Search results for: computational brain

Authors: Vishnu Pratap Singh Kirar

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Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.

Keywords: wireless sensor network (WSN), wireless network attacks, wireless network security, security requirements

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Authors: Fabiano Araujo Soares, Sauro Emerick Salomoni, Joao Paulo Lima da Silva, Igor Luiz Moura, Adson Ferreira da Rocha

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This paper presents a tool developed in the Matlab platform. It was developed to simplify the analysis of surface electromyography signals (S-EMG) in a way accessible to users that are not familiarized with signal processing procedures. The tool receives data by commands in window fields and generates results as graphics and excel tables. The underlying math of each S-EMG estimator is presented. Setup window and result graphics are presented. The tool was presented to four non-engineer users and all of them managed to appropriately use it after a 5 minutes instruction period.

Keywords: S-EMG estimators, electromyography, surface electromyography, ARV, RMS, MDF, MNF, CV

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Authors: Huafeng Wei

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Dementia in Alzheimer’s Disease (AD) is the number one cause of dementia internationally, without effective treatments. Increasing evidence suggest that disruption of intracellular calcium homeostasis, primarily pathological elevation of cytosol and mitochondria but reduction of endoplasmic reticulum (ER) calcium concentrations, play critical upstream roles on multiple pathologies and associated neurodegeneration, impaired neurogenesis, synapse, and cognitive dysfunction in various AD preclinical studies. The last federal drug agency (FDA) approved drug for AD dementia treatment, memantine, exert its therapeutic effects by ameliorating N-methyl-D-aspartate (NMDA) glutamate receptor overactivation and subsequent calcium dysregulation. More research works are needed to develop other drugs targeting calcium dysregulation at multiple pharmacological acting sites for future effective AD dementia treatment. Particularly, calcium channel blockers for the treatment of hypertension and dantrolene for the treatment of muscle spasm and malignant hyperthermia can be repurposed for this purpose. In our own research work, intranasal administration of dantrolene significantly increased its brain concentrations and durations, rendering it a more effective therapeutic drug with less side effects for chronic AD dementia treatment. This review summarizesthe progress of various studies repurposing drugs targeting calcium dysregulation for future effective AD dementia treatment as potentially disease-modifying drugs.

Keywords: alzheimer, calcium, cognitive dysfunction, dementia, neurodegeneration, neurogenesis

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: A. Shahsavar, Z. Jakub

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Due to the outstanding properties of the 2D metal-organic frameworks (MOF), intensive computational and experimental studies have been done. However, the lack of fundamental studies of MOFs on the graphene backbone is observed. This work studies Fe and Ni as metal and tetracyanoquinodimethane (TCNQ) with a high electron affinity as an organic linker functionalized on graphene. Here we present DFT calculations results to unveil the electronic and magnetic properties of iron and nickel-TCNQ physisorbed on graphene. Adsorption and Fermi energies, structural, and magnetic properties will be reported. Our experimental observations prove Fe- and NiTCNQ@Gr/Ir(111) are thermally highly stable up to 500 and 250°C, respectively, making them promising materials for single-atom catalysts or high-density storage media.

Keywords: DFT, graphene, MTCNQ, self-assembly

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Authors: Mitat Uysal, Aynur Uysal

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Computer engineering and mathematics share a deep and symbiotic relationship, with mathematics providing the foundational theories and models for computer engineering advancements. From algorithm development to optimization techniques, mathematics plays a pivotal role in solving complex computational problems. This paper explores key mathematical principles that underpin computer engineering, illustrating their significance through a case study that demonstrates the application of optimization techniques using Python code. The case study addresses the well-known vehicle routing problem (VRP), an extension of the traveling salesman problem (TSP), and solves it using a genetic algorithm.

Keywords: VRP, TSP, genetic algorithm, computer engineering, optimization

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Authors: Kadda Boumediene, Mohamed Bouzit

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The prediction of the flow around marine propellers and vessel hulls propeller interaction is one of the challenges of Computational fluid dynamics (CFD). The CFD has emerged as a potential tool in recent years and has promising applications. The objective of the current study is to predict the hydrodynamic performances of HSP marine propeller in open water and behind a vessel. The unsteady 3-D flow was modeled numerically along with respectively the K-ω standard and K-ω SST turbulence models for steady and unsteady cases. The hydrodynamic performances such us a torque and thrust coefficients and efficiency show good agreement with the experiment results.

