Search results for: multiple distribution supply chain network

Authors: Eduardo P. Wiechmann, Jorge A. Henríquez, Pablo E. Aqueveque, Luis G. Muñoz

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PV energy prices are declining rapidly. To take advantage of the benefits of those prices and lower the carbon footprint, operational practices must be modified. Undoubtedly, it challenges the electrowinning practice to operate at constant current throughout the day. This work presents a technology that contributes in providing modulation capacity to the electrode current distribution system. This is to raise the day time dc current and lower it at night. The system is a triple intercell bar that operates in current-source mode. The design is a capping board free dogbone type of bar that ensures an operation free of short circuits, hot swapability repairs and improved current balance. This current-source system eliminates the resetting currents circulating in equipotential bars. Twin auxiliary connectors are added to the main connectors providing secure current paths to bypass faulty or impaired contacts. All system conductive elements are positioned over a baseboard offering a large heat sink area to the ventilation of a facility. The system works with lower temperature than a conventional busbar. Of these attributes, the cathode current balance property stands out and is paramount for day/night modulation and the use of photovoltaic energy. A design based on a 3D finite element method model predicting electric and thermal performance under various industrial scenarios is presented. Preliminary results obtained in an electrowinning facility with industrial prototypes are included.

Keywords: electrowinning, intercell bars, PV energy, current modulation

Procedia PDF Downloads 140

Authors: Yan Liu

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The Gini coefficient indicates that the inequality of income distribution is rising in China. How individuals viewing the equality of current society is an important predicator of social turbulence. Perceptions of social justice may vary according to the social stratification. People usually use socioeconomic status to identify divisions between social stratifications. The objective of this study is to explore the potential influence of socioeconomic status on citizens’ perceptions of social justice in China. Socioeconomic status (SES) is usually reflected by either an SES indicator or a composite of three core dimensions: education, income and occupation. With data collected in the 2010 Chinese General Social Survey (CGSS), this study uses OLS regression analyses to examine the relationship between socioeconomic status (SES) and citizens’ perceptions of social justice. This study finds that most Chinese citizens believe that the current society is fair or more than fair. Socioeconomic status (SES) has a positive impact on citizens’ perceptions of social justice, which means individuals with higher indicator of socioeconomic status prefer to believe current society is fair. However, the three core dimensions which are used to measure socioeconomic status (SES) have different influences on perceptions of social justice: First, income helps enhance citizens’ sense of social justice. Second, education weakens citizens’ sense of social justice. Third, compared to the middle occupational status, people of both higher occupational status and lower occupational status have higher levels of perceptions of social justice. Though education creates a negative influence on perceptions of social justice, its effect is much weaker than that of income, which indicates income is a determining factor for enhancing people’s perceptions of social justice in China’s market society. Policy implications are discussed.

Keywords: education, income, occupation, perceptions of social justice, social stratification, socioeconomic status

Procedia PDF Downloads 288

Authors: Yunita Ratih Wijayanti, Dwi Rahmawati, Turniningtyas Ayu Rahmawati

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Gresik is one of the districts in East Java Province, Indonesia. Gresik Regency has three major rivers, namely Bengawan Solo River, Brantas River, and Lamong River. Lamong River is a tributary of Bengawan Solo River. Flood disasters that occur in Gresik Regency are often caused by the overflow of the Lamong River. The losses caused by the flood were very large and certainly detrimental to the affected people. Therefore, to be able to minimize the impact caused by the flood, it is necessary to take preventive action. However, before taking preventive action, it is necessary to have information regarding potential inundation areas and water levels at various points. For this reason, a flood simulation model is needed. In this study, the simulation was carried out using the Geographic Information System (GIS) method with the help of Global Mapper software. The approach used in this simulation is to use a topographical approach with Digital Elevation Models (DEMs) data. DEMs data have been widely used for various researches to analyze hydrology. The results obtained from this flood simulation are the distribution of flood inundation and water level. The location of the inundation serves to determine the extent of the flooding that occurs by referring to the 50-100 year flood plan, while the water level serves to provide early warning information. Both will be very useful to find out how much loss will be caused in the future due to flooding in Gresik Regency so that the Gresik Regency Regional Disaster Management Agency can take precautions before the flood disaster strikes.

