Search results for: big health data

Authors: R. P. Leite, M. A. S. Diamante, F. R. Gadelha, L. H. G. Ribeiro, H. Dolder

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Although industrial processes are the major contributor to increase cadmium environmental concentration, phosphate fertilizers have significantly increased its percentage in soil, making food and tobacco the main source of cadmium exposure to humans. Worldwide population surveys have shown a consistent link between environmental exposure to cadmium and several idiopathic pathologies among non-occupationally exposed subjects. Epidemiological investigations and animal experiments paralleling human chronic exposure to environmental cadmium are, therefore of major importance for establishing a relationship between cadmium and several pathologies of unspecific etiology. In the present study, Wistar rats were randomly divided into three different groups and subjected to increasing cadmium doses ranging between low to moderate environmentally realistic doses. At the end of the treatment, the testis was dissected and subjected to biochemical and histological analyses. Our data show a significant disturbance in the cellular oxidative status for all cadmium-treated group, accompanied by morphological changes in blood vessel lumen.

Keywords: cadmium, blood vessel, environmental realistic doses, oxidative stress

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Authors: Martina Kanciruk, Jac J. W. Andrews, Tyrone Donnon

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The purpose of this study was to determine the significance of history of obesity for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, family history, parents, childhood, risk factors. Eleven studies of family history and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that family history of obesity is a significant risk factor of overweight and /or obesity in offspring; risk for offspring overweight and/or obesity associated with family history varies depending of the family members included in the analysis; and when family history of obesity is present, the offspring are at greater risk for developing obesity or overweight. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment.

Keywords: childhood obesity, overweight, family history, risk factors, meta-analysis

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Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Olaitan Akanji, Cleophas Loto, Patricia Popoola, Andrei Kolesnikov

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Studies involving performance of corrosion inhibitors had been identified as one of the critical research needs for improving the durability of mild steel used in various industrial applications. This paper investigates the inhibiting effect of calcium gluconate against the corrosion of mild steel in 2.5M magnesium chloride using weight loss method and linear polarization technique, calculated corrosion rates from the obtained weight loss data, potentiodynamic polarization measurements are in good agreement. Results revealed calcium gluconate has strong inhibitory effects with inhibitor efficiency increasing with increase in inhibitor concentration at ambient temperature, the efficiency of the inhibitor increased in the following order of concentrations 2%g/vol,1.5%g/vol,1%g/vol,0.5%g/vol. Further results obtained from potentiodynamics experiments had good correlation with those of the gravimetric methods, the adsorption of the inhibitor on the mild steel surface from the chloride has been found to obey Langmuir, Frumkin and Freudlich adsorption isotherm. Scanning electron microscopy (SEM) observation confirmed the existence of an absorbed protective film on the metal surface.

Keywords: calcium gluconate, corrosion, magnesium chloride, mild steel

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Authors: Ashwini Bhosale, Yogesh Patil

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Urban areas are extremely complicated environmental settings, where health and well-being of an individual and population are governed by a large number of bio-physical, socio-economical, and inclusive aspects. Although poverty and slums are the prime issues under UN-HABITAT agenda of environmental sustainability, slums, the inevitable part of urban environment, have not accounted for inclusive city planning. Developing nations, where about 60 % of world slum population resides, are increasingly under pressure to uplift the urban poor, particularly slum dwellers. From a point of advantage, these new slum redevelopment projects have succeeded in providing legitimized and more permanent and stable shelter for the low income people, as well as individualized sanitation and water supply. However, they unfortunately follow the “one type fits all" approach and exhibit no response to the climatic design needs on Mumbai. The thesis focuses on the study of environmental perspectives in the context of Daylight, natural ventilation and social aspects in the design process of Slum-Rehabilitation schemes (SRS) – case of Mumbai. It attempts to investigate into Indian approaches about SRS and concludes upon strategies to be incorporated in SRS to improve the overall SRS environment. The main objectives of this work have been to identify and study the spatial configuration and possibilities of daylight and natural ventilation in Slum Rehabilitated buildings. The performance of the proposed method was evaluated by comparison with the daylight luminance simulated by lighting software, namely ECOTECT, and with measurements under real skies whereas for the ventilation study purpose, software named FLOW DESIGN was used.

