Search results for: soil crusting processing

Authors: Naresh Kumar, Savita Kumari, Naresh Kochhar

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The objective of the study was to assess the role of mineralogy and subsurface structure on water quality of Tosham, Malani Igneous Suite (MIS), Western Rajasthan, India. MIS is the largest (55,000 km2) A-type, anorogenic and high heat producing acid magmatism in the peninsular India and owes its origin to hot spot tectonics. Apart from agricultural and industrial wastes, geogenic activities cause fluctuations in quality parameters of water resources. Twenty water samples (20) selected from Tosham and surrounding areas were analyzed for As, Pb, B, Al, Zn, Fe, Ni using Inductive coupled plasma emission and F by Ion Chromatography. The concentration of As, Pb, B, Ni and F was above the stipulated level specified by BIS (Bureau of Indian Standards IS-10500, 2012). The concentration of As and Pb in surrounding areas of Tosham ranged from 1.2 to 4.1 mg/l and from 0.59 to 0.9 mg/l respectively which is higher than limits of 0.05mg/l (As) and 0.01 mg/l (Pb). Excess trace metal accumulation in water is toxic to humans and adversely affects the central nervous system, kidneys, gastrointestinal tract, skin and cause mental confusion. Groundwater quality is defined by nature of rock formation, mineral water reaction, physiography, soils, environment, recharge and discharge conditions of the area. Fluoride content in groundwater is due to the solubility of fluoride-bearing minerals like fluorite, cryolite, topaz, and mica, etc. Tosham is comprised of quartz mica schist, quartzite, schorl, tuff, quartz porphyry and associated granites, thus, fluoride is leached out and dissolved in groundwater. In the study area, Ni concentration ranged from 0.07 to 0.5 mg/l (permissible limit 0.02 mg/l). The primary source of nickel in drinking water is leached out nickel from ore-bearing rocks. Higher concentration of As is found in some igneous rocks specifically containing minerals as arsenopyrite (AsFeS), realgar (AsS) and orpiment (As2S3). MIS consists of granite (hypersolvus and subsolvus), rhyolite, dacite, trachyte, andesite, pyroclasts, basalt, gabbro and dolerite which increased the trace elements concentration in groundwater. Nakora, a part of MIS rocks has high concentration of trace and rare earth elements (Ni, Rb, Pb, Sr, Y, Zr, Th, U, La, Ce, Nd, Eu and Yb) which percolates the Ni and Pb to groundwater by weathering, contacts and joints/fractures in rocks. Additionally, geological setting of MIS also causes dissolution of trace elements in water resources beneath the surface. NE–SW tectonic lineament, radial pattern of dykes and volcanic vent at Nakora created a way for leaching of these elements to groundwater. Rain water quality might be altered by major minerals constituents of host Tosham rocks during its percolation through the rock fracture, joints before becoming the integral part of groundwater aquifer. The weathering process like hydration, hydrolysis and solution might be the cause of change in water chemistry of particular area. These studies suggest that geological relation of soil-water horizon with MIS rocks via mineralogical variations, structures and tectonic setting affects the water quality of the studied area.

Keywords: geochemistry, groundwater, malani igneous suite, tosham

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Amit Kumar, Archana Gupta, Poonam Tandon, E. D. D’Silva

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Nonlinear optical (NLO) materials are the key materials for the fast processing of information and optical data storage applications. In the last decade, materials showing nonlinear optical properties have been the object of increasing attention by both experimental and computational points of view. Chalcones are one of the most important classes of cross conjugated NLO chromophores that are reported to exhibit good SHG efficiency, ultra fast optical nonlinearities and are easily crystallizable. The basic structure of chalcones is based on the π-conjugated system in which two aromatic rings are connected by a three-carbon α, β-unsaturated carbonyl system. Due to the overlap of π orbitals, delocalization of electronic charge distribution leads to a high mobility of the electron density. On a molecular scale, the extent of charge transfer across the NLO chromophore determines the level of SHG output. Hence, the functionalization of both ends of the π-bond system with appropriate electron donor and acceptor groups can enhance the asymmetric electronic distribution in either or both ground and excited states, leading to an increased optical nonlinearity. In this research, the experimental and theoretical study on the structure and vibrations of (2E)-3-[4-(methylsulfanyl) phenyl]-1-(3-bromophenyl) prop-2-en-1-one (3Br4MSP) is presented. The FT-IR and FT-Raman spectra of the NLO material in the solid phase have been recorded. Density functional theory (DFT) calculations at B3LYP with 6-311++G(d,p) basis set were carried out to study the equilibrium geometry, vibrational wavenumbers, infrared absorbance and Raman scattering activities. The interpretation of vibrational features (normal mode assignments, for instance) has an invaluable aid from DFT calculations that provide a quantum-mechanical description of the electronic energies and forces involved. Perturbation theory allows one to obtain the vibrational normal modes by estimating the derivatives of the Kohn−Sham energy with respect to atomic displacements. The molecular hyperpolarizability β plays a chief role in the NLO properties, and a systematical study on β has been carried out. Furthermore, the first order hyperpolarizability (β) and the related properties such as dipole moment (μ) and polarizability (α) of the title molecule are evaluated by Finite Field (FF) approach. The electronic α and β of the studied molecule are 41.907×10-24 and 79.035×10-24 e.s.u. respectively, indicating that 3Br4MSP can be used as a good nonlinear optical material.

