Search results for: species at risk

Authors: William Cheng, Yuni Astria, Rini Sekartini

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Background: Prevalence of anemia among school-aged children is relatively high (25.4%). This condition can affect children’s life, including cognitive function. One of the most common factors that is associated with anemia in children is nutritional status. This simple indicator will be very helpful in identifying more population at risk. The aim of this study is to correlate the clinical implication of nutritional status to the prevalence of anemia in children, with intention to determine a more effective nutritional status indicator in detecting anemia. Method: Anthropometric and haemoglobin status were gathered from children between 5 to 7-years-old in one of the urban areas in Jakarta in 2012. We identified children with haemoglobin level under 11.5 as anemia and correlated them to their WHO z-score from each of these indicators: Body Weight for Age (normal weight and underweight), Height for Age (not stunted and stunted), and Body Mass Index for Age (not wasted and wasted). Results: A total of 195 children were included in this research and 57 of them (29,2%) were diagnosed as anemia. The majority of the children had good nutritional status, however, 30 (15,4%) of them were found to be underweight, 33 (16,9%) were stunted, and 1 children (0,5%) was wasted. There were no overweight result found in this population. From the three nutritional status indicators, none proved to be statistically significant in relation to the incidence of anemia (p>0.05). Out of 33 children who were diagnosed as stunted, 36.36 % were found to have anemia, in comparison to 27,7% of children who were not stunted. Meanwhile, among 30 children who were diagnosed as underweight, 33,3 % of them were anemic whereas only 28,4% of the normal weight group were anemic. Conclusion: In this study, there is no significant correlation between anemia with any nutritional status indicator. However, more than a third of the stunted children are proven to have low haemoglobin status. The finding of stunting in children should be given more attention to further investigate for anemia.

Keywords: school-aged children, nutritional status, anemia, pediatrics

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Authors: Joulié Aurélien, Jourdain Elsa, Bailly Xavier, Gasqui Patrick, Yang Elise, Leblond Agnès, Rousset Elodie, Sidi-Boumedine Karim

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Q fever is a worldwide zoonosis caused by the gram-negative obligate intracellular bacterium Coxiella burnetii. Following the recent outbreaks in the Netherlands, a hyper virulent clone was found to be the cause of severe human cases of Q fever. In livestock, Q fever clinical manifestations are mainly abortions. Although the abortion rates differ between ruminant species, C. burnetii’s virulence remains understudied, especially in enzootic areas. In this study, the infectious potential of three C. burnetii isolates collected from French farms of small ruminants were compared to the reference strain Nine Mile (in phase II and in an intermediate phase) using an in vivo (CD1 mice) model. Mice were challenged with 105 live bacteria discriminated by propidium monoazide-qPCR targeting the icd-gene. After footpad inoculation, spleen and popliteal lymph node were harvested at 10 days post-inoculation (p.i). The strain invasiveness in spleen and popliteal nodes was assessed by qPCR assays targeting the icd-gene. Preliminary results showed that the avirulent strains (in phase 2) failed to pass the popliteal barrier and then to colonize the spleen. This model allowed a significant differentiation between strain’s invasiveness on biological host and therefore identifying distinct virulence profiles. In view of these results, we plan to go further by testing fifteen additional C. burnetii isolates from French farms of sheep, goat and cattle by using the above-mentioned in vivo model. All 15 strains display distant MLVA (multiple-locus variable-number of tandem repeat analysis) genotypic profiles. Five of the fifteen isolates will bee also tested in vitro on ovine and bovine macrophage cells. Cells and supernatants will be harvested at day1, day2, day3 and day6 p.i to assess in vitro multiplication kinetics of strains. In conclusion, our findings might help the implementation of surveillance of virulent strains and ultimately allow adapting prophylaxis measures in livestock farms.

Keywords: Q fever, invasiveness, ruminant, virulence

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Authors: Sarakorn Sukaviriya

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This paper describes the inspection procedure, root cause analysis, the rectification of crack, and how to apply the procedure with other similar plants. During the operation of the steam turbine (620MW), instruments such as speed sensor of steam turbine, the servo valve of main stop valve and electrical wires were malfunction caused by leakage steam from main steam governing valve. Therefore, the power plant decided to shutdown steam turbines for figuring out the cause of leakage steam. Inspection techniques to be applied in this problem were microstructure testing (SEM), pipe stress analysis (FEM) and non-destructive testing. The crack was initially found on main governing valve’s weldment by visual inspection. To analyze more precisely, pipe stress analysis and microstructure testing were applied and results indicated that the crack was intergranular and originated from the weld defect. This weld defect caused the notch with high-stress concentration which created crack and then propagated to steam leakage. The major root cause of this problem was an inappropriate welding process, which created a weld defect. To repair this joint from damage, we used a welding technique by producing refinement of coarse grain HAZ and eliminating stress concentration. After the weldment was completely repaired, other adjacent weldments still had risk. Hence, to prevent any future cracks, non-destructive testing (NDT) shall be applied to all joints in order to ensure that there will be no indication of crack.

