Search results for: intelligent green energy management system

Authors: S. Rostampour Yasouri, M. Ghane, M. Doudi

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Leptospirosis is one of the most significant infectious and zoonotic diseases along with global spreading. This disease is causative agent of economoic losses and human fatalities in various countries, including Northern provinces of Iran. The aim of this research is to identify and compare the rapid diagnostic techniques of pathogenic leptospiras, considering the multifacetedness of the disease from a clinical manifestation and premature death of patients. In the spring and summer of 2020-2022, 25 fecal samples were collected from suspected leptospirosis patients and 25 Fecal samples from mice residing in the rice fields and factories in Tonekabon city. Samples were prepared by centrifugation and passing through membrane filters. Culture technique was used in liquid and solid EMJH media during one month of incubation at 30°C. Then, the media were examined microscopically. DNA extraction was conducted by extraction Kit. Diagnosis of leptospiras was enforced by PCR and Real time PCR (SYBR Green) techniques using lipL32 specific primer. Out of the patients, 11 samples (44%) and 8 samples (32%) were determined to be pathogenic Leptospira by Real time PCR and PCR technique, respectively. Out of the mice, 9 Samples (36%) and 3 samples (12%) were determined to be pathogenic Leptospira by the mentioned techniques, respectively. Although the culture technique is considered to be the gold standard technique, but due to the slow growth of pathogenic Leptospira and lack of colony formation of some species, it is not a fast technique. Real time PCR allowed rapid diagnosis with much higher accuracy compared to PCR because PCR could not completely identify samples with lower microbial load.

Keywords: culture, pathogenic leptospiras, PCR, real time PCR

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Authors: Luisito L. Lacatan, Gian Carlo J. Bergonia, Felipe C. Buado III, Gerald L. Gono, Ron Mark V. Ortil, Calvin A. Yap

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This paper features the development of a Mobile Self-sustaining Electricity Generator for water distillation process with MCU- based wireless controller & indicator designed to solve the problem of scarcity of clean water. It is a fact that pure water is precious nowadays and its value is more precious to those who do not have or enjoy it. There are many water filtration products in existence today. However, none of these products fully satisfies the needs of families needing clean drinking water. All of the following products require either large sums of money or extensive maintenance, and some products do not even come with a guarantee of potable water. The proposed project was designed to alleviate the problem of scarcity of potable water in the country and part of the purpose was also to identify the problem or loopholes of the project such as the distance and speed required to produce electricity using a wheel and alternator, the required time for the heating element to heat up, the capacity of the battery to maintain the heat of the heating element and the time required for the boiler to produce a clean and potable water. The project has three parts. The first part included the researchers’ effort to plan every part of the project from the conversion of mechanical energy to electrical energy, from purifying water to potable drinking water to the controller and indicator of the project using microcontroller unit (MCU). This included identifying the problem encountered and any possible solution to prevent and avoid errors. Gathering and reviewing related studies about the project helped the researcher reduce and prevent any problems before they could be encountered. It also included the price and quantity of materials used to control the budget.

Keywords: mobile, self – sustaining, electricity generator, water distillation, wireless battery indicator, wireless water level indicator

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Authors: Luan Vardari, Dena Arapi-Vardari

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Financial stability is a critical component of economic growth and development, and it has been recognized as a key policy objective in many countries around the world. In the Western Balkans, financial stability has been a key issue in recent years, with a number of challenges facing the region, including high levels of public debt, weak banking systems, and economic volatility. Corporate finance, which refers to the financial management practices of firms, is an important factor that can impact financial stability. This paper aims to investigate corporate finance's impact on financial stability in Western Balkan countries. This study will use a mixed-methods approach to investigate the impact of corporate finance on financial stability in the Western Balkans. The study will begin with a comprehensive review of the existing literature on corporate finance and financial stability, focusing on the Western Balkan region. This will be followed by an empirical analysis of regional corporate finance practices using data from various industries and firms. The analysis will explore the relationship between corporate finance practices and financial stability, taking into account factors such as regulatory frameworks, economic conditions, and firm size. The results of the study are expected to provide insights into the impact of corporate finance on financial stability in the Western Balkans. Specifically, the study will identify the key corporate finance practices that contribute to financial stability in the region, as well as the challenges and obstacles that firms face in implementing effective corporate finance strategies. The study will also provide recommendations for policymakers and firms looking to enhance financial stability and resilience in the region.

Keywords: financial regulation, debt management, investment decisions, dividend policies, economic volatility, banking systems, public debt, prudent financial management, firm size, policy recommendations

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Authors: Dhananjoy Dutta

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Field studies in lower Gangetic plains of India reveal that over-abstraction of groundwater for irrigation to paddy leads to a substantial depletion of groundwater over the decades, resulting in negative effects on lowering of the water table, drying up of surface water sources and aquifer pollution with leached-out arsenic. The aggravating arsenic toxicity in drinking water is manifested in health problems and ‘arsenicosis’ of people. A social conflict arises between farmers, who intend to grow paddy for livelihoods, and the groundwater authority, which enacts the ‘Regulation Laws’ by putting a check on the excessive installation of private tube-wells for irrigation. Hence, considering the challenges of resource sustainability, health issues, and food security, the study calls for a paradigm shift in policy from further groundwater development to sustainable water resources management and evaluates some strategies integrating supply and demand side management for mitigating the problems.

