Search results for: memory stimulation

Authors: Chanya Inprasit, Ching-Liang Hsieh, Yi-Wen Lin

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Obesity (OB) is a hazardous global health problem that has been increasing in prevalence, more severely in last decade. It is the mainly resultant from the imbalance between food consumption and energy expenditure, which is concordant with a modern lifestyle, implying an increase in calories with poorer quality of food intake accompanied by a decrease in physical activities. Obesity does not concern the appearance only but is also a major factor contributing to poor physiology, psychology, society and economic issues. Moreover, OB induces low-grade inflammation in the body through the regulatory effect it enacts on the adipocyte function. Various alternative treatments were investigated for body weight control, including Acupoint Catgut Embedding (ACE). ACE is the implantation of absorbable catgut sutures at specific acupoints, displaying durable and potent stimulation and thereby reducing the treatment frequency. Our study utilized a mouse model to exclude any psychological factors of OB and ACE treatment. High-fat diet and body weight were measured once a week before subjects in ACE and Sham group received the ACE treatment or placebo treatment. We hypothesized that ACE can control body weight through the interaction of the TRPV1 pathways, as TRPV1 accordingly responds to inflammatory factors. The results of body weight variation show a significant decrease in body weight in ACE group compared with the baseline of control and Sham group. Meanwhile, converse results were explored in TRPV1 knockout mice, where a significant maintenance of normal body weight throughout the experiment period was observed. There was no significant difference in food consumption of each group. These finding indicated that TRPV1 pathways and its associated pathways may be involved in the maintenance of body weight, which can be controlled by ACE treatment of genetic manipulation.

Keywords: acupoint catgut embedding, obesity, hypothalamus, TRPV1

Procedia PDF Downloads 151

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Muhammad Al Baqir Zinal Abidin, Md Hanif Md Nasir

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This paper will discuss how we optimize our physical verification flow in our IC Design Department having various rule decks from multiple foundries. Our ultimate goal is to achieve faster time to tape-out and avoid schedule delay. Currently the physical verification runtimes and memory usage have drastically increased with the increasing number of design rules, design complexity and the size of the chips to be verified. To manage design violations, we use a number of solutions to reduce the amount of violations needed to be checked by physical verification engineers. The most important functions in physical verifications are DRC (design rule check), LVS (layout vs. schematic) and XRC (extraction). Since we have a multiple number of foundries for our design tape-outs, we need a flow that improve the overall turnaround time and ease of use of the physical verification process. The demand for fast turnaround time is even more critical since the physical design is the last stage before sending the layout to the foundries.

Keywords: physical verification, DRC, LVS, XRC, flow, foundry, runset

Procedia PDF Downloads 654

Authors: Azza M. Atya, Mahmoud M. Nasser

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Background/ /Significance: Peripheral neuropathy is one of the long term serious complications of diabetes, which may attribute to postural instability and alteration of planter pressure. Whole body vibration (WBV) is a somatosensory stimulation type of exercise that has been emerged in sport training and rehabilitation of neuromuscular disorders. Purpose: The aim of this study was to investigate the effect of whole Body Vibration on antroposterior (AP), mediolateral (ML) posture stability and planter foot pressure in patients with diabetic neuropathy. Subjects: forty diabetic patients with moderate peripheral neuropathy aged from 35 to 50 years, were randomly assigned to WBV group (n=20) and control group (n=20). Methods and Materials: the WBV intervention consisted of three session weekly for 8 weeks (frequency 20 Hz, peak-to peak displacement 4mm, acceleration 3.5 g). Biodex balance system was used for postural stability assessment and the foot scan plate was used to measure the mean peak pressure under the first and lesser metatarsals. The main Outcome measures were antroposterior stability index (APSI), mediolateral stability index (MLSI), overall stability index (OSI),and mean peak foot pressure. Analyses: Statistical analysis was performed using the SPSS software package (SPSS for Windows Release 18.0). T-test was used to compare between the pre- and post-treatment values between and within groups. Results: For the 40 study participants (18male and 22 females) there were no between-group differences at baseline. At the end of 8 weeks, Subjects in WBV group experienced significant increase in postural stability with a reduction of mean peak of planter foot pressure (P<0.05) compared with the control group. Conclusion: The result suggests that WBV is an effective therapeutic modality for increasing postural stability and reducing planter pressure in patients with diabetic neuropathy.