Keywords: DFT, MEP, NLO, vibrational spectra

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Daramola Japheth, Tabiti S. Tabiti, Daramola Elizabeth Lara, Hussaini Yusuf Atulukwu

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Bida urban centre is faced with solid waste management problems which are evident in the processes of waste generation, onsite storage, collection, transfer and transport, processing and disposal of solid waste. As a result of this the urban centre is defaced with litters of garbage and offensive odours due to indiscriminate dumping of refuse within the neighborhood. The partial removal of the fuel subsidy by the Federal Government in January 2012 leads to the formation of Subsidy Reinvestment Programmes (SURE-P), the Federal Government’s share is 41 per cent of the savings while the States and Local Government shared the remaining 59 percent. The SURE-P Committee in carrying out the mandate entrusted upon it by the President by identifying few critical infrastructure and social Safety nets that will ameliorate the sufferings of Nigerians. Waste disposal programme as an aspect of Solid waste management is one of the areas of focus for Niger State SURE-programmes incorporated under Niger State Environmental Protection Agency. The emergence of this programme as related to waste management in Bida has left behind a huge refuse spots along major corridors leading to a serious state of mess. Major roads within the LGA is now turned to dumping site, thereby obstructing traffic movements, while the aesthetic nature of the town became something else with offensive odours all over. This paper however wishes to underscore the use of geographical Information System in identifying solid waste sports towards effective solid waste management in the Bida urban centre. The paper examined the spatial location of dumping points and its impact on the environment. Hand held Global Position System was use to pick the dumping points location; where a total number of 91 dumping points collected were uploaded to ArcGis 10.2 for analysis. Interview method was used to derive information from households living near the dumping site. It was discovered that the people now have to cope with offensive odours, rodents invasion, dog and cats coming around the house as a result of inadequate and in prompt collection of waste around the neighborhood. The researchers hereby recommend that more points needs to be created with prompt collections of waste within the neighborhood by the necessary SURE - P agencies.

Keywords: dumping site, neighborhood, refuse, waste

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Nahush Modak, Meena Pangarkar, Anand Pathak, Ankita Tamhane

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Background: Breast cancer is the prominent cause of cancer and mortality among women. This study was done to show the statistical analysis of a cohort of over 250 patients detected with breast cancer diagnosed by oncologists using Immunohistochemistry (IHC). IHC was performed by using ER; PR; HER2; Ki-67 antibodies. Materials and methods: Formalin fixed Paraffin embedded tissue samples were obtained by surgical manner and standard protocol was followed for fixation, grossing, tissue processing, embedding, cutting and IHC. The Ventana Benchmark XT machine was used for automated IHC of the samples. Antibodies used were supplied by F. Hoffmann-La Roche Ltd. Statistical analysis was performed by using SPSS for windows. Statistical tests performed were chi-squared test and Correlation tests with p<.01. The raw data was collected and provided by National Cancer Insitute, Jamtha, India. Result: Luminal B was the most prevailing molecular subtype of Breast cancer at our institute. Chi squared test of homogeneity was performed to find equality in distribution and Luminal B was the most prevalent molecular subtype. The worse prognostic indicator for breast cancer depends upon expression of Ki-67 and her2 protein in cancerous cells. Our study was done at p <.01 and significant dependence was observed. There exists no dependence of age on molecular subtype of breast cancer. Similarly, age is an independent variable while considering Ki-67 expression. Chi square test performed on Human epidermal growth factor receptor 2 (HER2) statuses of patients and strong dependence was observed in percentage of Ki-67 expression and Her2 (+/-) character which shows that, value of Ki depends upon Her2 expression in cancerous cells (p<.01). Surprisingly, dependence was observed in case of Ki-67 and Pr, at p <.01. This shows that Progesterone receptor proteins (PR) are over-expressed when there is an elevation in expression of Ki-67 protein. Conclusion: We conclude from that Luminal B is the most prevalent molecular subtype at National Cancer Institute, Jamtha, India. There was found no significant correlation between age and Ki-67 expression in any molecular subtype. And no dependence or correlation exists between patients’ age and molecular subtype. We also found that, when the diagnosis is Luminal A, out of the cohort of 257 patients, no patient shows >14% Ki-67 value. Statistically, extremely significant values were observed for dependence of PR+Her2- and PR-Her2+ scores on Ki-67 expression. (p<.01). Her2 is an important prognostic factor in breast cancer. Chi squared test for Her2 and Ki-67 shows that the expression of Ki depends upon Her2 statuses. Moreover, Ki-67 cannot be used as a standalone prognostic factor for determining breast cancer.

Keywords: breast cancer molecular subtypes , correlation, immunohistochemistry, Ki-67 and HR, statistical analysis

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Authors: Ricardo Torcato, Helder Morais

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The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

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Authors: Hülya Torun, Ondřej Novák, Jaromír Mikulík, Miroslav Strnad, Faik A. Ayaz

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World climate is changing. Millions of people in the world still face chronic undernourishment for conducting a healthy life and the world’s population is growing steadily. To meet this growing demand, agriculture and food systems must adapt to the adverse effects of climate change and become more resilient, productive and sustainable. From this perspective, to determine tolerant cultivars for undesirable environmental conditions will be necessary food production for sustainable development. Among abiotic stresses, soil salinity is one of the most detrimental global fact restricting plant sources. Development of salt-tolerant lines is required in order to increase the crop productivity and quality in salt-treated lands. Therefore, the objective of this study was to investigate the morphological and physiological responses of barley cultivars accessions to salinity stress by NaCl. For this purpose, it was aimed to determine the crosstalk between some endogenous phytohormones and exogenous salicylic acid (SA) in two different vegetative parts (leaves and roots) of barley (Hordeum vulgare L.; Poaceae; 2n=14; Ince-04) which is detected salt-tolerant. The effects of SA on growth parameters, leaf relative water content (RWC), endogenous phytohormones; including indole-3-acetic acid (IAA), cytokinins (CKs), abscisic acid (ABA), jasmonic acid (JA) and ethylene were investigated in barley cultivars under salinity stress. SA was applied to 17-day-old seedlings of barley in two different ways including before (pre-treated for 24 h) and simultaneously with NaCl stress treatment. NaCl (0, 150, 300 mM) exposure in the hydrophonic system was associated with a rapid decrease in growth parameters and RWC, which is an indicator of plant water status, resulted in a strong up-regulation of ABA as a stress indicator. Roots were more dramatically affected than leaves. Water conservation in 150 mM NaCl treated-barley plants did not change, but decreased in 300 mM NaCl treated plants. Pre- and simultaneously treatment of SA did not significantly alter growth parameters and RWC. ABA, JA and ethylene are known to be related with stress. In the present work, ethylene also increased, similarly to ABA, but not with the same intensity. While ABA and ethylene increased by the increment of salt concentrations, JA levels rapidly decreased especially in roots. Both pre- and simultaneously SA applications alleviated salt-induced decreases in 300 mM NaCl resulted in the increment of ABA levels. CKs and IAA are related to cell growth and development. At high salinity (300 mM NaCl), CKs (cZ+cZR) contents increased in both vegetative organs while IAA levels stayed at the same level with control groups. However, IAA increased and cZ+cZR rapidly decreased in leaves of barley plants with SA treatments before salt applications (in pre- SA treated groups). Simultaneously application of SA decreased CKs levels in both leaves and roots of the cultivar. Due to increasing concentrations of NaCl in association with decreasing ABA, JA and ethylene content and increments in CKs and IAA were recorded with SA treatments. As results of the study, in view of all the phytohormones that we tested, exogenous SA induced greater tolerance to salinity particularly when applied before salinity stress.

