Search results for: survival predictive values

Authors: Orkide Donma, Mustafa M. Donma

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Childhood obesity, which may lead to increased risk for heart diseases in children as well as adults, is one of the most important health problems throughout the world. Prevalences of morbid obesity and metabolic syndrome (MetS) are being increased during childhood age group. MetS is a cluster of metabolic and vascular abnormalities including hypercoagulability and an increased risk of cardiovascular diseases (CVDs). There are also some relations between some components of MetS and leukocytes. The aim of this study is to investigate complete blood cell count parameters that differ between morbidly obese boys and girls with MetS diagnosis. A total of 117 morbid obese children with MetS consulted to Department of Pediatrics in Faculty of Medicine Hospital at Namik Kemal University were included into the scope of the study. The study population was classified based upon their genders (60 girls and 57 boys). Their heights and weights were measured and body mass index (BMI) values were calculated. WHO BMI-for age and sex percentiles were used. The values above 99 percentile were defined as morbid obesity. Anthropometric measurements were performed. Waist-to-hip and head-to-neck ratios as well as homeostatic model assessment of insulin resistance (HOMA-IR) were calculated. Components of MetS (central obesity, glucose intolerance, high blood pressure, high triacylglycerol levels, low levels of high density lipoprotein cholesterol) were determined. Hematological variables were measured. Statistical analyses were performed using SPSS. The degree for statistical significance was p ≤ 0.05. There was no statistically significant difference between the ages (11.2±2.6 years vs 11.2±3.0 years) and BMIs (28.6±5.2 kg/m² vs 29.3±5.2 kg/m²) of boys and girls (p ≥ 0.05), respectively. Significantly increased waist-to-hip ratios were obtained for boys (0.94±0.08 vs 0.91±0.06; p=0.023). Significantly elevated values of hemoglobin (13.55±0.98 vs 13.06±0.82; p=0.004), mean corpuscular hemoglobin concentration (33.79±0.91 vs 33.21±1.14; p=0.003), eosinophils (0.300±0.253 vs 0.196±0.197; p=0.014), and platelet (347.1±81.7 vs 319.0±65.9; p=0.042) were detected for boys. There was no statistically significant difference between the groups in terms of neutrophil/lymphocyte ratios as well as HOMA-IR values (p ≥ 0.05). Statistically significant gender-based differences were found for hemoglobin as well as mean corpuscular hemoglobin concentration and hence, separate reference intervals for two genders should be considered for these parameters. Eosinophils may contribute to the development of thrombus in acute coronary syndrome. Eosinophils are also known to make an important contribution to mechanisms related to thrombosis pathogenesis in acute myocardial infarction. Increased platelet activity is observed in patients with MetS and these individuals are more susceptible to CVDs. In our study, elevated platelets described as dominant contributors to hypercoagulability and elevated eosinophil counts suggested to be related to the development of CVDs observed in boys may be the early indicators of the future cardiometabolic complications in this gender.

Keywords: children, complete blood count, gender, metabolic syndrome

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Authors: Pavana Basavakumar, Devadas Bhat

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Diabetes is a disease which often goes undiagnosed until its secondary effects are noticed. Early detection of the disease is necessary to avoid serious consequences which could lead to the death of the patient. Conventional invasive tests for screening of diabetes are mostly painful, time consuming and expensive. There’s also a risk of infection involved, therefore it is very essential to develop non-invasive methods to screen and estimate the level of blood glucose. Extensive research is going on with this perspective, involving various techniques that explore optical, electrical, chemical and thermal properties of the human body that directly or indirectly depend on the blood glucose concentration. Thus, non-invasive blood glucose monitoring has grown into a vast field of research. In this project, an attempt was made to device a prototype for screening of diabetes by measuring electrical impedance of the skin and building a model to predict a patient’s condition based on the measured impedance. The prototype developed, passes a negligible amount of constant current (0.5mA) across a subject’s index finger through tetra polar silver electrodes and measures output voltage across a wide range of frequencies (10 KHz – 4 MHz). The measured voltage is proportional to the impedance of the skin. The impedance was acquired in real-time for further analysis. Study was conducted on over 75 subjects with permission from the institutional ethics committee, along with impedance, subject’s blood glucose values were also noted, using conventional method. Nonlinear regression analysis was performed on the features extracted from the impedance data to obtain a model that predicts blood glucose values for a given set of features. When the predicted data was depicted on Clarke’s Error Grid, only 58% of the values predicted were clinically acceptable. Since the objective of the project was to screen diabetes and not actual estimation of blood glucose, the data was classified into three classes ‘NORMAL FASTING’,’NORMAL POSTPRANDIAL’ and ‘HIGH’ using linear Support Vector Machine (SVM). Classification accuracy obtained was 91.4%. The developed prototype was economical, fast and pain free. Thus, it can be used for mass screening of diabetes.