Keywords: whole body vibration, diabetic neuropathy, posture stability, foot pressure

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Authors: Pechpailin Kortnoi, Tanitnun Paprad

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Background: Myasthenia gravis (MG) is an autoimmune disorder characterized by impaired neuromuscular transmission due to antibodies against nicotinic receptors, leading to muscle weakness, ptosis, and respiratory issues. The incidence of MG has risen globally, emphasizing the need for effective diagnostics. Objective: This study evaluates the validity of a combined bedside test (the ice pack test and fatigability test) for diagnosing juvenile myasthenia gravis (JMG) in pediatric patients with ptosis. Methods: This cross-sectional study, conducted from January 2012 to May 2024 at King Chulalongkorn Memorial Hospital, Thailand, included pediatric patients (1 month to 18 years) with ptosis undergoing ice pack and fatigability tests. Data included demographics, clinical findings, and test results. Diagnostic efficacy was assessed using sensitivity, specificity, accuracy, PPV, NPV, Fagan Nomogram, Kappa Statistics, and McNemar’s Chi-Square. Results: Of 43 identified patients, 32 were included, with 47% male and a mean age of 7 years. The combined bedside test had high sensitivity (92.8%) and accuracy (87.5%) but moderate specificity (50%). It significantly outperformed the ice pack test (P = 0.0005), which showed low sensitivity (42.8%) and accuracy (43.8%). The fatigability test had 82% sensitivity and 92% PPV. Confirmatory tests (AChR-Ab, MuSK-Ab, neostigmine, repetitive nerve stimulation) supported most diagnoses. Conclusions: The combined bedside test, with high sensitivity (92.8%) and accuracy (87.5%), is an effective screening tool for juvenile myasthenia gravis, outperforming the ice pack test. Integrating it into clinical practice may improve diagnosis and enable timely treatment. The fatigability test (82% sensitivity) is also useful as an adjunct screening tool.

Keywords: myasthenia gravis (MG), the ice pack test, the fatigability test, the combined bedside test

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Authors: Irina Deputat, Anatoly Gribanov, Yuliya Dzhos, Alexandra Nekhoroshkova, Tatyana Yemelianova, Irina Bolshevidtseva, Irina Deryabina, Yana Kereush, Larisa Startseva, Tatyana Bagretsova, Irina Ikonnikova

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In the modern world the number of elderly people increases. Preservation of functionality of an organism in the elderly becomes very important now. During aging the higher cortical functions such as feelings, perception, attention, memory, and ideation are gradual decrease. It is expressed in the rate of information processing reduction, volume of random access memory loss, ability to training and storing of new information decrease. Perspective directions in studying of aging neurophysiological parameters are brain imaging: computer electroencephalography, neuroenergy mapping of a brain, and also methods of studying of a neurodynamic brain processes. Research aim – to study features of a brain aging in elderly people by electroencephalogram (EEG) and the DC-potential level. We examined 130 people aged 55 - 74 years that did not have psychiatric disorders and chronic states in a decompensation stage. EEG was recorded with a 128-channel GES-300 system (USA). EEG recordings are collected while the participant sits at rest with their eyes closed for 3 minutes. For a quantitative assessment of EEG we used the spectral analysis. The range was analyzed on delta (0,5–3,5 Hz), a theta - (3,5–7,0 Hz), an alpha 1-(7,0–11,0 Hz) an alpha 2-(11–13,0 Hz), beta1-(13–16,5 Hz) and beta2-(16,5–20 Hz) ranges. In each frequency range spectral power was estimated. The 12-channel hardware-software diagnostic ‘Neuroenergometr-KM’ complex was applied for registration, processing and the analysis of a brain constant potentials level. The DC-potential level registered in monopolar leads. It is revealed that the EEG of elderly people differ in higher rates of spectral power in the range delta (р < 0,01) and a theta - (р < 0,05) rhythms, especially in frontal areas in aging. By results of the comparative analysis it is noted that elderly people 60-64 aged differ in higher values of spectral power alfa-2 range in the left frontal and central areas (р < 0,05) and also higher values beta-1 range in frontal and parieto-occipital areas (р < 0,05). Study of a brain constant potential level distribution revealed increase of total energy consumption on the main areas of a brain. In frontal leads we registered the lowest values of constant potential level. Perhaps it indicates decrease in an energy metabolism in this area and difficulties of executive functions. The comparative analysis of a potential difference on the main assignments testifies to unevenness of a lateralization of a brain functions at elderly people. The results of a potential difference between right and left hemispheres testify to prevalence of the left hemisphere activity. Thus, higher rates of functional activity of a cerebral cortex are peculiar to people of early advanced age (60-64 years) that points to higher reserve opportunities of central nervous system. By 70 years there are age changes of a cerebral power exchange and level of electrogenesis of a brain which reflect deterioration of a condition of homeostatic mechanisms of self-control and the program of processing of the perceptual data current flow.

