Search results for: flexible slider crank mechanism

Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: support vector mechanism (SVM), machine learning (ML), support vector machines (SVM), department of transportation (DFT)

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Authors: Md. Afroz Ansari

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The Bengal basin is a spectacular example of a peripheral foreland basin formed by the convergence of the Indian plate beneath the Eurasian and Burmese plates. The basin is embraced on three sides; north, west and east by different fault-controlled tectonic features whereas released in the south where the rivers are drained into the Bay of Bengal. The Bengal basin in the eastern part of the Indian subcontinent constitutes the largest fluvio-deltaic to shallow marine sedimentary basin in the world today. This continental basin coupled with the offshore Bengal Fan under the Bay of Bengal forms the biggest sediment dispersal system. The continental basin is continuously receiving the sediments by the two major rivers Ganga and Brahmaputra (known as Jamuna in Bengal), and Meghna (emerging from the point of conflux of the Ganga and Brahmaputra) and large number of rain-fed, small tributaries originating from the eastern Indian Shield. The drained sediments are ultimately delivered into the Bengal fan. The significance of the present study is to delineate the variations in thicknesses of the sediments, different crustal structures, and the mantle lithosphere throughout the onshore-offshore Bengal basin. In the present study, the different crustal/geological units and the shallower mantle lithosphere were delineated by analyzing the Bouguer Gravity Anomaly (BGA) data along two long traverses South-North (running from Bengal fan cutting across the transition offshore-onshore of the Bengal basin and intersecting the Main Frontal Thrust of India-Himalaya collision zone in Sikkim-Bhutan Himalaya) and West-East (running from the Peninsular Indian Shield across the Bengal basin to the Chittagong–Tripura Fold Belt). The BGA map was derived from the analysis of topex data after incorporating Bouguer correction and all terrain corrections. The anomaly map was compared with the available ground gravity data in the western Bengal basin and the sub-continents of India for consistency of the data used. Initially, the anisotropy associated with the thicknesses of the different crustal units, crustal interfaces and moho boundary was estimated through spectral analysis of the gravity data with varying window size over the study area. The 2D density sections along the traverses were finalized after a number of iterations with the acceptable root mean square (RMS) errors. The estimated thicknesses of the different crustal units and dips of the Moho boundary along both the profiles are consistent with the earlier results. Further the results were encouraged by examining the earthquake database and focal mechanism solutions for better understanding the geodynamics. The earthquake data were taken from the catalogue of US Geological Survey, and the focal mechanism solutions were compiled from the Harvard Centroid Moment Tensor Catalogue. The concentrations of seismic events at different depth levels are not uncommon. The occurrences of earthquakes may be due to stress accumulation as a result of resistance from three sides.

Keywords: anisotropy, interfaces, seismicity, spectrum analysis

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Authors: Aliyu Damri

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This study analyzed the emergence of WhatsApp and how employees at the Federal Radio Corporation of Nigeria, Kaduna defined the concept base on their vast broadcasting experiences for over five decades and application of the phenomenon to the radio station. It also analyzed the nature, patterns, dimensions, features, challenges as well as the effects of WhatsApp as a social networking site with specific interest on the radio outlet. Also, the study identified how the radio organization responded to the challenges in an attempt to adapt to the new pattern of broadcasting characterized by many technological transformations. The study further explained in details such skills journalists need to function optimally using WhatsApp as well as the impacts of the WhatsApp on radio broadcasting. It used a combination of published materials, focus group discussion, in depth interviews and participant observation on the activities of the radio stations to address the research questions. The data generated provided insight to better understand the challenges posed to FRCN Kaduna as a result of WhatsApp application and how FRCN Kaduna responded to the challenges. It also provided information on the skills journalists need to function optimally in using WhatsApp application in the radio station. The interview and focus group discussion’s transcripts and the published materials were analyzed along thematic pattern related to the research questions in the study. The dominant response relied heavily on change in the radio station’s organizational and technical integration of newsrooms, the use of a multiskilled workforce, application of a flexible and user-friendly technology in all aspects of production, expansion of the station’s services in to new media such as internet and mobile phones as well as sharing of ideas across different units in the radio outfit.