Keywords: Barley, Hordeum vulgare, phytohormones, salicylic acid, salinity

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Authors: Katsue Edo, Yu Hiroi

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T Increasing attention has been paid to using pictures and photographs in research since the beginning of the 21th century in social sciences. Meanwhile we have been studying the usefulness of Picture mining, which is one of the new ways for a these picture using researches. Picture Mining is an explorative research analysis method that takes useful information from pictures, photographs and static or moving images. It is often compared with the methods of text mining. The Picture Mining concept includes observational research in the broad sense, because it also aims to analyze moving images (Ochihara and Edo 2013). In the recent literature, studies and reports using pictures are increasing due to the environmental changes. These are identified as technological and social changes (Edo et.al. 2013). Low price digital cameras and i-phones, high information transmission speed, low costs for information transferring and high performance and resolution of the cameras of mobile phones have changed the photographing behavior of people. Consequently, there is less resistance in taking and processing photographs for most of the people in the developing countries. In these studies, this method of collecting data from respondents is often called as ‘participant-generated photography’ or ‘respondent-generated visual imagery’, which focuses on the collection of data and its analysis (Pauwels 2011, Snyder 2012). But there are few systematical and conceptual studies that supports it significance of these methods. We have discussed in the recent years to conceptualize these picture using research methods and formalize theoretical findings (Edo et. al. 2014). We have identified the most efficient fields of Picture mining in the following areas inductively and in case studies; 1) Research in Consumer and Customer Lifestyles. 2) New Product Development. 3) Research in Fashion and Design. Though we have found that it will be useful in these fields and areas, we must verify these assumptions. In this study we will focus on the field of fashion and design, to determine whether picture mining methods are really reliable in this area. In order to do so we have conducted an empirical research of the respondents’ attitudes and behavior concerning pictures and photographs. We compared the attitudes and behavior of pictures toward fashion to meals, and found out that taking pictures of fashion is not as easy as taking meals and food. Respondents do not often take pictures of fashion and upload their pictures online, such as Facebook and Instagram, compared to meals and food because of the difficulty of taking them. We concluded that we should be more careful in analyzing pictures in the fashion area for there still might be some kind of bias existing even if the environment of pictures have drastically changed in these years.

Keywords: empirical research, fashion and design, Picture Mining, qualitative research

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Authors: Yaser S. Kishawi, Sadi R. Ali

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Part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely covers the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is finding non-conventional water resource from treated wastewater to cover agricultural requirements and serve the population. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line and infiltration basins-IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme–RRS– to capture the spreading plume). Currently, only phase A is functioning. Nearly 23 Mm3 of partially treated wastewater were infiltrated into the aquifer. Phase B and phase C witnessed many delays and this forced a reassessment of the RRS original design. An Environmental Management Plan was conducted from Jul 2013 to Jun 2014 on 13 existing monitoring wells surrounding the project location. This is to measure the efficiency of the SAT system and the spread of the contamination plume with relation to the efficiency of the proposed RRS. Along with the proposed location of the 27 recovery wells as part of the proposed RRS. The results of monitored wells were assessed compared with PWA baseline data. This was put into a groundwater model to simulate the plume to propose the best suitable solution to the delays. The redesign mainly manipulated the pumping rate of wells, proposed locations and functioning schedules (including wells groupings). The proposed simulations were examined using visual MODFLOW V4.2 to simulate the results. The results of monitored wells were assessed based on the location of the monitoring wells related to the proposed recovery wells locations (200m, 500m, and 750m away from the IBs). Near the 500m line (the first row of proposed recovery wells), an increase of nitrate (from 30 to 70mg/L) compare to a decrease in Chloride (1500 to below 900mg/L) was found during the monitoring period which indicated an expansion of plume to this distance. On this rate with the required time to construct the recovery scheme, keeping the original design the RRS will fail to capture the plume. Based on that many simulations were conducted leading into three main scenarios. The scenarios manipulated the starting dates, the pumping rate and the locations of recovery wells. A simulation of plume expansion and path-lines were extracted from the model monitoring how to prevent the expansion towards the nearby municipal wells. It was concluded that the location is the most important factor in determining the RRS efficiency. Scenario III was adopted and showed effective results even with a reduced pumping rates. This scenario proposed adding two additional recovery wells in a location beyond the 750m line to compensate the delays and effectively capture the plume. A continuous monitoring program for current and future monitoring wells should be in place to support the proposed scenario and ensure maximum protection.