Keywords: steam-pipe leakage, steam leakage, weld crack analysis, weld defect

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: A. Díaz-Roa, P. I. Silva Junior, F. J. Bello

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Sarconesiopsis magellanica (Diptera: Calliphoridae) is a medically important necrophagous fly which is used for establishing the post-mortem interval. Dipterous maggots release diverse proteins and peptides contained in larval excretion and secretion (ES) products playing a key role in digestion. The most important mechanism for combating infection using larval therapy depends on larval ES. These larvae are protected against infection by a diverse spectrum of antimicrobial peptides (AMPs), one already known like lucifensin. Special interest in these peptides has also been aroused regarding understanding their role in wound healing since they degrade necrotic tissue and kill different bacteria during larval therapy. The action of larvae on wounds occurs through 3 mechanisms of action: removal of necrotic tissue, stimulation of granulation tissue, and antibacterial action of larval ES. Some components of the ES include calcium, urea, allantoin ammonium bicarbonate and reducing the viability of Gram positive and Gram negative bacteria. The Lucilia sericata fly larvae have been the most used, however, we need to evaluate new species that could potentially be similar or more effective than fly above. This study was thus aimed at identifying and characterizing S. magellanica AMPs contained in ES products for the first time and compared them with the common fly used L. sericata. These products were obtained from third-instar larvae taken from a previously established colony. For the first analysis, ES fractions were separate by Sep-Pak C18 disposable columns (first step). The material obtained was fractionated by RP-HPLC by using Júpiter C18 semi-preparative column. The products were then lyophilized and their antimicrobial activity was characterized by incubation with different bacterial strains. The first chromatographic analysis of ES from L. sericata gives 6 fractions with antimicrobial activity against Gram-positive bacteria Micrococus luteus, and 3 fractions with activity against Gram-negative bacteria Pseudomonae aeruginosa while the one from S. magellanica gaves 1 fraction against M. luteus and 4 against P. aeruginosa. Maybe one of these fractions could correspond to the peptide already known from L. sericata. These results show the first work for supporting further experiments aimed at validating S. magellanica use in larval therapy. We still need to search if we find some new molecules, by making mass spectrometry and ‘de novo sequencing’. Further studies are necessary to identify and characterize them to better understand their functioning.

Keywords: antimicrobial peptides, larval therapy, Lucilia sericata, Sarconesiopsis magellanica

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Authors: Alireza Gholipour, Mergen H. Ghayesh, Anthony Zander, Stephen J. Nicholls, Peter J. Psaltis

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A three-dimensional numerical model of an atherosclerotic coronary ‎artery is developed for the determination of high-risk situation and ‎hence heart attack prediction. Employing the finite element method ‎‎(FEM) using ANSYS, fluid-structure interaction (FSI) model of the ‎artery is constructed to determine the shear stress distribution as well ‎as the von Mises stress field. A flexible model for an atherosclerotic ‎coronary artery conveying pulsatile blood is developed incorporating ‎three-dimensionality, artery’s tapered shape via a linear function for ‎artery wall distribution, motion of the artery, blood viscosity via the ‎non-Newtonian flow theory, blood pulsation via use of one-period ‎heartbeat, hyperelasticity via the Mooney-Rivlin model, viscoelasticity ‎via the Prony series shear relaxation scheme, and micro-calcification ‎inside the plaque. The material properties used to relate the stress field ‎to the strain field have been extracted from clinical data from previous ‎in-vitro studies. The determined stress fields has potential to be used as ‎a predictive tool for plaque rupture and dissection.‎ The results show that stress concentration due to micro-calcification ‎increases the von Mises stress significantly; chance of developing a ‎crack inside the plaque increases. Moreover, the blood pulsation varies ‎the stress distribution substantially for some cases.‎

Keywords: atherosclerosis, fluid-structure interaction‎, coronary arteries‎, pulsatile flow

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Authors: Marzieh Sayyad, Mohsen Salesi

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Metabolic syndrome (MetS), a collection of cardiometabolic risk factors, is linked to the development of cardiovascular disease (CVD) and diabetes. The prevalence of MetS is on the rise with more women affected than men. The goal of this study was to compare the effects of resistance and aerobic exercise training on metabolic syndrome components in non-athlete, middle-aged woman. 51 non-athlete overweight female participated voluntarily in this study. Participants were divided randomly into three groups including resistance, aerobic and control group (number of each group 17). 24 hours before the beginning of training program, the blood sample was taken in fasting state. The two training groups participated in sport activities for eight weeks, three times a week duration 60-90 minutes. Two days following the end of the 8th week, all the measurements were performed similar to the pretest phase. The data was analyzed using one-way analysis of variance. The results showed that aerobic exercise training significantly decreased weight (p=.05), triglyceride (p<0.01) and systolic blood pressure (p<0.02) and HDL-c (p<0.01) was significantly increased. Also in resistance exercise training group TG decreased significantly (p<0.01) and HDL-c (p<0.05) was significantly increased. This study demonstrated that a regular physical activity program improved several metabolic and physiological parameters in healthy, previously sedentary subjects with the metabolic syndrome. In conclusion, it seems that this type of training can be efficient, safe and inexpensive way in order to reduce and prevent metabolic syndrome.

