Search results for: modified simplex algorithm

Authors: Young-Tae Lee, Hee-Chang Lim

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This paper presents the performance characteristics of Darrieus-type vertical axis wind turbine (VAWT) with NACA airfoil blades. The performance of Darrieus-type VAWT can be characterized by torque and power. There are various parameters affecting the performance such as chord length, helical angle, pitch angle and rotor diameter. To estimate the optimum shape of Darrieustype wind turbine in accordance with various design parameters, we examined aerodynamic characteristics and separated flow occurring in the vicinity of blade, interaction between flow and blade, and torque and power characteristics derived from it. For flow analysis, flow variations were investigated based on the unsteady RANS (Reynolds-averaged Navier-Stokes) equation. Sliding mesh algorithm was employed in order to consider rotational effect of blade. To obtain more realistic results we conducted experiment and numerical analysis at the same time for three-dimensional shape. In addition, several parameters (chord length, rotor diameter, pitch angle, and helical angle) were considered to find out optimum shape design and characteristics of interaction with ambient flow. Since the NACA airfoil used in this study showed significant changes in magnitude of lift and drag depending on an angle of attack, the rotor with low drag, long cord length and short diameter shows high power coefficient in low tip speed ratio (TSR) range. On the contrary, in high TSR range, drag becomes high. Hence, the short-chord and long-diameter rotor produces high power coefficient. When a pitch angle at which airfoil directs toward inside equals to -2° and helical angle equals to 0°, Darrieus-type VAWT generates maximum power.

Keywords: darrieus wind turbine, VAWT, NACA airfoil, performance

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Ana Londral, Burcu Demiray, Marcus Cheetham

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Speech recording is a methodology used in many different studies related to cognitive and behaviour research. Modern advances in digital equipment brought the possibility of continuously recording hours of speech in naturalistic environments and building rich sets of sound files. Speech analysis can then extract from these files multiple features for different scopes of research in Language and Communication. However, tools for analysing a large set of sound files and automatically extract relevant features from these files are often inaccessible to researchers that are not familiar with programming languages. Manual analysis is a common alternative, with a high time and efficiency cost. In the analysis of long sound files, the first step is the voice segmentation, i.e. to detect and label segments containing speech. We present a comprehensive methodology aiming to support researchers on voice segmentation, as the first step for data analysis of a big set of sound files. Praat, an open source software, is suggested as a tool to run a voice detection algorithm, label segments and files and extract other quantitative features on a structure of folders containing a large number of sound files. We present the validation of our methodology with a set of 5000 sound files that were collected in the daily life of a group of voluntary participants with age over 65. A smartphone device was used to collect sound using the Electronically Activated Recorder (EAR): an app programmed to record 30-second sound samples that were randomly distributed throughout the day. Results demonstrated that automatic segmentation and labelling of files containing speech segments was 74% faster when compared to a manual analysis performed with two independent coders. Furthermore, the methodology presented allows manual adjustments of voiced segments with visualisation of the sound signal and the automatic extraction of quantitative information on speech. In conclusion, we propose a comprehensive methodology for voice segmentation, to be used by researchers that have to work with large sets of sound files and are not familiar with programming tools.

Keywords: automatic speech analysis, behavior analysis, naturalistic environments, voice segmentation

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Authors: Eva Masson, Andrea Kübler

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Anxiety disorders (AD) are the most prevalent psychological disorders. However, far from most affected individuals are diagnosed and receive treatment. This gap is probably due to the diagnosis criteria, relying on symptoms (according to the DSM-5 definition) with no objective biomarker. Approach-avoidance conflict tasks are one common approach to simulate such disorders in a lab setting, with most of the paradigms focusing on the relationships between behavior and neurophysiology. Approach-avoidance conflict tasks typically place participants in a situation where they have to make a decision that leads to both positive and negative outcomes, thereby sending conflicting signals that trigger the Behavioral Inhibition System (BIS). Furthermore, behavioral validation of such paradigms adds credibility to the tasks – with overt conflict behavior, it is safer to assume that the task actually induced a conflict. Some of those tasks have linked asymmetrical frontal brain activity to induced conflicts and the BIS. However, there is currently no consensus for the direction of the frontal activation. The authors present here a modified version of the T-Maze paradigm, a motivational conflict desktop task, in which behavior is recorded simultaneously to the recording of high-density EEG (HD-EEG). Methods: In this within-subject design, HD-EEG and behavior of 35 healthy participants was recorded. EEG data was collected with a 128 channels sponge-based system. The motivational conflict desktop task consisted of three blocks of repeated trials. Each block was designed to record a slightly different behavioral pattern, to increase the chances of eliciting conflict. This variety of behavioral patterns was however similar enough to allow comparison of the number of trials categorized as ‘overt conflict’ between the blocks. Results: Overt conflict behavior was exhibited in all blocks, but always for under 10% of the trials, in average, in each block. However, changing the order of the paradigms successfully introduced a ‘reset’ of the conflict process, therefore providing more trials for analysis. As for the EEG correlates, the authors expect a different pattern for trials categorized as conflict, compared to the other ones. More specifically, we expect an elevated alpha frequency power in the left frontal electrodes at around 200ms post-cueing, compared to the right one (relative higher right frontal activity), followed by an inversion around 600ms later. Conclusion: With this comprehensive approach of a psychological mechanism, new evidence would be brought to the frontal asymmetry discussion, and its relationship with the BIS. Furthermore, with the present task focusing on a very particular type of motivational approach-avoidance conflict, it would open the door to further variations of the paradigm to introduce different kinds of conflicts involved in AD. Even though its application as a potential biomarker sounds difficult, because of the individual reliability of both the task and peak frequency in the alpha range, we hope to open the discussion for task robustness for neuromodulation and neurofeedback future applications.

