Search results for: protein tertiary structure prediction

Authors: Simeon Adebayo Oladipo

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Institutional administrators are currently facing pressure and challenges in their daily operations. Reasons for this may include the increasing multiplicity, uncertainty and tension that permeate institutional leadership. Authentic engagement for institutional leadership is premised on the ethical foundation that the leaders in the schools are engaged. The institutional effectiveness is dependent on the relationship that exists between the leaders and employees in the workplace. Leader’s self-awareness, relational transparency, emotional control, strong moral code and accountability have a positive influence on authentic engagement which variably determines leadership effectiveness. This study therefore examined the role of authentic engagement in effective school leadership; explored the interrelationship of authentic engagement indices in school leadership. The study adopted the descriptive research of the survey type using a quantitative method to gather data through a questionnaire among school leaders in Lagos State Tertiary Institutions. The population for the study consisted of all Heads of Departments, Deans and Principal Officers in Lagos State Tertiary Institutions. A sample size of 255 Heads of Departments, Deans and Principal Officers participated in the study. The data gathered were analyzed using descriptive and inferential statistical tools. The findings indicated that authentic engagement plays a crucial role in increasing leadership effectiveness amongst Heads of Departments, Deans and Principal Officers. The study recommended among others that there is a need for effective measures to enhance authentic engagement of institutional leadership practices through relevant educational support systems and effective quality control.

Keywords: authentic engagement, self-awareness, relational transparency, emotional control

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Authors: Ravneil Nand

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Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature.

Keywords: cooperative coevaluation, feed forward network, problem decomposition, neuron, synapse

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Authors: Zhao Tianxu, Cui Shumei

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This paper proposes a novel multiphase motor structure. The armature winding consists of several independent multiphase windings that have different rating rotate speed and power. Compared to conventional motor, the novel motor structure has more operation mode and fault tolerance mode, which makes it adapt to high-reliability requirement situation such as electric vehicle, aircraft and ship. Performance of novel motor structure varies with winding match. In order to find optimum control strategy, motor torque character, efficiency performance and fault tolerance ability under different operation mode are analyzed in this paper, and torque distribution strategy for efficiency optimization is proposed. Simulation analyze is taken and the result shows that proposed structure has the same efficiency on heavy load and higher efficiency on light load operation points, which expands high efficiency area of motor and cruise range of vehicle. The proposed structure can improve motor highest speed.

Keywords: multiphase motor, armature winding match, torque distribution strategy, efficiency

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Hans-Klaus HöFfler, Tobias Schilling, Tim Kaufeld, Axel Haverich

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Tissue engineered (TE) heart valves based on degradable electrospun fiber scaffold represent a promising approach to overcome the known limitations of mechanical or biological prostheses. But the mechanical stress in the high-pressure system of the human circulation is a severe challenge for the delicate materials. Hence, the prediction of the scaffolds` in vivo degradation kinetics must be as accurate as possible to prevent fatal events in future animal or even clinical trials. Therefore, this study investigates whether long-term testing in full blood provides more meaningful results regarding the degradation behavior than conventional tests in simulated body fluids (SBF) or Phosphate Buffered Saline (PBS). Fiber mats were produced from a polycaprolactone (PCL)/tetrafluoroethylene solution by electrospinning. The morphology of the fiber mats was characterized via scanning electron microscopy (SEM). A maximum physiological degradation environment utilizing a test set-up with porcine full blood was established. The set-up consists of a reaction vessel, an oxygenator unit, and a roller pump. The blood parameters (pO2, pCO2, temperature, and pH) were monitored with an online test system. All tests were also carried out in the test circuit with SBF and PBS to compare conventional degradation media with the novel full blood setting. The polymer's degradation is quantified by SEM picture analysis, differential scanning calorimetry (DSC), and Raman spectroscopy. Tensile and cyclic loading tests were performed to evaluate the mechanical integrity of the scaffold. Preliminary results indicate that PCL degraded slower in full blood than in SBF and PBS. The uptake of water is more pronounced in the full blood group. Also, PCL preserved its mechanical integrity longer when degraded in full blood. Protein absorption increased during the degradation process. Red blood cells, platelets, and their aggregates adhered on the PCL. Presumably, the degradation led to a more hydrophilic polymeric surface which promoted the protein adsorption and the blood cell adhesion. Testing degradable implants in full blood allows for developing more reliable scaffold materials in the future. Material tests in small and large animal trials thereby can be focused on testing candidates that have proven to function well in an in-vivo-like setting.

