Search results for: squared prediction risk

Authors: Yasir M. Alyazichi, Brian G. Jones, Errol McLean, Hamd N. Altalyan, Ali K. M. Al-Nasrawi

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The main purpose of this study is to assess the sediment quality and potential ecological risk in marine sediments in Gymea Bay located in south Sydney, Australia. A total of 32 surface sediment samples were collected from the bay. Current track trajectories and velocities have also been measured in the bay. The resultant trace elements were compared with the adverse biological effect values Effect Range Low (ERL) and Effect Range Median (ERM) classifications. The results indicate that the average values of chromium, arsenic, copper, zinc, and lead in surface sediments all reveal low pollution levels and are below ERL and ERM values. The highest concentrations of trace elements were found close to discharge points and in the inner bay, and were linked with high percentages of clay minerals, pyrite and organic matter, which can play a significant role in trapping and accumulating these elements. The lowest concentrations of trace elements were found to be on the shoreline of the bay, which contained high percentages of sand fractions. It is postulated that the fine particles and trace elements are disturbed by currents and tides, then transported and deposited in deeper areas. The current track velocities recorded in Gymea Bay had the capability to transport fine particles and trace element pollution within the bay. As a result, hydrodynamic measurements were able to provide useful information and to help explain the distribution of sedimentary particles and geochemical properties. This may lead to knowledge transfer to other bay systems, including those in remote areas. These activities can be conducted at a low cost, and are therefore also transferrable to developing countries. The advent of portable instruments to measure trace elements in the field has also contributed to the development of these lower cost and easily applied methodologies available for use in remote locations and low-cost economies.

Keywords: current track velocities, gymea bay, surface sediments, trace elements

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Authors: Gary J. Pickering, Sarah Lucas, Catherine E. Klodnicki, Nicole J. Gaudette

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Two taste pheno types that are of interest in the study of habitual diet-related risk factors and disease are 6-n-propylthiouracil (PROP) responsiveness and thermal tasting. Individuals differ considerable in how intensely they experience the bitterness of PROP, which is partially explained by three major single nucleotide polymorphisms associated with the TAS2R38 gene. Importantly, this variable responsiveness is a useful proxy for general taste responsiveness, and links to diet-related disease risk, including body mass index, in some studies. Thermal tasting - a newly discovered taste phenotype independent of PROP responsiveness - refers to the capacity of many individuals to perceive phantom tastes in response to lingual thermal stimulation, and is linked with TRPM5 channels. Thermal tasters (TTs) also experience oral sensations more intensely than thermal non-tasters (TnTs), and this was shown to associate with differences in self-reported food preferences in a previous survey from our lab. Here we report on two related studies, where we sought to determine whether PROP responsiveness and thermal tasting would associate with perceptual differences in the oral sensations elicited by sampled energy-dense foods, and whether in turn this would influence liking. We hypothesized that hyper-tasters (thermal tasters and individuals who experience PROP intensely) would (a) rate sweet and high-fat foods more intensely than hypo-tasters, and (b) would differ from hypo-tasters in liking scores. (Liking has been proposed recently as a more accurate measure of actual food consumption). In Study 1, a range of energy-dense foods and beverages, including table cream and chocolate, was assessed by 25 TTs and 19 TnTs. Ratings of oral sensation intensity and overall liking were obtained using gVAS and gDOL scales, respectively. TTs and TnTs did not differ significantly in intensity ratings for most stimuli (ANOVA). In a 2nd study, 44 female participants sampled 22 foods and beverages, assessing them for intensity of oral sensations (gVAS) and overall liking (9-point hedonic scale). TTs (n=23) rated their overall liking of creaminess and milk products lower than did TnTs (n=21), and liked milk chocolate less. PROP responsiveness was negatively correlated with liking of food and beverages belonging to the sweet or sensory food grouping. No other differences in intensity or liking scores between hyper- and hypo-tasters were found. Taken overall, our results are somewhat unexpected, lending only modest support to the hypothesis that these taste phenotypes associate with energy-dense food liking and consumption through differences in the oral sensations they elicit. Reasons for this lack of concordance with expectations and some prior literature are discussed, and suggestions for future research are advanced.