Keywords: anxiety, approach-avoidance conflict, behavioral inhibition system, EEG

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Authors: Ling Liyun

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In the field of contemporary architecture, complex forms of architectural works continue to emerge in the world, along with some new terminology emerged: digital architecture, parametric design, algorithm generation, building information modeling, CNC construction and so on. Architects gradually mastered the new skills of mathematical logic in the form of exploration, virtual simulation, and the entire design and coordination in the construction process. Digital construction technology has a greater degree in controlling construction, and ensure its accuracy, creating a series of new construction techniques. As a result, the use of digital technology is an improvement and expansion of the practice of digital architecture design revolution. We worked by reading and analyzing information about the digital architecture development process, a large number of cases, as well as architectural design and construction as a whole process. Thus current developments were introduced and discussed in our paper, such as architectural discourse, design theory, digital design models and techniques, material selecting, as well as artificial intelligence space design. Our paper also pays attention to the representative three cases of digital design and construction experiment at great length in detail to expound high-informatization, high-reliability intelligence, and high-technique in constructing a humane space to cope with the rapid development of urbanization. We concluded that the opportunities and challenges of the shift existed in architectural paradigms, such as the cooperation methods, theories, models, technologies and techniques which were currently employed in digital design research and digital praxis. We also find out that the innovative use of space can gradually change the way people learn, talk, and control information. The past two decades, digital technology radically breaks the technology constraints of industrial technical products, digests the publicity on a particular architectural style (era doctrine). People should not adapt to the machine, but in turn, it’s better to make the machine work for users.

Keywords: artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

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Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to the exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes the multi-criteria nature of the problem and how decision-makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of a significant degree of ambiguity and indeterminacy observed in the decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies the Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method for a real problem of academic personnel selection, having as the main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherent ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: multi-criteria decision making methods, analytical hierarchy process, delphi method, personnel recruitment, neutrosophic set theory

Procedia PDF Downloads 118

Authors: Zongyan Yang, Gagan K. Jena, Sankar B. Karanam, Noora M. A. Hokal

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Jumeirah First beach, a segment of coastline of length 1.5 km, is one of the popular public beaches in Dubai, UAE. The stability of the beach has been affected by several coastal developmental projects, including The World, Island 2 and La Mer. A comprehensive stabilization scheme comprising of two composite groynes (of lengths 90 m and 125m), modification to the northern breakwater of Jumeirah Fishing Harbour and beach re-nourishment was implemented by Dubai Municipality in 2012. However, the performance of the implemented stabilization scheme has been compromised by La Mer project (built in 2016), which modified the wave climate at the Jumeirah First beach. The objective of the coastal modelling studies is to establish design basis for further beach stabilization scheme(s). Comprehensive coastal modelling studies had been conducted to establish the nearshore wave climate, equilibrium beach orientations and stable beach plan forms. Based on the outcomes of the modeling studies, recommendation had been made to extend the composite groynes to stabilize the Jumeirah First beach. Wave transformation was performed following an interpolation approach with wave transformation matrixes derived from simulations of a possible range of wave conditions in the region. The Dubai coastal wave model is developed with MIKE21 SW. The offshore wave conditions were determined from PERGOS wave data at 4 offshore locations with consideration of the spatial variation. The lateral boundary conditions corresponding to the offshore conditions, at Dubai/Abu Dhabi and Dubai Sharjah borders, were derived with application of LitDrift 1D wave transformation module. The Dubai coastal wave model was calibrated with wave records at monitoring stations operated by Dubai Municipality. The wave transformation matrix approach was validated with nearshore wave measurement at a Dubai Municipality monitoring station in the vicinity of the Jumeirah First beach. One typical year wave time series was transformed to 7 locations in front of the beach to count for the variation of wave conditions which are affected by adjacent and offshore developments. Equilibrium beach orientations were estimated with application of LitDrift by finding the beach orientations with null annual littoral transport at the 7 selected locations. The littoral transport calculation results were compared with beach erosion/accretion quantities estimated from the beach monitoring program (twice a year including bathymetric and topographical surveys). An innovative integral method was developed to outline the stable beach plan forms from the estimated equilibrium beach orientations, with predetermined minimum beach width. The optimal lengths for the composite groyne extensions were recommended based on the stable beach plan forms.

Keywords: composite groyne, equilibrium beach orientation, stable beach plan form, wave transformation matrix

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: M. Soleimani, D. Cree, C. Chafe, L. Bates