Keywords: brain, DC-potential level, EEG, elderly people

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

Procedia PDF Downloads 132

Authors: Ti-Jun Xiao, Zhe Xu

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Controllability is one of the fundamental issues in control systems. In this paper, we study the controllability of second order evolutional control systems in Hilbert spaces with memory and boundary controls, which model dynamic behaviors of some viscoelastic materials. Transferring the control problem into a moment problem and showing the Riesz property of a family of functions related to Cauchy problems for some integrodifferential equations, we obtain a general boundary controllability theorem for these second order evolutional control systems. This controllability theorem is applicable to various concrete 1D viscoelastic systems and recovers some previous related results. It is worth noting that Riesz sequences can be used for numerical computations of the control functions and the identification of new Riesz sequence is of independent interest for the basis-function theory. Moreover, using the Riesz sequences, we obtain the existence and uniqueness of (weak) solutions to these second order evolutional control systems in Hilbert spaces. Finally, we derive the exact boundary controllability of a viscoelastic beam equation, as an application of our abstract theorem.

Keywords: evolutional control system, controllability, boundary control, existence and uniqueness

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

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Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

Procedia PDF Downloads 178

Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

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Authors: Nunu Nakashidze, Shota Lominadze, Darejan Jashi

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Citrus culture used to be one of the leading fields of sub-tropical agriculture in Georgia and especially in Adjara region, but the citrus production has been significantly decreased in recent years due to deterioration of quality index of fruit and reduction of sale markets. The fact severely affected both the economy of Republic and population. Intensive technologies of citrus fruit production are widely implemented in the world practices, which include the following: variety of species, consumption of fertilizers and chemicals, proper use of fruit production and etc. However working on technologies which ensure getting of high quality and plentiful product is very much important if taking into consideration modern, global ecological problems. Using of bio-preparations for plant nourishment is considered as one of the activities. The present work discusses liquid organic fertilizer 'Biorag' produced in Georgia and influence of its growth stimulation (Gakhokidze N1, N2, N3) on agrochemical index of soils and mineral composition of fruit of Citrus Unshiu orchards cultivated in the sub-tropical zone of Black Sea in Adjara region. It was ascertained that liquid organic fertilizers used in the orchard of citrus 'Unshiu' and influence of growth stimulators on the quality index of fruit are not clearly shown in comparison with control one. A small priority is noticed in case of growth stimulators. In conditions of red soils, liquid organic fertilizers and growth stimulators added in the nutrition of the citrus more or less influence the dry material of fruit and the composition of ash and nutrition elements. Agro-chemical index of the soil, except exchange acidity, is somehow enlarged which is one of the positive results in this case.

