Search results for: vector control

Authors: Ahmad A. Kader

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In the principles of Microeconomics course taught during the Fall Semester 2019, 158out of 179 students participated in the completion of two questionnaires and a survey describing their demographic and academic profiles. The two questionnaires include the 29 items of the Rotter Locus of Control Scale and the 52 items of the Schraw andDennisonMetacognitive Awareness Scale. The 52 items consist of 17 items describing knowledge of cognition and 37 items describing the regulation of cognition. The paper is intended to show the combined influence of locus of control, metacognitive knowledge, and metacognitive regulation on student performance. The survey covers variables that have been tested and recognized in economic education literature, which include GPA, gender, age, course level, race, student classification, whether the course was required or elective, employments, whether a high school economic course was taken, and attendance. Regression results show that of the economic education variables, GPA, classification, whether the course was required or elective, and attendance are the only significant variables in their influence on student grade. Of the educational psychology variables, the regression results show that the locus of control variable has a negative and significant effect, while the metacognitive knowledge variable has a positive and significant effect on student grade. Also, the adjusted R square value increased markedly with the addition of the locus of control, metacognitive knowledge, and metacognitive regulation variables to the regression equation. The t test results also show that students who are internally oriented and are high on the metacognitive knowledge scale significantly outperform students who are externally oriented and are low on the metacognitive knowledge scale. The implication of these results for educators is discussed in the paper.

Keywords: locus of control, metacognitive knowledge, metacognitive regulation, student performance, economic education

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Authors: Yuanhao Gao, Pin Lin, Kees Weijer

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In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

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Authors: Sunita Gakkhar, Arti Mishra

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In this paper, a nonlinear host vector model has been proposed and analyzed for the two strain dengue dynamics incorporating ADE effect. The model considers that the asymptomatic infected people are more responsible for secondary infection than that of symptomatic ones and differentiates between them. The existence conditions are obtained for various equilibrium points. Basic reproduction number has been computed and analyzed to explore the effect of secondary infection enhancement parameter on dengue infection. Stability analyses of various equilibrium states have been performed. Numerical simulation has been done for the stability of endemic state.

Keywords: dengue, ade, stability, threshold, asymptomatic, infection

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Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

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In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

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Authors: Rameshwor Pudasaini

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An experiment was conducted to study the effect of pollination quality of rapeseed seed in Chitwan during 2012-2013. The experiment was designed in Randomized Complete Block with four replications and five pollination treatments. The rapeseed plots were caged with mosquito nets at 10% flowering except natural pollination. Two-framed colonies of Apis mellifera L. and Apis cerana F. were introduced separately for pollination, and control plot caged without pollinators. The highest germination percent was observed on Apis cerana F. pollinated plot seeds (90.50% germination) and lowest on control plots (42.00% germination) seeds. Similarly, seed test weight of Apis cerana F. pollinated plots (3.22 gm/ 1000 seed) and Apis mellifera L. pollinated plots (2.93 gm/1000 seed) were and control plots (2.26 gm/ 1000 seed) recorded respectively. However, oil content was recorded highest on pollinated by Apis cerana F. (36.1 %) and lowest on control plots (32.8%). This study clearly indicated pollination increases the seed quality of rapeseed and therefore, management of honeybee is necessary for higher quality of rapeseed under Chitwan condition.

Keywords: apis cerana, apis mellifera, rapeseed pollination, rapeseed quality

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Monish Sengupta, Benjamin Heydecker, Daniel Woodland