Keywords: Electrospun scaffold, full blood degradation test, long-term polymer degradation, tissue engineered aortic heart valve

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Authors: H. Masaeli, R. Ziaei, F. Khoshnoudian

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Shock response analysis of the soil–structure systems induced by near–fault pulses is investigated. Vibration transmissibility of the soil–structure systems is evaluated by Shock Response Spectra (SRS). Medium–to–high rise buildings with different aspect ratios located on different soil types as well as different foundations with respect to vertical load bearing safety factors are studied. Two types of mathematical near–fault pulses, i.e. forward directivity and fling step, with different pulse periods as well as pulse amplitudes are selected as incident ground shock. Linear versus nonlinear Soil–Structure Interaction (SSI) condition are considered alternatively and the corresponding results are compared. The results show that nonlinear SSI is likely to amplify the acceleration responses when subjected to long–period incident pulses with normalized period exceeding a threshold. It is also shown that this threshold correlates with soil type, so that increased shear–wave velocity of the underlying soil makes the threshold period decrease.

Keywords: nonlinear soil–structure interaction, shock response spectrum, near–fault ground shock, rocking isolation

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Authors: Waziralilah N. Fathiah, A. Aminudin, U. Alyaa Hashim, T. Vikneshvaran D. Shakirah Shukor

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This paper presents the experimental analysis conducted on a structure borne noise in a rectangular enclosure prototype made by joining of sheet aluminum metal and plywood. The study is significant as many did not realized the annoyance caused by structural borne-noise. In this study, modal analysis is carried out to seek the structure’s behaviour in order to identify the characteristics of enclosure in frequency domain ranging from 0 Hz to 200 Hz. Here, numbers of modes are identified and the characteristic of mode shape is categorized. Modal experiment is used to diagnose the structural behaviour while microphone is used to diagnose the sound. Spectral testing is performed on the enclosure. It is acoustically excited using shaker and as it vibrates, the vibrational and noise responses sensed by tri-axis accelerometer and microphone sensors are recorded respectively. Experimental works is performed on each node lies on the gridded surface of the enclosure. Both experimental measurement is carried out simultaneously. The modal experimental results of the modal modes are validated by simulation performed using MSC Nastran software. In pursuance of reducing the structure borne-noise, mitigation method is used whereby the stiffener plates are perpendicularly placed on the sheet aluminum metal. By using this method, reduction in structure borne-noise is successfully made at the end of the study.

Keywords: enclosure, modal analysis, sound analysis, structure borne-noise

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Authors: Nadia Allouache

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The concept of second law is assumed to be important to optimize the energy losses in heat exchangers. The present study is devoted to the numerical prediction of entropy generation due to heat transfer and friction in a double tube heat exchanger partly or fully filled with a porous medium. The goal of this work is to find the optimal conditions that allow minimizing entropy generation. For this purpose, numerical modeling based on the control volume method is used to describe the flow and heat transfer phenomena in the fluid and the porous medium. Effects of the porous layer thickness, its permeability, and the effective thermal conductivity have been investigated. Unexpectedly, the fully porous heat exchanger yields a lower entropy generation than the partly porous case or the fluid case even if the friction increases the entropy generation.

Keywords: heat exchangers, porous medium, second law approach, turbulent flow

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Hashem Shariatmadar, Mozhgansadat Momtazdargahi

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The purpose of control structure against earthquake is to dissipate earthquake input energy to the structure and reduce the plastic deformation of structural members. There are different methods for control structure against earthquake to reduce the structure response that they are active, semi-active, inactive and hybrid. In this paper two different combined control systems are used first system comprises base isolator and multi tuned mass dampers (BI & MTMD) and another combination is hybrid base isolator and multi tuned mass dampers (HBI & MTMD) for controlling an eight story isolated benchmark steel structure. Active control force of hybrid isolator is estimated by fuzzy logic algorithms. The influences of the combined systems on the responses of the benchmark structure under the two near-field earthquake (Newhall & Elcentro) are evaluated by nonlinear dynamic time history analysis. Applications of combined control systems consisting of passive or active systems installed in parallel to base-isolation bearings have the capability of reducing response quantities of base-isolated (relative and absolute displacement) structures significantly. Therefore in design and control of irregular isolated structures using the proposed control systems, structural demands (relative and absolute displacement and etc.) in each direction must be considered separately.

