Search results for: game outcome prediction

Authors: Saima Ali, Liaqat Ali, Nasir Orakzai

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Background: Hydronephrosis is the most common abnormal finding in the urinary tract on prenatal screening with Ultrasonography. The prenatal hydronephrosis is a diagnostic dilemma in differentiating between obstructive variant versus physiologic hydronephrosis. The assessment and prompt diagnosis of prenatal hydronephrosis is important because of the fact that untreated obstructive hydronephrosis usually leads to recurrent UTI, Urosepsis, deterioration of renal functions, non-functioning kidneys, and even end-stage renal disease. Objectives: To determine the etiology and outcome of postnatal treatment of children with prenatal hydronephrosis in two teaching hospitals of Khyber Pakhtunkhwa (KPK) Methods: It is a multicentric descriptive study that was conducted in department of Paediatrics in Kuwait teaching hospital Peshawar and Department of Urology in Institute of Kidney Diseases Hayatabad Medical Complex Peshawar from January 2008 till December 2010. Total numbers of 64 neonates were included in the study with the mean follow-up of 14.5 months. All the diagnostic data in prenatal, postnatal data, and operative and non-operative data were collected on structured Proforma and was analyzed on SPSS version 17. Results: Out of 64 patients, 39 (60.9 %) were male while 25 were female. 52 patients had unilateral while 12 patients had bilateral hydronephrosis. Based upon prenatal USG in term of AP diameter, 37 (57 %) patients had mild hydronephrosis (5-10 mm AP diameter), 14 patients had moderate hydronephrosis (10-15 mm AP diameter) while 13 patients had gross hydronephrosis (More than 15mm). Regarding etiology, 44(76 %) patients were labeled as physiologic hydronephrosis, 11 patients (9.3%) with PUJ obstruction, 5 patients with Vesicoureteric reflux (VUR) and 4 patients with posterior urethral valves. Surgery was performed in total of 15 (23.4%) patients that included open Pyeloplasty in 11 patients, Vesicostomy followed by posterior valve fulguration in 4 patients. All the patients of VUR treated medically. The severity in the grade of prenatal hydronephrosis is significantly associated with the need for definitive urological surgery p < 0.005. Ancillary procedures like percutaneous nephrostomy (PCN) were inserted 7 patients. Conclusions: Prenatal hydronephrosis is a common ailment associated with significant morbidity. Physiological Hydronephrosis and VUR can be successfully treated with medical treatment. However obstructive PUJ obstructions and posterior urethral valves require surgical correction with a good success rate.

Keywords: prenatal hydronephrosis, Pelviureteric Junction (PUJ) Obstruction, vesicoureteric reflux, posterior urethral valve, renography

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Authors: Khosro Barkhordari, Fateme Sadr, Mina Pashang

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Back ground: Blood transfusion is one of the major issues in cardiac surgery patients. Transfusing patients based on fixed cut-off points of hemoglobin is the current protocol in most institutions. The hemoglobin level of 7- 10 has been suggested for blood transfusion in cardiac surgery patients. We aimed to evaluate if blood transfusion based on change in percentage of hematocrit has different outcomes. Methods: In this retrospective cohort study, we investigated the early postoperative outcome of cardiac surgery patients who received blood transfusions at Tehran Heart Center Hospital, IRAN. We reviewed and analyzed the basic characteristics and clinical data of 700 patients who met our exclusion and inclusion criteria. The two groups of blood transfused patients were compared, those who have 30-50 percent decrease in basal hematocrit versus those with 10 -29 percent decrease. Results: This is ongoing study, and the results would be completed in two weeks after analysis of the date. Conclusion: Early analysis has shown no difference in early post-operative outcomes between the two groups, but final analysis will be completed in two weeks. 1-Department of Anesthesiology and Critical Care, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, IRAN 2- Department of Research, Tehran Heart Center, Tehran, IRAN Quantitative variables were compared using the Student t-test or the Mann‐Whitney U test, as appropriate, while categorical variables were compared using the χ2 or the Fisher exact test, as required. Our intention was to compare the early postoperative outcomes between the two groups, which include 30 days mortality, Length of ICU stay, Length of hospital stay, Intubation time, Infection rate, acute kidney injury, and respiratory complications. The main goal was to find if transfusing blood based on changes in hematocrit from a basal level was better than to fixed cut-off point regarding early post-operative outcomes. This has not been studied enough and may need randomized control trials.

Keywords: post-operative, cardiac surgery, outcomes, blood transfusion

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Authors: Stephanie Yun Yu Law

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Background: This study aims to investigate into communication between trainee doctors and patients, especially how doctor’s reaction to patient’s emotional issues expressed in the consultation affect patient’s satisfaction. Objectives: Thus, there are three aims in this study, 1.) how do trainee doctors react to patients emotional cues in OSCE station? 2.) Any differences in the respond type to emotional cues between first year students and third year students? 3.) Is response type (reducing space) related to OSCE outcome (patient satisfaction and expert rating)? Methods: Fifteen OSCE stations was videotaped, in which 9 were stations with first-year students and 6 were with third-year students. OSCE outcomes were measured by Communication Assessment Tool and Examiners Checklist. Analyses: All patient’s cues/concerns and student’s reaction were coded by Verona Coding Definitions of Emotional Sequence. Descriptive data was gathered from Observer XT and logistic regression (two-level) was carried out to see if occurrence of reducing space response can be predicted by OSCE outcomes. Results: Reducing space responses from all students were slightly less than a half in total responses to patient’s cues. The mean percentage of reducing space behaviours was lower among first year students when compared to third year students. Patient’s satisfaction significantly (p<0.05) and negatively predicted reducing space behaviours. Conclusions: Most of the medical students, to some extent, did not provide adequate responses for patient’s emotional cues. But first year students did provide more space for patients to talk about their emotional issues when compared to third year students. Lastly, patients would feel less satisfied if trainee doctors use more reducing space responses in reaction to patient’s expressed emotional cues/concerns. Practical implications: Firstly, medical training programme can be tailored on teaching students how to detect and respond appropriately to emotional cues in order to improve underperformed student’s communication skills in healthcare setting. Furthermore, trainee doctor’s relationship with patients in clinical practice can also be improved by reacting appropriately to patient’s emotive cues in consultations (such as limit the use of reducing space behaviours).