Keywords: Clarke’s error grid, electrical impedance of skin, linear SVM, nonlinear regression, non-invasive blood glucose monitoring, screening device for diabetes

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Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

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Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan

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Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.

Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation

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Authors: Iyagbaye O. Rich, Omoigberale O. Michael, Iyagbaye A. Louis

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The physical, chemical parameters and some trace contents of Ugbogui in Edo State, Nigeria were investigated from August 2015 to April 2016. Four stations were studied from upstream to downstream using standard methods. A total of thirty-three (33) physical and chemical characteristics and trace metal contents were examined; Air and water temperatures, depth, transparency, colour, turbidity, flow velocity, pH, total alkalinity, conductivity and dissolved solids etc. Other includes dissolved oxygen, oxygen saturation, biochemical oxygen demand, chloride, phosphate, sodium, nitrate, sulphate, potassium, calcium, magnesium, iron, lead, copper, zinc, nickel, cadmium, vanadium and chromium. Eleven (11) parameters exhibited clear seasonal variations. However, there were high significant differences (p < 0.01) in the values of depth, colour, total suspended solid, biochemical oxygen demand, chemical oxygen demand, chloride, bicarbonate, phosphate, sulphate, iron, manganese, zinc, copper, chromium and cadmium among the stations. The anthropogenic activities had negatively impacted at station 3 of the river, although most of the recorded values were still within permissible limits.

Keywords: anthropogenic activities, Nigeria, permissible limits, physical and chemical parameters, trace metal, water quality

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Authors: Latifat Afolake Ogunfolabo, Hakeem Babafemi Ogunfolabo

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The gastrointestinal tract is densely populated with micro-organism which closely and intensively interacts with the host and ingested feed. Food borne infections are some of the major international challenges that lead to high mortality and also, antimicrobial resistance, which has been classified as a serious threat by World Health Organization. Samples of slaughtered cattle and goats intestines were collected and standard culture methods were used for bacteria isolation and identification. Minimum inhibitory concentration of commonly used antibiotic using modification of the disk diffusion method was carried out on isolates. The samples cultured were all positive to Pseudomonas aeruginosa (95% and 90%), Escherichia coli (85%), Salmonella typhi (70% and 60%), Staphylococcus aureus (75%and 100%), Micrococcus luteus (55% and35%), Bacillus macerans (60% and 5%), Bacillus cereus (25% and 20%), Clostridium perfringens (20% and 5%), Micrococcus varians (20% and 5%), Bacillus subtilis (25% and 5%), Streptococcus faecalis (40% and 25%) and Streptococcus faecium (15% and 10%) in goat and cattle respectively. Also, Proteus mirabilis (40%), Micrococcus luteus (35%), Proteus vulgaris (30%), Klebsiella aerogenes(15%) were isolated from cattle. The total coliform (13.55 x10⁵cfu/gm ± 1.77) and (20.30 x10⁵cfu/gm ± 1.27) counts were significantly higher than the total bacteria count (8.3 x10⁵cfu/gm ± 1.41) and (16.60 x10⁵cfu/gm ±0.49) for goat and cattle respectively. Selected Bacteria count of isolates showed that Staphylococcus aureus had the highest significant value (6.9 x10⁵cfu/gm ± 0.57) and (16.80 x10⁵cfu/gm ± 0.57) Escherichia coli (4.60 x10⁵cfu/gm ± 0.42) and (7.05 x10⁵cfu/gm ± 0.64) while the lowest significant value was obtained in Salmonella/Shigella (1.7 x10⁵cfu/gm ± 0.00) and (1.5 x10⁵cfu/gm ± 0.00) for goat and cattle respectively. Susceptibility of bacteria isolated from slaughtered goat and cattle intestine to commonly used antibiotics showed that the highest statistical significant value for zone of inhibition for goat was obtained for Ciprofloxacin (30.00 ± 2.25, 23.75 ± 2.49, 17.17 ± 1.40) followed by Augmentin (28.33 ± 1.22, 21. 83 ± 2.44, 16.67 ± 1.49), Erythromycin (27.75 ±1.48, 20.25 ± 1.29, 16.67 ± 1.26) while the lowest values were obtained for Ofloxacin (27.17 ± 1.89, 21.42 ± 2.19, 16.83 ± 1.26) respectively and values obtained for cattle are Ciprofloxacin (30.64 ± 1.6, 25.79 ± 1.76, 8.07 ± 11.49) followed by Augmentin (28.29 ± 1.33, 22.64 ± 1.82, 17.43 ± 1.55) Ofloxacin (26.57 ± 2.02, 20.79 ± 2.75, 16.21 ± 1.19) while the lowest values were obtained for Erythromycin (26.64 ± 1.49, 20.29 ± 1.49, 16.29 ± 1.33) at different dilution factor (10⁻¹, 10⁻², 10⁻³) respectively. The isolates from goat and cattle were all susceptible to Augmentin at the three different dilution factors. Some goat isolates are intermediate to Ciprofloxacin and Erythromycin at 10⁻² and 10⁻³, while resistance to Ciprofloxacin at 10⁻³ dilution factor. Ciprofloxacin and Ofloxacin at the dilution factors of 10⁻³ and 10⁻¹ for some cattle isolate and resistance were observed for Ofloxacin and Erythromycin at dilution of 10⁻³. These results indicate the susceptibilities and the antimicrobial resistance to commonly used antibiotic.