Keywords: aerobic exercise, metabolic syndrome, overweight sedentary female, resistance exercise

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: Hanbyul Kim, Hye-Jin Kin, Taehun Park, Woo Jun Sul, Susun An

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Skin is the largest organ of the human body and can provide the diverse habitat for various microorganisms. The ecology of the skin surface selects distinctive sets of microorganisms and is influenced by both endogenous intrinsic factors and exogenous environmental factors. The diversity of the bacterial community in the skin also depends on multiple host factors: gender, age, health status, location. Among them, age-related changes in skin structure and function are attributable to combinations of endogenous intrinsic factors and exogenous environmental factors. Skin aging is characterized by a decrease in sweat, sebum and the immune functions thus resulting in significant alterations in skin surface physiology including pH, lipid composition, and sebum secretion. The present study gives a comprehensive clue on the variation of skin microbiota and the correlations between ages by analyzing and comparing the metagenome of skin microbiome using Next Generation Sequencing method. Skin bacterial diversity and composition were characterized and compared between two different age groups: younger (20 – 30y) and older (60 - 70y) Xian, Chinese women. A total of 73 healthy women meet two conditions: (I) living in Xian, China; (II) maintaining healthy skin status during the period of this study. Based on Ribosomal Database Project (RDP) database, skin samples of 73 participants were enclosed with ten most abundant genera: Chryseobacterium, Propionibacterium, Enhydrobacter, Staphylococcus and so on. Although these genera are the most predominant genus overall, each genus showed different proportion in each group. The most dominant genus, Chryseobacterium was more present relatively in Young group than in an old group. Similarly, Propionibacterium and Enhydrobacter occupied a higher proportion of skin bacterial composition of the young group. Staphylococcus, in contrast, inhabited more in the old group. The beta diversity that represents the ratio between regional and local species diversity showed significantly different between two age groups. Likewise, The Principal Coordinate Analysis (PCoA) values representing each phylogenetic distance in the two-dimensional framework using the OTU (Operational taxonomic unit) values of the samples also showed differences between the two groups. Thus, our data suggested that the composition and diversification of skin microbiomes in adult women were largely affected by chronological and physiological skin aging.

Keywords: next generation sequencing, age, Xian, skin microbiome

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Authors: Shahjada Selim

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Background: Erectile dysfunction (ED) is an important impediment to quality of life of men. ED is approximate, three times more common in diabetic than non-diabetic men, and diabetic men develop ED earlier than age-matched non-diabetic subjects. Glycemic control and other factors may contribute in developing and or deteriorating ED. Aim: The aim of the study was to determine the prevalence of ED and its risk factors in type 2 diabetic (T2DM) men in Bangladesh. Methods: During 2013-2014, 3980 diabetic men aged 30-69 years were interviewed at the out-patient departments of seven diabetic centers in Dhaka by using the validated Bengali version of the questionnaire of the International index of erectile function (IIEF) for evaluation of baseline erectile function (EF). The indexes indicate a very high correlation between the items and the questionnaire is consistently reliable. Data were analyzed with Chi-squared (χ²) test using SPSS software. P ≤ 0.05 was considered significant. Results: Out of 3790, ED was found in 2046 (53.98%) of T2DM men. The prevalence of ED was increased with age from 10.5% in men aged 30-39 years to 33.6% in those aged over 60 years (P < 0.001). In comparison with patients with reported diabetes lasting ≤ 5 years (26.4%), the prevalence of ED was less than in those with diabetes of 6-11 years (35.3%) and of 12-30 years (42.5%, P <0.001). ED increased significantly in those who had poor glycemic control. The prevalence of ED in patients with good, fair and poor glycemic control was 22.8%, 42.5% and 47.9% respectively (P = 0.004). Treatment modalities (medical nutrition therapy, oral agents, insulin, and insulin plus oral agents) had significant association with ED and its severity (P < 0.001). Conclusion: Prevalence of ED is very high among T2DM men in Bangladesh and can be reduced the burden by improving glycemic status. Glycemic control, duration of diabetes, treatment modalities, increasing age are associated with ED.

Keywords: erectile dysfunction, diabetes, men, Bangladesh

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Authors: Kouorsh Zarea, Fatemeh Hassani, Samira Beiranvand, Akram Mohamadi

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Background and Objectives: Medication error in hospitals is a major cause of the errors which disrupt the health care system. The aim of this study was to assess the nurses’ medication errors and related factors. Material and methods: This was a descriptive study on 225 nurses in various hospitals, selected through multistage random sampling. Data was collected by three researcher made tools; demographic, medication error and related factors questionnaires. Data was analyzed by descriptive statistics, Chi-square, Kruskal-Wallis, One-way analysis of variance. Results: Based on the results obtained, the type of medication errors giving drugs to patients later or earlier (55.6%), multiple oral medication together regardless of their interactions (36%) and the postoperative analgesic without a prescription (34.2%), respectively. In addition, factors such as the shortage of nurses to patients’ ratio (57.3%), high load functions (51.1%) and fatigue caused by the extra work (40.4%), were the most important factors affecting the incidence of medication errors. The fear of legal issues (40%) are the most important factor is the lack of reported medication errors. Conclusions: Based on the results, effective management and promotion motivate nurses. Therefore, increasing scientific and clinical expertise in the field of nursing medication orders is recommended to prevent medication errors in various states of nursing intervention. Employing experienced staff in areas with high risk of medication errors and also supervising less-experienced staff through competent personnel are also suggested.