Keywords: growth stimulator, liquid fertilizer, plant, fruit, soil

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Authors: Nima Shafaghi, Gunay Anlaş, C. Can Aydiner

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A realistic understanding of martensitic phase transition under complex stress states is key for accurately describing the mechanical behavior of shape memory alloys (SMAs). Particularly regarding the sharply changing stress fields at the tip of a crack, the size, nature and shape of transformed zones are of great interest. There is significant variation among various analytical models in their predictions of the size and shape of the transformation zone. As the fully transformed region remains inside a very small boundary at the tip of the crack, experimental validation requires microscopic resolution. Here, the crack tip vicinity of NiTi compact tension specimen has been monitored in situ with microscopic image correlation with 20x magnification. With nominal 15 micrometer grains and 0.2 micrometer per pixel optical resolution, the strains at the crack tip are mapped with intra-grain detail. The transformation regions are then deduced using an equivalent strain formulation.

Keywords: digital image correlation, fracture, martensitic phase transition, mode I, NiTi, transformation zone

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.

Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow

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Authors: Athicha Cherdpunt, Patompong Satapornpong

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The medical cannabis is made up of components also known as cannabinoids, which consists of two ingredients which are Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Interestingly, the Cannabinoid can be used for many treatments such as chemotherapy, including nausea and vomiting, cachexia, anorexia nervosa, spinal cord injury and disease, epilepsy, pain, and many others. However, the adverse drug reactions (ADRs) of THC can cause sedation, anxiety, dizziness, appetite stimulation and impairments in driving and cognitive function. Furthermore, genetic polymorphisms of CYP2C9, CYP2C19 and CYP3A4 influenced the THC metabolism and might be a cause of ADRs. Particularly, CYP2C19*17 allele increases gene transcription and therefore results in ultra-rapid metabolizer phenotype (UM). The aim of this study, is to investigate the frequency of CYP2C19*17 alleles in Thai patients who have been treated with medical cannabis. We prospectively enrolled 60 Thai patients who were treated with medical cannabis and clinical data from College of Pharmacy, Rangsit University. DNA of each patient was isolated from EDTA blood, using the Genomic DNA Mini Kit. CYP2C19*17 genotyping was conducted using the real time-PCR ViiA7 (ABI, Foster City, CA, USA). 30 patients with medical cannabis-induced ADRs group, 20 (67%) were female, and 10 (33%) were male, with an age range of 30-69 years. On the other hand, 30 patients without medical cannabis-induced ADRs (control group) consist of 17 (57%) female and 13 (43%) male. The most ADRs for medical cannabis treatment in the case group were dry mouth and dry throat (77%), tachycardia (70%), nausea (30%) and arrhythmia(10%). Accordingly, the case group carried CYP2C19*1/*1 (normal metabolizer) approximately 93%, while 7% patients carrying CYP2C19*1/*17 (ultra rapid metabolizers) exhibited in this group. Meanwhile, we found 90% of CYP2C19*1/*1 and 10% of CYP2C19*1/*17 in control group. In this study, we identified the frequency of CYP2C19*17 allele in Thai population which will support the pharmacogenetics biomarkers for screening and avoid ADRs of medical cannabis treatment.

Keywords: CYP2C19, allele frequency, ultra rapid metabolizer, medical cannabis

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Authors: Chirag Kothawade, Gourie Jagtap, PreetKaur Relusinghani, Vedang Chavan, Smitha S. Bhosale

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Psychological research has proven that music relieves stress, elevates mood, and is responsible for the release of “feel-good” chemicals like oxytocin, serotonin, and dopamine. It comes as no surprise that music has been a popular tool in rehabilitation centers and therapy for various disorders, thus with the interminably rising numbers of people facing mental health-related issues across the globe, addressing mental health concerns is more crucial than ever. Despite the existing music recommendation systems, there is a dearth of holistically curated algorithms that take care of the needs of users. Given that, an undeniable majority of people turn to music on a regular basis and that music has been proven to increase cognition, memory, and sleep quality while reducing anxiety, pain, and blood pressure, it is the need of the hour to fashion a product that extracts all the benefits of music in the most extensive and deployable method possible. Our project aims to ameliorate our users’ mental state by building a comprehensive mood-based music recommendation system called “Viby”.