Keywords: urban environment, slum-rehabilitation, daylight, natural-ventilation, architectural consequences

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Authors: B. Vishnupriya, R. Josphineleela

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Road sign recognition is a key element in advanced driver-assistance systems (ADAS) and self-driving technologies, as it is fundamental to maintaining safe and effective navigation. Conventional supervised learning approaches rely heavily on extensive labeled datasets for training, which can be resource-intensive and challenging to obtain. This study examines the effectiveness of three unsupervised image segmentation approaches—K- means clustering, GrabCut, and Gaussian Mixture Model (GMM)—in detecting road signs within complex settings. Using a publicly available Road Sign dataset from Kaggle, we assess the effectiveness of these methods based on clustering performance metrics. Our results indicate that GMM achieves the highest performance across these metrics, demonstrating superior segmentation accuracy under diverse lighting and weather conditions, followed by GrabCut and K-means clustering. This research highlights the potential of unsupervised techniques in reducing the dependency on labeled data, offering insights for future advancements in road sign detection systems for ADAS and autonomous vehicles.

Keywords: K-means clustering, unsupervised, Gaussian Mixture Model, segmentation accuracy

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Authors: Simona Pileviciene

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On 24th January 2014, Lithuania notified two primary cases of African swine fever (ASF) in wild boars. The animals were tested positive for ASF virus (ASFV) genome by real-time PCR at the National Reference Laboratory for ASF in Lithuania (NRL), results were confirmed by the European Union Reference Laboratory for African swine fever (CISA-INIA). Intensive wild and domestic animal monitoring program was started. During the period of 2014-2017 ASF was confirmed in two large commercial pig holding with the highest biosecurity. Pigs were killed and destroyed. Since 2014 ASF outbreak territory from east and south has expanded to the middle of Lithuania. Diagnosis by PCR is one of the highly recommended diagnostic methods by World Organization for Animal Health (OIE) for diagnosis of ASF. The aim of the present study was to compare singleplex real-time PCR assays to a duplex assay allowing the identification of ASF and internal control in a single PCR tube and to compare primers, that target the p72 gene (ASF 250 bp and ASF 75 bp) effectivity. Multiplex real-time PCR assays prove to be less time consuming and cost-efficient and therefore have a high potential to be applied in the routine analysis. It is important to have effective and fast method that allows virus detection at the beginning of disease for wild boar population and in outbreaks for domestic pigs. For experiments, we used reference samples (INIA, Spain), and positive samples from infected animals in Lithuania. Results show 100% sensitivity and specificity.

Keywords: African swine fewer, real-time PCR, wild boar, domestic pig

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Authors: Lotem Sarid, Meirav Trebicz-Geffen, Serge Ankri

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Queuosine (Q) is a naturally occurring modified nucleoside that occurs in the first position of transfer RNA anticodons such as Asp, Asn, His, and Tyr. As eukaryotes lack pathways to synthesize queuine, the nucleobase of queuosine, they must obtain it from their diet or gut microbiota. Our previous work investigated the effects of queuine on the physiology of the eukaryotic parasite Entamoeba histolytica and defined the enzyme EhTGT responsible for its incorporation into tRNA. To our best knowledge, it is unknown how E. histolytica salvages Q from gut bacteria. We used N-acryloyl-3-aminophenylboronic acid (APB) PAGE analysis to demonstrate that E. histolytica trophozoites can salvage queuine from Q or E. coli K12 but not from the modified E. coli QueC strain, which cannot produce queuine. Next, we examined the role of EhDUF2419, a protein with homology to DNA glycosylase, as a queuine salvage enzyme in E. histolytica. When EhDUF2419 expression is silenced, it inhibits Q's conversion to queuine, resulting in a decrease in Q-tRNA levels. We also observed that Q protects control trophozoites from oxidative stress (OS), but not siEhDUF2419 trophozoites. Overall, our data reveal that EhDUF2419 is central for the salvaging of queuine from bacteria and for the resistance of the parasite to OS.

Keywords: entamoeba histolytica, epitranscriptomics, gut microbiota, queuine, queuosine, response to oxidative stress, tRNA modification.

