Search results for: power limited sources

Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Si̇nem Uğuz, Yuksel Ardali

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Nowadays rapid population growth causes a mandatory increase in consumption. As a result of production activities which meet this consumption, energy sources decrease rapidly on our world. As well as with this production activities various waste occurs. At the end of the production and accumulation of this waste need a mandatory disposal. In this context, copyrolysis of waste polyolefins were investigated. In this study for pyrolysis process, polyethylene and polyprophylene are selected as polyolefins. The pyrolysis behavior (efficiency of solid, liquid and gas production) of selected materials were examined at the different temperatures and different mixtures. Pyrolysis process was carried out at 550 °C and 600 °C without air in a fixed bed pyrolysis oven solid under the nitrogen flow to provide inertness of medium. Elemental analyses (C, H, O, N, S) of this solid and liquid (bitumen) products were made and the calorific value was calculated. The availability of liquid product as a fuel was investigated. In addition different products’ amounts formed like solid, liquid and gas at different temperatures were evaluated.

Keywords: alternative energy, elemental analysis, pyrolysis, waste reduction

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Authors: Patience Oluchi Silas, Yemi Adeshina

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Financial transactions involving the use of the internet has become an important practice among commercial banks in Nigeria with the introduction of internet banking and this has improved banking efficiency in rending services to customers. However, customers in Lagos State are enslaved in the fear of insecurity, technical failure, inadequate operational facilities, including improper telecommunications and poor power supply. It is in line with this that this paper explores the obstacles faced by Lagosians, tourists, small scale business owners, companies, customers and the government's attitude in addressing the challenges associated with online banking system in Nigeria through relevant legislations. Internet banking has the potential to transform economic activity and achieve developmental goals. If the associated Challenges are addressed quickly, then it will have the desired impact on the Nigerian economy. In this study, Respondents, mostly bank employees and customers were issued well designed and structured questionnaires to effectively examine the new developments brought about by the introduction of Internet banking and the challenges inhibiting its adoption. Hypotheses were formulated to test assumptions and claims generated from the study. The results were statistically analyzed to address the issues of errors and chances, and at the end, the result of the statistical analysis shows that all especially insecurity, inadequate operational facilities and poor power supply are the significant factors affecting the adoption of internet banking services in Nigeria. The study recommends that for internet banking to assume a developmental dimension in Nigeria and for the country to be fully integrated and respected in global financial environment, the prevalent level of frauds in Lagos State and among Nigerians must first be addressed and the relevant local laws should be put in place and in consonance with international laws and conventions; get the citizens well educated on the intricacies of Internet usage and frauds.

Keywords: internet-banking, adoption, challenges, insecurity, legislation, fraud, Lagos state, statistics

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Authors: Man Guo

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This paper delves into the intricate interplay between spatial morphology and spatial cognition in Lidukou Village, utilizing a combined approach of spatial syntax and field data. Through a comparative analysis of the gathered data, it emerges that the spatial integration level of Lidukou Village exhibits a direct positive correlation with the spatial cognitive preferences of its inhabitants. Specifically, the areas within the village that exhibit a higher degree of spatial cognition are predominantly distributed along the axis primarily defined by Shuxiang Road. However, the accessibility to historical relics remains limited, lacking a coherent systemic relationship. To address the morphological challenges faced by Lidukou Village, this study proposes optimization strategies that encompass diverse perspectives, including the refinement of spatial mechanisms and the shaping of strategic spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: Marco Correa

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The increasing reduction of the volumes of surface water sources supplying most municipalities, as well as the rising demand for treated water, combined with the disposal of effluents from washing of decanters and filters of water treatment plants generates a continuous search for correct environmentally solutions to these problems. The effluents generated by the water treatment industry need to be suitably processed for return to the environment or re-use. This article shows alternatives for sludge dehydration from the water treatment plants (WTP) and eventual disposal of sludge drained. Using the simple design methodology, it is presented a case study for drainage in tanks geotextile, full-scale, which involve five sledge drainage tanks from WTP of the city of Rio Verde. Aiming to the reutilization of drained water from the sledge and enabling its reuse both at the beginning of the treatment process at the WTP and in less noble services as for watering the gardens of the local town hall. The sludge will be used to in the production of building materials.

