twenty-week cognitive training program in a BrainRx center. A matched control group received another twenty-week intervention with Feuerstein’s Instrumental Enrichment programs. A second matched control group did not receive training. As for pre- and post-test, we used a general intelligence test to assess IQ and a computer-based test battery for assessing cognition across the lifespan. Multiple regression analyses indicated that the experimental BrainRx treatment group had statistically significant higher outcomes in attention, working memory, processing speed, logic and reasoning, auditory processing, visual processing and long-term memory compared to the non-treatment control group with very large effect sizes. With the exception of logic and reasoning, the BrainRx treatment group realized significantly greater gains in six of the above given seven cognitive measures compared to the Feuerstein control group. Our one-year retention measures showed that all the cognitive training gains were above ninety percent with the greatest retention skills in visual processing, auditory processing, logic, and reasoning. The BrainRx program may be an effective tool to establish long-term cognitive changes in case of students with learning disabilities. Recommendations are made for treatment centers and special education institutions on the cognitive training of students with special needs. The importance of our study is that targeted, systematic, progressively loaded and intensive brain training approach may significantly change learning disabilities.

Keywords: cognitive rehabilitation training, cognitive skills, learning disability, permanent structural cognitive changes

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Authors: Lihyo Sung

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Background: Children and teens in Korea experience extreme levels of academic stress. To perform better on the college entrance exam and gain admission to Korea’s most prestigious universities, they devote a significant portion of their early lives to studying. Because of their excessive preparation for entrance exams, students have become accustomed to passive and involuntary engagement. Any student starting university, however, faces new challenges that require more active involvement and self-regulated practice. As a way to tackle this issue, the study focuses on investigating the mediating effects of positive psychological capital on the relationship between self-leadership and career maturity among Korean university students. Objectives and Hypotheses: The long term goal of this study is to offer insights that promote the use of positive psychological interventions in the development and adaptation of career maturity. The current objective is to assess the role of positive psychological capital as a mediator between self-leadership and career maturity among Korean university students. Based on previous research, the hypotheses are: (a) self-leadership will be positively associated with indices of career maturity, and (b) positive psychological capital will partially or fully mediate the relationship between self-leadership and career maturity. Sample Characteristics and Sample Size: Participants in the current study consisted of undergraduate students enrolled in various courses at 5 large universities in Korea. A total of 181 students participated in the study. Methodology: A quantitative research design was adopted to test the hypotheses proposed in the current study. By using a cross-sectional approach to research, a self-administered questionnaire was used to collect data on indices of positive psychological capital, self-leadership, and career maturity. The data were analyzed by means of Cronbach's alpha, Pierson correlation test, multiple regression, path analysis, and SPSS for Windows version 22.0 using descriptive statistics. Results: Findings showed that positive psychological capital fully mediated the relationship between self-leadership and career maturity. Self-leadership significantly impacted positive psychological capital and career maturity, respectively. Scientific Contribution: The results of the current study provided useful insights into the role of psychological strengths such as positive psychological capital in improving self-leadership and career maturity. Institutions can assist in increasing positive psychological capital through the creation of positive experiences for undergraduate students, such as opportunities for coaching and mentoring.

Keywords: career maturity, mediating role, positive psychological capital, self-leadership

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Authors: Jhoga Parth, T. Nasar, K. V. Anand

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An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

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Authors: Anshita Sharma

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India is one of the countries to initiate family planning with intention to control the growing population by reducing fertility. In effort to this, India had introduced the National family planning programme in 1952. The level of unmet need in India shows a reducing trend with increasing effectiveness of family planning services as in NFHS-1 the unmet need for limiting, spacing and total was 46 percent, 14 percent & 9 percent, respectively. The demand for spacing has reduced to at 8 percent, 8 percent for limiting and total unmet need was 16 percent in NFHS-2. The total unmet need has reduced to 13 percent in NFHS-3 for all currently married women and the demand for limiting and spacing is 7 percent and 6 percent respectively. The level of unmet need in India shows a reducing trend with increasing effectiveness of family planning services. Despite the progress, there is chunk of women who are deprived of controlling unintended and unwanted pregnancies. The present paper examines the socio-cultural and economic and demographic correlates of unmet need for contraception in India. It also examines the effect of women’s autonomy and unmet need for contraception on family size among different socio-economic groups of population. It uses data from national family health survey-3 carried out in 2005-06 and employs bi-variate techniques and multivariate techniques for analysis. The multiple regression analysis has done to seek the level and direction of relationship among various socio-economic and demographic factors. The result reveals that women with higher level of education and economic status have low level of unmet need for family planning. Women living in non-nuclear family have high unmet need for spacing and women living in nuclear family have high unmet need for limiting and family size is slightly higher of women of nuclear family. In India, the level of autonomy varies at different life point; usually women with higher age enjoy higher autonomy than their junior female member in the family. The finding shows that women with higher autonomy have large family size counter to women with low autonomy have low family size. Unmet need for family planning decrease with women’s increasing exposure to mass- media. The demographic factors like experience of child loss are directly related to family size. Women who experience higher child loss have low unmet need for spacing and limiting. Thus, It is established with the help that women’s autonomy status play substantial role in fulfilling demand of contraception for limiting and spacing which affect the family size.

