Search results for: polymer identification

Authors: Akbar Rostamabadi, Adel Mazloumi, Abbas Rahimi Foroushani

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This study aimed to determine the Work Ability Index (WAI) and examine the influence of health dimensions and demographic variables on the work ability of Iranian farmers working in small farm enterprises. A cross-sectional study was conducted among 294 male farmers. The WAI and SF-36 questionnaires were used to determine work ability and health status. The effect of demographics variables on the work ability index was investigated with the independent samples t-test and one-way ANOVA. Also, multiple linear regression analysis was used to test the association between the mean WAI score and the SF-36 scales. The mean WAI score was 35.1 (SD=10.6). One-way ANOVA revealed a significant relationship between the mean WAI and age. Multiple linear regression analysis showed that work ability was more influenced by physical scales of the health dimensions, such as physical function, role-physical, and general health, whereas a lower association was found for mental scales such as mental health. The average WAI was at a moderate work ability level for the sample population of farmers in this study. Based on the WAI guidelines, improvement of work ability and identification of factors affecting it should be considered a priority in interventional programs. Given the influence of health dimensions on WAI, any intervention program for preservation and promotion work ability among the studied farmers should be based on balancing and optimizing the physical and psychosocial work environments, with a special focus on reducing physical work load.

Keywords: farmers, SF-36, Work Ability Index (WAI), Iran

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Authors: Ataa A. Said, Elsayed A. Abuotabl, Gehan F. Abdel Raoof, Khaled Y. Mohamed

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The aim of this study is to evaluate antihyperglycaemic and antihyperlipidemic activities of Pleiogynium timorense (DC.) Leenh (Anacardiaceae) seeds as well as to isolate and identify the bioactive compounds. Antihyperglycaemic effect was evaluated by measuring the effect of two dose levels (150 and 300 mg/kg) of 70% methanol extract of Pleiogynium timorense seeds on blood glucose level when administered 45 minutes before glucose loading. In addition, the effect of the plant extract on the lipid profile was determined by measuring serum total lipids (TL), total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C). Furthermore, the bioactive compounds were isolated and identified by chromatographic and spectrometric methods.The results showed that the methanolic extract of the seeds significantly reduced the levels of blood glucose,(TL), (TC), (TG) and (LDL-C) but no significant effect on (HDL-C) comparing with control group. Furthermore, four phenolic compound were isolated which were identified as; catechin, gallic acid, para methoxy benzaldehyde and pyrogallol which were isolated for the first time from the plant. In addition sulphur -containing compound (sulpholane) was isolated for the first time from the plant and from the family. To our knowledge, this is the first study about antihyperglycaemicand antihyperlipidemic activities of the seeds of Pleiogyniumtimorense and its bioactive compounds. So, the methanolic extract of the seeds of Pleiogynium timorense could be a step towards the development of new antihyperglycaemic and antihyperlipidemic drugs.

Keywords: antihyperglycaemic, bioactive compounds, phenolic, Pleiogynium timorense, seeds

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Authors: Kumari Bandana Bhatt, Navin Bhatt

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Background: Orphans and vulnerable children (OVC) are high risk of physical, mental, sexual and emotional abuse and face social stigma and discrimination which significantly increase the risk of mental and behavioral disorders such as anxiety, depression or emotional problems even they stay in well run child care homes. The objective of this study was to estimate the prevalence of depression and determine the determinants among OVC in child care homes in Nepal. Methods: An institutional-based analytical cross-sectional study was conducted in twenty orphanages of five districts of Nepal. Six hundred two children were recruited into the study. After the informed consent form obtaining, the guardian and assent were interviewed by a semi-structured questionnaire and Beck Depression Inventory-II (BDI-II). Logistic regression was used for detecting the association between variables at the significant level of =0.05. Results: The study revealed that 33.20% of OVC had depression. Among them 66.80% of children experienced minimal depression, 17.40% had mild depression, 11.30% had moderate depression 4.50% had severe depression. Sex, alcohol drinking, congenital problem, social support and bully were the main variables associated with depression among OVC of the child care homes in Nepal. Conclusion: Prevalence of depression was high among the orphans and vulnerable children living in child care homes especially among the female children in Nepal. Therefore, early identification and instituting of preventive measures of depression are essential to reduce this problem in this special group of children living in child care homes.

