Search results for: anticipated consumption guilt

Authors: Steven Woods

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The use of Corporate Social Responsibility Statements has become ubiquitous in society. The appeal to consumers by being a well-behaved social entity has become a strategy not just to ensure brand loyalty but also to further larger scale projects of corporate interests. Specifically, the use of CSR to position corporations as good planetary citizens involves not just self-promotion but also a way of transferring responsibility from systems to individuals. By using techniques labeled as “greenwashing” and emphasizing ethical consumption choices as the solution, corporations present themselves as good members of the community and pursuing sustainability. Ultimately, the primary function of Corporate Social Responsibility statements is to maintain the economic status quo of ongoing growth and consumption while presenting and environmentally progressive image to the public, as well as reassuring them corporate behavior is superior to government intervention. By analyzing the communication techniques utilized through content analysis of specific examples, along with an analysis of the frames of meaning constructed in the CSR statements, the practices of Corporate Responsibility and Sustainability will be addressed from an ethical perspective.

Keywords: corporate social responsibility, ethics, greenwashing, sustainability

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Authors: Pallavi Roe

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Violent crime is a significant public safety concern in urban areas across the United States, and Washington, DC, is no exception. This research discusses the prevalence and types of crime, particularly violent crime, in Washington, DC, along with the factors contributing to the high rate of violent crime in the city, including poverty, inequality, access to guns, and racial disparities. The organizations working towards ensuring safety in neighborhoods are also listed. The proposal to perform spatial and temporal analysis on violent crime and the use of guns in crime analysis is presented to identify patterns and trends to inform evidence-based interventions to reduce violent crime and improve public safety in Washington, DC. The stakeholders for crime analysis are also discussed, including law enforcement agencies, prosecutors, judges, policymakers, and the public. The anticipated result of the spatial and temporal analysis is to provide stakeholders with valuable information to make informed decisions about preventing and responding to violent crimes.

Keywords: crime analysis, spatial analysis, temporal analysis, violent crime

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Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

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Authors: A. Anitha, M. Aishwariya

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The realization of truly ubiquitous wireless sensor networks (WSN) demands Ultra-low power wireless communication capability. Because the radio transceiver in a wireless sensor node consumes more power when compared to the computation part it is necessary to reduce the power consumption. Hence, a low power transceiver is designed and implemented in a 120 nm CMOS technology for wireless sensor nodes. The power consumption of the transceiver is reduced still by maintaining the sensitivity. The transceiver designed combines the blocks including differential oscillator, mixer, envelope detector, power amplifiers, and LNA. RF signal modulation and demodulation is carried by On-Off keying method at 2.4 GHz which is said as ISM band. The transmitter demonstrates an output power of 2.075 mW while consuming a supply voltage of range 1.2 V-5.0 V. Here the comparison of LNA and power amplifier is done to obtain an amplifier which produces a high gain of 1.608 dB at receiver which is suitable to produce a desired sensitivity. The multistage RF amplifier is used to improve the gain at the receiver side. The power dissipation of the circuit is in the range of 0.183-0.323 mW. The receiver achieves a sensitivity of about -95 dBm with data rate of 1 Mbps.

Keywords: CMOS, envelope detector, ISM band, LNA, low power electronics, PA, wireless transceiver

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Authors: Shotiros Protong

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In recent years, Thailand has been affected by climate change phenomenon, which is clearly seen from the season change for different times. The occurrence of violent storms, heavy rains, floods, and drought were found in several areas. In a long dry period, the water supply is not adequate in drought areas. Nowadays, it is renowned that there is a significant decrease of rainwater use for household consumption in rural area of Thailand. Rainwater harvesting is the practice of collection and storage of rainwater in storage tanks before it is lost as surface run-off. Rooftop rainwater harvesting is used to provide drinking water, domestic water, and water for livestock. Rainwater harvesting in households is an alternative for people to readily prepare water resources for their own consumptions during the drought season, can help mitigate flooding of flooded plains, and also may reduce demand on the basin and well. It also helps in the availability of potable water, as rainwater is substantially free of salts. Application of rainwater harvesting in rural water system provide a substantial benefit for both water supply and wastewater subsystems by reducing the need for clean water in water distribution systems, less generated storm water in sewer systems, and a reduction in storm water runoff polluting freshwater bodies. The combination of rainwater quality and rainfall quantity is used to determine proper rainwater harvesting for household consumption to be safe and adequate for survivals. Rainwater quality analysis is compared with the drinking water standard. In terms of rainfall quantity, the observed rainfall data are interpolated by GIS 10.5 and showed by map during 1980 to 2020, used to assess the annual yield for household consumptions.

