Search results for: data storage

Authors: M. Bortolini, E. Ferrari, F. G. Galizia, C. Mora

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In the last decades, an increasing set of companies adopted lean philosophy to improve their productivity and efficiency promoting the so-called continuous improvement concept, reducing waste of time and cutting off no-value added activities. In parallel, increasing attention rises toward green practice and management through the spread of the green supply chain pattern, to minimise landfilled waste, drained wastewater and pollutant emissions. Starting from a review on contributions deepening lean and green principles applied to supply chain management, the most relevant drivers to measure the performance of industrial processes are pointed out. Specific attention is paid on the role of cost because it is of key importance and it crosses both lean and green principles. This analysis leads to figure out an original reference framework for integrating lean and green principles in designing and managing supply chains. The proposed framework supports the application, to the whole value chain or to parts of it, e.g. distribution network, assembly system, job-shop, storage system etc., of the lean-green integrated perspective. Evidences show that the combination of the lean and green practices lead to great results, higher than the sum of the performances from their separate application. Lean thinking has beneficial effects on green practices and, at the same time, methods allowing environmental savings generate positive effects on time reduction and process quality increase.

Keywords: environmental sustainability, green supply chain, integrated framework, lean thinking, supply chain management

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Authors: Gachara Grace, Kebira Anthony, Harvey Jagger, Wainaina James

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Aflatoxin contamination of maize in Africa poses a major threat to food security and the health of many African people. In Kenya, aflatoxin contamination of maize is high due to the environmental, agricultural and socio-economic factors. Many studies have been conducted to understand the scope of the problem, especially at pre-harvest level. This research was carried out to gather scientific information on the fungi population, diversity and aflatoxin level during the post-harvest period. The study was conducted in three geographical locations of; Kitui, Kitale and Nakuru. Samples were collected from storage structures of farmers and transported to the Biosciences eastern and central Africa (BecA), International Livestock and Research Institute (ILRI) hub laboratories. Mycoflora was recovered using the direct plating method. A total of five fungal genera (Aspergillus, Penicillium, Fusarium, Rhizopus and Bssyochlamys spp.) were isolated from the stored maize samples. The most common fungal species that were isolated from the three study sites included A. flavus at 82.03% followed by A.niger and F.solani at 49% and 26% respectively. The aflatoxin producing fungi A. flavus was recovered in 82.03% of the samples. Aflatoxin levels were analysed on both the maize samples and in vitro. Most of the A. flavus isolates recorded a high level of aflatoxin when they were analysed for presence of aflatoxin B1 using ELISA. In Kitui, all the samples (100%) had aflatoxin levels above 10ppb with a total aflatoxin mean of 219.2ppb. In Kitale, only 3 samples (n=39) had their aflatoxin levels less than 10ppb while in Nakuru, the total aflatoxin mean level of this region was 239.7ppb. When individual samples were analysed using Vicam fluorometer method, aflatoxin analysis revealed that most of the samples (58.4%) had been contaminated. The means were significantly different (p=0.00<0.05) in all the three locations. Genetic relationships of A. flavus isolates were determined using 13 Simple Sequence Repeats (SSRs) markers. The results were used to generate a phylogenetic tree using DARwin5 software program. A total of 5 distinct clusters were revealed among the genotypes. The isolates appeared to cluster separately according to the geographical locations. Principal Coordinates Analysis (PCoA) of the genetic distances among the 91 A. flavus isolates explained over 50.3% of the total variation when two coordinates were used to cluster the isolates. Analysis of Molecular Variance (AMOVA) showed a high variation of 87% within populations and 13% among populations. This research has shown that A. flavus is the main fungal species infecting maize grains in Kenya. The influence of aflatoxins on human populations in Kenya demonstrates a clear need for tools to manage contamination of locally produced maize. Food basket surveys for aflatoxin contamination should be conducted on a regular basis. This would assist in obtaining reliable data on aflatoxin incidence in different food crops. This would go a long way in defining control strategies for this menace.