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New train control systems rely mainly on Automatic Train Protection (ATP) and Automatic Train Operation (ATO) dynamically to control the speed and hence performance. The ATP and the ATO form the vital element within the CBTC (Communication Based Train Control) and within the ERTMS (European Rail Traffic Management System) system architectures. Reliable and accurate measurement of train location, speed and acceleration are vital to the operation of train control systems. In the past, all CBTC and ERTMS system have deployed a balise or equivalent to correct the uncertainty element of the train location. Typically a CBTC train is allowed to miss only one balise on the track, after which the Automatic Train Protection (ATP) system applies emergency brake to halt the service. This is because the location uncertainty, which grows within the train control system, cannot tolerate missing more than one balise. Balises contribute a significant amount towards wayside maintenance and studies have shown that balises on the track also forms a constraint for future track layout change and change in speed profile.This paper investigates the causes of the location uncertainty that is currently experienced and considers whether it is possible to identify an effective filter to ascertain, in conjunction with appropriate sensors, more accurate speed, distance and location for a CBTC driven train without the need of any external balises. An appropriate sensor fusion algorithm and intelligent sensor selection methodology will be deployed to ascertain the railway location and speed measurement at its highest precision. Similar techniques are already in use in aviation, satellite, submarine and other navigation systems. Developing a model for the speed control and the use of Kalman filter is a key element in this research. This paper will summarize the research undertaken and its significant findings, highlighting the potential for introducing alternative approaches to train positioning that would enable removal of all trackside location correction balises, leading to huge reduction in maintenances and more flexibility in future track design.

Keywords: ERTMS, CBTC, ATP, ATO

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Authors: Hana A. Jameel Alsaeed, Rayyan Ibrahim Khaleel, Hanaa Hussein Mukhlif

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Background: Contamination in Iraq's hospitals is a localized problem with high rates of disease And deaths that mainly affect poor areas. Thus, this study aims to evaluate hospital infections in the city of Mosul and to identify the etiology. So to assess environmental infection prevention in pediatric wards and newborn critical care units in Mosul city. Methods: The present study is a cross-sectional hospital based in Mosul-Iraq between (10th February to 1st April 2022). Purposive sample of 60 nurses from neonatal intensive care units and pediatric wards in three pediatric teaching hospitals in Mosul city; Data was gathered using a questionnaire created by the researchers after reviewing previous studies. Results: The study showed that the majority of the study infection prevention and control policy isn't available in 46.7% of departments, and 45% of hospital workers in Iraq don't know if there is an Iraqi version of it. 70% of the study group had participated in an infection control training program. Conclusions: In the majority of samples 55% of respondents to the study claimed not to be aware of these rules. 60% of the study's participants had never attended a course on infection prevention and control, according to the study's findings on education and training programs. In the neonatal and critical care unit, nurses' skill levels, years of experience, and actual duties varied by wide statistically significant differences.

Keywords: pediatric, infection control, assessment, mosul city

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Authors: Haileyesus Tessema Alemneh, Abiyu Enyew Molla, Oluwole Daniel Makinde

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Introduction: Faba bean is one of the most important grown plants worldwide for humans and animals. Several biotic and abiotic elements have limited the output of faba beans, irrespective of their diverse significance. Many faba bean pathogens have been reported so far, of which the most important yield-limiting disease is chocolate spot disease (Botrytis fabae). The dynamics of disease transmission and decision-making processes for intervention programs for disease control are now better understood through the use of mathematical modeling. Currently, a lot of mathematical modeling researchers are interested in plant disease modeling. Objective: In this paper, a deterministic mathematical model for chocolate spot disease (CSD) on faba bean plant with an optimal control model was developed and analyzed to examine the best strategy for controlling CSD. Methodology: Three control interventions, quarantine (u2), chemical control (u3), and prevention (u1), are employed that would establish the optimal control model. The optimality system, characterization of controls, the adjoint variables, and the Hamiltonian are all generated employing Pontryagin’s maximum principle. A cost-effective approach is chosen from a set of possible integrated strategies using the incremental cost-effectiveness ratio (ICER). The forward-backward sweep iterative approach is used to run numerical simulations. Results: The Hamiltonian, the optimality system, the characterization of the controls, and the adjoint variables were established. The numerical results demonstrate that each integrated strategy can reduce the diseases within the specified period. However, due to limited resources, an integrated strategy of prevention and uprooting was found to be the best cost-effective strategy to combat CSD. Conclusion: Therefore, attention should be given to the integrated cost-effective and environmentally eco-friendly strategy by stakeholders and policymakers to control CSD and disseminate the integrated intervention to the farmers in order to fight the spread of CSD in the Faba bean population and produce the expected yield from the field.

