Search results for: Functional Networks (FN)

Authors: Manar Y. Abd El-Aziz, Alyaa E. Morgham, Amira A. El-Fallal, Heba Tolla E. Abo El Naga

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Sport wears almost preferred with knitted fabrics, specially interlock construction. But, there is a need for higher comfortability and functional properties for fabrics to be more fitted to this application. This study compared cotton and polyester microfibers and blended them to improve the functional activity of interlock in sport wear by mercerized and non-mercerized. also, fabric dyeing and dyeability are affected by mercerization. Many functional properties, such as UV protection as well as antimicrobial activity. The changes in different mechanical as well as physical properties were investigated. The washing fastness properties of the dyed fabrics are also given. The changes in moisture regain, loss in weight, and burst and burst elongation for all mercerized fabrics have been studied.

Keywords: interlock, mercirization, dyeability, function properties, moisture management

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Authors: Yun-Ching Tu, Yu-Chun Chih

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People with aphasia (PWA) may have communicative difficulties in their daily lives, but research on functional communication in aphasia is still limited in Taiwan. The aim of the study was to investigate the impact of aphasia-related factors on functional communication assessment. This study adopted a convenience sampling method. Thirty aphasic participants participated in the study. During the test, the examiner would ask questions that are encountered in daily life and record the participant‘s responses. Some questions would provide pictures to simulate situations in daily life. The results showed that the non-fluent aphasia group performed significantly worse than the fluent aphasia group. In addition, patients with severe aphasia performed significantly lower scores than patients with moderate aphasia and mild aphasia. However, group differences in the chronic stage and acute stage were not significant. In sum, since communication in daily life is diverse and language is still needed in the communication process, patients with aphasia who have better language ability may have relatively better functional communication. In contrast, the more severely impaired the language ability of a patient with aphasia is, the more functional communication will be affected, resulting in poor communication performance in daily life.

Keywords: adult, aphasia, assessment, functional communication

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Authors: Savaş Karpuz, Sami Küçükşen

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The aim of this study is to investigate the effectiveness of neurological rehabilitation in patients with traumatic brain injury. Participants were 45 consecutive adults with traumatic brain injury who were received the neurologic rehabilitation. Sociodemographic characteristics of the patients, the cause of the injury, the duration of the coma and posttraumatic amnesia, the length of stay in the other inpatient clinics before rehabilitation, the time between injury and admission to the rehabilitation clinic, and the length of stay in the rehabilitation clinic were recorded. The differences in functional status between admission and discharge were determined with Disability Rating Scale (DRS), Functional Independence Measure (FIM), and Functional Ambulation Scale (FAS) and levels of cognitive functioning determined with Ranchos Los Amigos Scale (RLAS). According to admission time, there was a significant improvement identified in functional status of patients who had been given the intensive in-hospital cognitive rehabilitation program. At discharge time, the statistically significant differences were obtained in DRS, FIM, FAS and RLAS scores according to admission time. Better improvement in functional status was detected in patients with lower scores in DRS, and higher scores FIM and RLAS scores at the entry time. The neurologic rehabilitation significantly affects the recovery of functional status after traumatic brain injury.

Keywords: traumatic brain injury, rehabilitation, functional status, neurological

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Authors: Adesola Odole, Nse Odunaiya, Samuel Adewale

