Search results for: efficient score function

Authors: Ji-yang Yu, Dan Huang, Guo-ping Feng, Xin Li, Lu-yuan Wang

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The navigation satellite network, especially the Beidou MEO Constellation, can relay data effectively with wide coverage and is applied in navigation, detection, and position widely. But the constellation has not been completed, and the amount of satellites on-board is not enough to cover the earth, which makes the data-relay disrupted or delayed in the transition process. The data-relay function needs to tolerant the delay or disruption in some extension, which make the Beidou MEO Constellation a delay/disruption-tolerant network (DTN). The traditional DTN designs mainly employ the relay table as the basic of data path schedule computing. But in practical application, especially in critical condition, such as the war-time or the infliction heavy losses on the constellation, parts of the nodes may become invalid, then the traditional DTN design could be useless. Furthermore, when transmitting the critical message in the navigation system, the maximum priority strategy is used, but the nodes still inquiry the relay table to design the path, which makes the delay more than minutes. Under this circumstances, it needs a function which could compute the optimum data path on-board in real-time according to the constellation states. The on-board critical message transmission design for navigation satellite delay/disruption-tolerant network (DTN) is proposed, according to the characteristics of navigation satellite network. With the real-time computation of parameters in the network link, the least-delay transition path is deduced to retransmit the critical message in urgent conditions. First, the DTN model for constellation is established based on the time-varying matrix (TVM) instead of the time-varying graph (TVG); then, the least transition delay data path is deduced with the parameters of the current node; at last, the critical message transits to the next best node. For the on-board real-time computing, the time delay and misjudges of constellation states in ground stations are eliminated, and the residual information channel for each node can be used flexibly. Compare with the minute’s delay of traditional DTN; the proposed transmits the critical message in seconds, which improves the re-transition efficiency. The hardware is implemented in FPGA based on the proposed model, and the tests prove the validity.

Keywords: critical message, DTN, navigation satellite, on-board, real-time

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Authors: Kiyohiro Yamazaki

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The purpose of this paper is to examine the hypothesis explaining the mechanism in the case, where the product is deleted or reduced the fundamental function of the product through the product concept changes in the digital camera industry. This paper points out not owning the fundamental technology might cause the change of the product concept. Casio could create new competitive factor so that this paper discusses a possibility of the mechanism of changing the product concept.

Keywords: firm without fundamental technology, product development, product concept, digital camera industry, Casio

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Authors: Ahmed Salam, Haithem Benkahla

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Recently, an efficient backward-stable algorithm for computing eigenvalues and vectors of a symmetric and Hamiltonian matrix has been proposed. The method preserves the symmetric and Hamiltonian structures of the original matrix, during the whole process. In this paper, we revisit the method. We derive a way for implementing the reduction of the matrix to the appropriate condensed form. Then, we construct a novel version of the implicit QR-algorithm for computing the eigenvalues and vectors.

Keywords: block implicit QR algorithm, preservation of a double structure, QR algorithm, symmetric and Hamiltonian structures

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Authors: Nicolas Lopez-Villalobos, Dorian J. Garrick, Hugh T. Blair

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Many dairy goat farmers of New Zealand milk herds of mixed breed does. Simultaneous evaluation of sires and does across breed is required to select the best animals for breeding on a common basis. Across-breed estimated breeding values (EBV) and estimated producing values for 208-day lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS; LOG2(SCC) of Saanen, Nubian, Alpine, Toggenburg and crossbred dairy goats from 75 herds were estimated using a test day model. Evaluations were based on 248,734 herd-test records representing 125,374 lactations from 65,514 does sired by 930 sires over 9 generations. Averages of MY, FY and PY were 642 kg, 21.6 kg and 19.8 kg, respectively. Average SCC and SCS were 936,518 cells/ml milk and 9.12. Pure-bred Saanen does out-produced other breeds in MY, FY and PY. Average EBV for MY, FY and PY compared to a Saanen base were Nubian -98 kg, 0.1 kg and -1.2 kg; Alpine -64 kg, -1.0 kg and -1.7 kg; and Toggenburg -42 kg, -1.0 kg and -0.5 kg. First-cross heterosis estimates were 29 kg MY, 1.1 kg FY and 1.2 kg PY. Average EBV for SCS compared to a Saanen base were Nubian 0.041, Alpine -0.083 and Toggenburg 0.094. Heterosis for SCS was 0.03. Breeding values are combined with respective economic values to calculate an economic index used for ranking sires and does to reflect farm profit.