Keywords: CSD, optimal control theory, Pontryagin’s maximum principle, numerical simulation, cost-effectiveness analysis

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Authors: Supawadee Phetkhajone, Wisuwat Songnuan

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Metalaxyl is one of the most common and effective fungicides used to control Phytophthora palmivora infection in durian (Durio zibethinus L.). The efficacy of metalaxyl residue in durian under greenhouse condition was evaluated using bioassay. Durian seedlings were treated with 2 methods of application, spraying, and soil drenching of metalaxyl, at recommended concentration (1000 mg/L). Mock treated samples were treated with 0.1% Tween20 and water for spraying and soil drenching methods, respectively. The experiment was performed in triplicates. Leaves were detached from treated plants at 0, 1, 7, 15, 20, 30, and 60 days after application, inoculated with metalaxyl-resistant and metalaxyl-sensitive isolates of P. palmivora, and incubated in a high humidity chamber for 5 days at room temperature. Metalaxyl efficacy was determined by measuring the lesion size on metalaxyl treated and mock treated samples. The results showed that metalaxyl can control metalaxyl-sensitive isolate of P. palmivora for at least 30 days after application in both methods of application. The metalaxyl-resistant isolate was not inhibited in all treatments. Leaf samples from spraying method showed larger lesions compared to soil drench method. These results demonstrated that metalaxyl applications, especially soil drenching methods showed high efficacy to control metalaxyl-sensitive isolates of P. palmivora, although it cannot control metalaxyl-resistant isolates of P. palmivora in all treatments. These qualitative data indicate that metalaxyl may suitable to control metalaxyl-sensitive isolates of P. palmivora infection.

Keywords: bioassay, degradation, durian, metalaxyl

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Authors: Chen Li-Ching

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The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.

Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

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Authors: Sylwia K. Naliwajko, Justyna Moskwa, Patryk Nowakowski, Renata Markiewicz-Zukowska, Krystyna Gromkowska-Kepka, Anna Puscion-Jakubik, Maria H. Borawska

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Amygdalin is found in many fruit seeds, including apricot, peach, quince, apples, and almonds. Amygdalin (also named vitamin B17), as well as its sources, are commonly used as an alternative therapy or prevention of cancer. The potential activity of amygdalin is related to its enzymatic degradation to the hydrogen cyanide. Hydrogen cyanide is a toxic substance that causes liver and nerves damage, fever, coma or even death. Amygdalin is much better tolerated after intravenous than oral administration. The aim of this study was to examine the influence of amygdalin on glioblastoma multiforme cell lines. Three glioblastoma multiforme cell lines – U87MG, T98, LN18 were incubated (48 h) with amygdalin in concentrations 100, 250, 500, 1000 and 2000 µg/mL. The MTT (Thiazolyl Blue Tetrazolium Bromide) test and DNA binding test by [3H]-thymidine incorporation were used to determine the anti-proliferative activity of amygdalin. The secretion of metalloproteinases (MMP2 and MMP-9) from U87MG cells was estimated by gelatin zymography. The statistical analysis was performed using Statistica v. 13.0 software. The data was presented as a % of control. Amygdalin did not show significant inhibition of viability of all the glioblastoma cells in concentrations 100, 250, 500, 1000 µg/mL. In 2000 µg/mL there were significant differences compared to the control, but inhibition of viability was less than 20% (more than 80% of control). The average viability of U87MG cells was 92,0±4%, T98G: 85,8±3% and LN18: 94,7±2% of the control. There was no dose-response viability, and IC50 value was not recognized. DNA binding in U87MG cells was not inhibited (109,0±3 % of control). After treatment with amygdalin, we observed significantly increased secretion of MMP2 and MMP9 in U87MG cells (130,3±14% and 112,0±5% of control, respectively). Our results suggest that amygdalin has no anticancer activity in glioblastoma cell lines.