Keywords: family size, socio-economic correlates, unmet need for limiting, unmet need for spacing, women`s autonomy

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Authors: Amr Mohamadien, Ali Imanpour, Sylvester Agbo, Nader Yoosef-Ghodsi, Samer Adeeb

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The fracture toughness resistance curve (e.g., J-R curve and crack tip opening displacement (CTOD) or δ-R curve) is important in facilitating strain-based design and integrity assessment of oil and gas pipelines. This paper aims to present laboratory experimental data to characterize the fracture behavior of pipeline steel. The influential parameters associated with the fracture of API 5L X52 pipeline steel, including different initial crack sizes, were experimentally investigated for a single notch edge bend (SENB). A total of 9 small-scale specimens with different crack length to specimen depth ratios were conducted and tested using single edge notch bending (SENB). ASTM E1820 and BS7448 provide testing procedures to construct the fracture resistance curve (Load-CTOD, CTOD-R, or J-R) from test results. However, these procedures are limited by standard specimens’ dimensions, displacement gauges, and calibration curves. To overcome these limitations, this paper presents the use of small-scale specimens and a 3D-digital image correlation (DIC) system to extract the parameters required for fracture toughness estimation. Fracture resistance curve parameters in terms of crack mouth open displacement (CMOD), crack tip opening displacement (CTOD), and crack growth length (∆a) were carried out from test results by utilizing the DIC system, and an improved regression fitting resistance function (CTOD Vs. crack growth), or (J-integral Vs. crack growth) that is dependent on a variety of initial crack sizes was constructed and presented. The obtained results were compared to the available results of the classical physical measurement techniques, and acceptable matchings were observed. Moreover, a case study was implemented to estimate the maximum strain value that initiates the stable crack growth. This might be of interest to developing more accurate strain-based damage models. The results of laboratory testing in this study offer a valuable database to develop and validate damage models that are able to predict crack propagation of pipeline steel, accounting for the influential parameters associated with fracture toughness.

Keywords: fracture toughness, crack propagation in pipeline steels, CTOD-R, strain-based damage model

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

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Authors: Sungeun Hyun, Sooin Lee, Gyewan Moon

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Work-Family Conflict has been an active research area for the past decades. Work-Family Conflict harms individuals and organizations, it is ultimately expected to bring the cost of losses to the company in the long run. WFC has mainly focused on effects of organizational effectiveness and job attitude such as Job Satisfaction, Organizational Commitment, and Turnover Intention variables. This study is different from consequence variable with previous research. For this purpose, we selected the positive job attitude 'Work Engagement' as a consequence of WFC. This research has its primary research purpose in identifying the negative effects of the Work-Family Conflict, and started out from the recognition of the problem that the research on the direct relationship on the influence of the WFC on Work Engagement is lacking. Based on the COR(Conservation of resource theory) and JD-R(Job Demand- Resource model), the empirical study model to examine the negative effects of WFC with Emotional Exhaustion as the link between WFC and Work Engagement was suggested and validated. Also, it was analyzed how much Positive Psychological Capital may buffer the negative effects arising from WFC within this relationship, and the Mediated Moderation model controlling the indirect effect influencing the Work Engagement by the Positive Psychological Capital mediated by the WFC and Emotional Exhaustion was verified. Data was collected by using questionnaires distributed to 500 employees engaged manufacturing, services, finance, IT industry, education services, and other sectors, of which 389 were used in the statistical analysis. The data are analyzed by statistical package, SPSS 21.0, SPSS macro and AMOS 21.0. The hierarchical regression analysis, SPSS PROCESS macro and Bootstrapping method for hypothesis testing were conducted. Results showed that all hypotheses are supported. First, WFC showed a negative effect on Work Engagement. Specifically, WIF appeared to be on more negative effects than FIW. Second, Emotional exhaustion found to mediate the relationship between WFC and Work Engagement. Third, Positive Psychological Capital showed to moderate the relationship between WFC and Emotional Exhaustion. Fourth, the effect of mediated moderation through the integration verification, Positive Psychological Capital demonstrated to buffer the relationship among WFC, Emotional Exhastion, and Work Engagement. Also, WIF showed a more negative effects than FIW through verification of all hypotheses. Finally, we discussed the theoretical and practical implications on research and management of the WFC, and proposed limitations and future research directions of research.

