Search results for: multi pass weld

Authors: Ridwan Dewayanto Rusli

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We show how prisoner's dilemma-type competition problems can be mitigated through rapid platform diversification and ecosystem expansion. We analyze a ride-hailing company in Southeast Asia, Gojek, whose network grew to more than 170 million users comprising consumers, partner drivers, merchants, and complementors within a few years and has already achieved higher contribution margins than ride-hailing peers Uber and Lyft. Its ecosystem integrates ride-hailing, food delivery and logistics, merchant solutions, e-commerce, marketplace and advertising, payments, and fintech offerings. The company continues growing its network of complementors and App developers, expanding content and gaining critical mass in consumer data analytics and advertising. We compare the company's growth and diversification trajectory with those of its main international rivals and peers. The company's rapid growth and future potential are analyzed using Cusumano's (2012) Staying Power and Six Principles, Hax and Wilde's (2003) and Hax's (2010) The Delta Model as well as Santos' (2016) home-market advantages frameworks. The recently announced multi-billion-dollar merger with one of Southeast Asia's largest e-commerce majors lends additional support to the above arguments.

Keywords: ride-hailing, prisoner's dilemma, platform and ecosystem strategy, digital applications, diversification, home market advantages, e-commerce

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Ibrahim Tiryakioglu, Mehmet Ali Ugur, Caglar Ozkaymak

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The development of GNSS technology has led to increasingly widespread and successful applications of GNSS surveys for monitoring crustal movements. However, multi-period GPS survey solutions have not been applied in monitoring vertical surface deformation. This study uses long-term GNSS time series that are required to determine vertical deformations. In recent years, the surface deformations that are parallel and semi-parallel to Bolvadin fault have occurred in Western Anatolia. These surface deformations have continued to occur in Bolvadin settlement area that is located mostly on alluvium ground. Due to these surface deformations, a number of cracks in the buildings located in the residential areas and breaks in underground water and sewage systems have been observed. In order to determine the amount of vertical surface deformations, two continuous GNSS stations have been established in the region. The stations have been operating since 2015 and 2017, respectively. In this study, GNSS observations from the mentioned two GNSS stations were processed with GAMIT/GLOBK (GNSS Analysis Massachusetts Institute of Technology/GLOBal Kalman) program package to create a coordinate time series. With the time series analyses, the GNSS stations’ behavior models (linear, periodical, etc.), the causes of these behaviors, and mathematical models were determined. The study results from the time series analysis of these two 2 GNSS stations shows approximately 50-80 mm/yr vertical movement.

Keywords: Bolvadin fault, GAMIT, GNSS time series, surface deformations

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Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

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In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

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Authors: Marcela Jelicova, Anna Lierova, Zuzana Sinkorova, Radovan Metelka

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At present, electrochemical methods are used in various research fields, especially for analysis of biological molecules. The fact offers the possibility of using the detection of oxidative damage induced indirectly by γ rays in DNA in biodosimentry. The main goal of our study is to optimize the detection of 8-hydroxyguanine by differential pulse voltammetry. The level of this stable and specific indicator of DNA damage could be determined in DNA isolated from peripheral blood lymphocytes, plasma or urine of irradiated individuals. Screen-printed carbon electrodes modified with carboxy-functionalized multi-walled carbon nanotubes were utilized for highly sensitive electrochemical detection of 8-hydroxyguanine. Electrochemical oxidation of 8-hydroxoguanine monitored by differential pulse voltammetry was found pH-dependent and the most intensive signal was recorded at pH 7. After recalculating the current density, several times higher sensitivity was attained in comparison with already published results, which were obtained using screen-printed carbon electrodes with unmodified carbon ink. Subsequently, the modified electrochemical technique was used for the detection of 8-hydroxoguanine in calf thymus DNA samples irradiated by 60Co gamma source in the dose range from 0.5 to 20 Gy using by various types of sample pretreatment and measurement conditions. This method could serve for fast retrospective quantification of absorbed dose in cases of accidental exposure to ionizing radiation and may play an important role in biodosimetry.