Keywords: Mental health, Depression, Orphans and vulnerable children, child care homes

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.

Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment

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Authors: Mina Sarabi, Dariush Sattarzadeh, Mitra Asadollahi Oula

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In the old days, gardens reflect the identity and culture of each country. Persian garden in urban planning and architecture has a high position and it is a kind of paradise in Iranian opinion. But nowadays, the gardens were replaced with parks and urban open spaces. On the other hand, due to the industrial development of cities and increasing air pollution in urban environments, living in this spaces make problem for people. And improving ecological conditions will be felt more than ever. The purposes of this study are identification and reproduction of Persian garden pattern and adaptation of it with sustainability features in green spaces in contemporary cities and developing meaningful green spaces instead of designing aimless spaces in urban environment. The research method in this article is analytical and descriptive. Studying and collecting information about Iranian garden pattern is referring to library documents, articles and analysis case studies. The result reveals that Persian garden was the main factor the bond between man and nature. But in the last century, this relationship is in trouble. It has a significant impact in reducing the adverse effects of urban air pollution, noise and etc as well. Nowadays, recreated pattern of Iranian gardens in urban green spaces not only keep Iranian identity for future generations but also, using the principles of sustainability can play an important role in sustainable development and quality space of a city.

Keywords: green open spaces, nature, Persian garden, urban sustainability

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Authors: Asep Sukohar, Ramadhan Triyandi, Muhammad Iqbal, Sahidin, Suharyani

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Introduction: Resveratrol is a class of bioactive chemicals found in melinjo, which has a wide range of biological actions. The purpose of this study is to determine the linarin content of the melinjo fraksi by using preparative-high-performance liquid chromatography (prep-HPLC). Method: Extraction used the soxhletation method with 96% ethanol solvent. Fractionation used ethyl acetate and ethanol in a ratio of 1:1. Tracing of linarin compound used prep-HPLC with a mobile phase ratio of distilled water: methanol (55: 45, v/v). The presence of linarin was detected using a wavelength of 215 nm. Fourier Transform Infrared (FTIR) was used to identify the functional groups of compound. Result: The retention time required to elute the ethyl acetate fraction was 2.601 minutes. Compound separation identification using Fourier Transform Infrared Spectroscopy - Quest Attenuated Total Reflectance (FTIR - QATR) has a similarity value range with standards from 0 to 1000. The elution results of the ethyl acetate fraction have similar values with the standard compounds linarin (668), resveratrol (578), and catechin (455). Conclusion: Tracing for active compound in the ethyl acetate fraction of Gnetum Gnemon L. using prep-HPLC showed a strong suspicion of the presence of linarin compound.

Keywords: Gnetum gnemon L., linarin, prep-HPLC, fraction ethyl acetate

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Authors: Asato Takaishi, Masashi Nasuhara, Ayuko Itsuki, Kenichi Suga

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Stevia (Stevia rebaudiana Bertoni) is a composite plant native to Paraguay. Stevia sweetener is derived from a hot water extract of Stevia (Stevia extract), which has some effects such as histamine decomposition, antioxidative effect, and blood sugar level-lowering function. The steviol glycosides in the Stevia extract are considered to contribute to these effects. In addition, these effects increase by the fermentation. However, it takes a long time for fermentation of Stevia extract and the fermentation liquid sometimes decays during the fermentation process because natural fermentation method is used. The aim of this study is to perform the fermentation of Stevia extract in a shorter period, and to produce the fermentation liquid in stable quality. From the natural fermentation liquid of Stevia extract, the four strains of useful (good taste) microorganisms were isolated using dilution plate count method and some properties were determined. The base sequences of 16S rDNA and 28S rDNA revealed three bacteria (two Lactobacillus sp. and Microbacterium sp.) and one yeast (Issatchenkia sp.). This result has corresponded that several kinds of lactic bacterium such as Lactobacillus pentosus and Lactobacillus buchneri were isolated from Stevia leaves. Liquid chromatography/mass spectrometory (LC/MS/MS) and High-Performance Liquid Chromatography (HPLC) were used to determine the contents of steviol glycosides and neutral sugars. When these strains were cultured in the sterile Stevia extract, the steviol and stevioside were increased in the fermented Stevia extract. So, it was suggested that the rebaudioside A and the mixture of steviol glycosides in the Stevia extract were decomposed into stevioside and steviol by microbial metabolism.