Keywords: rainwater harvesting, drinking water standard, annual yield, rainfall quantity

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Authors: Doga Erisik, Ahmet Karaman, Gulfem Alptekin, Ozlem Durmaz Incel

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Augmented reality (AR) is a type of virtual reality aiming to duplicate real world’s environment on a computer’s video feed. The mobile application, which is built for this project (called SARAS), enables annotating real world point of interests (POIs) that are located near mobile user. In this paper, we aim at introducing a robust and simple algorithm for placing labels in an augmented reality system. The system places labels of the POIs on the mobile device screen whose GPS coordinates are given. The proposed algorithm is compared to an existing one in terms of energy consumption and accuracy. The results show that the proposed algorithm gives better results in energy consumption and accuracy while standing still, and acceptably accurate results when driving. The technique provides benefits to AR browsers with its open access algorithm. Going forward, the algorithm will be improved to more rapidly react to position changes while driving.

Keywords: accurate tagging algorithm, augmented reality, localization, location-based AR

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Authors: Edit Xhajanka, Gresa Baboci, Irene Malagnino, Mimoza Canga, Vito Antonio Malagnino

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Purpose: This study aimed at identifying dental caries increment or reduction, based on factors such as smoking, the scaling of teeth, BMI before and during pregnancy, carbohydrates consumption in relation to childbirth. Material and method: In this observational study, the sample included a total of 98 pregnant women and their age class was 18-45 years old, with a median age of 31.5 years. The setting of the participants resides in Vlora –Albania. Moreover, 64.4% were from the city and 35.6% were from the nearby villages. The study was conducted in the time period January 2018 –June 2021. Body mass index (BMI) was calculated using the standard formula (kg/m²). Maternal pre, during and post-pregnancy BMI was collected by using a validated questionnaire. Statistical analysis was performed using IBM SPSS Statistics 23.0. The significance level (α) was set at 0.05, whereas P-value and analysis of variance (ANOVA) were used to analyze the data. Results: Based on the data analysis, 44.4% of the sample declared that they did smoke before pregnancy and 55.6% not smoked during their pregnancy. As a result, no association was found between smoking and length of pregnancy P=0.95. There is also a strong relation (P=0.000) between the number of teeth with caries before pregnancy and the number of teeth with caries during pregnancy. There is a significant relationship between the scaling of teeth and childbirth, P=0.05. BMI before and during pregnancy in relation to carbohydrates consumption have a significant correlation P=0.004 and P=0.002. The values of BMI before and during pregnancy in relation to childbirth have a strong correlation: P=0.043 and P=0.040, respectively. As a result, obesity was associated with preterm birth. The percentage of children born during 34-36 weeks of pregnancy was 69%, and children born during 32-34 weeks of pregnancy were 31%. CONCLUSION: There was a positive association between dental caries experience, BMI and carbohydrates consumption. Obesity in pregnancy is increasing worldwide; that is why this study suggests the importance of an appropriate weight before and during pregnancy.

Keywords: BMI, dental caries, pregnancy, scaling, smoking

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Authors: Prima Fithri, Lusi Susanti, Karin Bestarina

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Indonesia's electrification ratio is still around 80.1%, which means that approximately 19.9% of households in Indonesia have not been getting the flow of electrical energy. Household electricity consumptions in Indonesia are generally still dominated by the public urban. In the city of Padang, West Sumatera, Indonesia, about 94.10% are power users of government services (PLN). The most important thing of the issue is human resources efficient energy. Consumer behavior in utilizing electricity becomes significant. Intensive questioner survey, in-depth interview and statistical analysis are carried out to collect scientific evidences of the behavioral based changes instruments to reduce electricity consumption in household sector. The questioner was developed to include five factors assuming affect the electricity consumption pattern in household sector. They are: attitude, energy price, household income, knowledge and other determinants. The survey was carried out in Padang, West Sumatra Province Indonesia. About 210 questioner papers were proportionally distributed to households in 11 districts in Padang. Stratified sampling was used as a method to select respondents. The results show that the household size, income, payment methods and size of house are factors affecting electricity saving behavior in residential sector. Household expenses on electricity are strongly influenced by gender, type of job, level of education, size of house, income, payment method and level of installed power. These results provide a scientific evidence for stakeholders on the potential of controlling electricity consumption and designing energy policy by government in residential sector.