Keywords: language, communication, speech recognition, interaction

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: G. Ultanbekova, Zh. Suleimenova, Zh. Rakhmetova, G. Mombekova, S. Mantieva

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Plant Growth Promoting Rhizobacteria (PGPR) are a group of free-living bacteria that colonize the rhizosphere, enhance plant growth of many cereals and other important agricultural crops and protect plants from disease and abiotic stresses through a wide variety of mechanisms. The use of PGPR has been proven to be an environmentally sound way of increasing crop yields by facilitating plant growth. In the present study, strain improvement of PGPR isolates were carried out by chemical mutagenesis for the improvement of growth and yield of lima bean. Induced mutagenesis is widely used for the selection of microorganisms producing biologically active substances and further improving their activities. Strain improvement is usually done by classical mutagenesis which involves exposing the microbes to chemical or physical mutagens. The strains of Pseudomonas putida 4/1, Azotobacter chroococcum Р-29 and Bacillus subtilis were subjected to mutation process for strain improvement by treatment with a chemical agent (sodium nitrite) to cause mutation and were observed for its consequent action on the seeds germination and plant growth of lima bean (Phaseolus lunatus). Bacterial mutant strains of Pseudomonas putida M-1, Azotobacter chroococcum M-1 and Bacillus subtilis M-1, treated with sodium nitrite in the concentration of 5 mg/ml for 120 min, were found effective to enhance the germination of lima bean seeds compared to parent strains. Moreover, treatment of the lima bean seeds with a mutant strain of Bacillus subtilis M-1 had a significant stimulation effect on plant growth. The length of the stems and roots of lima bean treated with Bacillus subtilis M-1 increased significantly in comparison with parent strain in 1.6 and 1.3 times, respectively.

Keywords: chemical mutagenesis, germination, kidney bean, plant growth promoting rhizobacteria (PGPR)

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Authors: Nilamadhab Mohanty

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It is essential to use message formats that make communication understandable and correct. It is because; the information format can influence consumer decision on the purchase of a product. This study combines information from qualitative inquiry, media trend analysis, eye tracking experiment, and questionnaire data to examine the impact of specific message format and consumer perceived risk on attention to the information and risk retention. We investigated the influence of message framing (goal framing, attribute framing, and mix framing) on consumer memory, study time, and decisional uncertainty while deciding on the purchase of drugs. Furthermore, we explored the impact of consumer perceived risk (associated with the use of the drug, i.e., RISK-AB and perceived risk associated with the non-use of the drug, i.e., RISK-EB) on message format preference. The study used eye-tracking methods to understand the differences in message processing. Findings of the study suggest that the message format influences information processing, and participants' risk perception impacts message format preference. Eye tracking can be used to understand the format differences and design effective advertisements.

Keywords: message framing, consumer perceived risk, advertising, eye tracking

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Authors: Utkan Caliskan

Abstract:

Two types of numerical codes based on finite volume method are developed in order to solve compressible Euler equations to simulate the flow through forward facing step channel. Both algorithms have AUSM+- up (Advection Upstream Splitting Method) scheme for flux splitting and two-stage Runge-Kutta scheme for time stepping. In this study, the flux calculations differentiate between the algorithm based on OpenFOAM mesh format which is called 'face-based' algorithm and the basic algorithm which is called 'element-based' algorithm. The face-based algorithm avoids redundant flux computations and also is more flexible with hybrid grids. Moreover, some of OpenFOAM’s preprocessing utilities can be used on the mesh. Parallelization of the face based algorithm for which atomic operations are needed due to the shared memory model, is also presented. For several mesh sizes, 2.13x speed up is obtained with face-based approach over the element-based approach.