Keywords: amygdalin, anticancer, cell line, glioblastoma

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

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Authors: Farah Ali, Tehreem Fayyaz, Musadiq Idris

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The present work was undertaken to investigate effects of various extracts of withania somnifera for anti-diabetic activity in alloxan induced diabetic rabbits. Rabbits were acclimatized for a week to standard laboratory temperature. Animals were fed according to a strict schedule (8 am, 3 pm and 10 pm) with green fodder (Medicago sativa) and tap water ad libitum. Animals were divided into nine groups of six rabbits each in a random manner. Body weights and physical activities of all rabbits were recorded before start of experiments. The animals of group 1 and 2 were given lactose (250 mg/kg, p.o) and Withania somniferaroot powder (100 mg/kg, p.o) respectively daily from day 1-20. Animals of group 3 were given alloxan (100 mg/kg, i.v) as a single dose on day 1. Powdered root of Withania somnifera in the doses of 100, 150, 200 mg/kg and its aqueous and ethanol extracts (equivalent to 200 mg/kg of crude drug) were given to the treated animals (groups 4-8), respectively by oral route for three weeks (day 1-20o.d), along with alloxan (100 mg/kg, i.v) as a single dose on day 1. Group 9 was treated with metformin (200 mg/kg, p.o) daily from day 1-20, along with a single dose of alloxan (100 mg/ kg, i.v) on day 1. Fasting serum glucose concentration in groups 3-9 was increased significantly (p<0.05) on day 3, with a maximum increase (215.3 mg/dl) in animals of toxic control (TC) group (3) on day 21 of the experiment as compared to normal control (NC) group (1). Effects of different doses (100, 150, 200 mg/kg, p.o) of W. somnifera root powder (WS) decreased the fasting serum glucose concentration as compared to toxic control group, with a maximum decrease (88.3 mg/dl) in group 2 (treated control) on day 21 of the experiment. Metformin (200 mg/kg, p.o) (reference control), aqueous extract (AWS) and ethanol extract (EWS) of W. somnifera (equivalent to 100 mg/kg W.somnifera root, p.o) antagonized the effects of alloxan as compared to toxic control group. These results indicate that the W. somnifera possess significant anti–diabetic activity.

Keywords: diabetes, serum, glucose, blood, sugar, rabbits

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Authors: Shadi Kanan, Ghada Shahrour, Barbara Broome, Donna Bernert, Muntaha Alibrahim, Dana Hansen

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Coronary artery disease is responsible for over 7 million deaths a year worldwide. In developing countries, such as Jordan, the incidence of coronary artery disease exceeds that of developed countries. One contributing factor to this disparity is decreased physical activity among the population, for reasons related to specific cultural and religious values. Using the theory of planned behaviour, the purpose of this study was to investigate the intentions of Jordanian patients with coronary artery disease regarding physical activity. A total of 109 patients with coronary artery disease were recruited for this cross-sectional study from King Abdullah University Hospital in Jordan. A 15-item questionnaire based on the theory of planned behaviour was used to assess participants’ attitudes, subjective norms, perceived behavioural control and intentions towards engagement in physical activity. Perceived behavioural control was found to have the strongest significant relationship with participants’ intentions to engage in physical activity. Barriers to physical activity included lack of time, lack of support from family or friends, and feelings of exhaustion. Lifestyle interventions for patients with coronary artery disease should focus on fostering a sense of control over the environment to encourage patients to engage in physical activity.