Keywords: base-isolated benchmark structure, multi-tuned mass dampers, hybrid isolators, near-field earthquake, fuzzy algorithm

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Authors: Hanaa A. S. Oraby, Amal A. M. Hassan, Mahmoud M. Sakr, Atef A. A. Haiba

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Applying the profiling approach for the assessment of proteomic variations due to genetic modification of the Egyptian tomato cultivar "Edkawy", three complementary approaches were used. These methods are amino acids analysis, gel electrophoresis, and Gas chromatography coupled with mass spectrometry (GC/MS). The results of the present study Show evidence of proteomic variations between both modified tomato and its non-modified counterpart. Amino acids concentrations, and the protein patterns separation on the 1D SDS-PAGE were not similar in the case of transformed tomato compared to that of the non-transformed counterpart. These detected differences are most likely derived from the process of transformation. Results also revealed that the efficiency of GC/MS approach to identify a mixture of unknown proteins is limited. GC/MS analysis was only able to identify few number of protein molecules. Therefore, more advanced and specific technologies like MALDI-TOF-MS are recommended to be employed.

Keywords: GMOs, unintended effects, proteomic variations, 1D SDS-PAGE, GC/MS

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Authors: Krestina V. Alsaraeva, Victor E. Gromov, Sergey V. Konovalov, Anna A. Atroshkina

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Processing of Al-19.4Si alloy by high intensive electron beam has been carried out and multiple increase in fatigue life of the material has been revealed. Investigations of structure and surface modified layer destruction of Al-19.4Si alloy subjected to multicycle fatigue tests to fracture have been carried out by methods of scanning electron microscopy. The factors responsible for the increase of fatigue life of Al-19.4Si alloy have been revealed and analyzed.

Keywords: Al-19.4Si alloy, high intensive electron beam, multicycle fatigue, structure

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Authors: M. Cherki, I. Taouam, A. Amiri, F. Hmimid, T. Ould Bellahcen

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The Moroccan coasts represent an important wealth of red algae which have an economic interest. Among these algae, the Gelidium sesquipedale, which is exploited industrially for its richness in agar. The aim of this study is to establish a general overview of the macronutrient composition of Gelidium sesquipedale and to compare this composition according to three factors: the harvest site (El Jadida, Casablanca and Mohammadia), the harvest depth (coast and depth) and the drying process (open air and oven). Proteins, lipids, and carbohydrates are measured by different methods. The analysis of results show that the protein concentrations of the El Jadida and Mohammadia samples are significantly higher than that of Casablanca (0.026 ± 0.0007 µg/µg DW 0.024 ± 0.001 µg/µg DW and 0.006 ± 0.0007 µg/µg DW, p < 0.05 respectively). However, Casablanca samples are significantly richer in total sugars (0.023 ± 0.002 µg/µg DW, p < 0.05) and less rich in reducing sugars (0.0001 ± 0.00001 µg/µg DW, p < 0.05) compared to other samples. The lipid concentrations of the samples from the three harvest sites do not show any significant difference. With respect to depth, only total protein and total sugar concentrations were significantly higher in the coast versus depth samples (0.035 ± 0.004 µg/µg DW vs. 0.026 ± 0.0007 µg/µg DW and 0.035 ± 0.006 µg/µg DW vs. 0.012 ± 0.005 µg/µg DW p < 0.05 respectively). For the drying process, protein, total sugars and lipid concentrations were significantly higher in open air samples compared to oven samples (0.006 ± 0.0007 µg/µg DW). vs 0.004 ± 0.0003 µg/µg DW, 0.023 ± 0.002 µg/µg DW vs 0.007 ± 0.002 µg/µg DW and 8% vs 4% p < 0.05 respectively). Our results demonstrate that the chemical composition of Gelidium sesquipedale varies according to the harvest region. In addition, samples harvested on the coast and dried in the open air are the richest in macronutrients.

Keywords: biochemical composition, drying, depth, Gelidium sesquipedale, red algae, region

