Search results for: total load approach

Authors: Tanmaya Pradhan, K. Midhun, M. Joy Thomas

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Increasing the shelf life and improving the quality are important objectives for the success of packaged liquid food industry. One of the methods by which this can be achieved is by deactivating the micro-organisms present in the liquid food through pasteurization. Pasteurization is done by heating, but some serious disadvantages such as the reduction in food quality, flavour, taste, colour, etc. were observed because of heat treatment, which leads to the development of newer methods instead of pasteurization such as treatment using UV radiation, high pressure, nuclear irradiation, pulsed electric field, etc. In recent years the use of the pulsed electric field (PEF) for inactivation of the microbial content in the food is gaining popularity. PEF uses a very high electric field for a short time for the inactivation of microorganisms, for which we require a high voltage pulsed power source. Pulsed power sources used for PEF treatments are usually in the range of 5kV to 50kV. Different pulse shapes are used, such as exponentially decaying and square wave pulses. Exponentially decaying pulses are generated by high power switches with only turn-on capacity and, therefore, discharge the total energy stored in the capacitor bank. These pulses have a sudden onset and, therefore, a high rate of rising but have a very slow decay, which yields extra heat, which is ineffective in microbial inactivation. Square pulses can be produced by an incomplete discharge of a capacitor with the help of a switch having both on/off control or by using a pulse forming network. In this work, a pulsed power-based system is designed with the help of high voltage capacitors and solid-state switches (IGBT) for the inactivation of pathogenic micro-organism in liquid food such as fruit juices. The high voltage generator is based on the Marx generator topology, which can produce variable amplitude, frequency, and pulse width according to the requirements. Liquid food is treated in a chamber where pulsed electric field is produced between stainless steel electrodes using the pulsed output voltage of the supply. Preliminary bacterial inactivation tests were performed by subjecting orange juice inoculated with Escherichia Coli bacteria. With the help of the developed pulsed power source and the chamber, the inoculated orange has been PEF treated. The voltage was varied to get a peak electric field up to 15kV/cm. For a total treatment time of 200µs, a 30% reduction in the bacterial count has been observed. The detailed results and analysis will be presented in the final paper.

Keywords: Escherichia coli bacteria, high voltage generator, microbial inactivation, pulsed electric field, pulsed forming line, solid-state switch

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Authors: Rachid Dris, Robin Treilles, Max Beaurepaire, Minh Trang Nguyen, Sam Azimi, Vincent Rocher, Johnny Gasperi, Bruno Tassin

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Microplastic sources and fluxes in urban catchments are only poorly studied. Most often, the approaches taken focus on a single source and only carry out a description of the contamination levels and type (shape, size, polymers). In order to gain an improved knowledge of microplastic inputs at urban scales, estimating and comparing various fluxes is necessary. The Laboratoire Eau, Environnement et Systèmes Urbains (LEESU), the Laboratoire Eau Environnement (LEE) and the SIAAP (Service public de l’assainissement francilien) initiated several projects to investigate different urban sources and flows of microplastics. A systemic approach is undertaken at the scale of Paris Megacity, and several compartments are considered, including atmospheric fallout, wastewater treatments plants, runoff and combined sewer overflows. These investigations are carried out within the Limnoplast and OPUR projects. Atmospheric fallout was sampled during consecutive periods ranging from 2 to 3 weeks with a stainless-steel funnel. Both wet and dry periods were considered. Different treatment steps were sampled in 2 wastewater treatment plants (Seine-Amont for activated sludge and Seine-Centre for biofiltration) of the SIAAP, including sludge samples. Microplastics were also investigated in combined sewer overflows as well as in stormwater at the outlet suburban catchment (Sucy-en-Brie, France) during four rain events. Samples are treated using hydroperoxide digestion (H₂O₂ 30 %) in order to reduce organic material. Microplastics are then extracted from the samples with a density separation step using NaI (d=1.6 g.cm⁻³). Samples are filtered on metallic filters with a porosity of 14 µm between steps to separate them from the solutions (H₂O₂ and NaI). The last filtration was carried out on alumina filters. Infrared mapping analysis (using a micro-FTIR with an MCT detector) is performed on each alumina filter. The resulting maps are analyzed using a microplastic analysis software simple, developed by Aalborg University, Denmark and Alfred Wegener Institute, Germany. Blanks were systematically carried out to consider sample contamination. This presentation aims at synthesizing the data found in the various projects. In order to carry out a systemic approach and compare the various inputs, all the data were converted into annual microplastic fluxes (number of microplastics per year), and extrapolated to the Parisian agglomeration. PP, PE and alkyd are the most prevalent polymers found in storm water samples. Rain intensity and microplastic concentrations did not show any clear correlation. Considering the runoff volumes and the impervious surface area of the studied catchment, a flux of 4*107–9*107 MPs.yr⁻¹.ha⁻¹ was estimated. Samples of wastewater treatment plants and atmospheric fallout are currently being analyzed in order to finalize this assessment. The representativeness of such samplings and uncertainties related to the extrapolations will be discussed and gaps in knowledge will be identified. The data provided by such an approach will help to prioritize future research as well as policy efforts.