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Chronic Mechanical Low Back Pain (CMLBP) is prevalent in the aging population; some studies have documented the association among pain intensity, functional disability and physical activity in the general population but very few studies in the elderly. This study was designed to investigate the association among pain intensity, functional disability and physical activity of elderly individuals with CMLBP in the University College Hospital (UCH), Ibadan, Nigeria and also to determine the difference in physical activity, pain intensity and functional disability between males and females. A total of 96 participants diagnosed with CMLBP participated in this cross-sectional survey. They were conveniently sampled from selected units in the UCH, Ibadan, Nigeria. Data on sex, marital status, occupation and duration of onset of pain of participants were obtained from the participants. The Physical Activity Scale for the Elderly, Visual Analogue Scale and Oswestry Disability Questionnaire were used to measure the physical activity, pain intensity and functional disability of the participants respectively. Data was analysed using Spearman correlation, independent t-test; and α was set at 0.05. Participants (25 males, 71 females) were aged 69.64±7.43 years. The majority (76.0%) of the participants were married, and over half (55.2%) were retirees. Participants’ mean pain intensity score was 5.21±2.03 and mean duration of onset of low back pain was 63.63 ± 90.01 months. The majority (67.6%) of the participants reported severe to crippled functional disability. Their mean functional disability was 46.91 ± 13.99. Participants’ mean physical activity score was 97.47 ± 82.55. There was significant association between physical activity and pain intensity (r = -0.21, p = 0.04). There was significant association between physical activity and functional disability (r = -0.47, p = 0.00). Male (87.26 ± 79.94) and female (101.07 ± 83.71) participants did not differ significantly in physical activity (t = 0.00, p = 0.48). In addition, male (5.48 ± 2.06) and female (5.11 ± 2.02) participants’ pain intensity were comparable (t = 0.26, p = 0.44). There was also no significant difference in functional disability (t = 0.05, p = 0.07) between male (42.56 ±13.85) and female (48.45 ± 13.81) participants. It can be concluded from this study that majority of the elderly individuals with chronic mechanical low back pain had a severe to crippled functional disability. Those who reported increased physical activity had reduced pain intensity and functional disability. Male and female elderly individuals with chronic mechanical low back pain are comparable in their pain intensity, functional disability, and physical activity. Elderly individuals with CMLBP should be educated on the importance of participating in physical activity which could reduce their pain symptoms and improve functional disability.

Keywords: elderly, functional disability, mechanical low back pain, pain intensity, physical activity

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Authors: Lídia E. O. Cruz, Adriano P. C. Calvo, Renato J. Soares, Regiane A. Carvalho

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Individuals with non-specific chronic low back pain may present altered movement patterns during functional activities. However, muscle behavior before and after performing a functional task with different load conditions is not yet fully understood. The aim of this study is to analyze lumbar muscle activity before and after performing the functional task of picking up and placing an object on the ground (with and without load) in individuals with nonspecific chronic low back pain. 20 subjects with nonspecific chronic low back pain and 20 healthy subjects participated in this study. A surface electromyography was performed in the ilio-costal, longissimus and multifidus muscles to evaluate lumbar muscle activity before and after performing the functional task of picking up and placing an object on the ground, with and without load. The symptomatic participants had greater lumbar muscle activation compared to the asymptomatic group, more evident in performing the task without load, with statistically significant difference (p = 0,033) between groups for the right multifidus muscle. This study showed that individuals with nonspecific chronic low back pain have higher muscle activation before and after performing a functional task compared to healthy participants.

Keywords: chronic low back pain, functional task, lumbar muscles, muscle activity

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Adebola Ajayi, Olakunle M. Makanjuola

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Effect of sprouting period on proximate, functional and mineral properties of malted sorghum flour was evaluated. The study was carried out to determine the proximate, functional and mineral properties of sprouting period on malted sorghum flour produced. The malted sorghum flour was obtained by sorting, weighing, washing, steeping, draining, germination, drying, dry milling, sieving. Malted sorghum flour was evaluated for proximate composition, functional properties and mineral contents. Moisture, protein, fat content, crude fiber, ash contents and carbohydrate of 24 and 48 hours, were in the range of 10.50-11.0, 11.17-11.17, 1.50-4.00, 2.50-1.50, 1.50-1.54 and 73.15-70.79% respectively. Bulk density ranged between 0.64 and 0.59g/ml, water and oil absorption capacities ranged between 139.3 and 150.0 and 217.3 and 222.7g/g respectively. Calcium, Magnesium, Zinc, Iron and Manganese were also range of 12.5, 59.3-60.0, 3.22-3.25, 3.80-3.90 and 3.22-3.25 mg/100g respectively. The results indicate that the germination of red sorghum resulted in the enhancement of the nutritional quality and its functional properties.