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: Abdulrahman Alenezi

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This research paper investigates the surface heat transfer characteristics using computational fluid dynamics for orthogonal and inclined impinging jet. A jet Reynolds number (Rₑ) of 10,000, jet-to- plate spacing (H/D) of two and eight and two angles of impingement (α) of 45° and 90° (orthogonal) were employed in this study. An unconfined jet impinges steadily a constant temperature flat surface using air as working fluid. The numerical investigation is validated with an experimental study. This numerical study employs grid dependency investigation and four different types of turbulence models including the transition SSD to accurately predict the second local maximum in Nusselt number. A full analysis of the effect of both turbulence models and mesh size is reported. Numerical values showed excellent agreement with the experimental data for the case of orthogonal impingement. For the case of H/D =6 and α=45° a maximum percentage error of approximately 8.8% occurs of local Nusselt number at stagnation point. Experimental and numerical correlations are presented for four different cases

Keywords: turbulence model, inclined jet impingement, single jet impingement, heat transfer, stagnation point

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Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

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Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R² of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

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Authors: Mohammed Umar Manko

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A series of batch experiments were conducted in order to investigate the feasibility of Balanitesaegyptiaca seeds based activated carbon as compared with industrial activated carbon for the removal of chromium and lead ions from aqueous solution by the adsorption process within 30 to 150 minutes contact time. The activated samples were prepared using zinc chloride and tetraoxophophate(VI) acid. The results obtained showed that the activated carbon of Balanitesaegyptiaca seeds studied had relatively high adsorption capacities for these heavy metal ions compared with industrial Activated Carbon. The percentage removal of Cr (VI) and lead (II) ions by the three activated carbon samples were 64%, 70% and 71%; 60%, 66% and 60% respectively. Adsorption equilibrium was established in 90 minutes for the heavy metal ions. The equilibrium data fitted the pseudo second order out of the pseudo first, pseudo second, Elovich ,Natarajan and Khalaf models tested. The investigation also showed that the adsorbents can effectively remove metal ions from similar wastewater and aqueous media.

Keywords: activated carbon, pseudo second order, chromium, lead, Elovich model

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Authors: Amel Asselah, Nadia Chabli, Imane Haddad

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The adsorption of methylene blue and congo red dyes in an aqueous solution, on a food waste adsorbent: potato peel, and on a commercial adsorbent: activated carbon powder, was investigated using batch experiments. The objective of this study is the valorization of potato peel by its application in the elimination of these dyes. A comparison of the adsorption efficiency with a commercial adsorbent was carried out. Characterization of the potato peel adsorbent was performed by scanning electron microscopy coupled to energy-dispersive X-ray spectroscopy, Fourier transforms infrared spectroscopy, X-ray diffraction, and X-ray fluorescence. Various parameters were analyzed, in particular: the adsorbent mass, the initial dye concentration, the contact time, the pH, and the temperature. The results reveal that it is about 98% for methylene blue-potato peel, 84% for congo red-potato peel, 84% for methylene blue-activated carbon, and 66% for congo red-activated carbon. The kinetic data were modeled by different equations and revealed that the adsorption of textile dyes on adsorbents follows the model pseudo-second-order, and the particular extra diffusion governs the adsorption mechanism. It has been found that the adsorption process could be described by the Langmuir isotherm.

Keywords: bioadsorbent, waste valorization, adsorptio, textile dyes

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Wajeehah Aayeshah, Joy Higgs

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The term “transcending pedagogies” has been created to refer to teaching and learning strategies that transcend the mode of student enrolment, the needs of different students, and different learning spaces. The value of such pedagogies in the current arena when learning spaces, technologies and preferences are more volatile than ever before, is a key focus of this paper. The paper will examine current and emerging pedagogies that transcend the learning spaces and enrollment modes of on campus, distance, virtual and workplace learning contexts. A further point of interest is how academics in professional and higher education settings interpret and implement pedagogies in the current global conversation space and re-creation of higher education. This study questioned how the notion and practice of transcending pedagogies enables us to re-imagine and reshape university curricula. It explored the nature of teaching and learning spaces and those professional and higher education (current and emerging) pedagogies that can be implemented across these spaces. We set out to identify how transcending pedagogies can assist students in learning to deal with complexity, uncertainty and change in the practice worlds and better appeal to students who are making decisions on where to enrol. The data for this study was collected through in-depth interviews and focus groups with academics and policy makers within academia.