Keywords: medication error, nurse, clinical care, drug errors

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Authors: Laura Valdés-Santiago, José Luis Castro-Guillén, Jorge Noé García-Chávez, Rosalba Alonso-Rodríguez, Rafael Vargas-Bernal

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The quality and availability of the water contained in dams (artificial bodies of water) are at risk due to the presence of uncontrolled growths of cyanobacteria capable of producing cyanotoxins that affect the ecosystem and harm the health of humans and animals. The physicochemical properties were measured, and the degree of eutrophy of four dams from Guanajuato was determined. They presented a pH of 6.1 to 8.4, conductivity of 121 to 415 μS/cm², chlorophyll of 0.43-42.43 μg/L, NO₃- 0-1.2 mg/L and PO₄3- 0.11 to 0.84 mg/L; considering these parameters, the prey most prone to the development of cyanobacterial blooms were El Palote dam, La Purísima dam, and Allende dam, but not El Conejo dam. The potentially toxic cyanobacteria identified were Planktothrix agardhii, Oscillatoria sp., Raphidiopsis sp., and Microcystis sp., Microcystin-LR, Nodularin, and Cylindrospermopsin were quantified, presenting values between 0.08-0.42 and 0.02-2.05 ppb, respectively, the water bodies with the highest concentration were El Palote dam and La Purísima dam. Microcystin-LR and/or Nodularin levels are within the guideline values for human consumption in drinking water established by the World Health Organization for Microcystin-LR and for Cylindrospermopsin by the Oregon Health Authority (OHA) in all dams. This work is relevant due to the use of these bodies of water for agriculture and human consumption in the state, and the presence of toxin-producing cyanobacteria can represent an environmental, ecotoxicological, and health problem, so it is recommended to establish a program of frequent monitoring of cyanobacteria and cyanotoxins in the state's dams.

Keywords: Planktrothrix agardhii, Raphidiopsis sp., Microcystis sp., Cyanobacterial blooms, Cyanotoxins

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Authors: Ekta, G. K. Darbha

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Nanotechnology offers the potential of simultaneously increasing efficiency as compared to their bulk material as well as reducing harmful environmental impacts of pesticides in field of agriculture. The term nanopesticide covers different pesticides that are cumulative of several surfactants, polymers, metal ions, etc. of nanometer size ranges from 1-1000 nm and exhibit abnormal behavior (high efficacy and high specific surface area) of nanomaterials. Commercial formulations of pesticides used by farmers nowadays cannot be used effectively due to a number of problems associated with them. For example, more than 90% of applied formulations are either lost in the environment or unable to reach the target area required for effective pest control. Around 20−30% of pesticides are lost through emissions. A number of factors (application methods, physicochemical properties of the formulations, and environmental conditions) can influence the extent of loss during application. It is known that among various formulations, polymer-based formulations show the greatest potential due to their greater efficacy, slow release and protection against premature degradation of active ingredient as compared to other commercial formulations. However, the nanoformulations can have a significant effect on the fate of active ingredient as well as may release some new ingredients by reacting with existing soil contaminants. Environmental fate of these newly generated species is still not explored very well which is essential to field scale experiments and hence a lot to be explored in the field of environmental fate, nanotoxicology, transport properties and stability of such formulations. In our preliminary work, we have synthesized polymer based nanoformulation of commercially used weedicide atrazine. Atrazine belongs to triazine class of herbicide, which is used in the effective control of seed germinated dicot weeds and grasses. It functions by binding to the plastoquinone-binding protein in PS-II. Plant death results from starvation and oxidative damage caused by breakdown in electron transport system. The stability of the suspension of nanoformulation containing herbicide has been evaluated by considering different parameters like polydispersity index, particle diameter, zeta-potential under different environmental relevance condition such as pH range 4-10, temperature range from 25°C to 65°C and stability of encapsulation also have been studied for different amount of added polymer. Morphological characterization has been done by using SEM.

