Search results for: monitoring and modeling

Authors: Mahsa Houshdar, Seyed Mehdi Samimi Ardestani , ُSeyed Saeed Sadr

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Introduction: Online Medicare is a method in which parts of a medical process - whether its diagnostics, monitoring or the treatment itself will be done by using online services. This system has been operated in one boy’s high school, one girl’s high school and one high school in deprived aria. Method: At the first step the students registered for using the system. It was not mandatory and not free. They participated in estimating depression scale, anxiety scale and clinical interview by online medical care system. During this estimation, we could find the existence and severity of depression and anxiety in each one of the participants, also we could find the consequent needs of each one, such as supportive therapy in mild depression or anxiety, need to visited by psychologist in moderate cases, need to visited by psychiatrist in moderate-severe cases, need to visited by psychiatrist and psychologist in severe cases and need to perform medical lab examination tests. The lab examination tests were performed on persons specified by the system. The lab examinations were included: serum level of vitamin D, serum level of vitamin B12, serum level of calcium, fasting blood sugar, HbA1c, thyroid function tests and CBC. All of the students were solely treated by vitamins or minerals therapy and/ or treatment of medical problem (such as hypothyroidism). After a few months, we came back to high schools and estimated the existence and severity of depression and anxiety in treated students. With comparing these results, the affectability of the system could be prof. Results: Totally, we operate this project in 1077 participants in 243 of participant, the lab examination test were performed. In girls high schools: the existence and severity of depression significantly deceased (P value= 0.018<0.05 & P value 0.004< 0.05), but results about anxiety was not significant. In boys high schools: the existence and severity of depression significantly decreased (P value= 0.023<0.05 & P value = 0.004< 0.05 & P value= 0.049< 0.05). In boys high schools: the existence and severity of anxiety significantly decreased (P value= 0.041<0.05 & P value = 0.046< 0.05 &) but in one high school results about anxiety was not significant. In high school in deprived area the students did not have any problem paying for participating in the project, but they could not pay for medical lab examination tests. Thus, operation of the system was not possible in deprived area without a sponsor. Conclusion: This online medical system was successful in creating medical and psychiatric profile without attending physician. It was successful in decreasing depression without using antidepressants, but it was partially successful in decreasing anxiety.

Keywords: depression, diabetes, online medicare, vitamin D deficiency

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Authors: Jean De Dieu Ayabagabo, Paul A.Onjoro, Karubiu P. Migwi, Marie C. Dusingize

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This study investigated the effects of feed on milk yield and quality through feed monitoring and quality assessment, and the consequent enteric methane gas emissions from smallholder dairy farms in drier areas of Rwanda, using the Tier II approach for four seasons in three zones, namely; Mayaga and peripheral Bugesera (MPB), Eastern Savanna and Central Bugesera (ESCB), and Eastern plateau (EP). The study was carried out using 186 dairy cows with a mean live weight of 292 Kg in three communal cowsheds. The milk quality analysis was carried out on 418 samples. Methane emission was estimated using prediction equations. Data collected were subjected to ANOVA. The dry matter intake was lower (p<0.05) in the long dry season (7.24 Kg), with the ESCB zone having the highest value of 9.10 Kg, explained by the practice of crop-livestock integration agriculture in that zone. The Dry matter digestibility varied between seasons and zones, ranging from 52.5 to 56.4% for seasons and from 51.9 to 57.5% for zones. The daily protein supply was higher (p<0.05) in the long rain season with 969 g. The mean daily milk production of lactating cows was 5.6 L with a lower value (p<0.05) during the long dry season (4.76 L), and the MPB zone having the lowest value of 4.65 L. The yearly milk production per cow was 1179 L. The milk fat varied from 3.79 to 5.49% with a seasonal and zone variation. No variation was observed with milk protein. The seasonal daily methane emission varied from 150 g for the long dry season to 174 g for the long rain season (p<0.05). The rain season had the highest methane emission as it is associated with high forage intake. The mean emission factor was 59.4 Kg of methane/year. The present EFs were higher than the default IPPC value of 41 Kg from developing countries in African, the Middle East, and other tropical regions livestock EFs using Tier I approach due to the higher live weight in the current study. The methane emission per unit of milk production was lower in the EP zone (46.8 g/L) due to the feed efficiency observed in that zone. Farmers should use high-quality feeds to increase the milk yield and reduce the methane gas produced per unit of milk. For an accurate assessment of the methane produced from dairy farms, there is a need for the use of the Life Cycle Assessment approach that considers all the sources of emissions.