Keywords: dehydration, effluent discharges, re-use, sludge, WTP sludge

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Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

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Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: flaring, fuel gas network, GHG emissions, stream

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Authors: Justine Kiiza, Xu Jiafang

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The world’s demand for energy is increasing rapidly due to population growth and a reduction in shallow conventional oil and gas reservoirs, resorting to deeper and mostly unconventional reserves like shale oil and gas. Most shale formations contain a large amount of expansive sodium montmorillonite (Na-Mnt), due to high water adsorption, hydration, and when the drilling fluid filtrate enters the formation with high Mnt content, the wellbore wall can be unstable due to hydration and swelling, resulting to shrinkage, sticking, balling, time wasting etc., and well collapse in extreme cases causing complex downhole accidents and high well costs. Recently, polyamines like 1, 6 – hexane diamine (HEDA) have been used as typical drilling fluid shale inhibitors to minimize and/or cab clay mineral swelling and maintain the wellbore stability. However, their application is limited to shallow drilling due to their sensitivity to elevated temperature and pressure. Inorganic potassium salts i.e., KCl, have long been applied for restriction of shale formation hydration expansion in deep wells, but their use is limited due to toxicity. Understanding the adsorption behaviour of HEDA on Na-Mnt surfaces in present of organo-salts, organic K-salts e.g., HCO₂K - main component of organo-salt drilling fluid, is of great significance in explaining the inhibitory performance of polyamine inhibitors. Molecular dynamic simulations (MD) were applied to investigate the influence of HCO₂K and KCl on the adsorption mechanism of HEDA on the Na-Mnt surface. Simulation results showed that adsorption configurations of HEDA are mainly by terminal amine groups with a flat-lying alkyl hydrophobic chain. Its interaction with the clay surface decreased the H-bond number between H₂O-clay and neutralized the negative charge of the Mnt surface, thus weakening the surface hydration ability of Na-Mnt. The introduction of HCO₂K greatly improved inhibition ability, coordination of interlayer ions with H₂O as they were replaced by K+, and H₂O-HCOO- coordination reduced H₂O-Mnt interactions, mobility and transport capability of H₂O molecules were more decreased. While KCl showed little ability and also caused more hydration with time, HCO₂K can be used as an alternative for offshore drilling instead of toxic KCl, with a maximum concentration noted in this study as 1.65 wt%. This study provides a theoretical elucidation for the inhibition mechanism and adsorption characteristics of HEDA inhibitor on Na-Mnt surfaces in the presence of K+-salts and may provide more insight into the evaluation, selection, and molecular design of new clay-swelling high-performance WBDF systems used in oil and gas complex offshore drilling well sections.

Keywords: shale, hydration, inhibition, polyamines, organo-salts, simulation

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Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Zakir Husain, Deepak Kumar

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The harmonics are very harmful within an electrical system and can have serious consequences such as reducing the life of apparatus, stress on cable and equipment etc. This paper cites extensive analytical study of harmonic characteristics of multiphase (six-phase) and three-phase system equipped with two and three level inverters for non-linear loads. Multilevel inverter has elevated voltage capability with voltage limited devices, low harmonic distortion, abridged switching losses. Multiphase technology also pays a promising role in harmonic reduction. Matlab simulation is carried out to compare the advantage of multi-phase over three phase systems equipped with two or three level inverters for non-linear load harmonic reduction. The extensive simulation results are presented based on case studies.

Keywords: fast Fourier transform (FFT), harmonics, inverter, ripples, total harmonic distortion (THD)

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Albert T. Akume, Ankama G. Rosecana, Micheal Solomon

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Every citizen has rights that must be respected by others in the community. Ironically however, women in most communities are not accorded some of those rights as the male folks. This has not only facilitated their disempowerment but inhibited them from being treated with equal dignity that they deserve as their male counterpart; despite their valuable contribution to the society. Those forces against women empowerment are not limited to socio-cultural practices alone, but the character and nature of the state in Nigeria point to indicators of systemic and structural exclusion embedded in its framework. The consequence of this is that the vital contributions of women to sustainable community development have eluded many communities in Nigeria with adverse tell-tell signs on the environment. It is for this reason that the objective of this study is not only to highlight the causes and challenges associated with women disempowerment, but also to draw attention to the need to correct those anomaly against women in order to genuinely empower them to contribute to sustainable community development in Nigeria.