Keywords: biodosimetry, electrochemical detection, voltametry, 8-hydroxyguanine

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Authors: Rihab Hamdi, Amel Hadri Hamida, Ouafae Bennis, Sakina Zerouali

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This paper features a performance analysis and robustness assessment of a digitally controlled DC-DC three-cell buck converter associated in parallel, operating in continuous conduction mode (CCM), facing feeding parameters variation and loads disturbance. The control strategy relies on the continuous-time with an averaged modeling technique for high-frequency switching converter. The methodology is to modulate the complete design procedure, in regard to the existence of an instantaneous current operating point for designing the digital closed-loop, to the same continuous-time domain. Moreover, the adopted approach is to include a digital voltage control (DVC) technique, taking an account for digital control delays and sampling effects, which aims at improving efficiency and dynamic response and preventing generally undesired phenomena. The results obtained under load change, input change, and reference change clearly demonstrates an excellent dynamic response of the proposed technique, also as provide stability in any operating conditions, the effectiveness is fast with a smooth tracking of the specified output voltage. Simulations studies in MATLAB/Simulink environment are performed to verify the concept.

Keywords: continuous conduction mode, digital control, parallel multi-cells converter, performance analysis, power electronics

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Authors: Marc Gärtner, Monika Huesmann, Katharina Schiederig

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While workplace flexibility provides opportunities to better balance work and family care, careers in management are still predominantly based on physical presence, blurred boundaries and a culture of availability at the workplace. Thus, carers (mostly women) still experience disadvantages and stalled careers. In a multi-case study, funded by the German Federal Ministry of Education and Research, success factors and barriers of flexible work arrangements in five big organizations, including three of the largest German companies, have been identified. Using qualitative interview methods, the working models of 10 female and male users of flexible work arrangements like part time, home office and job sharing have been studied. The study group applied a 360-degree approach with focus groups, covering the users’ themselves, their superiors, colleagues and staff as well as in-house human resource managers. The group interviews reveal that success of flexible models is mainly built on three factors: (a) the inclusiveness of the organizational culture, (b) the commitment of leaders and especially the supervisors, and (c) the fitting of the model and the user(s). Flexibilization of time and space can indeed contribute to a better work-life balance. This is, however, not a necessary outcome, as the interviews suggest, but depends on the right implementation of the right model in the particular work environment. Beyond the actual study results, the presentation will also assess the methodological approach.

Keywords: flexible work, leadership, organizational culture, work-life balance

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Authors: Monique de Ritter, Annemieke Roobeek

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This study takes a holistic multi-layered systems approach on entrepreneurship, innovation, and sustainability. Concretely we looked how mission driven entrepreneurs (level 1) employ new business models and launch innovative products and/or ideas in their enterprises, which are (level 2) operating in entrepreneurial ecosystems (level 3), and how these in turn may generate higher level sustainable change (level 4). We employed a qualitative grounded research approach in which our aim is to contribute to theory. Fourteen in-depth semi-structured interviews were conducted with mission driven entrepreneurs in the Netherlands in which their individual drives, business models, and ecosystems were discussed. Interview transcripts were systematically coded and analysed and the ecosystems were visually mapped. Most important patterns include 1) entrepreneurs have a clear sustainable mission and regard this mission as de raison d’être of their enterprise; 2) entrepreneurs employ new business models with a focus on collaboration for innovation; the business model supports or enhances the sustainable mission of the enterprise, 3) entrepreneurs collaborate in ecosystems in which a) they also regard suppliers as partners for innovation and clients as ambassadors for the sustainable mission, b) would like to improve their relationships with financial institutions as they are in the entrepreneurs’ perspective often lagging behind with their innovative ideas and models, c) they collaborate for knowledge and innovation with several parties, d) personal informal connections are very important, and e) in which the higher sustainable mission is not a point of competition but of collaboration.