Keywords: groundwater, irrigation, paddy farming, water table depletion, arsenic pollution, gangetic plains

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Authors: Beata Skibska, Andrzej Stanczak, Agnieszka Skibska

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Nanodiamond (ND) is a carbon nanomaterial that has high biocompatibility, and it has a very positive effect on a number of biochemical processes. NDs have great potential in treating multiple inflammation-associated diseases. The purpose of this study was to investigate the anti-inflammatory effect of nanodiamonds and lipoic acid (LA) (as antioxidants) on rats' cardiovascular systems after lipopolysaccharide (LPS) administration. Animal experiments enabled the determination of how nanodiamonds act when applied independently or in combination with lipoic acid. The effect of NDs and LA on C-reactive protein (CRP) levels and heart edema was evaluated. NDs and LA administered after LPS administration attenuated heart edema and significantly decreased the CRP level. The results suggest that NDs and LA play an important role in LPS-induced inflammation in the heart. NDs find new applications in modern biomedical science and biotechnologies.

Keywords: nanodiamonds, lipoic acid, inflammation, cardiovascular system

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Authors: Manal M. Kame, Hanan G. El-Baz, Zeinab A.Demerdash, Engy M. Abd El-Moneem, Mohamed A. Hendawy, Ibrahim R. Bayoumi

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There is a constant need to improve the performance of current diagnostic assays of schistosomiasis as well as develop innovative testing strategies to meet new testing challenges. This study aims at increasing the diagnostic efficiency of monoclonal antibody (MAb)-based antigen detection assays through gold nanoparticles conjugated with specific anti-Schistosoma mansoni monoclonal antibodies. In this study, several hybidoma cell lines secreting MAbs against adult worm tegumental Schistosoma antigen (AWTA) were produced at Immunology Department of Theodor Bilharz Research Institute and preserved in liquid nitrogen. One MAb (6D/6F) was chosen for this study due to its high reactivity to schistosome antigens with highest optical density (OD) values. Gold nanoparticles (AuNPs) were functionalized and conjugated with MAb (6D/6F). The study was conducted on serum samples of 116 subjects: 71 patients with S. mansoni eggs in their stool samples group (gp 1), 25 with other parasites (gp2) and 20 negative healthy controls (gp3). Patients in gp1 were further subdivided according to egg count in their stool samples into Light infection {≤ 50 egg per gram(epg) (n= 17)}, moderate {51-100 epg (n= 33)} and severe infection {>100 epg(n= 21)}. Sandwich ELISA was performed using (AuNPs -MAb) for detection of circulating schistosomal antigen (CSA) levels in serum samples of all groups and the results were compared with that after using MAb/ sandwich ELISA system. Results Gold- MAb/ ELISA system reached a lower detection limit of 10 ng/ml compared to 85 ng/ml on using MAb/ ELISA and the optimal concentrations of AuNPs -MAb were found to be 12 folds less than that of MAb/ ELISA system for detection of CSA. The sensitivity and specificity of sandwich ELISA for detection of CSA levels using AuNPs -MAb were 100% & 97.8 % respectively compared to 87.3% &93.38% respectively on using MAb/ ELISA system. It was found that CSA was detected in 9 out of 71 S.mansoni infected patients on using AuNPs - MAb/ ELISA system and was not detected by MAb/ ELISA system. All those patients (9) was found to have an egg count below 50 epg feces (patients with light infections). ROC curve analyses revealed that sandwich ELISA using gold-MAb was an excellent diagnostic investigator that could differentiate Schistosoma patients from healthy controls, on the other hand it revealed that sandwich ELISA using MAb was not accurate enough as it could not recognize nine out of 71 patients with light infections. Conclusion Our data demonstrated that: Loading gold nanoparticles with MAb (6D/6F) increases the sensitivity and specificity of sandwich ELISA for detection of CSA, thus active (early) and light infections could be easily detected. Moreover this binding will decrease the amount of MAb consumed in the assay and lower the coast. The significant positive correlation that was detected between ova count (intensity of infection) and OD reading in sandwich ELISA using gold- MAb enables its use to detect the severity of infections and follow up patients after treatment for monitoring of cure.