Keywords: flood hazard, simulation model, potential inundation, global mapper, Gresik Regency

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

Procedia PDF Downloads 163

Authors: Noora Al Muftah, Reda Rawi, Richard Thompson, Halima Bensmail

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Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers of response to targeted agents. There is an urgent need to identify biomarkers that predict which patients with are most likely to respond to treatment. Systematic efforts to correlate tumor mutational data with biologic dependencies may facilitate the translation of somatic mutation catalogs into meaningful biomarkers for patient stratification. To identify genomic features associated with drug sensitivity and uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we have screened and integrated a panel of several hundred cancer cell lines from different databases, mutation, DNA copy number, and gene expression data for hundreds of cell lines with their responses to targeted and cytotoxic therapies with drugs under clinical and preclinical investigation. We found mutated cancer genes were associated with cellular response to most currently available Glioma cancer drugs and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

Keywords: cancer, gene network, Lasso, penalized regression, P-values, unbiased estimator

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Authors: Marine Nozadze, George Japoshvili, George Melika

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In 2020-2021 we studied oaks gall wasps of different oak species in Georgia at 7 locations of their natural distribution: 1. Quercuse petrea subsp. iberica - Mtskheta municipality, village. Mukhattskaro; 2. Quercus subsp. pendunculifloria - Kvareli municipality, village. Gramy;3. Quercus robur subsp. imeretina -Baghdati Municipality, Ajameti Reserve; 4. Quercus pontica -Chokhatauri municipality, village. Tskhratskaro; 5. Quercus macranthera -Tetritskaro Municipality, Algeti National Park; 6. Quercuse petrea subsp. iberica - Shuakhevi municipality, village. Uchamba 7. Quercus hartwissiana - Baghdatis municipality, village. Dimi. Samples were collected from early spring to late autumn. As a result, 7 forms of galls were collected and described wich caused by different species of oak gall wasps: 1. Neuroterus numismalis asexual gall 2. Neuroterus quercusbaccarum asexual galls 3. Cynips korsakovi asexual gall 4. Biorhiza pallida sexual gall 5. Neuroterus quercusbaccarum asexual galls 6. Neuroterus numismalis sexual gall 7. Cynips quercusfolii. Neuroterus quercusbaccarum asexual galls form the most represented of them: In Algeti National Park; In Mtskheta municipality; In Shuakhevi municipality and Ajameti reserve. The most damaged locations by oak gall wasps were Algeti National Park and Mtskheta Municipality, whereas the most biodiversity according to galls form was represented In Algeti National Park.

Keywords: gall wasps, oak, cynipidae, species

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Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

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Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its micro structure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

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Authors: Eskinder Desta Shumuye, Jun Zhao, Zike Wang

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This paper summarizes the results of experimental studies carried out at Zhengzhou University, School of Mechanics and Engineering Science, research laboratory, on the performance of concrete produced by combining Ordinary Portland Cement (OPC) with Ground-Granulated Blast Furnace Slag (GGBS). Concrete specimens cast with OPC and various percentage of GGBS (0%, 30%, 50%, and 70%) were subjected to high temperature exposure and extensive experimental test reproducing basic freeze-thaw cycle and a chloride-ion attack to determine their combined effects within the concrete samples. From the experimental studies, comparisons were made on the physical, mechanical, and microstructural properties in compassion with ordinary Portland cement concrete (OPC). Further, durability of GGBS cement concrete, such as exposure to accelerated carbonation, chloride ion attack, and freeze-thaw action in compassion with various percentage of GGBS and ordinary Portland cement concrete of similar mixture composition was analyzed. The microstructure, mineralogical composition, and pore size distribution of concrete specimens were determined via Scanning Electron Microscopy (SEM) analysis and X-Ray Diffraction (XRD). The result demonstrated that when the exposure temperature increases from 200 ºC to 400 ºC, the residual compressive strength was fluctuating for all concrete group, and compressive strength and chloride ion exposure of the concrete decreased with the increasing of slag content. The SEM and EDS results showed an increase in carbonation rate with increasing in slag content.