Keywords: footprint, forage, girinka, tier

Procedia PDF Downloads 198

Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Siswoyo Haryono

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Purpose – The fundamental goal of this research is to see if the integrative organizational behavior model can be used effectively in Islamic boarding schools. This paper also seeks to assess the effect of Islamic organizational culture, leadership, and spiritual intelligence on teachers' organizational commitment to Islamic Boarding schools. The goal of the mediation analysis is to see if the Islamic work ethic has a more significant effect on the instructors' organizational commitment than the direct effects of Islamic organizational culture, leadership, and Islamic spiritual intelligence. Design/methodology/approach – A questionnaire survey was used to obtain data from teachers at Islamic Boarding Schools. This study used the AMOS technique for structural equation modeling to evaluate the expected direct effect. To test the hypothesized indirect effect, employed Sobel test. Findings – Islamic organizational culture, Islamic leadership, and Islamic spiritual intelligence significantly affect Islamic work ethic. When it comes to Islamic corporate culture, Islamic leadership, Islamic spiritual intelligence, and Islamic work ethics have a significant impact. The findings of the mediation study reveal that Islamic organizational culture, leadership, and spiritual intelligence influences organizational commitment through Islamic work ethic. The total effect analysis shows that the most effective path to increasing teachers’ organizational commitment is Islamic leadership - Islamic work ethic – organizational commitment. Originality/value – This study evaluates the Integrative Model of Organizational Behavior by Colquitt (2016) applied in Islamic Boarding School. The model consists of contemporary leadership and individual characteristic as the antecedent. The mediating variables of the model consist of individual mechanisms such as trust, justice, and ethic. Individual performance and organizational commitment are the model's outcomes. These variables, on the other hand, do not represent the Islamic viewpoint as a whole. As a result, this study aims to assess the role of Islamic principles in the model. The study employs reliability and validity tests to get reliable and valid measures. The findings revealed that the evaluation model is proven to improve organizational commitment at Islamic Boarding School.

Keywords: Islamic leadership, Islamic spiritual intelligence, Islamic work ethic, organizational commitment, Islamic boarding school

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Authors: Siti Noor Syahirah Mohd Sabri

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The oil and gas industry is committed to net zero carbon emissions because the consequences of climate change could be catastrophic unless responded to very soon. One way of reducing CO₂ emissions is to inject it into a depleted reservoir buried underground. This greenhouse gas reduction technique significantly reduces CO₂ released into the atmosphere. In general, depleted oil and gas reservoirs provide readily available sites for the storage of CO₂ in offshore areas. This is mainly due to the hydrocarbons have been optimally produced and the existence of voids for effective CO₂ storage. Hence, make it a good candidate for a CO₂ well injector location. Geological storage sites are often evaluated in terms of capacity, injectivity and containment. Leakage through the cap rock or existing well is the main concern in the depleted fields. In order to develop these fields as CO₂ storage sites, the long-term integrity of wells drilled in these oil & gas fields must be ascertained to ensure good CO₂ containment. Well, integrity is often defined as the ability to contain fluids without significant leakage through the project lifecycle. Most plugged and abandoned (P & A) wells in Peninsular Malaysia have drilled 20 – 30 years ago and were not designed to withstand downhole conditions having >50%vol CO₂ and CO₂/H₂O mixture. In addition, Corrosive-Resistant Alloy (CRA) tubular and CO₂-resistant cement was not used during good construction. The reservoir pressure and temperature conditions may have further degraded the material strength and elevated the corrosion rate. Understanding all the uncertainties that may have affected cement-casing bonds, such as the quality of cement behind the casing, subsidence effect, corrosion rate, etc., is the first step toward well integrity evaluation. Secondly, proper quantification of all the uncertainties involved needs to be done to ensure long-term underground storage objectives of CO₂ are achieved. This paper will discuss challenges associated with estimating the performance of well barrier elements in existing P&A wells. Risk ranking of the existing P&A wells is to be carried out in order to ensure the integrity of the storage site is maintained for long-term CO₂ storage. High-risk existing P&A wells are to be re-entered to restore good integrity and to reduce future leakage that may happen. In addition, the requirement to design a fit-for-purpose monitoring and mitigation technology package for potential CO₂ leakage/seepage in the marine environment will be discussed accordingly. The holistic approach will ensure that the integrity is maintained, and CO₂ is contained underground for years to come.

Keywords: CCUS, well integrity, co₂ storage, offshore

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

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Authors: Sudheer Kumar Gundati, Umasankar Patro

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Carbon nanotube (CNT) – polymer composites have been extensively studied due to their exceptional electrical and mechanical properties. In the present study, poly(vinylidene fluoride) (PVDF) – multi-walled CNT composites were prepared by melt-blending technique using pristine (ufCNT) and a modified dilute nitric acid-treated CNTs (fCNT). Due to this dilute acid-treatment, the fCNTs were found to show significantly improved dispersion and retained their electrical property. The fCNT showed an electrical percolation threshold (PT) of 0.15 wt% in the PVDF matrix as against 0.35 wt% for ufCNT. The composites were made into films of thickness ~0.3 mm by compression-molding and the resulting composite films were subjected to various property evaluations. It was found that the water contact angle (WCA) of the films increased with CNT weight content in composites and the composite film surface became hydrophobic (e.g., WCA ~104° for 4 wt% ufCNT and 111.5° for 0.5 wt% fCNT composites) in nature; while the neat PVDF film showed hydrophilic behavior (WCA ~68°). Significant enhancements in the mechanical properties were observed upon CNT incorporation and there is a progressive increase in the tensile strength and modulus with increase in CNT weight fraction in composites. The composite films were tested for strain-sensing applications. For this, a simple and non-destructive method was developed to demonstrate the strain-sensing properties of the composites films. In this method, the change in electrical resistance was measured using a digital multimeter by applying bending strain by oscillation. It was found that by applying dynamic bending strain, there is a systematic change in resistance and the films showed piezo-resistive behavior. Due to the high flexibility of these composite films, the change in resistance was reversible and found to be marginally affected, when large number of tests were performed using a single specimen. It is interesting to note that the composites with CNT content notwithstanding their type near the percolation threshold (PT) showed better strain-sensing properties as compared to the composites with CNT contents well-above the PT. On account of the excellent combination of the various properties, the composite films offer a great promise as strain-sensors for structural health-monitoring.