Keywords: capacity development, community, social sustainability, sustainable development, women empowerment

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Authors: C. Makwana, S. R. Dave

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Arsenic is toxic to almost all living cells. Its contamination in natural sources affects the growth of microorganisms. The presence of arsenic is associated with various human disorders also. The attempt of this sort of study provides information regarding the performance of our isolated microorganisms in the presence of Arsenic, which have ample scope for bioremediation. Six isolates were selected from the polluted sample of industrial zone Vatva, Ahmedabad, Gujarat, India, out of which two were Thermophilic organisms. The thermophilic exopolysaccharide (EPS) producing Bacillus was used for microbial enhance oil recovery (MEOR) and in the bio beneficiation. Inorganic arsenic primarily exists in the form of arsenate or arsenite. This arsenic resistance isolate was capable of transforming As +3 to As+5. This isolate would be useful for arsenic remediation standpoint from aquatic systems. The study revealed that the thermophilic microorganism was growing at 55 degree centigrade showed considerable remediation property. The results on the growth and enzyme catalysis would be discussed in response to Arsenic remediation.

Keywords: aquatic systems, thermophilic, exopolysacchride, arsenic

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Authors: Naima Umar

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Mid-1960’s has been landmark in the history of Indian agriculture. It was in 1966-67 when a New Agricultural Strategy was put into practice to tide over chronic shortages of food grains in the country. This strategy adopted was the use High-Yielding Varieties (HYV) of seeds (wheat and rice), which was popularly known as the Green Revolution. This phase of agricultural development has saved us from hunger and starvation and made the peasants more confident than ever before, but it has also created a number of socio-economic and environmental implications such as the reduction in area under forest, salinization, waterlogging, soil erosion, lowering of underground water table, soil, water and air pollution, decline in soil fertility, silting of rivers and emergence of several diseases and health hazards. The state of Uttar Pradesh in the north is bounded by the country of Nepal, the states of Uttrakhand on the northwest, Haryana on the west, Rajasthan on the southwest, Madhya Pradesh on the south and southwest, and Bihar on the east. It is situated between 23052´N and 31028´N latitudes and 7703´ and 84039´E longitudes. It is the fifth largest state of the country in terms of area, and first in terms of population. Forming the part of Ganga plain the state is crossed by a number of rivers which originate from the snowy peaks of Himalayas. The fertile plain of the Ganga has led to a high concentration of population with high density and the dominance of agriculture as an economic activity. Present paper highlights the negative impact of new agricultural technology on health of the people and environment and will attempt to find out factors which are responsible for these implications. Karl Pearson’s Correlation coefficient technique has been applied by selecting 1 dependent variable (i.e. Productivity Index) and some independent variables which may impact crop productivity in the districts of the state. These variables have categorized as: X1 (Cropping Intensity), X2 (Net irrigated area), X3 (Canal Irrigated area), X4 (Tube-well Irrigated area), X5 (Irrigated area by other sources), X6 (Consumption of chemical fertilizers (NPK) Kg. /ha.), X7 (Number of wooden plough), X8 (Number of iron plough), X9 (Number of harrows and cultivators), X10 (Number of thresher machines), X11(Number of sprayers), X12 (Number of sowing instruments), X13 (Number of tractors) and X14 (Consumption of insecticides and pesticides (in Kg. /000 ha.). The entire data during 2001-2005 and 2006- 2010 have been taken and 5 years average value is taken into consideration, based on secondary sources obtained from various government, organizations, master plan report, economic abstracts, district census handbooks and village and town directories etc,. put on a standard computer programmed SPSS and the results obtained have been properly tabulated.