Keywords: Schistosomiasis, nanoparticles, gold, monoclonal antibodies, ELISA

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Authors: Paulina Solórzano Salgado, Luis Rodrigo Valencia Pérez, Alberto de Jesús Pastrana Palma

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In this research, it is presented a digital maturity framework, which contributes to the development of small and medium-sized enterprises (SMEs) in the commercial sector. This proposal is based on three important concepts: Marketing activities in the enterprise, information and communication technologies ICT, as well as Innovation. Prior to the development of this framework, was formulated a quantitative assessment tool through a literature review, and was validated with a method used by experts, and which determines the relationship of digital marketing and innovation activities in companies. The instrument was applied to 64 Mexican companies from the Made in Mexico database, which allowed both descriptive results and correlation results. These contributed to the development of the methodology, and confirming that the management of digital marketing has a positive relation with innovation activities of companies. Also, that analytics in digital marketing is a source for its development. In this paper, the management stages and activities are presented to be developed by companies in order to generate knowledge, which will allow them to reach its digital maturity.

Keywords: digital marketing, digital maturity, innovation, SMEs

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Authors: Kelsey Kimball

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Generalized anxiety disorder (GAD) is a common mental health illness affecting approximately 10% of the perinatal population. Research examining cognitive behavioral therapy in this population has only recently become more prevalent though exploring this subject is long overdue. This research examines the impact of cognitive behavioral therapy (CBT) on GAD during the perinatal period. The aim of this project was to identify the most effective way to manage GAD during the perinatal period to provide clinicians with evidence-based methods of caring for this population’s mental health. The research was conducted using several databases to identify ten primary research articles involving anxiety management. A critique and a systematic review of the literature was done. The results of the systematic literature review suggested that CBT had a significant positive impact on perinatal anxiety. Three main themes were derived from the literature: CBT for managing GAD in the general population, CBT for managing GAD in the perinatal population, and CBT’s effect on worry and problematic behaviors in both populations. Nurse practitioners are central in improving access to and treatment of perinatal anxiety disorders.

Keywords: anxiety, cognitive behavioral therapy, nurse practitioner, perinatal

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Authors: Riccardo Bonazzi, Michaël Poli, Abeba Nigussie Turi

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This paper presents an applied research of a new module for the financial administration and management industry, Personalizable and Automated Checklists Integrator, Overseeing Legal Investigations (PACIOLI). It aims at designing the business model of the trust company of the future. By identifying the key stakeholders, we draw a general business process design of the industry. The business model focuses on disintermediating the traditional form of business through the new technological solutions of a software company based in Switzerland and hence creating a new interactive platform. The key stakeholders of this interactive platform are identified as IT experts, legal experts, and the New Edge Trust Company (NATC). The mechanism we design and propose has a great importance in improving the efficiency of the financial business administration and management industry, and it also helps to foster the provision of high value added services in the sector.

Keywords: new edge trust company, business model design, automated checklists, financial technology

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Authors: Olga Biedova, Victoria Steblovskaya, Kai Wallbaum

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In the current capital market environment, investors constantly face the challenge of finding a successful and stable investment mechanism. Highly volatile equity markets and extremely low bond returns bring about the demand for sophisticated yet reliable risk management strategies. Investors are looking for risk management solutions to efficiently protect their investments. This study compares a classic Constant Proportion Portfolio Insurance (CPPI) strategy to a Volatility Target portfolio insurance (VTPI). VTPI is an extension of the well-known Option Based Portfolio Insurance (OBPI) to the case where an embedded option is linked not to a pure risky asset such as e.g., S&P 500, but to a Volatility Target (VolTarget) portfolio. VolTarget strategy is a recently emerged rule-based dynamic asset allocation mechanism where the portfolio’s volatility is kept under control. As a result, a typical VTPI strategy allows higher participation rates in the market due to reduced embedded option prices. In addition, controlled volatility levels eliminate the volatility spread in option pricing, one of the frequently cited reasons for OBPI strategy fall behind CPPI. The strategies are compared within the framework of the stochastic dominance theory based on numerical simulations, rather than on the restrictive assumption of the Black-Scholes type dynamics of the underlying asset. An extended comparative quantitative analysis of performances of the above investment strategies in various market scenarios and within a range of input parameter values is presented.

Keywords: CPPI, portfolio insurance, stochastic dominance, volatility target

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Authors: Neha Gupta, Sonika Verma, Seema Puri, Nikhil Tandon, Narendra K. Arora