Keywords: emotional exhaustion, positive psychological capital, work engagement, work-family conflict

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Authors: Shelley Harrington

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As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: A. Lianah, B. Peter Sopade, C. Krisantini

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Walikadep/Tetrastigma glabratum (Blume) Planch is a traditional herb that has been used by people of Blumah village; it is believed to have a stimulant effect and ailments for many illnesses. Our survey demonstrated that the people of Blumah village has exploited walikadep from Protected Forest of Mount Prau. More than 10% of 448 households at Blumah village have used walikadep as traditional herb or jamu. Part of the walikadep plants used is the liquid extract of the stem. The population of walikadep is getting scarce and it is rarely found now. The objectives of this study are to examine the stimulant effect of walikadep, to measure growth and exploitation rate of walikadep, and to find ways to effectively propagate the plants, as well as identifying the impact on the environment through field experiments and explorative survey. Stimulant effect was tested using open-field and hole-board test. Data were collected through field observation and experiment, and data were analysed using lab test and Anova. Rate of exploitation and plant growth was measured using Regression analysis; comparison of plant growth in-situ and ex-situ used descriptive analysis. The environmental impact was measured by population structure vegetation analysis method by Shannon Weinner. The study revealed that the walikadep exudates did not have a stimulant effect. Exploitation of walikadep and the long time required to reach harvestable size resulted in the scarcity of the plant in the natural habitat. Plant growth was faster in-situ than ex-situ; and fast growth was obtained from middle part cuttings treated with vermicompost. Biodiversity index after exploitation was higher than before exploitation, possibly due to the toxic and allellopathic effect (phenolics) of the plant. Based on these findings, further research is needed to examine the toxic effects of the leave and stem extract of walikadep and their allelopathic effects. We recommend that people of Blumah village to stop using walikadep as the stimulant. The local people, village government in the regional and central levels, and perhutani should do an integrated efforts to conserve walikadep through Pengamanan Terpadu Konservasi Walikadep Lestari (PTKWL) program, so this population of this plant in the natural habitat can be maintained.

Keywords: utilization, medical plants, traditional, Tetastigma glabratum

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Authors: Raymond Treacy, Paul Humphreys, Ronan McIvor, Trevor Cadden, Alan McKittrick

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This study employed event study methodology to examine the role of institutions, resources and dynamic capabilities in the relationship between the Environmental Management System ISO 14001 adoption and firm performance. Utilising financial data from 140 ISO 14001 certified firms and 320 non-certified firms, the results of the study suggested that the UK and Irish manufacturers were not implementing ISO 14001 solely to gain legitimacy. In contrast, the results demonstrated that firms were fully integrating the ISO 14001 standard within their operations as certified firms were able to improve both financial and operating performance when compared to non-certified firms. However, while there were significant and long lasting improvements for employee productivity, manufacturing cost efficiency, return on assets and sales turnover, the sample firms operating cycle and fixed asset efficiency displayed evidence of diminishing returns in the long-run, underlying the observation that no operating advantage based on incremental improvements can be everlasting. Hence, there is an argument for investing in dynamic capabilities which help renew and refresh the resource base and help the firm adapt to changing environments. Indeed, the results of the regression analysis suggest that dynamic capabilities for innovation acted as a moderator in the relationship between ISO 14001 certification and firm performance. This, in turn, will have a significant and symbiotic influence on sustainability practices within the participating organisations. The study not only provides new and original insights, but demonstrates pragmatically how firms can take advantage of environmental management systems as a moderator to significantly enhance firm performance. However, while it was shown that firm innovation aided both short term and long term ROA performance, adaptive market capabilities only aided firms in the short-term at the marketing strategy deployment stage. Finally, the results have important implications for firms operating in an economic recession as the results suggest that firms should scale back investment in R&D while operating in an economic downturn. Conversely, under normal trading conditions, consistent and long term investments in R&D was found to moderate the relationship between ISO 14001 certification and firm performance. Hence, the results of the study have important implications for academics and management alike.