Keywords: agricultural technology, environmental implications, health hazards, socio-economic problems

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Authors: Raquel Nieto, Marta Vázquez, Anita Drumond, Luis Gimeno

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One of the hot spots of climate change is the increment of ocean evaporation. The best estimation of evaporation, OAFlux data, shows strong increasing trends in evaporation from the oceans since 1978, with peaks during the hemispheric winter and strongest along the paths of the global western boundary currents and any inner Seas. The transport of moisture from oceanic sources to the continents is the connection between evaporation from the ocean and precipitation over the continents. A key question is to try to relate evaporative source regions over the oceans where trends have occurred in the last decades with their sinks over the continents to check if there have been also any trends in the precipitation amount or its characteristics. A Lagrangian approach based on FLEXPART and ERA-interim data is used to establish this connection. The analyzed period was 1980 to 2012. Results show that there is not a general pattern, but a significant agreement was found in important areas of climate interest.

Keywords: ocean evaporation, Lagrangian approaches, contiental precipitation, Europe

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Authors: Jett Black, Jordyn Godsey, Gaby G. Dagher, Steve Cutchin

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Despite the growing interest in distributed ledger technology, many data visualizations of blockchain are limited to monotonous tabular displays or overly abstract graphical representations that fail to adequately educate individuals on blockchain components and their functionalities. To address these limitations, it is imperative to develop data visualizations that offer not only comprehensive insights into these domains but education as well. This research focuses on providing a conceptual understanding of the consensus process that underlies blockchain technology. This is accomplished through the implementation of a dynamic network visualization and an interactive educational tool called BlueVision. Further, a controlled user study is conducted to measure the effectiveness and usability of BlueVision. The findings demonstrate that the tool represents significant advancements in the field of blockchain visualization, effectively catering to the educational needs of both novice and proficient users.

Keywords: blockchain, visualization, consensus, distributed network

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Authors: Cóndor C. José, Rodrigues E. Camila, Noronha L. Irene, Dos Santos Fernando, Irigoyen M. Claudia, Andrade Lúcia

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Sepsis induces alterations in hemodynamics and autonomic nervous system (ASN). The autonomic activity can be calculated by measuring heart rate variability (HRV) that represents the complex interplay between ASN and cardiac pacemaker cells. Wharton’s jelly mesenchymal stem cells (WJ-MSCs) are known to express genes and secreted factors involved in neuroprotective and immunological effects, also to improve the survival in experimental septic animals. We hypothesized, that WJ-MSCs present an important role in the autonomic activity and in the hemodynamic effects in a cecal ligation and puncture (CLP) model of sepsis. Methods: We used flow cytometry to evaluate WJ-MSCs phenotypes. We divided Wistar rats into groups: sham (shamoperated); CLP; and CLP+MSC (106 WJ-MSCs, i.p., 6 h after CLP). At 24 h post-CLP, we recorded the systolic arterial pressure (SAP) and heart rate (HR) over 20 min. The spectral analysis of HR and SAP; also the spontaneous baroreflex sensitivity (measure by bradycardic and tachycardic responses) were evaluated after recording. The one-way ANOVA and the post hoc Student– Newman– Keuls tests (P< 0.05) were used to data comparison Results: WJ-MSCs were negative for CD3, CD34, CD45 and HLA-DR, whereas they were positive for CD73, CD90 and CD105. The CLP group showed a reduction in variance of overall variability and in high-frequency power of HR (heart parasympathetic activity); furthermore, there is a low-frequency reduction of SAP (blood vessels sympathetic activity). The treatment with WJ-MSCs improved the autonomic activity by increasing the high and lowfrequency power; and restore the baroreflex sensitive. Conclusions: WJ-MSCs attenuate the impairment of autonomic control of the heart and vessels and might therefore play a protective role in sepsis. (Supported by FAPESP).