Keywords: broadcasting, challenge, northern Nigeria, radio, WhatsApp application

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Authors: Rosyidah Muhamad

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Democracies are premised on the idea that citizens can hold their leaders accountable for their actions by voting for or against them in regular elections. However, in order this ideal to be realized, citizens must possess a minimum amount of information about their leaders’ performance. Citizens should be made aware of the performance of their elected representatives. This study seeks to analyse this critical information with special reference to Malaysian Parliamentarians (MPs). We adopted several existence Parliamentary Performance model with special reference to their performance inside the parliament. Among indicators used by the Scholastic for analysing this performance are the number of bills proposed by parliamentarian, the number of proposals that would benefit their constituency, the number of speeches made by the parliamentarian during plenary and the percentage of laws passed among the proposals made by certain parliamentary. The broad goals of the study include the analysis of the capacity of a representative body to accommodate the diverse claims and demands that are made on it. We find that overall performances of MPs are average. This is due to not only the background characteristic of individuals MPs but also the limitation of the mechanism provides in the Parliament itself.

Keywords: member of parliament, democracy, evaluation, Malaysia

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Authors: Zohreh Afsharmand, Sokhanguei Yahya

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A growing body of literature suggests that that low-grade systemic inflammation associated to obesity plays a key role in the pathogenic mechanism of several disorders. In this study, the effect of 6 weeks aerobic training on IL-6 and IL-1B as inflammatory cytokine were investigated in adult obese women. For this purpose, 26 sedentary adult obese women were divided into exercise and control groups (n=12). Pre and post training of mentioned cytokines were measured in two groups. Student’s t-tests for paired samples were performed to determine whether there were significant within-group changes in the outcomes. A p value less than 0.05 was considered statistically significant. There were no statistically significant differences between the exercise and control groups with regard to anthropometrical markers or inflammatory cytokines. Despite the significant decrease in all anthropometrical markers, no significant differences were found in serum IL-6 and IL-1B by aerobic training with compared to baseline. Our findings indicate that aerobic training intervention for a short time is not associated with the anti-inflammatory property in obese women.

Keywords: aerobic training, cytokine, inflammation, obesity

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Olushola S. Ayanda, Olalekan S. Fatoki, Folahan A. Adekola, Bhekumusa J. Ximba, Cecilia O. Akintayo

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In the present study, the kinetics, equilibrium and thermodynamics of the adsorption of triphenyltin (TPT) from TPT-contaminated water onto nanoSiO2/fly ash/activated carbon composite was investigated in batch adsorption system. Equilibrium adsorption data were analyzed using Langmuir, Freundlich, Temkin and Dubinin–Radushkevich (D-R) isotherm models. Pseudo first- and second-order, Elovich and fractional power models were applied to test the kinetic data and in order to understand the mechanism of adsorption, thermodynamic parameters such as ΔG°, ΔSo and ΔH° were also calculated. The results showed a very good compliance with pseudo second-order equation while the Freundlich and D-R models fit the experiment data. Approximately 99.999 % TPT was removed from the initial concentration of 100 mg/L TPT at 80oC, contact time of 60 min, pH 8 and a stirring speed of 200 rpm. Thus, nanoSiO2/fly ash/activated carbon composite could be used as effective adsorbent for the removal of TPT from contaminated water and wastewater.

Keywords: isotherm, kinetics, nanoSiO₂/fly ash/activated carbon composite, tributyltin

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Anuj Kumar Vaksha

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The research paper examines the trends and approaches of the international investment arbitral tribunals to the issues of environment and the exercise of states' regulatory power for the preservation of environment vis-à-vis the rights of the affected foreign investors. The paper analyses arbitral awards, decisions and orders in the leading cases of international investment arbitrations involving issues of environment and finds that there has been strong trend among the arbitral tribunals to balance the imperatives of the environmental regulation and the interest of the foreign investors. The arbitral tribunals have reflected deference to States' competence for regulation of environment to the extent they were genuine, relevant and in proportion to the legitimate objective sought to be achieved. The arbitral tribunals have at times been innovative and non-conservative in promoting the cause of environment through the mechanism of investor-state arbitration.