Keywords: microplastics, atmosphere, wastewater, urban runoff, Paris megacity, urban waters

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Authors: Vojo George Fasinu, Nadaraj Govender, Predeep Kumar

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An Antenna, which remains the hub of technological development in Africa had been found to be a course that is been taught and designed in an abstract manner in some universities. One of the reasons attached to this is that the appropriate approach of teaching antenna design is not yet understood by many engineering academics in some universities in South Africa. Also, another problem reported is the main difficulty encountered when interpreting and applying some of the mathematical concepts learned into their practical antenna design course. As a result of this, some engineering experts classified antenna as a mysterious technology that could not be described by anybody using mathematical concepts. In view of this, this paper takes it as its point of departure in explaining what an antenna is all about with a strong emphasis on its mathematical modelling. It also argues that the place of modelling mathematical concepts into the teaching of engineering design cannot be overemphasized. Therefore, it explains the mathematical concepts adopted during the teaching of an antenna design course, the Strategies of modelling those mathematics concepts, the behavior of antennas, and their mathematics usage were equally discussed. More so, the paper also sheds more light on mathematical modelling in South Africa context, and also comparative analysis of mathematics concepts taught in mathematics class and mathematics concepts taught in engineering courses. This paper focuses on engineering academics teaching selected topics in electronic engineering (Antenna design), with special attention on the mathematical concepts they teach and how they teach them when teaching the course. A qualitative approach was adopted as a means of collecting data in order to report the naturalistic views of the engineering academics teaching Antenna design. The findings of the study confirmed that some mathematical concepts are being modeled into the teaching of an antenna design with the adoption of some teaching approaches. Furthermore, the paper reports a didactical-realistic mathematical model as a conceptual framework used by the researchers in describing how academics teach mathematical concepts during their teaching of antenna design. Finally, the paper concludes with the importance of mathematical modelling to the engineering academics and recommendations for further researchers.

Keywords: modelling, mathematical concepts, engineering, didactical, realistic model

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Authors: Amin Mojiri, Akiyoshi Ohashi, Tomonori Kindaichi

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Synthetic domestic wastewater was treated via combining treatment methods, including electrochemical oxidation, adsorption, and sequencing batch reactor (SBR). In the upper part of the reactor, an anode and a cathode (Ti/RuO₂-IrO₂) were organized in parallel for the electrochemical oxidation procedure. Sodium sulfate (Na₂SO₄) with a concentration of 2.5 g/L was applied as the electrolyte. The voltage and current were fixed on 7.50 V and 0.40 A, respectively. Then, 15% working value of the reactor was filled by activated sludge, and 85% working value of the reactor was added with synthetic wastewater. Powdered cockleshell, 1.5 g/L, was added in the reactor to do ion-exchange. Response surface methodology was employed for statistical analysis. Reaction time (h) and pH were considered as independent factors. A total of 97.0% biochemical oxygen demand, 99.9% phosphorous and 88.6% cadmium were eliminated at the optimum reaction time (80.0 min) and pH (6.4).

Keywords: adsorption, electrochemical oxidation, metals, SBR

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Authors: Duchduen Bhanthumnavin

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One of the most important characteristics to increase competitive ability in undergraduate students after post COVID-19 era is goal setting and self-control. This correlational study aimes at investigating the influence of psycho-social antecedents on goal setting and self-control in 550 Thai university students. Results from multiple regression analysis revealed that the important predictors of this characteristic were reasoning ability, psychological immunity, attitudes toward competition, core self-evaluation, and family nurture, which yielded 54.28 predictive percentage in the total sample. Moreover, the analysis identified three at-risk groups, namely, male students, low GPA students, and students with siblings. Discussion and implications in general and for specific purposes for the at-risk groups were offered.

Keywords: antecedents, plan and self-control, predictors, university students

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Authors: Madelyn N. Moawad, Hermine R. Z. Tadros, Mary G. Ghobrial, Ahmad R. Bassiouny, Kamal M. Kandeel, Athar Ata

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Seaweeds are potential renewable resources in marine environment. They provide an excellent source of bioactive substances such as dietary fibers and various functional polysaccharides that could potentially be used as ingredients for both human and animal health applications. The observations suggested that these bioactive compounds have strong antioxidant properties, which have beneficial effects on human health. The present research aimed at finding new chemical products from local marine macroalgae for natural medicinal uses and consumption for their nutritional values. Macroalgae samples were collected manually mainly from the Mediterranean Sea at shallow subtidal zone of Abu Qir Bay, Alexandria, Egypt. The chemical compositions of lyophilized materials of six selected macroalgal species; Colpomenia sinuosa, Sargassum linifolium, Padina pavonia, Pterocladiella capillacea, Laurencia pinnatifidia, and Caulerpa racemosa, were investigated for proteins using bovine serum albumin, and carbohydrates were assayed by phenol-sulfuric acid reaction. The macroalgae lipid was extracted with chloroform, methanol and phosphate buffer. Vitamins were extracted using trichloroacetic acid. Chlorophylls and total carotenoids were determined spectrophotometrically and total phenols were extracted with methanol. In addition, lipid-soluble, and water-soluble antioxidant, and anti α-glucosidase activities were measured spectrophotometrically. The antioxidant activity of hexane extracts was investigated using phosphomolybdenum reagent. The anti-α-glucosidase effect measurement was initiated by mixing α-glucosidase solution with p-nitrophenyl α-D-glucopyranoside. The results showed that the ash contents varied from 11.2 to 35.4 % on dry weight basis for P. capillacea and Laurencia pinnatifidia, respectively. The protein contents ranged from 5.63 % in brown macroalgae C. sinuosa to 8.73 % in P. pavonia. A relative wide range in carbohydrate contents was observed (20.06–46.75 %) for the test algal species. The highest lipid percentage was found in green alga C. racemosa (5.91%) followed by brown algae P. pavonia (3.57%) and C. sinuosa (2.64%). The phenolic contents varied from 1.32 mg GAE/g for C. sinuosa to 4.00 mg GAE/g in P. pavonia. The lipid-soluble compounds exhibited higher antioxidant capacity (73.18-145.95 µM/g) than that of the water-soluble ones ranging from 24.83 µM/g in C. racemosa to 74.07 µM/g in S. linifolium. The most potent anti-α-glucosidase activity was observed for P. pavonia with IC50 of 17.12 μg/ml followed by S. linifolium (IC50 = 71.75 μg/ml), C. racemosa (IC50 = 84.73 μg/ml), P. capillacea (IC50 = 92.16 μg/ml), C. sinuosa (IC50 = 112.44 μg/ml), and L. pinnatifida (IC50 = 115.11 μg/ml).

