Search results for: statistical potential

Authors: Abdallah Abusam, Andrzej Mydlarczyk, Fadila Al-Salameen, Moh Elmuntasir Ahmed

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Treated municipal wastewater produced in Kuwait is used mainly in agricultural and greenery landscape irrigations. However, there are strong doubts that severe sludge bulking and foaming problems, particularly during winter seasons, may render the treated wastewater to be unsuitable for irrigation purposes. To assess the impact of sludge bulking and foaming problems on the quality of treated effluents, samples were collected weekly for nine months (January to September 2014) from the secondary effluents, tertiary effluents and sludge-mixed liquor streams of the two plants that severely suffer from sludge bulking and foaming problems. Dominant filamentous bacteria were identified and quantified using a molecular method called VIT (Vermicon Identification Technology). Quality of the treated effluents was determined according to water and wastewater standard methods. Obtained results were then statistically analyzed and compared to irrigation water standards. Statistical results indicated that secondary effluents were greatly impacted by sludge bulking and foaming problems, while tertiary effluents were slightly affected. This finding highlights the importance of having tertiary treatment units in plants that encountering sludge bulking and foaming problems.

Keywords: agriculture, filamentous bacteria, reclamation, reuse, wastewater

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Authors: Muhammad Naeem, Juho Lee, Jin-Wook Yoo

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In this study, we hypothesized that prolonged gastrointestinal transit at the inflamed colon conferred by a pH-triggered mucoadhesive smart nanoparticulate drug delivery system aids in achieving selective and sustained levels of the drug within the inflamed colon for the treatment of ulcerative colitis. We developed budesonide-loaded pH-sensitive charge-reversal solid lipid nanoparticles (SLNs) using a hot homogenization method. Polyetylenimine (PEI) was used to render SLNs cationic (PEI-SLNs). Eudragit S100 (ES) was coated on PEI-SLNs for pH-trigger charge-reversal SLNs (ES-PEI-SLNs). Therapeutic potential of the prepared SNLs formulation was evaluated in ulcerative colitis in mice. The transmission electron microscopy, zeta size and zeta potential data showed the successful formation of SLNs formulations. SLNs and PEI-SLNs showed burst drug release in acidic pH condition mimicking stomach and early small intestine environment which limiting their application as oral delivery systems. However, ES-PEI-SLNs prevented a burst drug release in acidic pH conditions and showed sustained release at a colonic pH. Most importantly, the surface charge of ES-PEI-SLNs switched from negative to positive in colonic conditions by pH-triggered removal of ES coating and accumulated selectively in inflamed colon. Furthermore, a charge reversal ES-PEI-SLNs showed a superior mitigation of dextran sulfate sodium (DSS)-induced acute colitis in mice as compared to SLNs and PEI-SLNs treated groups. Moreover, histopathological analysis of distal colon sections stained with hematoxylin/eosin and E-cadherin immunostaining revealed attenuated inflammation in an ES-PEI-SLNs-treated group. We also found that ES-PEI-SLNs markedly reduced the myeloperoxidase level and expression of TNF-alpha in colon tissue. Our results suggest that the pH-triggered charge reversal SLNs presented in this study would be a promising approach for ulcerative colitis therapy.

Keywords: solid lipid nanoparticles, stimuli-triggered charge-reversal, ulcerative colitis, methacrylate copolymer, budesonide

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Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

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Authors: Madhu Sarwan, Ritu Dubey, Sadhna Singh

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We have investigated the structural phase transition from Zinc-Blende (ZB) to Rock-Salt (RS) structure of TlxGa1-xAs by using Interaction Potential Model (IPM). The IPM consists of Coulomb interaction, Three-Body Interaction (TBI), Van Der Wall (vdW) interaction and overlap repulsive short range interaction. The structural phase transition has been computed by using the vegard’s law. The volume collapse is also computed for this alloy. We have also investigated the second order elastic constants with composition for the alloy TlxGa1-xAs.

