Search results for: dynamic power transmission system studies

Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

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PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provide better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Ana Hol

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Digital systems are in the cognitive wave of the eTransformations and are now extensively aimed at meeting the individuals’ demands, both those of customers requiring services and those of service providers. It is also apparent that successful future systems will not just simply open doors to the traditional owners/users to offer and receive services such as Uber for example does today, but will in the future require more customized and cognitively enabled infrastructures that will be responsive to the system user’s needs. To be able to identify what is required for such systems, this research reviews the historical and the current effects of the eTransformation process by studying: 1. eTransitions of company websites and mobile applications, 2. Emergence of new sheared economy business models as Uber and, 3. New requirements for demand driven, cognitive systems capable of learning and just in time decision making. Based on the analysis, this study proposes a Cognitive eTransformation Framework capable of guiding implementations of new responsive and user aware systems.

Keywords: system implementations, AI supported systems, cognitive systems, eTransformation

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Authors: Rofayda A. Hout

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This study aims to investigate the relationship between women on board and corporate social responsibility (CSR) in addition to the role of corporate governance in introducing and implementing CSR practices. Analysis has been conducted on 30 prior studies published between 2007 and 2017 to investigate the common areas and differences across the studies with varying conclusions. The study also handles the differences between developing and developed countries when it comes to gender diverse board and corporate social responsibility. The review conducted reveals that there is a positive relationship between women on board and corporate social responsibility. Comparison between developed and developing countries with respect to CSR implementation highlighted differences due to possible reasons relating to socio-political, cultural, socio-economic, and institutional factors. In addition, developing countries perceive CSR as philanthropy rather than part of their business mission. Given that, CSR needs to be integrated into the corporate strategic planning and be considered as fundamental part of the operations to improve the region’s needs. Developing countries were late in adopting CSR in comparison to developed countries, thus to have a fair comparison between developed and developing countries, corporate governance in developing countries should take serious steps in developing a framework for CSR implementation and integrating it within corporate operations.

Keywords: corporate governance, corporate performance, corporate social responsibility, developed countries, developing countries, gender diverse board, systematic review

Procedia PDF Downloads 191

Authors: Dzmitry M. Kabanau, Vladimir V. Kabanov, Yahor V. Lebiadok, Denis V. Shabrov, Pavel V. Shpak, Gevork T. Mikaelyan, Alexandr P. Bunichev

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This article is deal with the experimental investigations of the laser diode matrixes (LDM) based on the AlGaAs/GaAs heterostructures (lasing wavelength 790-880 nm) to find optimal LDM parameters for active vision systems. In particular, the dependence of LDM radiation pulse power on the pulse duration and LDA active layer heating as well as the LDM radiation divergence are discussed.

Keywords: active vision systems, laser diode matrixes, thermal properties, radiation divergence

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Authors: Evagelia Makri, Maria Tsourela, Dimitris Paschaloudis, Dafni M. Nerantzaki

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One of the biggest financial and social problems, which at the same time constitute one of the greater challenges that Greek society faces today, is the illegal avoidance of tax payments. Tax evasion may negate financial data and community budgets, as well as breed financial chaos. This research seeks to reflect Greek reality concerning tax measures. Also, there will be an effort to record the factors surrounding tax evasion. Greek tax system’s data will be rendered in financial terms. Questionnaires will be handed out to tax payers, and interviews will be conducted to taxmen. The quantitative analysis of the questionnaire answers will define the tax payers’ opinion towards the existence of tax evasion. The qualitative analysis of the interviews will reveal the main reason that boosts tax evasion. At the end, there will be some realistic proposals about how to better collect taxes, through the creation of a strong regulatory mechanism.

Keywords: tax evasion, tax collection measures, insurance recovery measures, Greek tax system

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Authors: J. Martin Leal-Graciano, Juan J. Pérez-Gavilán, A. Reyes-Salazar, J. H. Castorena, J. L. Rivera-Salas

