Search results for: quality approach

Authors: Mohammed Lamine Benaouda

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This paper seeks to shed light on the African continent role with the crisis of natural gas supplies to European countries, which resulted from the repercussions of the Russian-Ukrainian war, by examining the case of re-launching the Trans-Saharan Gas Pipeline project Nigeria-Algeria, and clarifying the strategic importance This project is mutually beneficial in the long run. The paper relied on the analytical and statistical method in order to find out the the impact that the project represents on the huge needs of the European gas market on the one hand, and monitoring the various economic gains for Algeria and Nigeria on the other hand, in addition, the comparative approach to assess the possible effects of the success and feasibility of the project economy for all its beneficiaries. The paper founds that the complexity has multiplied in the global energy market in general and the European one in particular, following what the world witnessed from the repercussions of the Russian-Ukrainian war, as well as the extreme importance of the poles of African countries in the arena of the international struggle over resources, which allows them a margin From maneuvering and regional and global influence in various fields. With regard to the research outcoms and the future scope, the researcher believes that the African continent, in light of international competition and conflict, as well as what the world is witnessing in terms of restoring balances of power in the current international system, will play very important roles, especially with its enormous natural and human capabilities, which enable it to Weighting future conflicts over energy and spheres of influence.

Keywords: algeria, nigeria, west africa, ECOWAS, gas supplies, russia, ukrain

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: Rana Alkhamra

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Background: Child's earliest experiences with books and stories during the first years of his life are strongly linked with the development of his early language and literacy skills. Interacting in routine learning activities, such as shared book reading, storytelling, and teaching about the letters of the alphabet make a critical foundation for early learning, language growth and emergent literacy. Aim: The current study explores family and preschool early interactive literacy practices in families and preschools (nursery and kindergarten) in Jordan. It highlights the importance of early interactive literacy activities on child language and literacy growth and development. Methods: This is a cross sectional study that surveyed 243 Jordanian families. The survey investigated literacy routine practices, largely shared books reading, at home and at preschool; child speech and language development; and family demographics. Results: Around 92.5% of the families read books and stories to their children, as frequently as 1-2 times weekly or monthly (75%). Only 19.6% read books on daily basis. Many families reported preferring story-telling (97%). Despite that families acknowledged the importance of early literacy activities, on language, reading and writing, cognitive, and academic development, 45% asked for education and training pertaining to specific ways and ideas to help their young children develop language and literacy skills. About 69% of the families reported reading books and stories to their children for 15 minutes a day, while 71.2% indicated having their children watch television for 3 to > 6 hours a day. At preschool, only 52.8% of the teachers were reported to read books and stories. Factors like parent education, monthly income, living inside (33.6%) or outside (66.4%) the capital city of Amman significantly (p < 0.05) affected child early literacy interactive activities whether at home or at preschool. Conclusion: Early language and literacy skills depend largely on the opportunities and experiences provided to children in the home and in preschool environment. Family literacy programs can play an important role in bridging the gap in early literacy experiences for families that need help. Also, speech therapists can work in collaboration with families and educators to ensure that young children have high quality and sufficient opportunities to participate in early literacy activities both at home and in preschool environments.

Keywords: literacy, interactive activities, language, practices, family, preschool, Jordan

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

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Authors: Abdul Kadir, L. Meily Kurniawidjaja

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Batik Madura workers are exposed to many Musculoskeletal Disorders risk factors, particularly Low Back Pain (LBP). This study was conducted as an early detection of ergonomic risk level on Workers Industrial Sentra Batik Madura in Dusun Banyumas, Klampar Subdistrict, Proppo Pamekasan, Madura, East Java. This study includes 12 workers who 11 workers had pain in the upper and lower part of the neck, back, wrist right hand, also 10 workers had pain in the right shoulder. This is a descriptive observational study with cross-sectional approach. Qualitative research by observing workers activity such as draw and putting the wax motif, fabric dyeing, fabric painting, discoloration, washing, and drying. The results are workers have identified ergonomic hazards such as awkward postures, twisting movements, repetitive, and static work postures. Using the method of REBA and QEC, the results get a very high-risk level of activity in each of Madura batik making process is the draw and putting the wax motif, coloring, painting, discoloration, washing, and drying. The level of risk can be reduced by improvement of work equipment include the provision of seats, strut fabric, high settings furnaces, drums, coloring basin, and washing tub.