Keywords: carbon nanotubes, electrical percolation threshold, mechanical properties, poly(vinylidene fluoride), strain-sensor, water contact angle

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

Procedia PDF Downloads 316

Authors: Samuel Abebe Ebebo

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Scale precipitation causes a major issue for geothermal power plants because it reduces the production rate of geothermal energy. Each geothermal power plant's different chemical and physical conditions can cause the scale to precipitate under a particular set of fluid-rock interactions. Depending on the mineral, it is possible to have scale in the production well, steam separators, heat exchangers, reinjection wells, and everywhere in between. The scale consists mainly of smectite and trace amounts of chlorite, magnetite, quartz, hematite, dolomite, aragonite, and amorphous silica. The smectite scale is one of the difficult scales at injection wells in geothermal power plants. X-ray diffraction and chemical composition identify this smectite as Stevensite. The characteristics and the scale of each injection well line are different depending on the fluid chemistry. The smectite scale has been widely distributed in pipelines and surface plants. Mineral water equilibrium showed that the main factors controlling the saturation indices of smectite increased pH and dissolved Mg concentration due to the precipitate on the equipment surface. This study aims to characterize the scales and geothermal fluids collected from the Onuma geothermal power plant in Akita Prefecture, Japan. Field tests were conducted on October 30–November 3, 2021, at Onuma to determine the pH control methods for preventing magnesium silicate scaling, and as exemplified, the formation of magnesium silicate hydrates (M-S-H) with MgO to SiO2 ratios of 1.0 and pH values of 10 for one day has been studied at 25 °C. As a result, M-S-H scale formation could be suppressed, and stevensite formation could also be suppressed when we can decrease the pH of the fluid by less than 8.1, 7.4, and 8 (at 97 °C) in the fluid from O-3Rb and O-6Rb, O-10Rg, and O-12R, respectively. In this context, the scales and fluids collected from injection wells at a geothermal power plant in Japan were analyzed and characterized to understand the formation conditions of Mg-silicate scales with on-site synthesis experiments. From the results of the characterizations and on-site synthesis experiments, the inhibition method of their scale formation is discussed based on geochemical modeling in this study.

Keywords: magnesium silicate, scaling, inhibitor, geothermal power plant

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Authors: İlkay Özer Erselcan, Abdi Kükner, Gökhan Ceylan

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The power generated by eight point absorber type wave energy converters each having a different buoy are calculated in order to investigate the performances of buoys in this study. The calculations are carried out by modeling three different sea states observed in two different locations in the Black Sea. The floats analyzed in this study have two basic geometries and four different draft/radius (d/r) ratios. The buoys possess the shapes of a semi-ellipsoid and a semi-elliptic paraboloid. Additionally, the draft/radius ratios range from 0.25 to 1 by an increment of 0.25. The radiation forces acting on the buoys due to the oscillatory motions of these bodies are evaluated by employing a 3D panel method along with a distribution of 3D pulsating sources in frequency domain. On the other hand, the wave forces acting on the buoys which are taken as the sum of Froude-Krylov forces and diffraction forces are calculated by using linear wave theory. Furthermore, the wave energy converters are assumed to be taut-moored to the seabed so that the secondary body which houses a power take-off system oscillates with much smaller amplitudes compared to the buoy. As a result, it is assumed that there is not any significant contribution to the power generation from the motions of the housing body and the only contribution to power generation comes from the buoy. The power take-off systems of the wave energy converters are high pressure oil hydraulic systems which are identical in terms of their characteristic parameters. The results show that the power generated by wave energy converters which have semi-ellipsoid floats is higher than that of those which have semi elliptic paraboloid floats in both locations and in all sea states. It is also determined that the power generated by the wave energy converters follow an unsteady pattern such that they do not decrease or increase with changing draft/radius ratios of the floats. Although the highest power level is obtained with a semi-ellipsoid float which has a draft/radius ratio equal to 1, other floats of which the draft/radius ratio is 0.25 delivered higher power that the floats with a draft/radius ratio equal to 1 in some cases.