Keywords: α-glucosidase, lyophilized, macroalgae, spectrophotometrically

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Authors: Adjmal Ghaur, Christoph Peschel, Iris Dienwiebel, Lukas Haneke, Leilei Du , Laurin Profanter, Tobias Placke, Martin Winter

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In recent years, lithium-ion batteries (LIBs)are widely used in electric vehicles (EVs) and mobile energy storage devices (ESDs), which has led to higher requirements for energy density. To fulfill these requirements, tremendous attention has been paid to design advanced LIBs with various siliconactive materials as alternative negative electrodes to replace graphite (372 mAh g⁻¹)due to their high theoretical gravimetric capacity (4200mAh g⁻¹). However, silicon as potential anode material suffers from huge volume changes during charging and discharging and has poor electronicconductivity which negatively impacts the long-term performance and preventshigh silicon contents from practical application. Additionally, an unstable crystalline silicon structure tends to pulverization during the (de)lithiation process. To compensate for the volume changes, alleviate pulverization, and maintain high electronicconductivity, silicon-doped graphite composites with protecting coating layers are a promising approach. In this context, phosphazene compounds are investigated concerning their silicon protecting properties in silicon-doped graphite composites. In detail, electrochemical performance measurements in pouch full-cells(NCM523||SiOx/C), supressing gas formation properties, and post-mortem analyzes were carried out to characterize phosphazene compounds as additive materials. The introduction of the dual-additive approach in state-of-the-art electrolytes leads to synergistic effects between FEC and phosphazene compounds which accelerate the durability of silicon particles and results in enhanced electrochemical performance.

Keywords: silicon, phosphazene, solid electrolyte interphase, electrolyte, gasmeasurements

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Authors: Sarah-Anne Schumann, Chintan Shah, Sandeep Ponniah, Syeachia Dennis

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Effective interventions to prevent childhood obesity include limiting sugar-sweetened beverage intake (SOR: B, longitudinal study), school and home based strategies to reduce total screen time and increase physical activity, behavioral and dietary counseling, and support for parents and families (SOR: A, meta-analysis of randomized and non-randomized controlled trials). Risk factors for childhood obesity include maternal pre-pregnancy weight, high infant birth weight, early infant rapid weight gain and maternal smoking during pregnancy which may provide opportunities to intervene and prevent childhood obesity (SOR: B, meta-analysis of observational studies).

Keywords: childhood, obesity, prevent obesity, interventions to prevent obesity

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Authors: Leora Branfield Day, Stephanie Saunders, Leah Steinberg, Shiphra Ginsburg, Christine Soong

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Introduction: Discordance between patients expressed and documented preferences at the end of life is common. Although junior trainees frequently lead goals of care (GOC) conversations, lack of training can result in poor communication. Based on a needs assessment, we developed an interactive electronic learning module (eModule) for conducting patient-centred GOC discussions. The purpose of this study was to evaluate the impact of the eModule on residents’ attitudes towards GOC conversations. Methods: First-year internal medicine residents (n=11) from the University of Toronto selected using purposive sampling underwent semi-structured interviews before and after completing a GOC eModule. Interviews were anonymized, transcribed and open-coded using NVivo. Using a constructivist grounded theory approach, we developed a framework to understand the attitudes of residents to GOC conversations before and after viewing the module. Results: Before the module, participants described limited training and negative emotions towards GOC conversations. Many focused on code status and procedure choices (e.g., ventilation) instead of eliciting patient-centered values. Pressure to “get the DNR" led to conflicting feelings and distress. After the module, participants’ approached conversations with a greater focus on patient values and process. They felt more prepared and comfortable, recognizing the complexity of conversations and the importance of patient-centeredness. Conclusions: A novel GOC eModule allowed residents to develop a patient-centered and standardized approach to GOC conversations while improving confidence and preparedness. This resource could be an effective strategy toward attaining a critical communication competency among learners with the potential to enhance accurate GOC documentation.

Keywords: goals of care conversations, communication skills, emodule, medical education

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Omolara Lade, David Oloke

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The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). However, in Nigeria, implementation of sustainable water management, such as RWH systems, is inefficient and social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of reinforced concrete cement (RCC) storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use decision support tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of household respondents, Nigerian Architects and Civil Engineers and focus group discussion with stakeholders. 18 selection attributes have been defined and three alternatives have been identified in this research. The questionnaires were analysed using SPSS, excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were modelled using RainCycle software. From the results, the MDA model chose RCC tank as the most appropriate storage system for RWH.