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The concurrent increasing prevalence of underweight and overweight/obesity among children with changing lifestyle and the rapid transitioning society has necessitated the need for a unifying/multi-level approach to understand the determinants of the problem. The present community-based cross-sectional research study was conducted to assess the associations between lifestyle behavior and food environment of the child at household, neighborhood, and school with the BMI of children (6-12 year old) (n=612) residing in three rural clusters of Palwal district, Haryana. The study used innovative and robust methods for assessing the lifestyle and various components of food environment in the study. The three rural clusters selected for the study were located at three different locations according to their access to highways in the SOMAARTH surveillance site. These clusters were significantly different from each other in terms of their socio-demographic and socio-economic profile, living conditions, environmental hygiene, health seeking behavior and retail density. Despite of being different, the quality of living conditions and environmental hygiene was poor across three clusters. The children had higher intakes of dietary energy and sugars; one-fifth share of the energy being derived from unhealthy foods, engagement in high levels of physical activity and significantly different food environment at home, neighborhood and school level. However, despite having a high energy intake, 22.5% of the recruited children were thin/severe thin, and 3% were overweight/obese as per their BMI-for-age categories. The analysis was done using multi-variate logistic regression at three-tier hierarchy including individual, household and community level. The factors significantly explained the variability in governing the risk of getting thin/severe thin among children in rural area (p-value: 0.0001; Adjusted R2: 0.156) included age (>10years) (OR: 2.1; 95% CI: 1.0-4.4), the interaction between minority category and poor SES of the household (OR: 4.4; 95% CI: 1.6-12.1), availability of sweets (OR: 0.9; 95% CI: 0.8-0.99) and cereals (OR: 0.9; 95% CI: 0.8-1.0) in the household and poor street condition (proxy indicator of the hygiene and cleanliness in the neighborhood) (OR: 0.3; 95% CI: 0.1-1.1). The homogeneity of other factors at neighborhood and school level food environment diluted the heterogeneity in the lifestyles and home environment of the recruited children and their households. However, it is evident that when various individual factors interplay at multiple levels amplifies the risk of undernutrition in a rural community. Conclusion: These rural areas in Haryana are undergoing developmental, economic and societal transition. In correspondence, no improvements in the nutritional status of children have happened. Easy access to the unhealthy foods has become a paradox.

Keywords: transition, food environment, lifestyle, undernutrition, overnutrition

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Authors: Ravi Patel, Ravisinh Solanki, Dignesh Khunt

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A stability-indicating reverse phase high performance liquid chromatography (RP-HPLC) method was developed and validated for estimating Nirmatrelvir in its self-emulsifying drug delivery system (SEDDS). The separation of Nirmatrelvir and its degradation products was accomplished by employing an Agilent Zorbax Eclipse plus C18 (250 mm x 4.6 mm, 5 µm) column, through which the mobile phase 5 mM phosphate buffer (pH 4.0) as mobile phase A and Acetonitrile as mobile phase B in a ratio of (40:60 % v/v) was pumped at a flow rate of 1.0 mL/min, through the HPLC system. Chromatographic separation and elution were monitored by a photo-diode array detector at 210 nm. Stress studies have been employed to evaluate this method's ability to indicate stability. Nirmatrelvir was exposed to several stress conditions, such as acid, alkali, oxidative, photolytic, and thermal degradations. Significant degradation was observed during acid and alkali hydrolysis, and the resulting degradation product was successfully separated from the Nirmatrelvir peak, preventing any interference. Furthermore, the primary degradant produced under alkali degradation conditions was identified using UPLC-ESI-TQ-MS/MS. The method was validated in accordance with the International Council on Harmonization (ICH) and found to be selective, precise, accurate, linear, and robust. The apparent permeability of Nirmatrelvir SEDDS was 4.20 ± 0.21×10-6 cm/sec, and the average proportion of free drug recovered was 0.5%. The method developed in this study was feasible and accurate for routine quality control evaluation of Nirmatrelvir SEDDS.

Keywords: Nirmatrelvir, SEDDS, degradation study, HPLC, LC-MS/MS

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Authors: Byung Cheol Kim

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The Program Evaluation and Review Technique (PERT) is widely used for project management, but it struggles with subjective distributions, particularly due to its assumptions of constant variance and light tails. To overcome these limitations, we propose the Generalized PERT (G-PERT) model, which enhances PERT by incorporating variability in three-point subjective estimates. Our methodology extends the original PERT model to cover the full range of unimodal beta distributions, enabling the model to handle thick-tailed distributions and offering formulas for computing mean and variance. This maintains the simplicity of PERT while providing a more accurate depiction of uncertainty. Our empirical analysis demonstrates that the G-PERT model significantly improves performance, particularly when dealing with heavy-tail subjective distributions. In comparative assessments with alternative models such as triangular and lognormal distributions, G-PERT shows superior accuracy and flexibility. These results suggest that G-PERT offers a more robust solution for project estimation while still retaining the user-friendliness of the classic PERT approach.

Keywords: PERT, subjective distribution, project management, flexible variance

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Authors: Mark Watson, J.-F. Bousquet, Adam Forget

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A magnetic induction based underwater communication link is evaluated using an analytical model and a custom Finite-Difference Time-Domain (FDTD) simulation tool. The analytical model is based on the Sommerfeld integral, and a full-wave simulation tool evaluates Maxwell’s equations using the FDTD method in cylindrical coordinates. The analytical model and FDTD simulation tool are then compared and used to predict the system performance for various transmitter depths and optimum frequencies of operation. To this end, the system bandwidth, signal to noise ratio, and the magnitude of the induced voltage are used to estimate the expected channel capacity. The models show that in seawater, a relatively low-power and small coils may be capable of obtaining a throughput of 40 to 300 kbps, for the case where a transmitter is at depths of 1 to 3 m and a receiver is at a height of 1 m.