Keywords: taste phenotypes, sensory evaluation, PROP, thermal tasting, diet-related health risk

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Authors: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

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Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Sadia Ilyas, Hyunjung Kim, Rajiv R. Srivastava

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Current work has attempted to establish the linkages between circular bio-economy and recycling of copper and gold from urban mine by applying microbial activities instead of the smelter and chemical technologies. Thereafter, based on the potential of microbial approaches and research hypothesis, the structural model has been tested for a significance level of 99%, which is supported by the corresponding standardization co-efficient values. A prediction model applied to determine the recycling impact on circular bio-economy indicates to re-circulate 51,833 tons of copper and 58 tons of gold by 2030 for the production of virgin metals/raw-materials, while recycling rate of the accumulated e-waste remains to be 20%. This restoration volume of copper and gold through the microbial activities corresponds to mitigate 174 million kg CO₂ emissions and 24 million m³ water consumption if compared with the primary production activities. The study potentially opens a new window for environmentally-friendly biotechnological recycling of e-waste urban mine under the umbrella concept of circular bio-economy.

Keywords: urban mining, biobleaching, circular bio-economy, environmental impact

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Authors: Taddese Alemu Zerfu, Melaku Umeta Deressa, Kaleab Baye

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Background: Maternal and child under-nutrition is the underlying cause of 3•5 million annual deaths, globally. Anemia during pregnancy is among the leading nutritional disorders with serious short and long term consequences to both the mother and fetus. Objective: Examine the effect of dietary diversity on maternal anemia, nutritional status and key pregnancy outcomes of pregnancy. Methods: A prospective cohort study design, involving a total of 432 eligible pregnant women, in their second antenatal care visit was conducted between August 2014 to March, 2015. The individual dietary diversity status of mothers was used as the exposure variable to select, enroll and follow the mothers. All mothers were enrolled during second antenatal care visit and followed until delivery. Epi-data, SPSS and STATA software are used to enter and analyze the data. Chi-square test, independent 't'-test, and GLM are used to calculate risk, association and differences between key variables at P < 0.05. Results: Study participants did not differ in many of the basic characteristics (p < 0.05). The incidence of maternal anemia increased significantly from 28.6% to 32.1% between baseline and term. Pregnant mothers with inadequate dietary diversity groups had more (56% at baseline and 68% at term) risk of anemia than the comparison (adequate) groups, (RR, 1.56 and 1.68; 95% CI, 1.24 - 1.83 and 1.39 - 2.04). The overall incidence of still birth, low birth weight and pre-term birth was 4.5%, 9.1% and 13.6%, respectively. The variation of these outcomes was significant across study groups (P < 0.05). Conclusion and recommendations: Dietary diversity status of pregnant mothers has significant effect on the incidence of anemia and key pregnancy outcomes in resource limited settings, like rural Ethiopia. Therefore, apart from the ongoing routine IFA supplementation, special emphasis should be given to dietary diversity of mothers to improve related outcomes of pregnancy and maternal health.

Keywords: anemia, birth weight, dietary diversity, pregnancy, pregnancy outcome

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Authors: Briony Gray, Glenn Simpson, Hajira Dambha-Miller, Andrew Farmer

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Multimorbidity may be strongly affected by a variety of conditions, factors, and variables requiring higher demands on health and social care services, infrastructure, and expenses. Holding one or more conditions increases one’s risk for development of future conditions; with patients over 65 years old at highest risk. Psychosocial factors such as anxiety and depression are rising exponentially globally, which has been amplified by the COVID19 pandemic. These are highly correlated and predict poorer outcomes when held in coexistence and increase the likelihood of comorbid physical health conditions. While possible future reform of social and healthcare systems may help to alleviate some of these mounting pressures, there remains an urgent need to better understand the potential role health behaviours and psychosocial conditions - such as anxiety and depression – may have on aging populations. Using the UK healthcare scene as a lens for analysis, this study uses big data collected in the UK Longitudinal Study of Aging (ELSA) to examine the role of anxiety and depression in ageing populations (65yrs+). Using logistic regression modelling, results identify the 10 most significant variables correlated with both anxiety and depression from data categorised into the areas of health behaviour, psychosocial, socioeconomic, and life satisfaction (each demonstrated through literature review to be of significance). These are compared with wider global research findings with the aim of better understanding the areas in which social and healthcare reform can support multimorbidity interventions, making suggestions for improved patient-centred care. Scope of future research is outlined, which includes analysis of 59 total multimorbidity variables from the ELSA dataset, going beyond anxiety and depression.