Keywords: coronary artery disease, perceived behavioural control, subjective norms, theory of planned behaviour

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Authors: Jorge Martínez-Rodríguez, Esther Pérez-Carrillo, Diana Laura Anchondo Álvarez, Julia Lucía Leal Villarreal, Mariana Juárez Dominguez, Luisa Fernanda Torres Hernández, Daniela Salinas Morales, Erick Heredia-Olea

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Maize tortillas are a staple food in Mexico which are mostly made by nixtamalization, which includes the cooking and steeping of maize kernels in alkaline conditions. The cooking step in nixtamalization demands a lot of energy and also generates nejayote, a water pollutant, at the end of the process. The aim of this study was to reduce the cooking time by adding a maize soaking step before nixtamalization while maintaining the quality properties of masa and tortillas. Maize kernels were soaked for 36 h to increase moisture up to 36%. Then, the effect of different cooking times (0, 5, 10, 15, 20, 20, 25, 30, 35, 45-control and 50 minutes) was evaluated on viscosity profile (RVA) of masa to select the treatments with a profile similar or equal to control. All treatments were left steeping overnight and had the same milling conditions. Treatments selected were 20- and 25-min cooking times which had similar values for pasting temperature (79.23°C and 80.23°C), Maximum Viscosity (105.88 Cp and 96.25 Cp) and Final Viscosity (188.5 Cp and 174 Cp) to those of 45 min-control (77.65 °C, 110.08 Cp, and 186.70 Cp, respectively). Afterward, tortillas were produced with the chosen treatments (20 and 25 min) and for control, then were analyzed for texture, damage starch, colorimetry, thickness, and average diameter. Colorimetric analysis of tortillas only showed significant differences for yellow/blue coordinates (b* parameter) at 20 min (0.885), unlike the 25-minute treatment (1.122). Luminosity (L*) and red/green coordinates (a*) showed no significant differences from treatments with respect control (69.912 and 1.072, respectively); however, 25 minutes was closer in both parameters (73.390 and 1.122) than 20 minutes (74.08 and 0.884). For the color difference, (E), the 25 min value (3.84) was the most similar to the control. However, for tortilla thickness and diameter, the 20-minute with 1.57 mm and 13.12 cm respectively was closer to those of the control (1.69 mm and 13.86 cm) although smaller to it. On the other hand, the 25 min treatment tortilla was smaller than both 20 min and control with 1.51 mm thickness and 13.590 cm diameter. According to texture analyses, there was no difference in terms of stretchability (8.803-10.308 gf) and distance for the break (95.70-126.46 mm) among all treatments. However, for the breaking point, all treatments (317.1 gf and 276.5 gf for 25 and 20- min treatment, respectively) were significantly different from the control tortilla (392.2 gf). Results suggest that by adding a soaking step and reducing cooking time by 25 minutes, masa and tortillas obtained had similar functional and textural properties to the traditional nixtamalization process.

Keywords: tortilla, nixtamalization, corn, lime cooking, RVA, colorimetry, texture, masa rheology

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Surachart Koyadun

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Introduction: Plasmodium knowlesi (P. knowlesi) malaria is a zoonotic disease that is classified as type 5 of human malaria. Commonly found in macaques (Macaca fascicularis) and (Macaca nemestrina), P. knowlesi is capable of resulting in both uncomplicated and severe malaria in humans. Situation of P. knowlesi malaria in Phang-Nga province for the past 3 years from 2020 – 2022 revealed no case report in 2020, however, a total of 14 cases had been reported in 2021 - 2022. This research aimed to 1) study the epidemiology of P. knowlesi, 2) examine the clinical manifestations of P. knowlesi patients, 3) analyze the ecology and entomology of P. knowlesi, and 4) analyze the diagnosis and treatment of P. knowlesi. Method: This research was a retrospective descriptive study/case report. The study was conducted in 14 patients with P. knowlesi malaria between 2021 and 2022 in 4 districts of Phang-Nga Province, Thailand including Thapput, Kapong, Takuapa and Khuraburi. Results: The study subjects of P. knowlesi malaria were all males. Most of them were working age groups as farmers and worked in forest or plantation areas. All had no history of blood transfusions. Most of the patients did not use mosquito nets and had a history of camping in the forest prior to the onset of fever. An analysis of all 14 sources of infection unveiled the area is home to macaques, and that area has detected Anopheles mosquito, which is the carrier of the disease. Majority of them got sick in the dry season of Thailand (December-April). The main symptoms brought to the hospital were fever, chills, headache, body aches. Laboratory findings on the first day of diagnosis were as follows: The white blood cell count was found within the normal range. In the proportion of white blood cells, eosinophils were found to be slightly higher than normal. Slight anemia was found on early examination. The platelet count was found to be below normal in all cases. Severely low platelet count (2,000 cells/mm3) was found in severe cases with multiple complications. No patient was found dead but 85.7% of complications were found, with acute renal failure being the most common. Patients with delayed diagnosis and treatment of malaria (inaccurate diagnosis or late access to the hospital) had the highest severity and complications than those who had seen the doctor since the first 3-4 days of illness or the screening of symptoms and risk history by the malaria clinic staff at vector-borne disease control unit. Conclusion and Recommendation: P. knowlesi malaria is an emerging infectious disease transmitted from animals to humans. There are challenges in epidemiology, entomology, ecology for effective surveillance, prevention and control. Early diagnosis and treatment would reduce complications and prevent death.