Keywords: electricity, energy saving, household, behavior, policy

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Motahareh Fadaei

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

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Authors: Rakan A. Ahmed, Raja S. Khan, Mohammed M. Qahtani

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This paper explores the transformative impact of laser cladding technology on the circular economy, emphasizing its role in reducing environmental impact compared to traditional welding methods. Laser cladding, an innovative manufacturing process, optimizes resource efficiency and sustainability by significantly decreasing power consumption and minimizing material waste. The study explores how laser cladding operates within the framework of the circular economy, promoting energy efficiency, waste reduction, and emissions control. Through a comparative analysis of energy and material consumption between laser cladding and conventional welding methods, the paper highlights the significant strides in environmental conservation and resource optimization made possible by laser cladding. The findings highlight the potential for this technology to revolutionize industrial practices and propel a more sustainable and eco-friendly manufacturing landscape.

Keywords: laser cladding, circular economy, carbon emission, energy

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: Caio E. G. Reis, Sara Wassell, Adriana L. Porto, Angélica A. Amato, Leslie J. C. Bluck, Teresa H. M. da Costa

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Background: Multiple epidemiologic studies have consistently reported association between increased coffee consumption and a lowered risk of Type 2 Diabetes Mellitus. However, the mechanisms behind this finding have not been fully elucidated. Objective: We investigate the effect of coffee (caffeinated and decaffeinated) on glucose effectiveness and insulin sensitivity using the stable isotope minimal model protocol with oral glucose administration in healthy men. Design: Fifteen healthy men underwent 5 arms randomized crossover single-blinding (researchers) clinical trial. They consumed decaffeinated coffee, caffeinated coffee (with and without sugar), and controls – water (with and without sugar) followed 1 hour by an oral glucose tolerance test (75 g of available carbohydrate) with intravenous labeled dosing interpreted by the two compartment minimal model (225 minutes). One-way ANOVA with Bonferroni adjustment were used to compare the effects of the tested beverages on glucose metabolism parameters. Results: Decaffeinated coffee resulted in 29% and 85% higher insulin sensitivity compared with caffeinated coffee and water, respectively, and the caffeinated coffee showed 15% and 60% higher glucose effectiveness compared with decaffeinated coffee and water, respectively. However, these differences were not significant (p > 0.10). In overall analyze (0 – 225 min) there were no significant differences on glucose effectiveness, insulin sensitivity, and glucose and insulin area under the curve between the groups. The beneficial effects of coffee did not seem to act in the short-term (hours) on glucose metabolism parameters mainly on insulin sensitivity indices. The benefits of coffee consumption occur in the long-term (years) as has been shown in the reduction of Type 2 Diabetes Mellitus risk in epidemiological studies. The clinical relevance of the present findings is that there is no need to avoid coffee as the drink choice for healthy people. Conclusions: The findings of this study demonstrate that the consumption of caffeinated and decaffeinated coffee with or without sugar has no acute effects on glucose metabolism in healthy men. Further researches, including long-term interventional studies, are needed to fully elucidate the mechanisms behind the coffee effects on reduced risk for Type 2 Diabetes Mellitus.

Keywords: coffee, diabetes mellitus type 2, glucose, insulin

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Authors: Pil Kyoo Jo, Jee Young Kim, Yu Jin Oh, Sohyun Park, Young Ha Joo, Hye Suk Kim, Semi Kang

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When convenience drives daily food choices, the increased consumption of processed foods may be associated with the increased intakes of sodium and fat and further with the onset of chronic diseases. The purpose of this study was to investigate the levels of sodium, saturated fat, and calories intakes through processed foods and the dietary patterns among adult populations in South Korea. We used the nationally representative data from the 5th Korea National Health and Nutrition Examination Survey (KNHANES, 2010-2012) and a cross-sectional survey on the eating behaviors among university students(N=893, 380 men, 513 women) aged from 20 to 24 years. Results showed that South Koreans consumed 43.5% of their total food consumption from processed foods. The 24-hour recalls data showed that 77% of sodium, 60% of fats, 59% of saturated fat, and 44% of calories were consumed from processed food. The intake of processed foods increased by 1.7% in average since 2008 annually. Only 33% of processed food that respondents consumed had nutrition labeling. The data from university students showed that students selected processed foods in convenience store when eating alone compared to eating with someone else. Given the convenience and lack of time, more people will consume processed foods and it may impact their overall dietary intake and further their health. In order to help people to make healthier food choices, regulations and policies to reduce the potentially unhealthy nutrients of processed foods should be strengthened. This research was supported by the National Research Foundation of Korea for 2011 Korea-Japan Basic Scientific Cooperation Program. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2015S1A5B6037369).