Keywords: supply chain management, environmental management systems, quality management, sustainability, firm performance

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Authors: Dawit Hoyiso, Abinet Arega, Terefe Markos

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Background: - In spite of all the various programs and strategies to promote the use of research finding there is still gap between theory and practice. Difference in outcomes, health inequalities, and poorly performing health service continue to present a challenge to all nurses. A number of studies from various countries have reported that nurses’ experience of evidence-based practice is low. In Ethiopia there is an information gap on the extent of evidence based nursing practice and its associated factors. Objective: - the study aims to assess the implementation of evidence based nursing practice and associated factors among nurses in Jimma zone public hospitals. Method: - Institution based cross-sectional study was conducted from March 1-30/2015. A total of 333 sampled nurses for quantitative and 8 in-depth interview of key informants were involved in the study. Semi-structured questionnaire was adapted from funk’s BARRIER scale and Friedman’s test. Multivariable Linear regression was used to determine significance of association between dependent and independent variables. Pretest was done on 17 nurses of Bedele hospital. Ethical issue was secured. Result:-Of 333 distributed questionnaires 302 were completed, giving 90.6% response rate. Of 302 participants 245 were involved in EBP activities to different level (from seldom to often). About forty five(18.4%) of the respondents had implemented evidence based practice to low level (sometimes), one hundred three (42 %) of respondents had implemented evidence based practice to medium level and ninety seven (39.6 %) of respondents had implemented evidence based practice to high level(often). The first greatest perceived barrier was setting characteristic (mean score=26.60±7.08). Knowledge about research evidence was positively associated with implementation of evidence based nursing practice (β=0.76, P=0.008). Similarly, Place where the respondent graduated was positively associated with implementation of evidence based nursing practice (β=2.270, P=0.047). Also availability of information resources was positively associated with implementation of evidence based practice (β=0.67, P= 0.006). Conclusion: -Even though larger portion of nurses in this study were involved in evidence-based practice whereas small number of participants had implemented frequently. Evidence-based nursing practice was positively associated with knowledge of research, place where respondents graduated, and the availability of information resources. Organizational factors were found to be the greatest perceived barrier. Intervention programs on awareness creation, training, resource provision, and curriculum issues to improve implementation of evidence based nursing practice by stakeholders are recommended.

Keywords: evidence based practice, nursing practice, research utilization, Ethiopia

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Authors: Felicia N. Obialo, Aliza Wingo, Thomas Wingo

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Psychosocial factors such as personality traits and social networks influence cognitive aging and dementia outcomes both positively and negatively. The inherent complexity of these factors makes defining the underlying mechanisms of their influence difficult; however, exploring their interactions affords promise in the field of cognitive aging. The objective of this study was to elucidate some of these interactions by determining the relationship between social network size and dementia outcomes and by determining whether personality traits mediate this relationship. The longitudinal Alzheimer’s Disease (AD) database provided by Rush University’s Religious Orders Study/Memory and Aging Project was utilized to perform retrospective regression and mediation analyses on 3,591 participants. Participants who were cognitively impaired at baseline were excluded, and analyses were adjusted for age, sex, common chronic diseases, and vascular risk factors. Dementia outcome measures included cognitive trajectory, clinical dementia diagnosis, and postmortem beta-amyloid plaque (AB), and neurofibrillary tangle (NT) accumulation. Personality traits included agreeableness (A), conscientiousness (C), extraversion (E), neuroticism (N), and openness (O). The results show a positive correlation between social network size and cognitive trajectory (p-value = 0.004) and a negative relationship between social network size and odds of dementia diagnosis (p = 0.024/ Odds Ratio (OR) = 0.974). Only neuroticism mediates the positive relationship between social network size and cognitive trajectory (p < 2e-16). Agreeableness, extraversion, and neuroticism all mediate the negative relationship between social network size and dementia diagnosis (p=0.098, p=0.054, and p < 2e-16, respectively). All personality traits are independently associated with dementia diagnosis (A: p = 0.016/ OR = 0.959; C: p = 0.000007/ OR = 0.945; E: p = 0.028/ OR = 0.961; N: p = 0.000019/ OR = 1.036; O: p = 0.027/ OR = 0.972). Only conscientiousness and neuroticism are associated with postmortem AD pathologies; specifically, conscientiousness is negatively associated (AB: p = 0.001, NT: p = 0.025) and neuroticism is positively associated with pathologies (AB: p = 0.002, NT: p = 0.002). These results support the study’s objectives, demonstrating that social network size and personality traits are strongly associated with dementia outcomes, particularly the odds of receiving a clinical diagnosis of dementia. Personality traits interact significantly and beneficially with social network size to influence the cognitive trajectory and future dementia diagnosis. These results reinforce previous literature linking social network size to dementia risk and provide novel insight into the differential roles of individual personality traits in cognitive protection.

