Search results for: central auditory processing disorder

Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the central nervous system (CNS) that affects the myelination process in the CNS. Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Epstein-Barr virus (EBV) and MS, is one potential cause that is not well understood. In this study, we aim to summarize the available data on EBV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis," "Epstein-Barr virus," and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched, and 14 articles were chosen, studied, and analyzed. Results: Demyelinated lesions isolated from MS patients contain EBNAs from EBV proteins. The EBNA1 domain contains a pentapeptide fragment identical to B-crystallin, a heat shock peptide, that is increased in peripheral B cells in response to B-crystallin infection, resulting in myelin-directed autoimmunity mediated by proinflammatory T cells. EBNA2, which is involved in the regulation of viral transcription, may enhance transcription from MS risk loci. A 7-fold increase in the risk of MS has been observed in EBV infection with HLA-DR15 synergy. Conclusion: EBV infection along with a variety of specific genetic risk alleles, cause inflammatory cascades in the CNS by infected B cells. There is a high expression of EBV during the course of MS, which indicates the relationship between EBV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of EBV may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, Epstein-Barr virus, central nervous system, EBNAs

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Cely D. Magpantay, Geolynne Marie Adel, Cire-rine Mae Concepcion, Dessa Jean Orcajada, Jorgette Andrea Santos, Orian Laurace Canaman

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Mental illness initiative is very relevant in promoting the Mental Health Bill act of 2017. In the Philippines alone, the public is more open and receptive to people at risks with a mental condition. Although it is uncommon that parents can become more psychologically unfit compared to their children, research shows that parents who are suffering from mental illness have a more significant negative effect than another family member. The impact of parent’s mental health can put their children more susceptible to acquire the same disorder. The aim of the study is to explore the lived experiences of children whose parents suffered from mental illness. It discusses how their parent's mental condition in, anyway, affects their psychological development. Using Phenomenological Qualitative Research, an in-depth, interview was conducted to five (5) consenting adults who lived with their parents diagnosed with a mental disorder. Results are clustered into four themes. The first theme is the negative emotion towards parents, the second theme is the psychosocial dynamics in caring for the patient, third is accepting the disease, and fourth is a general perspective on the family. Each themes is validated by experts and the participants. This theme generates subcomponent like isolation, shallow relationship and debt of gratitude. Along with these themes comes the fear of having a family emerged. There is a growing need to strengthen the family ties even more because of parent’s mental illness. Therefore, parental mental illness has an effect on the children’s psychological and social development.

Keywords: lived experience in Philippines, mental health, parental mental illness, psychosocial dynamics

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Authors: Alla Tvardovskaya

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The family of a child with disabilities is an important mechanism of socialization. The relationship of mother and child with developmental difficulties is a significant predictor of the emergence, development and interiorization of various forms of mental activity. Complex impairments of the child form nonconstructive maternal attitude and destructive behavior strategies that complicate the dyadic relationship ‘mother-child’. The study of psychological characteristics of mother's personality was conducted within four years, and adaptive abilities of a child with a complex disorder were evaluated as well. 25 diads (25 mothers and 25 preschool children aged between 4-7 years with complex developmental disorders) took part in the study. Typological features of mothers rearing deafblind preschoolers are described. Constructive and non-constructive types of mothers’ attitude to a pre-school child with complex disorders are specified. The research shows that mothers of deafblind children are more depressed, they are engaged in children’s rearing more, and at the same time they experience difficulties to control negative emotions towards children or demonstrate impulsive behavior with a high level of anxiety. The correlation analysis of relationships between Vineland scales and the dominant type of mothers’ attitude to a child shows the presence of both general and specific links. Adaptive profile analysis of a child with complex disabilities allows to plan specific ways to increase their adaptation by developing a dyadic constructive relationship system. Techniques to develop constructive parental attitudes toward the child are proposed.