Keywords: soil aquifer treatment, recovery reuse scheme, infiltration basins, North Gaza

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Authors: Amandeep Kaur

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Farming is one of the most influential traditions which started around 10000 BC and has revolutionized human civilization. It is believed that farming originated at a separate location. Thus it has a great impact on local culture, which in turn gave rise to diversified farming practices. Farming activities are influenced by the culture of a particular region or community as local people have their own knowledge and belief system about soil and crops. With the inception of the Green Revolution, 'a high tech machinery model' in Punjab, various traditional farming methods and techniques changed. The present research concentrates on the local knowledge of farmers and local farming systems from an anthropological perspective. In view of the prevailing agrarian crisis in Punjab, this research is focused on farmer’s experiences and their perception regarding farming practices. Thus an attempt has to be made to focus on the local knowledge, perception, and experience of farmers for eco-friendly and sustainable agricultural development. Farmers voices are used to understand the relationship between farming practices and socio-cultural life of farmers in Faridkot district, Punjab. The research aims to comprehend the nature of changes taking place in the socio-cultural life of people with the development of capitalism and agricultural modernization. The study is based on qualitative methods of ethnography in Sarawan village of Faridkot District. Inferences drawn from in-depth case studies collected from 60 agricultural households lead to the concept of the process of diffusion, innovation, and adoption of farming technology, a variety of crops and the dissemination of agricultural skills regarding various cultural farming practices. The data is based on random sampling; the respondents were both males and females above the age of 18 years to attain a holistic understanding across the generations. A Quasi-participant observation related to lifestyle, the standard of living, and various farming practices performed by them were done. Narratives derived from the fieldwork depicts that farmers usually oppose the restrictions imposed by the government on certain farming practices, especially ban on stubble burning. This paper presents the narratives of farmers regarding the dissemination of awareness about the use of new varieties of seeds, technology, fertilizers, pesticides, etc. The study reveals that farming systems have developed in ways reflecting the activities and choices of farmers influenced by environmental, socio-cultural, economic, and political situations. Modern farming practices have forced small farmers into debt as farmers feel pride in buying new machinery. It has also led to the loss of work culture and excessive use of drugs among youngsters. Even laborers did not want to work on the land with cultivating farmers primarily for social and political reasons. Due to lack of proper marketing of crops, there is a continuum of the wheat-rice cycle instead of crop diversification in Punjab. Change in the farming system also affects the social structure of society. Agricultural modernization has commercialized the socio-cultural relations in Punjab and is slowly urbanizing the rural landscape revolutionizing the traditional social relations to capitalistic relations.

Keywords: agricultural modernization, capitalism, farming practices, narratives

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: Tarek Abdoun, Waleed Elsekelly

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Introduction: Liquefaction of soils during earthquakes can have significant consequences on the stability of structures and infrastructure. This study focuses on comparing two liquefaction case histories in California, namely the response of the Wildlife site in the Imperial Valley to the 2010 El-Mayor Cucapah earthquake (Mw = 7.2, amax = 0.15g) and the response of the Treasure Island Fire Station (F.S.) site in the San Francisco Bay area to the 1989 Loma Prieta Earthquake (Mw = 6.9, amax = 0.16g). Both case histories involve liquefiable layers of silty sand with non-plastic fines, similar shear wave velocities, low CPT cone penetration resistances, and groundwater tables at similar depths. The liquefaction charts based on shear wave velocity field predict liquefaction at both sites. However, a significant difference arises in their pore pressure responses during the earthquakes. The Wildlife site did not experience liquefaction, as evidenced by piezometer data, while the Treasure Island F.S. site did liquefy during the shaking. Objective: The primary objective of this study is to investigate and understand the reason for the contrasting pore pressure responses observed at the Wildlife site and the Treasure Island F.S. site despite their similar geological characteristics and predicted liquefaction potential. By conducting a detailed analysis of similarities and differences between the two case histories, the objective is to identify the factors that contributed to the higher liquefaction resistance exhibited by the Wildlife site. Methodology: To achieve this objective, the geological and seismic data available for both sites were gathered and analyzed. Then their soil profiles, seismic characteristics, and liquefaction potential as predicted by shear wave velocity-based liquefaction charts were analyzed. Furthermore, the seismic histories of both regions were examined. The number of previous earthquakes capable of generating significant excess pore pressures for each critical layer was assessed. This analysis involved estimating the total seismic activity that the Wildlife and Treasure Island F.S. critical layers experienced over time. In addition to historical data, centrifuge and large-scale experiments were conducted to explore the impact of prior seismic activity on liquefaction resistance. These findings served as supporting evidence for the investigation. Conclusions: The higher liquefaction resistance observed at the Wildlife site and other sites in the Imperial Valley can be attributed to preshaking by previous earthquakes. The Wildlife critical layer was subjected to a substantially greater number of seismic events capable of generating significant excess pore pressures over time compared to the Treasure Island F.S. layer. This crucial disparity arises from the difference in seismic activity between the two regions in the past century. In conclusion, this research sheds light on the complex interplay between geological characteristics, seismic history, and liquefaction behavior. It emphasizes the significant impact of past seismic activity on liquefaction resistance and can provide valuable insights for evaluating the stability of sandy sites in other seismic regions.

Keywords: liquefaction, case histories, centrifuge, preshaking

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Authors: Eva Šmelová, Alena Berčíková

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The issue of school maturity and readiness of a child for a successful start of compulsory education is one of the long-term monitored areas, especially in the context of education and psychology. In the context of the curricular reform in the Czech Republic, the issue has recently gained importance. Analyses of research in this area suggest a lack of a broader overview of indicators informing about the current level of children’s school maturity and school readiness. Instead, various studies address partial issues. Between 2009 and 2013 a research study was performed at the Faculty of Education, Palacký University Olomouc (Czech Republic) focusing on children’s maturity and readiness for compulsory education. In this study, social skills were of marginal interest; the main focus was on the mental area. This previous research is smoothly linked with the present study, the objective of which is to identify the level of school maturity and school readiness in selected characteristics of social skills as part of the adaptation process after enrolment in compulsory education. In this context, the following research question has been formulated: During the process of adaptation to the school environment, which social skills are weakened? The method applied was observation, for the purposes of which the authors developed a research tool – record sheet with 11 items – social skills that a child should have by the end of preschool education. The items were assessed by first-grade teachers at the beginning of the school year. The degree of achievement and intensity of the skills were assessed for each child using an assessment scale. In the research, the authors monitored a total of three independent variables (gender, postponement of school attendance, participation in inclusive education). The effect of these independent variables was monitored using 11 dependent variables. These variables are represented by the results achieved in selected social skills. Statistical data processing was assisted by the Computer Centre of Palacký University Olomouc. Statistical calculations were performed using SPSS v. 12.0 for Windows and STATISTICA: StatSoft STATISTICA CR, Cz (software system for data analysis). The research sample comprised 115 children. In their paper, the authors present the results of the research and at the same time point to possible areas of further investigation. They also highlight possible risks associated with weakened social skills.