Keywords: Black Sea, buoys, hydraulic power take-off system, wave energy converters

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Xiao Yang, Ji Zhang, Yingli Song, Hui Huang, Jing Zhang, Yan Wang, Rongrong Han, Zhixuan Xiang, Lu Chen, Lingling Gao

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Aim and Objectives: To examine physical activity self-efficacy, identify its predictors, and further explore the mechanism of action among the predictors in mainland Chinese pregnant women with high risk for gestational diabetes mellitus (GDM). Background: Physical activity could protect pregnant women from developing GDM. Physical activity self-efficacy was the key predictor of physical activity. Design: A cross-sectional study was conducted from October 2021 to May 2022 in Zhengzhou, China. Methods: 252 eligible pregnant women completed the Pregnancy Physical Activity Self-efficacy Scale, the Social Support for Physical Activity Scale, the Knowledge on Physical Activity Questionnaire, the 7-item Generalized Anxiety Disorder scale, the Edinburgh Postnatal Depression Scale, and a socio-demographic data sheet. Multiple linear regression was applied to explore the predictors of physical activity self-efficacy. Structural equation modeling was used to explore the mechanism of action among the predictors. Results: Chinese pregnant women with a high risk for GDM reported a moderate level of physical activity self-efficacy. The best-fit regression analysis revealed four variables explained 17.5% of the variance in physical activity self-efficacy. Social support for physical activity was the strongest predictor, followed by knowledge of the physical activity, intention to do physical activity, and anxiety symptoms. The model analysis indicated that knowledge of physical activity could release anxiety and depressive symptoms and then increase physical activity self-efficacy. Conclusion: The present study revealed a moderate level of physical activity self-efficacy. Interventions targeting pregnant women with high risk for GDM need to include the predictors of physical activity self-efficacy. Relevance to clinical practice: To facilitate pregnant women with high risk for GDM to engage in physical activity, healthcare professionals may find assess physical activity self-efficacy and intervene as soon as possible on their first antenatal visit. Physical activity intervention programs focused on self-efficacy may be conducted in further research.

Keywords: physical activity, gestational diabetes, self-efficacy, predictors

Procedia PDF Downloads 90

Authors: Alexandra Emmanuelle Membangbi, Jacky Njiki Bikoï, Esther Del-florence Moni Ndedi, Marie Joseph Nkodo Mindimi, Donatien Serge Mbaga, Elsa Nguiffo Makue, André Chris Mikangue Mbongue, Martha Mesembe, George Ikomey Mondinde, Eric Walter Perfura-yone, Sara Honorine Riwom Essama

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Background: Tuberculosis (TB) is one of the top lethal infectious diseases worldwide. In recent years, interferon-γ (INF-γ) release assays (IGRAs) have been established as routine tests for diagnosing TB infection. However, produced INF-γ assessment failed to distinguish active TB (ATB) from latent TB infection (LTBI), especially in TB epidemic areas. In addition to IFN-γ, interleukin-2 (IL-2), another cytokine secreted by activated T cells, is also involved in immune response against Mycobacterium tuberculosis. The aim of the study was to assess the capacity of IFN-γ and IL2 to evaluate the therapeutic response of patients on anti-tuberculosis treatment. Material and Methods: We conducted a cross-sectional study in the Pneumonology Departments of the Jamot Hospital in Yaoundé between May and August 2021. After signed the informed consent, the sociodemographic data, as well as 5 mL of blood, were collected in the crook of the elbow of each participant. Sixty-one subjects were selected (n= 61) and divided into 4 groups as followed: group 1: resistant tuberculosis (n=13), group 2: active tuberculosis (n=19), group 3 cured tuberculosis (n=16), and group 4: presumed healthy persons (n=13). The cytokines of interest were determined using an indirect Enzyme-linked Immuno-Sorbent Assay (ELISA) according to the manufacturer's recommendations. P-values < 0.05 were interpreted as statistically significant. All statistical calculations were performed using SPSS version 22.0 Results: The results showed that men were more 14/61 infected (31,8%) with a high presence in active and resistant TB groups. The mean age was 41.3±13.1 years with a 95% CI = [38.2-44.7], the age group with the highest infection rate was ranged between 31 and 40 years. The IL-2 and INF-γ means were respectively 327.6±160.6 pg/mL and 26.6±13.0 pg/mL in active tuberculosis patients, 251.1±30.9 pg/mL and 21.4±9.2 pg/mL in patients with resistant tuberculosis, while it was 149.3±93.3 pg/mL and 17.9±9.4 pg/mL in cured patients, 15.1±8.4 pg/mL and 5.3±2.6 pg/mL in participants presumed healthy (p <0.0001). Significant differences in IFN-γ and IL-2 rates were observed between the different groups. Conclusion: Monitoring the serum levels of INF-γ and IL-2 would be useful to evaluate the therapeutic response of anti-tuberculosis patients, particularly in the both cytokines association case, that could improve the accuracy of routine examinations.