Keywords: Transcending Pedagogies, teaching and learning strategies, learning spaces, pedagogies

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Authors: Ibrahim Iddrisu, Joseph Ayariga, Junhuan Xu, Ayomide Adebanjo, Boakai K. Robertson, Michelle Samuel-Foo, Olufemi Ajayi

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The rise of antimicrobial resistance is a global public health crisis that threatens the effective control and prevention of infections. Due to the emergence of pan drug-resistant bacteria, most antibiotics have lost their efficacy. Bacteriophages or their components are known to target bacterial cell walls, cell membranes, and lipopolysaccharides (LPS) and hydrolyze them. Bacteriophages, being the natural predators of pathogenic bacteria, are inevitably categorized as ‘human friends’, thus fulfilling the adage that ‘the enemy of my enemy is my friend’. Leveraging on their lethal capabilities against pathogenic bacteria, researchers are searching for more ways to overcome the current antibiotic resistance challenge. In this study, we expressed and purified epsilon 34 phage tail spike protein (E34 TSP) from the E34 TSP gene, then assessed the ability of this bacteriophage protein in the killing of two CBD-resistant strains of Salmonella spp. We also assessed the ability of the tail spike protein to cause bacteria membrane disruption and dehydrogenase depletion. We observed that the combined treatment of CBD-resistant strains of Salmonella with CBD and E34 TSP showed poor killing ability, whereas the mono treatment with E34 TSP showed considerably higher killing efficiency. This study demonstrates that the inhibition of the bacteria by E34 TSP was due in part to membrane disruption and dehydrogenase inactivation by the protein. The results of this work provide an interesting background to highlight the crucial role phage proteins such as E34 TSP could play in pathogenic bacterial control.

Keywords: cannabidiol, resistance, Salmonella, antimicrobials, phages

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Authors: Cheng-Yen Lu, Chin-Yuan Hsu

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Ambient temperature reduction (ATR) can extend the lifespan of an annual fish (Nothobranchius rachovii), but the underlying mechanism is unknown. In this study, the expression, concentration, and activity of cellular-degraded molecules were evaluated in the muscle of N. rachovii reared under high (30 °C), moderate (25 °C), and low (20 °C) ambient temperatures by biochemical techniques. The results showed that (i) the activity of the 20S proteasome, the expression of microtubule-associated protein 1 light chain 3-II (LC3-II), the expression of lysosome-associated membrane protein type 2a (Lamp 2a), and lysosome activity increased with ATR; (ii) the expression of the 70 kD heat shock cognate protein (Hsc 70) decreased with ATR; (iii) the expression of the 20S proteasome, the expression of lysosome-associated membrane protein type 1 (Lamp 1), the expression of molecular target of rapamycin (mTOR), the expression of phosphorylated mTOR (p-mTOR), and the p-mTOR/mTOR ratio did not change with ATR. These findings indicated that ATR activated the activity of proteasome, macroautophagy, and chaperone-mediated autophagy. Taken together these data reveal that ATR likely activates cellular degradation activity to extend the lifespan of N. rachovii.

Keywords: ambient temperature reduction, autophagy, degradation activity, lifespan, proteasome

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Authors: F. S. Alavi, D. Mowla, F. Esmaeilzadeh

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In this paper, the Eclipse 300 simulator was used to perform compositional modeling of gas injection process for enhanced condensate recovery of a real gas condensate well in south of Iran here referred to as SA4. Some experimental data were used to tune the Peng-Robinson equation of state for this case. Different scenarios of gas injection at current reservoir pressure and at abandonment reservoir pressure had been considered with different gas compositions. Methane, carbon dioxide, nitrogen and two other gases with specified compositions were considered as potential gases for injection. According to the obtained results, nitrogen leads to highest pressure maintenance in the reservoir but methane results in highest condensate recovery among the selected injection gases. At low injection rates, condensate recovery percent is strongly affected by gas injection rate but this dependency shifts to zero at high injection rates. Condensate recovery is higher in all cases of injection at current reservoir pressure than injection at abandonment pressure. Using a constant injection rate, increasing the production well bottom hole pressure results in increasing the condensate recovery percent and time of gas breakthrough.