Keywords: doctors-patients communication, applied clinical psychology, health psychology, healthcare professionals

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Authors: Yen Ling Liu, Shu-Fen Wu, Chen-Fuh Lam, I-Ling Tsai, Chia-Yu Chen

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Purpose: Nurse anesthetists are confronting extraordinarily high job stress in their daily practice, deriving from the fast-track anesthesia care, risk of perioperative complications, routine rotating shifts, teaching programs and interactions with the surgical team in the operating room. This study investigated the influence of work stress on the burnout and turnover intention of nurse anesthetists in a regional general hospital in Southern Taiwan. Methods: This was a descriptive correlational study carried out in 66 full-time nurse anesthetists. Data was collected from March 2017 to June 2017 by in-person interview, and a self-administered structured questionnaire was completed by the interviewee. Outcome measurements included the Practice Environment Scale of the Nursing Work Index (PES-NWI), Maslach Burnout Inventory (MBI) and nursing staff turnover intention. Numerical data were analyzed by descriptive statistics, independent t test, or one-way ANOVA. Categorical data were compared using the chi-square test (x²). Datasets were computed with Pearson product-moment correlation and linear regression. Data were analyzed by using SPSS 20.0 software. Results: The average score for job burnout was 68.7916.67 (out of 100). The three major components of burnout, including emotional depletion (mean score of 26.32), depersonalization (mean score of 13.65), and personal(mean score of 24.48). These average scores suggested that these nurse anesthetists were at high risk of burnout and inversely correlated with turnover intention (t = -4.048, P < 0.05). Using linear regression model, emotional exhaustion and depersonalization were the two independent factors that predicted turnover intention in the nurse anesthetists (19.1% in total variance). Conclusion/Implications for Practice: The study identifies that the high risk of job burnout in the nurse anesthetists is not simply derived from physical overload, but most likely resulted from the additional emotional and psychological stress. The occurrence of job burnout may affect the quality of nursing work, and also influence family harmony, in turn, may increase the turnover rate. Multimodal approach is warranted to reduce work stress and job burnout in nurse anesthetists to enhance their willingness to contribute in anesthesia care.

Keywords: anesthesia nurses, burnout, job, turnover intention

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Authors: Frida Carrillo Morales, Maria Maricela Carrasco Yépez, Saúl Rojas Hernández

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Naegleria fowleri is the causative agent of primary amebic meningoencephalitis, this disease is acute and fulminant that affects humans. It has been reported that despite the existence of therapeutic options against this disease, its mortality rate is 97%. Therefore, the need arises to have vaccines that confer protection against this disease and, in addition to developing adjuvants to enhance the immune response. In this regard, in our work group, we obtained a peptide designed from the membrane protein MP2CL5 of Naegleria fowleri called Smp145 that was shown to be immunogenic; however, it would be of great importance to enhance its immunological response, being able to co-administer it with a non-toxic adjuvant. Therefore, the objective of this work was to carry out the bioinformatic design of a peptide of the Naegleria fowleri membrane protein MP2CL5 conjugated with a non-toxic modified adjuvant from the native A1 structure of Cholera Toxin. For which different bioinformatics tools were used to obtain a model with a modification in amino acid 61 of the A1 subunit of the CT (CTA1), to which the Smp145 peptide was added and both molecules were joined with a 13-glycine linker. As for the results obtained, the modification in CTA1 bound to the peptide produces a reduction in the toxicity of the molecule in in silico experiments, likewise, the prediction in the binding of Smp145 to the receptor of B cells suggests that the molecule is directed in specifically to the BCR receptor, decreasing its native enzymatic activity. The stereochemical evaluation showed that the generated model has a high number of adequately predicted residues. In the ERRAT test, the confidence with which it is possible to reject regions that exceed the error values was evaluated, in the generated model, a high score was obtained, which determines that the model has a good structural resolution. Therefore, the design of the conjugated peptide in this work will allow us to proceed with its chemical synthesis and subsequently be able to use it in the mouse meningitis protection model caused by N. fowleri.

Keywords: immunology, vaccines, pathogens, infectious disease

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Authors: Beaula, M. Kruger, Silindisipho, T. Belot