Keywords: aflatoxin, Aspergillus flavus, genotyping, Kenya

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Authors: Huda Aljabi

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The existence of heavy metals similar to cadmium, arsenic, lead and mercury in the drinking water be able to be a threat to public health. The amount of the substances of these heavy metals in drinking water has expected importance. The National Primary Drinking Water Regulations have set limits for the concentrations of these elements in drinking water because of their toxicity. Furthermore, bromate shaped during the disinfection of drinking water by Ozonation can also be a health hazard. The Paper proposed here will concentrate on the compilation of all available data and information on the presence of trace metals and bromate in the drinking water at residential houses distributed over different areas in Kuwait. New data will also be collected through a sampling of drinking water at some of the residential houses present in different areas of Kuwait and their analysis for the contents of trace metals and bromate. The collected data will be presented on maps showing the distribution of these metals and bromate in the drinking water of Kuwait. Correlation among different chemical parameters will also be investigated using the GRAPHER software. This will help both the Ministry of Electricity and Water (MEW) and the Ministry of Health (MOH) in taking corrective measures and also in planning the infrastructure activities for the future.

Keywords: bromate, ozonation, GIS, heavy metals

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Authors: Hao Cheng, Yingzhou Ni, Amr M. Bakry, Li Liang

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Functional foods containing bioactive nutrients offer benefits beyond basic nutrition and hence the possibility of delaying and preventing chronic diseases. However, many bioactive nutrients degrade rapidly under food processing and storage conditions. Encapsulation can be used to overcome these limitations. Food proteins have been widely used as carrier materials for the preparation of nano/micro-particles because of their ability to form gels and emulsions and to interact with polysaccharides. The mechanisms of interaction between bioactive nutrients and proteins must be understood in order to develop protein-based lipid-free delivery systems. Beta-lactoglobulin, a small globular protein in milk whey, exhibits an affinity to a wide range of compounds. Alfa-tocopherol, resveratrol and folic acid were respectively bound to the central cavity, the outer surface near Trp19–Arg124 and the hydrophobic pocket in the groove between the alfa-helix and the beta-barrel of the protein. Beta-lactoglobulin could thus bind the three bioactive nutrients simultaneously to form protein-multi-ligand complexes. Beta-casein, an intrinsically unstructured but major milk protein, could also interact with resveratrol and folic acid to form complexes. These results suggest the potential to develop milk-protein-based complex carrier systems for encapsulation of multiple bioactive nutrients for functional food application and also pharmaceutical and medical uses.

Keywords: milk protein, bioactive nutrient, interaction, protection

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Authors: André Felipe Gimenez, Flávia Alessandra Ribeiro da Silva, Roberto Saverio Souza Costa

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Currently, the rural producer has been facing problems regarding environmental regularization, which is precisely why the CAR (Rural Environmental Registry) was created. CAR is an electronic registry for rural properties with the purpose of assimilating notions about legal reserve areas, permanent preservation areas, areas of limited use, stable areas, forests and remnants of native vegetation, and all rural properties in Brazil. . The objective of this work was to evaluate and compare altimetry and slope data from google Earth with a digital terrain model (MDT) generated by aerophotogrammetry, in three plots of a steep slope, for the purpose of declaration in the CAR (Rural Environmental Registry). The realization of this work is justified in these areas, in which rural landowners have doubts about the reliability of the use of the free software Google Earth to diagnose inclinations greater than 25 degrees, as recommended by federal law 12651/2012. Added to the fact that in the literature, there is a deficiency of this type of study for the purpose of declaration of the CAR. The results showed that when comparing the drone altimetry data with the Google Earth image data, in areas of high slope (above 40% slope), Google underestimated the real values of terrain slope. Thus, it is concluded that Google Earth is not reliable for diagnosing areas with an inclination greater than 25 degrees (46% declivity) for the purpose of declaration in the CAR, being essential to carry out the local topographic survey.

Keywords: MDT, drone, RPA, SiCar, photogrammetry

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Authors: Sudaporn Arundee

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The purposes of this research were to study in three areas: (1) to study political understanding and participating of the constitutional monarchy, (2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data. The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.

Keywords: political participation, constitutional monarchy, management and social sciences

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Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: Gabi N. Nehme

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Below-knee amputees commonly experience asymmetrical gait patterns. It is generally believed that ischemia is related to the formation of pressure sores due to uneven distribution of forces. Micro-vascular responses can reveal local malnutrition. Changes in local skin blood supply under various external loading conditions have been studied for a number of years. Radionuclide clearance, photo-plethysmography, trans-cutaneous oxygen tension along with other studies showed that the blood supply would be influenced by the epidermal forces, and the rate and the amount of blood supply would decrease with increased epidermal loads being shear forces or normal forces. Several cases of socket designs were investigated using Finite Element Model (FEM) and Design of Experiment (DOE) to increase flexibility and minimize the pressure at the limb/socket interface using ultra high molecular weight polyethylene (UHMWPE) and polyamide 6 (PA6) or Duraform. The pressure reliefs at designated areas where reducing thickness is involved are seen to be critical in determination of amputees’ comfort and are very important to clinical applications. Implementing a hole between the Patellar Tendon (PT) and Distal Tibia (DT) would decrease stiffness and increase prosthesis range of motion where flexibility is needed. In addition, displacement and prosthetic energy storage increased without compromising mechanical efficiency and prosthetic design integrity.

