Search results for: capillary effect model

Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Mustafa Tufekci, Caner Guven

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In Automotive Industry, sliding door systems that are also used as body closures, are safety members. Extreme product tests are realized to prevent failures in a design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for the design process. These analyses are used before production of a prototype for validation of design according to customer requirement. In result of this, the substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. The cheaper model can be created by the selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then the optimum combination was achieved.

Keywords: finite element analysis, sliding door mechanism, element type, structural analysis

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Authors: David Chao, John Lai, Alvin Wu, Carl Wang

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For lithium-ion batteries with multiple cell configurations, some use scenarios can cause uneven aging effects to each cell within the battery because of uneven current distribution. Hence the focus of the study is to explore the aging effect(s) on batteries with different construction designs. In order to systematically study the influence of various factors in some key battery configurations, a detailed analysis of three key battery construction factors is conducted. And those key factors are (1) terminal position; (2) cell alignment matrix; and (3) interconnect resistance between cells. In this study, the 2S2P circuitry has been set as a model multi-cell battery to set up different battery samples, and the aging behavior is studied by a cycling test to analyze the current distribution and recoverable capacity. According to the outcome of aging tests, some key findings are: (I) different cells alignment matrices can have an impact on the cycle life of the battery; (II) symmetrical structure has been identified as a critical factor that can influence the battery cycle life, and unbalanced resistance can lead to inconsistent cell aging status; (III) the terminal position has been found to contribute to the uneven current distribution, that can cause an accelerated battery aging effect; and (IV) the internal connection resistance increase can actually result in cycle life increase; however, it is noteworthy that such increase in cycle life is accompanied by a decline in battery performance. In summary, the key findings from the study can help to identify the key aging factor of multi-cell batteries, and it can be useful to effectively improve the accuracy of battery capacity predictions.

Keywords: multiple cells battery, current distribution, battery aging, cell connection

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Authors: Lucky Malise, Hilary Rutto, Tumisang Seodigeng

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Heavy metal contamination in waste water is a very serious issue affecting a lot of industrialized countries due to the health and environmental impact of these heavy metals on human life and the ecosystem. Adsorption using activated carbon is the most promising method for the removal of heavy metals from waste water but commercial activated carbon is expensive which gives rise to the need for alternatively activated carbon derived from cheap precursors, agricultural wastes, or byproducts from other processes. In this study activated bio-carbon derived from the carbonaceous material obtained from the pyrolysis of Marula nut shells was chemically activated and used as an adsorbent for the removal of lead (II) and copper (II) ions from aqueous solution. The surface morphology and chemistry of the adsorbent before and after chemical activation with zinc chloride impregnation were studied using SEM and FTIR analysis respectively and the results obtained indicate that chemical activation with zinc chloride improves the surface morphology of the adsorbent and enhances the intensity of the surface oxygen complexes on the surface of the adsorbent. The effect of process parameters such as adsorbent dosage, pH value of the solution, initial metal concentration, contact time, and temperature on the adsorption of lead (II) and copper (II) ions onto Marula nut activated carbon were investigated, and their optimum operating conditions were also determined. The experimental data was fitted to both the Langmuir and Freundlich isotherm models, and the data fitted best on the Freundlich isotherm model for both metal ions. The adsorption kinetics were also evaluated, and the experimental data fitted the pseudo-first order kinetic model better than the pseudo second-order kinetic model. The adsorption thermodynamics were also studied and the results indicate that the adsorption of lead and copper ions is spontaneous and exothermic in nature, feasible, and also involves a dissociative mechanism in the temperature range of 25-45 °C.

Keywords: adsorption, isotherms, kinetics, marula nut shells activated carbon, thermodynamics

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Authors: Seyedsamad Tahani, Samira Ghorbanpour

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The global warming crisis forced humans to consider their place in the world and the earth's future. In this regard, Electric Vehicles (EVs) are a significant step toward protecting the environment. By identifying factors that influence people's behavior intentions toward using Electric Vehicles (EV), we proposed a theoretical model by extending the Technology Acceptance Model (TAM), including three more concepts, Subjective Norm (SN), Self-Efficacy (SE), and Perceived Behavior Control (PBC). The study was conducted in South Korea, and a random sample was taken at a specific time. In order to collect data, a questionnaire was created in a Google Form and sent via Kakao Talk, a popular social media application used in Korea. There were about 220 participants in this survey. However, 201 surveys were completely done. The findings revealed that all factors in the TAM model and the other added concepts such as subjective norms, self-efficacy and perceived behavior control significantly affect the behavioral intention of using EVs.