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The accidental release of petroleum products into the environment could have harmful consequences to our ecosystem. Different techniques such as mechanical separation, membrane filtration, incineration, treatment processes using enzymes and dispersants, bioremediation, and sorption process using sorbents have been applied for oil spill remediation. Most of the techniques investigated are too costly or do not have high enough efficiency. This study was conducted to determine the sorption performance of hemp byproducts (cellulosic materials) in terms of sorption capacity and kinetics for hydrophobic and hydrophilic fluids. In this study, heavy oil, light oil, diesel fuel, and water/water vapor were used as sorbate fluids. Hemp stalk in different forms, including loose material (hammer milled (HM) and shredded (Sh) with low bulk densities) and densified forms (pellet form (P) and crumbled pellets (CP)) with high bulk densities, were used as sorbents. The sorption/retention tests were conducted according to ASTM 726 standard. For a quick-purpose application of the sorbents, the sorption tests were conducted for 15 min, and for an ideal sorption capacity of the materials, the tests were carried out for 24 h. During the test, the sorbent material was exposed to the fluid by immersion, followed by filtration through a stainless-steel wire screen. Water vapor adsorption was carried out in a controlled environment chamber with the capability of controlling relative humidity (RH) and temperature. To determine the kinetics of sorption for each fluid and sorbent, the retention capacity also was determined intervalley for up to 24 h. To analyze the kinetics of sorption, pseudo-first-order, pseudo-second order and intraparticle diffusion models were employed with the objective of minimal deviation of the experimental results from the models. The results indicated that HM and Sh materials had the highest sorption capacity for the hydrophobic fluids with approximately 6 times compared to P and CP materials. For example, average retention values of heavy oil on HM and Sh was 560% and 470% of the mass of the sorbents, respectively. Whereas, the retention of heavy oil on P and CP was up to 85% of the mass of the sorbents. This lower sorption capacity for P and CP can be due to the less exposed surface area of these materials and compacted voids or capillary tubes in the structures. For water uptake application, HM and Sh resulted in at least 40% higher sorption capacity compared to those obtained for P and CP. On average, the performance of sorbate uptake from high to low was as follows: water, heavy oil, light oil, diesel fuel. The kinetic analysis indicated that the second-pseudo order model can describe the sorption process of the oil and diesel better than other models. However, the kinetics of water absorption was better described by the pseudo-first-order model. Acetylation of HM materials could improve its oil and diesel sorption to some extent. Water vapor adsorption of hemp fiber was a function of temperature and RH, and among the models studied, the modified Oswin model was the best model in describing this phenomenon.

Keywords: environment, fiber, petroleum, sorption

Procedia PDF Downloads 124

Authors: Tatiana L. Avalos-Rendon, Elias A. Pasten Chelala, Carlos J. Mendoza EScobedo, Ignacio A. Figueroa, Victor H. Lara, Luis M. Palacios-Romero

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The cement industry is facing cost increments in energy supply, requirements for reduction of CO₂, and insufficient supply of raw materials of good quality. According to all these environmental issues, cement industry must change its consumption patterns and reduce CO₂ emissions to the atmosphere. This can be achieved by generating environmental consciousness, which encourages the use of industrial by-products and/or recycling for the production of cement, as well as alternate, environment-friendly methods of synthesis which reduce CO₂. Calcination is the conventional method for the obtainment of Portland cement clinker. This method consists of grinding and mixing of raw materials (limestone, clay, etc.) in an adequate dosage. Resulting mix has a clinkerization temperature of 1450 °C so that the formation of the main component occur: alite (Ca₃SiO₅, C₃S). Considering that the energy required to produce C₃S is 1810 kJ kg -1, calcination method for the obtainment of clinker represents two major disadvantages: long thermal treatment and elevated temperatures of synthesis, both of which cause high emissions of carbon dioxide (CO₂) to the atmosphere. Belite Portland clinker is characterized by having a low content of calcium oxide (CaO), causing the presence of alite to diminish and favoring the formation of belite (β-Ca₂SiO₄, C₂S), so production of clinker requires a reduced energy consumption (1350 kJ kg-1), releasing less CO₂ to the atmosphere. Conventionally, β-Ca₂SiO₄ is synthetized by the calcination of calcium carbonate (CaCO₃) and silicon dioxide (SiO₂) through the reaction in solid state at temperatures greater than 1300 °C. Resulting belite shows low hydraulic reactivity. Therefore, this study concerns a new simple modified combustion method for the synthesis of two belite cements at low temperatures (1000 °C). Silica fume, as subproduct of metallurgic industry and commercial natural zeolite were utilized as raw materials. These are considered low-cost materials and were utilized with no additional purification process. Belite cements properties were characterized by XRD, SEM, EDS and BET techniques. Hydration capacity of belite cements was calculated while the mechanical strength was determined in ordinary Portland cement specimens (PC) with a 10% partial replacement of the belite cements obtained. Results showed belite cements presented relatively high surface áreas, at early ages mechanical strengths similar to those of alite cement and comparable to strengths of belite cements obtained by different synthesis methods. Cements obtained in this work present good hydraulic reactivity properties.

Keywords: belite, silica fume, zeolite, hydraulic reactivity

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Authors: Amèdédjihundé H. J. Hounnou, Frédéric Dubas, François-Xavier Fifatin, Didier Chamagne, Antoine Vianou

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This paper presents the techno-economic evaluation of run-of-river small-hydropower plants. In this regard, a multi-objective optimization procedure is proposed for the optimal sizing of the hydropower plants, and NSGAII is employed as the optimization algorithm. Annual generated energy and investment cost are considered as the objective functions, and number of generator units (n) and nominal turbine flow rate (Q_T) constitute the decision variables. Site of Yeripao in Benin is considered as the case study. We have categorized the river of this site using its environmental characteristics: gross head, and first quartile, median, third quartile and mean of flow. Effects of each decision variable on the objective functions are analysed. The results gave Pareto Front which represents the trade-offs between annual energy generation and the investment cost of hydropower plants, as well as the recommended optimal solutions. We noted that with the increase of the annual energy generation, the investment cost rises. Thus, maximizing energy generation is contradictory with minimizing the investment cost. Moreover, we have noted that the solutions of Pareto Front are grouped according to the number of generator units (n). The results also illustrate that the costs per kWh are grouped according to the n and rise with the increase of the nominal turbine flow rate. The lowest investment costs per kWh are obtained for n equal to one and are between 0.065 and 0.180 €/kWh. Following the values of n (equal to 1, 2, 3 or 4), the investment cost and investment cost per kWh increase almost linearly with increasing the nominal turbine flowrate while annual generated. Energy increases logarithmically with increasing of the nominal turbine flowrate. This study made for the Yeripao river can be applied to other rivers with their own characteristics.