Keywords: multimorbidity, health behaviours, patient centred care, psychosocial factors

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Elisavet Kechagia

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Due to the interplay of different genetic and environmental risk factors and its heterogeneous nature, the concept of attention deficit hyperactivity disorder (ADHD) has shaped controversy and conflicts, which have been, in turn, reflected in the controversial arguments about its treatment. Taking into account recent well evidence-based researches suggesting that ADHD is a condition, in which biopsychosocial factors are all weaved together, the current paper explores the multiple risk-factors that are likely to influence ADHD, with a particular focus on adolescents with ADHD who might experience comorbid social, emotional and behavioural disorders (SEBD). In the first section of this paper, the primary objective was to investigate the conflicting ideas regarding the definition, diagnosis and treatment of ADHD at an international level as well as to critically examine and identify the limitations of the two most prevailing sets of diagnostic criteria that inform current diagnosis, the American Psychiatric Association’s (APA) diagnostic scheme, DSM-V, and the World Health Organisation’s (WHO) classification of diseases, ICD-10. Taking into consideration the findings of current longitudinal studies on ADHD association with high rates of comorbid conditions and social dysfunction, in the second section the author moves towards an investigation of the transitional points −physical, psychological and social ones− that students with ADHD might experience during early adolescence, as informed by neuroscience and developmental contextualism theory. The third section is an exploration of the different perspectives of ADHD as reflected in individuals’ with ADHD self-reports and the KENT project’s findings on school staff’s attitudes and practices. In the last section, given the high rates of SEBDs in adolescents with ADHD, it is examined how cognitive behavioural therapy (CBT), coupled with other interventions, could be effective in ameliorating anti-social behaviours and/or other emotional and behavioral difficulties of students with ADHD. The findings of a range of randomised control studies indicate that CBT might have positive outcomes in adolescents with multiple behavioural problems, hence it is suggested to be considered both in schools and other community settings. Finally, taking into account the heterogeneous nature of ADHD, the different biopsychosocial and environmental risk factors that take place during adolescence and the discourse and practices concerning ADHD and SEBD, it is suggested how it might be possible to make sense of and meaningful improvements to the education of adolescents with ADHD within a multi-modal and multi-disciplinary whole-school approach that addresses the multiple problems that not only students with ADHD but also their peers might experience. Further research that would be based on more large-scale controls and would investigate the effectiveness of various interventions, as well as the profiles of those students who have benefited from particular approaches and those who have not, will generate further evidence concerning the psychoeducation of adolescents with ADHD allowing for generalised conclusions to be drawn.

Keywords: adolescence, attention deficit hyperctivity disorder, cognitive behavioural theory, comorbid social emotional behavioural disorders, treatment

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Abhimanyu Kumar, Chirag Gupta

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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Maciej Czarnecki