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Kai Pai Huang

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Background: There are several types of plasma cell neoplasms including multiple myeloma, plasmacytoma, lymphoplasmacytic lymphoma, and monoclonal gammopathy of undetermined significance (MGUS) are found in our lab. Today, we want to compare with two cases using the method of capillary electrophoresis. Method: Serum is prepared and electrophoresis is performed at alkaline PH in a capillary using the Sebia® Capillary 2. Albumin and globulins are detected by the detector which is located in the cathode of the capillary and the signals are transformed to peaks. Serum was treated with beta-mercaptoethanol which reducing the polymerized immunoglobulin to monomer immunoglobulin to clarify two M-protein are secreted from the same plasma cell clone in bone marrow. Result: Case 1: A 78-year-old female presenting dysuria, oliguria and leg edema for several months. Laboratory data showed proteinuria, leukocytosis, results of high serum IgA and lambda light chain. A renal biopsy found amyloid fibrils in the glomerular mesangial area. Serum protein electrophoresis shows a major monoclonal peak in the β region and minor small peak in gamma region, and the immunotyping studies for serum showed two IgA/λ type. Case 2: A 55-year-old male presenting abdominal distension and low back pain for more than one month. Laboratory data showed T12 T8 compression fracture, results of high serum IgM and kappa light chain. Bone marrow aspiration showed the cells from the bone marrow are B cells with monotypic kappa chain expression. Bone marrow biopsy found this is lymphoplasmacytic lymphoma (Waldenstrom macroglobulin). Serum protein electrophoresis shows a monoclonal peak in the β region and the immunotyping studies for serum showed IgM/κ type. Conclusion: Plasma cell neoplasm can be diagnosed by many examinations. Among them, using capillary electrophoresis by a lab can separate several types of gammopathy and the quantification of a monoclonal peak can be used to evaluate the patients’ prognosis or treatment.

Keywords: plasma cell neoplasm, capillary electrophoresis, serum protein electrophoresis, immunotyping

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Authors: Z. Abdullah, A. R. Hamdan

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This paper is meant to analyze the ranking of University of Malaysia Terengganu, UMT’s website in the World Wide Web. There are only few researches have been done on comparing the ranking of universities’ websites so this research will be able to determine whether the existing UMT’s website is serving its purpose which is to introduce UMT to the world. The ranking is based on hub and authority values which are accordance to the structure of the website. These values are computed using two web-searching algorithms, HITS and SALSA. Three other universities’ websites are used as the benchmarks which are UM, Harvard and Stanford. The result is clearly showing that more work has to be done on the existing UMT’s website where important pages according to the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s website will act as a guideline for the web-developer to develop a more efficient website.

Keywords: algorithm, ranking, website, web structure mining

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Authors: Maria V. Morozova, Yulia V. Emelyanova, Anastasia A. Levina, Elena S. Buyanova, Zoya A. Mikhaylovskaya, Sofia A. Petrova

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The solid solutions of lanthanum niobates substituted by yttrium, bismuth and tungsten were synthesized. The structure of the solid solutions is either LaNbO4-based monoclinic or BiNbO4-based triclinic. The series where niobium is substituted by tungsten on B site reveals phase-modulated structure. The values of cell parameters decrease with increasing the dopant concentration for all samples except the tungsten series although the latter show higher total conductivity.

Keywords: impedance spectroscopy, LaNbO4, lanthanum ortho-niobates, solid electrolyte

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Authors: Razieh Rezaeekalantari

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Objective: The purpose of this study was to investigate the prediction of parenting orientations in terms of the components of couples' sexual review. Methods: This was a descriptive correlational research method. The population consisted of 500 couples referring to Sari Health Center. Two hundred and fifteen (215) people were selected randomly by using Krejcie-Morgan-sample-size-table. For data collection, the childbearing orientations scale and the Multidimensional Sexual Self-Concept Questionnaire were used. Result: For data analysis, the mean and standard deviation were used and to analyze the research hypothesis regression correlation and inferential statistics were used. Conclusion: The findings indicate that there is not a significant relationship between the tendency to childbearing and the predictive value of sexual review (r = 0.84) with significant level (sig = 219.19) (P < 0.05). So, with 95% confidence, we conclude that there is not a meaningful relationship between sexual orientation and tendency to child-rearing.

Keywords: couples referring, health center, sexual review component, parenting orientations

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: S. Perera, T. R. Walsh, M. Solvang

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The structure-property relationships of calcium aluminosilicate (CAS) glass surfaces are of scientific and technological interest regarding dissolution phenomena. Molecular dynamics (MD) simulations can provide atomic-scale insights into the structure and properties of the CAS interfaces in vacuo as the first step to conducting computational dissolution studies on CAS surfaces. However, one limitation to date is that although the bulk properties of CAS glasses have been well studied by MD simulation, corresponding efforts on CAS surface properties are relatively few in number (both theoretical and experimental). Here, a systematic computational protocol to create CAS surfaces in vacuo is developed by evaluating the sensitivity of the resultant surface structure with respect to different factors. Factors such as the relative thickness of the surface layer, the relative thickness of the bulk region, the cooling rate, and the annealing schedule (time and temperature) are explored. Structural features such as ring size distribution, defect concentrations (five-coordinated aluminium (AlV), non-bridging oxygen (NBO), and tri-cluster oxygen (TBO)), and linkage distribution are identified as significant features in dissolution studies.