Keywords: patellar tendon, distal tibia, prosthetic socket relief areas, hole implementation

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Authors: Feten Chihi, Gabriella Varga

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The world's most prevalent waste management strategy is landfills. However, it grew more difficult due to a lack of acceptable waste sites. In order to develop larger landfills and extend their lifespan, the purpose of this article is to expand the capacity of the construction by varying the slope's inclination and to examine its effect on the safety factor. The capacity change with tilt is mathematically determined. Using a new probabilistic calculation method that takes into account the heterogeneity of waste layers, the safety factor for various slope angles is examined. To assess the effect of slope variation on the overall safety of landfills, over a hundred computations were performed for each angle. It has been shown that capacity increases significantly with increasing inclination. Passing from 1:3 to 2:3 slope angles and from 1:3 to 1:2 slope angles, the volume of garbage that can be deposited increases by 40 percent and 25 percent, respectively, of the initial volume. The results of the safety factor indicate that slopes of 1:3 and 1:2 are safe when the standard method (homogenous waste) is used for computation. Using the new approaches, a slope with an inclination of 2:3 can be deemed safe, despite the fact that the calculation does not account for the safety-enhancing effect of daily cover layers. Based on the study reported in this paper, the malty layered nonhomogeneous calculating technique better characterizes the safety factor. As it more closely resembles the actual state of landfills, the employed technique allows for more flexibility in design parameters. This work represents a substantial advance in limiting both safe and economical landfills.

Keywords: landfill, municipal solid waste, slope inclination, capacity, safety factor

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Authors: Hebberly Ahatlan

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The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, IT/OT convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: digitalization, IT/OT convergence, semantic interoperability, VPP, energy blockchain

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

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Authors: Mosaad Attia Elkasaby

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The crude oil contains paraffines, aromatics, and asphaltenes in addition to some organic impurities, with increasing demands to reduce the cost of crude oil production, the uses of a pour point depressant is mandatory to maintain good flow rate. The wax materials cause many problems during production, storage, and transport, especially at low temperature, as these waxes tend, at low temperatures, to precipitate on the wall lines, thus leads to the high viscosity of crude oil and impede the flow rate, which represents an additional burden for crude oil pumping system from the place of production to the refinery. There are many ways to solve this problem, including, but not limited to, heat the crude and the use of organic solvents. But one of the most important disadvantages of these methods is the high economic cost. The aim of this innovation is to manufacture some polymeric materials (polymers based on aniline) that are processed locally that can be used as a pour point depressant of crude oil. For the first time, polymer based on aniline is modified and used with a number of organic solvents and tested with solvent (Styrene). It was found that the polymer based on aniline, when modified, had full solubility in styrene, unlike other organic solvent that was used in the past, such as chloroform and toluene. We also used a new solvent (PONA) that is obtained from the process of hydrotreating and separation of straight run naphtha to dissolve polymer based on aniline as a pour point depressant of crude oil. This innovative include studies conducted on highly paraffinic crude oil (C.O.1 and C.O.2). On using concentration (2500 ppm) of polymer based on aniline, the pour point of crude oil has decreased from +33 to - 9°C in case of crude oil (C.O.1) and from + 42 to – 6°C in case crude oil (C.O.2) at the same concentration.