Keywords: rainwater harvesting, modelling, hydraulic assessment, whole life cost, decision support system

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Authors: Farha Ibrahim, Ely Zarina Samsudin, Ahmad Razali Ishak, Jeyanthini Sathasivam

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Introduction: Indoor air quality (IAQ) has recently gained substantial traction as the airborne transmission of infectious respiratory disease has become an increasing public health concern. Public hospital outpatient department (OPD). IAQ warrants special consideration as it is the most visited department in which patients and staff are all directly impacted by poor IAQ. However, there is limited evidence on IAQ in these settings. Moreover, occupants’ behavior like occupant’s movement and operation of door, windows and appliances, have been shown to significantly affect IAQ, yet the influence of these determinants on IAQ in such settings have not been established. Objectives: This study aims to examine IAQ in Malaysian public hospitals OPD and assess its relationships with occupants’ behavior. Methodology: A multicenter cross-sectional study in which stratified random sampling of Johor public hospitals OPD (n=6) according to building age was conducted. IAQ measurements include indoor air temperature, relative humidity (RH), air velocity (AV), carbon dioxide (CO2), total bacterial count (TBC) and total fungal count (TFC). Occupants’ behaviors in Malaysian public hospital OPD are assessed using observation forms, and results were analyzed. Descriptive statistics were performed to characterize all study variables, whereas non-parametric Spearman Rank correlation analysis was used to assess the correlation between IAQ and occupants’ behavior. Results: After adjusting for potential cofounder, the study has suggested that occupants’ movement in new building, like seated quietly, is significantly correlated with AV in new building (r 0.642, p-value 0.010), CO2 in new (r 0.772, p-value <0.001) and old building (r -0.559, p-value 0.020), TBC in new (r 0.747, p-value 0.001) and old building (r -0.559, p-value 0.020), and TFC in new (r 0.777, p-value <0.001) and old building (r -0.485, p-value 0.049). In addition, standing relaxed movement is correlated with indoor air temperature (r 0.823, p-value <0.001) in new building, CO2 (r 0.559, p-value 0.020), TBC (r 0.559, p-value 0.020), and TFC (r -0.485, p-value 0.049) in old building, while walking is correlated with AV in new building (r -0.642, p-value 0.001), CO2 in new (r -0.772, p-value <0.001) and old building (r 0.559, p-value 0.020), TBC in new (r -0.747, p-value 0.001) and old building (r 0.559, p-value 0.020), and TFC in old building (r -0.485, p-value 0.049). The indoor air temperature is significantly correlated with number of doors kept opened (r 0.522, p-value 0.046), frequency of door adjustments (r 0.753, p-value 0.001), number of windows kept opened (r 0.522, p-value 0.046), number of air-conditioned (AC) switched on (r 0.698, p-value 0.004) and frequency of AC adjustment (r 0.753, p-value 0.001) in new hospital OPD building. AV is found to be significantly correlated with number of doors kept opened (r 0.642, p-value 0.01), frequency of door adjustments (r 0.553, p-value 0.032), number of windows kept opened (r 0.642, p-value 0.01), and frequency of AC adjustment, number of fans switched on, and frequency of fans adjustment(all with r 0.553, p-value 0.032) in new building. In old hospital OPD building, the number of doors kept opened is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), frequency of door adjustment is significantly correlated with CO₂, TBC (both r-0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of windows kept opened is significantly correlated with CO₂, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), frequency of window adjustment is significantly correlated with CO₂,TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of AC switched on is significantly correlated with CO₂, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049),, frequency of AC adjustment is significantly correlated with CO2 (r 0.559, p-value 0.020), TBC (0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049), number of fans switched on is significantly correlated with CO2, TBC (both r 0.559, p-value 0.020) and TFC (r 0.495, p-value 0.049), and frequency of fans adjustment is significantly correlated with CO2, TBC (both r -0.559, p-value 0.020) and TFC (r -0.495, p-value 0.049). Conclusion: This study provided evidence on IAQ parameters in Malaysian public hospitals OPD and significant factors that may be effective targets of prospective intervention, thus enabling stakeholders to develop appropriate policies and programs to mitigate IAQ issues in Malaysian public hospitals OPD.

Keywords: outpatient department, iaq, occupants practice, public hospital

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Authors: Mohsen Ehsanpour, Maryam Ehsanpour, ‎Majid Afkhami, Fatemeh Afkhami ‎

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Heavy metals are increasingly being released into natural waters from geological and anthropogenic sources. The distribution of several heavy metals (Cd, Pb) was investigated in muscle, liver in six different fish species seasonally collected in Persian Gulf (autumn 2009-summer 2010). The concentrations of all metals were lower in flesh than those recorded in liver due to their physiological roles. The THQ index for fish was calculated. Estimation of target hazard quotients calculations for the contaminated fish consumption was calculated to evaluate the effect of pollution on health. Total metal THQs values (Pb and Cd) for adults were 0.05 and 0.04 in Bushehr and Bandar-Genaveh, respectively, and for children they were 0.08 and 0.05 in Bandar-Abbas and Bandar-Lengeh, respectively.