Keywords: activities of Madura's batik, ergonomic risk level, equipment, QEC (Quick Exposure Checklist), REBA (Rapid Entire Body Assessment)

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Authors: Bidzina Matsaberidze

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It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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Authors: Hassan Ibrahim

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The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. We constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

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Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

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Authors: Qaiser Javed, Ahmad Azeem

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Salinity and water scarcity are major environmental problems which are limiting the agricultural production. This research was conducted to construct a model to find out appropriate regime to dilute saline water based on physiological and electrophysiological properties of Brassica napus L., and Orychophragmus violaceus (L.). Plants were treated under salt-stressed concentrations of NaCl (NL₁: 2.5, NL₂: 5, NL₃: 10; gL⁻¹), Na₂SO₄ (NO₁: 2.5, NO₂: 5, NO₃: 10; gL⁻¹), and mixed salt concentration (MX₁: NL₁+ NO₃; MX₂: NL₃+ NO₁; MX₃: NL₂+ NO₂; gL⁻¹) and 0 as control, followed by re-watering. Growth, physiological and electrophysiology traits were highly restricted under high salt concentration levels at NL₃, NO₃, MX₁, and MX₂, respectively. However, during the rewatering phase, growth, electrophysiological, and physiological parameters were recovered well. Consequently, the increase in net photosynthetic rate was noted under moderate stress condition which was 44.13, 37.07, and 43.01%, respectively in Orychophragmus violaceus (L.) and 44.94%, 53.45%, and 63.04%, respectively were found in Brassica napus L. According to the results, the best dilution point was 5–2.5% for NaCl and Na₂SO₄ alternatively, whereas it was 10–0.0% for the mixture of salts. Therefore, the effect of salinity in O. violaceus and B. napus may also be reduced effectively by dilution of saline irrigation. It would be a better approach to utilize dilute saline water for irrigation instead of applies direct saline water to plant. This study provides new insight in the field of agricultural engineering to plan irrigation scheduling considering the crop ability to salt tolerance and irrigation water use efficiency by apply specific quantity of irrigation calculated based on the salt dilution point. It would be helpful to balance between irrigation amount and optimum crop water consumption in salt-affected regions and to utilize saline water in order to safe freshwater resources.

Keywords: dilution model, plant growth traits, re-watering, salt stress

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Hossein Hassani, Ali Rezaei

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In recent years, the study of soil contamination problems surrounding mines and smelting plants has attracted some serious attention of the environmental experts. These elements due to the non- chemical disintegration and nature are counted as environmental stable and durable contaminants. Variability of these contaminants in the soil and the time and financial limitation for the favorable environmental application, in order to reduce the risk of their irreparable negative consequences on environment, caused to apply the favorable grading of these contaminant for the further success of the risk management processes. In this study, we use the contaminants factor risk indices, average concentration, enrichment factor and geoaccumulation indices for evaluating the metal contaminant of including Pb, Ni, Se, Mo and Zn in the soil of Sarcheshmeh copper mine area. For this purpose, 120 surface soil samples up to the depth of 30 cm have been provided from the study area. And the metals have been analyzed using ICP-MS method. Comparison of the heavy and potentially toxic elements concentration in the soil samples with the world average value of the uncontaminated soil and shale average indicates that the value of Zn, Pb, Ni, Se and Mo is higher than the world average value and only the Ni element shows the lower value than the shale average. Expert opinions on the relative importance of each indicators were used to assign a final weighting of the metals and the heavy metals were ranked using the TOPSIS approach. This allows us to carry out efficient environmental proceedings, leading to the reduction of environmental ricks form the contaminants. According to the results, Ni, Pb, Mo, Zn, and Se have the highest rate of risk contamination in the soil samples of the study area.