Keywords: accelerated carbonation, chloride-ion, concrete, ground-granulated blast furnace slag, GGBS, high-temperature

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Authors: Benhui Fan, Fahmi Bedoui, Jinbo Bai

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Incorporated carbon nanotube-BaTiO₃ hybrids (H-CNT-BT) with core-shell structure, a better dispersion of CNTs can be achieved in a semi-crystalline polymeric matrix, polyvinylidene fluoride (PVDF). Carried by BT particles, CNTs are easy to mutually connect which helps to obtain an extremely low percolation threshold (fc). After thermal treatments, the dielectric constants (ε’) of samples further increase which depends on the conditions of thermal treatments such as annealing temperatures, annealing durations and cooling ways. Thus, in order to study more comprehensively about the influence of thermal treatments on composite’s dielectric behaviors, in situ synchrotron X-ray is used to detect re-crystalline behavior of PVDF. Results of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) show that after the thermal treatment, the content of β polymorph (the polymorph with the highest ε’ among all the polymorphs of PVDF’s crystalline structure) has increased nearly double times at the interfacial region of CNT-PVDF, and the thickness of amorphous layers (La) in PVDF’s long periods (Lp) has shrunk around 10 Å. The evolution of CNT’s network possibly occurs in the procedure of La shrinkage, where the strong interfacial polarization may be aroused and increases ε’ at low frequency. Moreover, an increase in the thickness of crystalline lamella may also arouse more orientational polarization and improve ε’ at high frequency.

Keywords: dielectric properties, thermal treatments, carbon nanotubes, crystalline structure

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

Procedia PDF Downloads 143

Authors: Tai Chen, Caihuan Tian, Xiuxia Ren, Jingqi Xue, Xiuxin Zhang

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The herbaceous peony has become increasingly popular worldwide in recent years, especially as a cut flower with great economic value. However, peony has a very short vase life, only 3-5 d usually, which seriously affects its commodity value. In this study, we used the cut peony (Paeonia lactiflora cv. Sarah) as a material and found that melatonin treatment significantly improved its postharvest performance. In the control group, its vase life was 4.8 d, accompanied by petal dropping at last; melatonin treatment (40 μM) increased this time to 6.9 d without petal dropping at the end. Further study showed that melatonin treatment significantly increased the activity of antioxidant enzymes as well as reduced sugar content in petals, whereas the starch content in petals decreased. These results indicated that melatonin treatment may delay the oxidation reaction caused by aging, which also provides extra energy for maintaining flowering. Through full-length transcriptome sequencing, a total of 2819 differentially expressed genes (DEGs) between control and melatonin treatment groups were identified. KEGG enrichment analysis showed that these DEGs were mainly involved in three pathways, including melatonin synthesis, starch and sucrose conversion, and plant disease resistance. After the RT-qPCR verification, we identified three DEGs, named PlBAM3, PlWRKY22 and PlTIP1, and they should play major roles in melatonin-improved postharvest performance. One possible reason is that PlBAM3 caused maltose production (by starch degradation), maintained the proline biosynthesis, and then alleviated oxidative stress. Another reason is that both PlBAM3 and PlWRKY22 are key drought resistance regulators, which have the ability to alleviate osmotic stress and improve water absorption, which may also help to improve the postharvest quality of cut peony. In addition, PlTIP1 is involved in the sugar signal pathway, indicating sugar may also as a signal substance during this process. Our work may give new ideas for developing new ways to prolong the vase life of cut peony and improve its commodity value eventually.

Keywords: cut peony, melatonin, vase life, oxidation reaction, energy supply, differentially expressed genes