Keywords: hydropower plant, investment cost, multi-objective optimization, number of generator units

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Authors: Chung-Yuan Wang, Kai-Chun Lee, Min-Hung Wang, Yu-Ren Chen, Hung-Sheng Lin, Sen-Shan Fan

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Taiwan National Health Insurance (NHI) was launched in 1995. It is an important social welfare policy in Taiwan. Regardless of the diversified social and economic status, universal coverage of NHI was assured. In order to regain better self-care performance, stroke people received in-patient and out-patient rehabilitation. Though NHI limited the rehabilitation frequency to one per day, the cost of rehabilitation still increased rapidly. Through the intensive rehabilitation during the post-stroke rehabilitation golden period, stroke patients might decrease their disability and shorten the rehabilitation period. Therefore, the aim of this study was to investigate the effect of intensive post-acute stroke rehabilitation in hospital under per diem payment. This study was started from 2014/03/01. The stroke patients who were admitted to our hospital or medical center were indicated to the study. The neurologists would check his modified Rankin Scale (mRS). Only patients with their mRS score between 2 and 4 were included to the study. Patients with unclear consciousness, unstable medical condition, unclear stroke onset date and no willing for 3 weeks in-patient intensive rehabilitation were excluded. After the physiatrist’s systemic evaluation, the subjects received intensive rehabilitation programs. The frequency of rehabilitation was thrice per day. Physical therapy, occupational therapy and speech/swallowing therapy were included in the programs for the needs of the stroke patients. Activity daily life performance (Barthel Index) and functional balance ability (Berg Balance Scale) were used to measure the training effect. During 3/1 to 5/31, thirteen subjects (five male and eight female) were included. Seven subjects were aged below 60. Three subjects were aged over 70. Most of the subjects (seven subjects) received intensive post-stroke rehabilitation for three weeks. Three subjects drop out from the programs and went back home respectively after receiving only 7, 10, and 13 days rehabilitation. Among these 13 subjects, nine of them got improvement in activity daily life performance (Barthel Index score). Ten of them got improvement in functional balance ability (Berg Balance Scale). The intensive post-acute stroke rehabilitation did help stroke patients promote their health in our study. Not only their functional performance improved, but also their self-confidence improved. Furthermore, their family also got better health status. Stroke rehabilitation under per diem payment was noted in long-term care institution in developed countries. Over 95% populations in Taiwan were supported under the Taiwan's National Health Insurance system, but there was no national long-term care insurance system. Most of the stroke patients in Taiwan live with his family and continue their rehabilitation programs from out-patient department. This pilot study revealed the effect of intensive post-acute stroke rehabilitation in hospital under per diem payment. The number of the subjects and the study period were limited. Thus, further study will be needed.

Keywords: rehabilitation, post-acute stroke, per diem payment, NHI

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Authors: Anu S. Nair, V. Anantha Subramanian

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This paper presents a surface development and fairing technique combining the features of a modern computer-aided design tool namely the Non-Uniform Rational Basis Spline (NURBS) with an algorithm to obtain a rapidly faired hull form. Some of the older series based designs give sectional area distribution such as in the Wageningen-Lap Series. Others such as the FORMDATA give more comprehensive offset data points. Nevertheless, this basic data still requires fairing to obtain an acceptable faired hull form. This method uses the input of sectional area distribution as an example and arrives at the faired form. Characteristic section shapes define any general ship hull form in the entrance, parallel mid-body and run regions. The method defines a minimum of control points at each section and using the Golden search method or the bisection method; the section shape converges to the one with the prescribed sectional area with a minimized error in the area fit. The section shapes combine into evolving the faired surface by NURBS and typically takes 20 iterations. The advantage of the method is that it is fast, robust and evolves the faired hull form through minimal iterations. The curvature criterion check for the hull lines shows the evolution of the smooth faired surface. The method is applicable to hull form from any parent series and the evolved form can be evaluated for hydrodynamic performance as is done in more modern design practice. The method can handle complex shape such as that of the bulbous bow. Surface patches developed fit together at their common boundaries with curvature continuity and fairness check. The development is coded in MATLAB and the example illustrates the development of the method. The most important advantage is quick time, the rapid iterative fairing of the hull form.