Keywords: contamination coefficient, geoaccumulation factor, TOPSIS techniques, Sarcheshmeh copper complex

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Authors: Mahboubeh Varmaziar

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Depression is a significant public health concern affecting people of all ages and genders. Physical activity has been shown to have a positive effect on mental health, particularly in alleviating symptoms of depression. This study aims to explore the impact of continuous exercise on depression levels among young female athletes in Hamadan Province, Iran. In this randomized controlled trial, 72 women aged 20 to 35 years attending sports centers in Hamadan Province were selected through convenient sampling and randomly assigned to either the control or experimental group. The experimental group participated in a continuous exercise program consisting of 20 sessions over six weeks, with each session lasting 30 minutes. In contrast, the control group maintained their usual daily activities at the sports center. Both groups completed demographic and Beck Depression Inventory questionnaires. Data were analyzed using descriptive and inferential statistics, including two-way ANOVA. The results of the two-way ANOVA, after controlling for the pre-test effect, revealed a significant difference in the mean depression scores between the control and experimental groups (p < 0.001). This suggests that the continuous exercise program significantly reduced depression levels in the young female athletes. The findings suggest that continuous exercise is an effective non-pharmacological intervention for reducing depression in young female athletes. Incorporating regular physical activity into treatment plans may serve as a complementary therapy alongside conventional treatments, offering a low-risk and beneficial approach to managing depression.

Keywords: depression, exercise, female athletes, yong women

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Authors: Chuan Yang, Jing Bie, Panagiotis Psimoulis, Zhong Wang

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Modelling and understanding vehicle volume distribution over the urban network are essential for urban design and transport planning. The space syntax approach was widely applied as the main conceptual and methodological framework for contemporary vehicle volume models with the help of the statistical method of multiple regression analysis (MRA). However, the MRA model with space syntax variables shows a limitation in vehicle volume predicting in accounting for the crossed effect of the urban configurational characters and socio-economic factors. The aim of this paper is to construct models by interacting with the combined impact of the street network structure and socio-economic factors. In this paper, we present a multilevel linear (ML) and an agent-based (AB) vehicle volume model at an urban scale interacting with space syntax theoretical framework. The ML model allowed random effects of urban configurational characteristics in different urban contexts. And the AB model was developed with the incorporation of transformed space syntax components of the MRA models into the agents’ spatial behaviour. Three models were implemented in the same urban environment. The ML model exhibit superiority over the original MRA model in identifying the relative impacts of the configurational characters and macro-scale socio-economic factors that shape vehicle movement distribution over the city. Compared with the ML model, the suggested AB model represented the ability to estimate vehicle volume in the urban network considering the combined effects of configurational characters and land-use patterns at the street segment level.

Keywords: space syntax, vehicle volume modeling, multilevel model, agent-based model

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Authors: Huang Gui

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The issues of human rights and death penalty are always drawing attentions from international scholars, critics and observers, activities and Chinese scholars, and most of them looking at these problems are just doing with such legal or political from a single perspective, but the real relationship between Chinese political regime and legislation is often ignored. In accordance with the Constitution of P.R.C., Communist Party of China (CPC) does not merely play a key role in political field, but in legislation and law enforcement as well. Therefore, the legislation has to implement the party’s theory and outlook, and realize the party’s policies. So is the death penalty system, though it is only concrete punishment system. Considering this point, basic upon the introducing the relationship between CPC and legislation, this paper would like to explore the shifting of CPC’s outlook on human rights and the death penalty system changes in different eras. In Maoist era, the issue of human rights was rejected and deemed as an exclusion zone, and the death penalty was unjustifiably imposed; human rights were politically recognized and accepted in Deng era, but CPC has its own viewpoints on it. CPC emphasized on national security and stability in that era, and the individual human rights weren’t taken correspondingly and reasonably account of. The death penalty was abused and deemed as an important measure to control crime. In post-Deng, human rights were gradually developed and recognized. The term of ‘state respect and protect human rights’ is contained in Constitution of P.R.C., and the individual human rights are gradually valued, but the CPC still focus on state security, development, and stability, the individual right to life hasn’t been enough valued like the right to substance. Although the steps of reforming death penalty are taking, there are still 46 crimes punishable by death. CPC should change its outlook and pay more attention to the right to life, and try to abolish death penalty de facto and de jure.