Keywords: sodium, fat, processed foods, diet trends

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Authors: M. Ghasemi, S.Fazelifar

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Abstract Aim: Over-weight is not desirable and has implications for health and in the case of athletes affects performance. Exercise is a strategy used to counteract overweight owing to create a negative energy balance by increasing energy expenditure and influencing appetite regulating hormones. Interestingly, recent studies have revealed inhibitory effects of exercise on the hunger associated with these hormones in healthy subjects Neuropeptide Y(NPY) is a 36 amino acid protein that is a powerful stimulant appetite. NPY is an important central orexigenic hormone predominantly produced by the hypothalamus, and recently found to be secreted in adipose tissue. This neurotransmitter is secreted in the brain and autonomic nervous system. On the other hand, research has shown that thyme in addition to various properties, also affects the appetite. The purpose of this study was to determine Effects of eight weeks endurance training and thyme consumption on neuropeptide Y in untrained men. Methodology: 36 Healthy untrained men (mean body weight 78.25±3.2 kg, height 176±6.8 cm, age 34.32±4.54 years and BMI 29.1±4.3 kg/m2) voluntarily participated in this study . Subjects were randomly divided into four groups: 1. control, 2. Endurance training, 3. Thyme 4. Endurance training + Thyme. Amount of 10cc Blood sampling were obtained pre-test and post-test (after 8 weeks). The taken blood samples were centrifuged at 1500 × g for 15 min then plasma was stored at -20 °C until analysis. Endurance training consisted three session per week with 60% -75% of reserve heart rate for eight weeks. Exclusion criteria were history of gastrointestinal, endocrine, cardiovascular or psychological disease, and consuming any supplementation, alcohol and tobacco products. Descriptive statistics including means, standard deviations, and ranges were calculated for all measures. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p<0/05 accepted. Results: Results showed that aerobic training significantly reduced body weight, body mass index, percent body fat, but significant increase observed in maximal oxygen consumption level (p ≤ 0/05). The neuropeptide Y levels were significantly increased after exercise. Analysis of data determined that there was no significant difference between the four groups. Conclusion: Appetite control plays a critical role in the competition between energy consumption and energy expenditure. The results of this study showed that endurance training and thyme consumption can be cause improvement in physiological parameters such as increasing aerobic capacity, reduction of fat mass and improve body composition in untrained men.

Keywords: Endurance training, neuropeptide Y, thyme, untrained men

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Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

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Authors: Soumitr Sanjay Dubey, Shubhajit Roy Chowdhury, Rahul Shrestha

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In this paper, we have presented a novel approach of calculating eigenvalues of any matrix for the first time on Field Programmable Gate Array (FPGA) using Triangular Systolic Arra (TSA) architecture. Conventionally, additional computation unit is required in the architecture which is compliant to the algorithm for determining the eigenvalues and this in return enhances the delay and power consumption. However, recently reported works are only dedicated for symmetric matrices or some specific case of matrix. This works presents an architecture to calculate eigenvalues of any matrix based on QR algorithm which is fully implementable on FPGA. For the implementation of QR algorithm we have used TSA architecture, which is further utilising CORDIC (CO-ordinate Rotation DIgital Computer) algorithm, to calculate various trigonometric and arithmetic functions involved in the procedure. The proposed architecture gives an error in the range of 10−4. Power consumption by the design is 0.598W. It can work at the frequency of 900 MHz.