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The experimental results about the global behavior of twelve 1:2 scaled reinforced concrete frame subject to in-plane lateral load are presented. The main objective was to generate experimental evidence about the use of steel bars within mortar bed-joints as shear reinforcement in infill walls. Similar to the Canadian and New Zealand standards, the Mexican code includes specifications for this type of reinforcement. However, these specifications were obtained through experimental studies of load-bearing walls, mainly confined walls. Little information is found in the existing literature about the effects of joint reinforcement on the seismic behavior of infill masonry walls. Consequently, the Mexican code establishes the same equations to estimate the contribution of joint reinforcement for both confined walls and infill walls. A confined masonry construction and a reinforced concrete frame infilled with masonry walls have similar appearances. However, substantial differences exist between these two construction systems, which are mainly related to the sequence of construction and to how these structures support vertical and lateral loads. To achieve the objective established, ten reinforced concrete frames with masonry infill walls were built and tested in pairs, having both specimens in the pair identical characteristics except that one of them included joint reinforcement. The variables between pairs were the type of units, the size of the columns of the frame and the aspect ratio of the wall. All cases included tie-columns and tie-beams on the perimeter of the wall to anchor the joint reinforcement. Also, two bare frame with identical characteristic to the infilled frames were tested. The purpose was to investigate the effects of the infill wall on the behavior of the system to in-plane lateral load. In addition, the experimental results were compared with the prediction of the Mexican code. All the specimens were tested in cantilever under reversible cyclic lateral load. To simulate gravity load, constant vertical load was applied on the top of the columns. The results indicate that the contribution of the joint reinforcement to lateral strength depends on the size of the columns of the frame. Larger size columns produce a failure mode that is predominantly a sliding mode. Sliding inhibits the production of new inclined cracks, which are necessary to activate (deform) the joint reinforcement. Regarding the effects of joint reinforcement in the performance of confined masonry walls, many facts were confirmed for infill walls: this type of reinforcement increases the lateral strength of the wall, produces a more distributed cracking and reduces the width of the cracks. Moreover, it reduces the ductility demand of the system at maximum strength. The prediction of the lateral strength provided by the Mexican code is property in some cases; however, the effect of the size of the columns on the contribution of joint reinforcement needs to be better understood.

Keywords: experimental study, Infill wall, Infilled frame, masonry wall

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Authors: Marianna Russo

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Ageing population and youth unemployment are the major challenges that Western Countries – and Italy in particular – are facing in recent years. These phenomena have a significant impact not only on the labour market and the welfare system, but also on the organisational models of work. Therefore, in Italy, in the past few years, there have been some attempts to regulate the management of generational turn-over: intergenerational pacts, early retirement incentives, solidarity contracts, etc. In particular, this paper aims to focus on the expansive solidarity contracts, that were introduced in the Italian legal system for the first time in 1984. Indeed, they have been little used during the thirty years of their lives, so the Legislative Decree no. 148/2015, implementing the so-called Jobs Act, has given them another opportunity. The paper tries to analyse the rules and the empirical data, looking for a sustainable model of generational turn-over management.

Keywords: ageing population, generational turn-over, Italian jobs' act, solidarity contracts

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Authors: Israr Ahmad, Sehrish Sabir

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Present study deals with the taxonomic and ethno medicinal uses of some Pteridophytes species present in District Bagh AJK, Pakistan. The people of District Bagh extensively use Pteridophytes for different purposes. Ethno botanical evidence and Ornamental Potential of the taxa of wild pteridophytes was documented through field trips during 2017-2018, and data was collected through a structured questionnaire, and in-depth interviews were conducted from the natives in the hilly regions. Total of 22 Pteridophytes belonging to 13 genera 9 families were collected. Out of 22 species, one species (Cystoathyriumchinense ) newly record from Pakistan. The most leading family is Pteridaceae, having 9species, followed by Dryopteridaceae, having 4species, and Aspleniaceae having 3species. The remaining families are represented by single species of each. Inhabitants of mountainous and rural zones regularly used these taxa for different remedy, which are not discussed in the previous available literature. The novel remedies reported in this research areCystoathyriumchinense decoction used for irregular menstruation, Cyclosorusopulentus crushed leaves and stem are used for the treatment of stomach disorder.Onychiumlucidumused to treatJaundice, injury, pain dysentery, common cold, and arresting bleeding. Based on these findings, it is further recommended that phytochemical studies should be conducted to explore active chemical constituents for the cure of various diseases. Conservation efforts must be done to conserve many threatened species of the research area.