Keywords: International Investment Arbitration, environmental regulations, bilateral investment treaties, ICSID, NAFTA, amicus curiae, pollution havens hypothesis, environmental race to the bottom hypothesis

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Authors: Mahsa Fathollahzadeh

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The various nanoparticles employed in drug delivery applications include micelles, liposomes, solid lipid nanoparticles, polymeric nanoparticles, functionalized nanoparticles, nanocrystals, cyclodextrins, dendrimers, and nanotubes. Micelles, composed of amphiphilic block copolymers, can encapsulate hydrophobic molecules, allowing for targeted delivery. Liposomes, vesicular structures made up of phospholipids, can encapsulate both hydrophobic and hydrophilic molecules, providing a flexible platform for delivering therapeutic agents. Solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are designed to improve the stability and bioavailability of lipophilic drugs. Polymeric nanoparticles, such as poly(lactic-co-glycolic acid) (PLGA), are biodegradable and can be engineered to release drugs in a controlled manner. Functionalized nanoparticles, coated with targeting ligands or antibodies, can specifically target diseased cells or tissues. Nanocrystals, engineered to have specific surface properties, can enhance the solubility and bioavailability of poorly soluble drugs. Cyclodextrins, doughnut-shaped molecules with hydrophobic cavities, can be complex with hydrophobic molecules, allowing for improved solubility and bioavailability. Dendrimers, branched polymers with a central core, can be designed to deliver multiple therapeutic agents simultaneously. Nanotubes and metallic nanoparticles, such as gold nanoparticles, offer real-time tracking capabilities and can be used to detect biomolecular interactions. The use of these nanoparticles has revolutionized the field of drug delivery, enabling targeted and controlled release of therapeutic agents, reduced toxicity, and improved patient outcomes.

Keywords: nanotechnology, nanopharmaceuticals, drug-delivery, proteins, ligands, nanoparticles, chemistry

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Authors: P. Valsalal, S. Thangalakshmi

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There is a widespread changeover in the electrical power industry universally from old-style monopolistic outline towards a horizontally distributed competitive structure to come across the demand of rising consumption. When the transmission lines of derestricted system are incapable to oblige the entire service needs, the lines are overloaded or congested. The governor between customer and power producer is nominated as Independent System Operator (ISO) to lessen the congestion without obstructing transmission line restrictions. Among the existing approaches for congestion management, the frequently used approaches are reorganizing the generation and load curbing. There is a boundary for reorganizing the generators, and further loads may not be supplemented with the prevailing resources unless more private power producers are added in the system by considerably raising the cost. Hence, congestion is relaxed by appropriate Flexible AC Transmission Systems (FACTS) devices which boost the existing transfer capacity of transmission lines. The FACTs device, namely, Unified Power Flow Controller (UPFC) is preferred, and the correct placement of UPFC is more vital and should be positioned in the highly congested line. Hence, the weak line is identified by using power flow performance index with the new objective function with proposed hybrid Fish – Bee algorithm. Further, the location of UPFC at appropriate line reduces the branch loading and minimizes the voltage deviation. The power transfer capacity of lines is determined with and without UPFC in the identified congested line of IEEE 30 bus structure and the simulated results are compared with prevailing algorithms. It is observed that the transfer capacity of existing line is increased with the presented algorithm and thus alleviating the congestion.

Keywords: available line transfer capability, congestion management, FACTS device, Hybrid Fish-Bee Algorithm, ISO, UPFC

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Authors: Charles Amoo, Joshua New, Bill Eckman

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Buildings in the United States account for a significant proportion of energy consumption and greenhouse gas (GHG) emissions, and this trend is expected to continue as well as rise in the near future. Low-income households, in particular, bear a disproportionate burden of high building energy consumption and spending due to high energy costs. Energy efficiency improvements need to reach an average of 4% per year in this decade in order to meet global net zero emissions target by 2050, but less than 1 % of U.S. buildings are improved each year. The government has recognized the importance of technology in addressing this issue, and energy efficiency programs have been developed to tackle the problem. The Weatherization Assistance Program (WAP), the largest residential whole-house energy efficiency program in the U.S., is specifically designed to reduce energy costs for low-income households. Under the WAP, energy auditors must follow specific audit procedures and use Department of Energy (DOE) approved energy audit tools or software. This article proposes an expanded framework of factors that should be considered in energy audit software that is approved for use in energy efficiency programs, particularly for low-income households. The framework includes more than 50 factors organized under 14 assessment criteria and can be used to qualitatively and quantitatively score different energy audit software to determine their suitability for specific energy efficiency programs. While the tool can be useful for developers to build new tools and improve existing software, as well as for energy efficiency program administrators to approve or certify tools for use, there are limitations to the model, such as the lack of flexibility that allows continuous scoring to accommodate variability and subjectivity. These limitations can be addressed by using aggregate scores of each criterion as weights that could be combined with value function and direct rating scores in a multicriteria decision analysis for a more flexible scoring.