Keywords: antibiotic therapy, interferon gamma, interleukin 2, tuberculosis

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Authors: Ansoné Human, Nantes Kirsten, Tanja Verster, Willem D. Schutte

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Every year the telecommunications industry suffers huge losses due to fraud. Mobile fraud, or generally, telecommunications fraud is the utilisation of telecommunication products or services to acquire money illegally from or failing to pay a telecommunication company. A South African telecommunication operator developed two internal fraud scorecards to mitigate future risks of application fraud events. The scorecards aim to predict the likelihood of an application being fraudulent and surprise fraudsters before they surprise the telecommunication operator by identifying fraud at the time of application. The scorecards are utilised in the vetting process to evaluate the applicant in terms of the fraud risk the applicant would present to the telecommunication operator. Telecommunication providers can utilise these scorecards to profile customers, as well as isolate fraudulent and/or high-risk applicants. We provide the complete methodology utilised in the development of the scorecards. Furthermore, a Determination and Discrimination (DD) ratio is provided in the methodology to select the most influential variables from a group of related variables. Throughout the development of these scorecards, the following was revealed regarding fraudulent cases and fraudster behaviour within the telecommunications industry: Fraudsters typically target high-value handsets. Furthermore, debit order dates scheduled for the end of the month have the highest fraud probability. The fraudsters target specific stores. Applicants who acquire an expensive package and receive a medium-income, as well as applicants who obtain an expensive package and receive a high income, have higher fraud percentages. If one month prior to application, the status of an account is already in arrears (two months or more), the applicant has a high probability of fraud. The applicants with the highest average spend on calls have a higher probability of fraud. If the amount collected changes from month to month, the likelihood of fraud is higher. Lastly, young and middle-aged applicants have an increased probability of being targeted by fraudsters than other ages.

Keywords: application fraud scorecard, predictive modeling, regression, telecommunications

Procedia PDF Downloads 112

Authors: Ekeh Greg

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Learning has been part of human existence from time immemorial. The aim of every learning is to know the truth. In education, it is desirable that true knowledge is imparted and imbibed. For this to be achieved, there is need for honesty, in this context, academic honesty among students, especially in e-learning. This is an ethical issue since honesty bothers on human conduct. However, research findings have shown that academic honesty has remained a big challenge to online learners, especially among the university students. This is worrisome since the university education is the final education system and a gateway to life in the wider society after schooling. If they are practicing honesty in their academic life, it is likely that they will practice honesty in the in the society, thereby bringing positive contributions to the society wherever they find themselves. With this in mind, the significance of this study becomes obvious. On grounds of this significance, this paper focuses on strategies that are adjudged certain to enhance the practice of honesty in e-learning so as to enable learners to be well equipped to contribute to the society through honest ways. The aim of the paper is to contribute to the efforts of instilling the consciousness and practice of honesty in the minds and hearts of learners. This will, in turn, promote effective teaching and learning, academic high standard, competence and self-confidence in university education. Philosophical methods of conceptual analysis, clarification, description and prescription are adopted for the study. Philosophical perspective is chosen so as to ground the paper on the basis of rationality rather than emotional sentiments and biases emanating from cultural, religious and ethnic differences and orientations. Such sentiments and biases can becloud objective reasoning and sound judgment. A review of related literature is also carried out. The findings show that academic honesty in e-learning is a cherished value, but it is bedeviled by some challenges, such as care-free attitude on the part of students and absence of monitoring. The findings also show that despite the challenges facing academic honesty, strategies such as self-discipline, determination, hard work, imbibing ethical and philosophical principles, among others, can certainly enhance the practice of honesty in e-learning among university students. The paper, therefore, concludes that these constitute strategies for enhancing academic honesty among students. Consequently, it is suggested that instructors, school counsellors and other stakeholders should endeavour to see that students are helped to imbibe these strategies and put them into practice. Students themselves are enjoined to cherish honesty in their academic pursuit and avoid short-cuts. Short-cuts can only lead to mediocrity and incompetence on the part of the learners, which may have long adverse consequences, both on themselves and others.

Keywords: academic, ethical, philosophical, strategies

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

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Authors: Dina Magnaye

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In the Philippines, the performance of the agricultural sector is gauged through crop productivity and returns from farm production rather than the biodiversity in the agricultural ecosystem. Agricultural development hinges on the overall goal of increasing productivity through intensive agriculture, monoculture system, utilization of high yielding varieties in plants, and genetic upgrading in animals. This merits an analysis of the role of agro-biodiversity in terms of increasing productivity, food security and economic returns from community-based pro-biodiversity enterprises. These enterprises conserve biodiversity while equitably sharing production income in the utilization of biological resources. The study aims to determine how community-based pro-biodiversity enterprises become instrumental in local climate change adaptation and agro-biodiversity conservation as input to local green economic development planning. It also involves an assessment of the role of agrobiodiversity in terms of increasing productivity, food security and economic returns from community-based pro-biodiversity enterprises. The perceptions of the local community members both in urban and upland rural areas on community-based pro-biodiversity enterprises were evaluated. These served as a basis in developing a planning modality that can be mainstreamed in the management of local green economic enterprises to benefit the environment, provide local income opportunities, conserve species diversity, and sustain environment-friendly farming systems and practices. The interviews conducted with organic farmer-owners, entrepreneur-organic farmers, and organic farm workers revealed that pro-biodiversity enterprise such as organic farming involved the cyclic use of natural resources within the carrying capacity of a farm; recognition of the value of tradition and culture especially in the upland rural area; enhancement of socio-economic capacity; conservation of ecosystems in harmony with nature; and climate change mitigation. The suggested planning modality for community-based pro-biodiversity enterprises for a green economy encompasses four (4) phases to include community resource or capital asset profiling; stakeholder vision development; strategy formulation for sustained enterprises; and monitoring and evaluation.