Keywords: fermentation, lactobacillus, Stevia, steviol glycosides, yeast

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Authors: Zi-Yan Liao, Shan-Yu Zhang, Ya-Xian Lin, Ya-Lun Lee, Shih-Chuan Huang, Hong-Ru Lin

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Traditional wound dressings, such as gauze, bandages, etc., are easy to adhere to the tissue fluid exuded from the wound, causing secondary damage to the wound during removal. This study takes this as the idea to develop a hydrogel dressing, to explore that the dressing will not cause secondary damage to the wound when it is torn off, and at the same time, create an environment conducive to wound healing. First, the temperature-sensitive material N-isopropylacrylamide (NIPAAm) was used as the substrate. Due to its low mechanical properties, the hydrogel would break due to pulling during human activities. Polyvinyl alcohol (PVA) interpenetrates into it to enhance the mechanical properties, and a semi-interpenetration (semi-IPN) composed of poly(N-isopropylacrylamide) (PNIPAAm) and polyvinyl alcohol (PVA) was prepared by free radical polymerization. PNIPAAm was cross-linked with N,N'-methylenebisacrylamide (NMBA) in an ice bath in the presence of linear PVA, and tetramethylhexamethylenediamine (TEMED) was added as a promoter to speed up the gel formation. The polymerization stage was carried out at 16°C for 17 hours and washed with distilled water for three days after gel formation, and the water was changed several times in the middle to complete the preparation of semi-IPN hydrogel. Finally, various tests were used to analyze the effects of different ratios of PNIPAAm and PVA on semi-IPN hydrogels. In the swelling test, it was found that the maximum swelling ratio can reach about 50% under the environment of 21°C, and the higher the ratio of PVA, the more water can be absorbed. The saturated moisture content test results show that when more PVA is added, the higher saturated water content. The water vapor transmission rate test results show that the value of the semi-IPN hydrogel is about 57 g/m²/24hr, which is not much related to the proportion of PVA. It is found in the LCST test compared with the PNIPAAm hydrogel; the semi-IPN hydrogel possesses the same critical solution temperature (30-35°C). The semi-IPN hydrogel prepared in this study has a good effect on temperature response and has the characteristics of thermal sensitivity. It is expected that after improvement, it can be used in the treatment of surface wounds, replacing the traditional dressing shortcoming.

Keywords: hydrogel, N-isopropylacrylamide, polyvinyl alcohol, hydrogel wound dressing, semi-interpenetrating polymer network

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Martin Tazky, Rudolf Hela, Lucia Osuska, Petr Novosad