Keywords: antibiotic susceptibility, bacteria, cattle, goat, identification

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Authors: T. Lakshmi Priya

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With the widening definition of heritage, the challenges of heritage management has become more complex . Today heritage not only includes significant monuments but comprises historic areas / sites, historic cities, cultural landscapes, and living heritage sites. There is a need for a comprehensive understanding of the values associated with these heritage resources, which will enable their protection and management. These diverse cultural resources are managed by multiple agencies having their own way of operating in the heritage sites. An Integrated approach to management of these cultural resources ensures its sustainability for the future generation. This paper outlines the importance of an integrated approach for the management and protection of complex heritage sites in India by examining four case studies. The methodology for this study is based on secondary research and primary surveys conducted during the preparation of the conservation management plansfor the various sites. The primary survey included basic documentation, inventorying, and community surveys. Red Fort located in the city of Delhi is one of the most significant forts built in 1639 by the Mughal Emperor Shahjahan. This fort is a national icon and stands testimony to the various historical events . It is on the ramparts of Red Fort that the national flag was unfurled on 15th August 1947, when India became independent, which continues even today. Management of this complex fort necessitated the need for an integrated approach, where in the needs of the official and non official stakeholders were addressed. The understanding of the inherent values and significance of this site was arrived through a systematic methodology of inventorying and mapping of information. Hampi, located in southern part of India, is a living heritage site inscribed in the World Heritage list in 1986. The site comprises of settlements, built heritage structures, traditional water systems, forest, agricultural fields and the remains of the metropolis of the 16th century Vijayanagar empire. As Hampi is a living heritage site having traditional systems of management and practices, the aim has been to include these practices in the current management so that there is continuity in belief, thought and practice. The existing national, regional and local planning instruments have been examined and the local concerns have been addressed.A comprehensive understanding of the site, achieved through an integrated model, is being translated to an action plan which safeguards the inherent values of the site. This paper also examines the case of the 20th century heritage building of National Archives of India, Delhi and protection of a 12th century Tomb of Sultan Ghari located in south Delhi. A comprehensive understanding of the site, lead to the delineation of the Archaeological Park of Sultan Ghari, in the current Master Plan for Delhi, for the protection of the tomb and the settlement around it. Through this study it is concluded that the approach of Integrated Conservation has enabled decision making that sustains the values of these complex heritage sites in Indian context.