Keywords: sustainability, entrepreneurship, innovation, ecosystem, business models

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

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Authors: Lopita Pal, Suresh V. Madha

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Wetlands are areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. The rapidly expanding human population, large scale changes in land use/land cover, burgeoning development projects and improper use of watersheds all has caused a substantial decline of wetland resources in the world. Major degradations have been impacted from agricultural, industrial and urban developments leading to various types of pollutions and hydrological perturbations. Regular fishing activities and unsustainable grazing of animals are degrading the wetlands in a slow pace. The paper focuses on the spatio-temporal change detection of the area of the water body and the main cause of this depletion. The total area under study (22°19’87’’ N, 88°20’23’’ E) is a wetland region in West Bengal of 213 sq.km. The procedure used is the Normalized Difference Water Index (NDWI) from multi-spectral imagery and Landsat to detect the presence of surface water, and the datasets have been compared of the years 2016, 2006 and 1996. The result shows a sharp decline in the area of water body due to a rapid increase in the agricultural practices and the growing urbanization.

Keywords: spatio-temporal change, NDWI, urbanization, wetland

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Authors: James R. Wilson

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Music is typically defined as having the attributes of melody, harmony, and rhythm. In this paper, a fourth element is proposed -"flow". "Flow" is a new dimension in music that has always been present but only recently identified and measured. The Adagio "Flow Machine" enables us to envision this component and even suggests a new approach to music theory and analysis. The Adagio was created specifically to measure the underlying “flow” in music. The Adagio is an entirely new way to experience and visualize the music, to assist in performing music (both as a conductor and/or performer), and to provide a whole new methodology for music analysis and theory. The Adagio utilizes musical “hit points”, such as a transition from one musical section to another (for example, in a musical composition utilizing the sonata form, a transition from the exposition to the development section) to help define the compositions flow rate. Once the flow rate is established, the Adagio can be used to determine if the composer/performer/conductor has correctly maintained the proper rate of flow throughout the performance. An example is provided using Mozart’s Piano Concerto Number 21. Working with the Adagio yielded an unexpected windfall; it was determined via an empirical study conducted at Nova University’s Biofeedback Lab that watching the Adagio helped volunteers participating in a controlled experiment recover from stressors significantly faster than the control group. The Adagio can be thought of as a new arrow in the Musicologist's quiver. It provides a new, unique way of viewing the psychological impact and esthetic effectiveness of music composition. Additionally, with the current worldwide access to multi-media via the internet, flow analysis can be performed and shared with others with little time and/or expense.

Keywords: musicology, music analysis, music flow, music therapy

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Authors: Vangelis Papadimitropoulos

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The paper is part of the research project “Techno-Social Innovation in the Collaborative Economy'', funded by the Hellenic Foundation of Research and Innovation for the years 2022-2024. The research project examines the normative and empirical conditions of grassroots technologically driven innovation, potentially enabling the transition towards a commons-oriented post-capitalist economy. The project carries out a conceptually led and empirically grounded multi-case study of the digital commons, open-source technologies, platform cooperatives, open cooperatives and Distributed Autonomous Organizations (DAOs) on the Blockchain. The methodological scope of research is interdisciplinary inasmuch as it comprises political theory, economics, sustainability science and computer science, among others. The research draws specifically on Michel Bauwens and Vasilis Kostakis' model of open cooperativism between the commons, ethical market entities and a partner state. Bauwens and Kostakis advocate for a commons-based counter-hegemonic post-capitalist transition beyond and against neoliberalism. The research further employs Laclau and Mouffe's discourse theory of hegemony to introduce a post-hegemonic conceptualization of the model of open cooperativism. Thus, the paper aims to outline the theoretical contribution of the research project to contemporary political theory debates on post-capitalism and the collaborative economy.