Keywords: electric vehicles, behavioral intention, perceived trust, perceived enjoyment, self-efficacy

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Maria Magdy Danial Riad

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The objective of this study was to investigate the effect of different protein sources with different degradability ratios during late gestation of ewes on colostrum composition and its IgG concentration, body weight change of dams, and birth weight of their lambs. Objectives: 35 multiparous native crossbred ewes (BW= 59±2.5kg) were randomly allocated to five dietary treatments (7 ewes / treatment) for 2 months prior to lambing. Methods: Experimental diets were isonitrogenous (12.27% CP) and isocaloric (2.22 Mcal ME/kg DM). In diet I (the control), solvent extract soybeans (SESM 33% RUP of CP), II feed grade urea (FGU 31% RUP), III slow release urea (SRU 31% RUP). As sources of undegradable protein, extruded expeller SBM-EESM 40 (37% RUP) and extruded expeller SBM-EESM 60 (41% RUP) were used in groups IV and V, respectively. Results showed no significant effect on feed intake, crude protein (CP), metabolizable energy (ME), and body condition score (BCS). Ewes fed the 37% RUP diet gained more (p<0.05) weight compared with ewes fed the 31% RUP diet (5.62 vs. 2.5kg). Ewes in EESM 60 had the highest levels of fat, protein, total solid, solid not fat, and immunoglobulin and the lowest in urea N content (P< 0.05) in colostrum during the first 24hrs after lambing. Conclusions: Protein source and RUP levels in ewes’ diets had no significant effect (P< 0.05) on lambs’ birth weight and ewes' blood biochemical parameters. Increasing the RUP content of diet during late gestation resulted in an increase in colostrum constituents and its IgG level but had no effect on ewes’ performance and their lambs’ outcome.

Keywords: colostrum, ewes, lambs output, pregnancy, undegradable protein

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Kiurski S. Jelena, Aksentijević M. Snežana, Oros B. Ivana, Kecić S. Vesna, Djogo Z. Maja

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The paper investigates the effect of light intensity on the formation of two ketones, acetone and methyl ethyl ketone, in working premises of five pad printing departments in Novi Sad, Serbia. Multiple linear regression analysis examined the form of interdependency concentrations of methyl ethyl ketone, acetone and light intensity in five printing presses at seven sampling points, using Statistica software package version 10th. The results show an average stacking variation investigated variable and can be presented by the general regression model: y = b0 + b1xi1 + b2xi2.

Keywords: acetone, methyl ethyl ketone, multiple linear regression analysis, pad printing

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: P. Geetha, R. S. D. Wahida Banu

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The crowning advances in Silicon based electronic technology have dominated the computation world for the past decades. The captivating performance of Si devices lies in sustainable scaling down of the physical dimensions, by that increasing device density and improved performance. But, the fundamental limitations due to physical, technological, economical, and manufacture features restrict further miniaturization of Si based devices. The pit falls are due to scaling down of the devices such as process variation, short channel effects, high leakage currents, and reliability concerns. To fix the above-said problems, it is needed either to follow a new concept that will manage the current hitches or to support the available concept with different materials. The new concept is to design spintronics, quantum computation or two terminal molecular devices. Otherwise, presently used well known three terminal devices can be modified with different materials that suits to address the scaling down difficulties. The first approach will occupy in the far future since it needs considerable effort; the second path is a bright light towards the travel. Modelling paves way to know not only the current-voltage characteristics but also the performance of new devices. So, it is desirable to model a new device of suitable gate control and project the its abilities towards capability of handling high current, high power, high frequency, short delay, and high velocity with excellent electronic and optical properties. Carbon nanotube became a thriving material to replace silicon in nano devices. A well-planned optimized utilization of the carbon material leads to many more advantages. The unique nature of this organic material allows the recent developments in almost all fields of applications from an automobile industry to medical science, especially in electronics field-on which the automation industry depends. More research works were being done in this area. This paper reviews the carbon nanotube field effect transistor with various gate configurations, number of channel element, CNT wall configurations and different modelling techniques.