Keywords: PPD, aniline, paraffinic crude oils, polymers

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Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: Kassahun Tilahun

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Most of the studies available on adult psychological well-being have been centered on Western countries. However, psychological well-being does not have the same meaning across the world. The Euro-American and African conceptions and experiences of psychological well-being differ systematically. As a result, questions like, how do people living in developing African countries, like Ethiopia, report their psychological well-being; what would the context-specific prominent determinants of their psychological well-being be, needs a definitive answer. This study was, therefore, aimed at developing a new theory that would address these socio-cultural issues of psychological well-being. Consequently, data were obtained through interview and open ended questionnaire. A total of 438 adults, working in governmental and non-governmental organizations situated in Addis Ababa, participated in the study. Appropriate qualitative method of data analysis, i.e. thematic content analysis, was employed for analyzing the data. The thematic analysis involves a type of abductive analysis, driven both by theoretical interest and the nature of the data. Reliability and credibility issues were addressed appropriately. The finding identified five major categories of themes, which are viewed as essential in determining the conceptions and experiences of psychological well-being of Ethiopian adults. These were; socio-cultural harmony, social cohesion, security, competence and accomplishment, and the self. Detailed discussion on the rational for including these themes was made and appropriate positive psychology interventions were proposed. Researchers are also encouraged to expand this qualitative research and in turn develop a suitable instrument taping the psychological well-being of adults with different sociocultural orientations.

Keywords: sociocultural, psychological, well-being Ethiopia, adults

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Kefaya Qaddoum

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Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.

Keywords: tomato yield prediction, naive Bayes, redundancy, WSG

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Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

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Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi

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A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.

Keywords: posture correction, posture training, riding posture, riding simulator

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Authors: Esubalew Yehualaw Melaku

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In this study, two basic geophysical methods are applied for mapping the groundwater aquifer system in the Gode area along the Guder River, northeast of Hosanna town, near the western margin of the Central Main Ethiopian Rift. The main target of the study is to map the potential aquifer zone and investigate the groundwater potential for current and future development of the resource in the Gode area. The geophysical methods employed in this study include, Vertical Electrical Sounding (VES) and magnetic survey techniques. Electrical sounding was used to examine and map the depth to the potential aquifer zone of the groundwater and its distribution over the area. On the other hand, a magnetic survey was used to delineate contact between lithologic units and geological structures. The 2D magnetic modeling and the geoelectric sections are used for the identification of weak zones, which control the groundwater flow and storage system. The geophysical survey comprises of twelve VES readings collected by using a Schlumberger array along six profile lines and more than four hundred (400) magnetic readings at about 10m station intervals along four profiles and 20m along three random profiles. The study result revealed that the potential aquifer in the area is obtained at a depth range from 45m to 92m. This is the response of the highly weathered/ fractured ignimbrite and pumice layer with sandy soil, which is the main water-bearing horizon. Overall, in the neighborhood of four VES points, VES- 2, VES- 3, VES-10, and VES-11, shows good water-bearing zones in the study area.

Keywords: vertical electrical sounding, magnetic survey, aquifer, groundwater potential

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Sadaf Kalhori

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Introduction: Doxorubicin (DOX)-induced cardiotoxicity is widely known as the most severe complication of anthracycline-based chemotherapy in patients with cancer. It is unknown whether Deferiprone (DFP), could reduce the severity of DOX-induced cardiotoxicity by inhibiting free radical reactions. Thus, this study was performed to assess the protective effect of Deferiprone on DOX-induced cardiotoxicity in a rat model. Methods: The rats were divided into five groups. Group one was a control group. Group 2 was DOX (2 mg/kg/day, every other day for 12 days), and Group three to five which receiving DOX as in group 2 and DFP 75,100 and 150 mg/kg/day, for 19 days, respectively. DFP was starting 5 days prior to the first DOX injection and two days after the last DOX injection throughout the study. Electrocardiographic and hemodynamic studies, along with histopathological examination, were conducted. In addition, serum sample was taken and total cholesterol, Malone dialdehyde, triglyceride, albumin, AST, ALT, total protein, lactate dehydrogenase, total anti-oxidant and creatine kinase were assessed. Result: Our results showed the normal structure of endocardial, myocardial and pericardial in the control group. Pathologic data such as edema, hyperemia, bleeding, endocarditis, myocarditis and pericarditis, hyaline degeneration, cardiomyocyte necrosis, myofilament degeneration and nuclear chromatin changes were assessed in all groups. In the DOX group, all pathologic data was seen with mean grade of 2±1.25. In the DFP group with a dose of 75 and 100 mg, the mean grade was 1.41± 0.31 and 1±.23, respectively. In DFP group with a dose of 150, the pathologic data showed a milder change in comparison with other groups with e mean grade of 0.45 ±0.19. Most pathologic data in DFP groups showed significant changes in comparison with the DOX group (p < 0.001). Discussion: The results also showed that DFP treatment significantly improved DOX-induced heart damage, structural changes in the myocardium, and ventricular function. Our data confirm that DFP is protective against cardiovascular-related disorders induced by DOX. Clinical studies are needed to be involved to examine these findings in humans.