Keywords: open cooperativism, techno-social innovation, post-hegemony, post-capitalism

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Renukswamy Chikkamath, Vishvapalsinhji Ramsinh Parmar, Christoph Hewel, Markus Endres

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Given a patent document, identifying distinct semantic annotations is an interesting research aspect. Text annotation helps the patent practitioners such as examiners and patent attorneys to quickly identify the key arguments of any invention, successively providing a timely marking of a patent text. In the process of manual patent analysis, to attain better readability, recognising the semantic information by marking paragraphs is in practice. This semantic annotation process is laborious and time-consuming. To alleviate such a problem, we proposed a dataset to train machine learning algorithms to automate the highlighting process. The contributions of this work are: i) we developed a multi-class dataset of size 150k samples by traversing USPTO patents over a decade, ii) articulated statistics and distributions of data using imperative exploratory data analysis, iii) baseline Machine Learning models are developed to utilize the dataset to address patent paragraph highlighting task, and iv) future path to extend this work using Deep Learning and domain-specific pre-trained language models to develop a tool to highlight is provided. This work assists patent practitioners in highlighting semantic information automatically and aids in creating a sustainable and efficient patent analysis using the aptitude of machine learning.

Keywords: machine learning, patents, patent sentiment analysis, patent information retrieval

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Authors: Chia-Jung Li, Li-Te Lin, Kuan-Hao Tsui

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The study identifies SPP1 as a potential gene associated with ovarian aging, revealing a significant decline in its expression in aged ovaries. SPP1, also known as osteopontin (OPN), is a multifunctional glycoprotein involved with regulatory proteins and pro-inflammatory immune chemokines. However, its genetic links to ovarian aging have not been extensively explored. Spatial transcriptomic analyses were conducted on ovaries from young and aged female mice, along with a sample from a 73-year-old individual. Additionally, single-cell RNA sequencing analysis was performed to identify associations between SPP1 and key genes. The study focused on crucial genes, including ITGAV, ITGB1, CD44, MMP3, and FN1, with a particular emphasis on the correlation between SPP1 and ITGB1. The findings indicate a significant decline in SPP1 expression in aged ovaries, which was consistent in the 73-year-old sample. Single-cell RNA sequencing unveiled associations between SPP1 and key genes, emphasizing a strong co-expression correlation between SPP1 and ITGB1. While the study provides valuable insights, further research is necessary to understand the broader implications and potential applications of SPP1 in ovarian aging. Translating these findings to clinical settings requires careful consideration. The identification of SPP1 as a gene implicated in ovarian aging opens new avenues for advancing precision medicine and refining treatment strategies for conditions related to ovarian aging.

Keywords: SPP1, ovarian aging, spatial transcriptomic, single-cell RNA sequencing

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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One of the major interferences in the Philippines’ tuberculosis control program is the widespread prevalence of Mtb strains that are resistant to known drugs, such as the MDR-TB (Multi Drug Resistant Tuberculosis) and XDR-TB (Extensively Drug Resistant Tuberculosis). Therefore, there is a pressing need to search for novel Mtb drug targets in order to be able to combat these drug resistant strains. The enzyme 7,8-diaminopelargonic acid aminotransferase enzyme, or more commonly known as BioA, is one such ideal target, as it is known that humans do not possess this enzyme. BioA primarily plays a key role in Mtb’s lipid biosynthesis pathway; more specifically in the synthesis of the enzyme cofactor biotin. In this study, structure-based pharmacophore screening, docking, and ADMET evaluation of compounds obtained from the DrugBank chemical database were performed against the MtbBioA enzyme. Results of the screening, docking, ADMET, and TOPKAT calculations revealed that out of the 6,516 compounds in the library, only 7 compounds indicated more favorable binding energies as compared to the enzyme’s known inhibitor, amiclenomycin (ACM), as well as good solubility and toxicity properties. Moreover, out of these 7 compounds, Molecule 6 exhibited the best solubility and toxicity properties. In the future, these lead compounds may then be subjected to bioactivity assays in vitro or in vivo for further evaluation of its therapeutic efficacy.