Keywords: atrazine, nanoformulation, nanopesticide, nanotoxicology

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Tejinder Singh Sidhu

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Hot corrosion has been recognized as a severe problem in steam-powered electricity generation plants and industrial waste incinerators as it consumes the material at an unpredictably rapid rate. Consequently, the load-carrying ability of the components reduces quickly, eventually leading to catastrophic failure. The inability to either totally prevent hot corrosion or at least detect it at an early stage has resulted in several accidents, leading to loss of life and/or destruction of infrastructures. A number of countermeasures are currently in use or under investigation to combat hot corrosion, such as using inhibitors, controlling the process parameters, designing a suitable industrial alloy, and depositing protective coatings. However, the protection system to be selected for a particular application must be practical, reliable, and economically viable. Due to the continuously rising cost of the materials as well as increased material requirements, the coating techniques have been given much more importance in recent times. Coatings can add value to products up to 10 times the cost of the coating. Among the different coating techniques, thermal spraying has grown into a well-accepted industrial technology for applying overlay coatings onto the surfaces of engineering components to allow them to function under extreme conditions of wear, erosion-corrosion, high-temperature oxidation, and hot corrosion. In this study, the hot corrosion performances of Ni-20Cr and Cr₃C₂-NiCr coatings developed by High Velocity Oxy-Fuel (HVOF) process have been studied. The coatings were developed on a Fe-based superalloy, and experiments were performed in an actual industrial environment of a coal-fired boiler. The cyclic study was carried out around the platen superheater zone where the temperature was around 1000°C. The study was conducted for 10 cycles, and one cycle was consisting of 100 hours of heating followed by 1 hour of cooling at ambient temperature. Both the coatings deposited on Fe-based superalloy imparted better hot corrosion resistance than the uncoated one. The Ni-20Cr coated superalloy performed better than the Cr₃C₂-NiCr coated in the actual working conditions of the coal fired boiler. It is found that the formation of chromium oxide at the boundaries of Ni-rich splats of the coating blocks the inward permeation of oxygen and other corrosive species to the substrate.

Keywords: hot corrosion, coating, HVOF, oxidation

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Authors: Imad Buishi, Almabrouk Fares, Hallowma Helmi

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Infection with verocytotoxin-producing Escherichia coli O157 in humans can lead to mild or bloody diarrhea with the hemolytic uremic syndrome (HUS) as a possible complication. Cattle appear to be important reservoirs for VTEC O157. Epidemiologic studies on the prevalence of VTEC O157 in dairy cattle in Libya have never been conducted. To investigate the prevalence and the risk factors associated with VTEC O157 on dairy farms in Tripoli region, fecal samples from 200 apparently healthy cows were collected once from 15 randomly selected dairy farms in the period July 2010 through September 2010. All fecal samples were examined for the prevalence of VTEC O157 by conventional plating using Sorbitol-MacConkey agar (SMAC). Isolated of E. coli were subjected to slide agglutination test using E. coli O157 antiserum. The results pointed out that the prevalence within-herd and among herds were 9% and 60% respectively. The prevalence of VTEC O157 in fecal samples of dairy cattle was significantly associated with husbandry practices on farm-level such as signs of diarrhoea (p=0.02, OR=3.2) and sharing water trough (p= 0.03, OR=3.0). It was concluded that dairy cattle in Tripoli area are important reservoirs of VTEC O157 strains that are potentially pathogenic for humans. When aiming at reducing risks for human by intervention at farm-level, it is of importance to reduce the number of positive animals and farms. For this, more research is needed to devise mitigation strategies that will reduce the on-farm contamination of VTEC O157.

Keywords: VTEC O157, prevalence, dairy cattle, tripoli

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Arab M., Ait Abdallah M., Zeraoulia N., Boumaza H., Aoutia M., Griene L., Ait Abdelkader B.,

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breast and ovarian cancer are respectively the first and fourth leading causes of cancer among women in Algeria. A family story of cancer in the most important risk factor, and in most cases of families with breast and /or ovarian cancer, the pattern of cancer family can be attributed to mutation in BRCA1/2genes. objectibes: the aim of our study in to investigate the spectrum of BRCA1/2 germiline mutation in familial breast and /or ovarian cancer and to determine the prevalence and the nature of BRCA1/2mutation in Algeria methods: we deremined the prevalence of BRCA1/2 mutation within a cohort of 161 probands selected according the eisinger score double stranded sanger sequencing of all coding exons of BRCA1/2including flanking intronic region were performed results: we identified a total of 23 distinct deleterious mutations (class5) 12 differents mutations in BRCA1(52%) and 11 in BRCA2(48%). 78% (18/23) were protein truncating and 22%(5/23) missens mutations.3 novel deleterious mutations have been identified, which have not been described in public mutation database. one new mutation were found in two unrelated patients. the overall mutation detection rate in our study is 28,5%(46/161).more over, an UVS c7783 located in BRCA2 is found in two unrelated probands and segregate in the 02 families/ conclusion: our results sugget of large spectrum of BRCA1/2 mutation in Algerian breast/ovarian cancer family. The nature and prevalence of BRCA1/2mutation in algerian families are ongoing in a larger study, 80 probands are to day under investigation. This study which may therefore identify the genetic particularity of Algerian breast /ovarian cancer.