Keywords: agro-biodiversity, agro-biodiversity conservation, local green economy, organic farming, pro-biodiversity enterprise

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Authors: Omar Nouri, Wafa Mnejja, Nejla Fourati, Fatma Dhouib, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Jamel Daoud

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Background and objective: Induction chemotherapy (IC) followed by concomitant chemo radiotherapy with intensity modulated radiation (IMRT) technique is actually the recommended treatment modality for locally advanced nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the prognostic factors predicting loco regional relapse with this new treatment protocol. Patients and methods: A retrospective study of 52 patients with NPC treated between June 2016 and July 2019. All patients received IC according to the protocol of the Head and Neck Radiotherapy Oncology Group (Gortec) NPC 2006 (3 TPF courses) followed by concomitant chemo radiotherapy with weekly cisplatin (40 mg / m2). Patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. Median age was 49 years (19-69) with a sex ratio of 3.3. Forty five tumors (86.5%) were classified as stages III - IV according to the 2017 UICC TNM classification. Loco regional relapse (LRR) was defined as a local and/or regional progression that occurs at least 6 months after the end of treatment. Survival analysis was performed according to Kaplan-Meier method and Log-rank test was used to compare anatomy clinical and therapeutic factors that may influence loco regional free survival (LRFS). Results: After a median follow up of 42 months, 6 patients (11.5%) experienced LRR. A metastatic relapse was also noted for 3 of these patients (50%). Target volumes coverage was optimal for all patient with LRR. Four relapses (66.6%) were in high-risk target volume and two (33.3%) were borderline. Three years LRFS was 85,9%. Four factors predicted loco regional relapses: histologic type other than undifferentiated (UCNT) (p=0.027), a macroscopic pre chemotherapy tumor volume exceeding 100 cm³ (p=0.005), a reduction in IC doses exceeding 20% (p=0.016) and a total cumulative cisplatin dose less than 380 mg/m² (p=0.0.34). TNM classification and response to IC did not impact loco regional relapses. Conclusion: For nasopharyngeal carcinoma, tumors with initial high volume and/or histologic type other than UCNT, have a higher risk of loco regional relapse. Therefore, they require a more aggressive therapeutic approaches and a suitable monitoring protocol.

Keywords: loco regional relapse, modulation intensity radiotherapy, nasopharyngeal carcinoma, prognostic factors

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Authors: Liya Kalinnikova Magnusson

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The present and ongoing research investigation are focusing on special educational origins in Moldova for children with disabilities and its development towards inclusion. The research is coordinated with related research on inclusion in Ukraine and other countries. The research interest in these issues in Moldova is caused by several reasons. The first one is based upon one of the intensive processes of deconstruction of special education institutions in Moldova since 1989. A large number of children with disabilities have been dropping out of these institutions: from 11400 students in 1989 to 5800 students in 1996, corresponding to 1% of all school-age Moldovan learners. Despite the fact that a huge number of students was integrated into regular schools and the dynamics of this data across the country was uneven (the opposite, the dynamics of exclusion was raised in Trans-Dniester on the border of Moldova), the volume of the change was evident and traditional special educational provision was under stable decline. The second reason is tied to transitional challenges, which Moldova met under the force to economic liberalisation that led the country to poverty. Deinstitutionalization of the entire state system took place in the situation of economic polarization of the society. The level of social benefits was dramatically diminished, increasing inequality. The most vulnerable from the comprehensive income consideration were families with many children, children with disabilities, children with health problems, etc.: each third child belonged to the poorest population. In 2000-2001: 87,4% of all families with children had incomes below the minimum wage. The research question raised based upon these considerations has been addressed to the investigation of particular patterns of the origins of special education and its development towards inclusion in Moldova from 1980 until the present date: what is the pattern of special education origins and what are particular arrangements of special education development towards inclusion against inequality? This is a qualitative study, with relevant peer review resources connected to the research question and national documents of educational reforms towards inclusion retrospectively and contemporary, analysed by a content analysis approach. This study utilises long term statistics completed by the respective international agencies as a result of regular monitoring of the implementation of educational reforms. The main findings were composed in three big themes: adoption of the Soviet pattern of special education, ‘endemic stress’ of breaking the pattern, and ‘paradoxes of resolution’.