Keywords: array of channels, carbon nanotube field effect transistor, double gate transistor, gate wrap around transistor, modelling, multi-walled CNT, single-walled CNT

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Authors: N. Meziou-Chebouti, A. Merabet, Y. Chebouti N. Behidj

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This work is a contribution to the knowledge of physicochemical characteristics of mature carob followed by evaluation of the activity, antimicrobial phenolics leaves and green pods of Ceratonia siliqua L. physicochemical study shows that mature carob it has a considerable content of sugar (50.90%), but poor in proteins (7%), fat (8%) and also has a high mineral content. The results obtained from phenolic extracts of leaves and green pods of Ceratonia siliqua L. show a wealth leaf phenolic extract especially flavonoids (0,545 mg EqQ/g) relative to the extract of green pods (0,226 mgEqQ/g). Polyphenols leaves have a slightly inhibitory effect on the growth of strains: Staphylococcus aureus, Escherichia coli, Klebsiella pneumoiae, Streptococcus sp and Sanmonella enteritidis, a strong inhibitory effect on the growth of Pseudomonas strain aerogenosa. Moreover, polyphenols pod have a slightly inhibitory effect on the growth of Streptococcus sp strains, Pseudomonas and aerogenosa Sanmonella enteritidis, a slightly inhibitory effect on the growth of Klebsiella pneumoniae strains, E. coli and Staphylococcus aureus.

Keywords: antimicrobial activity, bacteria, clove, Ceratonia siliqua, polyphenols

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Authors: M. Y. Ismail, Arslan Kiyani

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Narrow bandwidth and high loss performance limits the use of reflectarray antennas in some applications. This article reports on the feasibility of employing strategic reflectarray resonant elements to characterize the reflectivity performance of reflectarrays in X-band frequency range. Strategic reflectarray resonant elements incorporating variable substrate thicknesses ranging from 0.016λ to 0.052λ have been analyzed in terms of reflection loss and reflection phase performance. The effect of substrate thickness has been validated by using waveguide scattering parameter technique. It has been demonstrated that as the substrate thickness is increased from 0.508mm to 1.57mm the measured reflection loss of dipole element decreased from 5.66dB to 3.70dB with increment in 10% bandwidth of 39MHz to 64MHz. Similarly the measured reflection loss of triangular loop element is decreased from 20.25dB to 7.02dB with an increment in 10% bandwidth of 12MHz to 23MHz. The results also show a significant decrease in the slope of reflection phase curve as well. A Figure of Merit (FoM) has also been defined for the comparison of static phase range of resonant elements under consideration. Moreover, a novel numerical model based on analytical equations has been established incorporating the material properties of dielectric substrate and electrical properties of different reflectarray resonant elements to obtain the progressive phase distribution for each individual reflectarray resonant element.

Keywords: numerical model, reflectarray resonant elements, scattering parameter measurements, variable substrate thickness

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Authors: Eda K. Murathan, Gulten Manioglu

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In the building design process, reducing heating and cooling energy consumption according to the climatic region conditions of the building are important issues to be considered in order to provide thermal comfort conditions in the indoor environment. Applying a phase-change material (PCM) on the surface of a building envelope is the new approach for controlling heat transfer through the building envelope during the year. The transparency ratios of the window are also the determinants of the amount of solar radiation gain in the space, thus thermal comfort and energy expenditure. In this study, a simulation-based evaluation was carried out by using Energyplus to determine the effect of coupling PCM and transparency ratio when integrated into the building envelope. A three-storey building, a 30m x 30m sized floor area and 10m x 10m sized courtyard are taken as an example of the courtyard building model, which is frequently seen in the traditional architecture of hot climatic regions. 8 zones (10m x10m sized) with 2 exterior façades oriented in different directions on each floor were obtained. The percentage of transparent components on the PCM applied surface was increased at every step (%30, %40, %50). For every zone differently oriented, annual heating, cooling energy consumptions, and thermal comfort based on the Fanger method were calculated. All calculations are made for the zones of the intermediate floor of the building. The study was carried out for Diyarbakır provinces representing the hot-dry climate region and Antalya representing the hot-humid climate region. The increase in the transparency ratio has led to a decrease in heating energy consumption but an increase in cooling energy consumption for both provinces. When PCM is applied to all developed options, It was observed that heating and cooling energy consumption decreased in both Antalya (6.06%-19.78% and %1-%3.74) and Diyarbakır (2.79%-3.43% and 2.32%-4.64%) respectively. When the considered building is evaluated under passive conditions for the 21st of July, which represents the hottest day of the year, it is seen that the user feels comfortable between 11 pm-10 am with the effect of night ventilation for both provinces.