Keywords: 7, 8-diaminopelargonic acid aminotransferase, BioA, pharmacophore, molecular docking, ADMET, TOPKAT

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Authors: Meki Detamo, Ahmed

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Access to improved sanitation facilities is crucial for promoting community sanitation worldwide. In Ethiopia, however, sanitation remains a major development challenge despite growing attention and efforts by governments and donors. This study aimed to assess the availability of improved sanitation facilities and associated factors in urban kebeles of Dire Dawa City, Eastern Ethiopia, in 2022. A community-based cross-sectional study was conducted from March 6 to 30, 2022, using a multi-stage sampling technique to select 508 households. Data was collected through structured and pre-tested questionnaires using face-to-face interviews and observations and analyzed using SPSS Version 23. The availability of improved sanitation facilities was found to be remarkably high at 98.2% (95% CI: 97.0, 99.2), with 60.8% of households having a handwashing facility in or around the latrine, 86.0% using soap and water, and 89.0% using an improved water source for drinking. Logistic regression analysis revealed that households with a family size of less than four, those who owned their own house, and those who had self-initiated latrine construction were significantly associated with the availability of improved sanitation facilities. The study recommends the implementation of continuous refreshment training to emphasize the benefits of improved sanitation facilities in the urban community and family planning. This study provides valuable insights into the high availability of improved sanitation facilities in urban areas of Ethiopia and can inform future efforts to improve community sanitation.

Keywords: sanitation facilities, availability, improved, Dire Dawa, Ethiopia

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Authors: Jay Gohel, Anant Parghi

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A tuned liquid column damper (TLCD) is a modified passive system of tuned mass damper, where a liquid is used in place of mass in the structure. A TLCD consists of U-shaped tube with an orifice that produces damping against the liquid motion in the tube. This paper provides a state-of-the-art review on the vibration control of wind and earthquake excited structures using liquid dampers. Further, the paper will also discuss the theoretical background of TCLD, history of liquid dampers and existing literature on experimental, numerical, and analytical study. The review will also include different configuration of TLCD viz single TLCD, multi tuned liquid column damper (MTLCD), TLCD-Interior (TLCDI), tuned liquid column ball damper (TLCBD), tuned liquid column ball gas damper (TLCBGD), and pendulum liquid column damper (PLCD). The dynamic characteristics of the different configurate TLCD system and their effectiveness in reducing the vibration of structure will be discussed. The effectiveness of semi-active TLCD will be also discussed with reference to experimental and analytical results. In addition, the review will also provide the numerous examples of implemented TLCD to control the vibration in real structures. Based on the comprehensive review of literature, some important conclusions will be made and the need for future research will be identified for vibration control of structures using TLCD.

Keywords: earthquake, wind, tuned liquid column damper, passive response control, structures

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Authors: Berhane Gebreslassie

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Conventional commericial buildings are among the highest unwisely consumes enormous amount of energy and as consequence produce significant amount Carbon Dioxide (CO2). Traditional/conventional buildings have been built for years without consideration being given to their impact on the global warming issues as well as their CO2 contributions. Since 1973, simulation of Green Building (GB) for Energy Efficiency started and many countries in particular the US showed a positive response to minimize the usage of energy in respect to reducing the CO2 emission. As a consequence many software companies developed their own unique building energy efficiency simulation software, interfacing interoperability with Building Information Modeling (BIM). The last decade has witnessed very rapid growing number of researches on GB energy efficiency system. However, the study also indicates that the results of current GB simulation are not yet satisfactory to meet the objectives of GB. In addition most of these previous studies are unlikely excluded the studies of ultimate building energy efficiencies simulation. The aim of this project is to meet the objectives of GB by design, modeling and simulation of building ultimate energy efficiencies system. This research project presents multi-level, L-shape office building in which every particular part of the building materials has been tested for energy efficiency. An overall of 78.62% energy is saved, approaching to NetZero energy saving. Furthermore, the building is implements with distributed energy resources like renewable energies and integrating with Smart Building Automation System (SBAS) for controlling and monitoring energy usage.