Keywords: special education, statistics, educational reforms, inclusion, children with disabilities, content analysis

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: Zhang Qingzhong

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Though there exists an increasing number of research studies on the headquarters-subsidiary relationship, and within this context, there is a focus on subsidiaries' contributory role to multinational corporations (MNC), subsidiary autonomy, and the conditions under which autonomy exerts an effect on subsidiary performance still constitute a subject of debate in the literature. The objective of this research is to study the MNC subsidiary autonomy and performance relationship and the effect of subsidiary entrepreneurial orientation and trust on subsidiary autonomy in the China environment, a phenomenon that has not yet been studied. The research addresses the following three questions: (i) Is subsidiary autonomy associated with MNC subsidiary performance in the China environment? (ii) How do subsidiary entrepreneurship and its trust in headquarters affect the level of subsidiary autonomy and its relationship with subsidiary performance? (iii) Does subsidiary autonomy have a mediating effect on subsidiary performance with subsidiary’s entrepreneurship and trust in headquarters? In the present study, we have reviewed literature and conducted semi-structured interviews with multinational corporation (MNC) subsidiary senior executives in China. Building on our insights from the interviews and taking perspectives from four theories, namely the resource-based view (RBV), resource dependency theory, integration-responsiveness framework, and social exchange theory, as well as the extant articles on subsidiary autonomy, entrepreneurial orientation, trust, and subsidiary performance, we have developed a model and have explored the direct and mediating effects of subsidiary autonomy on subsidiary performance within the framework of the MNC. To test the model, we collected and analyzed data based on cross-industry two waves of an online survey from 102 subsidiaries of MNCs in China. We used structural equation modeling to test measurement, direct effect model, and conceptual framework with hypotheses. Our findings confirm that (a) subsidiary autonomy is positively related to subsidiary performance; (b) subsidiary entrepreneurial orientation is positively related to subsidiary autonomy; (c) subsidiary’s trust in headquarters has a positive effect on subsidiary autonomy; (d) subsidiary autonomy mediates the relationship between entrepreneurial orientation and subsidiary performance; (e) subsidiary autonomy mediates the relationship between trust and subsidiary performance. Our study highlights the important role of subsidiary autonomy in leveraging the resource of subsidiary entrepreneurial orientation and its trust relationship with headquarters to achieve high performance. We discuss the theoretical and managerial implications of the findings and propose directions for future research.

Keywords: subsidiary entrepreneurial orientation, trust, subsidiary autonomy, subsidiary performance

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Authors: Nathalie Stephenne, Mathieu Veschkens, Stéphane Palm, Christophe Charlemagne, Jacques Defoux

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According to Europe’s first River basin Management Plans (RBMPs), 56% of European rivers failed to achieve the good status targets of the Water Framework Directive WFD. In Central European countries such as Belgium, even more than 80% of rivers failed to achieve the WFD quality targets. Although the RBMP’s should reduce the stressors and improve water body status, their potential to address multiple stress situations is limited due to insufficient knowledge on combined effects, multi-stress, prioritization of measures, impact on ecology and implementation effects. This paper describes a webGis prototype developed for the Walloon administration to improve the communication and the management of sediment dredging actions carried out in rivers and lakes in the frame of RBMPs. A large number of stakeholders are involved in the management of rivers and lakes in Wallonia. They are in charge of technical aspects (client and dredging operators, organizations involved in the treatment of waste…), management (managers involved in WFD implementation at communal, provincial or regional level) or policy making (people responsible for policy compliance or legislation revision). These different kinds of stakeholders need different information and data to cover their duties but have to interact closely at different levels. Moreover, information has to be shared between them to improve the management quality of dredging operations within the ecological system. In the Walloon legislation, leveling dredged sediments on banks requires an official authorization from the administration. This request refers to spatial information such as the official land use map, the cadastral map, the distance to potential pollution sources. The production of a collective geodatabase can facilitate the management of these authorizations from both sides. The proposed internet system integrates documents, data input, integration of data from disparate sources, map representation, database queries, analysis of monitoring data, presentation of results and cartographic visualization. A prototype of web application using the API geoviewer chosen by the Geomatic department of the SPW has been developed and discussed with some potential users to facilitate the communication, the management and the quality of the data. The structure of the paper states the why, what, who and how of this communication tool.