Keywords: compulsory education, curricular reform, educational diagnostics, pupil, school curriculum, school maturity, school readiness, social skills

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Authors: C. Brecher, M. Fey, F. Du Bois-Reymond, S. Neus

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Additive manufacturing has emerged into a fast-growing section within the manufacturing technologies. Established machine tool manufacturers, such as DMG MORI, recently presented machine tools combining milling and laser welding. By this, machine tools can realize a higher degree of flexibility and a shorter production time. Still there are challenges that have to be accounted for in terms of maintaining the necessary machining accuracy - especially due to thermal effects arising through the use of high power laser processing units. To study the thermal behavior of laser-integrated machine tools, it is essential to analyze and simulate the thermal behavior of machine components, individual and assembled. This information will help to design a geometrically stable machine tool under the influence of high power laser processes. This paper presents an approach to decrease the loss of machining precision due to thermal impacts. Real effects of laser machining processes are considered and thus enable an optimized design of the machine tool, respective its components, in the early design phase. Core element of this approach is a matched FEM model considering all relevant variables arising, e.g. laser power, angle of laser beam, reflective coefficients and heat transfer coefficient. Hence, a systematic approach to obtain this matched FEM model is essential. Indicating the thermal behavior of structural components as well as predicting the laser beam path, to determine the relevant beam intensity on the structural components, there are the two constituent aspects of the method. To match the model both aspects of the method have to be combined and verified empirically. In this context, an essential machine component of a five axis machine tool, the turn-swivel table, serves as the demonstration object for the verification process. Therefore, a turn-swivel table test bench as well as an experimental set-up to measure the beam propagation were developed and are described in the paper. In addition to the empirical investigation, a simulative approach of the described types of experimental examination is presented. Concluding, it is shown that the method and a good understanding of the two core aspects, the thermo-elastic machine behavior and the laser beam path, as well as their combination helps designers to minimize the loss of precision in the early stages of the design phase.

Keywords: additive manufacturing, laser beam machining, machine tool, thermal effects

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Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: Paulo Sérgio Ribeiro de Araújo Bogas

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Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

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Authors: Sana Rezig, Yosr Ben Mlik, Mounir Jaouadi, Foued Khoffi, Slah Msahli, Bernard Durand

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Increasing interest in environmental concerns, natural fibers are once again being considered as reinforcements for polymer composites. The main objective of this study is to explore another natural resource, Typha fiber; which is renewable without production cost and available abundantly in nature. The aim of this study was to study the flexural properties of composite resin with and without reinforcing Typha leaf and stem fibers. The specimens were made by the hand-lay-up process using polyester matrix. In our work, we focused on the effect of various treatment conditions (sea water, alkali treatment and a combination of the two treatments), as a surface modifier, on the flexural properties of the Typha fibers reinforced polyester composites. Moreover, weight ratio of Typha leaf or stem fibers was investigated. Besides, both fibers from leaf and stem of Typha plant were used to evaluate the reinforcing effect. Another parameter, which is reinforcement structure, was investigated. In fact, a first composite was made with air-laid nonwoven structure of fibers. A second composite was with a mixture of fibers and resin for each kind of treatment. Results show that alkali treatment and combined process provided better mechanical properties of composites in comparison with fiber treated by sea water. The fiber weight ratio influenced the flexural properties of composites. Indeed, a maximum value of flexural strength of 69.8 and 62,32 MPa with flexural modulus of 6.16 and 6.34 GPawas observed respectively for composite reinforced with leaf and stem fibers for 12.6 % fiber weight ratio. For the different treatments carried out, the treatment using caustic soda, whether alone or after retting seawater, show the best results because it improves adhesion between the polyester matrix and the fibers of reinforcement. SEM photographs were made to ascertain the effects of the surface treatment of the fibers. By varying the structure of the fibers of Typha, the reinforcement used in bulk shows more effective results as that used in the non-woven structure. In addition, flexural strength rises with about (65.32 %) in the case of composite reinforced with a mixture of 12.6% leaf fibers and (27.45 %) in the case of a composite reinforced with a nonwoven structure of 12.6 % of leaf fibers. Thus, to better evaluate the effect of the fiber origin, the reinforcing structure, the processing performed and the reinforcement factor on the performance of composite materials, a statistical study was performed using Minitab. Thus, ANOVA was used, and the patterns of the main effects of these parameters and interaction between them were established. Statistical analysis, the fiber treatment and reinforcement structure seem to be the most significant parameters.

Keywords: flexural properties, fiber treatment, structure and weight ratio, SEM photographs, Typha leaf and stem fibers

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Authors: Julien G. Chenet, Mario A. Hernandez, U. Leonardo Rodriguez