Keywords: BRCA1/2 mutations, hereditary breast cancer, algerian women, prvalence

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Authors: Valentina Colonnello, Paolo Maria Russo

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Decades of cross-species affective neuroscience research by Panksepp and others have identified basic evolutionarily preserved subcortical emotional systems that humans share with mammals and many vertebrates. These primary emotional systems encode unconditional affective responses and contribute to the development of personality traits throughout ontogenesis and interactions with the environment. The Affective Neuroscience Personality Scale (ANPS) measures individual differences in affective personality traits associated with the basic emotional systems of CARE, PLAY, SEEKING, SADNESS, FEAR, and ANGER, along with Spirituality, which is a more cognitively and socially refined expression of affectivity. Though the ANPS’s power to predict human psychological distress has been documented, to the best of our knowledge, its predictive power for psychological wellbeing has not been explored. This study therefore investigates the relationship between affective neuroscience traits and psychological wellbeing facets. Because the emotional systems are thought to influence cognitively-mediated mental processes about the self and the world, understanding the relationship between affective traits and psychological wellbeing is particularly relevant to understanding the affective dimensions of health. In a cross-sectional study, healthy participants (n = 402) completed the ANPS and the Psychological Wellbeing scale. Multiple regressions revealed that each facet of wellbeing was explained by two to four affective traits, and each trait was significantly related to at least one aspect of wellbeing. Specifically, SEEKING predicted all the wellbeing facets, except for positive relations; CARE predicted personal growth, positive relations, purpose in life, and self-acceptance; PLAY and, inversely, ANGER predicted positive relations; SADNESS inversely predicted autonomy, while FEAR inversely predicted purpose in life. SADNESS and FEAR inversely predicted environmental mastery and self-acceptance. Finally, Spirituality predicted personal growth, positive relations, and self-acceptance. These findings are the first to show the relationship between affective neuroscience personality traits and psychological wellbeing. They also call attention to the distinctive role of FEAR and PANIC traits in psychological wellbeing facets, thereby complementing or even overcoming the traditional personality approach to neuroticism as a global trait.

Keywords: affective neuroscience, individual differences, personality, wellbeing

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Authors: Larry Audet

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Creativity is suddenly and fortunately a new educational focus in the United Arab Emirates and around the world. Yet still today many leaders of creativity are not sure how to introduce it to their teachers. It is impossible to simultaneously introduce every aspect of creativity into a work climate and reach any degree of organizational coherence. The number of alternatives to explore is so great; the information teachers need to learn is so vast, that even an approximation to including every concept and theory of creativity into the school organization is hard to conceive. Effective leaders of creativity need evidence-based and practical guidance for introducing and stimulating creativity in others. Machine learning models reveal new findings from KEYS Survey© data about teacher perceptions of stimulants and barriers to their individual and collective creativity. Findings from predictive and causal models provide leaders with a rational for decision-making when introducing creativity into their organization. Leaders should focus on management practices first. Analyses reveal that creative outcomes are more likely to occur when teachers perceive supportive management practices: providing teachers with challenging work that calls for their best efforts; allowing freedom and autonomy in their practice of work; allowing teachers to form creative work-groups; and, recognizing them for their efforts. Once management practices are in place, leaders should focus their efforts on modeling risk-taking, providing optimal amounts of preparation time, and evaluating teachers fairly.

Keywords: creativity, leadership, KEYS survey, teaching, work climate

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Authors: Basanta Raj Adhikari

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Large and small scale earthquakes are frequent in the Nepal, Himalaya, and many co-seismic landslides are resulted out of it. Recently, Gorkha earthquake-2015 has triggered many co-seismic landslides destroying many lives and properties. People have displaced their original places due to having many cracks and unstable ground. Therefore, Nepal has been adopting a pronged development strategy to address the earthquake issues through reconstruction and rehabilitation policy, plans and budgets. Landslides are major threat for the mountain livelihood, and it is very important to investigate and mitigate to improve human wellbeing factoring in considerations of economic growth, environmental safety, and sustainable development. Community based landslide investigation was carried with the involvement of the local community in the Sindhupalchowk District of Central Nepal. Landslide training and field orientation were the major methodological approach of this study. Combination of indigenous and modern scientific knowledge has created unique working environment which enhanced the local capacity and trained people for replication. Local topography of the landslide was created with the help of Total Station and bill of quantity was derived based on it. River training works, plantation of trees and grasses, support structures, surface and sub-surface drainage management are the recommended mitigative measures. This is a very unique example of how academia and local community can work together for sustainable development by reducing disaster risk at the local level with very low-cost technology.

Keywords: community, earthquake, landslides, Nepal

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Authors: N. Mathew, A. Qureshi, D. C. Khakha, R. Sagar

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Adolescents in India, account for one-fifth of the total population and are a significant human resource. Present study was conducted to find out various life stressors of adolescents, coping strategies adopted by them and the impact of stress on adolescent mental health. A descriptive, cross sectional study conducted on schools in the south zone of Delhi, capital city of the country. Data was collected on 360 adolescents between the age group of 13-17 years on socio-demographic profile, Adolescent life event stress scale, brief cope and youth self report for ages 11-18. Adolescents had significantly higher stress on uncontrollable events such as family events, relocation events, accident events and ambiguous events as compared to controllable events such as sexual events, deviance events and autonomy events (p<0.01).Adolescent stress was significantly correlated with various demographic variables in the study. The most frequently used coping strategies by the adolescents were positive reframing, planning, active coping, and instrumental support. It has also been found that the stress has a significant impact on adolescent mental health in the form of either internalizing problems such as anxious, withdrawn and somatic problems or externalizing problems such as rule breaking and aggressive behaviors. Out of the total sample of 360 adolescents 150 were identified as having psycho-social morbidity, including 59 borderline cases and 91 high-risk cases Study pointed out the need for mental health screening among the adolescents and also indicated the need for mental health inputs in educational institutions.