Keywords: coordinate rotation digital computer, three angle complex rotation, triangular systolic array, QR algorithm

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Authors: Khalid Mahmoud Gaafar

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In human diets , ω-6 and ω-3 are important essential fatty acids for immunity and health. However, considerable alteration in dietary patterns and contents has resulted in change of the consumption of such fatty acids ,with subsequent increase in the consumption of ω-6 fatty acids and a marked decrease in the consumption of ω-3 fatty acids. This dietary alteration has led to an imbalance in the ratio for ω-6/ω-3, which at 20:1 now differs considerably from the original ratio (1:1). Therefore, dietary supplements such as eggs and meat enriched with omega 3 are necessary to increase the consumption of ω-3 to meet the recommended need for ω-3. Foods that supply ω-6 fatty acids include soybean, palm , sunflower, and rapeseed oils, whereas foods that supply ω-3 fatty acids such as linseed and fish oils. Lin seed oils contain Alpha – linolenic acid (ALA), which can be converted to DHA and EPA in the birds body, with linseed oil containing more than 50% ALA. On the other hand, high doses of omega 6 sources in the diet may have deleterious effects on humans. Maintaining an optimum ratio of ω-3 and ω-6fatty acids not only improves performance but also prevents these health risks. The ratio of n-6:ω-3 fatty acids also plays an important role in the immune response, production performance of broilers and designing meat enriched with ω-3 polyunsaturated fatty acids (PUFAs). Birds of three experimental groups fed on basal starter (0-2nd weeks), grower (3rd -4th weeks) and finisher (5th week) rations. The first is control group fed during the grower-finisher periods on basic diet with two replicate (one fed on basic diet contain vegetable oil and the other don’t) without any additives. The three experimental groups (T1 – T2 –T3) fed during the grower- finisher periods on diets free from vegetable oils and contain of 5% of extruded mixture of soybean and linseed (60%:40%). The second (T2) and third (T3) experimental groups supplemented with vitamin B12 and enzyme mixture. The first experimental groups don’t receive vitamins or enzymes. The obtained results showed a significant increased growth performance, immune response, highest antioxidant activity and serum HDL with lowest serum LDL and triglycerides levels in all experimental groups compared with control group, which was highly significant in group fed on vitamin B6.

Keywords: omega fatty acids, broiler, feeding, human health, growth performance, immunity

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Dawood Aghamohammadi, Mahmoud Eidi, Alireza Pishgahi, Azam Esmaeilnejad

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Adenosine has an analgesic and anti-inflammatory role and its injections are used for peri-operative pain management. We want to study efficacy of intrathecal injection of adenosine for post operative radicular pain after lumbar discectomy. 40 patients with unilevel lumbar discectomy who had radicular lower limb pain were treated by 1000 micrograms of intrathecal injection of adenosine. Pain severity, pain killer consumption per day and sleep quality were assessed during a 3 months follow up period. Radicular pain severity was significantly reduced in 3 month follow-up period in comparison to the baseline (F=19760, DF=2.53, p-value<0.001). Further painkiller medication consumption rate in average during 3 month follow-up period after injection was significantly lower in comparison to baseline (F= 19.244, df= 1.98, p-value<0.001). This study suggests that intrathecal injection of adenosine is a safe method in order to reduce postoperative pain after lumbar discectomy.

Keywords: adenosine, intrathecal injection, discectomy, neuropathic pain

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Akhil Dubey, Rajnesh Singh

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In modern days there occur many rapid modifications in field of ad hoc network. These modifications create many revolutionary changes in the routing. Predictive energy efficient routing is inspired on the bee’s behavior of swarm intelligence. Predictive routing improves the efficiency of routing in the energetic point of view. The main aim of this routing is the minimum energy consumption during communication and maximized intermediate node’s remaining battery power. This routing is based on food searching behavior of bees. There are two types of bees for the exploration phase the scout bees and for the evolution phase forager bees use by this routing. This routing algorithm computes the energy consumption, fitness ratio and goodness of the path. In this paper we review the literature related with predictive routing, presenting modified routing and simulation result of this algorithm comparison with artificial bee colony based routing schemes in MANET and see the results of path fitness and probability of fitness.

Keywords: mobile ad hoc network, artificial bee colony, PEEBR, modified predictive routing

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Authors: Juliane P. De Oliveira, Carlos H. Dos Santos, Marcia Shoji, Maria E. C. Ferreira, Natalia U. Yamaguchi

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The construction sector is considered a major generator of environmental impacts due to the high consumption of natural resources and waste generation. Thus, this article aims to evaluate the performance of a concrete produced by the partial and total replacement of natural coarse aggregate by recycled coarse aggregate, derived from the concrete residue of buildings and demolitions. The study was made by comparing the compressive strength and absorption of three different concrete traces, keeping the water/cement factor of 0.60 and changing only the proportions of recycled coarse aggregate between 0%, 50% and 100%. Traces 50% and 100% obtained good results by comparing the actual specific mass, because the material used is lighter to the natural coarse aggregate. It was concluded that the concrete produced with recycled aggregates, even with inferior results, can be used where it is not needed a structural function, giving an adequate destination to the construction and demolition waste and consequently reducing the extraction and consumption of natural resources.