Keywords: breed effects, dairy goats, milk traits, test-day model

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Authors: Punit Gandhi, J. C. Brezet, Tim Gorter, Uchechi Obinna

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This paper introduces how weather forecasting could help in more efficient energy management for smart homes with the use of Home Energy Management Systems (HEMS). The paper also focuses on educating consumers and helping them make more informed decisions while using the HEMS. A combined approach of technical and user perspective has been selected to develop a novel HEMS-product-service combination in a more comprehensive manner. The current HEMS switches on/off the energy intensive appliances based on the fluctuating electricity tariffs, but with weather forecasting, it is possible to shift the time of use of energy intensive appliances to maximum electricity production from the renewable energy system installed in the house. Also, it is possible to estimate the heating/cooling load of the house for the day ahead demand. Hence, relevant insight is gained in the expected energy production and consumption load for the next day, facilitating better (more efficient, peak shaved, cheaper, etc.) energy management practices for smart homes. In literature, on the user perspective, it has been observed that consumers lose interest in using HEMS after three to four months. Therefore, to further help in better energy management practices, the new system had to be designed in a way that consumers would sustain their interaction with the system on a structural basis. It is hypothesized that, if consumers feel more comfortable with using such system, it would lead to a prolonged usage, including more energy savings and hence financial savings. To test the hypothesis, a survey for the HEMS is conducted, to which 59 valid responses were recorded. Analysis of the survey helped in designing a system which imparts better information about the energy production and consumption to the consumers. It is also found from the survey that, consumers like a variety of options and they do not like a constant reminder of what they should do. Hence, the final system is designed to encourage consumers to make an informed decision about their energy usage with a wide variety of behavioral options available. It is envisaged that the new system will be tested in several pioneering smart energy grid projects in both the Netherlands and India, with a continued ‘design thinking’ approach, combining the technical and user perspective, as the basis for further improvements.

Keywords: weather forecasting, smart grid, renewable energy forecasting, user defined HEMS

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Authors: Rob Gesley Capistrano, Jasper James Isaac, Rose Mae Moralda, Therese Anne Peleo, Danica Rillo, Maria Virginia Santillian

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One of the valuable things that shows the intelligence among individuals is the academic background specifically their Grade Weighted Average and the significant result of the Comprehensive Examination. The general objective of the researchers to this study is to determine if there is a significant difference between General Weighted Average and Comprehensive Examination Result of Psychometrician Board Passers and Non-Board Passers. The respondents of this study composed of board passers and non-board passers. The researchers used purposive sampling technique. The result utilized by using T-test Independent Sample to determine the comparison of General Weighted Average and Comprehensive Examination Result of Board Passers and Non Board Passers. At the end, it concluded that the General Weighted Average of Board Passers and Non-Board Passers shows that there is no significant difference, but the average showed a minimal variation. The Comprehensive Examination Result of Board Passers and Non-Board Passers result revealed that there is a significant difference. The performance of comprehensive examination that will test the overall knowledge of an individual and will determine whose more proficient will likely to have a higher score. The result of the comprehensive examination had an impact in the passing performance of board examination.

Keywords: board passers, comprehensive examination result, grade weighted average, non board passers

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Authors: Fábio A. S. Mota, Mauro A. S. S. Ravagnani, E. P. Carvalho

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In the present paper the design of plate heat exchangers is formulated as an optimization problem considering two mathematical modeling. The number of plates is the objective function to be minimized, considering implicitly some parameters configuration. Screening is the optimization method used to solve the problem. Thermal and hydraulic constraints are verified, not viable solutions are discarded and the method searches for the convergence to the optimum, case it exists. A case study is presented to test the applicability of the developed algorithm. Results show coherency with the literature.