Keywords: criminal law, communist party of China, death penalty, human rights, China

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Authors: Yassir Abdelrazig, Ren Moses

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Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: Libing Zhu, Waichung Chen, Kwaicing Lo, Lei Li

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Background: Tian Jiu Therapy (a medicinal vesiculation therapy according to traditional Chinese medicine theory) in San Fu Days (the three hottest days in a year is calculated by the Chinese ancient calendar) is widely used by patients with chronic asthma in China although from modern medicine perspective there is insufficient evidence of its effectiveness and safety issues. We investigated the efficacy and safety of Tian Jiu Therapy compared with placebo in patients with chronic asthma. Methods: Patients with chronic asthma were randomly assigned to Tian Jiu treatment group (n=165), placebo control group (n=158). Registered Chinese Medicine practitioners, in Orthopedics-Traumatology, Acupuncture, and Tui-na Clinical Centre for Teaching and Research, School of Chinese Medicine, The University of Hong Kong, administered Tian Jiu Therapy and placebo treatment in 3 times over 2 months. Patients completed questionnaires and lung function test before treatment and after treatment, 3, 6, 9, and 11 months, respectively. The primary outcome was the no of asthma-related sub-healthy symptoms and the percentage of patients with twenty-three symptoms. Results: 451 patients were recruited totally, 111 patients refused or did not participate according the appointment time and 17 did not meet the inclusion criteria. Consequently, 323 of eligible patients were enrolled. There was nothing difference between Tian Jiu Therapy group and placebo control group at the end of all treatments neither primary nor secondary outcomes. While Tian Jiu Therapy as compared with placebo significantly reduced the percentage of participants who are susceptible waken up by asthma symptoms from 27% to 14% at 2nd follow-up (P < 0.05). Similarly, Tian Jiu Therapy significantly reduced the proportion of participants who had the symptom of running nose and sneezing before onset from 18% to 8% at 2nd follow-up (P < 0.05). Additionally, Tian Jiu Therapy significantly reduced the level of asthma, the proportion of participants who don’t need to processed during asthma attack increased from 6% to 15% at 1st follow-up and 0% to 7% at 3rd follow-up (P < 0.05). Improvements also occurred with Tian Jiu Therapy group, it reduced the proportion of participants who were spontaneously sweating at 3rd follow up and diarrhea after intake of oily food at 4th follow-up (P < 0.05). Conclusion: When added to a regimen of foundational therapy for chronic asthma participants, Tian Jiu Therapy further reduced the need for medications to control asthma, improved the quality of participants’ life, and significantly reduced the level of asthma. What is more, this benefit seems to have an accumulative effect over time was in accordance with the TCM theory of 'winter disease is being cured in summer'.

Keywords: asthma, Tian Jiu Therapy, San Fu Days, triaditional Chinese medicine, clinical trial

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Bhawana, Roshan Kamal Topno, Maneesh Kumar, Major Madhukar, Krishna Pandey, Ganesh Chandra Sahoo, Manas Ranjan Dikhit, Surya Suman, Devendra Prasad Yadav, Rishikesh Kumar, Pradeep Das

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Viral co-infection is now very common across taxa and environments that are involved in congenital infections. Herpes simplex virus (HSV) and Rubella are the two serious viral infections, well categorized in TORCH Syndrome. Here we had endeavoured the seroprevalence of co-infection of HSV and Rubella. Systematic tests have been performed to check the virulence pattern of the co-infection. The study was conducted at Department of Virology, Rajendra Memorial Research Institute of Medical Sciences (ICMR), Patna, Bihar, India during January 2018-July 2018. 299 newly cases were attended with the sign and symptoms of HSV and Rubella. After taking written consent forms from all the subjects, blood samples were collected for serological detection. ELISA was performed to detect the presence of IgM antibody level. 12 patients were found to be IgM positive from each HSV and Rubella infection. The findings of our study showed that 6 patients were positive for both HSV and rubella and hence were co-infected. Such co-infection causes severe health problems as it leads to the mortality rate of the patients during viral infectivity. Epidemiologically, proper screening should be needed to check any chance of occurrence of such co-infection in the affected regions in large scale and take suitable preventive approach to decrease the case totality. Concern has to be given to aid proper diagnosis and treatment in order to decrease the spread of HSV and Rubella co-infection.