Keywords: sprouting, sorghum, malted sorghum flour, cabinet dryer

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Khelifa Benahmed, Tarek Benahmed

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There are diverse applications of wireless sensor networks (WSNs) in the real world, typically invoking some kind of monitoring, tracking, or controlling activities. In an application, a WSN is deployed over the area of interest to sense and detect the events and collect data through their sensors in a geographical area and transmit the collected data to a Base Station (BS). This paper presents an overview of the research solutions available in the field of environmental monitoring applications, more precisely the problems of critical area monitoring using wireless sensor networks.

Keywords: critical infrastructure monitoring, environment monitoring, event region detection, wireless sensor networks

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.

Keywords: IoT, network formation, sensor nodes, SSAIL technology

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Authors: Naci Büyükkaracığan

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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

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Authors: Aicha Koulou, Norelislam El Hami, Nabil Hmina

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This paper aims at presenting basic concepts and principles in order to develop a methodology to set up sustainable interoperability within collaborative networks. Definitions and clarifications related to the concept of interoperability and sustainability are given. Interoperability levels and cycle that are components supporting the methodology are presented; a structured approach and related phases are proposed.

Keywords: Interoperability, sustainability, collaborative networks, sustainable Interoperability

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Authors: Setareh Shekarsaraei, Marjan Moridi, Nasser L. Hadipour

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In this study, nuclear magnetic resonance spectroscopy and nuclear quadrupole resonance spectroscopy parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen bonding for Histidine hydrochloride monohydrate were calculated via density functional theory. We considered a five-molecule model system of Histidine hydrochloride monohydrate. Also, we examined the trends of environmental effect on hydrogen bonds as well as cooperativity. The functional used in this research is M06-2X which is a good functional and the obtained results have shown good agreement with experimental data. This functional was applied to calculate the NMR and NQR parameters. Some correlations among NBO parameters, NMR, and NQR parameters have been studied which have shown the existence of strong correlations among them. Furthermore, the geometry optimization has been performed using M062X/6-31++G(d,p) method. In addition, in order to study cooperativity and changes in structural parameters, along with increase in cluster size, natural bond orbitals have been employed.

Keywords: hydrogen bonding, density functional theory (DFT), natural bond orbitals (NBO), cooperativity effect

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Authors: Shailendra Natraj, Kristin Paetzold, B. R. Katzy

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The significant role of technology in strategic business decisions has created the need for executives who understand technology and recognize profitable applications to products, services and processes. The role of CTO’s is very complex within technology-based firms, which stretches from the technology aspects to the strategic goal and vision of the firm. Often the roles of CTOs scales from as functional leaders, strategic leaders or supera- functional leaders. In most of the companies the roles are unclear and fuzzy. We in our research are trying to explore each of the orientation and link between leadership types (functional, strategic and super functional) of CTOs, responsibilities, credibility and strategic and conceptual responsibilities. Approach: We conducted a comprehensive literature review with the available databank sources. Results: From the conducted literature review we could identify that most of the research work conducted so far were mainly distributed between roles and responsibilities of CTOs. The available sources pointed were limited to roles of CTOs as functional leaders. Contribution: In our findings based on the literature review, we could identify that apart from the conducted research what so far has not been focused yet are (a) The leadership types (mainly) strategic and super-functional leaders) of CTOs, (b) the responsibilities and credibility of CTOs and (c) the strategic and conceptual responsibilities of CTOs.

Keywords: CTO, chief technology officer, strategy, technology leaders

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Skirmante Mozuriunaite

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Contemporary metropolitan areas and large cities are dynamic, rapidly growing and continuously changing. Thus, urban transformations and mutations are not a new phenomenon, but rather a continuous process. Basic factors of urban transformation are related to development of technologies, globalisation, lifestyle, etc., which, in combination with local factors, have generated an extremely great variety of urban development conditions. This article discusses the main urbanisation processes in Lithuania during last 50 year period and social factors affecting urban functional mutations.