Keywords: ultimate energy saving, optimum energy saving, green building, sustainable materials and renewable energy

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Authors: Sadaf Ilyas, Saba Riaz

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The extensive use of antibiotics has led to increases emergence of antibiotic-resistant organisms. Pseudomonas is a notorious opportunistic pathogen involoved in nosocomial infections and exhibit innate resistance to many antibiotics. The present study was conducted to assess the prevalence, levels of antimicrobial susceptibility and resistance mechanisms of Pseudomonas. A total of thirty clinical strains of Pseudomonas were isolated from different clinical sites of infection. All clinical specimens were collected from Chughtais Lahore Lab. Jail road, during 8-07-2010 to 11-01-2011. Biochemical characterization was done using routine biochemical tests. Antimicrobial susceptibility was determined by Kirby-Baeur method. The plasmids were isolated from all the strains and digested with restriction enzyme PstI and EcoRI. Transfer of Multi-resistance plasmid was checked via transformation and conjugation to confirm the plasmid mediated resistance to antibiotics. The prevalence of Pseudomonas in clinical specimens was found out to be 14% of all bacterial infections. IPM has shown to be the most effective drug against Pseudomonas followed by CES, PTB and meropenem, wheareas most of the Pseudomonas strains have developed significant resistance against Penicillins and some Cephalasporins. Antibiotic resistance determinants were carried by plasmids, as they conferred resistance to transformed K1 strains. The isolates readily undergo conjugation, transferring the resistant genes to other strains, illustrating the high rates of cross infection and nosocomial infection in the immunocompromised patients.

Keywords: pseudomonas, antibiotics, drug resistance, horizontal gene transfer

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Authors: Chris Ogwu Attah, Okpanachi Linus Odiji

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An election is no doubt a universally accepted means of resolving societal problems, particularly those with political connotations. While the process has often been conducted in advanced democracies without attacks on opponents and the populace, that ambiance of political tranquillity has hardly been enjoyed in many African states. While the violent nature of polls on this part of the globe have for long been linked among other things to monetization and the zero-sum character of politics, emerging trends show how the increasing rate of electoral violence may not be unconnected to the broadcasts of violent acts in the media. Anchored on the age-long complaints about the possible deleterious effects of mass media and Plato’s concern about the effects of plays on the youth, this study aims to interrogate the relationship between media and electoral violence in Nigeria using Kogi State as a case study. While the Social Cognitive Theory is adopted to guide the study to fruition, data was elicited primarily from a multi-stage sampling arrangement in which respondents from three purposively selected locations (Anyigba, Lokoja, and Okene) were randomly selected. Using chi-square to test the assumption that media violence catalyzes electoral violence in Kogi State, it was discovered among other revelations that electoral violence increases numerically with the depiction of violence in the media. As a recommendation, therefore, this paper advocate that Civil Society Organisations, as well as relevant governmental agencies, should carry out mass political education which aims at instilling political morals on the populace, especially the youths.

Keywords: electoral violence, media, media violence, violence

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Authors: Nazli Hardy

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Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

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Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

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Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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Authors: Hooman Dabirmanesh, Attila M. Zsaki

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The toppling failure mode in a rock mass is considerably different from the most common sliding failure type along an existing or an induced slip plane. Block toppling is observed in a rock mass which consists of both a widely-spaced basal cross-joint set and a closely-spaced discontinuity set dipping into the slope. For this case, failure occurs when the structure cannot bear the tensile portion of bending stress, and the columns or blocks overturn by their own weight. This paper presents a particle-based discrete element model of rock blocks subjected to a toppling failure where geometric conditions and interaction among blocks are investigated. A series of parametric studies have been conducted on particles’ size, arrangement and bond contact among of particles which are made the blocks. Firstly, a numerical investigation on a one-block system was verified. Afterward, a slope consisting of multi-blocks was developed to study toppling failure and interaction forces between blocks. The results show that the formation of blocks, especially between the block and basal plane surface, can change the process of failure. The results also demonstrate that the initial configuration of particles used to form the blocks has a significant role in achieving accurate simulation results. The size of particles and bond contacts have a considerable influence to change the progress of toppling failure.