Keywords: adiantum, cancer, pakistan, pteridophytes

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Authors: Eric Shannon, Mark J. McGuire, John P. Parmigiani

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A hazard associated with the use of timber harvesters is chain shot. Harvester saw chain is subjected to large dynamic mechanical stresses which can cause it to fracture. The resulting open loop of saw chain can fracture a second time and create a projectile consisting of several saw-chain links referred to as a chain shot. Its high kinetic energy enables it to penetrate operator enclosures and be a significant hazard. Accurate data on projectile composition, mass, and speed are needed for the design of both operator enclosures resistant to projectile penetration and for saw chain resistant to fracture. The work presented here contributes to providing this data through the use of a test machine designed and built at Oregon State University. The machine’s enclosure is a standard shipping container. To safely contain any anticipated chain shot, the container was lined with both 9.5 mm AR500 steel plates and 50 mm high-density polyethylene (HDPE). During normal operation, projectiles are captured virtually undamaged in the HDPE enabling subsequent analysis. Standard harvester components are used for bar mounting and chain tensioning. Standard guide bars and saw chains are used. An electric motor with flywheel drives the system. Testing procedures follow ISO Standard 11837. Chain speed at break was approximately 45.5 m/s. Data was collected using both a 75 cm solid bar (Oregon 752HSFB149) and 90 cm solid bar (Oregon 902HSFB149). Saw chains used were 89 Drive Link .404”-18HX loops made from factory spools. Standard 16-tooth sprockets were used. Projectile speed was measured using both a high-speed camera and a chronograph. Both rotational and translational kinetic energy are calculated. For this study 50 chain shot events were executed. Results showed that projectiles consisted of a variety combinations of drive links, tie straps, and cutter links. Most common (occurring in 60% of the events) was a drive-link / tie-strap / drive-link combination having a mass of approximately 10.33 g. Projectile mass varied from a minimum of 2.99 g corresponding to a drive link only to a maximum of 18.91 g corresponding to a drive-link / tie-strap / drive-link / cutter-link / drive-link combination. Projectile translational speed was measured to be approximately 270 m/s and rotational speed of approximately 14000 r/s. The calculated translational and rotational kinetic energy magnitudes each average over 600 J. This study provides useful information for both timber harvester manufacturers and saw chain manufacturers to design products that reduce the hazards associated with timber harvesting.

Keywords: chain shot, timber harvesters, safety, testing

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Authors: Yogita Tulsian, R. S. Gupta, K. F. Laserson

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Background: Delays in the diagnosis and treatment of TB facilitates disease transmission in the community, so we conducted a study to evaluate the burden of and risk factors for delay in TB diagnosis and initiation of TB treatment among patients in the private and public sectors in Udaipur district, Rajasthan, India. Methods: A retrospective cohort study was conducted among 100 new sputum-positive TB. Patients were interviewed in the intensive phase of treatment September 2013-November 2013 Long total diagnosis delay (TDD) was defined as a time interval between first symptom to confirmed diagnosis > 30 days. Long health treatment delay (HTD) was defined as a time interval between confirmed diagnosis to treatment initiation > 7 days. Results: We observed a median TDD of 55 days (range: 7-136 days) in the public sector and of 92 days (11-380 days) in the private sector. Long TDD in the private sector was significantly associated with middle-higher socio-economic status (Risk Ratio (RR): 2;95% CI: 1.3-3). The reasons reported from the private sector for long TDD were suspect TB patients not advised for sputum examination (RR: 42; 95% CI:2.6-660), practise of self-medication (RR: 17.4; 95% CI: 1.1-267), or lack of awareness (RR: 9.7;95% CI: 0.6-145). The median HTD in the public sector was 3 days (range: 0-14 days), and in the private sector, 2 days (range: 0-11 days) (non-significant difference). Conclusions: Long TDD in private sector may be improved through sputum referral for all suspect TB cases and better education to all regarding TB.

Keywords: diagnosis delay, treatment delay, privatesector, public sector

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Authors: Jhonas Geraldo Peixoto Flauzino, Pedro Pompeo Boechat Araujo, Alexia Allis Rocha Lima, Giovanna Biângulo Lacerda Chaves, Victor Ryan Ferrão Chaves

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Schizophrenia is characterized as a set of psychiatric signs and symptoms (syndrome) that commonly erupt in the stages of adolescence or early adulthood, being recognized as one of the most serious diseases, as it causes important problems during the life of the patient. carrier - both in mental health and in physical health and in social life. Objectives: This is an integrative literature review that aimed to verify what has been produced of scientific knowledge in the field of child and adolescent psychiatry regarding schizophrenia in these stages of life, correlated to the most discussed themes and methodologies of choice for the preparation of studies. Methods: Articles were selected from the following databases: Virtual Health Library and CAPES Journal Portal, published in the last five years; and on Google Scholar, published in 2021, totaling 62 works, searched in September 2021. Results: The studies focus mainly on diagnosis through the DSM-V (25.8%), on drug treatment (25.8%) and in psychotherapy (24.2%), most of them in the literature review format: integrative (27.4%) and systematic (24.2%). Conclusion: The themes and study methods are redundant, and do not cover in depth the immense aspects that encompass Schizophrenia in Childhood and Adolescence, giving attention to the disease in a general way or focusing on the adult patient.