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The tropical areas are places where there is scarcity of access to potable water and where renewable energies need further development. They also display high undernourishment levels, even though they are one of the resources-richest areas in the world. In these areas, it is common to count on great extension of soils, high solar radiation and raw water from rain, groundwater, surface water or even saltwater. Even though resources are available, access to them is limited, and the low-density habitat makes central solutions expensive and investments not worthy. In response to this lack of investment, rural inhabitants use fossil fuels and timber as an energy source and import agrochemical for soils fertilization, which increase GHG emissions. The OASIS project brings an answer to this situation. It supplies renewable energy, potable water and organic food. The first step is the determination of the needs of the communities in terms of energy, water quantity and quality, food requirements and soil characteristics. Second step is the determination of the available resources, such as solar energy, raw water and organic residues on site. The pilot OASIS project is located in the Vichada department, Colombia, and ensures the sustainable use of natural resources to meet the community needs. The department has roughly 70% of indigenous people. They live in a very scattered landscape, with no access to clean water and energy. They use polluted surface water for direct consumption and diesel for energy purposes. OASIS pilot will ensure basic needs for a 400-students education center. In this case, OASIS will provide 20 kW of solar energy potential and 40 liters per student per day. Water will be treated form groundwater, with two qualities. A conventional one with chlorine, and as the indigenous people are not used to chlorine for direct consumption, second train is with reverse osmosis to bring conservable safe water without taste. OASIS offers a solution to supply basic needs, shifting from fossil fuels, timber, to a no-GHG-emission solution. This solution is part of the mitigation strategy against Climate Change for the communities in low-density areas of the tropics. OASIS is a learning center to teach how to convert natural resources into utilizable ones. It is also a meeting point for the community with high pedagogic impact that promotes the efficient and sustainable use of resources. OASIS system is adaptable to any tropical area and competes technically and economically with any conventional solution, that needs transport of energy, treated water and food. It is a fully automatic, replicable and sustainable solution to sort out the issue of access to basic needs in rural areas. OASIS is also a solution to undernourishment, ensuring a responsible use of resources, to prevent long-term pollution of soils and groundwater. It promotes the closure of the nutrient cycle, and the optimal use of the land whilst ensuring food security in depressed low-density regions of the tropics. OASIS is under optimization to Vichada conditions, and will be available to any other tropical area in the following months.

Keywords: climate change adaptation and mitigation, rural development, sustainable access to clean and renewable resources, social inclusion

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Authors: Tahamina Begum, Wan Nor Azlen Wan Mohamad, Faruque Reza, Wan Rosilawati Wan Rosli

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To assess auditory perception and cognitive function during pregnancy is necessary as the pregnant women need extra effort for attention mainly for their executive function to maintain their quality of life. This study aimed to investigate neural correlates of cognitive and behavioral processing during mid trimester pregnancy. Event-Related Potentials (ERPs) were studied by using 128-sensor net and PAS or COWA (controlled Oral Word Association), WCST (Wisconsin Card Sorting Test), RAVLTIM (Rey Auditory Verbal and Learning Test: immediate or interference recall, delayed recall (RAVLT DR) and total score (RAVLT TS) were tested for neuropsychology assessment. In total 18 subjects were recruited (n= 9 in each group; control and pregnant group). All participants of the pregnant group were within 16-27 (mid trimester) weeks gestation. Age and education matched control healthy subjects were recruited in the control group. Participants were given a standardized test of auditory cognitive function as auditory oddball paradigm during ERP study. In this paradigm, two different auditory stimuli (standard and target stimuli) were used where subjects counted silently only target stimuli with giving attention by ignoring standard stimuli. Mean differences between target and standard stimuli were compared across groups. N100 (auditory sensory ERP component) and P300 (auditory cognitive ERP component) were recorded at T3, T4, T5, T6, Cz and Pz electrode sites. An equal number of electrodes showed non-significantly shorter amplitude of N100 component (except significantly shorter at T3, P= 0.05) and non-significant longer latencies (except significantly longer latency at T5, P= 0.008) of N100 component in pregnant group comparing control. In case of P300 component, maximum electrode sites showed non-significantly higher amplitudes and equal number of sites showed non-significant shorter latencies in pregnant group comparing control. Neuropsychology results revealed the non-significant higher score of PAS, lower score of WCST, lower score of RAVLTIM and RAVLTDR in pregnant group comparing control. The results of N100 component and RAVLT scores concluded that auditory perception is mildly impaired and P300 component proved very mild cognitive dysfunction with good executive functions in second trimester of pregnancy.

Keywords: auditory perception, pregnancy, stimuli, trimester

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Authors: Sarah A. Alotaibi, Mohammed A. Almutairi, Abdullah A. Alsayari, Adibah M. Almutairi, Somaiah K. Almubayedh

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Concerns over the presence of acrylamide in food date back to 2002, when Swedish scientists stated that, in carbohydrate-rich foods, amounts of acrylamide were formed when cooked at high temperatures. Similar findings were reported by other researchers which, consequently, caused major international efforts to investigate dietary exposure and the subsequent health complications in order to properly manage this issue. Due to this issue, in this work, we aim to determine the acrylamide level in different foods (coffee, potato chips, biscuits, and baby food) commonly consumed by the Saudi population. In a total of forty-three samples, acrylamide was detected in twenty-three samples at levels of 12.3 to 2850 µg/kg. In reference to the food groups, the highest concentration of acrylamide was found in coffee samples (<12.3-2850 μg/kg), followed by potato chips (655-1310 μg/kg), then biscuits (23.5-449 μg/kg), whereas the lowest acrylamide level was observed in baby food (<14.75 – 126 μg/kg). Most coffee, biscuits and potato chips products contain high amount of acrylamide content and also the most commonly consumed product. Saudi adults had a mean exposure of acrylamide for coffee, potato, biscuit, and cereal (0.07439, 0.04794, 0.01125, 0.003371 µg/kg-b.w/day), respectively. On the other hand, exposure to acrylamide in Saudi infants and children to the same types of food was (0.1701, 0.1096, 0.02572, 0.00771 µg/kg-b.w/day), respectively. Most groups have a percentile that exceeds the tolerable daily intake (TDI) cancer value (2.6 µg/kg-b.w/day). Overall, the MOE results show that the Saudi population is at high risk of acrylamide-related disease in all food types, and there is a chance of cancer risk in all age groups (all values ˂10,000). Furthermore, it was found that in non-cancer risks, the acrylamide in all tested foods was within the safe limit (˃125), except for potato chips, in which there is a risk for diseases in the population. With potato and coffee as raw materials, additional studies were conducted to assess different factors, including temperature, cocking time, and additives affecting the acrylamide formation in fried potato and roasted coffee, by systematically varying processing temperatures and time values, a mitigation of acrylamide content was achieved when lowering the temperature and decreasing the cooking time. Furthermore, it was shown that the combination of the addition of chitosan and NaCl had a large impact on the formation.