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Concrete’s volumetric changes are natural process caused by silicate minerals’ hydration. These changes can lead to cracking and subsequent destruction of cementitious material’s matrix. In most cases, cracks can be assessed as a negative effect of hydration, and in all cases, they lead to an acceleration of degradation processes. Preventing the formation of these cracks is, therefore, the main effort. Once of the possibility how to eliminate this natural concrete shrinkage process is by using different types of dispersed reinforcement. For this application of concrete shrinking, steel and polymer reinforcement are preferably used. Despite ordinarily used reinforcement in concrete to eliminate shrinkage it is possible to look at this specific problematic from the beginning by itself concrete mix composition. There are many secondary raw materials, which are helpful in reduction of hydration heat and also with shrinkage of concrete during curing. The new science shows the possibilities of shrinkage reduction also by the controlled formation of hydration products, which could act by itself morphology as a traditionally used dispersed reinforcement. This contribution deals with the possibility of controlled formation of mono- and tri-sulfate which are considered like degradation minerals. Mono- and tri- sulfate's controlled formation in a cementitious composite can be classified as a self-healing ability. Its crystal’s growth acts directly against the shrinking tension – this reduces the risk of cracks development. Controlled formation means that these crystals start to grow in the fresh state of the material (e.g. concrete) but stop right before it could cause any damage to the hardened material. Waste materials with the suitable chemical composition are very attractive precursors because of their added value in the form of landscape pollution’s reduction and, of course, low cost. In this experiment, the possibilities of using the fly ash from fluidized bed combustion as a mono- and tri-sulphate formation additive were investigated. The experiment itself was conducted on cement paste and concrete and specimens were subjected to a thorough analysis of physicomechanical properties as well as microstructure from the moment of mixing up to 180 days. In cement composites, were monitored the process of hydration and shrinkage. In a mixture with the used admixture of fluidized bed combustion fly ash, possible failures were specified by electronic microscopy and dynamic modulus of elasticity. The results of experiments show the possibility of shrinkage concrete reduction without using traditionally dispersed reinforcement.

Keywords: shrinkage, monosulphates, trisulphates, self-healing, fluidized fly ash

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Authors: Emma K. Sales

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Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments; 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit. Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR analysis, genotype, genetic diversity, cultivars

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Authors: Adria Rae Abigail R. Eda, Arvin C. Diesmos, Vance T. Vredenburg, Merab A. Chan

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Mitigating strategies using symbiotic cutaneous bacteria is one of the major concerns in the conservation of amphibian population. Batrachochytrium dendrobatidis is the causative agent of chytridiomycosis associated with mass mortality and amphibian extinctions worldwide. In the Philippines, there is a lack of study on the cutaneous bacteria of Philippine amphibians that may have beneficial effects to ward off the deadly fungal infection. In this study, cutaneous bacteria from frogs were isolated and examined for anti-B. dendrobatidis activity. Eight species of frogs were collected at Mt. Palay-palay Mataas na Gulod National Park in Cavite, a site positive for the presence of B. dendrobatidis. Bacteria were isolated from the skin of frogs by swabbing the surfaces of the body and inoculated in Reasoner´s 2A (R2A) agar. Isolated bacteria were tested for potential inhibitory properties against B. dendrobatidis through zoospore inhibition assay. Results showed that frog cutaneous bacteria significantly inhibited the growth of B. dendrobatidis in vitro. By means of 16S rRNA gene primers, the anti-B. dendrobatidis bacteria were identified to be Enterobacter sp., Alcaligenes faecalis and Pseudomonas sp. Cutaneous bacteria namely Enterobacter sp. (isolates PLd33 and PCv4) and Pseudomonas (isolate PLd31) remarkably cleared the growth of B. dendrobatidis zoospore in 1% tryptone agar. Therefore, frog cutaneous bacteria inhibited B. dendrobatidis in vitro and could possibly contribute to the immunity and defense of frogs against the lethal chytridiomycosis.

Keywords: Batrachochytrium dendrobatidis, cutaneous bacteria, frogs, zoospore inhibition assay

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Authors: Patricia O. Carvalho, Marcia C. F. Messias, Salvador Sanchez Vinces, Caroline F. A. Gatinoni, Vitor P. Iordanu, Carlos A. R. Martinez