Keywords: seiun maru propeller, steady, unstead, CFD, HSP

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Authors: Edgar Teixeira, Eurico Carrapatoso

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As 3D displays become increasingly affordable, while production techniques and computational resources to create stereoscopic content being ever more accessible, a new dimension is literally introduced along with new expressive and immersive potentialities in support of designing for the screen. Prospective design visionaries have already at the reach of their hands an innovative and powerful visualization technology, which enables them to actively envision future trends and vanguardist directions. This paper explores the aesthetic and informational potentialities of stereoscopic motion graphics, providing insight on the application of 3D displays in design practice, proposing strategies to investigate stereoscopic communication, discussing potential repercussions to extant theory and impacts on audience.

Keywords: design, visual communication, technology, stereoscopy, 3D media

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Authors: Wenyu Guo, Malachy O’Rourke, Mark Bowkett, Michael Gilchrist

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Many devices for real-time monitoring of surface water have been developed in the past few years to provide early warning of pollutions and so to decrease the risk of environmental pollution efficiently. One of the most common methodologies used in the detection system is a colorimetric process, in which a container with fixed volume is filled with target ions and reagents to combine a colorimetric dye. The colorimetric ions can sensitively absorb a specific-wavelength radiation beam, and its absorbance rate is proportional to the concentration of the fully developed product, indicating the concentration of target nutrients in the pre-mixed water samples. In order to achieve precise and rapid detection effect, channels with dimensions in the order of micrometers, i.e., microfluidic systems have been developed and introduced into these diagnostics studies. Microfluidics technology largely reduces the surface to volume ratios and decrease the samples/reagents consumption significantly. However, species transport in such miniaturized channels is limited by the low Reynolds numbers in the regimes. Thus, the flow is extremely laminar state, and diffusion is the dominant mass transport process all over the regimes of the microfluidic channels. The objective of this present work has been to analyse the mixing effect and chemistry kinetics in a stop-flow microfluidic device measuring Nitride concentrations in fresh water samples. In order to improve the temporal resolution of the Nitride microfluidic sensor, we have used computational fluid dynamics to investigate the influence that the effectiveness of the mixing process between the sample and reagent within a microfluidic device exerts on the time to completion of the resulting chemical reaction. This computational approach has been complemented by physical experiments. The kinetics of the Griess reaction involving the conversion of sulphanilic acid to a diazonium salt by reaction with nitrite in acidic solution is set in the Laminar Finite-rate chemical reaction in the model. Initially, a methodology was developed to assess the degree of mixing of the sample and reagent within the device. This enabled different designs of the mixing channel to be compared, such as straight, square wave and serpentine geometries. Thereafter, the time to completion of the Griess reaction within a straight mixing channel device was modeled and the reaction time validated with experimental data. Further simulations have been done to compare the reaction time to effective mixing within straight, square wave and serpentine geometries. Results show that square wave channels can significantly improve the mixing effect and provides a low standard deviations of the concentrations of nitride and reagent, while for straight channel microfluidic patterns the corresponding values are 2-3 orders of magnitude greater, and consequently are less efficiently mixed. This has allowed us to design novel channel patterns of micro-mixers with more effective mixing that can be used to detect and monitor levels of nutrients present in water samples, in particular, Nitride. Future generations of water quality monitoring and diagnostic devices will easily exploit this technology.

Keywords: nitride detection, computational fluid dynamics, chemical kinetics, mixing effect

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Authors: Jonathon Bailey, Neil Bressloff, Nick Curzen