Keywords: building envelope, heating and cooling energy consumptions, phase change material, transparency ratio

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Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

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Authors: Seolah Lee, Yoohyk Jang, Soyoung Lee, Kon Chu, Sang Kun Lee

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Objective: The International League Against Epilepsy (ILAE) currently suggests a topiramate serum level range of 5-20 mg/L. However, numerous institutions have observed substantial drug response at lower levels. This study aims to investigate the correlation between topiramate serum levels, drug responsiveness, and adverse events to establish a more accurate and tailored therapeutic range. Methods: We retrospectively analyzed topiramate serum samples collected between January 2017 and January 2022 at Seoul National University Hospital. Clinical data, including serum levels, antiseizure regimens, seizure frequency, and adverse events, were collected. Patient responses were categorized as "insufficient" (reduction in seizure frequency <50%) or "sufficient" (reduction ≥ 50%). Within the "sufficient" group, further subdivisions included seizure-free and tolerable seizure subgroups. A population pharmacokinetic model estimated serum levels from spot measurements. ROC curve analysis determined the optimal serum level cut-off. Results: A total of 389 epilepsy patients, with 555 samples, were reviewed, having a mean dose of 178.4±117.9 mg/day and a serum level of 3.9±2.8 mg/L. Out of the samples, only 5.6% (n=31) exhibited insufficient response, with a mean serum level of 3.6±2.5 mg/L. In contrast, 94.4% (n=524) of samples demonstrated sufficient response, with a mean serum level of 4.0±2.8 mg/L. This difference was not statistically significant (p = 0.45). Among the 78 reported adverse events, logistic regression analysis identified a significant association between ataxia and serum concentration (p = 0.04), with an optimal cut-off value of 6.5 mg/L. In the subgroup of patients receiving monotherapy, those in the tolerable seizure group exhibited a significantly higher serum level compared to the seizure-free group (4.8±2.0 mg/L vs 3.4±2.3 mg/L, p < 0.01). Notably, patients in the tolerable seizure group displayed a higher likelihood of progressing into drug-resistant epilepsy during follow-up visits compared to the seizure-free group. Significance: This study proposed an optimal therapeutic concentration for topiramate based on the patient's responsiveness to the drug and the incidence of adverse effects. We employed a population pharmacokinetic model and analyzed topiramate serum levels to recommend a serum level below 6.5 mg/L to mitigate the risk of ataxia-related side effects. Our findings also indicated that topiramate dose elevation is unnecessary for suboptimal responders, as the drug's effectiveness plateaus at minimal doses.

Keywords: topiramate, therapeutic range, low dos, antiseizure effect

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Authors: Mohammed A. Sakr, Tarek M. Khalifa, Walid N. Mansour

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Fiber reinforced polymer (FRP) installation is a very effective way to repair and strengthen structures that have become structurally weak over their life span. This technique attracted the concerning of researchers during the last two decades. This paper presents a simple uniaxial nonlinear finite element model (UNFEM) able to accurately estimate the load-carrying capacity, different failure modes and the interfacial stresses of reinforced concrete (RC) continuous beams flexurally strengthened with externally bonded FRP plates on the upper and lower fibers. Results of the proposed finite element (FE) model are verified by comparing them with experimental measurements available in the literature. The agreement between numerical and experimental results is very good. Considering fracture energy of adhesive is necessary to get a realistic load carrying capacity of continuous RC beams strengthened with FRP. This simple UNFEM is able to help design engineers to model their strengthened structures and solve their problems.

