Search results for: approach to local and institutional level

Authors: Jacky Liu, Dulani Jayasuriya, Ryan Elmore

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Match fixing and anomalous sports events have increasingly threatened the integrity of professional sports, prompting concerns about existing detection methods. This study addresses prior research limitations in match fixing detection, improving the identification of potential fraudulent matches by incorporating advanced anomaly detection techniques. We develop a novel method to identify anomalous matches and player performances by examining series of matches, such as playoffs. Additionally, we investigate bettors' potential profits when avoiding anomaly matches and explore factors behind unusual player performances. Our literature review covers match fixing detection, match outcome forecasting models, and anomaly detection methods, underscoring current limitations and proposing a new sports anomaly detection method. Our findings reveal anomalous series in the 2022 NBA playoffs, with the Phoenix Suns vs Dallas Mavericks series having the lowest natural occurrence probability. We identify abnormal player performances and bettors' profits significantly decrease when post-season matches are included. This study contributes by developing a new approach to detect anomalous matches and player performances, and assisting investigators in identifying responsible parties. While we cannot conclusively establish reasons behind unusual player performances, our findings suggest factors such as team financial difficulties, executive mismanagement, and individual player contract issues.

Keywords: anomaly match detection, match fixing, match outcome forecasting, problematic players identification

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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: 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: Teklay Gebrecherkos, Dawit Wolday, Muhamud Abdulkader

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Background: COVID-19 symptomatology in Africa appears significantly less serious than in the industrialized world. Our hypothesis for this phenomenon, being a different, more activated immune system due to parasite infections contributes to reduced COVID-19 outcome. We investigated this hypothesis in an endemic area in sub sub-saharan Africa. Methods: Ethiopian COVID-19 patients were enrolled and screened for intestinal parasites, between July 2020 and March 2021. The primary outcome was the proportion of patients with severe COVID-19. SARS-CoV-2 infection was confirmed by RT-PCR on samples obtained from nasopharyngeal swabs, while direct microscopic examination, modified Ritchie concentration, and Kato-Katz methods were used to identify parasites and ova from a fresh stool sample. Ordinal logistic regression models were used to estimate the association between parasite infection and COVID-19 severity. Models were adjusted for sex, age, residence, education level, occupation, body mass index, and comorbidities. Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant. Results: A total of 751 SARS-CoV-2 infected patients were enrolled, of whom 284 (37•8%) had an intestinal parasitic infection. Only 27/255 (10•6%) severe COVID-19 patients were co-infected with intestinal parasites, while 257/496 (51•8%) non-severe COVID-19 patients appeared parasite positive (p<0.0001). Patients co-infected with parasites had lower odds of developing severe COVID-19, with an adjusted odds ratio (AOR) of 0•14 (95% CI 0•09–0•24; p<0•0001) for all parasites, AOR 0•20 ([95% CI 0•11–0•38]; p<0•0001) for protozoa, and AOR 0•13 ([95% CI 0•07–0•26]; p<0•0001) for helminths. When stratified by species, co-infection with Entamoeba spp., Hymenolopis nana, and Schistosoma mansoni implied a lower probability of developing severe COVID-19. There were 11 deaths (1•5%), and all were among patients without parasites (p=0•009). Conclusions: Parasite co-infection is associated with a reduced risk of severe COVID-19 in African patients. Parasite-driven immunomodulatory responses may mute hyper-inflammation associated with severe COVID-19.