Keywords: baroreflex response, heart rate variability, sepsis, wharton’s jelly-derived mesenchymal stem cells

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Authors: Pekka Makkonen, Georgios Lampropoulos, Kerstin Siakas

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This paper examines the impact of social media on knowledge work. It discloses and highlights which specific aspects, areas and tasks of knowledge work can be improved by the use of social media. Moreover, the study includes a survey about higher education students’ viewpoints in regard to the use of social media as a means to enhance knowledge work and knowledge sharing. The analysis has been conducted based both on empirical data and on discussions about the sources dealing with knowledge work and how it can be enhanced by using social media. The results show that social media can improve knowledge work, knowledge building and maintenance tasks in which communication, information sharing and collaboration play a vital role. Additionally, by using social media, personal, collaborative and supplementary work activities can be enhanced. Based on the results of the study, we suggest how knowledge work can be enhanced when using the contemporary information and communications technologies (ICTs) of the 21^st century and recommend future directions towards improving knowledge work.

Keywords: knowledge work, social media, social media services, improving work performance

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Authors: Maggie Shen

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Ever since the late 20th century, business giants have been competing to provide better experiences for their users. One way they strive to do so is through more efficiently connecting users with their goals, with recommendation systems that filter out unnecessary or less relevant information. Today’s top online platforms such as Amazon, Netflix, Airbnb, Tiktok, Facebook, and Google all utilize algorithmic recommender systems for different purposes—Product recommendation, movie recommendation, travel recommendation, relationship recommendation, etc. However, while bringing unprecedented convenience and efficiency, the prevalence of algorithmic recommendation systems also influences society in many ways. In using a variety of primary, secondary, and social media sources, this paper explores the impacts of algorithms, particularly algorithmic recommender systems, on different sectors of society. Four fields of interest will be specifically addressed in this paper: economy, international relations, political ideologies, and education.

Keywords: algorithms, economy, international relations, political ideologies, education

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Authors: Ibtissam Mharzi Alaoui, Camélia Sehaqui

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The success of a bank depends upon its effective risk management. With the growing complexity and diversity of financial products and services, as well as the accelerating pace of globalization over the past decade, risk management is becoming increasingly difficult. thus, all measurement and monitoring functions must be much more vigorous, relevant and adequate. The Shariah non-compliance risk is specific aspect of Islamic finance which ipso facto, deserves particular attention. It affects the validity of all Islamic financial contracts and it turns out to be likely to result in considerable losses on the overall Islamic financial institutions (IFIs). The purpose of this paper is to review the theoretical literature on Shariah non-compliance risk in order to give a clearer understanding of its sources, causes and consequences. Our intention through this work is to bring added value to the Islamic finance industry all over the world. The findings provide a useful reference work for the Islamic banks in structuring (or restructuring) of their own system of shariah risk management and internal control.

Keywords: Shariah non-compliance, risk management, financial products, Islamic finance.

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Authors: Vishal Pareek, Shubham Gupta, Sushil Chandra Jain

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With increasing high-speed computation demand the power consumption, heat dissipation and chip size issues are posing challenges for logic design with conventional technologies. Recovery of bit loss and bit errors is other issues that require reversibility and fault tolerance in the computation. The reversible computing is emerging as an alternative to conventional technologies to overcome the above problems and helpful in a diverse area such as low-power design, nanotechnology, quantum computing. Bit loss issue can be solved through unique input-output mapping which require reversibility and bit error issue require the capability of fault tolerance in design. In order to incorporate reversibility a number of combinational reversible logic based circuits have been developed. However, very few sequential reversible circuits have been reported in the literature. To make the circuit fault tolerant, a number of fault model and test approaches have been proposed for reversible logic. In this paper, we have attempted to incorporate fault tolerance in sequential reversible building blocks such as D flip-flop, T flip-flop, JK flip-flop, R-S flip-flop, Master-Slave D flip-flop, and double edge triggered D flip-flop by making them parity preserving. The importance of this proposed work lies in the fact that it provides the design of reversible sequential circuits completely testable for any stuck-at fault and single bit fault. In our opinion our design of reversible building blocks is superior to existing designs in term of quantum cost, hardware complexity, constant input, garbage output, number of gates and design of online testable D flip-flop have been proposed for the first time. We hope our work can be extended for building complex reversible sequential circuits.