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Even though growth is one of the most important strategic objectives for many enterprises, we know relatively little about this phenomenon. This research contributes to broaden our knowledge of managerial consequences of growth. Scales for measuring organizational development and growing pains were developed. Conceptual model of connections among growth, organizational development, growing pains, selected development factors and financial performance were examined. The research process contained literature review, 20 interviews with managers, examination of 12 raters’ opinions, pilot research and 7 point Likert scale questionnaire research on 138 Polish enterprises employing 50-249 people which increased their employment at least by 50% within last three years. Factor analysis, Pearson product-moment correlation coefficient, student’s t-test and chi-squared test were used to develop scales. High Cronbach’s alpha coefficients were obtained. The verification of correlations among the constructs was carried out with factor correlations, multiple regressions and path analysis. When the enterprise grows, it is necessary to implement changes in its structure, management practices etc. (organizational development) to meet challenges of growing complexity. In this paper, organizational development was defined as internal changes aiming to improve the quality of existing or to introduce new elements in the areas of processes, organizational structure and culture, operational and management systems. Thus; H1: Growth has positive effects on organizational development. The main thesis of the research is that if organizational development does not catch up　with growing complexity of growing enterprise, growing pains will arise (lower work comfort, conflicts, lack of control etc.). They will exert a negative influence on the financial performance and may result in serious organizational crisis or even bankruptcy. Thus; H2: Growth has positive effects on growing pains, H3: Organizational development has negative effects on growing pains, H4: Growing pains have negative effects on financial performance, H5: Organizational development has positive effects on financial performance. Scholars considered long lists of factors having potential influence on organizational development. The development of comprehensive model taking into account all possible variables may be beyond the capacity of any researcher or even statistical software used. After literature review, it was decided to increase the level of abstraction and to include following constructs in the conceptual model: organizational learning (OL), positive organization (PO) and high performance factors (HPF). H1a/b/c: OL/PO/HPF has positive effect on organizational development, H2a/b/c: OL/PO/HPF has negative effect on growing pains. The results of hypothesis testing: H1: partly supported, H1a/b/c: supported/not supported/supported, H2: not supported, H2a/b/c: not supported/partly supported/not supported, H3: supported, H4: partly supported, H5: supported. The research seems to be of a great value for both scholars and practitioners. It proved that OL and HPO matter for organizational development. Scales for measuring organizational development and growing pains were developed. Its main finding, though, is that organizational development is a good way of improving financial performance.

Keywords: organizational development, growth, growing pains, financial performance

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Lawong Damian Bernsah

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Neglected Tropical Diseases (NTDs) are most predominant among the poor and rural populations and are endemic in 149 countries. These diseases are the most prevalent and responsible for infecting 1.4 billion people worldwide. There are 17 neglected tropical diseases recognized by WHO that constitute the fourth largest disease health and economic burden of all communicable diseases. Five of these 17 diseases are considered for the cost analysis of this paper: lymphatic filariasis, onchocerciasis, trachoma, schistosomiasis, and soil transmitted helminth infections. WHO has proposed a roadmap for eradication and elimination by 2020 and treatments have been donated through the London Declaration by pharmaceutical manufacturers. The paper estimates the cost of NTD control programme and elimination for each NTD disease and total in Nigeria. This is necessary as it forms the bases upon which programme budget and expenditure could be based. Again, given the opportunity cost the resources for NTD face it is necessary to estimate the cost so as to provide bases for comparison. Cost of NTDs control and elimination programme is estimated using the population at risk for each NTD diseases and for the total. The population at risk is gotten from the national master plan for the 2015 - 2020, while the cost per person was gotten for similar studies conducted in similar settings and ranges from US$0.1 to US$0.5 for Mass Administration of Medicine (MAM) and between US$1 to US$1.5 for each NTD disease. The combined cost for all the NTDs was estimated to be US$634.88 million for the period 2015-2020 and US$1.9 billion for each NTD disease for the same period. For the purpose of sensitivity analysis and for robustness of the analysis the cost per person was varied and all were still high. Given that health expenditure for Nigeria (% of GDP) averages 3.5% for the period 1995-2014, it is very clear that efforts have to be made to improve allocation to the health sector in general which is hoped could trickle to NTDs control and elimination. Thus, the government and the donor partners would need to step-up budgetary allocation and also to be aware of the costs of NTD control and elimination programme since they have alternative uses. Key Words: Neglected Tropical Disease, Cost Analysis, NTD Programme Control and Elimination, Cost per Person

Keywords: Neglected Tropical Disease, Cost Analysis, Neglected Tropical Disease Programme Control and Elimination, Cost per Person

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Authors: Najade Sheriff, Malaz Elsaddig, Kevin Jones