Keywords: COVID-19, SARS-COV-2, intestinal parasite, RT-PCR, co-infection

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Authors: Konstantinos G. Kostinakis, Manthos K. Papadopoulos, Asimina M. Athanatopoulou

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An important area of research in seismic risk analysis is the evaluation of expected seismic damage of structures under a specific earthquake ground motion. Several conventional intensity measures of ground motion have been used to estimate their damage potential to structures. Yet, none of them was proved to be able to predict adequately the seismic damage of any structural system. Therefore, alternative advanced intensity measures which take into account not only ground motion characteristics but also structural information have been proposed. The adequacy of a number of advanced earthquake intensity measures in prediction of structural damage of 3D R/C buildings under seismic excitation which attacks the building with arbitrary incident angle is investigated in the present paper. To achieve this purpose, a symmetric in plan and an asymmetric 5-story R/C building are studied. The two buildings are subjected to 20 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along horizontal orthogonal axes forming 72 different angles with the structural axes. The response is computed by non-linear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures determined for incident angle 0° as well as their maximum values over all seismic incident angles are correlated with 9 structure-specific ground motion intensity measures. The research identified certain intensity measures which exhibited strong correlation with the seismic damage of the two buildings. However, their adequacy for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage indices, non-linear response, seismic excitation angle, structure-specific intensity measures

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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: Ning Li, Jiacheng Zhang, Zheng Yang, Sylvia Kang

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Introduction: Polycystic ovary syndrome (PCOS) is a common physiological symptom in women of reproductive age. Women with PCOS may have infrequent or prolonged menstrual periods and excess male hormone (androgen) levels. Mira analyzes the cycle profiles and the luteinizing hormone (LH) changes in urine, closely related to the fertility level of healthy women and PCOS women. From the difference between the two groups, Mira helps to understand the physiological state of PCOS women and their hormonal changes in the menstrual cycle. Methods: In this study, data from 1496 cycles and information from 342 women belonging to two groups (181 PCOS and 161 Healthy) were collected and analyzed. Women test their luteinizing hormone (LH) in urine daily with Mira fertility test wand and Mira analyzer, from the day after the menstruation to the starting day of the next menstruation. All the collected data meets Mira’s user agreement and users’ identification was removed. The cycle length, LH peak, and other cycle information of the PCOS group were compared with the Healthy group. Results: The average cycle length of PCOS women is 41 days and of the Healthy women is 33 days. 91.4% of cycle length is within 40 days for the Healthy group, while it decreases to 71.9% for the PCOS group. This means PCOS women have a longer menstrual cycle and more variation during the cycle. With more variation, the ovulation prediction becomes more difficult for the PCOS group. The deviation between the LH surge day and the predicted ovulation day, calculated by the starting day of the next menstruation minus 14 days, is greater in the PCOS group compared with the Healthy group. Also, 46.96% of PCOS women have an irregular cycle, and only 19.25% of healthy women show an irregular cycle. Conclusion: PCOS women have longer menstrual cycles and more variation during the menstrual cycles. The traditional ovulation prediction is not suitable for PCOS women.

Keywords: menstrual cycle, PCOS, urinary luteinizing hormone, Mira

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Authors: S. Redjala, N. Ait Hocine, M. Gratton, N. Poirot, R. Ferhoum, S. Azem

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Polycarbonate (PC) is a promising polymer with high transparency in the range of the visible spectrum and is used in various fields, for example medical, electronic, automotive. Its low weight, chemical inertia, high impact resistance and relatively low cost are of major importance. In recent decades, some materials such as metals and ceramics have been replaced by polymers because of their superior advantages. However, some characteristics of the polymers are highly modified under the effect of ultraviolet (UV) radiation and temperature. The changes induced in the material by such aging depend on the exposure time, the wavelength of the UV radiation and the temperature level. The UV energy is sufficient to break the chemical bonds leading to a cleavage of the molecular chains. This causes changes in the mechanical, thermal, optical and morphological properties of the material. The present work is focused on the study of the effects of aging under ultraviolet (UV) radiation and under different temperature values on the physical-chemical and mechanical properties of a PC. Thus, various investigations, such as FTIR and XRD analyses, SEM and optical microscopy observations, micro-hardness measurements and monotonic and cyclic tensile tests, were carried out on the PC in the initial state and after aging. Results have shown the impact of aging on the properties of the PC studied. In fact, the MEB highlighted changes in the superficial morphology of the material by the presence of cracks and material de-bonding in the form of debris. The FTIR spectra reveal an attenuation of the peaks like the hydroxyl (OH) groups located at 3520 cm-1. The XRD lines shift towards a larger angle, reaching a maximum of 3°. In addition, Vickers micro-hardness measurements show that aging affects the surface and the core of the material, which results in different mechanical behaviours under monotonic and cyclic tensile tests. This study pointed out effects of aging on the macroscopic properties of the PC studied, in relationship with its microstructural changes.