Keywords: computer-aided design, methodical series, NURBS, ship design

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Authors: Wajeeha Zahid, Shafquat Rozi, Farhan Raza, Masood Kadir

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Background: Dental caries affects the overall health and well-being of children. Findings from various international studies regarding the association of dental caries with asthma are inconsistent. With the increasing burden of caries and childhood asthma, it becomes imperative for an underdeveloped country like Pakistan where resources are limited to identify whether there is a relationship between the two. This study aims to identify an association between dental caries and asthma. Methods: A cross-sectional study was conducted on 544 children aged 12-15 years recruited from five private schools in Karachi. Information on asthma was collected through the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. The questionnaire addressed questions regarding child’s demographics, physician diagnoses of asthma, type of medication administered, family history of asthma and allergies, dietary habits and oral hygiene behavior. Dental caries was assessed using DMFT Index (Decayed, Missing, Filled teeth) index The data was analyzed using Cox proportional Hazard algorithm and crude and adjusted prevalence ratios with 95% CI were reported. Results: This study comprises of 306 (56.3%) boys and 238 (43.8%) girls. The mean age of children was 13.2 ± (0.05) years. The total number of children with carious teeth (DMFT > 0) were 166/544 (30.5%), and the decayed component contributed largely (22.8%) to the DMFT score. The prevalence of physician’s diagnosed asthma was 13%. This study identified almost 7% asthmatic children using the internationally validated International Study of Asthma and Allergies in Childhood (ISAAC) tool and 8 children with childhood asthma were identified by parent interviews. Overall prevalence of asthma was 109/544 (20%). The prevalence of caries in asthmatic children was 28.4% as compared to 31% among non-asthmatic children. The adjusted prevalence ratio of dental caries in asthmatic children was 0.8 (95% CI 0.59-1.29). After adjusting for carious food intake, age, oral hygiene index and dentist visit, the association between asthma and dental caries turned out to be non-significant. Conclusion: There was no association between asthma and dental caries among children who participated in this study.

Keywords: asthma, caries, children, school-based

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Authors: Ibrahim Khan, Waqas Khalid

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The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.

Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning

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Authors: Katarzyna Bialik-Wąs, Klaudia Pluta, Dagmara Malina, Małgorzata Miastkowska

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In recent years, biocompatible hydrogels have been used more and more in medical applications, especially as modern dressings and drug delivery systems. The main goal of this research was the characteristics of bio-hybrid hydrogel materials incorporated with the nanocarrier-drug system, which enable the release in a gradual and prolonged manner, up to 7 days. Therefore, the use of such a combination will provide protection against mechanical damage and adequate hydration. The proposed bio-hybrid hydrogels are characterized by: transparency, biocompatibility, good mechanical strength, and the dual release system, which allows for gradual delivery of the active substance, even up to 7 days. Bio-hybrid hydrogels based on sodium alginate (SA), poly(vinyl alcohol) (PVA), glycerine, and Aloe vera solution (AV) were obtained through the chemical crosslinking method using poly(ethylene glycol) diacrylate as a crosslinking agent. Additionally, a nanocarrier-drug system was incorporated into SA/PVA/AV hydrogel matrix. Here, studies were focused on the release profiles of active substances from bio-hybrid hydrogels using the USP4 method (DZF II Flow-Through System, Erweka GmbH, Langen, Germany). The equipment incorporated seven in-line flow-through diffusion cells. The membrane was placed over support with an orifice of 1,5 cm in diameter (diffusional area, 1.766 cm²). All the cells were placed in a cell warmer connected with the Erweka heater DH 2000i and the Erweka piston pump HKP 720. The piston pump transports the receptor fluid via seven channels to the flow-through cells and automatically adapts the setting of the flow rate. All volumes were measured by gravimetric methods by filling the chambers with Milli-Q water and assuming a density of 1 g/ml. All the determinations were made in triplicate for each cell. The release study of the model active substance was carried out using a regenerated cellulose membrane Spectra/Por®Dialysis Membrane MWCO 6-8,000 Carl Roth® Company. These tests were conducted in buffer solutions – PBS at pH 7.4. A flow rate of receptor fluid of about 4 ml /1 min was selected. The experiments were carried out for 7 days at a temperature of 37°C. The released concentration of the model drug in the receptor solution was analyzed using UV-Vis spectroscopy (Perkin Elmer Company). Additionally, the following properties of the modified materials were studied: physicochemical, structural (FT-IR analysis), morphological (SEM analysis). Finally, the cytotoxicity tests using in vitro method were conducted. The obtained results exhibited that the dual release system allows for the gradual and prolonged delivery of the active substances, even up to 7 days.

Keywords: wound dressings, SA/PVA hydrogels, nanocarrier-drug system, USP4 method

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Vidhya Venugopal, Rekha S.

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Introduction: Climate change and the growing frequency of higher average temperatures and heat waves have detrimental health effects, especially for certain vulnerable groups with limited socioeconomic status (SES) or physiological capacity to adapt to or endure high temperatures. Little research has been conducted on the effects of heat stress on pregnant women and fetuses in tropical regions such as India. Very high ambient temperatures may worsen Adverse Pregnancy Outcomes (APOs) and are a major worry in the scenario of climate change. The relationship between rising temperatures and APO must be better understood in order to design more effective interventions. Methodology: We conducted an observational cohort study involving 865 pregnant women in various districts of Tamil Nadu districts between 2014 and 2021. Physiological Heat Strain Indicators (HSI) such as morning and evening Core Body Temperature (CBT) and Urine Specific Gravity (USG) were monitored using an infrared thermometer and refractometer, respectively. A validated, modified version of the HOTHAPS questionnaire was utilised to collect self-reported health symptoms. A follow-up was undertaken with the mothers to collect information regarding birth outcomes and APOs, such as spontaneous abortions, stillbirths, Preterm Birth (PTB), birth abnormalities, and Low Birth Weight (LBW). Major findings of the study: According to the findings of our study, ambient temperatures (mean WBGT°C) were substantially higher (>28°C) for approximately 46% of women performing moderate daily life activities. 82% versus 43% of these women experienced dehydration and heat-related complaints. 34% of women had USG >1.020, which is symptomatic of dehydration. APOs, which include spontaneous abortions, were prevalent at 2.2%, stillbirth/preterm birth/birth abnormalities were prevalent at 2.2%, and low birth weight was prevalent at 16.3%. With exposures to WBGT>28°C, the incidence of miscarriage or unexpected abortion rose by approximately 2.7 times (95% CI: 1.1-6.9). In addition, higher WBGT exposures were associated with a 1.4-fold increased risk of unfavorable birth outcomes (95% Confidence Interval [CI]: 1.02-1.09). The risk of spontaneous abortions was 2.8 times higher among women who conceived during the hotter months (February – September) compared to those women who conceived in the cooler months (October – January) (95% CI: 1.04-7.4). Positive relationships between ambient heat and APOs found in this study necessitate further exploration into the underlying factors for extensive cohort studies to generate information to enable the formulation of policies that can effectively protect these women against excessive heat stress for enhanced maternal and fetal health.