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Small informal retailers are considered one of the most important features of developing countries around the world. Those small informal retailers form part of the local communities in South African townships and are estimated to be more than 100,000 across the country. The township economic landscape has changed over time in South Africa. The traditional small informal retailers in South African Townships have been faced with numerous challenges of increasing competition; an increase in the number of local retail shops and foreign-owned shops. There is evidence that the South African personal and disposable income has increased amongst black African consumers. Historically, people residing in townships were restricted to informal retail shops; however, this has changed due to the growing number of formal large retail chains entering into the township market. The larger retail chains are aware of the improved income levels of the middle-income townships residence and as a result, larger retailers have followed certain strategies such as; (1) retail format development; (2) diversification growth strategy; (3) market penetration growth strategy and (4) market expansion. This research did a comparative analysis between the different retail models developed by Pick n Pay, Spar and Shoprite. The research methodology employed for this study was of a qualitative nature and made use of a case study to conduct a comparative analysis between larger retailers. A questionnaire was also designed to obtain data from existing smaller retailers. The study found that larger retailers have developed smaller retail formats to compete with the traditional smaller retailers operating in South African townships. Only one out of the two large retailers offers entrepreneurs a franchise model. One of the big retailers offers the opportunity to employ between 15 to 20 employees while the others are subject to the outcome of a feasibility study. The response obtained from the entrepreneurs in the townships were mixed, while some found their presence as having a “negative impact,” which has increased competition; others saw them as a means to obtain a variety of products. This research found that the most beneficial retail model for both bigger retail and existing and new entrepreneurs are from Pick n Pay. The other retail format models are more beneficial for the bigger retailers and not to new and existing entrepreneurs.

Keywords: Pick n Pay, retailers, shoprite, spar, townships

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Cherrie Mae S. Sia, Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Background: Parkinson’s disease (PD) is a chronic progressive, neurodegenerative disorder known for its motor symptoms such as bradykinesia, resting tremor, muscle rigidity, and postural instability. Patients with PD also experience non-motor symptoms (NMS) such as depression, fatigue, and sleep disturbances that are most of the time unrecognized by clinicians. This may be due to the lack of spontaneous reports from the patients or partly because of the lack of systematic questioning from the healthcare professional. There is limited data with regards to these NMS especially that of Filipino patients with PD. Objectives: This study aims to determine the non-motor symptoms of Filipino patients with Parkinson’s disease. Materials and Methods: This is a prospective, cohort study involving thirty-four patients of Filipino-descent diagnosed with PD in three out-patient clinics in Cebu City from April to September 2014. Each patient was interviewed using the Non-Motor Symptom Scale (NMSS). A Cebuano version of the NMSS was also provided for the non-English speaking patients. Interview time was approximately ten to fifteen minutes for each respondent. Results: Of the thirty-four patients with Parkinson’s disease, majority was noted to be males (N=19) and the disease was noted to be more prevalent in patients with a mean age of 62 (SD±9) years old. Hypertension (59%) and diabetes mellitus (29%) were the common co-morbidities in the study population. All patients presented more than one NMS, with insomnia (41.2%), poor memory (23.5%) and depression (14.7%) being the first non-motor symptoms to occur. Symptoms involving mood/cognition (mean=2.21), and attention/memory (mean=2.05) were noted to be the most frequent and of moderate severity. Based on the NMSS, the symptoms that were noted to be mild and often to occur were those that involved the mood/cognition (score=3.84), attention/memory (score=3.50), and sleep/fatigue (score=3.00) domains. Levodopa-Carbidopa, Ropinirole, and Pramipexole were the most frequently used medications in the study population. Conclusion: Non-motor symptoms (NMS) are common in patients with Parkinson’s disease (PD). They appear at the time of diagnosis of PD or even before the motor symptoms manifest. The earliest non-motor symptoms to occur are insomnia, poor memory, and depression. Those pertaining to mood/cognition and attention/memory are the most frequent NMS and they are of moderate severity. Identifying these NMS by doing a questionnaire-guided interview such as the Non-Motor Symptom Scale (NMSS) before they can become more severe and affect the patient’s quality of life is a must for every clinician caring for a PD patient. Early treatment and control of these NMS can then be given, hence, improving the patient’s outcome and prognosis.

Keywords: non motor symptoms, Parkinson's Disease, insomnia, depression

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Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Noor Suhaida Kasri

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In the last three decades, Malaysia has developed fundamental legal and regulatory structures that aim to accommodate and facilitate the growth of Islamic banking and finance industry. Important building blocks have been put in place, to cite a few, the elevation of the position of the Malaysian Central Bank Shariah Advisory Council (SAC) as the apex advisory body and the empowerment of their Shariah resolutions through the Central Bank Act 1958; the promulgation of the Islamic Financial Services Act 2013 that regulate and govern Islamic finance market with a robust statutory requirement of Shariah governance and Shariah compliance. Notwithstanding these achievements, enforceability of Shariah-compliant contract remains a contentious subject. The validity of Al Bai Bithaman Ajil concept that was commonly used by the Islamic financial institutions in their financing facilities structures and documentation has been unabatedly challenged by the customers in courts. The challenge was due to the manner in which the Al Bai Bithaman Ajil transactions were carried out. Due to this legal challenge, Al Bai Bithaman Ajil financing structure seems to no longer be the practitioners’ favourite in Malaysia, though its substitute tawarruq and commodity murabahah financing structure may potentially face similar legal challenges. This paper examines the legal challenges affecting the enforceability of these underlying Shariah contracts. The examination of these cases highlights the manner in which these contracts were being implemented and applied by the Malaysian Islamic financial institutions that triggered Shariah and legal concern. The analysis also highlights the approach adopted by the Malaysian courts in determining the Shariah issues as well as the SAC in ascertaining the rulings on the Shariah issues referred to it by the courts. The paper adopts a qualitative research methodology by using textual and documentary analysis approach. The outcome of this study underlines factors that require consideration by industry stakeholder in order to ameliorate the efficacy of the existing building blocks that would eventually strengthens the validity and enforceability of Shariah-compliant contracts. This, in the long run, will further reinforce financial stability and trust into the Islamic banking and finance industry in Malaysia.