Keywords: adaptive behavior, complex disorder, constructive maternal attitude, deaf-blindness, pre-school child

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Authors: Abdelghani Chahmi

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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Sawitree Wongkittirungrueang

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The objectives of this research were: 1) to study the effect of social stories on social interaction of students with autism. The sample was Pratomsuksa level 5 student with autism, Khon Kaen University Demonstration School, who was diagnosed by the Physician as High Functioning Autism since he was able to read, write, calculate and was studying in inclusive classroom. However, he still had disability in social interaction to participate in social activity group and communication. He could not learn how to develop friendship or create relationship. He had inappropriate behavior in social context. He did not understand complex social situations. In addition, he did seemed not know time and place. He was not able to understand feeling of oneself as well as the others. Consequently, he could not express his emotion appropriately. He did not understand or express his non-verbal language for communicating with friends. He lacked of common interest or emotion with nearby persons. He greeted inappropriately or was not interested in greeting. In addition, he did not have eye contact. He used inadequate language etc. He was elected by Purposive Sampling. His parents were willing to allow them to participate in this study. The research instruments were the lesson plan of social stories, and the picture book of social stories. The instruments used for data collection, were the social interaction evaluation of autistic students. This research was Quasi Experimental Research as One Group Pre-test, Post-test Design. For the Pre-test, the experiment was conducted by social stories. Then, the Post-test was implemented. The statistic used for data analysis, included the Mean, and Standard Deviation. The research findings were shown by Graph. The findings revealed hat the autistic students taught by social stories indicated better social interaction after being taught by social stories.

Keywords: social story, autism spectrum disorder (ASD), autism, social interaction

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: M. Hosseini, N. Ghorbani Amirabad, M. Zhian

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Seismic design codes accept structural and nonstructural damages after the sever earthquakes (provided that the building is prevented from collapse), so that in many cases demolishing and reconstruction of the building is inevitable, and this is usually very difficult, costly and time consuming. Therefore, designing and constructing of buildings in such a way that they can be easily repaired after earthquakes, even major ones, is quite desired. For this purpose giving the possibility of rocking or see-saw motion to the building structure, partially or as a whole, has been used by some researchers in recent decade .the central support which has a main role in creating the possibility of see-saw motion in the building’s structural system. In this paper, paying more attention to the key role of the central fuse and support, an innovative energy dissipater which can act as the central fuse and support of the building with seesaw motion is introduced, and the process of reaching an optimal geometry for that by using finite element analysis is presented. Several geometric shapes were considered for the proposed central fuse and support. In each case the hysteresis moment rotation behavior of the considered fuse were obtained under simultaneous effect of vertical and horizontal loads, by nonlinear finite element analyses. To find the optimal geometric shape, the maximum plastic strain value in the fuse body was considered as the main parameter. The rotational stiffness of the fuse under the effect of acting moments is another important parameter for finding the optimum shape. The proposed fuse and support can be called Yielding Curved Bars and Clipped Hemisphere Core (YCB&CHC or more briefly YCB) energy dissipater. Based on extensive nonlinear finite element analyses it was found out the using rectangular section for the curved bars gives more reliable results. Then, the YCB energy dissipater with the optimal shape was used in a structural model of a 12 story regular building as its central fuse and support to give it the possibility of seesaw motion, and its seismic responses were compared to those of a the building in the fixed based conditions, subjected to three-components acceleration of several selected earthquakes including Loma Prieta, Northridge, and Park Field. In building with see-saw motion some simple yielding-plate energy dissipaters were also used under circumferential columns.The results indicated that equipping the buildings with central and circumferential fuses result in remarkable reduction of seismic responses of the building, including the base shear, inter story drift, and roof acceleration. In fact by using the proposed technique the plastic deformations are concentrated in the fuses in the lowest story of the building, so that the main body of the building structure remains basically elastic, and therefore, the building can be easily repaired after earthquake.