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Transcatheter Aortic Valve Implantation (TAVI) devices are stent-like frames with prosthetic leaflets on the inside, which are percutaneously implanted. The device in a crimped state is fed through the arteries to the aortic root, where the device frame is opened through either self-expansion or balloon expansion, which reveals the prosthetic valve within. The frequency at which TAVI is being used to treat aortic stenosis is rapidly increasing. In time, TAVI is likely to become the favoured treatment over Surgical Valve Replacement (SVR). Mortality after TAVI has been associated with severe Paravalvular Aortic Regurgitation (PAR). PAR occurs when the frame of the TAVI device does not make an effective seal against the internal surface of the aortic root, allowing blood to flow backwards about the valve. PAR is common in patients and has been reported to some degree in as much as 76% of cases. Severe PAR (grade 3 or 4) has been reported in approximately 17% of TAVI patients resulting in post-procedural mortality increases from 6.7% to 16.5%. TAVI devices, like SVR devices, are circular in cross-section as the aortic root is often considered to be approximately circular in shape. In reality, however, the aortic root is often non-circular. The ascending aorta, aortic sino tubular junction, aortic annulus and left ventricular outflow tract have an average ellipticity ratio of 1.07, 1.09, 1.29, and 1.49 respectively. An elliptical aortic root does not severely affect SVR, as the leaflets are completely removed during the surgical procedure. However, an elliptical aortic root can inhibit the ability of the circular Balloon-Expandable (BE) TAVI devices to conform to the interior of the aortic root wall, which increases the risk of PAR. Self-Expanding (SE) TAVI devices are considered better at conforming to elliptical aortic roots, however the valve leaflets were not designed for elliptical function, furthermore the incidence of PAR is greater in SE devices than BE devices (19.8% vs. 12.2% respectively). If a patient’s aortic root is too severely elliptical, they will not be suitable for TAVI, narrowing the treatment options to SVR. It therefore follows that in order to increase the population who can undergo TAVI, and reduce the risk associated with TAVI, non-circular devices should be developed. Computational simulations were employed to further advance our understanding of non-circular TAVI devices. Radial stiffness of the TAVI devices in multiple directions, frame bending stiffness and resistance to balloon induced expansion are all computationally simulated. Finally, a simulation has been developed that demonstrates the expansion of TAVI devices into a non-circular patient specific aortic root model in order to assess the alterations in deployment dynamics, PAR and the stresses induced in the aortic root.

Keywords: tavi, tavr, fea, par, fem

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Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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Authors: Feng-Hisang Lai

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CFD(Computational Fluid Dynamics) is conducted to numerically study the flow and heat transfer features of a two-pole, 6,080HP, 60Hz, 3,150V open drip-proof (ODP) motor. The stator and rotor cores in this high voltage induction motor are segmented with the use of spacers for cooling purposes, which leads to difficulties in meshing when the entire system is to be simulated. The system is divided into 4 parts, meshed separately and then combined using interfaces. The deviation between the CFD and experimental results in temperature and flow rate is less than 10%. The internal flow is further examined and a final design is proposed to reduce the winding temperature by 10 degrees.

Keywords: CFD, open drip proof, induction motor, cooling

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Authors: Sang-Woo Han, Jong-Shik Shin

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w-Transaminase (w-TA) is broadly used for synthesizing chiral amines with a high enantiopurity. However, the reaction mechanism of w-TA has been not well studied, contrary to a-transaminase (a-TA) such as AspTA. Here, we propose in silico model on the reaction mechanism of w-TA. Based on the modeling results which showed large free energy gaps between external aldimine and quinonoid on deamination (or ketimine and quinonoid on amination), withdrawal of Ca-H seemed as a critical step which determines the reaction rate on both amination and deamination reactions, which is consistent with previous researches. Hyperconjugation was also observed in both external aldimine and ketimine which weakens Ca-H bond to elevate Ca-H abstraction.

Keywords: computational modeling, reaction intermediates, w-transaminase, in silico model

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Authors: Tunca Gul Altuntas, Aziz Baydar, Cemre Acar, Sezen Yılmaz, Tulay Coban

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Free radicals, which are generated in many bioorganic redox processes, play a role in the pathogenesis of several diseases including cancer, arthritis, hemorrhagic shock, inflammatory, cardiovascular, neurodegenerative diseases and age-related degenerative brain diseases. Exposures of normal cell to free radical damages several structures, oxidizes nucleic acids, proteins, lipids, or DNA. Compounds interfere with the action of reactive oxygen species might be useful in prevention and treatment of these pathologies. A series of indole compounds containing piperazine ring were synthesized. Coupling of indole-2-carboxylic acid with monosubstituted piperazines was accomplished with 1,1’-carbonyldiimidazole (CDI) in a good yield. The structures of prepared compounds were verified in good agreement with their 1H NMR (nuclear magnetic resonance), MS (mass spectrophotometry), and IR (infrared spectrophotometry) characteristics. In this work, all synthetized indole derivatives were screened in vitro for their antioxidative potential against vitamin E (α-tocopherol) using different antioxidant assays such as superoxide anion formation, lipid peroxidation levels in rat liver, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) stable radical scavenging activity. The synthesized compounds showed various levels of inhibition compared to vitamin E. This may give promising results for the development of new antioxidant agents.