Keywords: cardiomyopathy, deferiprone, doxorubicin, rat

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Authors: M. E. Semenov, U. Zh. Mirzakimov, A. S. Stoporev, R. S. Pavelev, M. A. Varfolomeev

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Gas hydrates are host-guest compounds. Guest molecules can be low molecular weight components of associated petroleum gas (C1-C4 hydrocarbons), carbon dioxide, hydrogen sulfide, and nitrogen. Gas hydrates have a number of unique properties that make them interesting from a technological point of view, for example, for storing hydrocarbon gases in solid form under moderate thermobaric conditions. Currently, the possibility of storing and transporting hydrocarbon gases in the form of solid hydrate is being actively explored throughout the world. The hydrate form of gas has a number of advantages, including a significant gas content in the hydrate, relative safety and environmental friendliness of the process. Recently, new developments have been proposed that seek to reduce the number of steps to obtain the finished hydrate, for example, using a pressing device/screw inside the reactor. However, the energy consumption required for the hydrate formation process remains a challenge. Thus, the goal of the current work is to study the patterns and mechanisms of the hydrate formation process using small additions of hydrate formation promoters under static conditions. The study of these aspects will help solve the problem of accelerated production of gas hydrates with minimal energy consumption. New compounds have been developed at Kazan Federal University that can accelerate the formation of methane hydrate with a small amount of promoter in water, not exceeding 0.1% by weight. These promoters were synthesized based on available natural compounds and showed high efficiency in accelerating the growth of methane hydrate. To test the influence of promoters on the process of hydrate formation, standard experiments are carried out under dynamic conditions with stirring. During such experiments, the time at which hydrate formation begins (induction period), the temperature at which formation begins (supercooling), the rate of hydrate formation, and the degree of conversion of water to hydrate are assessed. This approach helps to determine the most effective compound in comparative experiments with different promoters and select their optimal concentration. These experimental studies made it possible to study the features of the formation of associated petroleum gas hydrate from promoter solutions under static conditions. Phase transformations were studied using high-pressure micro-differential scanning calorimetry under various experimental conditions. Visual studies of the growth mode of methane hydrate depending on the type of promoter were also carried out. The work is an extension of the methodology for studying the effect of promoters on the process of associated petroleum gas hydrate formation in order to identify new ways to accelerate the formation of gas hydrates without the use of mixing. This work presents the results of a study of the process of associated petroleum gas hydrate formation using high-pressure differential scanning micro-calorimetry, visual investigation, gas chromatography, autoclaves study, and stability data. It was found that the synthesized compounds multiply the conversion of water into hydrate under static conditions up to 96% due to a change in the growth mechanism of associated petroleum gas hydrate.

Keywords: gas hydrate, gas storage, promotor, associated petroleum gas

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Authors: Mariam Tsitsagi, Ana Berdzenishvili

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Rainfall intensity change is one of the main indicators of climate change. It has a great influence on agriculture as one of the main factors causing soil erosion. Splash and sheet erosion are one of the most prevalence and harmful for agriculture. It is invisible for an eye at first stage, but the process will gradually move to stream cutting erosion. Our study provides the assessment of rainfall erosivity potential with the use of modern research methods in Kakheti region. The region is the major provider of wheat and wine in the country. Kakheti is located in the eastern part of Georgia and characterized quite a variety of natural conditions. The climate is dry subtropical. For assessment of the exact rate of rainfall erosion potential several year data of rainfall with short intervals are needed. Unfortunately, from 250 active metro stations running during the Soviet period only 55 of them are active now and 5 stations in Kakheti region respectively. Since 1936 we had data on rainfall intensity in this region, and rainfall erosive potential is assessed, in some old papers, but since 1990 we have no data about this factor, which in turn is a necessary parameter for determining the rainfall erosivity potential. On the other hand, researchers and local communities suppose that rainfall intensity has been changing and the number of haily days has also been increasing. However, finding a method that will allow us to determine rainfall erosivity potential as accurate as possible in Kakheti region is very important. The study period was divided into three sections: 1936-1963; 1963-1990 and 1990-2015. Rainfall erosivity potential was determined by the scientific literature and old meteorological stations’ data for the first two periods. And it is known that in eastern Georgia, at the boundary between steppe and forest zones, rainfall erosivity in 1963-1990 was 20-75% higher than that in 1936-1963. As for the third period (1990-2015), for which we do not have data of rainfall intensity. There are a variety of studies, where alternative ways of calculating the rainfall erosivity potential based on lack of data are discussed e.g.based on daily rainfall data, average annual rainfall data and the elevation of the area, etc. It should be noted that these methods give us a totally different results in case of different climatic conditions and sometimes huge errors in some cases. Three of the most common methods were selected for our research. Each of them was tested for the first two sections of the study period. According to the outcomes more suitable method for regional climatic conditions was selected, and after that, we determined rainfall erosivity potential for the third section of our study period with use of the most successful method. Outcome data like attribute tables and graphs was specially linked to the database of Kakheti, and appropriate thematic maps were created. The results allowed us to analyze the rainfall erosivity potential changes from 1936 to the present and make the future prospect. We have successfully implemented a method which can also be use for some another region of Georgia.