Keywords: risk assessment, dietary exposure, MOA, acrylamide, hazard

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Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

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It has been over 200 years since margarine was discovered and manufactured using liquid oil, liquified hardstock oils and other oil phase & aqueous phase ingredients. Henry W. Bradley first used vegetable oils in liquid state and around 1871, since then; spreads have been traditionally manufactured using liquified oils. The main objective of this study was to develop a process method to produce spreads using spray dried hardstock fat powders as a structing fats in place of current liquid structuring fats. A high shear mixing system was used to condition the fat phase and the aqueous phase was prepared separately. Using a single scraped surface heat exchanger and pin stirrer, margarine was produced. The process method was developed for to produce spreads with 40%, 50% and 60% fat . The developed method was divided into three steps. In the first step, fat powders were conditioned by melting and dissolving them into liquid oils. The liquified portion of the oils were at 65 °C, whilst the spray dried fat powder was at 25 °C. The two were mixed using a mixing vessel at 900 rpm for 4 minutes. The rest of the ingredients i.e., lecithin, colorant, vitamins & flavours were added at ambient conditions to complete the fat/ oil phase. The water phase was prepared separately by mixing salt, water, preservative, acidifier in the mixing tank. Milk was also separately prepared by pasteurizing it at 79°C prior to feeding it into the aqueous phase. All the water phase contents were chilled to 8 °C. The oil phase and water phase were mixed in a tank, then fed into a single scraped surface heat exchanger. After the scraped surface heat exchanger, the emulsion was fed in a pin stirrer to work the formed crystals and produce margarine. The margarine produced using the developed process had fat levels of 40%, 50% and 60%. The margarine passed all the qualitative, stability, and taste assessments. The scores were 6/10, 7/10 & 7.5/10 for the 40%, 50% & 60% fat spreads, respectively. The success of the trials brought about differentiated knowledge on how to manufacture spreads using non micronized spray dried fat powders as hardstock. Manufacturers do not need to store structuring fats at 80-90°C and even high in winter, instead, they can adapt their processes to use fat powders which need to be stored at 25 °C. The developed process method used one scrape surface heat exchanger instead of the four to five currently used in votator based plants. The use of a single scraped surface heat exchanger translated to about 61% energy savings i.e., 23 kW per ton of product. Furthermore, it was found that the energy saved by implementing separate pasteurization was calculated to be 6.5 kW per ton of product produced.

Keywords: margarine emulsion, votator technology, margarine processing, scraped sur, fat powders

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Authors: Priyanka Kumari Gupta, Punya Prasanna Paltani, Shrivishal Tripathi

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This paper proposes a nonlinear photonic crystal ring resonator-based all-optical 2 × 2 switch. The nonlinear Kerr effect is used to evaluate the essential 2 x 2 components of the photonic crystal-based optical switch, including the bar and cross states. The photonic crystal comprises a two-dimensional square lattice of dielectric rods in an air background. In the background air, two different dielectric materials are used for this comparison study separately. Initially with chalcogenide glass rods, then with GaAs rods. For both materials, the operating wavelength, bandgap diagram, operating power intensities, and performance parameters, such as the extinction ratio, insertion loss, and cross-talk of an optical switch, have also been estimated using the plane wave expansion and the finite-difference time-domain method. The chalcogenide glass material (Ag20As32Se48) has a high refractive index of 3.1 which is highly suitable for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 9.1 x 10-17 m2/W. The resonance wavelength is at 1552 nm, with the operating power intensities at the cross-state and bar state around 60 W/μm2 and 690 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are 17.19 dB, 0.051 dB, and -17.14 dB, and the bar state, the values are 11.32 dB, 0.025 dB, and -11.35 dB respectively. The gallium arsenide (GaAs) dielectric material has a high refractive index of 3.4, a direct bandgap semiconductor material highly preferred nowadays for switching operations. This dielectric material is immersed in an air background with a nonlinear Kerr coefficient of 3.1 x 10-16 m2/W. The resonance wavelength is at 1558 nm, with the operating power intensities at the cross-state and bar state around 110 W/μm2 and 200 W/μm2. The extinction ratio, insertion loss, and cross-talk value for the chalcogenide glass at the cross-state are found to be 3.36.19 dB, 2.436 dB, and -5.8 dB, and for the bar state, the values are 15.60 dB, 0.985 dB, and -16.59 dB respectively. This paper proposes an all-optical 2 × 2 switch based on a nonlinear photonic crystal using a ring resonator. The two-dimensional photonic crystal comprises a square lattice of dielectric rods in an air background. The resonance wavelength is in the range of photonic bandgap. Later, another widely used material, GaAs, is also considered, and its performance is compared with the chalcogenide glass. Our presented structure can be potentially applicable in optical integration circuits and information processing.

Keywords: photonic crystal, FDTD, ring resonator, optical switch

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Authors: Rakesh Tiwary, D. M. Diwakar, Sandhya Mahapatro