Keywords: adolecents, stress, coping, mental health

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Jamila Fakchich, Mostafa Jamila Lazaar Elachouri, Lakhder Fakchich, Fatna Ouali, Abd Errazzak Belkacem

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Diabetes is a chronic metabolic disease that has a significant impact on the health, quality of life, and life expectancy of patients as well as the health care system. By its nature diabetes, is a multisystem disease with wide-ranging complication that span nearly all region of the body. This epidemic problem, however, is not unique to the industrialized society, but has also hardly struck the developing countries. In Morocco, as developing country, there is an epidemic rise in diabetes, with ensuing concern about the management and control of this disease; it began a chronic burdensome disease of largely middle-aged and elderly people, with a long course and serious complications often resulting in high death-rate, the treatment of diabetes spent vast amount of resources including medicines, diets, physical training. Treatment of this disease is considered problematic due to the lack of effective and safe drugs capable of inducing sustained clinical, biochemical, and histological cure. In Moroccan society, the phytoremedies are some times the only affordable sources of healthcare, particularly for the people in remote areas. In this paper, we present a synthesis work obtained from the ethnobotanical data reported in different specialized journals. A Synthesis of four published ethnobotanical studies that have been carried out in different region of Morocco by different team seekers during the period from 1997 to 2015. Medicinal plants inventoried by different seekers in four Moroccan’s areas have been regrouped and codified, then, Factorial Analysis (FA) and Principal Components Analysis (PCA) are used to analyse the aggregated data from the four studies and plants are classified according to their frequency of use by population. Our work deals with an attempt to gather information on some traditional uses of medicinal plants from different regions of Morocco, also, it was designed to give a set of medicinal plants commonly used by Moroccan people in the treatment of diabetes; In this paper, we intended to provide a basic knowledge about plant species used by Moroccan society for treatment of diabetes. One of the most interesting aspects of this type of works is to assess the relative cultural importance of medicinal plants for specific illnesses and exploring its usefulness in the context of diabetes.

Keywords: Morocco, medicinal plants, ethnobotanical, diabetes, phytoremedies

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Ghanim A. Bekr

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Project success is what must be done for the project to be acceptable to the client, stakeholders and end-users who will be affected by the project. The study of project success and the critical success factors (CSFs) are the means adopted to improve the effectiveness of project. This research is conducted to make an attempt to identify which variables influence the success of project implementation. This study has selected, through an extensive literature review and interviews, (83) factors categorized in (7) groups that the questionnaire respondents were asked to score. The responses from 66 professionals with an average of 15 years of experience in different types of construction projects in Jordan were collected and analyzed using SPSS and most important factors for success for various success criteria are presented depending on the relative importance index to rank the categories. The research revealed the significant groups of factors are: Client related factors, Contractor’s related factors, Project Manager (PM) related factors, and Project management related factors. In addition the top ten sub factors are: Assertion of the client towards short time of the project, availability of skilled labor, Assertion of the client towards high level of the quality, capability of the client in taking risk, previous experience of the PM in similar projects, previous experience of the contractor in similar projects, decision making by the client/ the client’s representative at the right time, assertion of client towards low cost of project, experience in project management in previous projects, and flow of the information among parties. The results would be helpful to construction project professionals in taking proactive measures for successful completion of construction projects in Jordan.

Keywords: construction projects, critical success factors, Jordan, project success

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Authors: Ferah Tesfaye Admasu

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Autism Spectrum Disorder (ASD) often presents significant communication challenges, particularly for non-verbal individuals who struggle to express their needs and emotions effectively. Assistive technologies (AT) have emerged as vital tools in enhancing communication abilities for this population. Recent advancements in artificial intelligence (AI) hold the potential to revolutionize the design and functionality of these technologies. This study explores the application of AI in developing intelligent, adaptive, and user-centered assistive technologies for non-verbal individuals with autism. Through a review of current AI-driven tools, including speech-generating devices, predictive text systems, and emotion-recognition software, this research investigates how AI can bridge communication gaps, improve engagement, and support independence. Machine learning algorithms, natural language processing (NLP), and facial recognition technologies are examined as core components in creating more personalized and responsive communication aids. The study also discusses the challenges and ethical considerations involved in deploying AI-based AT, such as data privacy and the risk of over-reliance on technology. Findings suggest that integrating AI into assistive technologies can significantly enhance the quality of life for non-verbal individuals with autism, providing them with greater opportunities for social interaction and participation in daily activities. However, continued research and development are needed to ensure these technologies are accessible, affordable, and culturally sensitive.