Keywords: conservation, integrated, management, approach

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Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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Authors: Mariana Gomez Gomez, Maria Elena Sanchez Vergara

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Many sustainable approaches to generate electric energy have emerged in the last few decades; one of them is through solar cells. Yet, this also has the disadvantage of highly polluting inorganic semiconductor manufacturing processes. Therefore, the use of molecular semiconductors must be considered. In this work, allene compounds C24H26O4 and C24H26O5 were used as dopants to manufacture semiconductors films based on PbPc by high-vacuum evaporation technique. IR spectroscopy was carried out to determine the phase and any significant chemical changes which may occur during the thermal evaporation. According to UV-visible spectroscopy and Tauc’s model, the deposition process generated thin films with an activation energy range of 1.47 to 1.55 eV for direct transitions and 1.29 to 1.33 eV for indirect transitions. These values place the manufactured films within the range of low bandgap semiconductors. The flexible devices were manufactured: polyethylene terephthalate (PET), Indium tin oxide (ITO)/organic semiconductor/ Cubic Close Packed (CCP). The characterization of the devices was carried out by evaluating electrical conductivity using the four-probe collinear method. I-V curves were obtained under different lighting conditions at room temperature. OS1 (PbPc/C24H26O4) showed an Ohmic behavior, while OS2 (PbPc/C24H26O5) reached higher current values ​​at lower voltages. The results obtained show that the semiconductors devices doped with allene compounds can be used in the manufacture of optoelectronic devices.

Keywords: electrical properties, optical gap, phthalocyanine, thin film.

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Authors: Saroj Panthi

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The red panda (Ailurus fulgens fulgens) is distributed throughout the Himalayas and is found in both protected and unprotected areas of Nepal. Loss and fragmentation of habitat threaten red panda population throughout its range, and as a consequence, it is listed as vulnerable on the IUCN Red List of Threatened Species. Despite this pressing situation, data on the ecology of the red panda in western Nepal are lacking. Our aim in the current study was to determine the distribution, associated habitats, and summer diet of the red panda in Dhorpatan Hunting Reserve (DHR), Nepal. Evidence of red pandas was found in all 7 blocks of the reserve, spanning an area of 345.8 km2, between elevations of 2800 m and 4000 m and predominantly (> 75%) in forests comprising plant communities dominated by Abies spectabilis, Acer caesium, Tsuga domusa, and Betula utilis, with ground cover of Arundinaria spp. The dominant plant found in scat of the red panda was Arundinaria spp. (81.7%), with Acer spp., B. utilis, and lichen also frequently present. Livestock grazing and human activities were significantly higher in habitats where signs of pandas were recorded than in areas where they were absent. This habitat overlap between the red panda and livestock potentially poses a major threat to the panda’s survival in the DHR, a fact that should be taken into account in devising management strategies for this threatened species.

Keywords: red panda, Dhorpatan hunting reserve, diet, habitat preference

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan

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Authors: Annie Ramanbhai Mecwan

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Cleaning validation in a pharmaceutical manufacturing facility is documented evidence that a cleaning process has effectively removed contaminants, residues from previous drug products and cleaning agents below a pre-defined threshold from the reusable tools and parts of equipment. In shared manufacturing facilities more than one drug product is prepared. After cleaning of reusable tools and parts of equipment after one drug product manufacturing, there are chances that some residues of drug substance from previously manufactured drug products may be retained on the equipment and can carried forward to the next drug product and thus cause cross-contamination. Health-based limits through the derivation of a safe threshold value called permitted daily exposure (PDE) for the residues of drug substances should be employed to identify the risks posed at these manufacturing facilities. The PDE represents a substance-specific dose that is unlikely to cause an adverse effect if an individual is exposed to or below this dose every day for a lifetime. There are different practices to calculate PDE. Data for all APIs in the public domain are considered to calculate PDE value though, company to company may vary the final PDE value based on different toxicologist’s perspective or their subjective evaluation. Hence, Regulatory agencies should take responsibility for publishing PDE values for all APIs as it is done for elemental PDEs. This will harmonize the PDE values all over the world and prevent the unnecessary load on manufacturers for cleaning validation

Keywords: active pharmaceutical ingredient, good manufacturing practice, NOAEL, no observed adverse effect level, permitted daily exposure

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: A. M. Khourshid, A. M. El-Kassas, I. Sabry

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The objective of this work was to investigate the mechanical properties in order to demonstrate the feasibility of friction stir welding for joining Al 6061 aluminium alloys. Welding was performed on pipe with different thickness (2, 3 and 4 mm), five rotational speeds (485, 710, 910, 1120 and 1400 rpm) and a traverse speed of 4mm/min. This work focuses on two methods which are artificial neural networks using software and Response Surface Methodology (RSM) to predict the tensile strength, the percentage of elongation and hardness of friction stir welded 6061 aluminium alloy. An Artificial Neural Network (ANN) model was developed for the analysis of the friction stir welding parameters of 6061 pipe. Tensile strength, the percentage of elongation and hardness of weld joints were predicted by taking the parameters tool rotation speed, material thickness and axial force as a function. A comparison was made between measured and predicted data. Response Surface Methodology (RSM) was also developed and the values obtained for the response tensile strength, the percentage of elongation and hardness are compared with measured values. The effect of FSW process parameters on mechanical properties of 6061 aluminium alloy has been analysed in detail.