Keywords: Persian Gulf, heavy metals, health risks, THQ index

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Authors: Rouhollah Torabi, Ashkan Chavoshi, Sheyda Almasi, Shima Almasi

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In this paper the effect of impeller trim on centrifugal pump performance is studied and the most important effect which is decreasing the flow rate, differential head and efficiency is analyzed. For this case a low specific speed centrifugal pump is simulated with CFD. Total flow inside the pump including the secondary flow in sidewall gap which form internal leakage is modeled simultaneously in CFX software. The flow field in different area of pumps such as inside impeller, volute, balance holes and leakage through wear rings are studied. To validate the results experimental tests are done for various impeller diameters. Results also compared with analytic equations which predict pump performance with trimmed impeller.

Keywords: centrifugal pump, CFD, impeller, trim

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Authors: A. Bentabet, A. Aydin, N. Fenineche

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In this work, we try to determine the best analytical approximation of differential cross sections, used generally in Monte Carlo simulation, to study the electron/positron slowing down in solid targets in the energy range up to 10 keV. Actually, our comparative study was carried out on the angular distribution of the scattering angle, the elastic total and the first transport cross sections which are the essential quantities used generally in the electron/positron transport study by using both stochastic and deterministic methods. Indeed, the obtained results using the relativistic partial wave expansion method and the backscattering coefficient experimental data are used as criteria to evaluate the used model.

Keywords: differential cross-section, backscattering coefficient, Rutherford cross-section, Vicanek and Urbassek theory

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: Margaret K. Spoo-Chupka

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The Metropolitan Water District of Southern California (MWDSC) manages surface water reservoirs that are a source of drinking water for more than 19 million people in Southern California. These reservoirs experience periodic planktonic cyanobacteria blooms that can impact water quality. MWDSC imports water from two sources – the Colorado River (CR) and the State Water Project (SWP). The SWP brings supplies from the Sacramento-San Joaquin Delta that are characterized as having higher nutrients than CR water. Above average precipitation in 2017 after five years of drought allowed the majority of the reservoirs to fill. Phytoplankton was analyzed during the drought and after the drought at three reservoirs: Diamond Valley Lake (DVL), which receives SWP water exclusively, Lake Skinner, which can receive a blend of SWP and CR water, and Lake Mathews, which generally receives only CR water. DVL experienced a significant increase in water elevation in 2017 due to large SWP inflows, and there were no significant changes to total phytoplankton biomass, Shannon-Wiener diversity of the phytoplankton, or cyanobacteria biomass in 2017 compared to previous drought years despite the higher nutrient loads. The biomass of cyanobacteria that could potentially impact DVL water quality (Microcystis spp., Aphanizomenon flos-aquae, Dolichospermum spp., and Limnoraphis birgei) did not differ significantly between the heavy precipitation year and drought years. Compared to the other reservoirs, DVL generally has the highest concentration of cyanobacteria due to the water supply having greater nutrients. Lake Mathews’ water levels were similar in drought and wet years due to a reliable supply of CR water and there were no significant changes in the total phytoplankton biomass, phytoplankton diversity, or cyanobacteria biomass in 2017 compared to previous drought years. The biomass of cyanobacteria that could potentially impact water quality at Lake Mathews (L. birgei and Microcystis spp.) did not differ significantly between 2017 and previous drought years. Lake Mathews generally had the lowest cyanobacteria biomass due to the water supply having lower nutrients. The CR supplied most of the water to Lake Skinner during drought years, while the SWP was the primary source during 2017. This change in water source resulted in a significant increase in phytoplankton biomass in 2017, no significant change in diversity, and a significant increase in cyanobacteria biomass. Cyanobacteria that could potentially impact water quality at Skinner included: Microcystis spp., Dolichospermum spp., and A.flos-aquae. There was no significant difference in Microcystis spp. biomass in 2017 compared to previous drought years, but biomass of Dolichospermum spp. and A.flos-aquae were significantly greater in 2017 compared to previous drought years. Dolichospermum sp. and A. flos-aquae are two cyanobacteria that are more sensitive to nutrients than Microcystis spp., which are more sensitive to temperature. Patterns in problem cyanobacteria abundance among Southern California reservoirs as a result of above-average precipitation after more than five years of drought were most closely related to nutrient loading.

Keywords: drought, reservoirs, cyanobacteria, and phytoplankton ecology

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Authors: Redie Kidane Ghebrehawariat, Betiel Habte Hadgu, Filmon Berhane Kahsay, Rim Berhane Fisehaye, Samuel Haile Kahsay, Saron Yemane Yosief, Selemawit Mosazghi Gilazghi