Keywords: artificial intelligence, autism spectrum disorder, non-verbal communication, assistive technology, machine learning

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Authors: Ramesh Nagarajappa, Upasana Mohapatra

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Considered a modern phobia, Nomophobia (NO MObile PHOne PhoBIA) is a term that describes the irrational fear or anxiety of being unable to access one’s own mobile phone. Objectives: To develop and validate the nomophobia questionnaire, administering it to a sample of adolescents representing undergraduate dental students. To assess the prevalence of Nomophobia, determine the usage pattern of mobile phones, and evaluate the impact due to lack of access to mobile phones among undergraduate dental students. Methodology: A cross-sectional study was conducted on 302 undergraduate students at Bhubaneswar through a self-administered questionnaire via Google Forms consisting of 19 items evaluating the pattern and anxiety related to usage of mobile phones. Responses were recorded on a 5-point Likert scale. Kruskal Wallis, Mann-Whitney U, and Chi-square tests were used for statistical analysis. Results: Test-Retest reliability showed kappa of k=0.86 and Internal consistency Chronbach’s-Alpha to be α=0.82. Prevalence of nomophobia (score ≥ 58) was 32.1%, and students at risk of being nomophobic (score 39-57) was 61.9%. It was highest in males (32.6%) and amongst the interns (41.9%) and lowest (25.5%) amongst the second-year students. Participants felt nervous/insecure if their phones were away from them because of the fear that somebody might have accessed their data (3.07±1.93) and or tried to contact them (3.09±1.13), which were not statistically significant (p>0.05). Conclusions: Effect of mobile phone on dental students and the fear of not having their phones with them is increasing elaborately, that needs to be controlled, which if not achieved, would negatively hamper their academic performance and their being in the society.

Keywords: addiction, dental students, mobile phone, nomophobia

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Authors: Siti Khadijah Che Osmi, Mohammed Ahmad Syed

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Underground structures are crucial components which required detailed analysis and design. Tunnels, for instance, are massively constructed as transportation infrastructures and utilities network especially in urban environments. Considering their prime importance to the economy and public safety that cannot be compromised, thus any instability to these tunnels will be highly detrimental to their performance. Recent experience suggests that tunnels become vulnerable during earthquakes and blast scenarios. However, a very limited amount of studies has been carried out to study and understanding the dynamic response and performance of underground tunnels under those unpredictable extreme hazards. In view of the importance of enhancing the resilience of these structures, the overall aims of the study are to evaluate probabilistic future performance of shallow tunnels subjected to seismic and blast loads by developing detailed fragility analysis. Critical non-linear time history numerical analyses using sophisticated finite element software Midas GTS NX have been presented about the current methods of analysis, taking into consideration of structural typology, ground motion and explosive characteristics, effect of soil conditions and other associated uncertainties on the tunnel integrity which may ultimately lead to the catastrophic failure of the structures. The proposed fragility curves for both extreme loadings are discussed and compared which provide significant information the performance of the tunnel under extreme hazards which may beneficial for future risk assessment and loss estimation.

Keywords: fragility analysis, seismic loads, shallow tunnels, blast loads

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Authors: Ashit Syngle, Nidhi Garg, Pawan Krishan

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Background: Endothelial Progenitor Cells (EPCs) are depleted and contribute to increased cardiovascular (CV) risk in rheumatoid arthritis (RA). Statins exert a protective effect in CAD partly by promoting EPC mobilization. This vasculoprotective effect of statin has not yet been investigated in RA. We aimed to investigate the effect of rosuvastatin on EPCs in RA. Methods: 50 RA patients were randomized to receive 6 months of treatment with rosuvastatin (10 mg/day, n=25) and placebo (n=25) as an adjunct to existing stable antirheumatic drugs. EPCs (CD34+/CD133+) were quantified by Flow Cytometry. Inflammatory measures included DAS28, CRP and ESR were measured at baseline and after treatment. Lipids and pro-inflammatory cytokines (TNF-α, IL-6, and IL-1) were estimated at baseline and after treatment. Results: At baseline, inflammatory measures and pro-inflammatory cytokines were elevated and EPCs depleted among both groups. At baseline, EPCs inversely correlated with DAS28 and TNF-α in both groups. EPCs increased significantly (p < 0.01) after treatment with rosuvastatin but did not show significant change with placebo. Rosuvastatin exerted positive effect on lipid spectrum: lowering total cholesterol, LDL, non HDL and elevation of HDL as compared with placebo. At 6 months, DAS28, ESR, CRP, TNF-α and IL-6 improved significantly in rosuvastatin group. Significant negative correlation was observed between EPCs and DAS28, CRP, TNF-α, and IL-6 after treatment with rosuvastatin. Conclusion: First study to show that rosuvastatin improves inflammation and EPC biology in RA possibly through its anti-inflammatory and lipid lowering effect. This beneficial effect of rosuvastatin may provide a novel strategy to prevent cardiovascular events in RA.

Keywords: RA, Endothelial Progenitor Cells, rosuvastatin, cytokines

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