Keywords: friction stir welding, aluminium alloy, response surface methodology, artificial neural network

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Authors: Oluronke Odunjo

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The world is becoming increasingly urbanized and Nigeria is not left out. One of the indicators of human developments is housing and as such, water is needed by households for survival. This Paper assesses sources of water being used by residents in the newly urbanized areas of Ogbomoso, Southwest, Nigeria. Multistage sampling technique was used and Oke-Adunin Community was purposively selected for the study as it has large concentration of staff and students of Ladoke Akintola University of Technology. The area was captured with Google earth and two hundred and twenty two inhabited houses were found. Questionnaire was the instrument for data collection which was administered using total enumeration technique. Data obtained however, were analyzed with descriptive and inferential statistical analyses. Findings revealed that most of the respondents were male, while 36.03% house owners were between the ages of 46 and 55 years. Sources of water used by residents include well (56.94%), water vendors (17.77%), rain (15.29%) and borehole (3.72%). Distance travelled by house owners to sources of water was as high as 5.06 metres, resulting into stress (30.00 %), depression (25.00%) and aggressiveness (18.75%). Result of correlation analysis between the sources of water of respondents and disease prevalence showed that both rain water and water vendor had very strong positive correlation with typhoid, diarrhea and dysentery, while well water only had positive correlation with dysentery. Recommendations were therefore, proffered towards solving the problems associated with water in the area.

Keywords: newly urbanized area, Ogbomoso, sources of water, residents

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Authors: Kadiri Kayode Ibrahim

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Small and Medium Enterprises (SMEs) play significant roles in the economic development of Nigeria. However, the performance of these SMEs is influenced by various factors, including cultural factors. Keffi Local Government Area (LGA) in Nasarawa State, Nigeria, has a large number of registered SMEs. Understanding the impact of cultural factors on the performance of these SMEs in Keffi LGA is essential for their growth and sustainability. Therefore, this study aims to investigate the effect of cultural factors on the performance of selected SMEs in Keffi LGA, Nasarawa State. A cross-sectional survey research design was used to collect data from 165 purposefully selected SME owners out of the 283 registered SMEs in Keffi LGA. The data was collected using a questionnaire divided into three sections, and analysed using descriptive and ordinary least square regression (OLS). The results indicate that socio-cultural factors and ethical values have a positive and significant effect on the performance of SMEs in Keffi LGA, while attitude has a negative and significant effect on the performance of SMEs in Keffi LGA. Therefore, the study recommends that SMEs in Keffi LGA should understand the socio-cultural elements of their operating environment, adopt socio-cultural factors as elements to guide their planning and strategizing and take into consideration the ethical values of the business environment when offering new products or services. Additionally, SME Managers should take cognisance of people’s attitudes and use them to gauge their activities and ensure they support the overall performance of the business.

Keywords: cultural, factors, performance, SMEs

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Abdul Karim Zulkarnain, Marchaban, Subagus Wahyono, Ratna Asmah Susidarti

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Mahkota Dewa contains phalerin which has activity as sun screen. In this study, 13 formulations of cream oil in water (o/w) were prepared and tested for their physical characteristics. The physical characteristics were then used for determining the optimum formula. This study aimed to explore the physical stability of optimized formulation of cream, its sun protecting factor (SPF) values using in vitro and in vivo tests. The optimum formula of o/w cream were prepared based on Simplex Lattice Design (LSD) method using software Design Expert®. The formulation of o/w cream were varied based on the proportion of cetyl alcohol, mineral oil and tween 80. The difference of physical characteristic of optimum and predicted formula was tested using t-test with significant level of 95%. The optimum formula of o/w cream was the formula which consists of cetyl alcohol 9.71%, mineral oil, 29%, and tween 80 3.29. Based on t-test, there was no significant difference of physical characteristics of optimum and predicted formulation. Viscosity, spread power, adhesive power, and separation volume ratio of o/w at week 0-4 were relatively stable. The o/w creams were relatively stable at extreme temperature. The o/w creams from mahkota dewa, phalerin, and benzophenone have SPF values of 21.32, 33.12, and 42.49, respectively. The formulas did not irritate the skin based on in vivo test.