Keywords: III-V alloy, elastic moduli, phase transition, semiconductors

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Authors: Victor O. Abegunde, Melusi Sibanda

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There is need for a great deal of attention on small-scale agriculture for livelihood and food security because of the expanding global population. Small-scale agriculture has been identified as a major driving force of agricultural and rural development. However, the high dependence of the sector on natural and climatic resources has made small-scale farmers highly vulnerable to the adverse impact of climatic change thereby necessitating the need for embracing practices or concepts that will help absorb shocks from changes in climatic condition. This study examines the strategic position of small-scale farming in South African agriculture and in ensuring food security in the country, the vulnerability of small-scale agriculture to climate change and the potential of the concept of climate-smart agriculture to tackle the challenge of climate change. The study carried out a systematic review of peer-reviewed literature touching small-scale agriculture, climate change, food security and climate-smart agriculture, employing the realist review method. Findings revealed that increased productivity in the small-scale agricultural sector has a great potential of improving the food security of households in South Africa and reducing dependence on food purchase in a context of high food price inflation. Findings, however, also revealed that climate change affects small-scale subsistence farmers in terms of productivity, food security and family income, categorizing the impact on smallholder livelihoods into three major groups; biological processes, environmental and physical processes and impact on health. Analysis of the literature consistently showed that climate-smart agriculture integrates the benefits of adaptation and resilience to climate change, mitigation, and food security. As a result, farming households adopting climate-smart agriculture will be better off than their counterparts who do not. This study concludes that climate-smart agriculture could be a very good bridge linking small-scale agricultural sector and agricultural productivity and development which could bring about the much needed food security.

Keywords: climate change, climate-smart agriculture, food security, small-scale

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: A. Guemache, M. Omari

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Oxides with formula Ca1-xSrx MnO3(0≤x≤0.2) were synthesized using co precipitation method. The identification of the obtained phase was carried out using infrared spectroscopy and x-ray diffraction. Thermogravimetric and differential analysis was permitted to characterize different transformations of precursors which take place during one heating cycle. The study of electrochemical behavior was carried out by cyclic voltammetry and impedance spectroscopy. The obtained results show that apparent catalytic activity improved when increasing the concentration of strontium. Anodic current densities varies from 1.3 to 5.9 mA/cm2 at the rate scan of 20 mV.s-1 and a potential 0.8 V for oxides with composition x=0 to 0.2.

Keywords: oxide, co-precipitation, thermal analysis, electrochemical properties

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Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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Authors: Seyedtaghi Mirmohammadi, Jamshid Yazdani, Syavash Etemadi Nejad

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One of the main indoor air parameters in classrooms is dust pollution and it depends on the particle size and exposure duration. However, there is a lake of data about the exposure level to PM2.5 concentrations in rural area classrooms. The objective of the current study was exposure assessment for PM2.5 for students in the classrooms. One year monitoring was carried out for fifteen schools by time-series sampling to evaluate the indoor air PM2.5 in the rural district of Sari city, Iran. A hygrometer and thermometer were used to measure some psychrometric parameters (temperature, relative humidity, and wind speed) and Real-Time Dust Monitor, (MicroDust Pro, Casella, UK) was used to monitor particulate matters (PM2.5) concentration. The results show the mean indoor PM2.5 concentration in the studied classrooms was 135µg/m3. The regression model indicated that a positive correlation between indoor PM2.5 concentration and relative humidity, also with distance from city center and classroom size. Meanwhile, the regression model revealed that the indoor PM2.5 concentration, the relative humidity, and dry bulb temperature was significant at 0.05, 0.035, and 0.05 levels, respectively. A statistical predictive model was obtained from multiple regressions modeling for indoor PM2.5 concentration and indoor psychrometric parameters conditions.

Keywords: classrooms, concentration, humidity, particulate matters, regression

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: Xianming Chen, Yu Lei, Meinan Wang