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

Procedia PDF Downloads 169

Authors: Rohollah Asadian Kohestani, Nazanin Sedghi

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As the number of banks and financial institutions working in Iran has been significantly increased, the attracting and retaining customers and encouraging them to continually use the modern banking services have been important and vital issues. Therefore, there would be a serious competition without a deep perception of consumers and fitness of banking services with their needs in the current economic conditions of Iran. It should be noted that concepts such as 'brand equity' is defined based on the view of consumers; however, it is also focused by shareholders, competitors and other beneficiaries of a firm in addition to bank and its consumers. This study examines the impact of brand equity on the competitive advantage in the banking industry as intensive competition between brands of different banks leads to pay more attention to the brands. This research is based on the Aaker’s model examining the impact of four dimensions of brand equity on the competitive advantage of private banks in Behshahr city. Moreover, conducting an applied research and data analysis has been carried out by a descriptive method. Data collection was done using literature review and questionnaire. A 'simple random' methodology was selected for sampling staff of banks while sampling methodology to select consumers of banks was the distribution of questionnaire between staff and consumers of five private banks including Tejarat, Mellat, Refah K., Ghavamin and, Tose’e Ta’avon banks. Results show that there is a significant relationship between brand equity and their competitive advantage. In this research, software of SPSS 16 and LISREL 8.5, as well as different methods of descriptive inferential statistics for analyzing data and test hypotheses, were employed.

Keywords: brand awareness, brand loyalty, brand equity, competitive advantage

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Ayna Yusubova, Bart Clarysse

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This paper explores role of research institutes in creation of support ecosystem for new technology-based ventures. Previous literature introduced research institutes as part of business and knowledge ecosystem, very few studies are available that consider a research institute as an ecosystem that support high-tech startups at every stage of development. Based on a resource-based view and a stage-based model of high-tech startups growth, this study aims to analyze how a research institute builds a startup support ecosystem by attracting different stakeholders in order to help startups to overcome resource. This paper is based on an in-depth case study of public research institute that focus on development of entrepreneurial ecosystem in a developed region. Analysis shows that the idea generation stage of high-tech startups that related to the invention and development of product or technology for commercialization is associated with a lack of critical knowledge resources. Second, at growth phase that related to market entrance, high-tech startups face challenges associated with the development of their business network. Accordingly, the study shows the support ecosystem that research institute creates helps high-tech startups overcome resource gaps in order to achieve a successful transition from one phase of growth to the next.

Keywords: new technology-based firms, ecosystems, resources, business incubators, research instutes

Procedia PDF Downloads 246

Authors: Mohamed Saad Gad Elzoghby

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Nanomaterials are widely used nowadays for the consolidation of degraded archaeological limestone. It’s one of the most predominant stones in monumental buildings and statuary works. It is exposed to different weathering processes that cause degradation and the presence of deterioration pattern as cracks, fissures, and granular disintegration. Nanomaterials have been applied to limestone consolidation. Among these nanomaterials are nanolimes, i.e., dispersions of lime nanoparticles in alcohols, and nano-silica, i.e., dispersions of silica nanoparticles in water, promising consolidating products for limestone. It was investigated and applied to overcome the disadvantages of traditional consolidation materials such as lime water, water glass, and paraliod. So, researchers investigated and tested the effectiveness of nanomaterials as consolidation materials for limestone. The present study includes an evaluation of some nanomaterials in consolidation limestone stone in comparison with traditional consolidants. These consolidation materials are nano calcium hydroxide nanolime, and nanosilica. The latter is known commercially as Nano Estel and the former Known as Nanorestore compared to traditional consolidants Wacker OH (ethyl silicate) and Paraloid B72 (a copolymer of ethyl methacrylate and methyl acrylate). The study evaluated the consolidation effectiveness of nanomaterials and traditional consolidants by using followed methods, characterization of physical properties of stone, scanning electron microscopy (SEM), X-ray diffractometry, Fourier transforms infrared spectroscopy, and mechanical properties. The study confirmed that nanomaterials were better in the distribution and encapsulation of calcite grains in limestone, and traditional materials were better in improving the physical properties of limestone. It demonstrated that good results could be achieved through mixtures of nanomaterials and traditional consolidants.