Keywords: MD simulation, CAS glasses, surface structure, structure-property, CAS interface

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: Hainan Chen, Jina Qing, Xiao Zhu, Ling Gao, Ampadu O. Jackson, Min Zhang, Kai Yin

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Objective: Editing macrophage activation to dampen inflammatory diseases by promoting the repolarization of inflammatory (M1) macrophages to anti-inflammatory (M2) macrophages is highly associated with mitochondrial respiration. Recent studies have suggested that mitochondrial apolipoprotein A-1 binding protein (APOA1BP) was essential for the cellular metabolite NADHX repair to NADH, which is necessary for the mitochondrial function. The exact role of APOA1BP in the repolarization of M1 to M2, however, is uncertain. Material and method: THP-1-derived macrophages were incubated with LPS (10 ng/ml) or/and IL-4 (100 U/ml) for 24 hours. Biochemical parameters of oxidative phosphorylation and M1/M2 markers were analyzed after overexpression of APOA1BP in cells. Results: Compared with control and IL-4-exposed M2 cells, APOA1BP was downregulated in M1 macrophages. APOA1BP restored the decline in mitochondrial function to improve metabolic and phenotypic reprogramming of M1 to M2 macrophages. Blocking oxidative phosphorylation by oligomycin blunts the effects of APOA1BP on M1 to M2 repolarization. Mechanistically, LPS triggered the hydration of NADH and increased its hydrate NADHX which inhibit cellular NADH dehydrogenases, a key component of electron transport chain for oxidative phosphorylation. APOA1BP decreased the level of NADHX via converting R-NADHX to biologically useful S-NADHX. The mutant of APOA1BP aspartate188, the binding site of NADHX, fail to repair oxidative phosphorylation, thereby preventing repolarization. Conclusions: Restoring mitochondrial function by increasing mitochondrial APOA1BP might be useful to improve the reprogramming of inflammatory macrophages into anti-inflammatory cells to control inflammatory diseases.

Keywords: inflammatory diseases, macrophage repolarization, mitochondrial respiration, apolipoprotein A-1 binding protein, NADHX, NADH

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Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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Authors: F. Alaa Ali, S. A. Sherein Abdelgayed, S. Osama. EL-Tawil, M. Adel Bakeer

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Tartrazine is an organic azo dyes food additive widely used in foods, drugs, and cosmetics. The present study aimed to investigate the toxic effects of tartrazine on kidneys and liver biomarkers in addition to the investigation of oxidative stress and change of histopathological structure of liver and kidneys in 30 male rats. Tartrazine was orally administrated daily at dose 200 mg/ kg bw (1/ 10 LD₅₀) for sixty days. Serum and tissue samples were collected at the end of the experiment to investigate the underlying mechanism of tartrazine through assessment oxidative stress (Glutathione (GSH), Superoxide dismutase (SOD) and malondialdehyde (MDA) and biochemical markers (alanine aminotransferase (ALT), aspartate aminotransferase (AST), Total protein and Urea). Liver and kidneys tissue were collected and preserved in 10% formalin for histopathological examination. The obtained values were statistically analyzed by one way analysis of variance (ANOVA) followed by multiple comparison test. Biochemical analysis revealed that tartrazine induced significant increase in serum ALT, AST, total protein, urea level compared to control group. Tartrazine showed significant decrease in liver GSH and SOD where their values when compared to control group. Tartrazine induced increase in liver MDA compared to control group. Histopathology of the liver showed diffuse vacuolar degeneration in hepatic parenchyma, the portal area showed sever changes sever in hepatoportal blood vessels and in the bile ducts. The kidneys showed degenerated tubules at the cortex together with mononuclear leucocytes inflammatory cells infiltration. There is perivascular edema with inflammatory cell infiltration surrounding the congested and hyalinized vascular wall of blood vessel. The present study indicates that the subchronic effects of tartrazine have a toxic effect on the liver and kidneys together with induction of oxidative stress by formation of free radicals. Therefore, people should avoid the hazards of consuming tartrazine.