Keywords: malaria, plasmodium knowlesi, epidemiology, ecology, entomology, diagnosis, treatment

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Authors: Richa Mishra, Sonia Munjal

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In this increasingly hectic and competitive climate, employees are expected to manage the resources available to them to perform their work. However, many are wasting the most precious and scarce resource at their disposal, time, by procrastinating on tasks and thereby costing themselves and their organizations. As timely performance is a requirement of most jobs, procrastination is particularly problematic in the workplace. Evidence suggests that procrastination and poor performance go hand-in-hand, as procrastinators miss more deadlines than non-procrastinators and make more errors and work at a slower speed than non-procrastinators when performing timed tasks. This research is hence an effort to add a little in the sparse knowledge base. It is an effort to throw light on the relationship of Levenson’s multi dimensions of locus of control and also an effort to identify if it is one of the causes and of employees procrastination which have not been explored earlier. The study also explores the effect and relationship of multidimensional locus of control and various levels of stress on procrastination. The results of the research have ascertained that there is significant impact of LOC dimensions on the procrastinating behavior of the employees. One of the major findings to emerge from the current research that managers with powerful others as their LOC dimensions were least procrastinating, contradicts the previous research results that external procrastinate more than internals.

Keywords: Multidimensional Locus of Control, workplace procrastination, employee behaviour, manufacturing industry

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Authors: Jung–Min Yang

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Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: asynchronous sequential machines, corrective control, model matching, input/output control

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Authors: Levan Sabauri

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Audit is an independent inspection of the financial statement of the audited person and expresses the opinion of an auditor on the reliability of this statement. The auditor’s activity (auditor’s service) is realized by auditing organizations, individual auditors in connection to conduction of an audit and rendering of audit accompanying services. The profession of auditor means a high level of responsibility for rendered service. Results of decisions made by information users depend on the quality of the auditor’s conclusion. Owners, investors, creditors, and society rely on the opinion of the auditor under the condition that inspection was conducted with good quality. Therefore, the existence of the well-functioning audit quality control system for the administering of the audit is an important issue. An efficient audit quality control system is a substantial challenge that many countries face worldwide, especially those states where these systems are being formed within the respective reform program. The presented article reflects on the best practices of the leading countries, the assumptions and recommendations for the financial accounting, reporting and audit; current reforms in Georgia are made based on this comparative analysis.