Keywords: schizophrenia, mental health, childhood, adolescence

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Authors: Elena Pucci, Margherita Tufarelli, Leonardo Giliberti

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As central for human and social development of the future, sustainability is becoming a recurring theme also in the fashion industry, where the need to explore new possible directions aimed at achieving sustainability goals and their communication is rising. Scholars have been devoted to the overall environmental impact of the textile and fashion industry, which, emerging as one of the world’s most polluting, today concretely assumes the need to take the path of sustainability in both products and production processes. Every day we witness the impact of our consumption, showing that the sustainability concept is as vast as complex: with a sometimes ambiguous definition, sustainability can concern projects, products, companies, sales, packagings, supply chains in relation to the actors proximity as well as traceability, raw materials procurement, and disposal. However, in its primary meaning, sustainability is the ability to maintain specific values and resources for future generations. The contribution aims to address sustainability in the fashion system as a layered problem that requires substantial changes at different levels: in the fashion product (materials, production processes, timing, distribution, and disposal), in the functioning of the system (life cycle, impact, needs, communication) and last but not least in the practice of fashion design which should conceive durable, low obsolescence and possibly demountable products. Moreover, consumers play a central role for the growing awareness, together with an increasingly strong sensitivity towards the environment and sustainable clothing. Since it is also a market demand, undertaking significant efforts to achieve total transparency and sustainability in all production and distribution processes is becoming fundamental for the fashion system. Sustainability is not to be understood as purely environmental but as the pursuit of collective well-being in relation to conscious production, human rights, and social dignity with the aim to achieve intelligent, resource, and environmentally friendly production and consumption patterns. Assuming sustainability as a layered problem makes the role of communication crucial to convey scientific or production specific content so that people can obtain and interpret information to make related decisions. Hence, if it is true that “what designers make becomes the future we inhabit'', design is facing great and challenging responsibility. The fashion industry needs a system of rules able to assess the sustainability of products, which is transparent and easily interpreted by consumers, identifying and enhancing virtuous practices. There are still complex and fragmented value chains that make it extremely difficult for brands and manufacturers to know the history of their products, to identify exactly where the risks lie, and to respond to the growing demand from consumers and civil society for responsible and sustainable production practices in the fashion industry.

Keywords: fashion design, fashion system, sustainability, communication, complexity

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Authors: L. Joseph, B. Farid, F. Ravelet

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Fundamental studies were performed on bifurcation, instabilities and turbulence in Taylor-Couette flow and applied to many engineering applications like astrophysics models in the accretion disks, shrouded fans, and electric motors. Such rotating machinery performances need to have a better understanding of the fluid flow distribution to quantify the power losses and the heat transfer distribution. The present investigation is focused on high gap ratio of Taylor-Couette flow with high rotational speeds, for smooth and grooved surfaces. So far, few works has been done in a very narrow gap and with very high rotation rates and, to the best of our knowledge, not with this combination with grooved surface. We study numerically the turbulent flow between two coaxial cylinders where R1 and R2 are the inner and outer radii respectively, where only the inner is rotating. The gap between the rotor and the stator varies between 0.5 and 2 mm, which corresponds to a radius ratio η = R1/R2 between 0.96 and 0.99 and an aspect ratio Γ= L/d between 50 and 200, where L is the length of the rotor and d being the gap between the two cylinders. The scaling of the torque with the Reynolds number is determined at different gaps for different smooth and grooved surfaces (and also with different number of grooves). The fluid in the gap is air. Re varies between 8000 and 30000. Another dimensionless parameter that plays an important role in the distinction of the regime of the flow is the Taylor number that corresponds to the ratio between the centrifugal forces and the viscous forces (from 6.7 X 105 to 4.2 X 107). The torque will be first evaluated with RANS and U-RANS models, and compared to empirical models and experimental results. A mesh convergence study has been done for each rotor-stator combination. The results of the torque are compared to different meshes in 2D dimensions. For the smooth surfaces, the models used overestimate the torque compared to the empirical equations that exist in the bibliography. The closest models to the empirical models are those solving the equations near to the wall. The greatest torque achieved with grooved surface. The tangential velocity in the gap was always higher in between the rotor and the stator and not on the wall of rotor. Also the greater one was in the groove in the recirculation zones. In order to avoid endwall effects, long cylinders are used in our setup (100 mm), torque is measured by a co-rotating torquemeter. The rotor is driven by an air turbine of an automotive turbo-compressor for high angular velocities. The results of the experimental measurements are at rotational speed of up to 50 000 rpm. The first experimental results are in agreement with numerical ones. Currently, quantitative study is performed on grooved surface, to determine the effect of number of grooves on the torque, experimentally and numerically.