Keywords: rocking mechanism, see-saw motion, finite element analysis, hysteretic behavior

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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Authors: Johannes Dregger, Michael Schmidt, Christian Prasse, Michael ten Hompel

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Most of the today’s companies face increasing need to operate efficiently. Driven by global trends like shorter product cycles, mass customization and the rising speed of delivery, manufacturing value chains are becoming more and more distributed. Manufacturing processes are becoming highly integrated, e.g. 3D printing. All these changes are affecting companies´ organization. They are leading towards individual, small scale, and ad-hoc logistics processes and structures, and finally, towards a significant increase in the importance of logistics itself since traditional value chains transform into agile value networks. In the past logistics has been following manufacturing but in the future industry, this role allocation might change. With this increase in the logistics practice of companies and businesses, the relevance of logistics research as the methodological foundation of logistics networks and processes is gaining importance. Logistics research is evolving into a central and highly interdisciplinary science for the future industry. Using the example of Germany, this paper discusses ways to establish logistics as a central scientific discipline of the future industry. About three million people work in the logistics sector in Germany. Only automotive and retail industry have more employees. Even though there is a bunch of logistics degree programs at more than 100 institutions of higher education, a common understanding of logistics as a research discipline is missing. In this paper an innovative approach will be presented, including; identified perspectives on logistics, such as process orientation, IT orientation or employees orientation, relevant scientific disciplines for logistics science, a concept for interdisciplinary research approaches to unify the perspectives of the different scientific disciplines on logistics and the methodological base of logistics science.

Keywords: logistics, logistics science, logistics management, future challenges

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Authors: Mohamed Sadok Bensalem, Soulef Amamria, Khaled Lazzez, Mohamed Ghanmi

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The southern-central Tunisian Atlas presents a typical example of an external zone. It occupies a particular position in the North African chains: firstly, it is the eastern limit of atlassic structures; secondly, it is the edges between the belts structures to the north and the stable Saharan platform in the south. The evolution of deformation study is based on several methods, such as classical or numerical methods. The principals parameters controlling the genesis of folds in the southern central Tunisian Atlas are; the reactivation of pre-existing faults during the later compressive phase, the evolution of decollement level, and the relation between thin and thick-skinned. One of the more principal characters of the southern-central Tunisian Atlas is the variation of belts structures directions determined by: NE-SW direction, named the attlassic direction in Tunisia, the NW-SE direction carried along the Gafsa fault (the oriental limit of southern atlassic accident), and the E-W direction defined in the southern Tunisian Atlas. This variation of direction is the result of important variation of deformation during different tectonics phases. A classical modelling of the Jebel ElKebar anticline, based on faults throw of the pre-existing faults and its reactivation during compressive phases, shows the importance of extensional deformation, particular during Aptian-Albian period, comparing with that of later compression (Alpine phases). A numerical modelling, based on the software Rampe E.M. 1.5.0, applied on the anticline of Jebel Orbata confirms the interpretation of “fault related fold” with decollement level within the Triassic successions. The other important parameter of evolution of deformation is the vertical migration of decollement level; indeed, more than the decollement level is in the recent series, most that the deformation is accentuated. The evolution of deformation is marked the development of duplex structure in Jebel At Taghli (eastern limit of Jebel Orbata). Consequently, the evolution of deformation is proportional to the depth of the decollement level, the most important deformation is in the higher successions; thus, is associated to the thin-skinned deformation; the decollement level permit the passive transfer of deformation in the cover.

Keywords: evolution of deformation, pre-existing faults, decollement level, thin-skinned

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Cheng Wen, Zhang Jianhua

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This paper aims to probe into the general rules of industry specialization or diversification in a region during its process of economic growth and the specific reasons for the difference of industry specialization development in the eastern, central and western regions of China. It is found in this paper that the changes of regional industry specialization in China, like most of countries in the world, also present the U-shaped curve. Regional industrial structure is diversified in the first place. And when the per capita income exceeds a certain level, distribution of economic resources in this region will be concentrated again. From the perspective of rising total factor productivity and falling of transaction cost in the process of economic development, this paper comes up with a theoretical model to explain the U-shaped curve. Through the empirical test of China's provincial panel data, this paper explains the factors that cause the inequality of the industry specialization development in the eastern, central and western regions of China.

Keywords: u-shaped curve, regional industrial specialization, technological progress, transaction costs

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Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

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Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez

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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.

Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks

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Authors: H. Khaled, F. Chaabani, F. Boulvain

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This paper focuses on the studied of Aptian series that crops out at the Jebel Serdj in the north central Tunisia. The study series is about 590 meters thick and it is consisting of limestones, marly limestones associated with some levels of siltstones and marls. Two sections are studied in detail regarding lithology, microfacies, magnetic susceptibility and mineralogical composition to provide new insights into the paleoenvironmental evolution and paleoclimatological implications during this period. The following facies associations representing different ramp palaeoenvironments have been identified: mudstone–wackestone outer ramp facies; skeletal grainstone- packstone mid-ramp facies, packstone-grainstone inner-ramp facies which include a variety of organisms such as rudists and ooids and mudstone–wackestone coastal facies rich with miliolidea and orbitolines. The magnetic susceptibility (Xᵢₙ) of all samples was compared with the lithological and microfacies variation. We show that high values of magnetic susceptibility are correlated with the distal facies.

Keywords: Aptian, Serdj Formation, geochemical, mineralogy

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Authors: Sucihatiningsih Dian Wisika Prajanti, Himawan Arif Susanto

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Fruits are perishable products and have relatively low price, especially at harvest time. Generally, farmers only sell the products shortly after the harvest time without any processing. Farmers also only play role as price takers leading them to have less power to set the price. Sometimes, farmers are manipulated by middlemen, especially during abundant harvest. Therefore, it requires an effort to cultivate fruits and create innovation to make them more durable and have higher economic value. The purpose of this research is how to increase the added- value of fruits that have high economic value. The research involved 60 farmers of Salak fruit as the sample. Then, descriptive analysis was used to analyze the data in this study. The results showed the selling price of Salak fruit is very low. Hence, to increase the added-value of the fruits, fruit processing is carried out by freezing - frying which can cause the fruits last longer. In addition to increase these added-value, the products can be accommodated for further processed without worrying about their crops rotted or unsold.

Keywords: fruits processing, Salak fruit, freezing frying, farmer’s welfare, Sleman, Yogyakarta

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Authors: Yosra Baaziz, Moez Labidi

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Given limited research on monetary policy rules in revolutionary countries, this paper challenges the suitability of the Taylor rule in characterizing the monetary policy behavior of the Tunisian Central Bank (BCT), especially in turbulent times. More specifically, we investigate the possibility that the Taylor rule should be formulated as a threshold process and examine the validity of such nonlinear Taylor rule as a robust rule for conducting monetary policy in Tunisia. Using quarterly data from 1998:Q4 to 2013:Q4 to analyze the movement of nominal short-term interest rate of the BCT, we find that the nonlinear Taylor rule improves its performance with the advent of special events providing thus a better description of the Tunisian interest rate setting. In particular, our results show that the adoption of an appropriate nonlinear approach leads to a reduction in the errors of 150 basis points in 1999 and 2009, and 60 basis points in 2011, relative to the linear approach.

Keywords: policy rule, central bank, exchange rate, taylor rule, nonlinearity

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Authors: Mathieu Bere

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Al-Qaeda and Islamic State-affiliated groups such as Ja’amat Nusra al Islam Wal Muslimim (JNIM) and the Islamic State-Greater Sahara Faction, which is now part of the Boko Haram splinter group, Islamic State in West Africa, were responsible, between 2018 and 2020, for at least 1.333 violent incidents against both military and civilian targets, including the assassination and kidnapping for ransom of Western citizens in Mali, Burkina Faso and Niger, the Central Sahel. Protecting civilians from the terrorist violence that is now spreading from the Sahel to the coastal countries of West Africa has been very challenging, mainly because of the many unknowns that surround the perpetrators. To contribute to a better protection of civilians in the region, this paper aims to shed light on the motivations and targeting logic of jihadist perpetrators of terrorist violence against civilians in the central Sahel region. To that end, it draws on relevant secondary data retrieved from datasets, the media, and the existing literature, but also on primary data collected through interviews and surveys in Burkina Faso. An analysis of the data with the support of qualitative and statistical analysis software shows that military and rational strategic motives, more than purely ideological or religious motives, have been the main drivers of terrorist violence that strategically targeted government symbols and representatives as well as local leaders in the central Sahel. Behind this targeting logic, the jihadist grand strategy emerges: wiping out the Western-inspired legal, education and governance system in order to replace it with an Islamic, sharia-based political, legal, and educational system.