Keywords: gas-condensate reservoir, case-study, compositional modelling, enhanced condensate recovery, gas injection

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Authors: José Davi Oliveira De Moura, Chou Sin Chan

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In this study, the effect of convective momentum transport (CMT) on the life of cyclone systems and their organization is analyzed. A case of strong precipitation, in the southeast of Brazil, was simulated using Eta model with two kinds of convective parameterization: Kain-Fritsch without CMT and Kain-fritsch with CMT. Reanalysis data from CFSR were used to compare Eta model simulations. The Wind, mean sea level pressure, rain and temperature are included in analysis. The rain was evaluated by Equitable Threat Score (ETS) and Bias Index; the simulations were compared among themselves to detect the influence of CMT displacement on the systems. The result shows that CMT process decreases the intensity of meso cyclones (higher pressure values on nuclei) and change the positions and production of rain. The decrease of intensity in meso cyclones should be caused by the dissolution of momentum from lower levels from up levels. The rain production and rain distribution were altered because the displacement of the larger systems scales was changed. In addition, the inclusion of CMT process is very important to improve the simulation of life time of meteorological systems.

Keywords: convection, Kain-Fritsch, momentum, parameterization

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Authors: Jean C. G. Silva, Kaline N. Ferreira, Rennio F. Sena, Flavio L. H. Silva

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The Prosopis juliflora (called algaroba in Northeastern Region of Brazil) is a species of medium to large size that can reach 18 meters high, being typical of arid and semi-arid regions by to requirement less water to survive; this is a fundamental attribute from its adaptation. It's considered of multiple uses, because the trunk, the fruit, and the algaroba pods are utilized for several purposes, among them, the production of wood from lumber mill, charcoal, alcohol, animal and human consumption, being hence, a culture of economic and social value. The use of waste Prosopis juliflora can be carried out for like pyrolysis and gasification processes, in order to energy production in those regions where it is grown. Thus this study aims to characterize the residue of the algaroba pods and evaluate the kinetic parameters, activation energy (Ea) and pre-exponential factor (k0), the devolatilization process through the data obtained from TG/DTG curves with different levels of heating rates. At work was used the heating rates of 5 K.min-1, 10 K.min-1, 15 K.min-1, 20 K.min-1 and 30 K.min-1, in inert nitrogen atmosphere (99.997%) under a flow of 40 ml.min-1. The kinetic parameters were obtained using the methods of Friedman and Ozawa-Flynn-Wall.

Keywords: activation energy, devolatilization, kinetic parameters, waste

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy

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Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.

Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink

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Authors: Ana M. Korol, Bibiana Riquelme, Osvaldo A. Rosso

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Since erythrocyte deformability analysis is mostly qualitative, the development of quantitative nonlinear methods is crucial for restricting subjectivity in the study of cell behaviour. An electro-optic mechanic system called erythrodeformeter has been developed and constructed in our laboratory in order to evaluate the erythrocytes' viscoelasticity. A numerical method formulated on the basis of fractal approximation for ordinary (OBM) and fractionary Brownian motion (FBM), as well as wavelet transform analysis, are proposed to distinguish chaos from noise based on the assumption that diffractometric data involves both deterministic and stochastic components, so it could be modelled as a system of bounded correlated random walk. Here we report studies on 25 donors: 4 alpha thalassaemic patients, 11 beta thalassaemic patients, and 10 healthy controls non-alcoholic and non-smoker individuals. The Correlation Coefficient, a nonlinear parameter, showed evidence of the changes in the erythrocyte deformability; the Wavelet Entropy could quantify those differences which are detected by the light diffraction patterns. Such quantifiers allow a good deal of promise and the possibility of a better understanding of the rheological erythrocytes aspects and also could help in clinical diagnosis.

Keywords: red blood cells, deformability, nonlinear dynamics, chaos theory, wavelet trannsform

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Authors: Rigas Dimakopoulos, Marianna Papadopoulou, Roser Pons

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Background: Participation in family, recreational activities and self-care is an integral part of health. It is also the main outcome of rehabilitation services for children and adolescents with motor disabilities. There are currently no tools in Greek to assess participation in young children. Purpose: To culturally adapt and validate the Greek version of the Child Engagement in Daily Living (CEDL). Method: The CEDL was cross-culturally translated into Greek using forward-backward translation, review by the expert committee, pretest application and final review. Internal consistency was evaluated using the Cronbach alpha and test-retest reliability using the intra-class correlation coefficient (ICC). Parents of children aged 18 months to 5 years and with motor disabilities were recruited. Participants completed the CEDL and the children’s gross motor function was classified using the Gross Motor Function Classification System (GMFCS). Results: Eighty-three children were included, GMFCS I-V. Mean ± standard deviation of the CEDL domains “frequency of participation” “enjoyment of participation” and “self-care” were 58.4±14.0, 3.8±1.0 and 49.9±24, respectively. Internal consistency of all domains was high; Cronbach alpha for “frequency of participation” was 0.83, for “enjoyment of participation” was 0.76 and for “self-care” was 0.92. Test-retest reliability (ICC) was excellent for the “self-care” (0.95) and good for “frequency of participation” and “enjoyment of participation” domains (0.90 and 0.88, respectively). Conclusion: The Greek CEDL has good reliability. It can be used to evaluate participation in Greek young children with motor disabilities GMFCS levels I-V.