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The dikaryotic basidiomycete fungus, Puccinia striiformis, causes stripe rust, one of the most important diseases of wheat and barley worldwide. The pathogen is largely reproduced asexually, and asexual recombination has been hypothesized to be one of the mechanisms for the pathogen variations. To test the hypothesis and understand the genetic process of asexual recombination, somatic recombinant isolates were obtained under controlled conditions by inoculating susceptible host plants with a mixture of equal quantity of urediniospores of isolates with different virulence patterns and selecting through a series of inoculation on host plants with different genes for resistance to one of the parental isolates. The potential recombinant isolates were phenotypically characterized by virulence testing on the set of 18 wheat lines used to differentiate races of the wheat stripe rust pathogen, P. striiformis f. sp. tritici (Pst), for the combinations of Pst isolates; or on both sets of the wheat differentials and 12 barley differentials for identifying races of the barley stripe rust pathogen, P. striiformis f. sp. hordei (Psh) for combinations of a Pst isolate and a Psh isolate. The progeny and parental isolates were also genotypically characterized with 51 simple sequence repeat and 90 single-nucleotide polymorphism markers. From nine combinations of parental isolates, 68 potential recombinant isolates were obtained, of which 33 (48.5%) had similar virulence patterns to one of the parental isolates, and 35 (51.5%) had virulence patterns distinct from either of the parental isolates. Of the 35 isolates of distinct virulence patterns, 11 were identified as races that had been previously detected from natural collections and 24 were identified as new races. The molecular marker data confirmed 66 of the 68 isolates as recombinants. The percentages of parental marker alleles ranged from 0.9% to 98.9% and were significantly different from equal proportions in the recombinant isolates. Except for a couple of combinations, the greater or less contribution was not specific to any particular parental isolates as the same parental isolates contributed more to some of the progeny isolates but less to the other progeny isolates in the same combination. The unequal contributions by parental isolates appear to be a general role in somatic recombination for the stripe rust fungus, which may be used to distinguish asexual recombination from sexual recombination in studying the evolutionary mechanisms of the highly variable fungal pathogen.

Keywords: molecular markers, Puccinia striiformis, somatic recombination, stripe rust

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Authors: Mehrnoosh Jafari, Zeinolabedin Amini Sabegh, Habibollah Azimian

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Background: Today variable and dynamic environment doubles importance of using suitable solutions for confronting these changes in th4e organizations. One of the best ways for coping with environmental changes is directing the organization towards agility. Current research aims at investigating status of organizational agility in Tehran municipality (22 districts). Research Methodology: This research is applied research in terms of purpose of study and it is survey in terms of collection of descriptive data. A sample (n = 377) was selected from Tehran Municipality (22 districts) employees using multistage sampling method (cluster and regular). Data were collected using organizational agility standard questionnaire, and they were analyzed using statistical tests in SPSS software as well as inferential statistics such as one-sample t-test and Friedman test and descriptive statistics such as mean and median. Findings: Research findings showed organizational agility status in the organizations under study is in relatively optimal status and competence has highest priority in terms of ranking and priority of organizational agility indexes. Conclusion: It is necessary that managers provide suitable conditions for promoting organizational agility status in the organizations under study by identifying factors affecting change in the organizational environments and using available potentials for better coping with changes and higher flexibility and speed.

Keywords: organizational, municipality, employer, agility

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Authors: Andrey Khalov

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The rapid growth of unstructured data necessitates advanced methods for transforming raw information into structured knowledge, particularly in domain-specific contexts such as IT service management and outsourcing. This paper presents a methodology for automatically constructing domain ontologies using the DOLCE framework as the base ontology. The research focuses on expanding ITIL-based ontologies by integrating concepts from ITSMO, followed by the extraction of entities and relationships from domain-specific texts through transformers and statistical methods like formal concept analysis (FCA). In particular, this work introduces an R-GNN-based approach for ontology mapping, enabling more efficient entity extraction and ontology alignment with existing knowledge bases. Additionally, the research explores transfer learning techniques using pre-trained transformer models (e.g., DeBERTa-v3-large) fine-tuned on synthetic datasets generated via large language models such as LLaMA. The resulting ontology, termed IT Ontology (ITO), is evaluated against existing methodologies, highlighting significant improvements in precision and recall. This study advances the field of ontology engineering by automating the extraction, expansion, and refinement of ontologies tailored to the IT domain, thus bridging the gap between unstructured data and actionable knowledge.

Keywords: ontology mapping, knowledge graphs, R-GNN, ITIL, NER

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Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

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Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

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An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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Authors: Nayla El-Kork, Farah Korjieh, Ahmed Bentiba, Mahmoud Korek

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Ab-initio calculations have been performed to investigate the spectroscopic constants for the diatomic compound BeF. Values of the internuclear distance Re, the harmonic frequency ωe, the rotational constants Be, the electronic transition energy with respect to the ground state Te, the eignvalues Ev, the abscissas of the turning points Rmin, Rmax, the rotational constants Bv and the centrifugal distortion constants Dv have been calculated for the molecule’s ground and excited electronic states. Results are in agreement with experimental data.