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A cross-sectional study was conducted from 22 February to 9 April 2022 on small, medium, and large holder dairy farms to determine the bovine mastitis prevalence and associated risk factors in the Anseba region, Eritrea. A total of 34 dairy farms and 193 dairy cows were randomly selected. Dairy cows were physically examined for any change on the udder and milk; a California mastitis test was performed to check sub-clinical mastitis; a closed-ended semi-structured questionnaire composed of 28 variables/risk factors (21 management risk factors and 7 animal-level risk factors) was used to determine the risk factors responsible for clinical and sub-clinical mastitis in the dairy cows. The overall cow-level prevalence of mastitis was 147 (76.2%). The animal level prevalence rate of clinical and sub-clinical mastitis was found to be 22 (11.4%) and 125 (64.8%), respectively, while herd level prevalence both for clinical and subclinical mastitis was found to be 14 (41.2%) and 26 (76.5%) respectively. Based on the already set P-value, which is <0.05, a number of risk factors were found to have a significant relationship with the occurrence of clinical and sub-clinical mastitis. Generally, animal risk factors such as animal age, parity, injury on the udder or teat, and previous history of mastitis presence of injury on the udder and lactation stage were risk factors with a significant relationship with the occurrence of clinical and sub-clinical mastitis. On the other hand, management risk factors with a significant relationship to the occurrence of clinical and sub-clinical mastitis were herd size, failure to milk mastitic cow, at last, educational level, floor type, failure to use a towel, using one towel for more than one cow and failure to practice mastitis test. From a total of 772 quarters, 280 (36.3%) were found positive for sub-clinical mastitis using the California mastitis test; of these, 70 (9%) were weakly positive, 90 (11.7%) were distinct positive, and 120 (15.5%) were strongly positive. Furthermore, 13 (1.7%) quarters were blocked. Quarter level prevalence was right front 80 (41.5%), left front 64 (33.3%), right hind 69 (35.8%) and left hind 67 (34.7%). The study has shown that mastitis is a major problem for dairy farms and the findings suggested that mastitis is one of the limiting factors in increasing milk production. Subclinical mastitis was found to be a devastating problem, and it occurred in all three breeds of lactating dairy cattle. Therefore, farmers should work hard to avoid the above-mentioned risk factors to minimize the infection of their dairy cattle by mastitis and thereby increase their profit. On the other hand, the Ministry of Agriculture, through the extension unit, should work in close contact with the farmers to increase awareness of the economic importance of the disease and associated risk factors.

Keywords: mastitis, prevalence, dairy cattle, Anseba, Eritrea

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Authors: Sami M. Alshareef

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The rapid growth of smart grid technology has brought significant advancements to the power industry. However, with the increasing interconnectivity and reliance on information and communication technologies, smart grids have become vulnerable to cyber-attacks, posing significant threats to the reliable operation of power systems. Among the critical components of smart grids, the Automatic Generation Control (AGC) system plays a vital role in maintaining the balance between generation and load demand. Therefore, protecting the AGC system from cyber threats is of paramount importance to maintain grid stability and prevent disruptions. Traditional security measures often fall short in addressing sophisticated and evolving cyber threats, necessitating the exploration of innovative approaches. Machine learning, with its ability to analyze vast amounts of data and learn patterns, has emerged as a promising solution to enhance AGC system security. Therefore, this research proposal aims to address the challenges associated with detecting and mitigating cyber-attacks on AGC in smart grids by leveraging machine learning techniques on automatic generation control of two-area power systems. By utilizing historical data, the proposed system will learn the normal behavior patterns of AGC and identify deviations caused by cyber-attacks. Once an attack is detected, appropriate mitigation strategies will be employed to safeguard the AGC system. The outcomes of this research will provide power system operators and administrators with valuable insights into the vulnerabilities of AGC systems in smart grids and offer practical solutions to enhance their cyber resilience.

Keywords: machine learning, cyber-attacks, automatic generation control, smart grid

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Authors: Rida Wanbha Nongbri, Sabuj Kumar Mandal

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The Sustainable Development Goals (SDGs) for 2016-2030 were adopted in response to Millennium Development Goals (MDGs) which focused on access to sustainable water and sanitations. For over a decade, water has been a significant subject that is explored in various facets of life. Our day-to-day life is significantly impacted by water poverty at the socio-economic level. Reducing water poverty is an important policy challenge, particularly in emerging economies like India, owing to its population growth, huge variation in topology and climatic factors. To design appropriate water policies and its effectiveness, a proper measurement of water poverty is essential. In this backdrop, this study uses the Alkire Foster (AF) methodology to estimate a multidimensional water poverty index for India at the household level. The methodology captures several attributes to understand the complex issues related to households’ water deprivation. The study employs two rounds of Indian Human Development Survey data (IHDS 2005 and 2012) which focuses on 4 dimensions of water poverty including water access, water quantity, water quality, and water capacity, and seven indicators capturing these four dimensions. In order to quantify water deprivation at the household level, an AF dual cut-off counting method is applied and Multidimensional Water Poverty Index (MWPI) is calculated as the product of Headcount Ratio (Incidence) and average share of weighted dimension (Intensity). The results identify deprivation across all dimensions at the country level and show that a large proportion of household in India is deprived of quality water and suffers from water access in both 2005 and 2012 survey rounds. The comparison between the rural and urban households shows that higher ratio of the rural households are multidimensionally water poor as compared to their urban counterparts. Among the four dimensions of water poverty, water quality is found to be the most significant one for both rural and urban households. In 2005 round, almost 99.3% of households are water poor for at least one of the four dimensions, and among the water poor households, the intensity of water poverty is 54.7%. These values do not change significantly in 2012 round, but we could observe significance differences across the dimensions. States like Bihar, Tamil Nadu, and Andhra Pradesh are ranked the most in terms of MWPI, whereas Sikkim, Arunachal Pradesh and Chandigarh are ranked the lowest in 2005 round. Similarly, in 2012 round, Bihar, Uttar Pradesh and Orissa rank the highest in terms of MWPI, whereas Goa, Nagaland and Arunachal Pradesh rank the lowest. The policy implications of this study can be multifaceted. It can urge the policy makers to focus either on the impoverished households with lower intensity levels of water poverty to minimize total number of water poor households or can focus on those household with high intensity of water poverty to achieve an overall reduction in MWPI.