Keywords: plate heat exchanger, optimization, modeling, simulation

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Authors: Baris Sezer

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A great number of projects have been implemented by Turkey in order to integrate technologies into education. The FATİH Project is intended to integrate technology into all levels of education in Turkey. As part of the FATİH Project that is aimed to complete in 2016, it is intended to initially deliver a tablet PC to every student and teacher. We aimed to detect grade 9 students’ acceptance perception level of tablet PCs during the 2014 – 2015 school year in this study where quantitative and qualitative data collection techniques were used in combination. The study group consisted of 228 grade 9 students of high schools in Istanbul, Ankara, Zonguldak and Bursa in Turkey. Study data was obtained through the “Tablet PC Acceptance Scale” and structured interview forms. Given the results obtained from the study, the mean overall score was 70.08 (3.72 out of 5), which was derived from all the dimensions of the acceptance perception level of tablet PCs in the students’ view. Findings of the study indicate that mean scores for students’ acceptance perception level of tablet PCs did not differ by their gender and their level of use of Information and Communication Technology (ICT). Focus group interviews with students suggest that students did not effectively and actively use the tablet PCs; instead they used the interactive board during classes.

Keywords: acceptance of technology, student’s view, FATIH project, tablet PCs

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Authors: G. Imran, A. Pandurangan

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Epoxides constitute important intermediates for the production of fine and bulk chemicals as well as valuable building blocks for the synthesis of a variety of bioactive molecules. Manganese oxides are used as selective catalyst for various redox type reactions and also effectively used in the field of catalytic disposal of pollutants. Non-toxic, cost efficient factor and more over existence of wide range of oxidation state (+2 to +7) makes catalyst more interesting for both academic research and industrial applications. However, the serious drawback lying is the lower surface area. Exceedingly dispersed manganese oxide grafted over mesoporous solid material KIT-6 through ALD (Atomic Layer Deposition) technique effectively catalyze cyclohexene with H2O2 (30% in water) to corresponding epoxides. Highly selective epoxide >99% with 55.7% conversion of cyclohexene was achieved using huge dispersed active sites of MnOx species containing catalysts. Various weight percent such as (1, 3, 5, 7 & 10 wt %) of manganese (II) acetylacetonate complex was employed as Mn source to post-graft via active silanol groups of KIT-6 and are designated as (Mn-G-KIT-6). XRD, N2 sorption, HR-TEM, DRS-UV-VIS, EPR and H2-TPR were employed for structural and textural properties. Immense Mn species of about 95% proportion on silica matrix obtained was evident from ICP-OES.The resulting materials exhibited Type IV adsorption isotherms indiacting mesopore in nanorange. Si-KIT-6 and Mn-G-KIT-6 materials exhibited surface area of 519-289 m2/g and with decrease in pore volume of 0.96-0.49 cm3/g with pore diameter ranging 7.9- 7.2 with increase in wt%. DRS-UV-VIS spectroscopy and EPR studies reveal that manganese coexists as Mn2+/3+ species as extra-framework sites and frame-work sites that result in dispersion on surface of silica matrix of KIT-6 and incorporated manganese sites with silanol groups along with small sized MnO cluster, evident from HR-TEM which increase with Mn content. Conventional production of epoxides by the intramolecular etherification of chlorohydrins formed by the reaction of alkenes with hypochlorous acid is the major drawbacks obtained recently. The most efficient synthesis of oxiranes (epoxides) is obtained by mesoporous catalysts (Mn-G-KIT-6) are presented here and discussed.

Keywords: ALD, epoxidation, mesoporous, MnOx

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Authors: Ammar Edress Mohamed, Mustafa Aziz, David Wright

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This paper analyses and calculates the head fields of asymmetrical 2D magnetic recording heads when the soft-underlayer is present using the appropriate Green's function to derive the surface potential/field by utilising the surface potential for asymmetrical head without underlayer. The results follow closely the corners, while the gap region shows a linear behaviour for d/g < 0.5 compared with the calculated fields from finite-element.

Keywords: magnetic recording, finite elements, asymmetrical magnetic heads, superposition, Laplace's equation

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Authors: Meltem Betül Sağlam, Halil İbrahim Güler, Aykut Sağlam

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In this work, phthalocyanine compounds containing α-naphtholbenzeinunits have been synthesized. Mutagenicity and DNA binding properties of the compounds were investigated by Salmonella/Microsome Assay and spectrophotometer. According to the results of the preliminary range finding tests, the compounds gave no toxic effect to all tester strain S. typhimurium TA98 and TA100 at doses of 500, 1100, 350, 500 and 750 µg/plate in the presence and absence of S9, respectively. This study showed that all compounds exhibited efficient DNA-binding activity. In conclusion, these non-toxic compounds may be used as effective DNA dyes for molecular biology studies.