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Lipidomics methods are widely used in the identification and validation of disease-specific biomarkers and therapy response evaluation. The present study aimed to identify a panel of potential lipid biomarkers to evaluate response to neoadjuvant chemoradiotherapy in rectal adenocarcinoma (RAC). Liquid chromatography–mass spectrometry (LC-MS)-based untargeted lipidomic was used to profile human serum samples from patients with clinical stage T2 or T3 resectable RAC, after and before chemoradiotherapy treatment. A total of 28 blood plasma samples were collected from 14 patients with RAC who recruited at the São Francisco University Hospital (HUSF/USF). The study was approved by the ethics committee (CAAE 14958819.8.0000.5514). Univariate and multivariate statistical analyses were applied to explore dysregulated metabolic pathways using untargeted lipidic profiling and data mining approaches. A total of 36 statistically significant altered lipids were identified and the subsequent partial least-squares discriminant analysis model was both cross validated (R2, Q2) and permutated. Lisophosphatidyl-choline (LPC) plasmalogens containing palmitoleic and oleic acids, with high variable importance in projection score, showed a tendency to be lower after completion of chemoradiotherapy. Chemoradiotherapy seems to change plasmanyl-phospholipids levels, indicating that these lipids play an important role in the RAC pathogenesis.

Keywords: lipidomics, neoadjuvant chemoradiotherapy, plasmalogens, rectal adenocarcinoma

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Authors: Shirin jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani

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Biosensors in forensic analysis are ideal biological tools that can be used for rapid and sensitive initial screening and testing to detect of suspicious components like biological and chemical agent in crime scenes. The wide use of different biomolecules such as proteins, nucleic acids, microorganisms, antibodies and enzymes makes it possible. These biosensors have great advantages such as rapidity, little sample manipulation and high sensitivity, also Because of their stability, specificity and low cost they have become a very important tool to Forensic analysis and detection of crime. In crime scenes different substances such as rape samples, Semen, saliva fingerprints and blood samples, act as a detecting elements for biosensors. On the other hand, successful fluid recovery via biosensor has the propensity to yield a highly valuable source of genetic material, which is important in finding the suspect. Although current biological fluid testing techniques are impaired for identification of body fluids. But these methods have disadvantages. For example if they are to be used simultaneously, Often give false positive result. These limitations can negatively result the output of a case through missed or misinterpreted evidence. The use of biosensor enable criminal researchers the highly sensitive and non-destructive detection of biological fluid through interaction with several fluid-endogenous and other biological and chemical contamination at the crime scene. For this reason, using of the biosensors for detecting the biological fluid found at the crime scenes which play an important role in identifying the suspect and solving the criminal.

Keywords: biosensors, forensic analysis, biological fluid, crime detection

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Authors: Don August G. Delgado

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Foreign Language acquisition without enough motivation is tough because it is the force that drives students’ interest or enthusiasm to achieve learning. In addition, it also serves as the students’ beacon to achieve their goals, desires, dreams, and aspirations in life. Since it plays an integral factor in language learning acquisition, this study focuses on the integrative and instrumental motivation levels of all the first year students of Naresuan University International College. The identification of their motivation level and inclination in learning the English language will greatly help all NUIC lecturers and administrators to create a project or activities that they will truly enjoy and find worth doing. However, if the findings of this study will say otherwise, this study can also show to NUIC lecturers and administrators how they can help and transform NUIC freshmen on becoming motivated learners to enhance their English proficiency levels. All respondents in this study received an adopted and developed questionnaire from different researches in the same perspective. The questionnaire has 24 questions that were randomly arranged; 12 for integrative motivation and 12 for instrumental motivation. The questionnaire employed the five-point Likert scale. The tabulated data were analyzed according to its means and standard deviations using the Standard Deviation Calculator. In order to interpret the motivation level of the respondents, the Interpretation of Mean Scores was utilized. Thus, this study concludes that majority of the NUIC freshmen are neither integratively motivated nor instrumentally motivated students.