Keywords: spectroscopic constant, potential energy curve, diatomic molecule, spectral analysis

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Authors: Gaurav Kumar Sinha

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As the world grapples with climate challenges, this study highlights the instrumental role of AWS services in amplifying the impact of LCVs. Their ability to harness the cloud, data analytics, and scalable infrastructure offered by AWS empowers LCVs to innovate, scale, and drive meaningful change in the quest for a sustainable future. This study serves as a rallying cry, urging stakeholders to recognize, embrace, and maximize the potential of AWS-powered solutions in advancing sustainable and resilient global initiatives.

Keywords: low carbon ventures, sustainability solutions, AWS services, data analytics

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Authors: Jude A. Mbanasor, Chigozirim N. Onwusiribe

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The enigma climate change is no longer an illusion but a reality. In the recent years, the Nigeria climate has changed and the changes are shown by the changing patterns of rainfall, the sunshine, increasing level carbon and nitrous emission as well as deforestation. This study analyzed the behavioural response of bee keepers to variations in the climate and the adaptation techniques developed in response to the climate variation. Beekeeping is a viable economic activity for the alleviation of poverty as the products include honey, wax, pollen, propolis, royal jelly, venom, queens, bees and their larvae and are all marketable. The study adopted the multistage sampling technique to select 120 beekeepers from the five states of Southeast Nigeria. Well-structured questionnaires and focus group discussions were adopted to collect the required data. Statistical tools like the Principal component analysis, data envelopment models, graphs, and charts were used for the data analysis. Changing patterns of rainfall and sunshine with the increasing rate of deforestation had a negative effect on the habitat of the bees. The bee keepers have adopted the Kenya Top bar and Langstroth hives and they establish the bee hives on fallow farmland close to the cultivated communal farms with more flowering crops.

Keywords: climate, farmer, response, smart

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Authors: Amani M. Al-Hussan

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The current study aimed to explore the effects of science teaching strategies course (CURR422) on developing academic self efficacy and motivation towards teaching it in female primary classroom teachers in College of Education in Princess Nora Bint AbdulRahman University. The study sample consisted (48) female student teachers. To achieve the study aims, the researcher designed two instruments: Academic Self Efficacy Scale & Motivation towards Teaching Science Scale while maintaining the validity and reliability of these instruments.. Several statistical procedures were conducted i.e. Independent Sample T-test, Eta Square, Cohen D effect size. The results reveal that there were statistically significant differences between means of pre and post test for the sample in favor of post test. For academic self efficacy scale, Eta square was 0.99 and the effect size was 27.26. While for the motivation towards teaching science scale, Eta was 0.99 and the effect size was 51.72. These results indicated high effects of independent variable on the dependent variable.

Keywords: academic self efficiency, achievement, motivation, primary classroom teacher, science teaching strategies course, evaluation

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Authors: Gechbaia Badri

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The paper discusses in today's world of economic globalization and development of innovative economic integration is one of the issues of the day in the world. The article analyzes the innovation economy development trends in EU, showed the innovation economy formation of the main problems and results, also the development of innovative potential of the economy. The author reckons that the European economy will contribute to the development of innovative economic space of speech in recent years developed a financial and economic crisis.

Keywords: European Union, innovative system, innovative development, innovations

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Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: Che Zarrina Sa'ari, Sheriza Izwa Zainuddin, Hasimah Chik, Sharifah Basirah Syed Muhsin

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Palliative care is holistic care for patients with serious illnesses and for the family as well by interdisciplinary specialties to optimize quality of life by preventing, treating, and comforting the suffering and struggling. Palliative care is not a curative treatment but a comprehensive care to ensure the well-being of patients. This study was to identify the perceptions of patients and carers on healthcare needs and any factors related to the needs of palliative patients. Validated questionnaires survey of 254 patients and carers were analysed using a Statistical Package for the Social Sciences (SPSS) version 22. The findings were processed with Cronbach Alpha analysis, frequency, and descriptive to compare the important of each element in healthcare. Open-ended responses were analysed using thematic framework approach. The findings proved that all the items in healthcare needs elements were important because the frequency shown higher values, which were physical needs (5.91), mental needs (6.10), spiritual needs (6.34), emotional needs (6.05), social needs (5.88) and logistics needs (5.05). The total score of Cronbach’s alpha (α) for this study is 0.958, which is suggesting very good internal consistency reliability for the elements for healthcare needs. Professionals and healthcare providers need to ensure healthcare planning is individualised by tailoring it to the values, priorities, and ethnic/cultural/religious context of each person.