Keywords: terrorism, jihadism, Sahel, targeting logic

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Authors: Ahmed Saheel, Milad Ahmed Elmaradi, Tim Archer, Muammer Ahmed Aboaesha, Abdulkhaliq Abdulmajid Altoubashi

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Enhanced oil recovery using carbon dioxide (CO₂-EOR) is a method that can increase oil production beyond what is typically achievable using conventional recovery methods by injecting and hence storing, carbon dioxide (CO₂) in the oil reservoir. In Libya, plans are underway to source a proportion of this CO₂ from subsurface geology that is known from previous drilling to contain high volumes of CO₂. But first, these subsurface volumes need to be more clearly defined and understood. Focusing on the Al-Harouj region of central Libya, ground gravity and airborne magnetic data from the LPI database and the African Magnetic Mapping Project respectively have been prepared and processed by Libyan Petroleum Institute (LPI) and Reid Geophysics Limited (RGL) to produce a range of grids and related products suitable for interpreting geological structure and to make recommendations for subsequent work that will assist CO₂ exploration for purposes of enhanced oil recovery (EOR).

Keywords: gravity anomaly, magnetic anomaly, DEDUCED lineaments, Total horizontal derivative, upward-continuation

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Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Mingzhu Lyu, Runlei Ren, Xinyu Dai, Jiaxuan Pi, Kanghua Li

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The study of video game policy in China has been divided into two branches: "pedagogy" and "game industry". The binary perspective of policy reveals the "contradictory" side of policy performance. Based on this suspicion, this paper constructs a three-dimensional sequence of time, content and institutions of game policy, and establishes the "contradictory" aspects of policy performance between 1949 and 2019. A central-level database of game policies, clarifying that our game policies follow a shift from reactive response to proactive guidance, stigmatization and de-stigmatization, the evolutionary logic. The study found that the central government has always maintained a strict requirement and prudent guidance for game policy, and the deep contradictions in game policy stem from the essential conflict between the natural amusement of games and the seriousness of the educational system, and the Chinese government's use of the understanding of the public and private domains and the Managing of the conflict.

Keywords: game industry, gaming policy, public domain, private domain

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Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

Abstract:

Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

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Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

Abstract:

The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

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Authors: Nina Kaufmans

Abstract:

Traditional therapies, utilizing spoken narratives as a primary source of intervention, are proven to be limited in effectively treating post traumatic stress disorder. Following the effects of the global pandemic of COVID-19, an increasing number of mental health consumers are beginning to experience somatically-based distress in addition to existing mental health symptoms. Moreover, the aftermath of the rapid increase in demand for mental health services has caused significant burnout in mental health professionals. This paper explores the ramifications of recent changes and challenges in the mental health demands and subsequent response and its consequences for mental health workers. We will begin by investigating the neurobiological mechanisms involved in traumatic experiences, then discuss the premises for "bottom-up" or somatically oriented psychotherapy approaches, and finally offer clinical skills and interventions for clients diagnosed with post traumatic stress disorder. In addition, we will discuss how somatically-based psychotherapy interventions implemented in sessions may decrease burnout and improve the well-being of clinicians. We will discuss how the integration of somatically-based interventions into counseling would increase the effectiveness of mental health recovery and sustain remission while simultaneously providing opportunities for self-care for mental health professionals.

Keywords: somatic psychotherapy interventions, trauma counseling, preventing and treating burnout, adults with PTSD, bottom-up skills, the effectiveness of trauma treatment

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Authors: Vivienne Cameron

Abstract:

Background: Between 2010 and 2017, teachers in a suburban public school district struggled to get students to consistently produce adequate writing samples as measured by the Pennsylvania state writing rubric for measuring focus, content, organization, style, and conventions. A common thread in all of the data was the need to develop stamina in the student writers. Method: All of the teachers used the traditional writing process model (prewrite, draft, revise, edit, final copy) during writing instruction. One teacher taught the writing process using word processing and incentivizing with publication instead of the traditional pencil/paper/grading method. Students did not have instruction in typing/keyboarding. The teacher submitted resulting student work to real-life contests, magazines, and publishers. Results: Students in the test group increased both the quantity and quality of their writing over a seven month period as measured by the Pennsylvania state writing rubric. Reluctant writers, as well as students with autism spectrum disorder, benefited from this approach. This outcome was repeated consistently over a five-year period. Interpretation: Removing the burden of pencil and paper allowed students to participate in the writing process more fully. Writing with pencil and paper is physically tiring. Students are discouraged when they submit a draft and are instructed to use the Add, Remove, Move, Substitute (ARMS) method to revise their papers. Each successive version becomes shorter. Allowing students to type their papers frees them to quickly and easily make changes. The result is longer writing pieces in shorter time frames, allowing the teacher to spend more time working on individual needs. With this additional time, the teacher can concentrate on teaching focus, content, organization, style, conventions, and audience. S/he also has a larger body of works from which to work on whole group instruction such as developing effective leads. The teacher submitted the resulting student work to contests, magazines, and publishers. Although time-consuming, the submission process was an invaluable lesson for teaching about audience and tone. All students in the test sample had work accepted for publication. Students became highly motivated to succeed when their work was accepted for publication. This motivation applied to special needs students, regular education students, and gifted students.

Keywords: elementary-age students, reluctant writers, teaching strategies, writing process

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Authors: Collins Nkapnwo Formella

Abstract:

The democratic wave of the 1980s and 1990s brought a lot of hopes to the politics of African states as many nation-states adopted ‘democracy.’ The end of the Cold War ushered in, with a lot of rush, pro-democracy movements, which led to multi-party politics, following constitutional reviews. For the very first time since independence, Africans revolted against personalized dictatorship and adopted the idea of limited office terms for the presidents. This paper dives deep into the history of Africa post-independence with the aim of allowing the readers to understand the nature of the differences in the political setups that currently govern the continent and the central region in particular. Time has proven the euphoria that characterized post-Cold War African politics at least for many countries short-lived, as their leaders were unable to re-design the institutions of governance from the compromise and interest-oriented structures handed down after independence. The result has been that politics in many of the countries have been tailored down along the lines of winner takes all approach, with the accumulation of state power being the sole objective of the leaders. The paper contends that 21ˢᵗ Century African politics is exactly the politics of inclusion/exclusion based on ethnic and interest groups, leading to the flourishing of patrimonial authoritarian regimes. It also puts to the test, whether authoritarian responses to delivering growth (economic, political, social) and peace as has been the model adopted by many leaders is superior compared to democracy. This paper then concludes by adding that the practice of democracy in the Central African region in its current form is inherently flawed from its foundations, thus incapable of rooting out the crises faced in the region.

Keywords: authoritarianism, democracy, development, power, institutions

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Authors: In Hee Shim, Dong Sik Bae

Abstract:

Introduction: Obesity and unfavorable lipid profile may be linked to depressive disorders. This study compared the levels of obesity, lipid profiles and depression severity of patients with depressive disorders. Methods: This study included 156 patients diagnosed with a depressive disorder who were hospitalized between March 2012 and February 2016. The patients were categorized into mild to moderate and severe depressive groups, based on Hamilton Depression Rating Scale scores (Mild to moderate depression 8-23 vs. severe depression ≥ 24). The charts of the patients were reviewed to evaluate body mass index and lipid profiles, including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG), confounding factors, such as other general medical disorders (hypertension, diabetes mellitus, and dyslipidemia), except smoking status (insufficient data). Demographic and clinical characteristics, such as age, sex, comorbidities, family history of mood disorders, psychotic features, and prescription patterns were also assessed. Results: Compared to the mild to the moderate depressive group, patients with severe depression had significantly lower rate of male and comorbidity. The patients with severe depression had a significantly lower TG than patients in the mild to moderate depressive group. After adjustment for the sex and comorbidity, there were no significant differences between the two groups in terms of the obesity and lipid profiles, including TG. Conclusion: These results did not show a significant difference in the association between obesity, lipid profiles and the depression severity. The role of obesity and lipid profiles in the pathophysiology of depression remains to be clarified.

Keywords: depression, HAM-D, lipid profiles, obesity

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