Keywords: erosivity potential, Georgia, GIS, Kakheti, rainfall

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Authors: Qiong Li

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This study investigated in which condition computer-mediated communication (CMC) could promote pragmatic development. The focal feature included four Chinese sentence final particles (SFPs), a, ya, ba, and ne. They occur frequently in Chinese, and function as mitigators to soften the tone of speech. However, L2 acquisition of SFPs is difficult, suggesting the necessity of additional exposure to or explicit instruction on Chinese SFPs. This study follows this line and aims to explore two research questions: (1) Is CMC combined with data-driven instruction more effective than CMC alone in promoting L2 Chinese learners’ SFP use? (2) How does L2 Chinese learners’ SFP use change over time, as compared to the production of native Chinese speakers? The study involved 19 intermediate-level learners of Chinese enrolled at a private American university. They were randomly assigned to two groups: (1) the control group (N = 10), which was exposed to SFPs through CMC alone, (2) the treatment group (N = 9), which was exposed to SFPs via CMC and data-driven instruction. Learners interacted with native speakers on given topics through text-based CMC over Skype. Both groups went through six 30-minute CMC sessions on a weekly basis, with a one-week interval after the first two CMC sessions and a two-week interval after the second two CMC sessions (nine weeks in total). The treatment group additionally received a data-driven instruction after the first two sessions. Data analysis focused on three indices: token frequency, type frequency, and acceptability of SFP use. Token frequency was operationalized as the raw occurrence of SFPs per clause. Type frequency was the range of SFPs. Acceptability was rated by two native speakers using a rating rubric. The results showed that the treatment group made noticeable progress over time on the three indices. The production of SFPs approximated the native-like level. In contrast, the control group only slightly improved on token frequency. Only certain SFPs (a and ya) reached the native-like use. Potential explanations for the group differences were discussed in two aspects: the property of Chinese SFPs and the role of CMC and data-driven instruction. Though CMC provided the learners with opportunities to notice and observe SFP use, as a feature with low saliency, SFPs were not easily noticed in input. Data-driven instruction in the treatment group directed the learners’ attention to these particles, which facilitated the development.

Keywords: computer-mediated communication, data-driven instruction, pragmatic development, second language Chinese, sentence final particles

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Reka Zsuzsanna Mathe

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The globalization and the Europeanization have significantly contributed to a change in the role of the nation-states. The global economic crisis, the climate changes, and the recent refugee crisis, are just a few among many challenges that cannot be effectively addressed by the traditional role of the nation-states. One of the main roles of the states is to solve collective action problems, however due to their changing roles; apparently this is getting more and more difficult. Depending on political culture, collective action problems are solved either through cooperation or conflict. The political culture of Central and Eastern European (CEE) countries is marked by low civic participation and by a weak civil society. In this type of culture collective action problems are likely to be induced through conflict, rather than the democratic process of dialogue and any type of social change is probably to be introduced by social movements. Several studies have been conducted on the social movements of the CEE countries, yet, it is still not clear if the most significant social movements of the region tend to choose rather the cooperative or the conflictual way as action strategy. This study differentiates between a national and a European action field, having different social orders. The actors of the two fields are the broadly understood civil society members, conceptualized as social movements. This research tries to answer the following questions: a) What are the norms that best characterize the CEE countries’ social order? b) What type of actors would prefer a change and in which areas? c) Is there a significant difference between the main actors active in the national versus the European field? The main hypotheses are that there are conflicting norms defining the national and the European action field, and there is a significant difference between the action strategies adopted by social movements acting in the two different fields. In mapping the social order, the study uses data provided by the European Social Survey. Big data of the Global Data on Events, Location and Tone (GDELT) database offers information regarding the main social movements and their preferred type of action. The unit of the analysis is the so called ‘Visegrad 4’ countries: Poland, Czech Republic, Slovakia and Hungary and the research uses data starting from 2005 (after the European accession of these four countries) until May, 2017. According to the data, the main hypotheses were confirmed.