Keywords: antioxidant, indoles, piperazines, reactive oxygen species

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Authors: Siamak Shahidi, Nasrin Hashemi-Firouzi, Sara Soleimani-Asl, Alireza Komaki

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Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory and cognitive performance. Recently, an involvement of the serotonergic system and their receptors are suspected in the AD progression. In the present behavioral study, the effects of BIMU (selective 5-HT4 receptor agonist) on cognition and memory in the rat model of AD was investigated. Material and Methods: The animal model of the AD was induced by intracerebroventricular (Icv) injection of amyloid beta (Aβ) in adult male Wistar rats. Animals were divided into experimental groups included control, sham, Aβ, Aβ +BIMU groups. The treatment substances were icv injected (1 μg/μL) for thirty consecutive days. Then, novel object recognition (NOR) and passive avoidance learning (PAL) tests were applied to investigate memory and cognitive performance. Results: Aβ decrease the discrimination index of NOR test. Also, it increases the time spent in the dark compartment during PAL test, as compared with sham and control groups. In addition, compared to Aβ groups, BIMU significantly increased the discrimination index of NOR test and decreased the time spent in the dark compartment of PAL test. Conclusion: These findings suggest that 5-HT4 receptor activation prevents progression of memory and cognitive impairment in a rat model of AD.

Keywords: Alzheimer disease, cognition, memory, serotonin receptors

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: W. Ling, Mohamed Saufi Bin Awang

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Introduction: Mycobacterium tuberculosis post a major health problem worldwide. Central nervous system (CNS) infection by mycobacterium tuberculosis is one of the most devastating complications of tuberculosis. Although with advancement in medical fields, we are yet to understand the pathophysiology of how mycobacterium tuberculosis was able to cross the blood-brain barrier (BBB) and infect the CNS. CNS TB may present with nonspecific clinical symptoms which can mimic other diseases/conditions; this is what makes the diagnosis relatively difficult and challenging. Public health has to be informed and educated about the spread of TB, and early identification of TB is important as it is a curable disease. Case Report: A young 21-year-old Malay gentleman was initially presented to us with symptoms of ear discharge, tinnitus, and right-sided headache for the past one year. Further history reveals that the symptoms have been mismanaged and neglected over the period of 1 year. Initial investigation reveals features of inflammation of the ear. Further imaging showed the feature of chronic inflammation of the otitis media and atypical right cerebral abscess, which has the same characteristic features and consistency. He further underwent a biopsy, and results reveal positive Mycobacterium tuberculosis of the otitis media. With the results and the available imaging, we were certain that this is likely a case of disseminated tuberculosis causing CNS TB. Conclusion: We aim to highlight the challenge and difficult face in our health care system and public health in early identification and treatment.

Keywords: central nervous system tuberculosis, intracranial tuberculosis, tuberculous encephalopathy, tuberculous meningitis

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Authors: M. A. Rubio, A. Urquia

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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: optimization, sensitivity, genetic algorithms, model calibration

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Authors: Hernández Eva Selene, Reyna Mary Carmen, Rivera Héctor, Barragán Irving

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We propose an approach that jointly addresses the layout of a facility and the scheduling of a sequence of jobs. In real production, these two problems are interrelated. However, they are treated separately in the literature. Our approach is an extension of the job shop problem with transportation delay, where the location of the machines is selected among possible sites. The model minimizes the makespan, using the short processing times rule with two algorithms; the first one considers all the permutations for the location of machines, and the second only a heuristic to select some specific permutations that reduces computational time. Some instances are proved and compared with literature.