Keywords: buildings, energy efficiency, energy audit, software

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Authors: Piotr Prewysz-Kwinto

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A dynamic development of financial market is accompanied by the emergence of new products on stock exchanges which give absolutely new possibilities of investing money. Currently, the most innovative financial instruments offered to investors are exchange traded products (ETP). They can be defined as financial instruments whose price depends on the value of the underlying instrument. Thus, they offer investors a possibility of making a profit that results from the change in value of the underlying instrument without having to buy it. Currently, the Warsaw Stock Exchange offers many types of ETPs. They are investment products with full or partial capital protection, products without capital protection as well as leverage products, issued on such underlying instruments as indices, sector indices, commodity indices, prices of energy commodities, precious metals, agricultural produce or prices of shares of domestic and foreign companies. This paper presents the mechanism of functioning of ETP available on the Warsaw Stock Exchange and the results of the analysis of statistical data on these financial instruments.

Keywords: exchange traded products, financial market, investment, stock exchange

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Authors: Dandan Shen, Hui-zhu Wang, Xi Yu, LiLi Gui, Xiao Wei, Xiao-yan Jiang, Da-wei Wang, Min Hong

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Yu-ping-feng-san (YPFS) is a clinical medicine for asthma and other allergic diseases, but the mechanism of YPFS on relapse of allergy is unclear. Currently, people come to realize the epithelial cells(EC) play a key role in stimulating and regulating local immune response. The study of thymic stromal lymphopoietin（TSLP derived from EC provides an important evidence that the EC can regulate immune response to stimulate allergic response. In this study, we observed the effect of YPFS on TSLP in vivo and in vitro. We established a method by using bronchial epithelial cells (16HBE) for screening potential bioactive components by HPLC-MS in YPFS and then analyzed the components in serum containing YPFS by UPLC-MS. The results showed that YPFS could decrease TSLP protein level in OVA-sensitized mice and 16HBE cells. Five components combing with the 16HBE cells were both detected in the serum.

Keywords: TSLP, bronchial epithelial cells, cell-binding, drug-containing serum

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Authors: Debarag Banerjee, Pooja Singh, Arjun Avadhanam, Saksham Srivastava

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Autonomous conversational agents, i.e., chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbots, especially ones powered by Generative AI tools like Large Language Models (LLMs), we need to be able to accurately assess their performance. This is where chatbot benchmarking becomes important. In this paper, authors propose the use of a benchmark that they call the E2E (End to End) benchmark and show how the E2E benchmark can be used to evaluate the accuracy and usefulness of the answers provided by chatbots, especially ones powered by LLMs. The authors evaluate an example chatbot at different levels of sophistication based on both our E2E benchmark as well as other available metrics commonly used in the state of the art and observe that the proposed benchmark shows better results compared to others. In addition, while some metrics proved to be unpredictable, the metric associated with the E2E benchmark, which uses cosine similarity, performed well in evaluating chatbots. The performance of our best models shows that there are several benefits of using the cosine similarity score as a metric in the E2E benchmark.

Keywords: chatbot benchmarking, end-to-end (E2E) benchmarking, large language model, user centric evaluation.

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Authors: Roohollah Jamshidpour, Elaheh Ahmadi, Farhad Shah Veisi

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Present research seeks to answer this question: Is there any relationship between corporate governance mechanisms and decision on corporate investments? Percentages of institutional, board of director’s, and stockholder’s ownership are among internal mechanisms of corporate governance relationship of which with investment-based decisions are studied by this research. Information on 103 companies during 1388 (2009)- 1393 (2014). Initially, research variables are identified; next, Rah Avard-e Novin software is used to gather Information. SPSS software is employed to test hypotheses with respect to descriptive and inferential statistics like correlation analysis. Research results show that percentage of institutional stockholders’ ownership has a significant direct relationship with investment decisions. For other cases, no significant relationship is observed between corporate governance mechanisms and investment decisions.