Keywords: HSV, Rubella, seroprevalence, co-infection, ELISA, viral infectivity

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Authors: Nounamo Nguedie Yann Harold

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The factors behind the debt have been the subject of several studies in the literature. Pioneering studies based on the 'double deficit' approach linked indebtedness to the imbalance between savings and investment, the budget deficit and the current account deficit. Most studies on identifying factors that may stimulate or reduce the level of external public debt agree that the following variables are important explanatory variables in leveraging debt: the budget deficit, trade opening, current account and exchange rate, import, export, interest rate, term variation exchange rate, economic growth rate and debt service, capital flight, and over-indebtedness. Few studies addressed the impact of political factors on the level of external debt. In general, however, the IMF's stabilization programs in developing countries following the debt crisis have resulted in economic recession and the advent of political crises that have resulted in changes in governments. In this sense, political institutions are recognised as factors of accumulation of external debt in most developing countries. This paper assesses the role of political factors on the external debt level of African countries in the Franc Zone over the period 1985-2016. Data used come from World Bank and ICRG. Using a logit in panel, the results show that the more a country is politically stable, the lower the external debt compared to the gross domestic product. Political stability multiplies 1.18% the chances of being in the sustainable debt zone. For example, countries with good political institutions experience less severe external debt burdens than countries with bad political institutions.

Keywords: African countries, external debt, Franc Zone, political factors

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Authors: Chih-Hsien Chen, Yi-Hung Ho, Chih-Wei Wang, Chih-Wei Chang, Yen-Nien Chen, Chih-Han Chang, Chun-Ting Li

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Laminotomy is a spinal decompression surgery compatible with a minimally invasive approach. However, the unilateral laminotomy for bilateral side decompression leads to more perioperative complications than the bilateral laminotomy. Although the unilateral laminotomy removes the least bone tissue among the spinal decompression surgeries, the difference of spinal stability between unilateral and bilateral laminotomy and laminectomy is rarely investigated. This study aims to compare the biomechanical effects of unilateral and bilateral laminotomy and laminectomy on the lumbar spine by finite element (FE) simulation. A three-dimensional FE model of the lumbar spine (L1–L5) was constructed with the vertebral body, discs, and ligaments, as well as the sacrum was constructed. Three different surgical methods, namely unilateral laminotomy, bilateral laminotomy and laminectomy, at L3–L4 and L4–L5 were considered. Partial pedicle and entire ligamentum flavum were removed to simulate bilateral decompression in laminotomy. The entire lamina and spinal processes from the lower L3 to upper L5 were detached in the laminectomy model. Then, four kinds of loadings, namely flexion, extension, lateral bending and rotation, were applied on the lumbar with various decompression conditions. The results indicated that the bilateral and unilateral laminotomy both increased the range of motion (ROM) compared with intact lumbar, while the laminectomy increased more ROM than both laminotomy did. The difference of ROM between the bilateral and unilateral laminotomy was very minor. Furthermore, bilateral laminotomy demonstrated similar poster element stress with unilateral laminotomy. Unilateral and bilateral laminotomy are equally suggested to bilateral decompression of lumbar spine with minimally invasive technique because limited effect was aroused due to more bone remove in the bilateral laminotomy on the lumbar stability. Furthermore, laminectomy is the last option for lumbar decompression.

Keywords: minimally invasive technique, lumbar decompression, laminotomy, laminectomy, finite element method

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Catriona Hilliard

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Food identity is synonymous with many national tourism destinations and perceptions in tourist source markets – stereotypes could include snails in France; beer in Britain and Germany; paella in Spain - and is an accepted element of national identity that can be incorporated into tourism experiences. Irish transatlantic food connections are culturally strong with diaspora subsequent generations in the US displaying an online interest in traditional Irish food, even with a twist. Back ‘home’, the value of the local indigenous experience was a specific element of the way The Gathering 2013 was promoted to the Irish diaspora, developing community interest and input to tourism. Over the past 20 years, Ireland has realized the value of its food industry to tourism. This has included the establishment of food development programmes for the hospitality industry; food festivals as a possible element of the tourist experience; and a programmes of food ambassadors to market Irish produce and to encourage service providers to understand; utilize and incorporate this into their offerings. Irish produce is being now actively marketed as part of the proposed tourism experience, to particular segment markets including transatlantic visitors. In addition, individual providers are becoming aware of the value of the market, and how to gain from it. Also, networks of food providers have developed collaborative structures of promoting their experiences to audiences, displaying a cluster approach of tourism development towards that sector. A power point presentation will look at how Irish produce contributes to tourism marketing and promotion of Ireland to America; how that may have assisted sustainable development of communities here; and hopes to elicit some discussion relating to longer term identification of Irish food, as part of tourism, for the potential benefit of the ‘locale’.