Keywords: nanomaterials, limestone, consolidation, evaluation, weathering, nanolime, nanosilica, scanning electron microscope

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Authors: Raana Babadi Fathipour

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Tea, a beverage widely cherished across the globe, has captured the interest of scholars with its recent acknowledgement for possessing noteworthy health advantages. Of particular significance is its proven ability to ward off ailments such as cancer and cardiovascular afflictions. Moreover, within the realm of culinary creations, lipid oxidation poses a significant challenge for food product development. In light of these aforementioned concerns, this present discourse turns its attention towards exploring diverse methodologies employed in extracting polyphenols from various types of tea leaves and examining their utility within the vast landscape of the ever-evolving food industry. Based on the discoveries unearthed in this comprehensive investigation, it has been determined that the fundamental constituents of tea are polyphenols possessed of intrinsic health-enhancing properties. This includes an assortment of catechins, namely epicatechin, epigallocatechin, epicatechin gallate, and epigallocatechin gallate. Moreover, gallic acid, flavonoids, flavonols and theaphlavins have also been detected within this aromatic beverage. Of these myriad components examined vigorously in this study's analysis, catechin emerges as particularly beneficial. Multiple techniques have emerged over time to successfully extract key compounds from tea plants, including solvent-based extraction methodologies, microwave-assisted water extraction approaches and ultrasound-assisted extraction techniques. In particular, consideration is given to microwave-assisted water extraction method as a viable scheme which effectively procures valuable polyphenols from tea extracts. This methodology appears adaptable for implementation within sectors such as dairy production along with meat and oil industries alike.

Keywords: camellia sinensis, extraction, food application, shelf life, tea

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Authors: Som Pal Baliyan

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Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

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Authors: Sangeeta Tripathi, Muna Al Shahri

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This research article presents the changing role and status of women in Oman. Transformation of women’s status started with the regime of His Majesty Sultan Qaboos Bin Said in 1970. It is always desired by the Sultan to enable women in all the ways for the balance growth of the country. Forbidding full face veil for women in public offices is one of the best efforts for their empowerment. Women education is also increasing rapidly. They are getting friendly with new information communication technology and using different social media applications such as WhatsApp, Instagram and Facebook for interaction and economic growth. Though there are some traditional and tribal boundaries, women are infused with courage and enjoying fair treatment and equal opportunities in different career positions. The study will try to explore changing mindset of young Omani women towards these traditional tribal boundaries, cultural heritage, business and career: ‘How are young Omani women making balance between work and social prestige?’, ‘How are they preserving their cultural values, embracing new technologies and approaching social network to enhance their economic power.’ This paper will discover their hurdles while using internet for their new entrepreneur. It will also examine the prospects of online business in Oman. The mixed research methodology is applied to find out the result.

Keywords: advertising, business, entrepreneurship, tribal barrier

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Authors: Mesbah Khaled, Bouraoui Ouissal, Benkiniouar Rachid, Belkhiri Lotfi

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Alstonia, which are tropical plants with a wide geographical distribution, have been divided into different sections by different authors based on previous studies of several species within the genus. Monachino divides Alstonia into 5 sections, while Pichon divides it into 3 sections. Several plants belonging to this genus, such as Alstonia brassii, have been used in traditional folk medicine to treat ailments such as fever, malaria and dysentery]. Previous studies focusing on the chemical composition of these plants have successfully identified indol alkaloids with cytotoxic, anti-diabetic and anti-inflammatory properties. The newly discovered monomers are structurally similar to the backbones of picralin, affinisin and macrolin. On the other hand, all recently isolated dimeric compounds have a macrolin moiety. In this study, a computational analysis was performed on a series of novel molecules, including both monomeric and dimeric compounds with different structural frameworks. This investigation represents the first computational study of these molecules using an in silico approach incorporating 2D-QSAR data. The analysis involved various computational techniques, including 2D-QSAR modelling, molecular docking studies and subsequent validation by molecular dynamics simulation and assessment of ADMET properties. The chemical composition was identified by 1D and 2D NMR. Eight new alkaloids were isolated, 5 monomers and 3 dimers. In this section, we focus on the biological activity of 4 new alkaloids belonging to two different skeletons, the affinisine skeleton.