Keywords: motivation, integrative, foreign language acquisition, instrumental

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

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

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

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Authors: Qing Liu, Jean-fabien Capsal, Claude Richard

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In this current contribution, authors are dedicated to investigate influence of the crystal lamellae orientation on electromechanical behaviors of relaxor ferroelectric Poly (vinylidene fluoride –trifluoroethylene -chlorotrifluoroethylene) (P(VDF-TrFE-CTFE)) films by control of polymer microstructure, aiming to picture the full map of structure-property relationship. In order to define their crystal orientation films, terpolymer films were fabricated by solution-casting, stretching and hot-pressing process. Differential scanning calorimetry, impedance analyzer, and tensile strength techniques were employed to characterize crystallographic parameters, dielectric permittivity, and elastic Young’s modulus respectively. In addition, large electrical induced out-of-plane electrostrictive strain was obtained by cantilever beam mode. Consequently, as-casted pristine films exhibited surprisingly high electrostrictive strain 0.1774% due to considerably small value of elastic Young’s modulus although relatively low dielectric permittivity. Such reasons contributed to large mechanical elastic energy density. Instead, due to 2 folds increase of elastic Young’s modulus and less than 50% augmentation of dielectric constant, fully-crystallized film showed weak electrostrictive behavior and mechanical energy density as well. And subjected to mechanical stretching process, Film C exhibited stronger dielectric constant and out-performed electrostrictive strain over Film B because edge-on crystal lamellae orientation induced by uniaxially mechanical stretch. Hot-press films were compared in term of cooling rate. Rather large electrostrictive strain of 0.2788% for hot-pressed Film D in quenching process was observed although its dielectric permittivity equivalent to that of pristine as-casted Film A, showing highest mechanical elastic energy density value of 359.5 J/m^3. In hot-press cooling process, dielectric permittivity of Film E saw values at 48.8 concomitant with ca.100% increase of Young’s modulus. Films with intermediate mechanical energy density were obtained.

Keywords: crystal orientation, electrostroctive strain, mechanical energy density, permittivity, relaxor ferroelectric

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Authors: Menouni Aziza, Chbihi Kaoutar, Duca Radu Corneliu, Gilissen Liesbeth, Bounou Salim, Godderis Lode, El Jaafari Samir

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In Africa, environmental and occupational health risks are mostly underreported. The aim of this research is to develop and implement a sentinel surveillance system comprising training and guidance of occupational physicians (OC) who will report new work-related diseases in African countries. A group of 30 OC are recruited and trained in each of the partner countries (Morocco, Benin and Ethiopia). Each committed OC is asked to recruit 50 workers during a consultation in a time-frame of 6 months (1500 workers per country). Workers are asked to fill out an online questionnaire about their health status and work conditions, including exposure to 20 chemicals. Urine and blood samples are then collected for human biomonitoring of common exposures. Some preliminary results showed that 92% of the employees surveyed are exposed to physical constraints, 44% to chemical agents, and 24% to biological agents. The most common physical constraints are manual handling of loads, noise pollution and thermal pollution. The most frequent chemical risks are exposure to pesticides and fuels. This project will allow a better understanding of effective sentinel systems as a promising method to gather high quality data, which can support policy-making in terms of preventing emerging work-related diseases.

Keywords: sentinel system, occupational diseases, human biomonitoring, Africa

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: Rachel M. Lørum, Henrik Eriksson, Frida Smith

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Purpose: In recent years, the use of benchmarks for the improvement of healthcare has become increasingly common. There has been an increasing interest in why improvement initiatives so often fail to eliminate the problems they aspire to solve. Benchmarking comes with its fair share of challenges and problems, such as capturing the dynamics and complexities of the care environments, among others. In this study, we demonstrate how learning-oriented, voluntary benchmarks in the complex environment of public healthcare could be designed. Findings: Our four most important findings were the following: first, important organizational learning (OL) regarding the complexity of the service and implications on how to design a benchmark for learning and improvement occurred during the process. Second, participation by a wide range of professionals and stakeholders was crucial for capturing the complexity of people and organizations and increasing the quality of the template. Third, the continuous dialogue between all organizations involved was an important tool for ongoing organizational learning throughout the process. The last important finding was the impact of the facilitator’s role through supporting progress, coordination, and dialogue. Design: We chose participatory design as the research design. Data were derived from written materials such as e-mails, protocols, observational notes, and reflection notes collected during a period of 1.5 years. Originality: Our main contributions are the identification of important strategies, initiatives, and actors to involve when designing voluntary benchmarks for learning and improvement.