Keywords: cream, stability, In vitro, In vivo

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Authors: Pugazhenthan Thangaraju

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Background: Since the pandemic began, more than millions of people have become infected with COVID-19. Globally, researchers are working for safe and effective treatments for this disease. Remdesivir is a drug that has been approved for the treatment of COVID-19. Many aspects are still being considered that may influence the future use of remdesivir. Aim: To assess the safety and efficacy of Remdesivir in hospitalized adult patients diagnosed with moderate and severe COVID-19. Methods: It was a record-based retrospective cohort study conducted between April 1st, 2020 and June 30th, 2021 at the tertiary care teaching hospital All India Institutes of Medical Sciences (AIIMS), Raipur Results: There were a total of 10,559 medical records of COVID-19 patients of which 1034 records were included in this study. Overall, irrespective of the survival status, there was statistical significant difference observed between the WHO score at the time of admission and discharge. Clinical improvement among the survivors was found to be statistically significant. Conclusion: Remdesivir's potential efficacy against coronaviruses has so far been limited to in vitro studies and animal models. However, information about COVID-19 is rapidly expanding. Several clinical trials for the treatment of COVID-19 with remdesivir are now underway. However, the findings of this study support remdesivir as a promising agent in the fight against SARS-CoV-2.

Keywords: Remdesivir, COVID-19, SARS-CoV-2, antiviral, RNA-dependent RNA polymerase, viral pneumonia

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Authors: Omar Pillaca-Pullo, Arturo Alejandro-Paredes, Carol Flores-Fernandez, Marijuly Sayuri Kina, Amparo Iris Zavaleta

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Aqueous two-phase system (ATPS) is an interesting alternative for separating industrial enzymes due to it is easy to scale-up and low cost. Polyethylene glycol (PEG) mixed with potassium phosphate or magnesium sulfate is one of the most frequently polymer/salt ATPS used, but the consequences of its use is a high concentration of phosphates and sulfates in wastewater causing environmental issues. Citrate could replace these inorganic salts due to it is biodegradable and does not produce toxic compounds. On the other hand, statistical design of experiments is widely used for ATPS optimization and it allows to study the effects of the involved variables in the purification, and to estimate their significant effects on selected responses and interactions. The 24 factorial design with four central points (20 experiments) was employed to study the partition and purification of proteases produced by Pseudomonas sp. in PEG/citrate ATPS system. ATPS was prepared with different sodium citrate concentrations [14, 16 and 18% (w/w)], pH values (7, 8 and 9), PEG molecular weight (2,000; 4,000 and 6,000 g/mol) and PEG concentrations [18, 20 and 22 % (w/w)]. All system components were mixed with 15% (w/w) of the fermented broth and deionized water was added to a final weight of 12.5 g. Then, the systems were mixed and kept at room temperature until to reach two-phases separation. Volumes of the top and bottom phases were measured, and aliquots from both phases were collected for subsequent proteolytic activity and total protein determination. Influence of variables such as PEG molar mass (MPEG), PEG concentration (CPEG), citrate concentration (CSal) and pH were evaluated on the following responses: purification factor (PF), activity yield (Y), partition coefficient (K) and selectivity (S). STATISTICA program version 10 was used for the analysis. According to the obtained results, higher levels of CPEG and MPEG had a positive effect on extraction, while pH did not influence on the process. On the other hand, the CSal could be related with low values of Y because of the citrate ions have a negative effect on solubility and enzymatic structure. The optimum values of Y (66.4 %), PF (1.8), K (5.5) and S (4.3) were obtained at CSal (18%), MPEG (6,000 g/mol), CPEG (22%) and pH 9. These results indicated that the PEG/citrate system is accurate to purify these Pseudomonas sp. proteases from fermented broth as a first purification step.