Keywords: block toppling failure, contact interaction, discrete element, particle size, random generation

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Authors: Balram Panjwani, Bernd Wittgens, Jan Erik Olsen, Stein Tore Johansen

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The Norwegian ferroalloy industry is a world leader in sustainable production of ferrosilicon, silicon and manganese alloys with the lowest global specific energy consumption. One of the byproducts during the metal reduction process is energy rich off-gas and usually this energy is not harnessed. A novel concept for sustainable energy recovery from ferroalloy off-gas is discussed. The concept is founded on the idea of introducing a combustion chamber in the off-gas section in which energy rich off-gas mainly consisting of CO will be combusted. This will provide an additional degree of freedom for optimizing energy recovery. A well-controlled and high off-gas temperature will assure a significant increase in energy recovery and reduction of emissions to the atmosphere. Design and operation of the combustion chamber depend on many parameters, including the total power capacity of the combustion chamber, sufficient residence time for combusting the complex Poly Aromatic Hydrocarbon (PAH), NOx, as well as converting other potential pollutants. The design criteria for the combustion chamber have been identified and discussed and sizing of the combustion chamber has been carried out considering these design criteria. Computational Fluid Dynamics (CFD) has been utilized extensively for sizing the combustion chamber. The results from our CFD simulations of the flow in the combustion chamber and exploring different off-gas fuel composition are presented. In brief, the paper covers all aspect which impacts the sizing of the combustion chamber, including insulation thickness, choice of insulating material, heat transfer through extended surfaces, multi-staging and secondary air injection.

Keywords: CFD, combustion chamber, arc furnace, energy recovery

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Authors: Dweepabiswa Bagchi, D. V. Senthilkumar

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Numerous studies have typically demonstrated the devastation of invasions on an isolated ecosystem or, at most, a network of dispersively coupled similar ecosystem patches. Using such a simplistic 2-D network model, one can only consider dispersal coupling and inter-species trophic interactions. However, in a realistic ecosystem, numerous species co-exist and interact trophically and non-trophically in groups of 2 or more. Even different types of dispersal can introduce complexity in an ecological network. Therefore, a more accurate representation of actual ecosystems (or ecological networks) is a complex network consisting of motifs formed by two or more interacting species. Here, the apropos structure of the network should be multiplex or multi-layered. Motifs between different patches or species should be identical within the same layer and vary from one layer to another. This study investigates three distinct ecological multiplex networks facing invasion from one or more external species. This work determines and quantifies the criteria for the increased extinction risk of these networks. The dynamical states of the network with high extinction risk, i.e., the danger states, and those with low extinction risk, i.e., the resistive network states, are both subsequently identified. The analysis done in this study further quantifies the persistence of the entire network corresponding to simultaneous changes in the strength of invasive dispersal and higher-order trophic and non-trophic interactions. This study also demonstrates that the ecosystems enjoy an inherent advantage against invasions due to their multiplex network structure.

Keywords: increased ecosystem persistence, invasion on ecosystems, multiplex networks, non-trophic interactions

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Authors: P. O. Fatoki, R. S. Olaleye, B. O. Adeniji