Keywords: dispersion, functional mutations, urbanization, urban mutations, social factors

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Authors: Mohammad Yahaghifar

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Nowadays Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications. Evolving future communication network generation cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, for example, higher data rates, excellent end-to-end performance, and user coverage in hot-spots and crowded areas with lower latency,energy consumption and cost per information transfer. In this paper we propose a potential cellular architecture that separates indoor and outdoor scenarios and discuss various promising technologies for future wireless communication systemssystems, such as massive MIMO, energy-efficient communications,cognitive radio networks, and visible light communications and we disscuse about 5G that is next generation of wireless networks.

Keywords: future challenges in networks, cellur architecture, visible light communication, 5G wireless technologies, spatial modulation, massiva mimo, cognitive radio network, green communications

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

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Authors: Sorin Valcan, Mihail Gaianu

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Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need for labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to an algorithm used for the generation of ground truth data for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher, which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual label adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: labeling automation, infrared camera, driver monitoring, eye detection, convolutional neural networks

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Authors: Ali Kara, Asim Olgun, Sevgi Sozugecer, Sahin Ozel, Kubra Nur Yildiz, P. Sevinç, Abdurrahman Kuresh, Guliz Turhan, Duygu Gulgun

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The synthetic dyes, one of the most hazardous chemical compound classes, are important potential water pollutions since their presence in water bodies reduces light penetration, precluding the photosynthesis of aqueous flora and causing various diseases. Some the synthetic dyes are highly toxic and/or carcinogenic, and their biodegradation can produce even more toxic aromatic amines. The adsorption procedure is one of the most effective means of removing synthetic dye pollutants, and has been described in a number of previous studies by using the functional polymers. In this study, we investigated the removal of synthetic dyes from aqueous solution by using a functional polymer as an adsorbent material. The effect of initial solution concentration, pH, and contact time on the adsorption capacity of the adsorbent were studied in details. The results showed that functional polymer has a potential to be used as cost-effective and efficient adsorbent for the treatment of aqueous solutions from textile industries.

Keywords: functional polymers, synhetic dyes, adsorption, physicochemical parameters

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Authors: M. Taibeche, L. Guerbous, M. Kechouane, R. Nedjar, T. Zergoug

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It is known that Y2O3 Material is the most important among the sesquioxides within the general class of refractory ceramics. Indeed, this compound has many applications such as sintering optical windows, components for rare-earth doped lasers as well as inorganic scintillators in the detection scintillation. In particular Eu2+ and Ce3+ are favored dopants in many the scintillators due to its allowed optical 5d-4f transition. In this work, we present new results concerning structural and electronic properties of Ce-doped Y2O3, investigated by density functional theory (DFT), using the Heyd–Scuseria–Ernzerhof (HSE) hybrid functional and DFT+U two approaches. When, we compared the results from the two methods we obtain a good agreement available experimental data. Furthermore, the effect of cerium on the material has also been studied and discussed in the same framework.

Keywords: DFT, vienne ab initio simulation packages, scintillators, Heyd–Scuseria–Ernzerhof (HSE) hybrid functional

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: C. S. Marques, M. J. Reis Lima, J. Oliveira, E. Teixeira-Lemos

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The growing concerns for physical wellbeing and health have been reflected in the way we choose food in our table. Nowadays, we are all more informed consumers and choose healthier foods. On the other hand, stroke, cancer and atherosclerosis may be somehow minimized by the intake of some bioactive compounds present in food, the so-called nutraceuticals and functional foods. The aim of this work was to make a revision of the published studies about the effects of some bioactive compounds, namely lycopene in human health, in the prevention of diseases, thus playing the role of a functional food. Free radical in human body can induce cell damage and consequently can be responsible for the development of some cancers and chronic diseases. Lycopene is one of the most powerful antioxidants known, being the predominant carotenoid in tomato. The respective chemistry, bioavailability, and its functional role in the prevention of several diseases will be object of this work. On the other hand the inclusion of lycopene in some foods can also be made by biotechnology and represents a way to recover the wastes in the tomato industry with nutritional positive effects in health.