Keywords: citrate, polyethylene glycol, protease, Pseudomonas sp

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Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: F. Tahiri, F. Grajçevci

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The cities are coping with permanent demands to extend their residential and economical capacity. The new urban zones are sometimes induced to be developed in more vulnerable environments. This study is aimed to identify and mitigate the seismic hazards in the stage of urban planning for new settlements, including the existing urban environments which initially have not considered the seismic hazard. Seismic microzoning shall study the amplification/attenuation of seismic excitations from the bedrock to the ground surface. Modification of the seismic excitation is governed from the site specific ground conditions, presented on ground surface as mean values of the ratio of maximum accelerations at the surface versus acceleration of subsoil media – presented with dynamic amplification factors (DAF). The values shall be used to create the maps with isolines of DAF and then seismic microzoning with expected maximum mean surface acceleration as a product of DAF with maximum accelerations at bedrock. Development of resonant map shall conglomerate the information’s obtained from seismic microzoning in regard to expected predominant ground periods of seismic excitation and periods of vibrations of designed/built structures. These information’s shall be used as indispensible tool in early stages of urban planning to determine the most optimal zones for construction, the constructive materials, structural systems, range of buildings height, etc. so the resonance of soil media with built structures is avoided. The information’s could be used also for assessment of seismic risk and vulnerability-damageability of existing urban environments.

Keywords: vulnerable environment, mitigation, seismic microzoning, resonant map, urban planning

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Authors: Rachid Zentar, Mokrane Bala, Pascal Boustingorry

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The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.

Keywords: crushed aggregates, intrinsic viscosity, packing density, rolled aggregates, slump, yield stress of concrete

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Authors: H. Minor-Pérez, A. M. Mota-Silva, S. Ortiz-Barrios

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Substances of vegetable origin with antioxidant capacity have a high potential for application on the conservation of some foods, can prevent or reduce for example oxidation of lipids. However a food is a complex system whose wide variety of components wich can reduce or eliminate this antioxidant capacity. The antioxidant activity can be determined with the ABTS technique. The radical ABTS+ is generated from the acid 2, 2´ - Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). This radical is a composite color bluish-green, stable and with a spectrum of absorption into the UV-visible. The addition of antioxidants causes discoloration, value that can be reported as a percentage of inhibition of the cation radical ABTS+. The objective of this study was evaluated the effect of the combination of the pH and the essential oil of cinnamon (EOC) on inhibition of the radical ABTS+, using statistical design of central point (Design Expert) to obtain mathematical models that describe this phenomenon. Were evaluated 17 treatments with combinations of pH 5, 6 and 7 (citrate-phosphate buffer) and the concentration of essential oil of cinnamon (C): 0 µg/mL, 100 µg/mL and 200 µg/mL. The samples were analyzed using the ABTS technique. The reagent was dissolved in methanol 80% to standardized the absorbance to 0.7 +/- 0.1 at 754 nm. Then samples were mixed with reagent standardized ABTS and after 1 min and 7 min absorbance was read for each treatment at 754 nm. Was used a curve pattern with vitamin C and reported the values as inhibition (%) of radical ABTS+. The statistical analysis shows the experimental results were adjusted to a quadratic model, to the times of 1 min and 7 min. This model describes the influence of the factors investigated independently: pH and cinnamon essential oil (µg/mL) and the effect of the interaction between pH*C, as well as the square of the pH2 and C2. The model obtained was Y = 10.33684 - 3.98118*pH + 1.17031*C + 0.62745*pH2 - 3.26675*10-3*C2 - 0.013112*pH*C, where Y is the response variable. The coefficient of determination was 0.9949 for 1 min. The equation was obtained at 7 min and = - 10.89710 + 1.52341*pH + 1.32892*C + 0.47953*pH2 - 3.56605*10- *C2 - 0.034687*pH*C. The coefficient of determination was 0.9970. This means that only 1% of the total variation is not explained by the developed models. At 100 µg/mL of EOC was obtained an inhibition percentage of 80%, 84% and 97% for the pH values of 5,6 and 7 respectively, while a value of 200 µg/mL the inhibition (%) was very similar for the treatments. In these values of pH was obtained an inhibition close 97%. In conclusion the pH does not have a significant effect on the antioxidant capacity, while the concentration of EOC was decisive for the antioxidant capacity. The authors acknowledge the funding provided by the CONACYT for the project 131998.