Keywords: sediments, web application, GIS, rivers management

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Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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The transportation of dangerous goods by lorries throughout Europe must be done by using the roads conforming the European Road Transport Network. In this network, there are several parking areas where lorry drivers can park to rest according to the regulations. According to the "European Agreement concerning the International Carriage of Dangerous Goods by Road", parking areas where lorries transporting dangerous goods can park to rest, must follow several security stipulations to keep safe the rest of road users. At this respect, these lorries must be parked in adapted areas with strict and permanent surveillance measures. Moreover, drivers must satisfy several restrictions about resting and driving time. Under these facts, one may expect that there exist enough parking areas for the transport of this type of goods in order to obey the regulations prescribed by the European Union and its member countries. However, the already-existing parking areas are not sufficient to cover all the stops required by drivers transporting dangerous goods. Our main goal is, starting from the already-existing parking areas and the loading-and-unloading location, to provide an optimal answer to the following question: how many additional parking areas must be built and where must they be located to assure that lorry drivers can transport dangerous goods following all the stipulations about security and safety for their stops? The sense of the word “optimal” is due to the fact that we give a global solution for the location of parking areas throughout the whole European Road Transport Network, adjusting the number of additional areas to be as lower as possible. To do so, we have modeled the problem using graph theory since we are working with a road network. As nodes, we have considered the locations of each already-existing parking area, each loading-and-unloading area each road bifurcation. Each road connecting two nodes is considered as an edge in the graph whose weight corresponds to the distance between both nodes in the edge. By applying a new efficient algorithm, we have found the additional nodes for the network representing the new parking areas adapted for dangerous goods, under the fact that the distance between two parking areas must be less than or equal to 400 km.

Keywords: trans-european transport network, dangerous goods, parking areas, graph-based modeling

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: M. Abuziarov

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The designed complex is intended for the numerical simulation of fast dynamic processes of interaction of heterogeneous environments susceptible to the significant formability. The main challenges in solving such problems are associated with the construction of the numerical meshes. Currently, there are two basic approaches to solve this problem. One is using of Lagrangian or Lagrangian Eulerian grid associated with the boundaries of media and the second is associated with the fixed Eulerian mesh, boundary cells of which cut boundaries of the environment medium and requires the calculation of these cut volumes. Both approaches require the complex grid generators and significant time for preparing the code’s data for simulation. In this codes these problems are solved using two grids, regular fixed and mobile local Euler Lagrange - Eulerian (ALE approach) accompanying the contact and free boundaries, the surfaces of shock waves and phase transitions, and other possible features of solutions, with mutual interpolation of integrated parameters. For modeling of both liquids and gases, and deformable solids the Godunov scheme of increased accuracy is used in Lagrangian - Eulerian variables, the same for the Euler equations and for the Euler- Cauchy, describing the deformation of the solid. The increased accuracy of the scheme is achieved by using 3D spatial time dependent solution of the discontinuity problem (3D space time dependent Riemann's Problem solver). The same solution is used to calculate the interaction at the liquid-solid surface (Fluid Structure Interaction problem). The codes does not require complex 3D mesh generators, only the surfaces of the calculating objects as the STL files created by means of engineering graphics are given by the user, which greatly simplifies the preparing the task and makes it convenient to use directly by the designer at the design stage. The results of the test solutions and applications related to the generation and extension of the detonation and shock waves, loading the constructions are presented.

Keywords: fluid structure interaction, Riemann's solver, Euler variables, 3D codes

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Authors: Tarek Duzan

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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

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Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

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Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

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Authors: Omid Giahi, Ebrahim Darvishi, Mahdi Akbarzadeh

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Introduction: Occupational low back pain (LBP) is one of the most prevalent work-related musculoskeletal disorders in which a lot of risk factors are involved that. The present study focuses on the relation between personal, psycho-social and occupational risk factors and LBP severity in industrial workers. Materials and Methods: This research was a case-control study which was conducted in Kurdistan province. 100 workers (Mean Age ± SD of 39.9 ± 10.45) with LBP were selected as the case group, and 100 workers (Mean Age ± SD of 37.2 ± 8.5) without LBP were assigned into the control group. All participants were selected from various industrial units, and they had similar occupational conditions. The required data including demographic information (BMI, smoking, alcohol, and family history), occupational (posture, mental workload (MWL), force, vibration and repetition), and psychosocial factors (stress, occupational satisfaction and security) of the participants were collected via consultation with occupational medicine specialists, interview, and the related questionnaires and also the NASA-TLX software and REBA worksheet. Chi-square test, logistic regression and structural equation modeling (SEM) were used to analyze the data. For analysis of data, IBM Statistics SPSS 24 and Mplus6 software have been used. Results: 114 (77%) of the individuals were male and 86 were (23%) female. Mean Career length of the Case Group and Control Group were 10.90 ± 5.92, 9.22 ± 4.24, respectively. The statistical analysis of the data revealed that there was a significant correlation between the Posture, Smoking, Stress, Satisfaction, and MWL with occupational LBP. The odds ratios (95% confidence intervals) derived from a logistic regression model were 2.7 (1.27-2.24) and 2.5 (2.26-5.17) and 3.22 (2.47-3.24) for Stress, MWL, and Posture, respectively. Also, the SEM analysis of the personal, psycho-social and occupational factors with LBP revealed that there was a significant correlation. Conclusion: All three broad categories of risk factors simultaneously increase the risk of occupational LBP in the workplace. But, the risks of Posture, Stress, and MWL have a major role in LBP severity. Therefore, prevention strategies for persons in jobs with high risks for LBP are required to decrease the risk of occupational LBP.

Keywords: industrial workers occupational, low back pain, occupational risk factors, psychosocial factors

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