Keywords: healthcare, need, holistic, palliative, multi speciality

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate which minimize the total incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: subcontracting, optimal control, deterioration, simulation, production planning

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Authors: Alexandra Papagianni, George Filis, Panagiotis Papadopoulos

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The liberalization of the energy market and the increasing penetration of fluctuating renewables (e.g., wind and solar power) have heightened the importance of the spot market for ensuring efficient electricity supply. This is further emphasized by the EU’s goal of achieving net-zero emissions by 2050. The day-ahead market (DAM) plays a key role in European energy trading, accounting for 80-90% of spot transactions and providing critical insights for next-day pricing. Therefore, short-term electricity price forecasting (EPF) within the DAM is crucial for market participants to make informed decisions and improve their market positioning. Existing literature highlights out-of-sample performance as a key factor in assessing EPF accuracy, with influencing factors such as predictors, forecast horizon, model selection, and strategy. Several studies indicate that electricity demand is a primary price determinant, while renewable energy sources (RES) like wind and solar significantly impact price dynamics, often lowering prices. Additionally, incorporating data from neighboring countries, due to market coupling, further improves forecast accuracy. Most studies predict up to 24 steps ahead using hourly data, while some extend forecasts using higher-frequency data (e.g., half-hourly or quarter-hourly). Short-term EPF methods fall into two main categories: statistical and computational intelligence (CI) methods, with hybrid models combining both. While many studies use advanced statistical methods, particularly through different versions of traditional AR-type models, others apply computational techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). Recent research combines multiple methods to enhance forecasting performance. Despite extensive research on EPF accuracy, a gap remains in understanding how forecasting strategy affects prediction outcomes. While iterated strategies are commonly used, they are often chosen without justification. This paper contributes by examining whether the choice of forecasting strategy impacts the quality of day-ahead price predictions, especially for multi-step forecasts. We evaluate both iterated and direct methods, exploring alternative ways of conducting iterated forecasts on benchmark and state-of-the-art forecasting frameworks. The goal is to assess whether these factors should be considered by end-users to improve forecast quality. We focus on the Greek DAM using data from July 1, 2021, to March 31, 2022. This period is chosen due to significant price volatility in Greece, driven by its dependence on natural gas and limited interconnection capacity with larger European grids. The analysis covers two phases: pre-conflict (January 1, 2022, to February 23, 2022) and post-conflict (February 24, 2022, to March 31, 2022), following the Russian-Ukraine conflict that initiated an energy crisis. We use the mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (sMAPE) for evaluation, as well as the Direction of Change (DoC) measure to assess the accuracy of price movement predictions. Our findings suggest that forecasters need to apply all strategies across different horizons and models. Different strategies may be required for different horizons to optimize both accuracy and directional predictions, ensuring more reliable forecasts.

Keywords: short-term electricity price forecast, forecast strategies, forecast horizons, recursive strategy, direct strategy

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Authors: Zheng Zhang, Xin Chen, Guoqing Ding

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Electronic apex locators (EAL) has been widely used clinically for measuring root canal working length with high accuracy, which is crucial for successful endodontic treatment. In order to maintain high accuracy in different measurement environments, this study presented a system for root canal length measurement based on multifrequency impedance method. This measuring system can generate a sweep current with frequencies from 100 Hz to 1 MHz through a direct digital synthesizer. Multiple impedance ratios with different combinations of frequencies were obtained and transmitted by an analog-to-digital converter and several of them with representatives will be selected after data process. The system analyzed the functional relationship between these impedance ratios and the distance between the file and the apex with statistics by measuring plenty of teeth. The position of the apical foramen can be determined by the statistical model using these impedance ratios. The experimental results revealed that the accuracy of the system based on multifrequency impedance ratios method to determine the position of the apical foramen was higher than the dual-frequency impedance ratio method. Besides that, for more complex measurement environments, the performance of the system was more stable.