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The study investigated farmers’ perception of the effects of climate change on rice production in Nasarawa State, Nigeria. Multi-stage sampling technique was used in selecting a total of 248 rice farmers from the study area. Data for the study were collected through the use of interview schedule. The data were analysed using both descriptive and inferential statistics. Results showed that majority (71.8%) of the respondents were married and the mean age of the respondents was 44.54 years. The results also showed that most adapted strategies for mitigating the effects of climate change on rice production were change of planting and harvesting date (67.7%), movement to another site (63.7%) and increased or reduced land size (58.5%). Relationship between the roles of extension agents in mitigating climate change effects on rice production and farmers’ perception were significant as revealed Chi-Square analysis from the study ; Dissemination of information ( = 2.16, P < 0.05) and use of demonstration methods ( = 2.15, P < 0.05). Poisson regression analysis revealed that educational status, farm size, experience and yield had significant relationship with the perception of the effects of climate change at 0.01 significance level while household size was as well significant at 0.05. It is recommended that some of the adaptive strategies and practices for mitigating the effects of climate change in rice production should be improved, while the extension outfits should be strengthened to ensure adequate dissemination of relevant information on climate change with a view to mitigate its effects on rice production.

Keywords: perception, rice farmers, climate change, mitigation, adaptive strategies

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Authors: Umme Shahera, Saifullah Munshi, Munira Jahan, Afzalun Nessa, Shahinul Alam, Shahina Tabassum

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The development of HCC is a multi-stage process. Several extrinsic factors, such as aflatoxin, HBV, nutrition, alcohol, and trace elements are thought to initiate or/and promote the hepatocarcinogenesis. Alteration of p53 status is an important intrinsic factor in this process as p53 is essential for preventing inappropriate cell proliferation and maintaining genome integrity following genotoxic stress. This study was designed to assess the correlation of p53 gene expression with HBV-DNA and serum Alanine transaminase (ALT) in patients with cirrhosis and HCC. The study was conducted among 60 patients. The study population were divided into four groups (15 in each groups)-HBV positive cirrhosis, HBV negative cirrhosis, HBV positive HCC and HBV negative HCC. Expression of p53 gene was observed using real time PCR. P53 gene expressions in the above mentioned groups were correlated with serum ALT level and HBV viral load. p53 gene was significantly higher in HBV-positive patients with HCC than HBV-positive cirrhosis. Similarly, the expression of p53 was significantly higher in HBV-positive HCC than HBV-negative HCC patients. However, the expression of p53 was reduced in HBV-positive cirrhosis in comparison with HBV-negative cirrhosis. P53 gene expression in liver was not correlated with the serum levels of ALT in any of the study groups. HBV- DNA load also did not correlated with p53 gene expression in HBV positive HCC and HBV positive cirrhosis patients. This study shows that there was no significant change with the expression of p53 gene in any of the study groups with ALT level or viral load, though differential expression of p53 gene were observed in cirrhosis and HCC patients.

Keywords: P53, ALT, HBV-DNA, liver cirrhosis, hepatocellular carcinoma

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Authors: Yeliz Karaca, Carlo Cattani

Abstract:

This study focuses on the local Holder exponent as a measure of the function regularity for time series related to finance data. In this study, the attributes of the finance dataset belonging to 13 countries (India, China, Japan, Sweden, France, Germany, Italy, Australia, Mexico, United Kingdom, Argentina, Brazil, USA) located in 5 different continents (Asia, Europe, Australia, North America and South America) have been examined.These countries are the ones mostly affected by the attributes with regard to financial development, covering a period from 2012 to 2017. Our study is concerned with the most important attributes that have impact on the development of finance for the countries identified. Our method is comprised of the following stages: (a) among the multi fractal methods and Brownian motion Holder regularity functions (polynomial, exponential), significant and self-similar attributes have been identified (b) The significant and self-similar attributes have been applied to the Artificial Neuronal Network (ANN) algorithms (Feed Forward Back Propagation (FFBP) and Cascade Forward Back Propagation (CFBP)) (c) the outcomes of classification accuracy have been compared concerning the attributes that have impact on the attributes which affect the countries’ financial development. This study has enabled to reveal, through the application of ANN algorithms, how the most significant attributes are identified within the relevant dataset via the Holder functions (polynomial and exponential function).

Keywords: artificial neural networks, finance data, Holder regularity, multifractals

Procedia PDF Downloads 246