Keywords: green concrete, recycled aggregate, recycling, sustainable development

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Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

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Authors: Vakhtang Geladze, Nana Bolashvili, Tamazi Karalashvili, Nino Machavariani, Ana Karalashvili, George Geladze, Nana Kvirkvelia

Abstract:

Fresh water deficit is one of the most important global problems today. It must be taken into consideration that in the nearest future fresh water crisis will become even more acute owing to the global climate warming and fast desertification processes in the world. Georgia is rich in water resources, but there are disbalance between the eastern and western parts of the country. The goal of the study is to integrate the recent mechanisms compatible with European standards into Georgian water resources management system on the basis of GIS. Moreover, to draw up water economy balance for the purpose of proper determination of water consumption priorities that will be an exchange ratio of water resources and water consumption of the concrete territory. For study region was choose south-eastern part of country, Kvemo kartli Region. This is typical agrarian region, tends to the desertification. The water supply of the region was assessed on the basis of water economy balance, which was first time calculated for this region.

Keywords: desertification, GIS, sustainable management, water management

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Authors: Innocent Uzougbo Onwuegbuzie

Abstract:

Wireless Sensor Networks (WSNs) are crucial for numerous applications, yet they face significant challenges due to resource constraints such as limited power and memory. Traditional routing algorithms like Dijkstra, Ad hoc On-Demand Distance Vector (AODV), and Bellman-Ford, while effective in path establishment and discovery, are not optimized for the unique demands of WSNs due to their large memory footprint and power consumption. This paper introduces the Adaptive Energy-Aware Routing (AEAR) model, a solution designed to address these limitations. AEAR integrates reactive route discovery, localized decision-making using geographic information, energy-aware metrics, and dynamic adaptation to provide a robust and efficient routing strategy. We present a detailed comparative analysis using a dataset of 50 sensor nodes, evaluating power consumption, memory footprint, and path cost across AEAR, Dijkstra, AODV, and Bellman-Ford algorithms. Our results demonstrate that AEAR significantly reduces power consumption and memory usage while optimizing path weight. This improvement is achieved through adaptive mechanisms that balance energy efficiency and link quality, ensuring prolonged network lifespan and reliable communication. The AEAR model's superior performance underlines its potential as a viable routing solution for energy-constrained WSN environments, paving the way for more sustainable and resilient sensor network deployments.

Keywords: wireless sensor networks (WSNs), adaptive energy-aware routing (AEAR), routing algorithms, energy, efficiency, network lifespan

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Authors: Mihaela Munteanu (Pila), Silvius Stanciu

Abstract:

This paper presents the aspects of the official control of fishery in the Republic of Moldova. Currently, the regulations and the activity of national institutions with responsibilities in the field of food quality are in a process of harmonization with the European rules, aiming at European integration, quality improvement and providing a higher level of food safety. The National Agency for Food Safety is the main national body with responsibilities in the field of food safety. In the field of fishery products, the Agency carries out an intensive activity of informing the citizen and controlling the products marketed. The paper presents the dangers related to the consumption of fish and fishery products traded on the national market, the sanitary-veterinary inspections conducted by the profile institution and the improper situations identified. The national market of fishery products depends largely on imports, mainly focused on ocean fish. The research carried out has shown that during the period 2011-2018, following the inspections carried out on fishery products traded on the national market, a number of inconsistencies have been identified. Thus, indigenous products were frequently detected with sensory characteristics unfit for consumption, and being commercialized in inappropriate locations or contaminated with chemical pollutants. On import products controlled, the most frequent inconsistent situations have been represented by inconsistent sensory aspects and by parasite contamination. Taking into account the specific aspects of aquatic products, including the high level of alterability, special conditions of growth, marketing, culinary preparation and consumption are necessary in order to decrease the risk of disease over the population. Certificates, attestations and other documents certifying the quality of batches, completed by additional laboratory examinations, are necessary in order to increase the level of confidence on the quality of products marketed in the Republic. The implementation of various control procedures and mechanisms at national level, correlated with the focused activity of the specialized institutions, can decrease the risk of contamination and avoid cases of disease on the population due to the consumption of fishery products.