Keywords: affinisine, talcarpine, macroline, cytotoxicity, alkaloids

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Authors: Norhan El Dallal

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The MENA region is a challenging, rapid urbanizing region, with a special profile; culturally, socially, economically and environmentally. Despite the diversity between different countries of the MENA region they all share similar urban challenges where extensive interventions are crucial. A climate sensitive region as the MENA region requires special attention for development, adaptation and mitigation. Integrating climatic and environmental parameters into the planning process to create a responsive urban form is the aim of this research in which “Parametric Urbanism” as a trend serves as a tool to reach a more sustainable urban morphology. An attempt to parameterize the relation between the climate and the urban form in a detailed manner is the main objective of the thesis. The aim is relating the different passive approaches suitable for the MENA region with the design guidelines of each and every part of the planning phase. Various conceptual scenarios for the network pattern and block subdivision generation based on computational models are the next steps after the parameterization. These theoretical models could be applied on different climatic zones of the dense communities of the MENA region to achieve an energy efficient neighborhood or city with respect to the urban form, morphology, and urban planning pattern. A final criticism of the theoretical model is to be conducted showing the feasibility of the proposed solutions economically. Finally some push and pull policies are to be proposed to help integrate these solutions into the planning process.

Keywords: parametric urbanism, climate responsive, urban form, urban and regional studies

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Showkat Ahmad Bhat, Iqra Reyaz, Falaque ul Afshan, Ahmad Arif Reshi, Muneeb U. Rehman, Manzoor R. Mir, Sabhiya Majid, Sonallah, Sheikh Bilal, Ishraq Hussain

Abstract:

Background: Gastric cancer is the fourth most common cancer and the second leading cause of worldwide cancer-related deaths, with a wide variation in incidence rates across different geographical areas. The current view of cancer is that a malignancy arises from a transformation of the genetic material of a normal cell, followed by successive mutations and by chain of alterations in genes such as DNA repair genes, oncogenes, Tumor suppressor genes. Minerals are necessary for the functioning of several transcriptional factors, proteins that recognize certain DNA sequences and have been found to play a role in gastric cancer. Material Methods:The present work was a case control study and its aim was to ascertain the role of minerals and promoter hypermethylation of CpG islands of DAP-K gene in Gastric cancer patients among the Kashmiri population. Serum was extracted from all the samples and mineral estimation was done by AAS from serum, DNA was also extracted and was modified using bisulphite modification kit. Methylation-specific PCR was used for the analysis of the promoter hypermethylation status of DAP-K gene. The epigenetic analysis revealed that unlike other high risk regions, Kashmiri population has a different promoter hypermethylation profile of DAP-K gene and has different mineral profile. Results: In our study mean serum copper levels were significantly different for the two genders (p<0.05), while as no significant differences were observed for iron and zinc levels. In Methylation-specific PCR the methylation status of the promoter region of DAP-K gene was as 67.50% (27/40) of the gastric cancer tissues showed methylated DAP-K promoter and 32.50% (13/40) of the cases however showed unmethylated DAP-K promoter. Almost all 85% (17/20) of the histopathologically confirmed normal tissues showed unmethylated DAP-K promoter except only in 3 cases where DAP-K promoter was found to be methylated. The association of promoter hypermethylation with gastric cancer was evaluated by χ2 (Chi square) test and was found to be significant (P=0.0006). Occurrence of DAP-K methylation was found to be unequally distributed in males and females with more frequency in males than in females but the difference was not statistically significant (P =0.7635, Odds ratio=1.368 and 95% C.I=0.4197 to 4.456). When the frequency of DAP-K promoter methylation was compared with clinical staging of the disease, DAP-K promoter methylation was found to be certainly higher in Stage III/IV (85.71%) compared to Stage I/ II (57.69%) but the difference was not statistically significant (P =0.0673). These results suggest that DAP-K aberrant promoter hypermethylation in Kashmiri population contributes to the process of carcinogenesis in Gastric cancer and is reportedly one of the commonest epigenetic changes in the development of Gastric cancer.