Keywords: cell centered finite volume method, compressible Euler equations, OpenFOAM mesh format, OpenMP

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Authors: Shohreh Azizi, Memory Tekere, Wag Nel

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An evaluation of the characteristics of wastewater generated from small communities was carried out in relation to decentralized approach for domestic sewage treatment plant and design of biological nutrient removal system. The study included the survey of the waste from various individual communities such as a hotel, a residential complex, an office premise, and an educational institute. The results indicate that the concentration of organic pollutant in wastewater from the residential complex is higher than the waste from all the other communities with COD 664 mg/l, BOD 370.2 mg/l and TSS 248.8 mg/l. And the waste water from office premise indicates low organic load with COD428 mg/l, BOD 232mg/l and TSS 157mg/l. The wastewater from residential complex was studied under activated sludge process to evaluate this technology for decentralized wastewater treatment. The Activated sludge process was operated at different 12to 4 hrs hydraulic retention times and the optimum 6 hrs HRT was selected, therefore the average reduction of COD (85.92%) and BOD (91.28 %) was achieved. The issue of sludge recycling, maintenance of biomass concentration and high HRT reactor (10 L) volume are making the system non-practical for smaller communities.

Keywords: wastewater, small communities, activated sludge process, decentralized system

Procedia PDF Downloads 357

Authors: Wajeeha Shahid

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The study was designed to assess the impact of transformational and transactional leadership styles on work motivation and organizational commitment among faculty members of universities of Punjab. 713 faculty members were selected as sample through convenient random sampling technique. Three self-constructed questionnaires namely Leadership Styles Questionnaire (LSQ), Work Motivation Questionnaire (WMQ) and Organizational Commitment Questionnaire (OCMQ) were used as research instruments. Major objectives of the study included assessing the effect and impact of transformational and transactional leadership styles on work motivation and organizational commitment. Theoretical frame work of the study included Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Contingent Rewards and Management by Exception as independent variables and Extrinsic motivation, Intrinsic motivation, Affective commitment, Continuance commitment and Normative commitment as dependent variables. SPSS Version 21 was used to analyze and tabulate data. Cronbach's Alpha reliability, Pearson Correlation and Multiple regression analysis were applied as statistical treatments for the analysis. Results revealed that Idealized Influence correlated significantly with intrinsic motivation and Affective commitment whereas Contingent rewards had a strong positive correlation with extrinsic motivation and affective commitment. Multiple regression models revealed a variance of 85% for transformational leadership style over work motivation and organizational commitment. Whereas transactional style as a predictor manifested a variance of 79% for work motivation and 76% for organizational commitment. It was suggested that changing organizational cultures are demanding more from their leadership. All organizations need to consider transformational leadership style as an important part of their equipment in leveraging both soft and hard organizational targets.

Keywords: leadership styles, work motivation, organizational commitment, faculty member

Procedia PDF Downloads 308

Authors: Marc Sebastián-Romagosa, Woosang Cho, Rupert Ortner, Christy Li, Christoph Guger

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Neurorehabilitation based on Brain-Computer Interfaces (BCIs) shows important rehabilitation effects for patients after stroke. Previous studies have shown improvements for patients that are in a chronic stage and/or have severe hemiparesis and are particularly challenging for conventional rehabilitation techniques. For this publication, seven stroke patients in the chronic phase with hemiparesis in the lower extremity were recruited. All of them participated in 25 BCI sessions about 3 times a week. The BCI system was based on the Motor Imagery (MI) of the paretic ankle dorsiflexion and healthy wrist dorsiflexion with Functional Electrical Stimulation (FES) and avatar feedback. Assessments were conducted to assess the changes in motor improvement before, after and during the rehabilitation training. Our primary measures used for the assessment were the 10-meters walking test (10MWT), Range of Motion (ROM) of the ankle dorsiflexion and Timed Up and Go (TUG). Results show a significant increase in the gait speed in the primary measure 10MWT fast velocity of 0.18 m/s IQR = [0.12 to 0.2], P = 0.016. The speed in the TUG was also significantly increased by 0.1 m/s IQR = [0.09 to 0.11], P = 0.031. The active ROM assessment increased 4.65º, and IQR = [ 1.67 - 7.4], after rehabilitation training, P = 0.029. These functional improvements persisted at least one month after the end of the therapy. These outcomes show the feasibility of this BCI approach for chronic stroke patients and further support the growing consensus that these types of tools might develop into a new paradigm for rehabilitation tools for stroke patients. However, the results are from only seven chronic stroke patients, so the authors believe that this approach should be further validated in broader randomized controlled studies involving more patients. MI and FES-based non-invasive BCIs are showing improvement in the gait rehabilitation of patients in the chronic stage after stroke. This could have an impact on the rehabilitation techniques used for these patients, especially when they are severely impaired and their mobility is limited.