Keywords: dye, mutagenicity, phthalocyanine, toxicity

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cecile Donze

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Multiple sclerosis (MS) is a disease, which affects the central nervous system, and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. Forty volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and two types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: balance, multiple sclerosis, nonlinear analysis, postural sway

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Authors: Yutong Wan, John N. Wood

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Introduction: SCN9A encoded Nav1.7 is an ideal therapeutic target with minimal side effects for the pharmaceutical industry because SCN9A variants can cause both human gains of function pain-related mutations and loss of function pain-free mutations. This study reviews the clinical effectiveness of existing Nav1.7 inhibitors, which theoretically should be powerful analgesics. Methods: A systematic review is conducted on the effectiveness of current Nav1.7 blockers undergoing clinical trials. Studies were mainly extracted from PubMed, U.S. National Library of Medicine Clinical Trials, World Health Organization International Clinical Trials Registry, ISRCTN registry platform, and Integrated Research Approval System by NHS. Only studies with full text available and those conducted using double-blinded, placebo controlled, and randomised designs and reporting at least one analgesic measurement were included. Results: Overall, 61 trials were screened, and eight studies covering PF 05089771 (Pfizer), TV 45070 (Teva & Xenon), and BIIB074 (Biogen) met the inclusion criteria. Most studies were excluded because results were not published. All three compounds demonstrated insignificant analgesic effects, and the comparison between PF 05089771 and pregabalin/ibuprofen showed that PF 05089771 was a much weaker analgesic. All three drug candidates only have mild side effects, indicating the potentials for further investigation of Nav1.7 antagonists. Discussion: The failure of current Nav1.7 small molecule inhibitors might attribute to ignorance of the key role of endogenous systems in Nav1.7 null mutants, the lack of selectivity and blocking potency, and central impermeability. The synergistic combination of analgesic drugs, a recent UCL patent, combining a small dose of Nav1.7 blockers and opioids or enkephalinase inhibitors dramatically enhanced the analgesic effects. Conclusion: The current clinical testing Nav1.7 blockers are generally disappointing. However, the newer generation of Nav1.7 targeting analgesics has overcome the major constraints of its predecessors.

Keywords: chronic pain, Nav1.7 blockers, SCN9A, systematic review

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Authors: Phawida Wattanasoonthorn

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Ventilator-associated pneumonia is a serious infection found to be among the top three infections in the hospital. To investigate the effects of clinical practice guideline on knowledge and preventive practices of nursing personnel, and incidences of ventilator-associated pneumonia. A pre-post quasi-experimental study on 17 professional nurses, and 123 ventilator-associated pneumonia patients admitted to the surgical intensive care unit, and the accident and surgical ward of Songkhla Hospital from October 2013 to January 2014. The study found that after using the clinical practice guideline, the subjects’ median score increased from 16.00 to 19.00. The increase in practicing correctly was from 66.01 percent to 79.03 percent with the statistical significance level of .05, and the incidences of ventilator-associated pneumonia decreased by 5.00 percent. The results of this study revealed that the use of the clinical practice guideline helped increase knowledge and practice skill of nursing personnel, and decrease incidences of ventilator-associated pneumonia. Thus, nursing personnel should be encouraged, reminded and promoted to continue using the practice guideline through various means including training, providing knowledge, giving feedback, and putting up posters to remind them of practicing correctly and sustainably.

Keywords: Clinical Practice Guideline, knowledge, Preventive Ventilator, Pneumonia

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Authors: Saradha Priya

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Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

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Authors: Markus Stralla

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This study employs a GMM framework to examine the impact of potential regulatory intervention regarding the occupations of supervisory board members in cooperative banking. To achieve insights, the study proceeds in two different ways. First, it investigates the changes in board structure prior and following to the German Act to Strengthen Financial Market and Insurance Supervision (FinVAG). Second, the study estimates the influence of Ph.D.Share, professional concentration and supervisory power on bank-risk changes in consideration of the implementation of FinVAG. Therefore, the study is based on a sample of 246 German cooperative banks from 2006-2011 while applying four different measures of bank risk, namely credit-, equity-, liquidity-risk, and Z-Score, with the former three also being addressed in FinVAG. Results indicate that the implementation of FinVAG results in (most likely unintentional) structural changes, especially at the expense of farmers, and affects all risk measures and relations between risk measures and supervisory board characteristics in a risk-reducing and therefore intended way. To disentangle the complex relationship between board characteristics and risk measures, the study utilizes two-step system GMM estimator to account for unobserved heterogeneity and simultaneity in order to reduce endogeneity problems. The findings may be especially relevant for stakeholders, regulators, supervisors and managers.