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Background: Death in the first month of life accounts for an increasing proportion of under-five mortality. Advancement to reduce this number is being made across the globe; however, progress is slowest in sub-Saharan Africa. Objectives: The study aims to identify differences between neonatal deaths of inpatient babies born in a hospital facility in rural Uganda to those of neonates admitted from the community and to explore whether they can be used to risk stratify neonatal admissions. Results: A retrospective chart review was conducted on records for neonates admitted to the Special Care Baby Unit (SCBU) Kitovu Hospital from 1st July 2016 to 21st July 2017. A total of 442 babies were admitted and the overall neonatal mortality was 24.8% (40% inpatient, 37% community, 23% hospital referrals). 40% of deaths occurred within 24 hours of admission and the majority were male (63%). 43% of babies were hypothermic upon admission, a significantly greater proportion of which were inpatient babies born in labour ward (P=0.0025). Intrapartum related death accounted for ½ of all inpatient babies whereas complications of prematurity were the predominant cause of death in the community group (37%). Severe infection does not seem like a significant factor of mortality for inpatients (2%) as it does for community admissions (29%). Furthermore, with 52.5% of community admissions weighing < 1500g, very low birth weight (VLBW) may be a significant risk factor for community neonatal death. Conclusion: The neonatal mortality rate in this study is high, and the leading causes of death are all largely preventable. A high rate of inpatient birth asphyxiation indicates the need for good quality facility-based perinatal care as well as a greater focus on the management of hypothermia, such as Kangaroo care. Moreover, a reduction in preterm deliveries is necessary to reduce associated comorbidities, and monitoring for signs of infection is especially important for community admissions.

Keywords: community, mortality, newborn, Uganda

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Authors: Dona Pamoda W. Jayatunga, Veer Bala Gupta, Eugene Hone, Ralph N. Martins

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Being a neurodegenerative disorder, Alzheimer’s disease (AD) affects a majority of the elderly demented worldwide. The key risk factors for AD are age, metabolic syndrome, allele status of APOE gene, head injuries and lifestyle. The progressive nature of AD is characterized by symptoms of multiple cognitive deficits exacerbated over time, leading to death within a decade from clinical diagnosis. However, it is revealed that AD originates via a prodromal phase that spans from one to few decades before symptoms first manifest. The key pathological hallmarks of AD brains are deposition of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFT). However, the yet unknown etiology of the disease fails to distinguish mitochondrial dysfunction between a cause or an outcome. The absence of early diagnosis tools and definite therapies for AD have permitted recruits of nutraceutical-based approaches aimed at reducing the risk of AD by modulating lifestyle or be used as preventive tools during AD prodromal state before widespread neurodegeneration begins. The objective of the present study was to investigate beneficial effects of luteolin, a plant-based flavone compound, against AD. The neuroprotective effects of luteolin on amyloid beta (Aβ) (1-42)-induced neurotoxicity was measured using cultured human neuroblastoma BE(2)-M17 cells. After exposure to 20μM Aβ (1-42) for 48 h, the neuroblastoma cells exhibited marked apoptotic death. Co-treatment of 20μM Aβ (1-42) with luteolin (0.5-5μM) significantly protected the cells against Aβ (1-42)-induced toxicity, as assessed by the MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2(4sulfophenyl)-2H-tetrazolium, inner salt; MTS] reduction assay and the lactate dehydrogenase (LDH) cell death assay. The results suggest that luteolin prevents Aβ (1-42)-induced apoptotic neuronal death. However, further studies are underway to determine its protective mechanisms in AD including the activity against tau hyperphosphorylation and mitochondrial dysfunction.

Keywords: Aβ (1-42)-induced toxicity, Alzheimer’s disease, luteolin, neuroblastoma cells

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Authors: Abdul Hakim Chikho

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A simple method of calculating satisfactory of the effect of instability on the distribution of in-plane bending moments in unbraced semi-rigidly multistory steel framed structures is presented in this paper. This method, which is a modified form of the current amplified sway method of BS5950: part1:2000, uses an approximate load factor at elastic instability in each storey of a frame which in turn dependent up on the axial loads acting in the columns. The calculated factors are then used to represent the geometrical deformations due to the presence of axial loads, acting in that storey. Only a first order elastic analysis is required to accomplish the calculation. Comparison of the prediction of the proposed method and the current BS5950 amplified sway method with an accurate second order elastic computation shows that the proposed method leads to predictions which are markedly more accurate than the current approach of BS5950.