Keywords: Alzheimer’s disease, cognitive trajectory, personality traits, social network size

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Authors: Ojo Johnson Adelakun

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This study explores the long-term relationships between manufacturing output (MO) and several economic determinants, interest rate (IR), inflation rate (INF), exchange rate (EX), credit to the private sector (CPSM), gross claims on the government sector (GCGS), using monthly data from March 1966 to December 2023. Employing advanced econometric techniques including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), the analysis provides several key insights. The findings reveal a positive association between interest rates and manufacturing output, which diverges from traditional economic theory that predicts a negative correlation due to increased borrowing costs. This outcome is attributed to the financial resilience of large enterprises, allowing them to sustain investment in production despite higher interest rates. In addition, inflation demonstrates a positive relationship with manufacturing output, suggesting that stable inflation within target ranges creates a favourable environment for investment in productivity-enhancing technologies. Conversely, the exchange rate shows a negative relationship with manufacturing output, reflecting the adverse effects of currency depreciation on the cost of imported raw materials. The negative impact of CPSM underscores the importance of directing credit efficiently towards productive sectors rather than speculative ventures. Moreover, increased government borrowing appears to crowd out private sector credit, negatively affecting manufacturing output. Overall, the study highlights the need for a coordinated policy approach integrating monetary, fiscal, and financial sector strategies. Policymakers should account for the differential impacts of interest rates, inflation, exchange rates, and credit allocation on various sectors. Ensuring stable inflation, efficient credit distribution, and mitigating exchange rate volatility are critical for supporting manufacturing output and promoting sustainable economic growth. This research provides valuable insights into the economic dynamics influencing manufacturing output and offers policy recommendations tailored to South Africa’s economic context.

Keywords: domestic credit, government claims, financial variables, manufacturing output, financial analysis

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: Anya Glikman, Anastasia Gorodzeisky

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Since the late 1990th labor immigration and its consequences on the society have become one of the most frequently discussed and debated issues in Russia. Social scientists point that the negative attitudes towards immigrants among Russian majority population is widespread, and their level, at least, twice as high as their level in most other European countries. Moreover, recent study by Gorodzeisky, Glikman and Maskyleison (2014) demonstrates that the two sets of individual level predictors of anti-foreigner sentiment – socio-economic status and conservative views and ideologies – that have been repeatedly proved in research in Western countries are not effective in predicting of anti-foreigner sentiment in Post-Socialist Russia. Apparently, the social mechanisms underlying anti-foreigner sentiment in Western countries, which are characterized by stable regimes and relatively long immigration histories, do not play a significant role in the explanation of anti-foreigner sentiment in Post-Socialist Russia. The present study aims to examine alternative possible sources of anti-foreigner sentiment in Russia while controlling for socio-economic position of individuals and conservative views. More specifically, following the research literature on the topic worldwide, we aim to examine whether and to what extent human values (such as tradition, universalism, safety and power), ethnic residential segregation, fear of crime and exposure to mass media affect anti-foreigner sentiments in Russia. To do so, we estimate a series of multivariate regression equations using the data obtained from 2012 European Social Survey. The national representative sample consists of 2337 Russian born respondents. Descriptive results reveal that about 60% percent of Russians view the impact of immigrants on the country in negative terms. Further preliminary analysis show that anti-foreigner sentiments are associated with exposer to mass media as well as with fear of crime. Specifically, respondents who devoted more time watching news on TV channels and respondents who express higher levels of fear of crime tend to report higher levels of anti-immigrants sentiments. The findings would be discussed in light of sociological perspective and the context of Russian society.

Keywords: anti-immigrant sentiments, fear of crime, human values, mass media, Russia

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Authors: Xiaoyuan Chen

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Background: This study aimed to characterize the epidemiological and clinical features of five rare subtypes of hepatocellular carcinoma (HCC) and to create a competing risk nomogram for predicting cancer-specific survival. Methods: This study used the Surveillance, Epidemiology, and End Results database to analyze the clinicopathological data of 50,218 patients with classic HCC and five rare subtypes (ICD-O-3 Histology Code=8170/3-8175/3) between 2004 and 2018. The annual percent change (APC) was calculated using Joinpoint regression, and a nomogram was developed based on multivariable competing risk survival analyses. The prognostic performance of the nomogram was evaluated using the Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve. Decision curve analysis was used to assess the clinical value of the models. Results: The incidence of scirrhous carcinoma showed a decreasing trend (APC=-6.8%, P=0.025), while the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality plateau in all subtypes during the period. Clear cell carcinoma was the most common subtype (n=551, 1.1%), followed by fibrolamellar (n=241, 0.5%), scirrhous (n=82, 0.2%), spindle cell (n=61, 0.1%), and pleomorphic (n=17, ~0%) carcinomas. Patients with fibrolamellar carcinoma were younger and more likely to have non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro clinical characteristics and outcomes as classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were identified as independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice. Conclusion: The rare subtypes of HCC had distinct clinicopathological features and biological behaviors compared with classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could accurately predict prognoses, which is beneficial for individualized management.