Keywords: magnetic induction, FDTD, underwater communication, Sommerfeld

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Authors: Afshin Zohdi, Selçuk Özdemir, Mustafa Aksoy

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Tungsten carbide-cobalt (WC-Co) is a widely utilized material for cold forming dies, including those employed in fastener production. In this study, we investigated the effectiveness of the pack boriding method in improving the surface properties of WC-Co cold forging dies. The boriding process involved embedding WC-Co samples, along with a steel control sample, within a chamber made of H13 tool steel. A boriding powder mixture was introduced into the chamber, which was then sealed using a paste. Subsequently, the samples were subjected to a temperature of 700°C for 5 hours in a furnace. Microstructural analysis, including cross-sectional examination and scanning electron microscopy (SEM), confirmed successful boron diffusion and its presence on the surface of the borided samples. The microhardness of the borided layer was significantly increased (3980 HV1) compared to the unborided sample (1320 HV3), indicating enhanced hardness. The borided layer exhibited an acceptable thickness of 45 microns, with a diffusion coefficient of 1.125 × 10-7 mm²/s, signifying a moderate diffusion rate. Energy-dispersive X-ray spectroscopy (EDS) mapping revealed an increase in boron content, desirable for the intended purpose, while an undesired increase in oxygen content was observed. Furthermore, the pin-on-disk wear test demonstrated a reduction in friction coefficient, indicating improved mechanical and tribological properties of the surface. The successful implementation of the pack boriding process highlights its potential for enhancing the performance of WC-Co cold forging dies.

Keywords: WC-Co, cold forging dies, pack boriding, surface hardness, wear resistance, microhardness, diffusion coefficient, scanning electron microscopy, energy-dispersive X-ray spectroscopy

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Irina Khutsishvili

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The presented study develops a decision support methodology for multi-criteria group decision-making problem. The proposed methodology is based on the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach in the hesitant fuzzy environment. The main idea of decision-making problem is a selection of one best alternative or several ranking alternatives among a set of feasible alternatives. Typically, the process of decision-making is based on an evaluation of certain criteria. In many MCDM problems (such as medical diagnosis, project management, business and financial management, etc.), the process of decision-making involves experts' assessments. These assessments frequently are expressed in fuzzy numbers, confidence intervals, intuitionistic fuzzy values, hesitant fuzzy elements and so on. However, a more realistic approach is using linguistic expert assessments (linguistic variables). In the proposed methodology both the values and weights of the criteria take the form of linguistic variables, given by all decision makers. Then, these assessments are expressed in triangular fuzzy numbers. Consequently, proposed approach is based on triangular hesitant fuzzy TOPSIS decision-making model. Following the TOPSIS algorithm, first, the fuzzy positive ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. Based on proposed approach the software package has been developed, which was used to rank investment projects in the real investment decision-making problem. The application and testing of the software were carried out based on the data provided by the ‘Bank of Georgia’.

Keywords: fuzzy TOPSIS approach, investment project, linguistic variable, multi-criteria decision making, triangular hesitant fuzzy set

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Authors: Yessi Rahmawati, Andiga Kusuma Nur Ichsan, Fitria Nur Anggraeni

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Climate change is one of the focus studies that many researchers focus on in the present world, either in the emerging countries or developed countries which is one of the main pillars on Sustainable Development Goals (SDGs). There is on-going discussion that climate change can affect natural disaster, namely drought, storm, flood, and many others; and also the impact on human life. East Java is the best performances and has economic potential that should be utilized. Despite the economic performance and high agriculture productivity, East Java has the highest number of people under the poverty line. The present study is to measuring the contribution of drought and productivity of agriculture to the poverty in East Java, Indonesia, using spatial econometrics analysis. The authors collect data from 2008 – 2015 from Indonesia’s Ministry of Agriculture, Natural Disaster Management Agency (BNPB), and Official Statistic (BPS). First, the result shows the existence of spatial autocorrelation between drought and poverty. Second, the present research confirms that there is strong relationship between drought and poverty. the majority of farmer in East Java are still relies on the rainfall and traditional irrigation system. When the drought strikes, mostly the farmer will lose their income; make them become more vulnerable household, and trap them into poverty line. The present research will give empirical studies regarding drought and poverty in the academics world.

Keywords: SDGs, drought, poverty, Indonesia, spatial econometrics, spatial autocorrelation

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Authors: Djehich Mohamed Yousri

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The field of political science is one of the sciences in which there is much controversy, in terms of the multiplicity of schools, trends, and goals. This overlap and complexity in the interpretation of the political phenomenon in political science has been linked to other disciplines associated with it, and the science of international relations and the huge amount of theories that have found a wide range and a decisive position after the national tide in the history of Western political thought, especially after the Westphalia Conference 1648, and as a result was approved The new foundations of international politics, the most important of which is respect for state sovereignty. Historical events continued and coincided with scientific, intellectual, and economic developments following the emergence of the industrial revolution, followed by the technological revolutions in all their contents, which led to the rooting and establishment of a comprehensive political system that is more complex and overlapping than it was in the past during the First and Second World Wars. The international situation has become dependent on the digital revolution and its aspirations in The comprehensive transformation witnessed by international political relations after the Cold War.