Keywords: organizational learning, quality improvement, learning-oriented benchmark, healthcare, patient safety

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Authors: Kritika Kulhari, Aparna Sahu

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Test anxiety results from concerns about failure in examinations or evaluative situations. Attentional biases are known to pronounce the symptomatic expression of test anxiety. In recent times, the inattentional blindness (IB) paradigm has shown promise as an attention bias modification treatment (ABMT) for anxiety by overcoming practice and expectancy effects which preexisting paradigms fail to counter. The IB paradigm assesses the inability of an individual to attend to a stimulus that appears suddenly while indulging in a perceptual discrimination task. The present study incorporated an IB task with three critical items (book, face, and triangle) appearing randomly in the perceptual discrimination task. Attentional biases were assessed as detection and identification of the critical item. The sample (N = 50) consisted of low test anxiety (LTA) and high test anxiety (HTA) groups based on the reactions to tests scale scores. Test threat manipulation was done with pre- and post-test assessment of test anxiety using the State Test Anxiety Inventory. A mixed factorial design with gender, test anxiety, presence or absence of test threat, and critical items was conducted to assess their effects on attentional biases. Results showed only a significant main effect for test anxiety on detection with higher accuracy of detection of the critical item for the LTA group. The study presents promising results in the realm of ABMT for test anxiety.

Keywords: attentional bias, attentional bias modification treatment, inattentional blindness, test anxiety

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Authors: Haleh Rezaei Zanjirabadi, Fatemeh Saberi, Bahman Rahimzadeh, Fariborz Masoudi, Mohammad Rahgosha

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In this study, apatite minerals from the iron-phosphate deposit of Yazd have been investigated within the microcontinent zone of Iran in the Zagros structural zone. The geological units in the Esfordi area belong to the pre-Cambrian to lower-Cambrian age, consisting of a succession of carbonate rocks (dolomite), shale, tuff, sandstone, and volcanic rocks. In addition to the mentioned sedimentary and volcanic rocks, the granitoid mass of Bahabad, which is the largest intrusive mass in the region, has intruded into the eastern part of this series and has caused its metamorphism and alteration. After collecting the available data, various samples of Esfordi’s apatite were prepared, and their mineralogy and crystallography were investigated using laboratory methods such as petrographic microscopy, Raman spectroscopy, EDS, and SEM. In non-destructive Raman spectroscopy, the molecular structure of apatite minerals was revealed in four distinct spectral ranges. Initially, the spectra of phosphate and aluminum bonds with O2HO, OH, were observed, followed by the identification of Cl, OH, Al, Na, Ca and hydroxyl units depending on the type of apatite mineral family. In SEM analysis, based on various shapes and different phases of apatites, their constituent major elements were identified through EDS, indicating that the samples from the Esfordi mining area exhibit a dense and coherent texture with smooth surfaces. Based on the elemental analysis results by EDS, the apatites in the Esfordi area are classified into the calcic apatite group.

Keywords: petrology, apatite, Esfordi, EDS, SEM, Raman spectroscopy

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Authors: María Fernanda Quiceno Vallejo, Patricia del Portillo, María Mercedes Zambrano, Jeisson Alejandro Triana, Dayana Calderon, Juan Manuel Anzola