Keywords: antioxidant activity, ABTS technique, essential oil of cinnamon, mathematical models

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Authors: Samantha Borja, Vladimir Valle, Pamela Molina

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The development of adhesives from renewable raw materials attracts the attention of the scientific community, due to it promises the reduction of the dependence with materials derived from oil. This work proposes the use of modified 'oca (Oxalis tuberosa)' starch and polyvinyl alcohol (PVA) in the elaboration of adhesives for lignocellulosic substrates. The investigation focused on the formulation of adhesives with 3 different PVA:starch (modified and native) ratios (of 1,0:0,33; 1,0:1,0; 1,0:1,67). The first step to perform it was the chemical modification of starch through acid hydrolysis and a subsequent urea treatment to get carbamate starch. Then, the adhesive obtained was characterized in terms of instantaneous viscosity, Fourier-transform infrared spectroscopy (FTIR) and shear strength. The results showed that viscosity and mechanical tests exhibit data with the same tendency in relation to the native and modified starch concentration. It was observed that the data started to reduce its values to a certain concentration, where the values began to grow. On the other hand, two relevant bands were found in the FTIR spectrogram. The first in 3300 cm⁻¹ of OH group with the same intensity for all the essays and the other one in 2900 cm⁻¹, belonging to the group of alkanes with a different intensity for each adhesive. On the whole, the ratio PVA:starch (1:1) will not favor crosslinking in the adhesive structure and causes the viscosity reduction, whereas, in the others ones, the viscosity is higher. It was also observed that adhesives made with modified starch had better characteristics, but the adhesives with high concentrations of native starch could equal the properties of the adhesives made with low concentrations of modified starch.

Keywords: polyvinyl alcohol, PVA, chemical modification, starch, FTIR, viscosity, shear strength

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Authors: Emery Coppola Jr., Marwan Sadat, Il Kim, Diane Trube, Richard Kurisko

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Contamination sites like landfills often pose significant risks to receptors like surface water bodies. Surface water bodies are often a source of recreation, including fishing and swimming, which not only enhances their value but also serves as a direct exposure pathway to humans, increasing their need for protection from water quality degradation. In this paper, a case study presents the potential effects of leachate-impacted groundwater from a large closed sanitary landfill on the surface water quality of the nearby Raritan River, situated in New Jersey. The study, performed over a two year period, included in-depth field evaluation of both the groundwater and surface water systems, and was supplemented by computer modeling. The analysis required delineation of a representative average daily groundwater discharge from the Landfill shoreline into the large, highly tidal Raritan River, with a corresponding estimate of daily mass loading of potential contaminants of concern. The average daily groundwater discharge into the river was estimated from a high-resolution water level study and a 24-hour constant-rate aquifer pumping test. The significant tidal effects induced on groundwater levels during the aquifer pumping test were filtered out using an advanced algorithm, from which aquifer parameter values were estimated using conventional curve match techniques. The estimated hydraulic conductivity values obtained from individual observation wells closely agree with tidally-derived values for the same wells. Numerous models were developed and used to simulate groundwater contaminant transport and surface water quality impacts. MODFLOW with MT3DMS was used to simulate the transport of potential contaminants of concern from the down-gradient edge of the Landfill to the Raritan River shoreline. A surface water dispersion model based upon a bathymetric and flow study of the river was used to simulate the contaminant concentrations over space within the river. The modeling results helped demonstrate that because of natural attenuation, the Landfill does not have a measurable impact on the river, which was confirmed by an extensive surface water quality study.

Keywords: groundwater flow and contaminant transport modeling, groundwater/surface water interaction, landfill leachate, surface water quality modeling

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Authors: Muhamad Saiful Bahri Yusoff

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This study aimed to evaluate the construct, convergent, and discriminant validity of the Secondary School Stressor Questionnaire (3SQ) as well as to evaluate its internal consistency among adolescents in Malaysian secondary schools. A cross-sectional study was conducted on 700 secondary school students in five secondary schools. Stratified random sampling was used to select schools and participants. The confirmatory factor analysis was performed by AMOS to examine construct, convergent, and discriminant validity. The reliability analysis was performed by SPSS to determine internal consistency. The results showed that the original six-factor model with 44 items failed to achieve acceptable values of the goodness of fit indices, suggesting poor model fit. The new five-factor model of 3SQ with 22 items demonstrated acceptable level of goodness of fit indices to signify a model fit. The overall Cronbach’s alpha value for the new version 3SQ was 0.93, while the five constructs ranged from 0.68 to 0.94. The composite reliability values of each construct ranged between 0.68 and 0.93, indicating satisfactory to high level of convergent validity. Our study did not support the construct validity of the original version of 3SQ. We found the new version 3SQ showed more convincing evidence of validity and reliability to measure stressors of adolescents. Continued research is needed to verify and maximize the psychometric credentials of 3SQ across countries.

Keywords: stressors, adolescents, secondary school students, 3SQ, psychometric properties

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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