Keywords: continuous beams, debonding, finite element, fibre reinforced polymer

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Authors: N. Kaneva, A. Bojinova, K. Papazova

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Thin ZnO films are deposited on glass substrates via sol–gel method and dip-coating. The films are prepared from zinc acetate dehydrate as a starting reagent. After that the as-prepared ZnO sol is aged for different periods (0, 1, 3, 5, 10, 15, and 30 days). Nanocrystalline thin films are deposited from various sols. The effect ZnO sols aging time on the structural and photocatalytic properties of the films is studied. The films surface is studied by Scanning Electron Microscopy. The effect of the aging time of the starting solution is studied inrespect to photocatalytic degradation of Reactive Black 5 (RB5) by UV-vis spectroscopy. The experiments are conducted upon UV-light illumination and in complete darkness. The variation of the absorption spectra shows the degradation of RB5 dissolved in water, as a result of the reaction acurring on the surface of the films, and promoted by UV irradiation. The initial concentrations of dye (5, 10 and 20 ppm) and the effect of the aging time are varied during the experiments. The results show, that the increasing aging time of starting solution with respect to ZnO generally promotes photocatalytic activity. The thin films obtained from ZnO sol, which is aged 30 days have best photocatalytic degradation of the dye (97,22%) in comparison with the freshly prepared ones (65,92%). The samples and photocatalytic experimental results are reproducible. Nevertheless, all films exhibit a substantial activity in both UV light and darkness, which is promising for the development of new ZnO photocatalysts by sol-gel method.

Keywords: ZnO thin films, sol-gel, photocatalysis, aging time

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Authors: Hasn Perera, Is Almeida, Hnk Perera, Mzf Mohammed, Ade Silva, H. Wijesinghe, Ajal Fernando

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Introduction: Dengue is a major Public Health burden of two clinical entities, Dengue Fever & Dengue Haemorrhagic Fever (DHF). The vast majority of dengue deaths occur in DHF patients, where the diagnosis hinges on the presence of fluid leakage. Limited Ultrasound Scans (USS) of chest and abdomen are used widely at Centre for Clinical Management of Dengue & Dengue Haemorrhagic Fever (CCMDDHF), as the primary method for detecting fluid leaking in DHF. This study analyses the relationship between haematological and USS findings at the onset of leaking and to further determine the usefulness of ultrasound in diagnosing DHF. Methods: A prospective analysis of 80 serologically confirmed dengue patients initially admitted to a General Medical and Paediatric wards who were subsequently transferred to the CCMDDHF from March to September 2017 were analysed. In addition to repeated blood counts and capillary haematocrits’, serial USS were done to detect the onset fluid leaking by three competent and experienced doctors at CCMDDHF. Results: 80 patients (male: female: 38:42) with a mean age of 20 years (SD ±16.8, range 3-74) were evaluated. Dropping of platelet counts below 100,000 and haematocrit rise towards 20% started 4±1.3 day of fever with a mean platelet value of 69x103(range17-98x103). Gallbladder wall thickening was the commonest (98.7%) USS finding followed by fluid in hepato-renal pouch (95%), pelvic fluid (58.7%), right-sided pleural effusion (35%), bilateral effusions (7.5%). USS evidence of plasma leakage was detected in 11.25 %( n=9) of DHF cases from 1 day before significant haematocrit rise was noted. 35 (43.7%) patients with lowering platelets and haematocrit rise showed no objective evidence of plasma leaking on ultrasound scan. Conclusion: This outbreak underscores the importance of USS as a useful, sensitive and cost-effective tool for early diagnosis of suspected DHF cases, facilitating the tracking of progress of leaking and management of epidemics.

Keywords: dengue, ultrasound, plasma leaking, South Asia

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Authors: Maryam Hoorzad, Narges Shokry, Mandan Momeni

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According to importance of socialization in effectiveness of organizations and on the other hand assessing the impact of individual differences on socialization tactics by measuring employees satisfaction, can be assessed for each of the personality types which socialization tactics is the more effective. The aim of this paper is to investigate how organizational socialization tactics affect job satisfaction of employees according to personality types. A survey was conducted using a measurement tool based on Van Maanen and Schein’s theory on organizational socialization tactics and Myers Briggs’ measurement tools of personality types. The respondents were employees with more than 3 years backward in Tehran University of Medical Science. Data collection was performed using both library and field, the data collection instrument was questionnaires and data were analysed using the Spss and Lisrel programs. It was found that investiture and serial tactics has a significant effect on employees satisfaction, any increase in investiture and serial tactics led to increase in job satisfaction and any increase in divestiture and disjunctive tactics led to reduction of job satisfaction. Investiture tactic has the most effect on employees satisfaction. Also based on the results, personality types affect the relationship between socialization tactics and job satisfaction. In the ESFJ personality type the effect of investiture tactic on employee satisfaction is the most.