Keywords: albino rats, tartrazine, toxicity, pathology

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Authors: Hatane Semuel, Hartmann H. Ngono, Sautma R. Basana

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The effect of capital structure on profitability is often debated by many financial investigators. The application of the trade-off theory and pecking order theory to analyze this relationship may generate different views. Each company has its own strategies to achieve its objectives and the external environment, such as state policy has a broad impact on the relationship with the capital structure of the company's profitability. Malaysia is the country closest to Indonesia that had a similar growth rate of GDP and industrial production with Indonesia, but Malaysia has lower inflation rate than Indonesia. This study was conducted to compare the performance of manufacturing sector between two countries when entering the era of the ASEAN Economic Community (AEC). The samples for this study were 69 companies in Indonesia and 242 companies in Malaysia that engaged in manufacturing sector. The study uses panel data analysis. The study found that the capital structure have positive effect on profitability of manufacturing company in Indonesia, and it turns to negative effect on manufacturing companies in Malaysia. The results also showed that there are significant differences in short-term debt towards profitability of manufacturing companies in the two countries Indonesia and Malaysia.

Keywords: capital structure, Indonesia, Malaysia, manufacturing, profitability

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Authors: Nasim Hashemi, Abbas Sheikhtaheri

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Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

Procedia PDF Downloads 354

Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 138

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 105

Authors: Sarah K. Basudan, Ragad I. Al Jazzar, Zeinah Sulaihim, Hanan M. Al-Kadri

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Background: Cesarean section has been increasing in recent years, with a wide range of etiologies contributing to this rise. This study aimed to assess the indications, outcomes, and complications in Riyadh, Saudi Arabia. Methods: A Retrospective Cohort study was conducted at King Abdulaziz medical city. The study includes two cohorts: G1 (2009) and G2 (2020) groups who met the inclusion criteria. The data was transferred to the SPSS (statistical package for social sciences) version 24 for analysis. The initial descriptive statistics were run for all variables, including numerical and categorical data. The numerical data were reported as median, and standard deviation and categorical data were reported as frequencies and percentages. Results: The data were collected from 399 women who were divided into two groups, G1(199) and G2(200). The mean age of all participants is 32+-6​; G1 and G2 had significant differences in age means with 30+-6 and 34+-5, respectively, with a p-value of <0.001, which indicates delayed fertility by four years. Moreover, a breech presentation was less likely to occur in G2 (OR 0.64, CI: 0.21-0.62. P<0.001). Nonetheless, maternal causes such as repeated C-sections and maternal medical conditions were more likely to happen in G2 (OR 1.5, CI: 1.04-2.38, p=0.03) and (OR 5.4, CI: 1.12-23.9, P=0.01), respectively. Furthermore, postpartum hemorrhage showed an increase of 12% in G2 (OR 5.4, CI: 2.2-13.4, p<0.001). G2 was more likely to be admitted to the neonatal intensive care unit (NICU) (OR 16, CI: 7.4-38.7) and to special care baby (SCB) (OR 7.2, CI: 3.9-13.1), both with a p-value<0.001 compared to regular nursery admission. Conclusion: There are multiple factors that are contributing to the increase in c section rate in a Saudi tertiary hospitals. The factors were suggested to be previous c-sections, abnormal fetal heart rate, malpresentation, and maternal or fetal medical conditions.

Keywords: cesarean sections, maternal indications, maternal complications, neonatal condition

Procedia PDF Downloads 62

Authors: Ali Ait Boughrous, Said Benyoussef, Hossain El Ouarghi, Moulay Abdelazize Aboulhassan, Samah Aitbnichou, Said Benguamra

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The Rhiss-Nekor aquifer represents a primary water source for the central Rif region. Many operating structures were built for irrigation and drinking water supply. Because of the vulnerability of this aquifer, a thorough knowledge of the environment is needed to evaluate and protect resources. This work aims at the quality assessment of the water table of the plain Ghiss-Nekor and determination of pollution sources in order to establish a map of the web. The plain-Rhiss Nekor, with an area of 100 km2, is located on the Mediterranean coast of Morocco. It has a particular geological structure resulting from the opening of a graben at the end of the Tertiary, which is filled by the accumulation of hundreds of meters of sediment, generating considerable heterogeneity in deposits. This heterogeneity gives various hydrodynamic properties within the aquifer of the plain. The analysis of the water quality of twenty water points, well distributed over the plain, showed high natural salinity linked to the geological nature of the area. This salinity increases in the littoral area by the seawater intrusion phenomenon. This is accentuated by overexploitation of the ground water due to the growing demand. Some wells, located inland, are characterized by organic pollution caused by wastewater seepage from septic tanks and lost wells widespread in the region.

Keywords: anthropogenic factors, groundwater quality, marine intrusion, Rhiss-Nekor aquifer

Procedia PDF Downloads 124