Keywords: Irish, USA, food, tourism

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Authors: Mohammad Saleem, Neeta Kumar, Anita Sharma, Sazina Muzammil

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It is observed that some of the dental students in our setting take less interest in medical subjects. Various teaching methods are focus of research interest currently and being tried to generate interest among students. An approach of interactive integrated tutorial was used to assess its feasibility in teaching medical subjects to dental undergraduates. The aim was to generate interest and promote active self-learning among students. The objectives were to (1) introduce the integrated interactive learning method through two departments, (2) get feedback from the students and faculty on feasibility and effectiveness of this method. Second-year students in Bachelor of Dental Surgery course were divided into two groups. Each group was asked to study physiology and pathology of a common and important condition (anemia and hypertension) in a week’s time. During the tutorial, students asked questions on physiology and pathology of that condition from each other in the presence of teachers of both physiology and pathology departments. The teachers acted only as facilitators. After the session, the feedback from students and faculty on this alternative learning method was obtained. Results: Majority of the students felt that this method of learning is enjoyable, helped to develop reasoning skills and ability to correlate and integrate the knowledge from two related fields. Majority of the students felt that this kind of learning led to better understanding of the topic and motivated them towards deep learning. Teachers observed that the study promoted interdepartmental cross-discipline collaboration and better students’ linkages. Conclusion: Interactive integrated tutorial is effective in motivating dental students for better and deep learning of medical subjects.

Keywords: active learning, education, integrated, interactive, self-learning, tutorials

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Authors: Martina Dickson, Lilly Tennant

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The young Emirati female university students of today are the first generation of women in the UAE for whom higher education as become not only a possibility, but almost an expectation. Young women in the UAE today make up around 77% of students in higher education institutes in the country. However, the societal expectations placed upon these women in terms of early marriage, child-bearing and rearing are similar to those placed upon their mothers and grandmothers in a time where women were not expected to go to university. A large proportion of female university students in the UAE are mothers of young children, or become mothers whilst at the university. This creates a challenging situation for young student mothers, where two weeks’ maternity leave is typical across institutions. The context of this study is in one such institution in the UAE. We have employed a mixed method approach to gathering interview data from twenty mothers, and survey data from over one hundred mothers. The main findings indicate that mothers have strong desires for their institution to support them more, for example by the provision of nursery facilities and resting areas for new mothers, and giving them greater flexibility over course selections and schedules including the provision of online learning. However, the majority felt supported on a personal level by their tutors. The major challenges which they identified in returning to college after only two weeks’ leave included the inevitable health and lack of sleep issues when caring for a newborn, struggling to catch up with missed college work and handling their course load. We also explored the women's’ home support systems which were provided from a variety of extended family, spouses and paid domestic help.

Keywords: student mothers, challenges, supports, United Arab Emirates

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Authors: Stevens Phaphadi Mamorobela

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The Covid-19 pandemic has accelerated the use of social media in SMEs to stay abreast with information about the latest news and developments and to predict the future world of business. The national shutdown regulations for curbing the spread of the Covid-19 virus resulted in SMEs having to distribute large volumes of information through social media platforms to collaborate and conduct business remotely. How much of the information shared on social media is used by SMEs as significant knowledge for economic rent is yet to be known. This study aims to investigate the facilitating conditions that enable SMEs’ intention to use social media as a knowledge-sharing platform to create economic rent and to cope with the Covid-19 challenges. A qualitative research approach was applied where semi-structured interviews were conducted with 13 SME owners located in the Gauteng province in South Africa to identify and explain the facilitating conditions of SMEs towards their intention to use social media as a knowledge-sharing tool in the Covid-19 era. The study discovered that the national lockdown regulations towards curbing the spread of the Covid-19 pandemic had compelled SMEs to adopt digital technologies that enabled them to quickly transform their business processes to cope with the challenges of the pandemic. The facilitating conditions, like access to high bandwidth internet coverage in the Gauteng region, enable SMEs to have strong intentions to use social media to distribute content and to reach out to their target market. However, the content is shared informally using diverse social media platforms without any guidelines for transforming content into rent-yielding knowledge.