Keywords: hepatocellular carcinoma, pathological subtype, fibrolamellar carcinoma, scirrhous carcinoma, clear cell carcinoma, spindle cell carcinoma, pleomorphic carcinoma

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Authors: Mark A. S. Laidlaw, Howard W. Mielke

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In California between the late 1920’s and 1986 the lead concentrations in urban soils and dust climbed rapidly following the deposition of greater than 387,000 tonnes of lead emitted from gasoline. Previous research indicates that when children are lead exposed around 90% of the lead is retained in their bones and teeth due to the substitution of lead for calcium. Lead in children’s bones has been shown to accumulate over time and is highest in inner-city urban areas, lower in suburban areas and lowest in rural areas. It is also known that women’s bones demineralize during pregnancy due to the foetus's high demand for calcium. Lead accumulates in women’s bones during childhood and the accumulated lead is subsequently released during pregnancy – a lagged response. This results in calcium plus lead to enter the blood stream and cross the placenta to expose the foetus with lead. In 1970 in the United States, the average age of a first‐time mother was about 21. In 2008, the average age was 25.1. In this study, it is demonstrated that in California there is a forward lagged relationship between the accumulated emissions of lead from vehicle fuel additives and later autism prevalence trends between the 1990’s and current time period. Regression analysis between a 24 year forward lag of accumulated lead emissions and autism prevalence trends in California are associated strongly (R2=0.95, p=0.00000000127). It is hypothesized that autism in genetically susceptible children may stem from vehicle fuel lead emission exposures of their mothers during childhood and that the release of stored lead during subsequent pregnancy resulted in lead exposure of foetuses during a critical developmental period. It is furthermore hypothesized that the 24 years forward lag between lead exposures has occurred because that is time period is the average length for women to enter childbearing age. To test the hypothesis that lead in mothers bones is associated with autism, it is hypothesized that retrospective case-control studies would show an association between the lead in mother’s bones and autism. Furthermore, it is hypothesized that the forward lagged relationship between accumulated historical vehicle fuel lead emissions (or air lead concentrations) and autism prevalence trends will be similar in cities at the national and international scale. If further epidemiological studies indicate a strong relationship between accumulated vehicle fuel lead emissions (or accumulated air lead concentrations) and lead in mother’s bones and autism rates, then urban areas may require extensive soil intervention to prevent the development of autism in children.

Keywords: autism, bones, lead, gasoline, petrol, prevalence

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Authors: Jonix Owino, Heather Fuller

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Refugees flee from their home countries due to civil unrest, war, persecution and migrate to Western countries such as the United States in search of a safe haven. Transitioning into a new society and culture can be challenging, thereby affecting refugee’s quality of life and well-being in the host communities. Moreover, as individuals age, they experience physical, cognitive and socioemotional changes that may impact their quality of life. However, little is known about the predictors of quality of life among aging refugees. It is not clear how quality of life varies by age, that is, between midlife refugees in comparison to their older counterparts. In addition to age, other sociodemographic factors such as gender, socioeconomic status, or country of origin are likely to have differential associations to quality of life, yet research on such variations among older refugees is sparse. Thus the present study seeks to explore factors associated with quality of life by asking the following research questions: 1) Do sociodemographic factors (such as age and gender) predict quality of life among older refugees, 2) Is there an association between social integration and quality of life, and 3) Is there an association between migratory related experiences (such as post migratory adjustments) and quality of life. The present study recruited 90 refugees (primarily originating from Bhutan, Somalia, Burundi, and Sudan) aged 50 or older living in the US. The participants completed a structured questionnaire which assessed factors such as participant’s sociodemographic attributes (e.g., age, gender, length of residence in the US, country of origin, employment, level of education, and marital status), and validated measures of social integration, post-migration living difficulties, and quality of life. Preliminary results suggest sociodemographic variability in quality of life among these refugees. Further analyses will be conducted using hierarchical regression analyses to address the following hypotheses: first, it is hypothesized that quality of life will vary by age and gender such that younger refugees and men will report higher quality of life. Second, it is expected that refugees with greater levels of social integration will also report better quality of life. Finally, post-migration factors such as language barriers and family stress are hypothesized to predict poorer quality of life. Further results will be analyzed, including potential moderating effects of age and gender, and resulting findings will be interpreted and discussed. The findings from this study have potential implications for communities on how they can better support older refugees as well as develop social programs that can effectively cater to their well-being. Conclusions will be drawn and discussed in light of policies related to both aging and refugee migration within the context of the US.