Keywords: heat exposures, community, pregnant women, physiological strain, adverse outcome, interventions

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Authors: Victoria Brennan, Andrea Mallaburn, Linda Seton

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Science outreach programmes connect school pupils with external agencies to provide activities and experiences that enhance their exposure to science. It can be argued that these programmes not only aim to support teachers with curriculum engagement and promote scientific literacy but also provide pivotal opportunities to spark scientific interest in students. In turn, a further objective of these programmes is to increase awareness of career opportunities within this field. Although outreach work is also often described as a fun and satisfying venture, a plethora of researchers express caution to how successful the processes are to increases engagement post-16 in science. When researching the impact of outreach programmes, it is often student feedback regarding the activities or enrolment numbers to particular science courses post-16, which are generated and analysed. Although this is informative, the longevity of the programme’s impact could be better informed by the teacher’s perceptions; the evidence of which is far more limited in the literature. In addition, there are strong suggestions that teachers can have an indirect impact on a student’s own self-concept. These themes shape the focus and importance of this ongoing research project as it presents the rationale that teachers are under-used resources when it comes to considering the design of science outreach programmes. Therefore, the end result of the research will consist of a presentation of an ‘optimum’ model of outreach. The result of which should be of interest to the wider stakeholders such as universities or private or government organisations who design science outreach programmes in the hope to recruit future scientists. During phase one, questionnaires (n=52) and interviews (n=8) have generated both quantitative and qualitative data. These have been analysed using the Wilcoxon non-parametric test to compare teachers’ perceptions of science outreach interventions and thematic analysis for open-ended questions. Both of these research activities provide an opportunity for a cross-section of teacher opinions of science outreach to be obtained across all educational levels. Therefore, an early draft of the ‘optimum’ model of science outreach delivery was generated using both the wealth of literature and primary data. This final (ongoing) phase aims to refine this model using teacher focus groups to provide constructive feedback about the proposed model. The analysis uses principles of modified Grounded Theory to ensure that focus group data is used to further strengthen the model. Therefore, this research uses a pragmatist approach as it aims to focus on the strengths of the different paradigms encountered to ensure the data collected will provide the most suitable information to create an improved model of sustainable outreach. The results discussed will focus on this ‘optimum’ model and teachers’ perceptions of benefits and drawbacks when it comes to engaging with science outreach work. Although the model is still a ‘work in progress’, it provides both insight into how teachers feel outreach delivery can be a sustainable intervention tool within the classroom and what providers of such programmes should consider when designing science outreach activities.

Keywords: educational partnerships, science education, science outreach, teachers

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Authors: Felipe M. de Freitas, Ícaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

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There is a dispersed energy in Radio Frequencies (RF) that can be reused to power electronics circuits such as: sensors, actuators, identification devices, among other systems, without wire connections or a battery supply requirement. In this context, there are different types of energy harvesting systems, including rectennas, coil systems, graphene and new materials. A secondary step of an energy harvesting system is the rectification of the collected signal which may be carried out, for example, by the combination of one or more Schottky diodes connected in series or shunt. In the case of a rectenna-based system, for instance, the diode used must be able to receive low power signals at ultra-high frequencies. Therefore, it is required low values of series resistance, junction capacitance and potential barrier voltage. Due to this low-power condition, voltage multiplier configurations are used such as voltage doublers or modified bridge converters. Lowpass filter (LPF) at the input, DC output filter, and a resistive load are also commonly used in the rectifier design. The electronic circuits projects are commonly analyzed through simulation in SPICE (Simulation Program with Integrated Circuit Emphasis) environment. Despite the remarkable potential of SPICE-based simulators for complex circuit modeling and analysis of quasi-static electromagnetic fields interaction, i.e., at low frequency, these simulators are limited and they cannot model properly applications of microwave hybrid circuits in which there are both, lumped elements as well as distributed elements. This work proposes, therefore, the electromagnetic modelling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-high frequencies, with application in rectifiers coupled to antennas, as in energy harvesting systems, that is, in rectennas. For this purpose, the numerical method FDTD (Finite-Difference Time-Domain) is applied and SPICE computational tools are used for comparison. In the present work, initially the Ampere-Maxwell equation is applied to the equations of current density and electric field within the FDTD method and its circuital relation with the voltage drop in the modeled component for the case of lumped parameter using the FDTD (Lumped-Element Finite-Difference Time-Domain) proposed in for the passive components and the one proposed in for the diode. Next, a rectifier is built with the essential requirements for operating rectenna energy harvesting systems and the FDTD results are compared with experimental measurements.