Keywords: .alkire-foster (AF) methodology, deprivation, dual cut-off, multidimensional water poverty index (MWPI)

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Authors: Arun Kumar

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For the present study a total of 219 women, from urban and rural areas of Sagar district of central India were selected. The mean age at menarche of rural women was found 13.89±1.17 years and for urban women, it was 13.78±1.12 years. The difference between the mean age at menarche of urban and rural women was statistically insignificant (t=0.580, p≤0.05). Mean age at menopause among rural women was (47.4±4.92). The difference between the mean of urban and rural women was statistically insignificant (t=0.739 and p≤0.05). These findings indicate that rural women experience menopause at a later age as compared to their urban counterparts.

Keywords: menarche, menopause, urban, rural, Bidi workers

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Authors: I. P. Singh, Ajesh Kumar Kapoor

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Rapid globalization have led to a change towards massive uncontrolled urbanization. Whereas during initial years negligence was there in the name of development, growth and vision toward healthier and better tomorrow. Considering the scenario of developing nations (India) where 70% of their population is living on 30% (urban areas) of their total land available. The need of an hour is to consider the ethical values of each and every person living in urban fringes, whereby the sustainable urban development is promoted which encompasses the move toward low carbon developments. It would help reviving a city lung space and reducing carbon credits as per Kyoto Protocol 1991. This paper would provide an overview about Indian scenario of current urban areas, ongoing developments, series of regulatory policy measures, materials innovative use and policies framed and opted for low carbon development.

Keywords: urban sustainability, indicators for sustainable development, low carbon development, Indian Policies toward low carbon development

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Authors: Hyppolite Aignon, Souleymane Yorou, Martin Ryberg, Anneli Svanholm

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Climate change and human actions cause the extinction of wild mushrooms. In Benin, the diversity of fungi is large and may still contain species new to science but the inventory effort remains low and focuses on particularly edible species (Russula, Lactarius, Lactifluus, and also Amanita). In addition, inventories have started recently and some groups of fungi are not sufficiently sampled, however, the degradation of fungal habitat continues to increase and some species are already disappearing. (Yorou and De Kesel, 2011), however, the degradation of fungi habitat continues to increase and some species may disappear without being known. This genus (Inocybe) overlooked has a worldwide distribution and includes more than 700 species with many undiscovered or poorly known species worldwide and particularly in tropical Africa. It is therefore important to orient the inventory to other genera or important families such as Inocybe (Fungi, Agaricales) in order to highlight their diversity and also to know their phylogenetic positions with a combined approach of gene regions. This study aims to evaluate the species richness and phylogenetic position of Inocybe species and affiliated taxa in West Africa. Thus, in North Benin, we visited the Forest Reserve of Ouémé Supérieur, the Okpara forest and the Alibori Supérieur Forest Reserve. In the center, we targeted the Forest Reserve of Toui-Kilibo. The surveys have been carried during the raining season in the study area meaning from June to October. A total of 24 taxa were collected, photographed and described. The DNA was extracted, the Polymerase Chain Reaction was carried out using primers (ITS1-F, ITS4-B) for Internal transcribed spacer (ITS), (LROR, LWRB, LR7, LR5) for nuclear ribosomal (LSU), (RPB2-f5F, RPB2-b6F, RPB2- b6R2, RPB2-b7R) for RNA polymerase II gene (RPB2) and sequenced. The ITS sequences of the 24 collections of Inocybaceae were edited in Staden and all the sequences were aligned and edited with Aliview v1.17. The sequences were examined by eye for sufficient similarity to be considered the same species. 13 different species were present in the collections. In addition, sequences similar to the ITS sequences of the thirteen final species were searched using BLAST. The nLSU and RPB2 markers for these species have been inserted in a complete alignment, where species from all major Inocybaceae clades as well as from all continents except Antarctica are present. Our new sequences for nLSU and RPB2 have been manually aligned in this dataset. Phylogenetic analysis was performed using the RAxML v7.2.6 maximum likelihood software. Bootstrap replications have been set to 100 and no partitioning of the dataset has been performed. The resulting tree was viewed and edited with FigTree v1.4.3. The preliminary tree resulting from the analysis of maximum likelihood shows us that these species coming from Benin are much diversified and are distributed in four different clades (Inosperma, Inocybe, Mallocybe and Pseudosperma) on the seven clades of Inocybaceae but the phylogeny position of 7 is currently known. This study marks the diversity of Inocybe in Benin and the investigations will continue and a protection plan will be developed in the coming years.

Keywords: Benin, diversity, Inocybe, phylogeny placement

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Authors: Ademola Bamgbose

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The new media revolution, which encompasses a wide variety of new media technologies like blogs, social networking, visual worlds, wikis, have had a great influence on communications, traditional media and across other disciplines. This paper gives a review of the impact of new media technologies on the news, social interactions and traditional media in developing and developed countries. The study points to the fact that there is a significant impact of new media technologies on the news, social interactions and the traditional media in developing and developed countries, albeit both positively and negatively. Social interactions have been significantly affected, as well as in news production and reporting. It is reiterated that despite the pervasiveness of new media technologies, it would not bring to a total decline of traditional media. This paper contributes to the theoretical framework on the new media and will help to assess the extent of the impact of the new media in different locations.