Keywords: participation, child, disabilities, child engagement in daily living

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

Abstract:

Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: M. Nasiri

Abstract:

Aim: Considering the hypoglisimic ad hipolipidimic effect of the fenugreek seed and aerobic exercise training, this study was conducted to evaluate the effect of fenugreek and aerobic exercise training on insulin resistance in women with type 2 diabetes. Methodology: 32 patients with type II diabetes were selected and randomly divided into four groups: control, fenugreek, training and fenugreek - training. Fenugreek groups used 10 grams of fenugreek seeds daily for eight weeks on two occasions before noon and evening meal. Training of groups is also performed a regular program of aerobic exercise 65-55% of maximum heart rate (4 days per week).Two days before and after the training period, blood samples were taken from their brachial veins in a fasting state (12 hours prior to the test) in a sitting position. The data was analyzed used of t-independent and ANOVA at a significance level of α < 0.05. Results: Intra-group changes in all experimental groups showed that significant decrease insulin resistance, and the difference between groups showed significant difference between the groups of fenugreek - training than other groups there. Conclusions: According to the research findings to fenugreek combined with aerobic exercise more beneficial effect on the inhibition of insulin resistance in women with diabetes are recommended to them.

Keywords: fenugreek, training, insulin resistance, diabetes

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Authors: Yi Shan Wu, Ting Hsuan Wu, Li Wei Cheng, Pei Yu Guo

Abstract:

Given the fiercely competitive environment, human capital is one of the most valuable assets in a commercial enterprise. Therefore, developing strategies to acquire more talents is crucial. Talents are mainly attracted by both internal and external employer brands as well as by the messages conveyed from the employer image. This not only manifests the importance of a brand and an image of an organization but shows people might be affected by their personal values when assessing an organization as an employer. The goal of the present study is to examine the association between employer brand, employer image, and the likelihood of increasing organizational attractiveness. In addition, we draw from social identity theory to propose value congruence may affect the relationship between employer brand and employer image. Data was collected from those people who only worked less than a year in the industry via an online survey (N=209). The results show that employer image partly mediates the effect of employer brand on organizational attractiveness. In addition, the results also suggest that value congruence does not moderate the relationship between employer brand and employer image. These findings explain why building a good employer brand could enhance organization attractiveness and indicate there should be other factors that may affect employer image building, offering directions for future research.

Keywords: organizational attractiveness, employer brand, employer image, value congruence

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Authors: Sakti Mandal

Abstract:

Varying distribution of land surface temperature in an urbanized environment is a globally addressed phenomenon. Usually has been noticed that criticality of surface temperature increases from the periphery to the urban centre. As the centre experiences maximum severity of heat throughout the year, it also represents most critical zone in terms of thermal condition. In this present study, an attempt has been taken to propose a quantitative approach of thermal critical zonation (TCZ) on the basis of seasonal temperature variation. Here the zonation is done by calculating thermal critical value (TCV). From the Landsat 8 thermal digital data of summer and winter seasons for the year 2014, the land surface temperature maps and thermally critical zonation has been prepared, and corresponding dataset has been computed to conduct the overall study of that particular study area. It is shown that TCZ can be clearly identified and analyzed by the help of inter-seasonal temperature range. The results of this study can be utilized effectively in future urban development and planning projects as well as a framework for implementing rules and regulations by the authorities for a sustainable urban development through an environmentally affable approach.

Keywords: thermal critical values (TCV), thermally critical zonation (TCZ), land surface temperature (LST), Landsat 8, Kolkata Municipal Corporation (KMC)

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Authors: Terada Pinyo

Abstract:

This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.

Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

Abstract:

In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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