Keywords: enforceability of Shariah compliant contract, legal challenge, legal and regulatory framework, Shariah Advisory Council

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Siddharth Jain, Abhenil Mittal, Surendra Kumar Sharma

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Background: With its recent emergence and re-emergence, dengue has become a major international public health concern, imposing significant financial burden especially in developing countries. Despite aggressive control measures in place, India experienced one of its largest outbreaks in 2015 with Delhi being most severely affected. There is a lack of reliable predictors of disease severity and mortality in dengue. The present study was carried out to identify these predictors during the 2015 outbreak. Methods: This prospective observational study conducted at an apex tertiary care center in Delhi, India included confirmed adult dengue patients admitted between August-November 2015. Patient demographics, clinical details, and laboratory findings were recorded in a predesigned proforma. Appropriate statistical tests were used to summarize and compare the clinical and laboratory characteristics and derive predictors of mortality and severe disease, while developing a clinical risk score for mortality. Serotype analysis was also done for 75 representative samples to identify the dominant serotypes. Results: Data of 369 patients were analyzed (mean age 30.9 years; 67% males). Of these, 198 (54%) patients had dengue fever, 125 (34%) had dengue hemorrhagic fever (DHF Grade 1,2)and 46 (12%) developed dengue shock syndrome (DSS). Twenty two (6%) patients died. Late presentation to the hospital (≥5 days after onset) and dyspnoea at rest were identified as independent predictors of severe disease. Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. A clinical risk score was developed (12*age + 14*sensorium + 10*dyspnoea) which, if ≥ 22, predicted mortality with a high sensitivity (81.8%) and specificity (79.2%). The predominant serotypes in Delhi (2015) were DENV-2 and DENV-4. Conclusion: Age ≥ 24 years, dyspnoea at rest and altered sensorium were identified as independent predictors of mortality. Platelet counts did not determine the outcome in dengue patients. Timely referral/access to health care is important. Development and use of validated predictors of disease severity and simple clinical risk scores, which can be applied in all healthcare settings, can help minimize mortality and morbidity, especially in resource limited settings.

Keywords: dengue, mortality, predictors, severity

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Authors: E. Ghoneim, C. Narron, I. Iqbal, I. Hassan, E. Hammam

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The scarcity of water is becoming a more prominent threat, especially in areas that are already arid in nature. Although the Kingdom of Saudi Arabia (KSA) is an arid country, its southwestern region offers a high variety of botanical landscapes, many of which are wooded forests, while the eastern and northern regions offer large areas of groundwater irrigated farmlands. At present, some parts of KSA, including forests and farmlands, have witnessed protracted and severe drought due to change in rainfall pattern as a result of global climate change. Such prolonged drought that last for several consecutive years is expected to cause deterioration of forested and pastured lands as well as cause crop failure in the KSA (e.g., wheat yield). An analysis to determine vegetation drought vulnerability and severity during the growing season (September-April) over a fourteen year period (2000-2014) in KSA was conducted using MODIS Terra imagery. The Vegetation Condition Index (VCI), derived from the Normalized Difference Vegetation Index (NDVI), and the Temperature Condition Index (TCI), derived from the Land Surface Temperature (LST) data was extracted from MODIS Terra Images. The VCI and TCI were then combined to compute the Vegetation Health Index (VHI). The VHI revealed the overall vegetation health for the area under investigation. A preliminary outcome of the modeled VHI over KSA, using averaged monthly vegetation data over a 14-year period, revealed that the vegetation health condition is deteriorating over time in both naturally vegetated areas and irrigated farmlands. The derived drought map for KSA indicates that both extreme and severe drought occurrences have considerably increased over the same study period. Moreover, based on the cumulative average of drought frequency in each governorate of KSA it was determined that Makkah and Jizan governorates to the east and southwest, witness the most frequency of extreme drought, whereas Tabuk to the northwest, exhibits the less extreme drought frequency. Areas where drought is extreme or severe would most likely have negative influences on agriculture, ecosystems, tourism, and even human welfare. With the drought risk map the kingdom could make informed land management decisions including were to continue with agricultural endeavors and protect forested areas and even where to develop new settlements.

Keywords: drought, vegetation health condition, TCI, Saudi Arabia

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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a systematic observation from a defined time of origin up to certain failure or censor is known as survival data. Survival analysis is a major area of interest in biostatistics and biomedical researches. At the heart of understanding, the most scientific and medical research inquiries lie for a causality analysis. Thus, the main concern of this study is to investigate the causal effect of treatment on survival time conditional to the possibly time-varying covariates. The theory of causality often differs from the simple association between the response variable and predictors. A causal estimation is a scientific concept to compare a pragmatic effect between two or more experimental arms. To evaluate an average treatment effect on survival outcome, the estimating equation was adjusted for time-varying covariates under the semi-parametric transformation models. The proposed model intuitively obtained the consistent estimators for unknown parameters and unspecified monotone transformation functions. In this article, the proposed method estimated an unbiased average causal effect of treatment on survival time of interest. The modified estimating equations of semiparametric transformation models have the advantage to include the time-varying effect in the model. Finally, the finite sample performance characteristics of the estimators proved through the simulation and Stanford heart transplant real data. To this end, the average effect of a treatment on survival time estimated after adjusting for biases raised due to the high correlation of the left-truncation and possibly time-varying covariates. The bias in covariates was restored, by estimating density function for left-truncation. Besides, to relax the independence assumption between failure time and truncation time, the model incorporated the left-truncation variable as a covariate. Moreover, the expectation-maximization (EM) algorithm iteratively obtained unknown parameters and unspecified monotone transformation functions. To summarize idea, the ratio of cumulative hazards functions between the treated and untreated experimental group has a sense of the average causal effect for the entire population.