Keywords: layout problem, job shop scheduling problem, concurrent scheduling and layout problem, metaheuristic

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Authors: Igna Brajević Gizdić, Gorka Vuletić

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Introduction: Addiction is a chronic brain relapsing disorder. Opioid Substitution Therapy (OST) using buprenorphine as a medical treatment option shows as a promising option for achieving and maintaining abstinence in opioid-addicted patients. This research aimed to determine and evaluate the quality of life (QoL) in opiate-addicted patients after five years of buprenorphine therapy. Method: The total sample included 44 buprenorphine-maintained opiate addicts in outpatient treatment. The participants were administered the QoL questionnaire (WHOQOL-BREF) at two-time points (T1 and T2) with an interval of at least five years. WHOQOL-BREF contains a total of 26 questions. The first two questions, related to overall QoL and general health status, and the remaining questions (3–26), which represented four domains—physical, psychological, social, and environmental health—were evaluated separately. Results: The results indicated no significant differences in overall self-assessed QoL nor in individual domains after five years (T2) of abstinence with OST buprenorphine- maintenance. Conclusion: These findings indicated no improvement in QoL of buprenorphine-maintenance opiate addicts in outpatient treatment. However, this might be due to the smaller sample size and participants' overall high scores in QoL at T1. This study suggests the importance of expectations when considering the QoL and general health of buprenorphine-maintenance opiate addicts in outpatient treatment.

Keywords: abstinence, addicts, buprenorphine, opioid substitution therapy, quality of life

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Francielle A. Vargas, Thiago A. S. Pardo

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According to the standard philosophical definition, lying is saying something that you believe to be false with the intent to deceive. For deception detection, the FBI trains its agents in a technique named statement analysis, which attempts to detect deception based on parts of speech (i.e., linguistics style). This method is employed in interrogations, where the suspects are first asked to make a written statement. In this poster, we model false statements using linguistics style. In order to achieve this, we methodically analyze linguistic features in a corpus of fake news in the Portuguese language. The results show that they present substantial lexical, syntactic and semantic variations, as well as punctuation and emotion distinctions.

Keywords: deception detection, linguistics style, computational linguistics, natural language processing

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Authors: Sang-Sun Yoon, Yea-Hyun Leem, Sangmee Ahn Jo

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The N-acetylated-alpha-linked-acidic (NAAG) peptidase inhibitor 2-phosphonomethyl pentanedioic acid (2-PMPA) has demonstrated to be neuroprotective against glutamate-mediated neuron degeneration and neurological disorders such as ischemia. Several studies have demonstrated impaired psychiatric function by altered glutamate carboxypeptidase II expression, although 2-PMPA has not yet been studied. Thus, we investigated effect of 2-PMPA on depressive-like phenotype using C57BL/6 mice. Treatment of 2-PMPA (10 mg/kg for 6 days/daily, ip injection) on C57BL/6 naïve mice showed depressive-like symptoms such as decreased social preference, but did not affect the immobility measured by tail suspension test. Reduction of phosphorylated cAMP-responsive element binding (p-CREB) known as a representative marker of depressive-like behavior was observed in layer 1 and piriform cortex subregions of the prefrontal cortex of 2-PMPA-treated mice. The immunoreactivity of metabotropic glutamate receptors 5 (mGluR5) that mediate phosphorylation of CREB was also decreased in layer 1 and piriform cortex subregions of the prefrontal cortex of 2-PMPA injected mice. Thus, our results suggest that dysregulation of the GCPII or NAAG by 2-PMPA treatment is likely to be associated with pathogenesis of depression and further studies are needed to understand whether the reduced NAAG level or enhanced glutamate level in the brain is involved in this response.

Keywords: depression, GCPII, 2-PMPA, p-CREB, mGluR5

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Authors: Jayaprakash Kar, Daniyal M. Alghazzawi

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The article proposes a novel construction of signcryption scheme with provable security which is most suited to implement on smart card. It is secure in random oracle model and the security relies on Decisional Bilinear Diffie-Hellmann Problem. The proposed scheme is secure against adaptive chosen ciphertext attack (indistiguishbility) and adaptive chosen message attack (unforgebility). Also, it is inspired by zero-knowledge proof. The two most important security goals for smart card are Confidentiality and authenticity. These functions are performed in one logical step in low computational cost.