Keywords: neuroscience, brain computer interfaces, rehabilitat, stroke

Procedia PDF Downloads 92

Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: C. van den Berg, C. Pokpas

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Popular discourse touts entrepreneurship as a universal solution for underdevelopment, unemployment, and poverty. Moreover, claims are made that women and other disadvantaged groups can achieve material and personal success through digital entrepreneurship. This paper examines the potential of digital technology in entrepreneurial ventures to stimulate economic growth for marginalized groups and communities. Although digital entrepreneurship is hailed as a means to empower under-resourced and socially marginalized people, these opportunities still exist within the confines of existing social and cultural practices. The perspectives of female digital entrepreneurs in developing countries are sorely understudied, particularly concerning an understanding of the complex underlying socio-cultural factors impeding women’s entrepreneurial behaviors. This qualitative study, guided by a feminist phenomenological perspective, focused on the experiences of digital female entrepreneurs in the Western Cape of South Africa. Data were collected via semi-structured interviews and analyzed through the interpretative phenomenological analysis (IPA) approach to determine the relationships between digital entrepreneurship and structural and agential enabling conditions. Findings show that digital entrepreneurship is not a panacea for economic growth in marginalized groups and communities and highlight the importance of addressing socio-cultural gender inequality to enable successful entrepreneurial activity. The paper concludes with recommendations for specialized training initiatives aimed at female entrepreneurs that address internalized constraints and barriers that keep women subservient and measures to shift gender and power beliefs. The outcome will benefit the stimulation of gender-specific public policies to develop a successful digital start-up ecosystem further.

Keywords: digital innovation, female digital entrepreneurs, feminist phenomenology, gender, marginalised communities

Procedia PDF Downloads 135

Authors: Jay P. Sipani, Riki H. Patel, Trushit Upadhyaya

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Today there is a demand to monitor environmental factors almost in all research institutes and industries and even for domestic uses. The analog data measurement requires manual effort to note readings, and there may be a possibility of human error. Such type of systems fails to provide and store precise values of parameters with high accuracy. Analog systems are having drawback of storage/memory. Therefore, there is a requirement of a smart system which is fully automated, accurate and capable enough to monitor all the environmental parameters with utmost possible accuracy. Besides, it should be cost-effective as well as portable too. This paper represents the Wireless Sensor (WS) data communication using DHT11, Arduino, SIM900A GSM module, a mobile device and Liquid Crystal Display (LCD). Experimental setup includes the heating arrangement of DHT11 and transmission of its data using Arduino and SIM900A GSM shield. The mobile device receives the data using Arduino, GSM shield and displays it on LCD too. Heating arrangement is used to heat and cool the temperature sensor to study its characteristics.

Keywords: wireless communication, Arduino, DHT11, LCD, SIM900A GSM module, mobile phone SMS

Procedia PDF Downloads 282

Authors: Hisyam Hidayatullah

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Utilization game on a lesson needs to be done in order to provide proper motoric learning model to improve students' skills. Approach to the game, as one of the models of a motoric learning, is intended to improve student learning outcomes math trigonometry materials generally that prioritize a Memory or rote. The purpose of this study is producting innovation to improve a cognitive abilities of students in the field, to improve student performance, and ultimately to improve student understanding in determining a value of trigonometry in various quadrants, and it apply a approach to the game Domino "Cassava H154M" who is adopted from cassava game and it has made total revised in cassava content. The game is divided into 3 sessions: sine cassava, cosine cassava and cassava tangent. Researchers using action of research method, which consists of several stages such as: planning, implementation, observation, reporting and evaluation. Researchers found that a game approaches can improve student learning outcomes, enhance students' creativity in terms of their motoric learning, and creating a supportive learning environment.

Keywords: cassava "H154M", motoric, value of trigonometry, quadrant

Procedia PDF Downloads 325