Keywords: organizational socialization, organizational socialization tactics, personality types, job satisfaction

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Authors: Behrang Dadfar, Hossein Bidhendi, Jimmy Susetyo, John Paul Abbatangelo

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Finding structural demand under various conditions that a structure may experience during its service life is an important step towards structural life-cycle analysis. In this paper, structural demand for the precast concrete tunnel lining (PCTL) segments of Toronto’s 60-year-old subway tunnels is investigated. Numerical modelling was conducted using FLAC3D, a finite difference-based software capable of simulating ground-structure interaction and ground material’s flow in three dimensions. The specific structural details of the segmental tunnel lining, such as the convex shape of the PCTL segments at radial joints and the PCTL segment pockets, were considered in the numerical modelling. Also, the model was developed in a way to accommodate the flexibility required for the simulation of various deterioration scenarios, shapes, and patterns that have been observed over more than 20 years. The soil behavior was simulated by using plastic-hardening constitutive model of FLAC3D. The effect of the depth of the tunnel, the coefficient of lateral earth pressure as well as the patterns of deterioration of the segments were studied. The structural capacity under various deterioration patterns and the existing loading conditions was evaluated using axial-flexural interaction curves that were developed for each deterioration pattern. The results were used to provide recommendations for the next phase of tunnel lining rehabilitation program.

Keywords: precast concrete tunnel lining, ground-structure interaction, numerical modelling, deterioration, tunnels

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Authors: Chongyang Ye, Rong Liu

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Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction

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Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn

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In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.

Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter

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Authors: Settapong Malisuwan, Jesada Sivaraks, Peerawat Promkladpanao, Nattakit Suriyakrai, Navneet Madan

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In this paper, a compact microstrip patch antenna is designed for mobile LTE applications by applying the frequency-dependent Smith-Chart (FDSC) model. The FDSC model is adopted in this research to reduce the error on the frequency-dependent characteristics. The Ansoft HFSS and various techniques is applied to meet frequency and size requirements. The proposed method within this research is suitable for use in computer-aided microstrip antenna design and RF integrated circuit (RFIC) design.

Keywords: frequency-dependent, smith-chart, microstrip, antenna, LTE, CAD

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Authors: Sajjad Baghernezhad

Abstract:

Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: T. Hojageldiyev, Y. Bolmammedov, S. Gurbanaliyev

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It is known that drugs used in the treatment of tuberculosis show toxic effect to organism especially to liver besides its therapeutic effect. Because of ineffectiveness of drugs used in the treatment regimen of tuberculosis against multidrug resistance (MDR) and extensively drug-resistance (XDR) tuberculosis requires the development of new treatment methods and new, novel drugs. Considering the usage of Artemisia absinthium in traditional medicine in treatment of wounds which suggests its antibacterial activity it seems that, also it may have significant antimycobacterial activity. The objective of present study was to evaluate antibacterial activity of ethanolic extract of A. absinthium against M. tuberculosis. In this study, the effect of ethanolic extract of A. absinthium was tested against tuberculosis and pharmaco-toxicological properties evaluated on laboratory animals. The 20%, 40%, 70% and 96% ethanolic extracts of A. absinthium prepared then its bacteriostatic and bactericidal activities were evaluated by validated methods. Data were analyzed by GraphPad Prism 7.0 at the level P < 0.05. Results showed that ethanolic extracts of A. absinthium show no toxicological properties with having high LD50. All concentrations of extract show high bacteriostatic activity on M. tuberculosis. 96% ethanolic extract has highest bactericidal effect among other concentrations. By conducting further studies, as a result of our study, antimycobacterial drug can be prepared from A. absinthium.

Keywords: Artemisia absinthium, antimycobacterial, ethanolic extract, Mycobacteria tuberculosis

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Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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