Keywords: theorizing, international relations, approaches to international relations, political science, the political system

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Authors: Chris George, Adam Hamlin, Lily Pereg, Richard Charlesworth, Gal Winter

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Background: According to the ‘hygiene hypothesis’ the current rise in allergies and autoimmune diseases stems mainly from reduced microbial exposure due, amongst other factors, to urbanisation and distance from soil. However, this hypothesis is based on epidemiological and not biological data. Useful insights into the underlying mechanisms of this hypothesis can be gained by studying our interaction with soil. Soil microbiota may be directly ingested or inhaled by humans, enter the body through skin-soil contact or using plants as vectors. This study aims to examine the ability of soil microbiota to colonise the gut, study the interaction of soil microbes with the immune system and their potential protective activity. Method: The nutrition of the rats was supplemented daily with fresh or autoclaved soil for 21 days followed by 14 days of no supplementations. Faecal samples were collected throughout and analysed using 16S sequencing. At the end of the experiment rats were sacrificed and tissues and digesta were collected. Results/Conclusion: Results showed significantly higher richness and diversity following soil supplementation even after recovery. Specific soil microbial groups identified as able to colonise the gut. Of particular interest was the mucosal layer which emerged as a receptive host for soil microorganisms. Histological examination revealed innate and adaptive immune activation. Findings of this study reinforce the ‘hygiene hypothesis’ by demonstrating the ability of soil microbes to colonise the gut and activate the immune system. This paves the way for further studies aimed to examine the interaction of soil microorganisms with the immune system.

Keywords: gut microbiota, hygiene hypothesis, microbiome, soil

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

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Authors: Sristi Silwal

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South Asian rivers support ecosystems and sustain well-being of thousands of riparian communities. Rivers however are also sources of conflict between countries and one of the contested issues between governments of the region. Governments have signed treaties to harness some of the rivers but their provisions have not been successful in improving the quality of life of those who depend on water as common property resources. This paper will present a case of the study of the status of the water commons along the lower command areas of Koshi, Gandka and Mahakali rivers. Nepal and India have signed treaties for development and management of these rivers in 1928, 1954 and 1966. The study investigated perceptions of the local community on climate-induced disasters, provision of the treaties such as water for irrigation, participation in decision-making and specific impact of women. It looked at how the local community coped with adversities. The study showed that the common pool resources are gradually getting degraded, flood events increasing while community blame ‘other state’ and state administration for exacerbating these ills. The level of awareness about provisions of existing treatise is poor. Ongoing approach to trans-boundary water management has taken inadequate cognizance of these realities as the dominant narrative perpetuates cooperation between the governments. The paper argues that on-going discourses on trans-boundary water development and management need to use a new metrics of taking cognizance of the condition of the commons and that of the people depended on them for sustenance. In absence of such narratives, the scale of degradation would increase making those already marginalized more vulnerable to impacts of global climate change.

Keywords: climate change vulnerability, conflict, cooperation, water commons

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Authors: Shivani Thakur, Jasmin Dominguez Cervantes, Ahmed Zabiba, Fatima Zabiba, Sandhini Agarwal, Kamalpreet Kaur, Hussein Maatouk, Shae Chand, Omar Madriz, Tiffany Huang, Saloni Bansal

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The prevalence of lymphedema in women in rural communities highlights the importance of developing effective treatment and prevention methods. Subjects with secondary lymphedema in California’s Central Valley were surveyed at 6 surgical clinics to assess demographics and symptoms of lymphedema. Additionally, subjects on semaglutide treatment for obesity and/or T2DM were monitored for their diabetes management, weight loss progress, and lymphedema symptoms compared to subjects who were not treated with semaglutide. The subjects were followed for 12 months. Subjects who were treated with semaglutide completed pre-treatment questionnaires and follow-up post-treatment questionnaires at 3, 6, 9, 12 months, along with medical assessment. The untreated subjects completed similar questionnaires. The questionnaires investigated subjective feelings regarding lymphedema symptoms and management using a Likert-scale; quantitative leg measurements were collected, and blood work reviewed at these appointments. Paired difference t-tests, chi-squared tests, and independent sample t-tests were performed. 50 subjects, aged 18-75 years, completed the surveys evaluating secondary lymphedema: 90% female, 69% Hispanic, 45% Spanish speaking, 42% disabled, 57 % employed, 54% income range below 30 thousand dollars, and average BMI of 40. Both treatment and non-treatment groups noted the most common symptoms were leg swelling (x̄=3.2, ▁d= 1.3), leg pain (x̄=3.2, ▁d=1.6 ), loss of daily function (x̄=3, ▁d=1.4 ), and negative body image (x̄=4.4, ▁d=0.54). Subjects in the semaglutide treatment group >3 months of treatment compared to the untreated group demonstrated: 55% subject in the treated group had a 10% weight loss vs 3% in the untreated group (average BMI reduction by 11% vs untreated by 2.5%, p<0.05) and improved subjective feelings about their lymphedema symptoms: leg swelling (x̄=2.4, ▁d=0.45 vs x̄=3.2, ▁d=1.3, p<0.05), leg pain (x̄=2.2, ▁d=0.45 vs x̄= 3.2, ▁d= 1.6, p<0.05), and heaviness (x̄=2.2, ▁d=0.45 vs x̄=3, ▁d=1.56, p<0.05). Improvement in diabetes management was demonstrated by an average of 0.9 % decrease in A1C values compared to untreated 0.1 %, p<0.05. In comparison to untreated subjects, treatment subjects on semaglutide noted 6 cm decrease in the circumference of the leg, knee, calf, and ankle compared to 2 cm in untreated subjects, p<0.05. Semaglutide was shown to significantly improve weight loss, T2DM management, leg circumference, and secondary lymphedema functional, physical and psychosocial symptoms.