Keywords: a modified estimation equation, causal effect, semiparametric transformation models, survival analysis, time-varying covariate

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Authors: Thanooja Naushad, Meena Natarajan, Tushar Vasant Kulkarni

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Background: The Lacey Assessment of Preterm Infants (LAPI) is used in clinical practice to identify premature babies at risk of neuromotor impairments, especially cerebral palsy. This study attempted to find the validity of the Lacey assessment of preterm infants to predict neuromotor outcomes of premature babies at 12 months corrected age and to compare its predictive ability with the brain ultrasound. Methods: This prospective cohort study included 89 preterm infants (45 females and 44 males) born below 35 weeks gestation who were admitted to the neonatal intensive care unit of a government hospital in Dubai. Initial assessment was done using the Lacey assessment after the babies reached 33 weeks postmenstrual age. Follow up assessment on neuromotor outcomes was done at 12 months (± 1 week) corrected age using two standardized outcome measures, i.e., infant neurological international battery and Alberta infant motor scale. Brain ultrasound data were collected retrospectively. Data were statistically analyzed, and the diagnostic accuracy of the Lacey assessment of preterm infants (LAPI) was calculated -when used alone and in combination with the brain ultrasound. Results: On comparison with brain ultrasound, the Lacey assessment showed superior specificity (96% vs. 77%), higher positive predictive value (57% vs. 22%), and higher positive likelihood ratio (18 vs. 3) to predict neuromotor outcomes at one year of age. The sensitivity of Lacey assessment was lower than brain ultrasound (66% vs. 83%), whereas specificity was similar (97% vs. 98%). A combination of Lacey assessment and brain ultrasound results showed higher sensitivity (80%), positive (66%), and negative (98%) predictive values, positive likelihood ratio (24), and test accuracy (95%) than Lacey assessment alone in predicting neurological outcomes. The negative predictive value of the Lacey assessment was similar to that of its combination with brain ultrasound (96%). Conclusion: Results of this study suggest that the Lacey assessment of preterm infants can be used as a supplementary assessment tool for premature babies in the neonatal intensive care unit. Due to its high specificity, Lacey assessment can be used to identify those babies at low risk of abnormal neuromotor outcomes at a later age. When used along with the findings of the brain ultrasound, Lacey assessment has better sensitivity to identify preterm babies at particular risk. These findings have applications in identifying premature babies who may benefit from early intervention services.

Keywords: brain ultrasound, lacey assessment of preterm infants, neuromotor outcomes, preterm

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Authors: Gayathri.G, Hemamalini.A.J, Chandrasekaran.A

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Problem statement: Nutritional deficiency, especially calcium, may lead to poor bone formation and mineralization. Although there are plenty of synthetic supplements available, it is essential to make a calcium rich food supplement accessible to combat calcium deficiency that could be readily prepared at the household level. Thus the current study aimed to formulate and standardize an indigenous low-cost calcium-rich food supplement and to study the impact of supplementation on the bone resorption and formation markers. Methods: A Randomized controlled trial was conducted with 60 subjects distributed equally in control and experimental groups, including perimenopausal and postmenopausal women. A plant-based calcium-rich product was developed and supplemented in form of balls as a midmorning and evening snack by addition of optimized proportions of leaves of Sesbania Grandiflora, seeds of Sesamum indicum, Eleusine coracana, Glycine max, Vigna mungo for a period of 6 months. Postmenopausal and perimenopausal women received 1200mg and 800mg of calcium per day from the supplemented, respectively. Outcome measures like serum calcium; betacrosslaps (bone resorption marker) and total P1NP (bone absorption marker) were assessed after 3 months and after 6 months. Results: There were no significant changes seen in the serum calcium and total P1NP levels (bone formation marker) among the subjects during the supplementation period. The bone resorption marker (betacrosslaps) reduced in all the groups and the reduction (0.32 ± 0.130 ng/ml to 0.25 ± 0.130 ng/ml) was found to be statistically highly significant (p < 0.01) in experimental group of perimenopausal subjects and significant (p < 0.05) in experimental group of postmenopausal subjects (1.11 ± 0.290 ng/ml to 0.42 ± 0.263 ng/ml). Conclusion: With the current severe calcium deficiency in the Indian population, integrating low-cost, calcium-rich native foods that could be readily prepared at household level would be useful in raising the nutritional consumption of calcium, which would, in turn, decrease bone turnover.

Keywords: calcium, sesbania grandiflora, sesamum indicum, eleusine coracana, glycine max, vigna mungo, postmenopause, perimenopause, bone resorption, bone absorption, betacrosslaps, total P1NP

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Authors: Caroline Nnokwe, Iheanyi Eneremadu

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Teachers and principals are vital and integral parts of the educational system. For educational objectives to be met, the role of teachers and the functions of the principals are not to be overlooked. However, the inability of teachers and principals to carry out their roles effectively has impacted the outcome of the students’ performance. The study, therefore, examined teachers’ roles and principal’s administrative functions as correlates of effective academic performance of public secondary school students in Imo state, Nigeria. Four research questions and two hypotheses guided the study. The study adopted a correlation research design. The sample size was 5,438 respondents via the Yaro-Yamane technique, which consists of 175 teachers, 13 principals and 5,250 students using the proportional stratified random sampling technique. The instruments for data collection were a researcher-made questionnaire titled Teachers’ Role/Principals’ Administrative Functions Questionnaire (TRPAFQ) with a Cronbach Alpha coefficient of .82 and student's internal results obtained from the school authorities. Data collected were analyzed using the Pearson product-moment correlation coefficient and simple linear regression. Research questions were answered using Pearson Product Moment Correlation statistics, while the hypotheses were tested at 0.05 level of significance using regression analysis. The findings of the study showed that the educational qualification of teachers, organizing, and planning correlated student’s academic performance to a great extent, while availability and proper use of instructional materials by teachers correlated the academic performance of students to a very high extent. The findings also revealed that there is a significant relationship between teachers’ role, principals’ administrative functions and student’s academic performance of public secondary schools in Imo State, The study recommended among others that there is the need for government, through the ministry of education, and education authorities to adequately staff their supervisory department in order to carry out proper supervision of secondary school teachers, and also provide adequate instructional materials to ensure greater academic performance among secondary school students of Imo state, Nigeria.