Keywords: audit quality control, audit program, financial statement, perspective analysis

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Authors: Sara Franco Ortega, Alina Goldberg Cavalleri, Nawaporn Onkokesung, Richard Dale, Melissa Brazier-Hicks, Robert Edwards

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Safeners are agrochemicals that enhance the selective chemical control of wild grasses by increasing the ability of the crop to metabolise the herbicide. Although these compounds are widely used, their mode of action is not well understood. It is known that safeners enhance the metabolism of herbicides, by up-regulating the associated detoxification system we have termed the xenome. The xenome proteins involved in herbicide metabolism have been previously divided into four different phases, with cytochrome P450s (CYPs) playing a key role in phase I metabolism by catalysing hydroxylation and dealkylation reactions. Subsequently, glutathione S-transferases (GSTs) and UDP-glucosyltransferases lead to the formation of Phase II conjugates prior to their transport into the vacuole by ABCs transporters (Phase III). Maize (Zea mays), was been treated with different safeners to explore the selective induction of xenome proteins, with a special interest in the regulation of the CYP superfamily. Transcriptome analysis enabled the identification of key safener-inducible CYPs that were then functionally assessed to determine their role in herbicide detoxification. In order to do that, CYP’s were codon optimised, synthesised and inserted into the yeast expression vector pYES3 using in-fusion cloning. CYP’s expressed as recombinant proteins in a strain of yeast engineered to contain the P450 co-enzyme (cytochrome P450 reductase) from Arabidopsis. Microsomes were extracted and treated with herbicides of different chemical classes in the presence of the cofactor NADPH. The reaction products were then analysed by LCMS to identify any herbicide metabolites. The results of these studies will be presented with the key CYPs identified in maize used as the starting point to find orthologs in other crops and weeds to better understand their roles in herbicide selectivity and safening.

Keywords: CYPs, herbicide detoxification, LCMS, RNA-Seq, safeners

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

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Authors: Chuan-Ching Sue, Kai-Chun Chuang

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Peer-to-Peer (P2P) live streaming systems still suffer a challenge when thousands of new peers want to join into the system in a short time, called flash crowd, and most of new peers suffer long start-up delay. Recent studies have proposed a slot-based user access control mechanism, which periodically determines a certain number of new peers to enter the system, and a user batch join mechanism, which divides new peers into several tree structures with fixed tree size. However, the slot-based user access control mechanism is difficult for accurately determining the optimal time slot length, and the user batch join mechanism is hard for determining the optimal tree size. In this paper, we propose a structured access control (SAC) mechanism, which constructs new peers to a multi-layer mesh structure. The SAC mechanism constructs new peer connections layer by layer to replace periodical access control, and determines the number of peers in each layer according to the system’s remaining upload bandwidth and average video rate. Furthermore, we propose an analytical model to represent the behavior of the system growth if the system can utilize the upload bandwidth efficiently. The analytical result has shown the similar trend in system growth as the SAC mechanism. Additionally, the extensive simulation is conducted to show the SAC mechanism outperforms two previously proposed methods in terms of system growth and start-up delay.

Keywords: peer-to-peer, live video streaming system, flash crowd, start-up delay, access control

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Authors: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

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Authors: Kaveh Qaderi Bagajan, Osman Khanahmadi, Ziba Mamaghani Chaharborj, Majid Chenaparchi

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The purpose of this study is to investigate the efficacy of the solution-focused brief therapy on improving the psychological wellbeing of family supervisor woman. This study has been carried out by semi-experimental method and in the form of pre-test, post-test performance on two groups (experimental and control), so that one sample group of 30 individuals was randomly achieved and were randomly divided in two groups of experimental (n=15) and control (n=15). To collect data, Ryff scale psychological wellbeing was used. After conducting pre-test (RSPWB) for two experimental and control groups, Solution-focused brief therapy interference was conducted on the experimental group during five two-hour sessions. Finally, Ryff scale psychological wellbeing was reused for the two groups as post-test and achieved outcomes that were analyzed using covariance. The results indicated that the significant increase of average marks of the experimental group in psychological wellbeing had better function than that of the control group. Finally, solution-focused brief therapy for improving psychological well-being of family supervisor women has a suitable capability and could be used in this way.

Keywords: solution-focused brief therapy, short-term therapy, family supervisor women, psychological well-being

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Authors: Jingwei Du

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The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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