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Microorganisms from tropical ecosystems can be novel in terms of adaptations and conservation. Given the macrodiversity of Colombian ecosystems, it is possible that this diversity is also present in Colombian soils. Tropical soil bacteria could offer a potentially novel source of bioactive compounds. In this study we analyzed a metagenomic fosmid library constructed with tropical bacterial DNAs with the aim of understanding its underlying diversity and functional potential. 8640 clones from the fosmid library were sequenced by NANOPORE MiniOn technology, then analyzed with bioinformatic tools such as Prokka, AntiSMASH and Bagel4 in order to identify functional biosynthetic pathways in the sequences. The strains showed ample difference when it comes to biosynthetic pathways. In total we identified 4 pathways related to aryl polyene synthesis, 12 related to terpenes, 22 related to NRPs (Non ribosomal peptides), 11 related PKs (Polyketide synthases) and 7 related to RiPPs (bacteriocins). We designed primers for the metagenomic clones with the most BGCs (sample 6 and sample 2). Results show the biotechnological / pharmacological potential of tropical ecosystems. Overall, this work provides an overview of the genomic and functional potential of Colombian soil and sets the groundwork for additional exploration of tropical metagenomic sequencing.

Keywords: bioactives, biosyntethic pathways, bioinformatic, bacterial gene clusters, secondary metabolites

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Tasnuba Binte Jamal, Khan Mahmud Amanat

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Carbon Fiber-Reinforced Polymer (CFRP) composite materials have proven to have valuable properties and suitability to be used in the construction of new buildings and in upgrading the existing ones due to its effectiveness, ease of implementation and many more. In the present study, a numerical finite element investigation has been conducted using ANSYS 18.1 to study the behavior of square HSS AISC sections under eccentric compressive loading strengthened with CFRP materials. A three-dimensional finite element model for square HSS section using shell element was developed. Application of CFRP strengthening was incorporated in the finite element model by adding an additional layer of shell elements. Both material and geometric nonlinearities were incorporated in the model. The developed finite element model was applied to simulate experimental studies done by past researchers and it was found that good agreement exists between the current analysis and past experimental results, which established the acceptability and validity of the developed finite element model to carry out further investigation. Study was then focused on some selected non-compact AISC square HSS columns and the effects of number of CFRP layers, amount of eccentricities and cross-sectional geometry on the strength gain of those columns were observed. Load was applied at a distance equal to the column dimension and twice that of column dimension. It was observed that CFRP strengthening is comparatively effective for smaller eccentricities. For medium sized sections, strengthening tends to be effective at smaller eccentricities as well. For relatively large AISC square HSS columns, with increasing number of CFRP layers (from 1 to 3 layers) the gain in strength is approximately 1 to 38% to that of unstrengthened section for smaller eccentricities and slenderness ratio ranging from 27 to 54. For medium sized square HSS sections, effectiveness of CFRP strengthening increases approximately by about 12 to 162%. The findings of the present study provide a better understanding of the behavior of HSS sections strengthened with CFRP subjected to eccentric compressive load.

Keywords: CFRP strengthening, eccentricity, finite element model, square hollow section

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: M. A. Gad, A. Z. Al-Herrawy

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Microsporidia comprises various pathogenic species can infect humans by means of water. Moreover, chlorine disinfection of drinking-water has limitations against this protozoan pathogen. A total of 48 water samples were collected from two drinking water treatment plants having two different filtration systems (slow sand filter and rapid sand filter) during one year period. Samples were collected from inlet and outlet of each plant. Samples were separately filtrated through nitrocellulose membrane (142 mm, 0.45 µm), then eluted and centrifuged. The obtained pellet from each sample was subjected to DNA extraction, then, amplification using genus-specific primer for microsporidia. Each microsporidia-PCR positive sample was performed by two species specific primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis. The results of the present study showed that the percentage of removal for microsporidia through different treatment processes reached its highest rate in the station using slow sand filters (100%), while the removal by rapid sand filter system was 81.8%. Statistically, the two different drinking water treatment plants (slow and rapid) had significant effect for removal of microsporidia. Molecular identification of microsporidia-PCR positive samples using two different primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis showed the presence of the two pervious species in the inlet water of the two stations, while Encephalitozoon intestinalis was detected in the outlet water only. In conclusion, the appearance of virulent microsporidia in treated drinking water may cause potential health threat.

Keywords: removal, efficacy, microsporidia, drinking water treatment plants, PCR

Procedia PDF Downloads 210