Keywords: communication, media, news, new media technologies, social interactions, traditional media

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Authors: Jessica Gonzalez

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Veganism, along with different types of vegetarianism, consists in the abstinence of animal products. Far from being only an alimentary regulation, it stands as a political posture against the food industry generating itself a set of beliefs, prohibitions, and attitudes that compel the individual to a reevaluation of his obligations towards the environment. Veganism defends animal rights and at the same time reinforces a different conception of natural resources embodying it in alimentary restrictions. These practices emerge in the context of alimentary modernity, which is characterized by bringing new concerns to the consumer. An increased skepticism towards the government ability to protect food supply; a notable distrust toward the market guaranties on providing safe food with sustainable techniques and the desire to react to the neoliberal forms of exploitation are some of its consequences of this phenomenon. This study aims to approach the concept of governmentality as a coproduced system of legitimized practices and knowledge, formed by the interaction of the different actors that are involved. In a scenario where the State seems to retreat from centralized regulation of food production giving up importance to citizens, dietary consultants, farmers, and stockbreeders, veganism plays its role on the conformation of distinctive forms of environmentalism, nature rights and responses to ecological crisis. The ethnographic method allows observing the mechanisms of interaction of consumers and discourses with the mainstream food system, providing evidence about the means of generation of new conceptions about nature and the environment. The paper focuses on how the dietary restrictions, consumption patterns and public discourses of vegans in Barcelona impact local consumption, demonstrating its relevance as a mechanism that associates particular concerns about food with political economy.

Keywords: animal rights, environmentalism, food system, governmentality, veganism

Procedia PDF Downloads 113

Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen

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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.

Keywords: administrative law, algorithmic decision-making, decision support, public law

Procedia PDF Downloads 202

Authors: Ezeamagu M.U, Madu B.C

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This study was designed to investigate the efficacy of 5Es constructivist-based instructional model on students’ retention in primary Mathematics. 5Es stands for Engagement, Exploration, Explanation, Elaboration and Evaluation. The study adopted the pre test post test non-equivalent control group quasi-experimental research design. The sample size for the study was one hundred and thirty four pupils (134), seventy six male (76) and fifty eight female (58) from two primary schools in Nsukka education zone. Two intact classes in each of the sampled schools comprising all the primary four pupils were used. Each of the schools was given the opportunity of being assigned randomly to either experimental or control group. The Experimental group was taught using 5Es model while the control group was taught using the conventional method. Two research questions were formulated to guide the study and three hypotheses were tested at p ≤ 0. 05. A Fraction Achievement Test (FAT) of ten (10) questions were used to obtain data on pupils’ retention. Research questions were answered using mean and standard deviation while hypotheses were tested using analysis of covariance (ANCOVA). The result revealed that the 5Es model was more effective than the conventional method of teaching in enhancing pupils’ performance and retention in mathematics, secondly there is no significant difference in the mean retention scores of male and female students taught using 5Es instructional model. Based on the findings, it was recommended among other things, that the 5Es instructional model should be adopted in the teaching of mathematics in primary level of the educational system. Seminar, workshops and conferences should be mounted by professional bodies, federal and state ministries of education on the use of 5Es model. This will enable the mathematics educator, serving teachers, students and all to benefit from the approach.

Keywords: constructivist, education, mathematics, primary, retention

Procedia PDF Downloads 435

Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Diana F. Lopes, Jorge Simoes, José Martins, Eduardo Castro

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Health professionals are the keystone of any health system, by delivering health services to the population. Given the time and cost involved in training new health professionals, the planning process of the health workforce is particularly important as it ensures a proper balance between the supply and demand of these professionals and it plays a central role on the Health 2020 policy. In the past 40 years, the planning of the health workforce in Portugal has been conducted in a reactive way lacking a prospective vision based on an integrated, comprehensive and valid analysis. This situation may compromise not only the productivity and the overall socio-economic development but the quality of the healthcare services delivered to patients. This is even more critical given the expected shortage of the health workforce in the future. Furthermore, Portugal is facing an aging context of some professional classes (physicians and nurses). In 2015, 54% of physicians in Portugal were over 50 years old, and 30% of all members were over 60 years old. This phenomenon associated to an increasing emigration of young health professionals and a change in the citizens’ illness profiles and expectations must be considered when planning resources in healthcare. The perspective of sudden retirement of large groups of professionals in a short time is also a major problem to address. Another challenge to embrace is the health workforce imbalances, in which Portugal has one of the lowest nurse to physician ratio, 1.5, below the European Region and the OECD averages (2.2 and 2.8, respectively). Within the scope of the HEALTH 2040 project – which aims to estimate the ‘Future needs of human health resources in Portugal till 2040’ – the present study intends to get a comprehensive dynamic approach of the problem, by (i) estimating the needs of physicians and nurses in Portugal, by specialties and by quinquenium till 2040; (ii) identifying the training needs of physicians and nurses, in medium and long term, till 2040, and (iii) estimating the number of students that must be admitted into medicine and nursing training systems, each year, considering the different categories of specialties. The development of such approach is significantly more critical in the context of limited budget resources and changing health care needs. In this context, this study presents the drivers of the healthcare needs’ evolution (such as the demographic and technological evolution, the future expectations of the users of the health systems) and it proposes a Bayesian methodology, combining the best available data with experts opinion, to model such evolution. Preliminary results considering different plausible scenarios are presented. The proposed methodology will be integrated in a user-friendly decision support system so it can be used by politicians, with the potential to measure the impact of health policies, both at the regional and the national level.

Keywords: bayesian estimation, health economics, health workforce planning, human health resources planning

Procedia PDF Downloads 239