Keywords: improved amplified sway method, steel frames, semi-rigid connections, secondary effects

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Authors: Bhavita S. Dave, Jaimin Vaidya, Chandresh H. Solanki, Atul K.

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To measure the permeability of a soil specimen, one of the basic assumptions of Darcy's law is that the soil sample should be saturated. Unlike saturated soils, the permeability of unsaturated soils cannot be found using conventional methods as it does not follow Darcy's law. Many empirical models, such as the Van Genuchten Model and Fredlund-Xing Model were suggested to predict permeability value for unsaturated soil. Such models use data from the soil-freezing characteristic curve to find fitting parameters for frozen unsaturated soils. In this study, soil specimens were subjected to 0, 1, 3, and 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and its soil freezing characteristic curves were formulated for all F-T cycles. Changes in fitting parameters and relative permeability with subsequent F-T cycles are presented in this paper for both models.

Keywords: frozen unsaturated soil, Fredlund Xing model, soil-freezing characteristic curve, Van Genuchten model

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

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Authors: Ardalan Tofighi Soleimandarabi

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Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

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Authors: Tadesse Melaku Abegaz

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Background: there was paucity of data on the self-reported adverse drug reactions (ADRs), level of adherence and clinical outcomes with antidepressants among major depressive disorder (MDD) patients in Ethiopia. Hence, the present study sought to determine the level of adherence for and clinical outcome with antidepressants and the magnitude of ADRs. Methods: A prospective cross-sectional study was employed on MDD patients from September 2016 to January 2017 at Gondar university hospital psychiatry clinic. All patients who were available during the study period were included under the study population. The Naranjo adverse drug reaction probability scale was employed to assess the adverse drug reaction. The rate of medication adherence was determined using morisky medication adherence measurement scale eight. Clinical Outcome of patients was measured by using patient health questionnaire. Multivariable logistic carried out to determine factors for adherence and patient outcome. Results: two hundred seventy patients were participated in the study. More than half of the respondents were males 122(56.2%). The mean age of the participants was 30.94 ± 8.853. More than one-half of the subjects had low adherence to their medications 124(57.1%). About 186(85.7%) of patients encountered ADR. The most common ADR was weight gain 29(13.2). Around 198(92.2%) ADRs were probable and 19(8.8%) were possible. Patients with long standing MDD had high risk of non-adherence COR: 2.458[4.413-4.227], AOR: 2.424[1.185-4.961]. More than one-half 125(57.6) of respondents showed improved outcome. Optimal level of medication adherence was found to be associated with reduced risk of progression of the diseases COR: 0.37[0.110-5.379] and AOR: 0.432[0.201-0.909]. Conclusion: Patient reported adverse drug reactions were more prevalent in major depressive disorder patients. Adherence to medications was very poor in the setup. However, the clinical outcome was relatively higher. Long standing depression was associated with non-adherence. In addition, clinical outcome of patients were affected by non-adherence. Therefore, adherence enhancing interventions should be provided to improve medication adherence and patient outcome.

Keywords: adverse drug reactions, clinical outcomes, Ethiopia, prospective study, medication adherence