Keywords: Taylor-Couette flow, high gap ratio, grooved surface, high speed

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Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

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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: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: M. Bouferhane, A. Boukhebza, L. Hatab

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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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Authors: Manal Alosaimi

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Many rehabilitation strategies exist to aid persons with neurological disorders relearn motor skills through intensive training. Evidence supporting the theory that cortical areas involved in motor execution can be triggered by observing actions performed by others is attributed to the function of the mirror neuron system (MNS) indicates that activation of the MNS is associated with improvements in physical action and motor learning. Therefore, it is important to investigate the relationship between motor training (in this case, playing the drums) and the activation of the MNS. To achieve this, 15 healthy right-handed participants received drum-kit training for 21 weeks, during which time blood oxygen level-dependent (BOLD) signals were monitored in the brain using functional magnetic resonance imaging (fMRI). Participants were required to perform action–observation and action–execution fMRI tasks. The main results are that BOLD signals in classical regions of the MNS such as supramarginal gyri, inferior parietal lobule, and supplementary motor area increase significantly over the training period. Activation of these areas indicates that passive-observation of others performing these same skills may facilitate recovery of persons suffering from neurological disorders, and complement conventional rehabilitation programs that focus on action execution or intense training.

Keywords: fMRI, mirror neuron system, magnetic resonance imaging, neuroplasticity, drumming, learning, music, action observation, action execution

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Siddhartha Paul, Debabrata Das

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Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Trung Hieu Tran, Jesse O'Hanley, Russell Fowler

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When in-wheel wireless charging technology for electric vehicles becomes mature, a need for such integrated charging stations network development is essential. In this paper, we thus investigate the optimisation problem of in-wheel wireless electric vehicle charging network design. A mixed-integer linear programming model is formulated to solve into optimality the problem. In addition, a meta-heuristic algorithm is proposed for efficiently solving large-sized instances within a reasonable computation time. A parallel computing strategy is integrated into the algorithm to speed up its computation time. Experimental results carried out on the benchmark instances show that our model and algorithm can find the optimal solutions and their potential for practical applications.

Keywords: electric vehicle, wireless charging station, mathematical programming, meta-heuristic algorithm, parallel computing

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Anjana Aggarwal, Sheilja Walia

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Prevalence of obesity and overweight is increasing due to sedentary lifestyles and busy schedules of people that spend less time on physical exercise. To reduce weight, people are finding easier and more convenient ways. The easiest solution is the use of dietary supplements and fat burners. These are products that decrease body weight by increasing the basal metabolic rate. Various reports have been published on the consumption of fat burners leading to heart palpitations, seizures, anxiety, depression, psychosis, bradycardia, insomnia, muscle contractions, hepatotoxicity, and even liver failure. Case reports and series are reporting that the ingredients present in the fat burners caused acute liver failure (ALF) and hepatic toxicity in many cases. Another contributing factor is the absence of regulations from the Food and Drug Administration on these products, leading to increased consumption and a higher risk of liver diseases among the population. This systematic review aims to attain a better understanding of the dietary supplements used globally to reduce weight and document the case reports/series of acute liver failure caused by the consumption of fat burners. Electronic databases like PubMed, Cochrane, Google Scholar, etc., will be systematically searched for relevant articles. Various websites of dietary products and brands that sell such supplements, Journals of Hepatology, National and international projects launched for ALF, and their reports, along with the review of grey literature, will also be done to get a better understanding of the topic. After discussing with the co-author, the selection and screening of the articles will be performed by the author. The studies will be selected based on the predefined inclusion and exclusion criteria. The case reports and case series that will be included in the final list of the studies will be assessed for methodological quality using the CARE guidelines. The results from this study will provide insights and a better understanding of fat burners. Since the supplements are easily available in the market without any restrictions on their sale, people are unaware of their adverse effects. The consumption of these supplements causes acute liver failure. Thus, this review will provide a platform for future larger studies to be conducted.