Keywords: root canal length, apex locator, multifrequency impedance, sweep frequency

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Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

Abstract:

Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

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Authors: Ahmadi, Iriansyah, Raihana Yahman

Abstract:

The giant freshwater prawn (Macrobrachium rosenbergii de Man, 1879) is a valuable species for fisheries and aquaculture, especially in Southeast Asia, including Indonesia due to their high market demand and potential for export. The growing demand for prawns is straining the sustainability of the Banjar Regency fishery. To ensure the long-term sustainability and economic viability of the prawn fishing in this region, it is imperative to implement evidence-based management practices. This requires comprehensive data on the Catch per Unit Effort (CPUE), Maximum Sustainable Yield (MSY) and the current rate of prawn resource exploitation. it analyzed five years of prawn catch data (2019-2023) obtained from South Kalimantan Marine and Fisheries Services. Fishing gears (e.g. hook & line and cast net) were first standardized with Fishing Power Index, and then calculated effort and MSY. The intercept (a) and the slope (b) values of regression curve were used to estimate the catch-maximum sustainable yield (CMSY) and optimal fishing effort (Fopt) levels within the framework of the Surplus Production Model. The estimated rates of resource utilization were then compared to the criteria of The National Commission of Marine Fish Stock Assessment. The findings showed that the CPUE value peaked in 2019 at 33.48 kg/trip, while the lowest value observed in 2022 at 5.12 kg/trip. The CMSY value was estimated to be 17,396 kg/year, corresponding to the Fopt level of 1,636 trips/year. The highest utilization rate was 56.90% recorded in 2020, while the lowest rate was observed in 2021 at 46.16%. The annual utilization rates were classified as “medium”, suggesting that increasing fishing effort by 45% could potentially maximize prawn catches at an optimum level. These findings provide a baseline for sustainable fisheries management in the region.

Keywords: giant prawns, CPUE, fishing power index, sustainable potential, utilization rate

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Authors: Karishma Chester, Sarvesh Paliwal, Sayeed Ahmad

Abstract:

Solanumnigrum L. (Family: Solanaceae), is an important Indian medicinal plant and have been used in various traditional formulations for hepato-protection. It has been reported to contain significant amount of steroidal glycosides such as solamargine and solasonine as well as their aglycone part solasodine. Being important pharmacologically active metabolites of several members of Solanaceae these markers have been attempted various times for their extraction and quantification but separately for glycoside and aglycone part because of their opposite polarity. Here, we propose for the first time simultaneous extraction and quantification of aglycone (solasodine)and glycosides (solamargine and solasonine) inleaves and berries of S.nigrumusing solvent extraction followed by HPTLC analysis. Simultaneous extraction was carried out by sonication in mixture of chloroform and methanol as solvent. The quantification was done using silica gel 60F254HPTLC plates as stationary phase and chloroform: methanol: acetone: 0.5 % ammonia (7: 2.5: 1: 0.4 v/v/v/v) as mobile phaseat 400 nm, after derivatization with an isaldehydesul furic acid reagent. The method was validated as per ICH guideline for calibration, linearity, precision, recovery, robustness, specificity, LOD, and LOQ. The statistical data obtained for validation showed that method can be used routinely for quality control of various solanaceous drugs reported for these markers as well as traditional formulations containing those plants as an ingredient.

Keywords: solanumnigrum, solasodine, solamargine, solasonine, quantification

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Authors: Ana Gavardashvili

Abstract:

The field-and-scientific studies to evaluate the modern ecological state in the water area of the estuaries of the major water-abundant rivers in the coastal line of the Black Sea (Chorokhi, Kintrishi, Natanebi, Supsa, Khobistskali, Rioni and Enguri) and sea ports (Batumi, Poti) and sea terminals of the oil pipeline (Baku-Tbilisi-Supsa, Kulevi) were accomplished in the months of June and July of 2015. GPS coordinates and GIS programs were used to fix the areas of the estuaries of the above-listed rivers on a digital map, with their values varying within the limits of 0,861 and 20,390 km2. Water samples from the Black Sea were taken from the river estuaries and sea ports during the field works, with their statistical series of 125 points. The temperatures of air (t2) and water in the Black Sea (t1) were measured locally, and their relative value is (t1 /t2 ) = 0,69 – 0,92. 125 water samples taken from the study object in the Black Sea coastal line were subject to laboratory analysis, and it was established that the Black Sea acidity (pH) changes within the limits of 7,71 – 8,22 in the river estuaries and within 8,42 - 8,65 in the port water areas and at oil terminals. As for the Sea water salinity index (TDS), it changes within the limits of 6,15 – 12,67 in the river estuaries, and (TDS) = 11,80 – 13,67 in the port water areas and at oil terminals. By taking the gained data and climatic changes into account, by using the theories of reliability and risk at the following stage, the nature of the changes of the function of the Black Sea ecological parameters will be established.

Keywords: acidity, estuary, salinity, sea

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Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

Procedia PDF Downloads 133