Keywords: corporate governance, company size, free floating stock, institutional investors, major shareholders

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Authors: Bassam Istanbouli

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With the technology evolving every day and with the increase in global competition, industries are always under the pressure to be the best. They need to provide good quality products at competitive prices, when and how the customer wants them.  In order to achieve this level of service, products and their respective supply chain processes need to be flexible and evolvable; otherwise changes will be extremely expensive, slow and with many combinatorial effects. Those combinatorial effects impact the whole organizational structure, from a management, financial, documentation, logistics and specially the information system Enterprise Requirement Planning (ERP) perspective. By applying the normalized system concept/theory to segments of the supply chain, we believe minimal effects, especially at the time of launching an organization global software project. The purpose of this paper is to point out that if an organization wants to develop a software from scratch or implement an existing ERP software for their business needs and if their business processes are normalized and modular then most probably this will yield to a normalized and modular software system that can be easily modified when the business evolves. Another important goal of this paper is to increase the awareness regarding the design of the business processes in a software implementation project. If the blueprints created are normalized then the software developers and configurators will use those modular blueprints to map them into modular software. This paper only prepares the ground for further studies;  the above concept will be supported by going through the steps of developing, configuring and/or implementing a software system for an organization by using two methods: The Software Development Lifecycle method (SDLC) and the Accelerated SAP implementation method (ASAP). Both methods start with the customer requirements, then blue printing of its business processes and finally mapping those processes into a software system.  Since those requirements and processes are the starting point of the implementation process, then normalizing those processes will end up in a normalizing software.

Keywords: blueprint, ERP, modular, normalized

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Authors: Prafulla Kumar Choubey, Krishna Kishor Jha, S. B. Vaisakh Punnekkattu Chirayil

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In Graphics-display subsystem, frame buffers are shared between producer i.e. content rendering and consumer i.e. display. If a common buffer is operated by both producer and consumer simultaneously, their processing rates mismatch can cause tearing effect in displayed content. Therefore, Android OS employs triple buffered system, taking in to account an additional composition stage. Three stages-rendering, composition and display refresh, operate synchronously on three different buffers, which is achieved by using vsync pulses. This synchronization, however, brings in to the pipeline an additional latency of up to 26ms. The present study details about the existing synchronization mechanism of android graphics-display pipeline and discusses a new adaptive architecture which reduces the wait time to 5ms-16ms in all the use-cases. The proposed method uses two adaptive software vsyncs (PLL) for achieving the same result.

Keywords: Android graphics system, vertical synchronization, atrace, adaptive system

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Authors: Pia Kastl

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By combining face-to-face sessions with digital selflearning units, the learning process can be enhanced and learning success improved. Potentials of blended learning are the flexibility and possibility to get in touch with lecturers and fellow students face-toface. It also offers the opportunity to individualize and self-regulate the learning process. Aim of this article is to analyse how different learning environments affect students’ learning behavior and how digital tools can be used effectively. The analysis also considers the extent to which the field of study affects the students’ preferences. Semi-structured interviews were conducted with students from different disciplines at two German universities (N= 60). The questions addressed satisfaction and perception of online, faceto-face and blended learning courses. In addition, suggestions for improving learning experience and the use of digital tools in the different learning environments were surveyed. The results show that being present on campus has a positive impact on learning success and online teaching facilitates flexible learning. Blended learning can combine the respective benefits, although one challenge is to keep the time investment within reasonable limits. The use of digital tools differs depending on the subject. Medical students are willing to use digital tools to improve their learning success and voluntarily invest more time. Students of the humanities and social sciences, on the other hand, are reluctant to invest additional time. They do not see extra study material as an additional benefit their learning success. This study illustrates how these heterogenous demands on learning environments can be met. In addition, potential for improvement will be identified in order to foster both learning process and learning success. Learning environments can be meaningfully enriched with digital elements to address student diversity in higher education.

Keywords: blended learning, higher education, diversity, learning styles

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Nastaran Soltani

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Heavy metals such as Mercury are toxic elements that enter the environment through different ways and endanger the environment, plants, animals, and humans’ health. Microbial activities reduce the amount of heavy metals. Therefore, an effective mechanism to eliminate heavy metals in the nature and factory slops, is using bacteria living in polluted areas. Karun River in Khuzestan Province in Iran has been always polluted by heavy metals as it is located among different industries in the region. This study was performed based on the data from sampling water and sediments of four stations across the river during the four seasons of a year. The isolation of resistant bacteria was performed through enrichment and direct cultivation in a solid medium containing mercury. Various bacteria such as Pseudomonas sp., Serratia Marcescens, and E.coli were identified as mercury-resistant bacteria. The power of these bacteria to remove mercury varied from 28% to 86%, with strongest power belonging to Pseudomonas sp. isolated in spring making a good candidate to be used for mercury biological removal from factory slops.