Keywords: facilitating conditions, knowledge sharing, social media, intention to use, SME

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Authors: Maria Luisa Boninelli

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This study wants to explore the effects of a mediated intervention program in a primary school. The participants where 120 students aged 8-9, half of them Italian and half immigrants of first or second generation. The activities consisted on the cognitive enhancement of the participants through Feuerstein’s Instrumental Enrichment, (IE) and on an activity centred on body awareness and mediated learning experience. Given that there are limited studied on learners in remedial schools, the current study intented to hypothesized that participants exposed to mediation would yiel a significant improvement in cognitive functioning. Hypothesis One proposed that, following the intervention, improved Q1vata scores of the participants would occur in each of the groups. Hypothesis two postulated that participants within the Mediated Learning Experience would perform significantly better than those group of control. For the intervention a group of 60 participants constituted a group of Mediation sample and were exposed to Mediated Learning Experience through Enrichment Programm. Similiary the other 60 were control group. Both the groups have students with special needs and were exposed to the same learning goals. A pre-experimental research design, in particular a one-group pretest-posttest approach was adopted. All the participants in this study underwent pretest and post test phases whereby they completed measures according to the standard instructions. During the pretest phase, all the participants were simultaneously exposed to Q1vata test for logical and linguistic evaluation skill. During the mediation intervention, significant improvement was demonstrated with the group of mediation. This supports Feuerstein's Theory that initial poor performance was a result of a lack of mediated learning experience rather than inherent difference or deficiencies. Furthermore the use of an appropriate mediated learning enabled the participants to function adequately.

Keywords: cognitive structural modifiability, learning to learn, mediated learning experience, Reuven Feuerstein, special needs

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Authors: Wing Chi Wong

Abstract:

Globally, studying parents caring for children with attention deficit/ hyperactivity disorder (ADHD) is valuable in order to design measures in supporting those parents by health care providers and government. Such parents in Hong Kong seem to encounter detrimental stress and enormous difficulties which are exacerbated by the traditional Chinese culture, exclusion from social members and fiercely competitive educational system. However, seldom studies scrutinize this issue in Hong Kong. This article aims to review the literature regarding parents caring offsprings with ADHD in Hong Kong. Criteria were set for searching among published studies listed in various databases, including MEDLINE, CINCAHL, PsycINFO, ProQuest, Embase, Cochrane Library and Springer Link. Articles with words 'Attention Deficit Hyperactivity Disorder', 'parenting', 'parent', 'family', 'father', 'mother', 'care' in titles and abstracts were identified. Articles with all types of research designs and methods, regardless in English or Chinese, were included. They were limited to years between January 2008 and September 2018. Four relevant studies have resulted. Of them, two were exploratory studies, one was a qualitative study, and one was a survey. Samples were recruited from child psychiatric clinic, Child and Adolescent Mental Health Unit, or multiple family group therapy centres. Authors proclaimed that quality of life of those parents was usually low; particularly mothers perceived a higher stress than fathers; parenting barriers existed; conflicts were commonly raised in parent-child relationship resulting in probable maltreatment to children. Previous studies generally suggested the potential negative outcomes of parents caring children with ADHD. The types and effectiveness of interventions to those parents on relieving their tortures under Hong Kong context had not been explored and systematically evaluated. The scanty studies and existing understanding could not give a promising conclusion pertaining to the appropriate family intervention to parents living with children with ADHD. A stringent research design is necessary to establish evidence on the effectiveness of interventions for those families.

Keywords: attention deficit/ hyperactivity disorder, Hong Kong, parents, interventions

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