Keywords: parity preserving gate, quantum computing, fault tolerance, flip-flop, sequential reversible logic

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Authors: Jesus Ruano, Francesc Xavier Trias, Asensi Oliva

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A three-dimensional incompressible Large Eddy Simulation (LES) is performed to compute the hydrodynamic field around a pair of tandem cylinders. Symmetry-preserving schemes will be used during this simulation in conjunction with Finite Volume Method (FVM) to obtain the hydrodynamic field around the selected geometry. A set of results consisting of pressure and velocity and the combination of them will be stored at different surfaces near the cylinders as the initial input for the second part of the study. A post-processing of the obtained results based on Ffowcs-Williams and Hawkings (FWH) equation with a Fourier Transform of the acoustic sources will be used to compute noise at several probes located far away from the region where the hydrodynamics are computed. Directivities as well as spectral profile of the obtained acoustic field will be analyzed.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, long-span bodies

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Bennabhaktula Lavanya

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The study of women, their societal roles, and their importance has been a subject of intense discussion and scholarly inquiry. Researchers have diligently endeavoured to understand the influence of women in the domains of society, economy, culture, and politics, as well as the broader ramifications for society. Women's history aims to improve existing historical accounts by analyzing political institutions, economic events, social frameworks, cultural trends, and primary sources that have historically underprivileged women. The extensive research undertaken has resulted in the formation and recognition of women's history as a valid and unique subject of study within history. The Present paper analyses the academic discipline of Women's History and investigates its changing patterns. Tries to address the challenge of transforming the prevailing historical tradition by using innovative methods and frameworks and analyses the interests, experiences, and achievements of women in order to recreate their perceptions and priorities. The paper also examines the principles of Women's History, Gender Studies, and Feminist History and varying perspectives on women.

Keywords: history, perspectives, research, women

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Authors: Konstantinos Kottikas, Vlasis Stathakopoulos, Ioannis G. Theodorakis, Efthymia Kottika

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Theorists have argued that Market Orientation is comprised of two facets, namely the Market Driven and the Market Driving components. The present theoretical paper centers on the latter, which to date has been notably under-investigated. The term Market Driving (MD) pertains to influencing the structure of the market, or the behavior of market players in a direction that enhances the competitive edge of the firm. Presently, the main objectives of the paper are the specification of key antecedents and outcomes of Market Driving behavior. Market Driving firms behave proactively, by leading their customers and changing the rules of the game rather than by responding passively to them. Leading scholars were the first to conceptually conceive the notion, followed by some qualitative studies and a limited number of quantitative publications. However, recently, academicians noted that research on the topic remains limited, expressing a strong necessity for further insights. Concerning the key antecedents, top management’s Transformational Leadership (i.e. the form of leadership which influences organizational members by aligning their values, goals and aspirations to facilitate value-consistent behaviors) is one of the key drivers of MD behavior. Moreover, scholars have linked the MD concept with Entrepreneurship. Finally, the role that Employee’s Creativity plays in the development of MD behavior has been theoretically exemplified by a stream of literature. With respect to the key outcomes, it has been demonstrated that MD Behavior positively triggers firm Performance, while theorists argue that it empowers the Competitive Advantage of the firm. Likewise, researchers explicate that MD Behavior produces Radical Innovation. In order to test the robustness of the proposed theoretical framework, a combination of qualitative and quantitative methods is proposed. In particular, the conduction of in-depth interviews with distinguished executives and academicians, accompanied with a large scale quantitative survey will be employed, in order to triangulate the empirical findings. Given that it triggers overall firm’s success, the MD concept is of high importance to managers. Managers can become aware that passively reacting to market conditions is no longer sufficient. On the contrary, behaving proactively, leading the market, and shaping its status quo are new innovative approaches that lead to a paramount competitive posture and Innovation outcomes. This study also exemplifies that managers can foster MD Behavior through Transformational Leadership, Entrepreneurship and recruitment of Creative Employees. To date, the majority of the publications on Market Orientation is unilaterally directed towards the responsive (i.e. the Market Driven) component. The present paper further builds on scholars’ exhortations, and investigates the Market Driving facet, ultimately aspiring to conceptually integrate the somehow fragmented scientific findings, in a holistic framework.