Keywords: acute liver failure, dietary supplements, fat burners, weight loss supplements

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Authors: Y. N. Fung, R. Liu, T. M. Choi

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Over the past decades, previous studies have explored different consumers’ attitudes towards sustainable fashion and how these attitudes affect consumer behaviors. Researchers have attempted to provide solutions for product suppliers (e.g., retailers, designers, developers, and manufacturers) through studying consumers’ attitudes towards sustainable fashion. However, based on the studies of consumer attitudes, investigations on the sales and market share of sustainable sportswear products remain under-explored. Gaps may exist between the consumers’ expectations and the developed sustainable sportswear products. In this study, a novel study has been carried out to examine the attitude gaps existing between the sustainable sportswear suppliers’ (SSSs) and the sustainable sportswear consumers (SSCs). This study firstly identifies the key attitudes towards sustainable sportswear product development. It analyses how sustainable attitudes affect the products being developed, as well as the effects of the attitude’s difference between the SSSs and the SSCs on the consumers’ satisfaction towards sportswear product consumption. A gap analysis research framework is adopted with the use of collected questionnaire survey data. The results indicate that a significant difference exists between SSSs and SSCs’ attitudes towards sustainable design, manufacture, product features, and branding. Based on in-depth interviews, the major causes of the difference in attitudes are studied to provide managerial insights for sustainable sportswear product management and business development.

Keywords: sustainability, sportswear, attitude, gap analysis, suppliers, consumers

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Authors: Massimo Ferrari, Maria Sole Pagliari

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Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: Francisco Pedroza-Montero, Jesús Naín Pedroza-Montero, Diego Soto-Puebla, Osiris Alvarez-Bajo, Beatriz Castaneda, Sofía Navarro-Espinoza, Martín Pedroza-Montero

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Nanodiamonds have been widely studied for their physical properties, including chemical inertness, biocompatibility, optical transparency from the ultraviolet to the infrared region, high thermal conductivity, and mechanical strength. In this work, we studied how the fluorescence spectrum of nanodiamonds quenches concerning the concentration in aqueous solutions systematically ranging from 0.1 to 10 mg/mL. Our results demonstrated a non-linear fluorescence quenching as the concentration increases for both of the NV zero-phonon lines; the 5 mg/mL concentration shows the maximum fluorescence emission. Furthermore, this behaviour is theoretically explained as an electronic recombination process that modulates the intensity in the NV centres. Finally, to gain more insight, the FRET methodology is used to determine the fluorescence efficiency in terms of the fluorophores' separation distance. Thus, the concentration level is simulated as follows, a small distance between nanodiamonds would be considered a highly concentrated system, whereas a large distance would mean a low concentrated one. Although the 5 mg/mL concentration shows the maximum intensity, our main interest is focused on the concentration of 0.5 mg/mL, which our studies demonstrate the optimal human cell viability (99%). In this respect, this concentration has the feature of being as biocompatible as water giving the possibility to internalize it in cells without harming the living media. To this end, not only can we track nanodiamonds on the surface or inside the cell with excellent precision due to their fluorescent intensity, but also, we can perform thermometry tests transforming a fluorescence contrast image into a temperature contrast image.

Keywords: nanodiamonds, fluorescence spectroscopy, concentration, bioimaging, thermometry

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Authors: Hyungoo Kang, Minsung Kim, Jinkoo Kim

Abstract:

This study investigates the performance of a 2D and 3D steel moment frame subjected to vehicle collision at a first story column using LS-DYNA. The finite element models of vehicles provided by the National Crash Analysis Center (NCAC) are used for numerical analysis. Nonlinear dynamic time history analysis of the 2D and 3D model structures are carried out based on the arbitrary column removal scenario, and the vertical displacement of the damaged structures are compared with that obtained from collision analysis. The analysis results show that the model structure remains stable when the speed of the vehicle is 40km/h. However, at the speed of 80 and 120km/h both the 2D and 3D structures collapse by progressive collapse. The vertical displacement of the damaged joint obtained from collision analysis is significantly larger than the displacement computed based on the arbitrary column removal scenario.

Keywords: vehicle collision, progressive collapse, FEM, LS-DYNA

Procedia PDF Downloads 327