Keywords: diabetes, secondary lymphedema, semaglutide, obesity

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Authors: Erik Vassøy Olsen, Hirpa G. Lemu

Abstract:

Inspired by the Formula-1 competition, IMechE (Institute of Mechanical Engineers) and Formula SAE (Society of Mechanical Engineers) organize annual competitions for University and College students worldwide to compete with a single-seat race car they have designed and built. The design of the chassis or the frame is a key component of the competition because the weight and stiffness properties are directly related with the performance of the car and the safety of the driver. In addition, a reduced weight of the chassis has a direct influence on the design of other components in the car. Among others, it improves the power to weight ratio and the aerodynamic performance. As the power output of the engine or the battery installed in the car is limited to 80 kW, increasing the power to weight ratio demands reduction of the weight of the chassis, which represents the major part of the weight of the car. In order to reduce the weight of the car, ION Racing team from the University of Stavanger, Norway, opted for a monocoque design. To ensure fulfilment of the above-mentioned requirements of the chassis, the monocoque design should provide sufficient torsional stiffness and absorb the impact energy in case of a possible collision. The study reported in this article is based on the requirements for Formula Student competition. As part of this study, diverse mechanical tests were conducted to determine the mechanical properties and performances of the monocoque design. Upon a comprehensive theoretical study of the mechanical properties of sandwich composite materials and the requirements of monocoque design in the competition rules, diverse tests were conducted including 3-point bending test, perimeter shear test and test for absorbed energy. The test panels were homemade and prepared with an equivalent size of the side impact zone of the monocoque, i.e. 275 mm x 500 mm so that the obtained results from the tests can be representative. Different layups of the test panels with identical core material and the same number of layers of carbon fibre were tested and compared. Influence of the core material thickness was also studied. Furthermore, analytical calculations and numerical analysis were conducted to check compliance to the stated rules for Structural Equivalency with steel grade SAE/AISI 1010. The test results were also compared with calculated results with respect to bending and torsional stiffness, energy absorption, buckling, etc. The obtained results demonstrate that the material composition and strength of the composite material selected for the monocoque design has equivalent structural properties as a welded frame and thus comply with the competition requirements. The developed analytical calculation algorithms and relations will be useful for future monocoque designs with different lay-ups and compositions.

Keywords: composite material, Formula student, ION racing, monocoque design, structural equivalence

Procedia PDF Downloads 497

Authors: Saskya E. Carrera P., Ben Hankamer, Melanie Oey

Abstract:

The green alga C. reinhardtii provides a platform for the cheap, scalable, and safe production of complex proteins. Despite gene expression in photosynthetic organisms being tightly regulated by light, most expression studies have analysed chloroplast recombinant protein production under constant light. Here the influence of illumination time and intensity on GFP and a GFP-PlyGBS (bacterial-lysin) fusion protein expression was investigated. The expression of both proteins was strongly influenced by the light regime (6-24 hr illumination per day), the light intensity (0-450 E m⁻²s⁻¹) and growth condition (photoautotrophic, mixotrophic and heterotrophic). Heterotrophic conditions resulted in relatively low recombinant protein yields per unit volume, despite high protein yields per cell, due to low growth rates. Mixotrophic conditions exhibited the highest yields at 6 hrs illumination at 200µE m⁻²s⁻¹ and under continuous low light illumination (13-16 mg L⁻¹ GFP and 1.2-1.6 mg L⁻¹ GFP-PlyGBS), as these conditions supported good cell growth and cellular protein yields. A ~23-fold increase in protein accumulation per cell and ~9-fold increase L⁻¹ culture was observed compared to standard constant 24 hr illumination for GFP-PlyGBS. The highest yields under photoautotrophic conditions were obtained under 9 hrs illumination (6 mg L⁻¹ GFP and 2.1 mg L⁻¹ GFP-PlyGBS). This represents a ~4-fold increase in cellular protein accumulation for GFP-PlyGBS. On a volumetric basis the highest yield was at 15 hrs illumination (~2-fold increase L⁻¹ over the constant light for GFP-PlyGBS). Optimising illumination conditions to balance growth and protein expression can thus significantly enhance overall recombinant protein production in C. reinhardtii cultures.