Keywords: gastric cancer, minerals, AAS, hypermethylation, CpG islands, DAP-K gene

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Y. S. Shen, B. H. Liao

Abstract:

This study aimed to develop the design equation of a laminar-falling-film-slurry (LFFS) type photoreactor for the treatment of organic wastewaters containing isopropyl alcohol (IPA) by VUV-based advanced oxidation processes (AOPs). The photoreactor design equations were established by combining with the chemical kinetics of the photocatalytic system, light absorption model within the photoreactor, and was used to predict the decomposition of IPA in aqueous solutions in the photoreactors of different geometries at various operating conditions (volumetric flow rate, oxidants, catalysts, solution pH values, UV light intensities, and initial concentration of pollutants) to verify its rationality and feasibility. By the treatment of the LFFS-VUV only process, it was found that the decomposition rates of IPA in aqueous solutions increased with the increase of volumetric flow rate, VUV light intensity, dosages of TiO2 and H2O2. The removal efficiencies of IPA by photooxidation processes were in the order: VUV/H2O2>VUV/TiO2/H2O2>VUV/TiO2>VUV only. In VUV, VUV/H2O2, VUV/TiO2/H2O2 processes, integrating with the reaction kinetic equations of IPA, the mass conservation equation and the linear light source model, the photoreactor design equation can reasonably to predict reaction behaviors of IPA at various operating conditions and to describe the concentration distribution profiles of IPA within photoreactors.The results of this research can be useful basis for the future application of the homogeneous and heterogeneous VUV-based advanced oxidation processes.

Keywords: isopropyl alcohol, photoreactor design, VUV, AOPs

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Authors: Hong Zhang, Runlian Miao, Min Zhang

Abstract:

Coordinated development of Beijing-Tianjin-Hebei region is of great importance and has been emphasized by the government in recent years. Beijing-Tianjin-Hebei region accumulates a large part of S&T resources of the whole country and boasts the most influential achievements. In order to improve innovation capability of the region, universities, research institutions and enterprises from Beijing, Tianjin and Hebei have cooperated in many forms, but technological innovation is not so satisfactory due to unbalanced allocation, poor sharing and low utilization efficiency of S&T resources. Therefore, it’s very necessary to promote resources sharing, optimize their overall layout, and enhance their innovation performance, which can further deepen coordination development of the region. This study focuses on S&T resources with the methods of documents research plus field investigation and qualitative research combing plus quantitive research. It starts from the macro background of promoting coordinated development of Beijing-Tianjin-Hebei region and arrives at improving regional innovation capability. Firstly, the author makes a literature review on coordinated development of Beijing-Tianjin-Hebei region and summarizes that coordinated development has been carried forward in the major fields which lay foundation for regional innovation; secondly, analyzes current S&T resources distribution and coordinated innovation by taking key industries as the examples; based on analysis of the status quo of resources sharing and innovation in the region, the author points out problems and obstacles that holdbacks coordinated innovation of the region and at last raises some suggestions to resources sharing and regional innovation. It reaches the conclusion that an efficient management mechanism, market laws, favorable environment, model innovation and incentive measures can help to accelerate resources sharing and regional innovation in the region.

Keywords: Beijing-Tianjin-Hebei region, coordinated development, innovation, S&T resources

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Authors: Yountaik Leem, Sang Ho Lee

Abstract:

In this paper, different goals and the ways to reach smart cities shown in many countries during planning and implementation processes will be discussed. Each country dealt with technologies which have been embedded into space as development of ICTs (information and communication technologies) for their own purposes and by their own ways. For example, European countries tried to adapt technologies to reduce greenhouse gas emission to overcome global warming while US-based global companies focused on the way of life using ICTs such as EasyLiving of Microsoft™ and CoolTown of Hewlett-Packard™ during last decade of 20th century. In the North-East Asian countries, urban space with ICTs were developed in large scale on the viewpoint of capitalism. Ubiquitous city, first introduced in Korea which named after Marc Weiser’s concept of ubiquitous computing pursued new urban development with advanced technologies and high-tech infrastructure including wired and wireless network. Japan has developed smart cities as comprehensive and technology intensive cities which will lead other industries of the nation in the future. Not only the goals and strategies but also new directions to which smart cities are oriented also suggested at the end of the paper. Like a Finnish smart community whose slogan is ‘one more hour a day for citizens,’ recent trend is forwarding everyday lives and cultures of human beings, not capital gains nor physical urban spaces.

Keywords: smart cities, urban strategy, future direction, comparative study

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Authors: M. Bahari Mehrabani, Hua-Peng Chen

Abstract:

Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

Abstract:

This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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