Keywords: bacteria, Karun River, mercury, biological removal, mercury-resistant

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Mohammed Auwal Ibrahim, Aminu Mohammed

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Stigmasterol has previously been reported to possess antitrypanosomal activity using in vitro and in vivo models. However, the mechanism of antitrypanosomal activity is yet to be elucidated. In the present study, molecular docking was used to decipher the mode of interaction and binding affinity of stigmasterol to three known antitrypanosomal drug targets viz; adenosine kinase, ornithine decarboxylase and triose phosphate isomerase. Stigmasterol was found to bind to the selected trypanosomal enzymes with minimum binding energy of -4.2, -6.5 and -6.6 kcal/mol for adenosine kinase, ornithine decarboxylase, and triose phosphate isomerase respectively. However, hydrogen bond was not involved in the interaction of stigmasterol with all the three enzymes, but hydrophobic interaction seemed to play a vital role in the binding phenomenon which was predicted to be non-competitive like type of inhibition. It was concluded that binding to the three selected enzymes, especially triose phosphate isomerase, might be involved in the antitrypanosomal activity of stigmasterol but not mediated via a hydrogen bond interaction.

Keywords: antitrypanosomal, in silico, molecular docking, stigmasterol

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Authors: Li Xu, Yang Hong, T. Zhao Wen

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Experimental results of many RC beam-column subassemblage indicate that slippage of longitudinal beam rebar within the joint and the shear deformation of joint core have significant influence on seismic behavior of the subassemblage. However, rigid joint assumption has been generally used in the seismic response analysis of RC frames, in which two kinds of inelastic deformation of joint have been ignored. Based on OpenSees platform, ‘Super Joint Element Model’ with more detailed inelastic mechanism is used to simulate the inelastic response of joints. Two finite element models of typical RC plane frame, namely considering or ignoring the inelastic deformation of joint respectively, were established and analyzed under seven strong earthquake waves. The simulated global and local inelastic deformations of the RC plane frame is shown and discussed. The analyses also confirm the security of the earthquake-resistant frame designed according to Chinese codes.

Keywords: frame structure, beam-column joint, longitudinal bar slippage, shear deformation, nonlinear analysis

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Authors: T. Gayen

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Although, there are several software reliability models existing today there does not exist any versatile model even today which can be used for the reliability assessment of software. Complex software has a large number of states (unlike the hardware) so it becomes practically difficult to completely test the software. Irrespective of the amount of testing one does, sometimes it becomes extremely difficult to assure that the final software product is fault free. The Black Box Software Reliability models are found be quite uncertain for the reliability assessment of various systems. As mission critical applications need to be highly reliable and since it is not always possible to ensure the development of highly reliable system. Hence, in order to achieve fault-free operation of software one develops some mechanism to handle faults remaining in the system even after the development. Although, several such techniques are currently in use to achieve fault tolerance, yet these mechanisms may not always be very suitable for various systems. Hence, this discussion is focused on analyzing the issues and challenges faced with the existing techniques for reliability assessment and fault tolerance of various software systems.

Keywords: black box, fault tolerance, failure, software reliability

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Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

Abstract:

The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

Procedia PDF Downloads 501

Authors: Sonia A. Stoica, Lexi Frankel, Amalia Ardeljan, Selena Rashid, Ali Yasback, Omar Rashid

Abstract:

Introduction Enterococcus is a vast genus of lactic acid bacteria, gram-positivecocci species. They are common commensal organisms in the intestines of humans: E. faecalis (90–95%) and E. faecium (5–10%). Rare groups of infections can occur with other species, including E. casseliflavus, E. gallinarum, and E. raffinosus. The most common infections caused by Enterococcus include urinary tract infections, biliary tract infections, subacute endocarditis, diverticulitis, meningitis, septicemia, and spontaneous bacterial peritonitis. The treatment for sensitive strains of these bacteria includes ampicillin, penicillin, cephalosporins, or vancomycin, while the treatment for resistant strains includes daptomycin, linezolid, tygecycline, or streptogramine. Enterococcus faecalis CECT7121 is an encouraging nominee for being considered as a probiotic strain. E. faecalis CECT7121 enhances and skews the profile of cytokines to the Th1 phenotype in situations such as vaccination, anti-tumoral immunity, and allergic reactions. It also enhances the secretion of high levels of IL-12, IL-6, TNF alpha, and IL-10. Cytokines have been previously associated with the development of cancer. The intention of this study was to therefore evaluate the correlation between Enterococcus infections and incidence of bone carcinoma. Methods A retrospective cohort study (2010-2019) was conducted through a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using International Classification of Disease (ICD) 9th and 10th codes for bone carcinoma diagnosis in a previously Enterococcus infected population. Patients were matched for age range and Charlson Comorbidity Index (CCI). Access to the database was granted by Holy Cross Health for academic research. Chi-squared test was used to assess statistical significance. Results A total number of 17,056 patients was obtained in Enterococcus infected group as well as in the control population (matched by Age range and CCI score). Subsequent bone carcinoma development was seen at a rate of 1.07% (184) in the Enterococcal infectious group and 3.42% (584) in the control group, respectively. The difference was statistically significant by p= 2.2x10-¹⁶, Odds Ratio = 0.355 (95% CI 0.311 - 0.404) Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 78 out of 6,624 (1.17%) patients with a prior enterococcus infection and treated with antibiotics were compared to 202 out of 6,624 (3.04%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed bone carcinoma. Results remained statistically significant (p<2.2x10-), Odds Ratio=0.456 (95% CI 0.396-0.525). Conclusion This study shows a statistically significant correlation between Enterococcus infection and a decreased incidence of bone carcinoma. The immunologic response of the organism to Enterococcus infection may exert a protecting mechanism from developing bone carcinoma. Further exploration is needed to identify the potential mechanism of Enterococcus in reducing bone carcinoma incidence.

Keywords: anti-tumoral immunity, bone carcinoma, enterococcus, immunologic response

Procedia PDF Downloads 179

Authors: Prakash Singh

Abstract:

Employees who are satisfied at their place of work rate their leaders’ intrapersonal competencies as being high. They also believe that a leader’s intrapersonal competencies influence their sense of job satisfaction. Employees who indicate that they are unhappy at their place of work rate their leaders’ intrapersonal competencies as being low. They also believe that a leader’s intrapersonal intelligence influence their feeling of job satisfaction. The leader’s appropriate intrapersonal competencies are crucial to the creation of a motivated and satisfied employee team. In this study, the quantitative research method was used to determine the employees’ perceptions of their leaders’ intrapersonal competencies and their influence on their job satisfaction; the six competencies being self-awareness, self-confidence, self-expression, self-control, adaptability, and optimism. All the competencies of leaders identified in this quantitative study can therefore be described as intervening variables that influence an employee’s sense of job satisfaction. The number of responses that indicate that each of the intrapersonal competencies of a leader that will have an influence on an employee’s sense of job satisfaction, ranges from 93% (a leader’s sense of self-awareness) to 99% (a leader’s ability to be adaptable). As the responses are significantly similar, it can be stated that the respondents indicate that all the intrapersonal competencies of a leader can influence an employee’s sense of job satisfaction. The findings of this study strongly suggest that in order to be satisfied at work, employees prefer to be led by leaders who are confident in their leadership roles; who send out clear, unambiguous messages; who maintain self-control; who are adaptable and flexible;, who face the future with optimism and who support the establishment of a collegial working environment. Evidently, the findings corroborate the hypothesis that employees believe that the intrapersonal competencies of leaders have a positive influence on the employees’ sense of job satisfaction. This study’s findings, therefore, confirm that the key to the leaders’ self-knowledge is access to their own feelings and the ability to discriminate among them and draw upon them to guide behaviour in their organisations. This exploratory study makes a contribution to the emerging research being accomplished on leaders’ intrapersonal intelligence with more research still needing to be attempted to determine to what extent these competencies of leaders can reshape the organizational climate and culture.

Keywords: emotional intelligence, employees’ job satisfaction, leaders’ intrapersonal competencies, leaders’ self-knowledge

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Authors: Hassam Muazzam

Abstract:

This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

Procedia PDF Downloads 409