Keywords: energy harvesting system, LE-FDTD, rectenna, rectifier, wireless power systems

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Christian Andrä, Pauline Hähner, Sebastian Ludyga

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Introduction: In the recent past, discussions on the importance of physical activity for child development have contributed to a growing interest in executive functions, which refer to cognitive processes. By controlling, modulating and coordinating sub-processes, they make it possible to achieve superior goals. Major components include working memory, inhibition and cognitive flexibility. While executive functions can be trained easily in school children, there are still research deficits regarding the trainability during preschool age. Methodology: This quasi-experimental study with pre- and post-design analyzes 23 children [age: 5.0 (mean value) ± 0.7 (standard deviation)] from four different sports groups. The intervention group was made up of 13 children (IG: 4.9 ± 0.6), while the control group consisted of ten children (CG: 5.1 ± 0.9). Between pre-test and post-test, children from the intervention group participated special games that train executive functions (i.e., changing rules of the game, introduction of new stimuli in familiar games) for ten units of their weekly sports program. The sports program of the control group was not modified. A computer-based version of the Eriksen Flanker Task was employed in order to analyze the participants’ inhibition ability. In two rounds, the participants had to respond 50 times and as fast as possible to a certain target (direction of sight of a fish; the target was always placed in a central position between five fish). Congruent (all fish have the same direction of sight) and incongruent (central fish faces opposite direction) stimuli were used. Relevant parameters were response time and accuracy. The main objective was to investigate whether children from the intervention group show more improvement in the two parameters than the children from the control group. Major findings: The intervention group revealed significant improvements in congruent response time (pre: 1.34 s, post: 1.12 s, p<.01), while the control group did not show any statistically relevant difference (pre: 1.31 s, post: 1.24 s). Likewise, the comparison of incongruent response times indicates a comparable result (IG: pre: 1.44 s, post: 1.25 s, p<.05 vs. CG: pre: 1.38 s, post: 1.38 s). In terms of accuracy for congruent stimuli, the intervention group showed significant improvements (pre: 90.1 %, post: 95.9 %, p<.01). In contrast, no significant improvement was found for the control group (pre: 88.8 %, post: 92.9 %). Vice versa, the intervention group did not display any significant results for incongruent stimuli (pre: 74.9 %, post: 83.5 %), while the control group revealed a significant difference (pre: 68.9 %, post: 80.3 %, p<.01). The analysis of three out of four criteria demonstrates that children who took part in a special sports program improved more than children who did not. The contrary results for the last criterion could be caused by the control group’s low results from the pre-test. Conclusion: The findings illustrate that inhibition can be trained as early as in preschool age. The combination of familiar games with increased requirements for attention and control processes appears to be particularly suitable.

Keywords: executive functions, flanker task, inhibition, preschool children

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Authors: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes on the multi-criteria nature of the problem and on how decision makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of significant degree of ambiguity and indeterminacy observed in decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method to a real problem of academic personnel selection, having as main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherit ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: analytical hierarchy process, delphi method, multi-criteria decision maiking method, neutrosophic set theory, personnel recruitment

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Authors: S. A. Bhat, Ahmad Arif, Muneeb U. Rehman, Manzoor R Mir, S. Bilal, Ishraq Hussain, H. M Khan, S. Shanaz, M. I Mir, Sabhiya Majid

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Background: Geologically Climatic conditions of the state range from sub-tropical (Jammu), temperate (Kashmir) to cold artic (Ladakh) zones, which exerts significant influence on its agro-climatic conditions. Gastrointestinal parasitism is a major problem in sheep production worldwide. Materials and Methods: The present study was to evaluate the resistance status of sheep breeds reared in Kashmir Valley for natural resistance against Haemonchus contortus by natural pasture challenge infection. Ten microsatellite markers were used in the study for evaluation of association of Ovar-MHC with parasitic resistance in association with biochemical and parasitological parameters. Following deworming, 500 animals were subjected to selected contaminated pastures in a vicinity of the livestock farms of SKUAST-K and Sheep Husbandry Kashmir. For each animal about 10-15 ml blood was collected aseptically for molecular and biochemical analysis. Weekly fecal samples (3g) were taken, directly from the rectum of all experimental animals and examined for Fecal egg count (FEC) with modified McMaster technique. Packed cell volume (PCV) was determined within 2-5 h of blood collection, all the biochemical parameters were determined in serum by semi automated analyzer. DNA was extracted from all the blood samples with phenol-chloroform method. Microsatellite analysis was done by denaturing sequencing gel electrophoresis Results: Overall sheep from Bakerwal breed followed by Corriediale breed performed relatively better in the trial; however difference between breeds remained low. Both significant (P<0.05) and non-significant differences with respect to resistance against haemonchosis were noted at different intervals in all the parameters.. All the animals were typed for the microsatellites INRA132, OarCP73, DRB1 (U0022), OLA-DQA2, BM1818, TFAP2A, HH56, BM1815, IL-3 and BM-1258. An association study including the effect of FEC, PCV, TSP, SA, LW, and the number of alleles within each marker was done. All microsatellite markers showed degree of heterozygosity of 0.72, 0.72, 0.75, 0.62, 0.84, 0.69, 0.66, 0.65, 0.73 and 0.68 respectively. Significant association between alleles and the parameters measured were only found for the OarCP73, OLA-DQA2 and BM1815 microsatellite marker. Standard alleles of the above markers showed significant effect on the TP, SA and body weight. The three sheep breeds included in the study responded differently to the nematode infection, which may be attributed to their differences in their natural resistance against nematodes. Conclusion: Our data confirms that some markers (OarCP73, OLA-DQA2 and BM1815) within Ovar-MHC are associated with phenotypic parameters of resistance and suggest superiority of Bakerwal sheep breed in natural resistance against Haemonchus contortus.