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Agro-forestry offers huge opportunities for diversification of agriculture in middle Gangetic Basin of India, particularly in the state of Bihar as the region is identified with traditional & stagnant agriculture, low productivity, high population pressure, rural poverty and lack of agro- industrial development. The region is endowed with favourable agro-climatic, soil & drainage conditions; interestingly, there has been an age old tradition of agro-forestry in the state. However, due to demographic pressures, declining land holdings and other socio- economic factors, agro forestry practices have declined in recent decades. The government of Bihar has initiated a special program for expansion of agro-forestry based on modern practices with an aim to raise income level of farmers, make available raw material for wood based industries and increase green cover in the state. The Agro-forestry Schemes – Poplar & Other Species are the key components of the program being implemented by Department of Environment & Forest, Govt. of Bihar. The paper is based on fieldwork based evaluation study on experiences of implementation of the agro-forestry schemes. Understanding adoption patterns, identification of key motives for practising agro-forestry, experiences of farmers well analysing the barriers in expansion constituted the major themes of the research study. This paper is based on primary as well as secondary data. The primary data consists of beneficiary household survey, Focus Group Discussions among beneficiary communities, dialogue and multi stakeholder meetings and field visit to the sites. The secondary data information was collected and analysed from official records, policy documents and reports. Primary data was collected from about 500 beneficiary households of Muzaffarpur & Saharsa- two populous, large and agriculture dominated districts of middle Gangetic basin of North Bihar. Survey also covers 100 households of non-beneficiaries. Probability Proportionate to Size method was used to determine the number of samples to be covered in different blocks of two districts. Qualitative tools were also implemented to have better insights about key research questions. Present paper discusses socio-economic background of farmers practising agro-forestry; the adoption patterns of agro- forestry (choice of plants, methods of plantation and others); and motivation behind adoption of agro-forestry and the comparative benefits of agro-forestry (vis-a-vis traditional agriculture). Experience of beneficiary farmers with agro-forestry based on government programs & promotional campaigns (in terms of awareness, ease of access, knowhow and others) have been covered in the paper. Different aspects of survival of plants have been closely examined. Non beneficiaries but potential adopters were also interviewed to understand barriers of adoption of agro- forestry. Paper provides policy recommendations and interventions required for effective expansion of the agro- forestry and realisation of its future prospects for agricultural diversification in the region.

Keywords: agro-forestry adoption patterns, farmers’ motivations & experiences, Indian middle Gangetic plains, strategies for expansion

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Authors: Belbaly Nassim

Abstract:

Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

Procedia PDF Downloads 174

Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 151

Authors: Sangho Park, Mansoo Kim, Kyujung Chae, Junhyuk Yang

Abstract:

The International Maritime Organization (IMO) recognized the problem of invasive species invasion and adopted the "International Convention for the Control and Management of Ships' Ballast Water and Sediments" in 2004, which came into force on September 8, 2017. In 2011, the IMO approved the "Guidelines for the Control and Management of Ships' Biofouling to Minimize the Transfer of Invasive Aquatic Species" to minimize the movement of invasive species by hull-attached organisms and required ships to manage the organisms attached to their hulls. Invasive species enter new environments through ships' ballast water and hull attachment. However, several obstacles to implementing these guidelines have been identified, including a lack of underwater cleaning equipment, regulations on underwater cleaning activities in ports, and difficulty accessing crevices in underwater areas. The shipping industry, which is the party responsible for understanding these guidelines, wants to implement them for fuel cost savings resulting from the removal of organisms attached to the hull, but they anticipate significant difficulties in implementing the guidelines due to the obstacles mentioned above. Robots or people remove the organisms attached to the hull underwater, and the resulting wastewater includes various species of organisms and particles of paint and other pollutants. Currently, there is no technology available to sterilize the organisms in the wastewater or stabilize the heavy metals in the paint particles. In this study, we aim to analyze the characteristics of the wastewater generated from the removal of hull-attached organisms and select the optimal treatment technology. The organisms in the wastewater generated from the removal of the attached organisms meet the biological treatment standard (D-2) using the sterilization technology applied in the ships' ballast water treatment system. The heavy metals and other pollutants in the paint particles generated during removal are treated using stabilization technologies such as thermal decomposition. The wastewater generated is treated using a two-step process: 1) development of sterilization technology through pretreatment filtration equipment and electrolytic sterilization treatment and 2) development of technology for removing particle pollutants such as heavy metals and dissolved inorganic substances. Through this study, we will develop a biological removal technology and an environmentally friendly processing system for the waste generated after removal that meets the requirements of the government and the shipping industry and lays the groundwork for future treatment standards.

Keywords: biofouling, ballast water treatment system, filtration, sterilization, wastewater

Procedia PDF Downloads 111

Authors: Krishna Nand, Mohammad Taufik

Abstract:

Fused Filament Fabrication (FFF) is one of the most popular additive manufacturing (AM) technology. In FFF technology, a wire form material (filament) is fed inside a heated chamber, where it gets converted into semi-solid form and extruded out of a nozzle to be deposited on the build platform to fabricate the part. FFF technology is expanding and covering the market at a very rapid rate, so the need of raw materials for 3D printing is also increasing. The cost of 3D printing is directly affected by filament cost. To make 3D printing more economic, a compact and portable filament/wire extrusion system is needed. Wire extrusion systems to extrude ordinary wire/filament made of a single material are available in the market. However, extrusion system to make a composite wire/filament are not available. Hence, in this study, initial efforts have been made to develop a table-top composite wire extruder. The developed system is consisted of mechanical parts, electronics parts, and a control system. A multiple channel hopper, extrusion screw, melting chamber and nozzle, cooling zone, and spool winder are some mechanical parts. While motors, heater, temperature sensor, cooling fans are some electronics parts, which are used to develop this system. A control board has been used to control the various process parameters like – temperature and speed of motors. For the production of composite wire/filament, two different materials could be fed through two channels of hopper, which will be mixed and carried to the heated zone by extrusion screw. The extrusion screw is rotated by a motor, and the speed of this motor will be controlled by the controller as per the requirement of material extrusion rate. In the heated zone, the material will melt with the help of a heating element and extruded out of the nozzle in the form of wire. The developed system occupies less floor space due to the vertical orientation of its heating chamber. It is capable to extrude ordinary filament as well as composite filament, which are compatible with 3D printers available in the market. Further, the developed system could be employed in the research and development of materials, processing, and characterization for 3D printer. The developed system presented in this study could be a better choice for hobbyists and researchers dealing with the fused filament fabrication process to reduce the 3D printing cost significantly by recycling the waste material into 3D printer feed material. Further, it could also be explored as a better alternative for filament production at the commercial level.

Keywords: additive manufacturing, 3D Printing, filament extrusion, pellet extrusion

Procedia PDF Downloads 169