Keywords: fishery products, food safety, quality control, Republic of Moldova

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Authors: A. E. Mukhametov, M. T. Yerbulekova, D. R. Dautkanova, G. A. Tuyakova, G. Aitkhozhayeva

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The accumulation of heavy metals in food is a constant problem in many parts of the world. Vegetable oils are widely used, both for cooking and for processing in the food industry, meeting the main dietary requirements. One of the main chemical pollutants, heavy metals, is usually found in vegetable oils. These chemical pollutants are carcinogenic, teratogenic and immunotoxic, harmful to consumption and have a negative effect on human health even in trace amounts. Residues of these substances can easily accumulate in vegetable oil during cultivation, processing and storage. In this article, the content of the concentration of heavy metal ions in vegetable oils of Kazakhstan production is studied: sunflower, rapeseed, safflower and linseed oil. Heavy metals: arsenic, cadmium, lead and nickel, were determined in three repetitions by the method of flame atomic absorption. Analysis of vegetable oil samples revealed that the largest lead contamination (Pb) was determined to be 0.065 mg/kg in linseed oil. The content of cadmium (Cd) in the largest amount of 0.009 mg/kg was found in safflower oil. Arsenic (As) content was determined in rapeseed and safflower oils at 0.003 mg/kg, and arsenic (As) was not detected in linseed and sunflower oil. The nickel (Ni) content in the largest amount of 0.433 mg/kg was in linseed oil. The heavy metal contents in the test samples complied with the requirements of regulatory documents for vegetable oils. An assessment of the health risk of vegetable oils with a daily consumption of 36 g per day shows that all samples of vegetable oils produced in Kazakhstan are safe for consumption. But further monitoring is needed, since all these metals are toxic and their harmful effects become apparent only after several years of exposure.

Keywords: vegetable oil, sunflower oil, linseed oil, safflower oil, toxic metals, food safety, rape oil

Procedia PDF Downloads 133

Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

Procedia PDF Downloads 152

Authors: Shahid Mahmood, Ghulam Mueen-Ud-Din, Farah Naz Akbar, Yousaf Quddoos, Syeda Mahvish Zahra, Wajiha Saeed, Tayyaba Sami Ullah

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Obesity is an epidemic across the globe that affects all the segments of the population. Physical inactivity, passionate consumption of junk food, inadequate water intake and an unhealthy lifestyle are evident among university girls that are ruining their health gravely especially fat accumulation. The study was carried out to investigate the potential etiological factors of obesity development in university girls. The cross sectional study was carried out after approval of the Departmental Review Committee for Ethics (DRCE) as the par Declaration of Helsinki at Institute of Food Science and Nutrition (IFSN), University of Sargodha, Sargodha-Pakistan and Department of Food Science and Home Economics, G. C. Women University, Faisalabad-Pakistan. 400 girls were selected randomly from different departments of both universities. Nutritional status of the volunteers was assessed through approved protocols for demographics, anthropometrics, body composition, energetics, vital signs, clinical signs and symptoms, medical/family history, and dietary intake assessment (FFQ), water intake and physical activity level. The obesity was determined on body fat (%). Alarming and unheeded etiological factors for the development of obesity in girls were explored by the study. About 93 % girls had a sedentary level of physical activity, zealous consumption of junk food (5.31±1.23 servings), drank little water (1.09±0.26 L/day) that consequent high heaps of fat (35.06±3.02 %), measly body water (52.38±3.4 %), poor bone mass (05.14±0.31 Kg), and high BMI (26.68±1.14 Kg/m²) in 34% girls. The malnutrition also depicted by poor vital signs i.e. low body temperature (97.11±0.93 °F), slightly higher blood pressure (124.19±4.08 / 85.25±2.97 mmHg), rapid pulse rate (99.2 ± 6.85 beats/min), reduced blood O₂ saturation (96.53±0.96 %), scanty peak expiratory flow rate (297 ± 15.7 L /min). The outcomes of the research articulated that physical inactivity; extreme intakes of junk food, insufficient water consumption are etiological factors for obesity development among girls which are usually overlooked in Pakistan.

Keywords: informed consent, junk food, obesity, physical inactivity

Procedia PDF Downloads 189