Keywords: instructional materials, principals’ administrative functions, students’ academic performance, teacher role

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Authors: Jamel Slaughter

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Father involvement across the development of a child has been linked to children’s psychological adjustment, fewer behavioral problems, and higher educational attainment. Conversely, there is much less research that highlights father involvement in relation to childhood development during early childhood period prior to preschool age (ages 1-3 years). Most research on fathers and child outcomes have been limited by its focus on the stages of adolescence, middle childhood, and infancy. This study examined the influence of father involvement, during the toddler stage, on 5th grade cognitive development, rule-breaking, and behavior outcomes measured by Child Behavior Checklist (CBCL) scores. Using data from the Early Head Start Research and Evaluation (EHSRE) Study, 1996-2010: United States, a total of 3,001 children and families were identified in 17 sites (cities), representing a diverse demographic sample. An independent samples t-test was run to compare cognitive development, aggressive, and rule-breaking behavior mean scores among children who had early continuous father involvement for the first 14 – 36 months to children who did not have early continuous father involvement for the first 14 – 36 months. Multiple linear regression was conducted to determine if continuous, or non-continuous father involvement (14 month-36 months), can be used to predict outcome scores on the Child Behavior Checklist in aggressive behavior, rule-breaking behavior, and cognitive development, at 5th grade. A statistically significant mean difference in cognitive development scores were found for children who had continuous father involvement (M=1.92, SD=2.41, t (1009) =2.81, p =.005, 95% CI=.146 to .828) compared to those who did not (M=2.60, SD=3.06, t (1009) =-2.38, p=.017, 95% CI= -1.08 to -.105). There was also a statistically significant mean difference in rule-breaking behavior scores between children who had early continuous father involvement (M=1.95, SD=2.33, t (1009) = 3.69, p <.001, 95% CI= .287 to .940), compared to those that did not (M=2.87, SD=2.93, t (1009) = -3.49, p =.001, 95% CI= -1.30 to -.364). No statistically significant difference was found in aggressive behavior scores. Multiple linear regression was performed using continuous father involvement to determine which has the largest relationship to rule-breaking behavior and cognitive development based on CBCL scores. Rule-breaking behavior was found to be significant (F (2, 1008) = 8.353, p<.001), with an R2 of .016. Cognitive development was also significant (F (2, 1008) = 4.44, p=.012), with an R2 of .009. Early continuous father involvement was a significant predictor of rule-breaking behavior and cognitive development at middle childhood. Findings suggest early continuous father involvement during the first 14 – 36 months of their children’s life, may lead to lower levels of rule-breaking behaviors and thought problems at 5th grade.

Keywords: cognitive development, early continuous father involvement, middle childhood, rule-breaking behavior

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Getahun Nigusie Demise

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Background; antiretroviral treatment reduce HIV-related morbidity, and prolonged survival of patients however, there is lack of up-to-date information concerning the treatment long term effect on the survival of HIV positive children especially in the study area. Objective: The aim of this study is to assess the incidence and predictors of mortality among HIV positive children on antiretroviral therapy (ART) in public hospitals of Harer town who were enrolled from 2011 to 2021. Methodology: Institution based retrospective cohort study was conducted among 429 HIV positive children enrolled in ART clinic from January 1st 2011 to December30th 2021. Data were collected from medical cards by using a data extraction form, Descriptive analyses were used to Summarized the results, and life table was used to estimate survival probability at specific point of time after introduction of ART. Kaplan Meier survival curve together with log rank test was used to compare survival between different categories of covariates, and Multivariate Cox-proportional hazard regression model was used to estimate adjusted Hazard rate. Variables with p-values ≤0.25 in bivariable analysis were candidates to the multivariable analysis. Finally, variables with p-values < 0.05 were considered as significant variables. Results: The study participants had followed for a total of 2549.6 child-years (30596 child months) with an overall mortality rate of 1.5 (95% CI: 1.1, 2.04) per 100 child-years. Their median survival time was 112 months (95% CI: 101–117). There were 38 children with unknown outcome, 39 deaths, and 55 children transfer out to different facility. The overall survival at 6, 12, 24, 48 months were 98%, 96%, 95%, 94% respectively. being in WHO clinical Stage four (AHR=4.55, 95% CI:1.36, 15.24), having anemia(AHR=2.56, 95% CI:1.11, 5.93), baseline low absolute CD4 count (AHR=2.95, 95% CI: 1.22, 7.12), stunting (AHR=4.1, 95% CI: 1.11, 15.42), wasting (AHR=4.93, 95% CI: 1.31, 18.76), poor adherence to treatment (AHR=3.37, 95% CI: 1.25, 9.11), having TB infection at enrollment (AHR=3.26, 95% CI: 1.25, 8.49),and no history of change their regimen(AHR=7.1, 95% CI: 2.74, 18.24), were independent predictors of death. Conclusion: more than half of death occurs within 2 years. Prevalent tuberculosis, anemia, wasting, and stunting nutritional status, socioeconomic factors, and baseline opportunistic infection were independent predictors of death. Increasing early screening and managing those predictors are required.