Keywords: aging out of place, migration, older refugees, quality of life, social integration

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Authors: Rosa S. Wong, Keith T.S. Tung, H.W. Tsang, Frederick K. Ho, Patrick Ip

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Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention and hyperactive-impulsive behavior. Evidence shows that ADHD and mood problems such as depression and anxiety often co-occur and yet not everyone with ADHD reported elevated emotional problems. Given that cholesterol is essential for healthy brain development including the regions governing emotion regulation, reports found lower cholesterol levels in patients with major depressive disorder and those with suicide attempt behavior compared to healthy subjects. This study explored whether ADHD adolescents experienced more emotional problems and whether emotional problems correlated with cholesterol levels in these adolescents. This study used a portion of data from the longitudinal cohort study which was designed to investigate the long-term impact of family socioeconomic status on child development. In 2018/19, parents of 300 adolescents (average age: 12.57+/-0.49 years) were asked to rate their children’s emotional problems and report whether their children had doctor-diagnosed psychiatric diseases. We further collected blood samples from 263 children to study their lipid profile (total cholesterol, high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol). Regression analyses were performed to test the relationships between variables of interest. Among 300 children, 27 (9%) had ADHD diagnosis. Analysis based on overall sample found no association between ADHD and emotional problems, but when investigating the relationship by gender, there was a significant interaction effect of ADHD and gender on emotional problems (p=0.037), with ADHD males displaying more emotional problems than ADHD females. Further analyses based on 263 children (21 with ADHD diagnosis) found significant interaction effect of ADHD and gender on total cholesterol (p=0.038) and low LDL-cholesterol levels (p=0.013) after adjusting for the child’s physical disease history. Specifically, ADHD males had significantly lower total cholesterol and low lipoprotein-cholesterol levels than ADHD females. In ADHD males, more emotional problems were associated with lower LDL-cholesterol levels (B = -4.26, 95%CI (-7.46, -1.07), p=0.013). We found preliminary support for the association between more emotional problems and lower cholesterol levels in ADHD children, especially among males. Although larger prospective studies are needed to substantiate these claims, the evidence highlights the importance of healthy lifestyle to keep cholesterol levels in normal range which can have positive effects on physical and mental health.

Keywords: attention-deficit hyperactivity disorder, cholesterol, emotional problems, adolescents

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Authors: Emilio Galdeano-Gómez, Ángeles Godoy-Durán, Juan C. Pérez-Mesa, Laura Piedra-Muñoz

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Eco-efficiency is receiving ever-increasing interest as an indicator of sustainability, as it links environmental and economic performances in productive activities. In agriculture, these indicators and their determinants prove relevant due to the close relationships in this activity between the use of natural resources, which is generally limited, and the provision of basic goods to society. In this context, various analyses have focused on eco-efficiency by considering individual family farms as the basic production unit. However, not only must the measure of efficiency be taken into account, but also the existence of a series of factors which constitute socio-economic, political-institutional, and environmental determinants. Said factors have been studied to a lesser extent in the literature. The present work analyzes eco-efficiency at a micro level, focusing on small-scale family farms as the main decision-making units in horticulture in southeast Spain, a sector which represents about 30% of the fresh vegetables produced in the country and about 20% of those consumed in Europe. The objectives of this study are a) to obtain a series of eco-efficiency indicators by estimating several pressure ratios and economic value added in farming, b) to analyze the influence of specific social, economic and environmental variables on the aforementioned eco-efficiency indicators. The present work applies the method of Data Envelopment Analysis (DEA), which calculates different combinations of environmental pressures (water usage, phytosanitary contamination, waste management, etc.) and aggregate economic value. In a second stage, an analysis is conducted on the influence of the socio-economic and environmental characteristics of family farms on the eco-efficiency indicators, as endogeneous variables, through the use of truncated regression and bootstrapping techniques, following Simar-Wilson methodology. The results reveal considerable inefficiency in aspects such as waste management, while there is relatively little inefficiency in water usage and nitrogen balance. On the other hand, characteristics, such as product specialization, the adoption of quality certifications and belonging to a cooperative do have a positive impact on eco-efficiency. These results are deemed to be of interest to agri-food systems structured on small-scale producers, and they may prove useful to policy-makers as regards managing public environmental programs in agriculture.