Keywords: big data, Central and Eastern Europe, civil society, GDELT, social movements

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Authors: Latha V. Prabhu, B.V. Murlimanju, P.J. Jiji, Mangala M. Pai

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Background: The capitate is the largest among the carpal bones. There exists no literature about the vascular foramina of the capitate bone. The objective of the present study was to investigate the morphology and number of the nutrient foramina in the cadaveric dried capitate bones of the Indian population. Methods: The present study included 59 capitate bones (25 right sided and 34 left sided) which were obtained from the gross anatomy laboratory of our institution. The bones were macroscopically observed for the nutrient foramina and the data was collected with respect to their number. The tabulation of the data and analysis were done. Results: All of our specimens (100%) exhibited the nutrient foramina over the non-articular and articular surfaces. The foramina were observed at the medial, lateral, palmar and dorsal surfaces of the capitate bones. The foramina were ranged from 6 to 23 in each capitate bone. In the medial surface, the foramina ranged from 1 to 6, lateral surface from 0 to 7, the foramina ranged between 0 and 5 in the palmar surface. However most of the foramina were located at the dorsal surface which ranged from 3 to 11. Conclusion: We believe that the present study has provided additional data about the nutrient foramina of the capitate bones. The data is enlightening to the orthopedic surgeon and would help in the hand surgeries. The knowledge about the foramina is also important to the radiologists to prevent the misinterpretation of the findings in the x ray and computed tomogram scan films. The foramina may mimick like erosions and ossicles. The morphological knowledge of the vasculature, their foramina of entry and number is required to understand the concepts in the avascular necrosis of the capitate.

Keywords: avascular necrosis, capitate, morphology, nutrient foramen

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Authors: Phenias Nsabimana, Jérôme W. Some, Hilda Vasanthakaalam, Stefaan De Henauw, Souheila Abbeddou

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Tools for the dietary assessment in adults are limited in low- and middle-income settings. The objective of this study was to develop and validate a semi-quantitative food frequency questionnaire (FFQ) against the multiple pass-24 h recall tool for use in urban and rural Rwanda. A total of 212 adults (154 females and 58 males), 18-49 aged, including 105 urban and 107 rural residents, from the four regions of Rwanda, were recruited in the present study. A multiple-pass 24- H recall technique was used to collect dietary data in both urban and rural areas in four different rounds, on different days (one weekday and one weekend day), separated by a period of three months, from November 2020 to October 2021. The details of all the foods and beverages consumed over the 24h period of the day prior to the interview day were collected during face-to-face interviews. A list of foods, beverages, and commonly consumed recipes was developed by the study researchers and ten research assistants from the different regions of Rwanda. Non-standard recipes were collected when the information was available. A single semi-quantitative FFQ was also developed in the same group discussion prior to the beginning of the data collection. The FFQ was collected at the beginning and the end of the data collection period. Data were collected digitally. The amount of energy and macro-nutrients contributed by each food, recipe, and beverage will be computed based on nutrient composition reported in food composition tables and weight consumed. Median energy and nutrient contents of different food intakes from FFQ and 24-hour recalls and median differences (24-hour recall –FFQ) will be calculated. Kappa, Spearman, Wilcoxon, and Bland-Altman plot statistics will be conducted to evaluate the correlation between estimated nutrient and energy intake found by the two methods. Differences will be tested for their significance and all analyses will be done with STATA 11. Data collection was completed in November 2021. Data cleaning is ongoing and the data analysis is expected to be completed by July 2022. A developed and validated semi-quantitative FFQ will be available for use in dietary assessment. The developed FFQ will help researchers to collect reliable data that will support policy makers to plan for proper dietary change intervention in Rwanda.

Keywords: food frequency questionnaire, reproducibility, 24-H recall questionnaire, validation

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