Keywords: random oracle, provable security, unforgebility, smart card

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Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

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Authors: Mandeep Kataria, Ritu Narula, Navneet Kaur

Abstract:

Asparagine is vital amino acid which is required for the development of brain and it regulates the equilibrium of central nervous system. Asparagine is the chief amino acid that forms acrylamide in baked food by reacting with reducing sugars at high temperature ( Millard Reaction i.e. amino acids and sugars give new flavors at high temperature). It can also be a parameter of freshness in fruit juices because on storage of juices at 37°C caused an 87% loss in the total free amino acids and major decrease was recorded in asparagine contents. With this significance of monitoring asparagine, in the present work a biosensor for determining asparagine in fruit juices is developed. For the construction of biosensor L-asparaginase enzyme (0.5 IU) was co-immobilized with phenol red on TEOS chitosan sol-gel plastic disc and fixed on the fiber optic tip. Tip was immersed in a cell having 5ml of substrate and absorption was noted at response time of 5 min with 10-1 - 10-10 M concentrations of asparagine at 538 nm. L-asparaginase was extracted and from Solanum nigrum Asparagine biosensor was applied fruit juices on the monitoring asparagine contents. L-asparagine concentration found to be present in fruit juices like Guava Juice, Apple Juice, Mango Juice, Litchi juice, Strawberry juice, Pineapple juice Lemon juice, and Orange juice. Hence the developed biosensor has commercial aspects in quality insurance of fruit juices.

Keywords: fiber optic biosensor, chitosan, teos, l-asparaginase

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Authors: Ioanna Koumi

Abstract:

The aim of the intervention presented is to show the positive effects a mindfulness programme can have on the behaviour of preschoolers (years 4-6). The programme was implemented as part of the psychologist's work in 5 preschool units on the Greek island of Chios. Classroom-based activities of mindfulness were shown and practiced in 5 sessions, in collaboration with teachers, in order to make preschoolers aware of how their brain affects their behaviour, as well as of how they can have more positive behaviours, especially in instances of negative feelings. The outcomes of the intervention were assessed via questionnaire completion before and after the sessions by the teachers, as well as focus groups procedures with students, teachers, and parents. Implications of how mindfulness programmes can also be implemented at home are further discussed. School year in which the programme is being implemented: 2022-23 Intervention method: based on basic mindfulness theory and practice, the 220 students (age 4-6) in 11 classes of the 5 preschools that participated were given lessons of how to become aware of their states of focusing, regulation, attention, emotional situation, as well as body and social situations. Furthermore, the preschoolers were encouraged to make more mindful choices when it came to negative situations and emotions. Assessment method: The school as a caring community Profile II – Questionnaire completed by 20 preschool teachers prior to and after the intervention, Focus group sessions with teachers, students, parents at the end of the intervention Results: the assessment will be completed in May 2023.

Keywords: preschool, mindfulness training, self-awareness, social-emotional development

Procedia PDF Downloads 97

Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Yuna Inada, Chihiro Tohda

Abstract:

Intro: Trigonella foenum-graecum (Fenugreek), from Fabaceae family is a well-known plant traditionally used as food and medicine. Many pharmacological effects of Trigonella foenum- graecum seeds extract (TF extract) were evaluated such as anti-diabetic, anti-tumor and anti-dementia effects using in vivo models. Regarding the anti-dementia effects of TF extract, diabetic rats, aluminum chloride-induced amnesia rats and scopolamine-injected mice were used previously for evaluation, which are not well established as Alzheimer’s disease models. In addition, those previous studies, active constituents in TF extract for memory function were not identified. Method: This study aimed to clarify the effect of TF extract on Alzheimer’s disease model, 5XFAD mouse that overexpresses mutated APP and PS1 genes and determine the major active constituent in the brain after oral intake of TF extract. Results: Trigonelline was detected in the cerebral cortex of 5XFAD mice after 24 hours of oral administration of TF extract by LC-MS/MS. Oral administration of TF extract for 17 days improved object location memory in 5XFAD mice. Conclusion: These results suggest that TF extract and its active constituents could be an expected therapeutic candidate for Alzheimer’s disease.

Keywords: Alzheimer's disease, LC-MS/MS, memory recovery, Trigonella foenum-graecum Seeds, 5XFAD mice

Procedia PDF Downloads 149

Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

Abstract:

The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

Procedia PDF Downloads 425