Keywords: bank governance, bank risk-taking, board of directors, regulation

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: Emhimed Saffor

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In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications.

Keywords: CT images, Matlab, medical images, edge detection

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Authors: Felipe Aguirre

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In this paper some of the relevant features of the πλῆκτρον within GrecoLatin tradition will be analyzed. Starting from the formal aspects (shape, materials, technical properties) and the archaeological evidence, some of its symbolic implications that emerge in the light of literary and iconographic analysis will be discussed. I shall expose that, in addition to fulfilling a purely physical function within the process of sound production, the πλῆκτρον was the object of a rich imaginery that provided it with an allegorical, metaphorical-poetic and even metaphysical dimension.

Keywords: musicology, ethnomusicology, ancient greek music, plectrum, stringed instruments

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Authors: Wen Cai Ng, Saman Ilankoon, Meng Nan Chong

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The vast increase in global energy demand, coupled with the growing concerns on environmental issues, has triggered the search for cleaner alternative energy sources. In view of this, the photoelectrochemical (PEC) water splitting offers a sustainable hydrogen (H2) production route that only requires solar energy, water, and PEC system operating in an ambient environment. However, the current advancement of PEC water splitting technologies is still far from the commercialization benchmark indicated by the solar-to-H2 (STH) efficiency of at least 10 %. This is largely due to the shortcomings of photoelectrodes used in the PEC system, such as the rapid recombination of photogenerated charge carriers and limited photo-responsiveness in the visible-light spectrum. Silver orthophosphate (Ag3PO4) possesses many desirable intrinsic properties for the fabrication into photoanode used in PEC systems, such as narrow bandgap of 2.4 eV and low valence band (VB) position. Hence, in this study, a highly efficient Ag3PO4-based photoanode was synthesized and characterized. The surface of the Ag foil substrate was directly oxidized to fabricate a top layer composed of {111}-bound Ag3PO4 tetrahedrons layer with a porous structure, forming the dual-layer Ag/Ag3PO4 photoanode. Furthermore, the key synthesis parameters were systematically investigated by varying the concentration ratio of capping agent-to-precursor (R), the volume ratio of hydrogen peroxide (H2O2)-to-water, and reaction period. Results showed that the optimized dual-layer Ag/Ag3PO4 photoanode achieved a photocurrent density as high as 4.19 mA/cm2 at 1 V vs. Ag/AgCl for the R-value of 4, the volume ratio of H2O2-to-water of 3:5 and 20 h reaction period. The current work provides a solid foundation for further nanoarchitecture modification strategies on Ag3PO4-based photoanodes for more efficient PEC water splitting applications. This piece of information needs to be backed up by evidence; therefore, you need to provide a reference. As the abstract should be self-contained, all information requiring a reference should be removed. This is a fact known to the area of research, and not necessarily required a reference to support.

Keywords: solar-to-hydrogen fuel, photoelectrochemical water splitting, photoelectrode, silver orthophosphate

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Authors: Himanshu Kushwah, Nidhi Sandal, Meenakshi K. Chauhan, Gaurav Mittal

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Excessive bleeding is the primary factor of avoidable death in both civilian trauma centers as well as the military battlefield. Hundreds of Indian troops die every year due to blood loss caused by combat-related injuries. These deaths are avoidable and can be prevented to a large extent by making available a suitable hemostatic dressing in an emergency medical kit. In this study, natural gums were evaluated as potential hemostatic agents in combination with calcium gluconate. The study compares the hemostatic activity of Gum Tragacanth (GT), Guar Gum (GG), Xanthan Gum (XG) and Gum Acacia (GA) by carrying out different in-vitro and in-vivo studies. In-vitro studies were performed using the Lee-White method and Eustrek method, which includes the visual and microscopic analysis of blood clotting. MTT assay was also performed using human lymphocytes to check the cytotoxicity of the gums. The in-vivo studies were performed in Sprague Dawley rats using tail bleeding assay to evaluate the hemostatic efficacy of the gums and compared with a commercially available hemostatic sponge, Surgispon. Erythrocyte agglutination test was also performed to check the interaction between blood cells and the natural gums. Other parameters like blood loss, adherence strength of the developed hemostatic dressing material incorporating these gums, re-bleeding, and survival of the animals were also studied. The data obtained from the MTT assay showed that Guar gum, Gum Tragacanth, and Gum Acacia were not significantly cytotoxic, but substantial cytotoxicity was observed in Xanthan gum samples at high concentrations. Also, Xanthan gum took the least time with its minimum concentration to achieve hemostasis, (approximately 50 seconds at 3mg concentration). Gum Tragacanth also showed efficient hemostasis at a concentration of 35mg at the same time, but the other two gums tested were not able to clot the blood in significantly less time. A sponge dressing made of Tragacanth gum was found to be more efficient in achieving hemostasis and showed better practical applicability among all the gums studied and also when compared to the commercially available product, Surgispon, thus making it a potentially better alternative.