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

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Authors: Nulu Nanono

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Background: The Ugandan national health policy and the national population policy all recognize the need to increase access to quality, affordable, acceptable and sustainable contraceptive services for all people but provision and utilization of quality services remains low. Two contraceptive methods are categorized as long-acting temporary methods: intrauterine contraceptive devices (IUCDs) and implants. Copper-containing IUCDs, generally available in Ministry of Health (MoH) family planning programs and is effective for at least 12 years while Implants, depending on the type, last for up to three to seven years. Uganda’s current policy and political environment are favorable towards achieving national access to quality and safe contraceptives for all people as evidenced by increasing government commitments and innovative family planning programs. Despite the increase of modern contraception use from 14% to 26%, long acting reversible contraceptive (LARC) utilization has relatively remained low with less than 5% using IUDs & Implants which in a way explains Uganda’s persistent high fertility rates. Main question/hypothesis: The purpose of the study was to examine relationship between the demographic, socio-economic characteristics of women, health facility factors and long acting reversible contraception utilization. Methodology: LARC utilization was investigated comprising of the two questions namely are you or your partner currently doing something or using any method to delay or avoid getting pregnant? And which method or methods are you using? Data for the study was sourced from the 2016 Uganda Performance Monitoring and Accountability 2020 Survey comprising of 3816 female respondents aged 15 to 49 years. The analysis was done using the Chi-squared tests and the probit regression at bivariate and multivariate levels respectively. The model was further tested for validity and normality of the residuals using the Sharipo wilks test and test for kurtosis and skewness. Results: The results showed the model the age, parity, marital status, region, knowledge of LARCs, availability of LARCs to be significantly associated with long acting contraceptive utilization with p value of less than 0.05. At the multivariate analysis level, women who had higher parities (0.000) tertiary education (0.013), no knowledge about LARCs (0.006) increases their probability of using LARCs. Furthermore while women age 45-49, those who live in the eastern region reduces their probability of using LARCs. Knowledge contribution: The findings of this study join the debate of prior research in this field and add to the body of knowledge related to long acting reversible contraception. An outstanding and queer finding from the study is the non-utilization of LARCs by women who are aware and have knowledge about them, this may be an opportunity for further research to investigate the attribution to this.

Keywords: contraception, long acting, utilization, women (15-49)

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Abraham Finkelman

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Computerized Surgical Guides have been proven to be a predictable way to perform dental implants, with a relatively high accuracy in comparison to a treatment plan. When using the CSG Bone supported, it allows us to make the necessary changes of the hard tissue prior to the implant placement and after the implant placement. The CSG gives us an accurate position for the drilling, and during the implant placement it allows us to alter the vertical position of the implant altering the final position of the abutment and avoiding any risk of any damage to the adjacent anatomical structures. Any Changes required to the bone level can be done prior to the fixation of the CSG using a reduction guide, which incur extra surgical fees and the need of a second surgical guide. Any changes of the bone level after the implant placement are at the risk of damaging the implant neck surface. The technique consists of a universal system that allows us to remove the excess bone around the implant sockets prior to the implant placement which then enables us to place the implant in the vertical position with accuracy as planned with the CSG. The systems consist of a hollow pin of different sizes and diameters. Depending on the implant system that we are using. Length sizes are from 6mm-16mm and a diameter of 2.6mm-4.8mm. Upon the completion of the drilling, the pin is then inserted into the implant socket-using the insertion tool. Once the insertion tool has unscrewed the pin, we can continue with the bone reduction. The bone reduction can be done using conventional methods upon the removal of all the excess bone around the pin. The insertion tool is then screwed into the pin and the pin is then removed. We now, have the new bone level at the crest of the implant socket which is our mark for the vertical position of the implant. In some cases, when we are locating the implant very close to anatomical structures, any form of deviation to the vertical position of the implant during the surgery, can cause damage to such anatomical structures, creating irreversible damages such as paresthesia or dysesthesia of the mandibular nerve. If we are planning for immediate loading and we have done our temporary restauration in base of our computerized plan, deviation in the vertical position of the implant will affect the position of the abutment, affecting the accuracy of the temporary prosthesis, extending the working time till we adapt the prosthesis to the new position.

Keywords: bone reduction, computer aided navigation, dental implant placement, surgical guides