Keywords: data envelopment analysis, eco-efficiency, family farms, horticulture, socioeconomic features

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Authors: Min Ju Kim, Beom Jin Park, Deuk Jae Sung, Na Yeon Han, Kichoon Sim

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Purpose: The purpose of this study is to determine the significant magnetic resonance (MR) imaging factors of lateral pelvic lymph node (LPLN) on the assessment of survival outcomes of neoadjuvant combined chemotherapy and radiation therapy (CRT) in patients with mid/low rectal cancer. Materials and Methods: The institutional review board approved this retrospective study of 63 patients with mid/low rectal cancer who underwent MR before and after CRT and patient consent was not required. Surgery performed within 4 weeks after CRT. The location of LPLNs was divided into following four groups; 1) common iliac, 2) external iliac, 3) obturator, and 4) internal iliac lymph nodes. The short and long axis diameters, numbers, shape (ovoid vs round), signal intensity (homogenous vs heterogenous), margin (smooth vs irregular), and diffusion-weighted restriction of LPLN were analyzed on pre- and post-CRT images. For treatment response using size, lymph node groups were defined as group 1) short axis diameter ≤ 5mm on both MR, group 2) > 5mm change into ≤ 5mm after CRT, and group 3) persistent size > 5mm before and after CRT. Clinical findings were also evaluated. The disease-free survival and overall survival rate were evaluated and the risk factors for survival outcomes were analyzed using cox regression analysis. Results: Patients in the group 3 (persistent size >5mm) showed significantly lower survival rates than the group 1 and 2 (Disease-free survival rates of 36.1% and 78.8, 88.8%, p < 0.001). The size response (group 1-3), multiplicity of LPLN, the level of carcinoembryonic antigen (CEA), patient’s age, T and N stage, vessel invasion, perineural invasion were significant factors affecting disease-free survival rate or overall survival rate using univariate analysis (p < 0.05). The persistent size (group 3) and multiplicity of LPLN were independent risk factors among MR imaging features influencing disease-free survival rate (HR = 10.087, p < 0.05; HR = 4.808, p < 0.05). Perineural invasion and T stage were shown as independent histologic risk factors (HR = 16.594, p < 0.05; HR = 15.891, p < 0.05). Conclusion: The persistent size greater than 5mm and multiplicity of LPLN on both pre- and post-MR after CRT were significant MR factors affecting survival outcomes in the patients with mid/low rectal cancer.

Keywords: rectal cancer, MRI, lymph node, combined chemoradiotherapy

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: L. Bruckert, A. Mansourzadeh

Abstract:

The voice has a major influence on interpersonal communication in everyday life via the perception of pleasantness. The evolutionary perspective postulates that the mechanisms underlying the pleasantness judgments are universal adaptations that have evolved in the service of choosing a mate (through the process of sexual selection). From this point of view, the favorite voices would be those with more marked sexually dimorphic characteristics; for example, in men with lower voice pitch, pitch is the main criterion. On the other hand, one can postulate that the mechanisms involved are gradually established since childhood through exposure to the environment, and thus the prosodic elements could take precedence in everyday life communication as it conveys information about the speaker's attitude (willingness to communicate, interest toward the interlocutors). Our study focuses on voice pleasantness and its relationship with social impression formation, exploring both the spectral aspects (pitch, timbre) and the prosodic ones. In our study, we recorded the voices through two vocal corpus (five vowels and a reading text) of 25 French males speaking French and 25 Iranian males speaking Farsi. French listeners (40 male/40 female) listened to the French voices and made a judgment either on the voice's pleasantness or on the speaker (judgment about his intelligence, honesty, sociability). The regression analyses from our acoustic measures showed that the prosodic elements (for example, the intonation and the speech rate) are the most important criteria concerning pleasantness, whatever the corpus or the listener's gender. Moreover, the correlation analyses showed that the speakers with the voices judged as the most pleasant are considered the most intelligent, sociable, and honest. The voices in Farsi have been judged by 80 other French listeners (40 male/40 female), and we found the same effect of intonation concerning the judgment of pleasantness with the corpus «vowel» whereas with the corpus «text» the pitch is more important than the prosody. It may suggest that voice perception contains some elements invariant across culture/language, whereas others are influenced by the cultural/linguistic background of the listener. Shortly in the future, Iranian people will be asked to listen either to the French voices for half of them or to the Farsi voices for the other half and produce the same judgments as the French listeners. This experimental design could potentially make it possible to distinguish what is linked to culture and what is linked to language in the case of differences in voice perception.

Keywords: cross-cultural psychology, impression formation, pleasantness, voice perception

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

Abstract:

Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

Procedia PDF Downloads 297