Keywords: cytotoxicity, hemostasis, natural gums, sponge

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Authors: Liaqat Ali, Hubert E. Blum, Türkân Sakinc

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Enterococcus faecium is an emerging multidrug-resistant nosocomial pathogen increased dramatically worldwide and causing bacteremia, endocarditis, urinary tract and surgical site infections in immunocomprised patients. The capsular polysaccharides that contribute to pathogenesis through evasion of the host innate immune system are also involved in hindering leukocyte killing of enterococci. The gene cluster (enterococcal polysaccharide antigen) of E. faecalis encoding homologues of many genes involved in polysaccharide biosynthesis. We identified two putative loci with 22 kb and 19 kb which contained 11 genes encoding for glycosyltransferases (GTFs); this was confirmed by using genome comparison of already sequenced strains that has no homology to known capsule genes and the epa-locus. The polysaccharide-conjugate vaccines have rapidly emerged as a suitable strategy to combat different pathogenic bacteria, therefore, we investigated a polysaccharide biosynthesis CapD protein in E. faecium contains 336 amino acids and had putative function for N-linked glycosylation. The deletion/knock-out capD mutant was constructed and complemented by homologues recombination method and confirmed by using PCR and sequencing. For further characterization and functional analysis, in-vitro cell culture and in-vivo a mouse infection models were used. Our ΔcapD mutant shows a strong hydrophobicity and all strains exhibited biofilm production. Subsequently, the opsonic activity was tested in an opsonophagocytic assay which shows increased in mutant compared complemented and wild type strains but more than two fold decreased in colonization and adherence was seen on surface of uroepithelial cells. However, a significant higher bacterial colonialization was observed in capD mutant during animal bacteremia infection. Unlike other polysaccharides biosynthesis proteins, CapD does not seems to be a major virulence factor in enterococci but further experiments and attention is needed to clarify its function, exact mechanism and involvement in pathogenesis of enteroccocal nosocomial infections eventually to develop a vaccine/ or targeted therapy.

Keywords: E. faecium, pathogenesis, polysaccharides, biofilm formation

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Authors: Jay Xiong, Li Lin

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Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

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Authors: Yan Lu, Song Hong, Janakiraman Udaiyappan, Aarti Nagayach, Quoc-Viet A. Duong, Masao Morita, Shun Saito, Yuichi Kobayashi, Yuhai, Zhao, Hongying Peng, Nicholas B. Pham, Walter J Lukiw, Christopher A. Vuong, Nicolas G. Bazan

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Aims: Neurodegeneration and behavior dysfunction occurs in patients with Alzheimer's Disease (AD), and as the disease progresses many patients develop cognitive impairment. 5XFAD mouse model of AD is widely used to study AD pathogenesis and treatment. This study aimed to investigate the effect of maresin like 1 (MaR-L1) treatment in AD pathology using 5XFAD mice. Methods: We tested 12-month-old male 5XFAD mice and wild type control mice treated with MaR-L1 in a battery of behavioral tasks. We performed open field test, beam walking test, clasping test, inverted grid test, acetone test, marble burring test, elevated plus maze test, cross maze test and novel object recognition test. We also studied neuronal loss, amyloid β burden, and inflammation in the brains of 5XFAD mice using immunohistology and Western blotting. Results: MaR-L1 treatment to the 5XFAD mice showed improved cognitive function of 5XFAD mice. MaR-L1 showed decreased anxiety behavior in open field test and marble burring test, increased muscular strength in the beam walking test, clasping test and inverted grid test. Cognitive function was improved in MaR-L1 treated 5XFAD mice in the novel object recognition test. MaR-L1 prevented neuronal loss and aberrant inflammation. Conclusion: Our finding suggests that behavioral abnormalities were normalized by the administration of MaR-L1 and the neuroprotective role of MaR-L1 in the AD. It also indicates that MaR-L1 treatment is able to prevent and or ameliorate neuronal loss and aberrant inflammation. Further experiments to validate the results are warranted using other AD models in the future.