Keywords: Ovar-Mhc, ovine leukocyte antigen (OLA), sheep, parasitic resistance, Haemonchus contortus, phenotypic & genotypic markers

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Maria F. Seran

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In second language interaction, an EFL student always carries his knowledge of targeted language and sometimes gets influenced by his first language cultures which makes him transfer his utterances from the first language to the second language. The influence of L1 cultures somehow can lead to face-threatening act when it comes to responding on speech act, for instance, compliment. A speaker praises a compliment to show gratitude, and in return, he expects for compliment respond uttered by the hearer. While Western people use more acceptance continuum on compliment response, Indonesians utter more denial continuum which can somehow put the speakers into a face-threating situation and offense. This study investigated compliment response employed by EFL students and English native speakers. The study was distinct as none compliment response studies had been conducted to compare the compliment response between English native speakers and two different Indonesian EFL proficiency groups in which this research sought to meet this need. This study was significant for EFL teachers because it gave insight on cross-cultural understanding and brought pedagogical implication on explicit pragmatic instruction. Two research questions were set, 1. How do Indonesian EFL students and English native speakers respond compliments? 2. Is there any correlation between Indonesia EFL students’ proficiency and their compliment response use in English? The study involved three groups of participants; 5 English native speakers, 10 high-proficiency and 10 low-proficiency Indonesian EFL university students. The research instruments used in this study were as follows, an online TOEFL prediction test, focusing on grammar skill which was modified from Barron TOEFL exercise test, and a discourse completion task (DCT), consisting of 10 compliment respond items. Based on the research invitation, 20 second-year university students majoring in English education at Widya Mandira Catholic University, Kupang, East Nusa Tenggara, Indonesia who willingly participated in the research took the TOEFL prediction test online from the link provided. Students who achieved score 75-100 in test were categorized as high-proficiency students, while, students who attained score below 74 were considered as low-proficiency students. Then, the DCT survey was administered to these EFL groups and the native speaker group. Participants’ responses were coded and analyzed using categories of compliment response framework proposed by Tran. The study found out that 5 native speakers applied more compliment upgrades and appreciation token in compliment response, whereas, Indonesian EFL students combined some compliment response strategies in their utterance, such as, appreciation token, return and compliment downgrade. There is no correlation between students’ proficiency level and their CR responds as most EFL students in both groups produced less varied compliment responses and only 4 Indonesian high-proficiency students uttered more varied and were similar to the native speakers. The combination strategies used by EFL students can be explained as the influence of pragmatic transfer from L1 to L2; therefore, EFL teachers should explicitly teach more compliment response strategies to raise students’ awareness on English culture and elaborate their speaking to be more competence as close to native speakers as possible.

Keywords: compliment response, English native speakers, Indonesian EFL students, speech acts

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Durri Andriani, Irsan Tahar, Lilian Sarah Hiariey

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Every institution has to develop, implement, and control its policies to ensure the effectiveness of the institution. In doing so, all related stakeholders have to be involved to maximize the benefit of the policies and minimize the potential constraints and resistances. Open and distance education (ODE) institution is no different. As an education institution, ODE institution has to focus their attention to fulfilling academic needs of their students through open and distance measures. One of them is quality learning support system. Significant stakeholders in learning support system are tutors since they are the ones who directly communicate with students. Tutors are commonly seen as objects whose main responsibility is limited to implementing policies decided by management in ODE institutions. Nonetheless, tutors’ perceptions of tutorials are believed to influence tutors’ performances in facilitating learning support. It is therefore important to analyze tutors’ perception on various aspects of learning support. This paper presents analysis of tutors’ perceptions on policies of tutoriala in ODE institution using Policy Analysis Framework (PAF) modified by King, Nugent, Russell, and Lacy. Focus of this paper is on on-line tutors, those who provide tutorials via Internet. On-line tutors were chosen to stress the increasingly important used of Internet in ODE system. The research was conducted in Universitas Terbuka (UT), Indonesia. UT is purposely selected because of its large number (1,234) of courses offered and large area coverage (6000 inhabited islands). These posed UT in a unique position where learning support system has, to some extent, to be standardized while at the same time it has to be able to cater the needs of different courses in different places for students with different backgrounds. All 598 listed on-line tutors were sent the research questionnaires. Around 20% of the email addresses could not be reached. Tutors were asked to fill out open-ended questionnaires on their perceptions on definition of on-line tutorial, roles of tutors and students in on-line tutorials, requirement for on-line tutors, learning materials, and student evaluation in on-line tutorial. Data analyzed was gathered from 40 on-line tutors who sent back filled-out questionnaires. Data were analyzed qualitatively using content analysis from all 40 tutors. The results showed that using PAF as entry point in choosing learning support services as area of policy with delivery learning materials as the issue at UT has been able to provide new insights of aspects need to be consider in formulating policies in online tutorial and in learning support services. Involving tutors as source of information could be proven to be productive. In general, tutors had clear understanding about definition of online tutorial, roles of tutors and roles of students, and requirement of tutor. Tutors just need to be more involved in the policy formulation since they could provide data on students and problem faced in online tutorial. However, tutors need an adjustment in student evaluation which according tutors too focus on administrative aspects and subjective.

Keywords: distance education, on-line tutorial, tutorial policy, tutors’ perspectives

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