Keywords: entrepreneurial orientation, market driving behavior, market orientation

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Authors: Ireen Manase Kabembo, Patrick Chanda

Abstract:

Background: Substance use disorders are among the chronic conditions that affect all age groups. Worldwide, there is an increase in young people affected by SUDs, which implies that more family members are transitioning into the caregiver role. Family caregivers play a buffering role in the formal healthcare system due to their involvement in caring for persons with acute and chronic conditions in the home setting. Family carers of youth with problematic alcohol and marijuana use experience myriad challenges in managing daily care for this medically vulnerable group. In addition, the poor health-seeking behaviours of youth with SUDs characterized by eluding treatment and runaway tendencies coupled with the effects of the pandemic made caregiving a daunting task for most family caregivers. Issues such as limited and unavailable psychotropic medications, social stigma and discrimination, financial hurdles, systemic barriers in adolescent and young adult mental healthcare services, and the lack of a perceived vulnerability to Covid-19 by youth with SUDs are experiences of family caretakers. Methods: A qualitative study with 30 family caregivers of youth aged 16-24 explored their lived experiences and subjective meanings using two in-depth semi-structured interviews, a caregiving timeline, and participant observation. Findings: Results indicate that most family caregivers had challenges managing care for treatment elusive youth, let alone having them adhere to Covid-19 regulations. However, youth who utilized healthcare services and adhered to treatment regimens had positive outcomes and sustained recovery. The effects of the pandemic, such as job losses and the closure of businesses, further exacerbated the financial challenges experienced by family caregivers, making it difficult to purchase needed medications and daily necessities for the youth. The unabated stigma and discrimination of families of substance-dependent youth in Zambian communities further isolated family caregivers, leaving them with limited support. Conclusion: Since young people with SUDs have a compromised mental capacity due to the cognitive impairments that come with continued substance abuse, they often have difficulties making sound judgements, including the need to utilize SUD recovery services. Also, their tendency to not adhere to the Covid-19 pandemic requirements places them at a higher risk for adverse health outcomes in the (post) pandemic era. This calls for urgent implementation of robust youth mental health services that address prevention and recovery for these emerging adults grappling with substance use disorders. Support for their family caregivers, often overlooked, cannot be overemphasized.

Keywords: chronic care management, Covid-19 pandemic, family caregivers, youth with substance use disorders

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

Abstract:

Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: Abdou Khafor Ndiaye

Abstract:

The article examines clean water and sanitation in Saint-Louis region schools. It finds that 59% have clean water, with disparities between departments, urban/rural areas, and school types. Podor and Dagana lack water due to distance and costs. 70% have sanitation, but rural schools lack it due to low investment. Podor and Dagana suffer the most. Many sanitation facilities need renovation. Wastewater treatment is effective, reducing pollutants and nitrogen, but adjustments are needed for nitrates. Treated water meets Senegalese standards and can be used for irrigation but needs monitoring for strict standards. In conclusion, the wastewater system is good for regions with limited water. Meeting stricter European standards and monitoring for health and environmental standards are needed.

Keywords: water, constructed wetland, sanitation, hygiene

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Authors: Faisal Algosair

Abstract:

We examine the role of monetary policy in the presence of commodity price shocks using a Dynamic stochastic general equilibrium (DSGE) model with price and wage rigidities. The model characterizes a commodity exporter by its degree of export diversification, and explores the following monetary regimes: flexible domestic inflation targeting; flexible Consumer Price Index inflation targeting; exchange rate peg; and optimal rule. An increase in the degree of diversification is found to mitigate responses to commodity shocks. The welfare comparison suggests that a flexible exchange rate regime under the optimal rule is preferred to an exchange rate peg. However, monetary policy provides limited stabilization effects in an economy with low degree of export diversification.

Keywords: business cycle, commodity price, exchange rate, global financial cycle

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

Procedia PDF Downloads 378