Keywords: Alzheimer's disease, motor and cognitive behavior, 5XFAD mice, Maresin Like 1, microglial cell, astrocyte, neurodegeneration, inflammation, resolution of inflammation

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

Procedia PDF Downloads 87

Authors: María José Núñez-Ruiz, Luis Álvarez-González, Cristian Olivares-Rodriguez, Benjamin Lazo-Letelier

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This paper begins with some concept of formative assessment and the relationship with learning objective: contents objectives, processes objectives, and metacognitive objectives. Two methodologies are describes Evidence-Based teaching and Question Drive Instruction. To do formative assessments in larges classes a Classroom Response System (CRS) is needed. But most of CRS use only Multiple Choice Questions (MCQ), True/False question, or text entry; however, this is insufficient to formative assessment. To do that a new CRS, call FAMA was developed. FAMA support six types of questions: Choice, Order, Inline choice, Text entry, Associated, and Slider. An experiment participated in 149 students from four engineering careers. For results, Kendall's Range Correlation Analysis and descriptive analysis was done. In conclusion, there is a strong relation between contents question, process questions (ask in formative assessment without a score) and metacognitive questions, asked in summative assessment. As future work, the lecturer can do personalized teaching, because knows the behavior of all students in each formative assessment

Keywords: Python language, formative assessment, classroom response systems, evidence-Based teaching, question drive instruction

Procedia PDF Downloads 124

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 194

Authors: Avani Jain, Hasmukh Jain, S. Shelley, M. Indirani, Shilpa Kalal, Jayakanth Amalachandran

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Aim of the Study: To assess the effect of orally administered Itopride on gall bladder ejection fraction by fatty meal cholescintigraphy in patients with diabetes. Materials and Methods: Thirty patients (20 males, 10 females, mean age 46+10 yrs) with history of diabetes mellitus (mean duration 4.8+4.1 yrs, fasting blood glucose level 130+35 mg/dl and 2-hours post-prandial blood glucose level 196+76 mg/dl) and found to have gall bladder dysfunction on fatty-meal stimulated cholescintigraphy were selected for this study. These patients underwent a repeat cholescintigraphy similar to baseline study, with 50 mg of Itopride orally along with fatty meal. Pre- and post-Itopride GBEF were then compared to assess the effect of Itopride on gall bladder contraction. Results: Out of these 30 patients, 2 had dyskinetic, 4 had akinetic, 22 had moderately hypokinetic and the remaining 2 had hypokinetic gall bladder function in the baseline study with > 60% GBEF being taken as the normal value. Mean percentage of GBEF in the baseline study was 32%+13% and the mean percentage of GBEF in the post-Itopride study was 57%+17% with change in mean percentage of GBEF being 24%+21%. GBEF of the “baseline study” was significantly lower as compared to GBEF in the “post-Itopride study” (p < 0.05). Conclusion: Diabetic patients with biliary-type pain often tend to have impaired gallbladder function. Cholescintigraphy with fatty meal-stimulation is a simple, cheap and useful investigation for assessment of gallbladder dysfunction in these patients, before any structural changes occur within the lumen or wall of the gall bladder. Improvement in gallbladder ejection fraction after oral administration of a single dose of Itopride, a newer prokinetic drug with fewer side effects, as assessed by cholescintigraphy, provides enough evidence of future therapeutic response. Administration of Itopride, in therapeutic dosage, therefore may be expected to cause significant improvement in gallbladder ejection fraction and hence prolong stone formation within the gall bladder and also prevent the associated long term complications. Hence, based on scintigraphic evidence, Itopride may be recommended, by clinicians, for management of symptomatic diabetic patients having gallbladder dysfunction.

Keywords: itopride, gall bladder ejection fraction, fatty meal, cholescintigraphy, diabetes

Procedia PDF Downloads 421

Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

Procedia PDF Downloads 176