Keywords: tomato, lycopene, bioavailability, functional foods, carotenoids, cancer and antioxidants

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: Seyed Alireza Mirmohammadi

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Tehran Metro vendors are one of the working minorities in the capital, which is an essential cross-cultural case study. Today, with difficult economic conditions, subway vendors are increasing. Tehran metro vendors are in daily contact with many people in different metro stations. Due to the ban on their activities in this place and sometimes the humiliating look of some people, they experience special conditions compared to other people in the community. One of the most critical sources of shaping people's mentality toward their social status and identity in the media and, in the meantime, virtual social networks, due to various communication facilities such as Dualism and the possibility of high activity of users have a special place. Statistics have shown that virtual social networks have become an indispensable source of communication, information, and entertainment today. In this study, 15 semi-structured interviews were conducted with 15 metro vendors in Tehran about their membership in various virtual social networks and their mental perception of using them. The research results indicate that the obtained mentality of metro peddlers towards themselves is negative in virtual social networks, and they do not receive a good image of themselves in these networks.

Keywords: metro, tehran, intercultural communication, metro vendors, self image

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Authors: Karolis Leonavičius, Dalius Kučiauskas, Dangiras Lukošius, Arnoldas Jasiūnas, Kostas Zdanys, Rokas Stanislovas, Emilis Gegevičius, Žana Kapustina, Juozas Nainys

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Screening throughput is a common bottleneck in many research areas, including functional genomics, drug discovery, and directed evolution. High-throughput screening techniques can be classified into two main categories: (i) affinity-based screening and (ii) functional screening. The first one relies on binding assays that provide information about the affinity of a test molecule for a target binding site. Binding assays are relatively easy to establish; however, they reveal no functional activity. In contrast, functional assays show an effect triggered by the interaction of a ligand at a target binding site. Functional assays might be based on a broad range of readouts, such as cell proliferation, reporter gene expression, downstream signaling, and other effects that are a consequence of ligand binding. Screening of large cell or gene libraries based on direct activity rather than binding affinity is now a preferred strategy in many areas of research as functional assays more closely resemble the context where entities of interest are anticipated to act. Droplet sorting is the basis of high-throughput functional biological screening, yet its applicability is limited due to the technical complexity of integrating high-performance droplet analysis and manipulation systems. As a solution, the Droplet Genomics Styx platform enables custom droplet sorting workflows, which are necessary for the development of early-stage or complex biological therapeutics or industrially important biocatalysts. The poster will focus on the technical design considerations of Styx in the context of its application spectra.

Keywords: functional screening, droplet microfluidics, droplet sorting, dielectrophoresis

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Authors: Hanaa H. Abd El Baky, Gamal S. El Baroty, Eman A. Ibrahem

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Microalgae Scenedesmus obliquus, the carotenoides (astaxanine and β-caroteine) were identified as the major bioactive constituents. In this work we prepared functional pre-biotic cakes to increase general mental health. Functional cakes were formulated by adding algal caroteinods at 2 and 4 mg/100g to flower and the cakes were storage for 20 days. Oxidative stability of both function cakes products were examined during storage periods by DPPH and TBA assays, and the results revealed that both values in function food products were significantly much low than that in untreated food products. Data of sensory evaluation revealed that treated biscuit and cakes with algae or algae extracts were significantly acceptable as control for main sensory characteristics (colour, odour/aroma, flavour, texture, the global appreciation, and overall acceptability). Thus, it could be concluded that functional biscuits and cakes (very popular and well balanced nutritional food) had good sensory and nutritional profiles and can be developed as new niche food market.

Keywords: Scenedesmus obliquus, carotenoids, functional cakes antioxidant, nutritional profiles

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Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

Abstract:

In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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