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Authors: Alexander K. Guo

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PM2.5 poses a large threat to people’s health and the environment and is an issue of large concern in Beijing, brought to the attention of the government by the media. In addition, both the United States Embassy in Beijing and the government of China have increased monitoring of PM2.5 in recent years, and have made real-time data available to the public. This report utilizes hourly historical data (2008-2016) from the U.S. Embassy in Beijing for the first time. The first objective was to attempt to fit probability distributions to the data to better predict a number of days exceeding the standard, and the second was to uncover any yearly, seasonal, monthly, daily, and hourly patterns and trends that may arise to better understand of air control policy. In these data, 66,650 hours and 2687 days provided valid data. Lognormal, gamma, and Weibull distributions were fit to the data through an estimation of parameters. The Chi-squared test was employed to compare the actual data with the fitted distributions. The data were used to uncover trends, patterns, and improvements in PM2.5 concentration over the period of time with valid data in addition to specific periods of time that received large amounts of media attention, analyzed to gain a better understanding of causes of air pollution. The data show a clear indication that Beijing’s air quality is unhealthy, with an average of 94.07µg/m3 across all 66,650 hours with valid data. It was found that no distribution fit the entire dataset of all 2687 days well, but each of the three above distribution types was optimal in at least one of the yearly data sets, with the lognormal distribution found to fit recent years better. An improvement in air quality beginning in 2014 was discovered, with the first five months of 2016 reporting an average PM2.5 concentration that is 23.8% lower than the average of the same period in all years, perhaps the result of various new pollution-control policies. It was also found that the winter and fall months contained more days in both good and extremely polluted categories, leading to a higher average but a comparable median in these months. Additionally, the evening hours, especially in the winter, reported much higher PM2.5 concentrations than the afternoon hours, possibly due to the prohibition of trucks in the city in the daytime and the increased use of coal for heating in the colder months when residents are home in the evening. Lastly, through analysis of special intervals that attracted media attention for either unnaturally good or bad air quality, the government’s temporary pollution control measures, such as more intensive road-space rationing and factory closures, are shown to be effective. In summary, air quality in Beijing is improving steadily and do follow standard probability distributions to an extent, but still needs improvement. Analysis will be updated when new data become available.

Keywords: Beijing, distribution, patterns, pm2.5, trends

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Authors: P. H. G. J. Pushpakumara, A. M. P. Adikari, S. U. B. Tennakoon, Ranil Abeysinghe, Andrew Dawson

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Introduction: Deliberate Self-harm (DSH) is a global public health problem. Since 1950, suicide rates in Sri Lanka are among the highest national rates in the world. It has become an increasingly common response to emotional distress in young adults. However, it remains unclear the reason for this occurrence. Objectives: The descriptive component of this study was conducted to identify of epidemiological pattern of DSH and suicide in Kurunegala District (KD). Assessment of association between DSH socio-cultural, economical and psychological factors were the objectives of the case control component. Methods: Prospective data collection of DSH and suicide was conducted at all (46) hospitals and all (28) police stations in the KD for thirty six months, from 1st January 2011, as the descriptive component. Case control component was conducted at T.H. Kurunegala (THK) for eighteen months duration, from 1st July 2011. Cases (n=439) were randomly selected from a block of 7 consecutively admitted consenting DSP patients using a computer program. Age, sex and residential divisional secretariat division one to one matched, individuals were randomly selected as controls from patients presented to Out Patient Department. Structured Clinical Interview for DSM-IV-TR Axis I and II Disorders was used to diagnose psychiatric disorders. Validated tools were used to measure other constructs. Results: Suicide incidences in KD were, 21.6, 20.7 and 24.3 per 100,000 population in 2011- 2013 (Male:female ratio 5.7, 4.4 and 6.4). 60% of suicides were due to poisoning. DSP incidences were 205.4, 248.3 and 202.5 per 100,000 population in 2011- 2013. Highest age standardized male DSP incidence reported in 20-24 years (769.6/100,000) and female in 15-19 years (1304.0/100,000). Bing married (age >25 years), monthly family income less than Rs.30,000, not achieving G.C.E (O/L) qualifications, a school drop-out, not in a permanent position in occupation, being a manual and an own account worker, were significantly associated with DSP. Perceiving the quality of relationship as bad or very bad with parents, spouse/ girlfriend/ boyfriend and sibling as associated with 8, 40 and 10.5 times higher risk respectively. Feeling and experiences of neglect, other emotional abuses, feeling of insecurity with the family, in child hood, and having a contact history carried an excess risk for DSP. Cases were less likely to seek help. Further, they had significantly lower scores for life skills and life skills application ability. 25.6% DSH patients had DSM TR axis-I and/or TR axis-II disorder. The presence of psychiatric disorder carried 7.7 (95% CI 4.3 – 13.8) times higher risk for DSP. Conclusion: In general, pattern of DSH and suicide is, unique, different from developed, upper and middle income and lower and middle income countries. It is a learned way of expressing emotions in difficult situations of vulnerable people.

Keywords: deliberate self-harm, help-seeking, life-skills, mental- health, psychological, social, suicide

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