Keywords: human immunodeficiency virus-positive children, anti-retroviral therapy, survival, treatment, Ethiopia

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions

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Authors: Heerak Banerjee, Sourov Roy

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Supersymmetry, one of the most celebrated fields of study for explaining experimental observations where the standard model (SM) falls short, is reeling from the lack of experimental vindication. At the same time, the idea of additional gauge symmetry, in particular, the gauged Lμ-Lτ symmetric models have also generated significant interest. They have been extensively proposed in order to explain the tantalizing discrepancy in the predicted and measured value of the muon anomalous magnetic moment alongside several other issues plaguing the SM. While very little parameter space within these models remain unconstrained, this work finds that the γ + Missing Energy (ME) signal at the Belle-II detector will be a smoking gun for supersymmetry (SUSY) in the presence of a gauged U(1)Lμ-Lτ symmetry. A remarkable consequence of breaking the enhanced symmetry appearing in the limit of degenerate (s)leptons is the nondecoupling of the radiative contribution of heavy charged sleptons to the γ-Z΄ kinetic mixing. The signal process, e⁺e⁻ →γZ΄→γ+ME, is an outcome of this ubiquitous feature. Taking the severe constraints on gauged Lμ-Lτ models by several low energy observables into account, it is shown that any significant excess in all but the highest photon energy bin would be an undeniable signature of such heavy scalar fields in SUSY coupling to the additional gauge boson Z΄. The number of signal events depends crucially on the logarithm of the ratio of stau to smuon mass in the presence of SUSY. In addition, the number is also inversely proportional to the e⁺e⁻ collision energy, making a low-energy, high-luminosity collider like Belle-II an ideal testing ground for this channel. This process can probe large swathes of the hitherto free slepton mass ratio vs. additional gauge coupling (gₓ) parameter space. More importantly, it can explore the narrow slice of Z΄ mass (MZ΄) vs. gₓ parameter space still allowed in gauged U(1)Lμ-Lτ models for superheavy sparticles. The spectacular finding that the signal significance is independent of individual slepton masses is an exciting prospect indeed. Further, the prospect that signatures of even superheavy SUSY particles that may have escaped detection at the LHC may show up at the Belle-II detector is an invigorating revelation.

Keywords: additional gauge symmetry, electron-positron collider, kinetic mixing, nondecoupling radiative effect, supersymmetry

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Authors: Humaira M. Khan, Kanwal Asif

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Ischemic stroke is a neurological disorder with a complex pathophysiology associated with motor, sensory and cognitive deficits. Major approaches developed to treat acute ischemic stroke fall into two categories, thrombolysis and neuroprotection. The objectives of this study were to evaluate the neuroprotective and anti-thrombolytic effects of Olea europaea (olive oil) and Malus domestica (apple cider vinegar) and their combination in rat stroke model. Furthermore, histopathological analysis was also performed to assess the severity of ischemia among treated and reference groups. Male albino rats (12 months age) weighing 300- 350gm were acclimatized and subjected to middle cerebral artery occlusion method for stroke induction. Olea europaea and Malus domestica was administered orally in dose of 0.75ml/kg and 3ml/kg and combination was administered at dose of 0.375ml/kg and 1.5ml/kg prophylactically for consecutive 21 days. Negative control group was dosed with normal saline whereas piracetam (250mg/kg) was administered as reference. Neuroprotective activity of standard piracetam, Olea europaea, Malus domestica and their combination was evaluated by performing functional outcome tests i.e. Cylinder, pasta, ladder run, pole and water maize tests. Rats were subjected to surgery after 21 days of treatment for analysis from stroke recovery. Olea europaea and Malus domestica in individual doses of 0.75ml/kg and 3ml/kg respectively showed neuroprotection by significant improvement in ladder run test (121.6± 0.92;128.2 ± 0.73) as compare to reference (125.4 ± 0.74). Both test doses showed significant neuroprotection as compare to reference (9.60 ± 0.50) in pasta test (8.40 ± 0.24;9.80 ± 0.37) whereas with cylinder test, experimental groups showed significant increase in movements (6.60 ± 0.24; 8.40 ± 0.24) in contrast to reference (7.80 ± 0.37).There was a decrease in percentage time taken f to reach the hidden maize in water maize test (56.80 ± 0.58;61.80 ± 0.66) at doses 0.75ml/kg and 3ml/kg respectively as compare to piracetam (59.40 ± 1.07). Olea europaea and Malus domestica individually showed significant reduction in duration of mobility (127.0 ± 0.44; 123.0 ± 0.44) in pole test as compare to piracetam (124.0 ± 0.70). Histopathological analysis revealed the significant extent of protection from ischemia after prophylactic treatments. Hence it is concluded that Olea europaea and Malus domestica are effective neuroprotective agents alone as compare to their combination.