Keywords: chlamydomonas reinhardtii, light, mixotrophic, recombinant protein

Procedia PDF Downloads 249

Authors: Azri Yamina Mounia, Zitouni Dalila, Aziza Majda, Tou Insaf, Sadi Meriem

Abstract:

To confront the fossil fuel crisis and the consequences of global warning, many efforts were devoted to develop alternative electricity generation and attracted numerous researchers, especially in the microbial fuel cell field, because it allows generating electric energy and degrading multiple organics compounds at the same time. However, one of the main constraints on power generation is the slow rate of oxygen reduction at the cathode electrode. This paper describes the potential of algal biomass (Chlorella vulgaris) as photosynthetic cathodes, eliminating the need for a mechanical air supply and the use of often expensive noble metal cathode catalysts, thus improving the sustainability and cost-effectiveness of the MFC system. During polarizations, MFC power density using algal biomass was 0.4mW/m², whereas the MFC with mechanic aeration showed a value of 0.2mW/m². Chlorella vulgaris was chosen due to its fastest growing. C. vulgaris grown in BG11 medium in sterilized Erlenmeyer flask. C. vulgaris was used as a bio‐cathode. Anaerobic activated sludge from the plant of Beni‐Messous WWTP(Algiers) was used in an anodic compartment. A dual‐chamber reactor MFC was used as a reactor. The reactor has been fabricated in the laboratory using plastic jars. The cylindrical and rectangular jars were used as the anode and cathode chambers, respectively. The volume of anode and cathode chambers was 0.8 and 2L, respectively. The two chambers were connected with a proton exchange membrane (PEM). The plain graphite plates (5 x 2cm) were used as electrodes for both anode and cathode. The cyclic voltammetry analysis of oxygen reduction revealed that the cathode potential was proportional to the amount of oxygen available in the cathode surface electrode. In the case of algal aeration, the peak reduction value of -2.18A/m² was two times higher than in mechanical aeration -1.85A/m². The electricity production reached 70 mA/m² and was stimulated immediately by the oxygen produced by algae up to the value of 20 mg/L.

Keywords: Chlorella vulgaris, cyclic voltammetry, microbial fuel cell, oxygen reduction

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Kusum Tharani, Ratna Dahiya

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This paper aims to analyze the power flow of a grid connected 100-kW Photovoltaic(PV) array connected to a 25-kV grid via a DC-DC boost converter and a three-phase three-level Voltage Source Converter (VSC). Maximum Power Point Tracking (MPPT) is implemented in the boost converter bymeans of a Simulink model using the 'Perturb & Observe' technique. First, related papers and technological reports were extensively studied and analyzed. Accordingly, the system is tested under various loading conditions. Power flow analysis is done using the Newton-Raphson method in Matlab environment. Finally, the system is subject to Single Line to Ground Fault and Three Phase short circuit. The results are simulated under the grid-connected operating model.

Keywords: grid connected PV Array, Newton-Raphson Method, power flow analysis, three phase fault

Procedia PDF Downloads 549

Authors: Philippe Larvet

Abstract:

This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

Procedia PDF Downloads 216

Authors: Sedigheh Salemi, Mahnaz Sanjari, Maryam Aalaa, Mohammad Mirzabeigi

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Clinical governance is the framework within which the health service provider is required to ongoing accountability and improvement of the quality of their services. This cross-sectional study was conducted in 661 nurses who work in government hospitals from 35 hospitals of 9 provinces in Iran. The study was approved by the Nursing Council and was carried out with the authorization of the Research Ethics Committee. The questionnaire included 24 questions in which 4 questions focused on clinical governance defining from the nurses' perspective. The reliability was evaluated by Cronbach's alpha (α=0/83). Statistical analyzes were performed, using SPSS version 16. Approximately 40% of nurses correctly answered that clinical governance is not "system of punishment and rewards for the staff". The most nurses believed that "clinical efficacy" is one of the main components of clinical governance. A few of nurses correctly responded that "Evidence Based Practice" and "management" is not part of clinical governance. The small number of nurses correctly answered that the "maintenance of patient records" and "to recognize the adverse effects" is not the role of nurse in clinical governance. Most "do not know" answer was to the "maintenance of patient records". The most nurses unanimously believed that the implementation of clinical governance led to "promoting the quality of care". About a third of nurses correctly stated that the implementation of clinical governance will not lead to "an increase in salaries and benefits of the medical team". As a member of the health team, nurses are responsible in terms of participation in quality improvement and it is necessary to create an environment in which clinical care will flourish and serve to preserve the high standards.

Keywords: clinical governance, nurses, salary, health team

Procedia PDF Downloads 427