Keywords: ischemia, Malus domestica, neuroprotection, Olea europaea

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Authors: Alisha M. Ebrahim, Bijoy K. Menon, Eddy Lang, Shelagh B. Coutts, Katie Lin

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Introduction: Frontline emergency physicians require clear and evidence-based approaches to guide neuroimaging investigations for patients presenting with suspected acute stroke or transient ischemic attack (TIA). Various forms of computed tomography (CT) are currently available for initial investigation, including non-contrast CT (NCCT), CT angiography head and neck (CTA), and CT perfusion (CTP). However, there is uncertainty around optimal imaging choice for cost-effectiveness, particularly for minor or resolved neurological symptoms. In addition to the cost of CTA and CTP testing, there is also a concern for increased incidental findings, which may contribute to the burden of overdiagnosis. Methods: In this cross-sectional observational study, analysis was conducted on 586 anonymized triage and diagnostic imaging (DI) reports for neuroimaging orders completed on patients presenting to adult emergency departments (EDs) with a suspected stroke or TIA from January-December 2019. The primary outcome of interest is the diagnostic yield of NCCT+CTA compared to NCCT alone for patients presenting to urban academic EDs with Canadian Emergency Department Information System (CEDIS) complaints of “symptoms of stroke” (specifically acute stroke and TIA indications). DI reports were coded into 4 pre-specified categories (endorsed by a panel of stroke experts): no abnormalities, clinically significant findings (requiring immediate or follow-up clinical action), incidental findings (not meeting prespecified criteria for clinical significance), and both significant and incidental findings. Standard descriptive statistics were performed. A two-sided p-value <0.05 was considered significant. Results: 75% of patients received NCCT+CTA imaging, 21% received NCCT alone, and 4% received NCCT+CTA+CTP. The diagnostic yield of NCCT+CTA imaging for prespecified clinically significant findings was 24%, compared to only 9% in those who received NCCT alone. The proportion of incidental findings was 30% in the NCCT only group and 32% in the NCCT+CTA group. CTP did not significantly increase the yield of significant or incidental findings. Conclusion: In this cohort of patients presenting with suspected stroke or TIA, an NCCT+CTA neuroimaging strategy had a higher diagnostic yield for clinically significant findings than NCCT alone without significantly increasing the number of incidental findings identified.

Keywords: stroke, diagnostic yield, neuroimaging, emergency department, CT

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Authors: Dina Siniora, Jasia Baig

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During the past few decades, the healthcare system has undergone profound changes in their healthcare decision-making competencies and moral aptitudes due to the vast advancement in technology, clinical skills, and scientific knowledge. Healthcare decision-making deals with morally contentious dilemmas ranging from illness, life and death judgments that require sensitivity and awareness towards the patient’s preferences while taking into consideration medicine’s abilities and boundaries. As the ever-evolving field of medicine continues to become more scientifically and morally multifarious; physicians and the hospital administrators increasingly rely on ethics committees to resolve problems that arise in everyday patient care. The role and latitude of responsibilities of ethics committees which includes being dispute intermediaries, moral analysts, policy educators, counselors, advocates, and reviewers; suggest the importance and effectiveness of a fully integrated committee. Despite achievements on Integrated Ethics and progress in standards and competencies, there is an imminent necessity for further improvement in quality within ethics consultation services in areas of credentialing, professionalism and standards of quality, as well as the quality of healthcare throughout the system. These concerns can be resolved first by collecting data about particular quality gaps and comprehend the level to which ethics committees are consistent with newly published ASBH quality standards. Policymakers should pursue improvement strategies that target both academic bioethics community and major stakeholders at hospitals, who directly influence ethics committees. This broader approach oriented towards education and intervention outcome in conjunction with preventive ethics to address disparities in quality on a systematic level. Adopting tools for improving competencies and processes within ethics consultation by implementing a credentialing process, upholding normative significance for the ASBH core competencies, advocating for professional Code of Ethics, and further clarifying the internal structures will improve productivity, patient satisfaction, and institutional integrity. This cannot be systemically achieved without a written certification exam for HCEC practitioners, credentialing and privileging HCEC practitioners at the hospital level, and accrediting HCEC services at the institutional level.

Keywords: ethics consultation, hospital, medical ethics, quality

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Authors: Shilpi, Indu Gaur, Neha Bhadauria, Susmita Goswami, Prabir K. Paul

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Cultivation and consumption of organically grown fruits and vegetables have increased by several folds. However, the presence of Human Enteric Pathogens on the surface of organically grown vegetables causing Gastro-intestinal diseases, are most likely due to contaminated water and fecal matter of farm animals. Human Enteric Pathogens are adapted to colonize the human gut, and also colonize plant surface. Microbes on plant surface communicate with each other to establish quorum sensing. The cross talk study is important because the enteric pathogens on phylloplane have been reported to mask the beneficial resident bacteria of plant. In the present study, HEPs and bacterial colonizers were identified using 16s rRNA sequencing. Microbial colonization patterns after interaction between Human Enteric Pathogens and natural bacterial residents on tomato phylloplane was studied. Tomato plants raised under aseptic conditions were inoculated with a mixture of Serratia fonticola and Klebsiella pneumoniae. The molecules involved in cross-talk between Human Enteric Pathogens and regular bacterial colonizers were isolated and identified using molecular techniques and HPLC. The colonization pattern was studied by leaf imprint method after 48 hours of incubation. The associated protein-protein interaction in the host cytoplasm was studied by use of crosslinkers. From treated leaves the crosstalk molecules and interaction proteins were separated on 1D SDS-PAGE and analyzed by MALDI-TOF-TOF analysis. The study is critical in understanding the molecular aspects of HEP’s adaption to phylloplane. The study revealed human enteric pathogens aggressively interact among themselves and resident bacteria. HEPs induced establishment of a signaling cascade through protein-protein interaction in the host cytoplasm. The study revealed that the adaptation of Human Enteric Pathogens on phylloplane of Solanum lycopersicum involves the establishment of complex molecular interaction between the microbe and the host including microbe-microbe interaction leading to an establishment of quorum sensing. The outcome will help in minimizing the HEP load on fresh farm produce, thereby curtailing incidences of food-borne diseases.

Keywords: crosslinkers, human enteric pathogens (HEPs), phylloplane, quorum sensing

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Authors: O. Ekrami, P. Claes, S. Van Dongen

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Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

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