Keywords: mechanical properties, physical-chemical properties, polycarbonate, UV aging, temperature aging

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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: Junzhang Wu, Yifeng Zou, Alessandro Manzardo, Antonio Scipioni

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Dynamic expiration dates (DEDs) play an essential role in reducing food waste in the context of the sustainable cold chain and food system. However, it is unknown for the trades-off in retail benefits when setting an expiration date on fresh food products. This study aims to develop a multi-dimensional decision-making model that integrates DEDs with food waste based on wireless sensor network technology. The model considers the initial quality of fresh food and the change rate of food quality with the storage temperature as cross-independent variables to identify the potential impacts of food waste in retail by applying s DEDs system. The results show that retail benefits from the DEDs system depend on each scenario despite its advanced technology. In the DEDs, the storage temperature of the retail shelf leads to the food waste rate, followed by the change rate of food quality and the initial quality of food products. We found that the DEDs system could reduce food waste when food products are stored at lower temperature areas. Besides, the potential of food savings in an extended replenishment cycle is significantly more advantageous than the fixed expiration dates (FEDs). On the other hand, the information-sharing approach of the DEDs system is relatively limited in improving sustainable assessment performance of food waste in retail and even misleads consumers’ choices. The research provides a comprehensive understanding to support the techno-economic choice of the DEDs associated with food waste in retail.

Keywords: dynamic expiry dates (DEDs), food waste, retail benefits, fixed expiration dates (FEDs)

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Authors: Intisar Al Busaidi, Rashid Al Maamari, Daowoud Al Mahroqi, Mahvash Karimi

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In recent years, some research studies have been performed on the hybrid application of polymer and low salinity water flooding (LSWF). Numerous technical and economic benefits of low salinity polymer flooding (LSPF) have been reported. However, as with any EOR technology, there are various risks involved in using LSPF. Ions exchange between porous media and brine is one of the Crude oil/ brine/ rocks (COBR) reactions that is identified as a potential risk in LSPF. To the best of our knowledge, this conclusion was drawn based on bulk rheology measurements, and no explanation was provided on how water chemistry changed in the presence of polymer. Therefore, this study aimed to understand rock/ brine interactions with high and low salinity brine in the absence and presence of polymer with Omani reservoir core plugs. Many single-core flooding experiments were performed with low and high salinity polymer solutions to investigate the influence of partially hydrolyzed polyacrylic amide with different brine salinities on cation exchange reactions. Ion chromatography (IC), total organic carbon (TOC), rheological, and pH measurements were conducted for produced aqueous phase. A higher increase in pH and lower polymer adsorption was observed in LSPF compared with conventional polymer flooding. In addition, IC measurements showed that all produced fluids in the absence and presence of polymer showed elevated Ca²⁺, Mg²⁺, K+, Cl- and SO₄²⁻ ions compared to the injected fluids. However, the divalent cations levels, mainly Ca²⁺, were the highest and remained elevated for several pore volumes in the presence of LSP. The results are in line with rheological measurements where the highest viscosity reduction was recorded with the highest level of Ca²⁺ production. Despite the viscosity loss due to cation exchange reactions, LSP can be an attractive alternative to conventional polymer flooding in the Marmul field.

Keywords: polymer, ions, exchange, recovery, low salinity

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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: Gabriel Adesina, Ruixue Cheng, Geetika Aggarwal, Michael Short

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With the global shift towards sustainability and technological advancements, electric Hybrid vehicles (EHVs) are increasingly considered viable alternatives to traditional internal combustion (IC) engine vehicles, which also require efficient cooling systems. The electric Automotive Water Pump (AWP) has been introduced as an alternative to IC engine belt-driven pump systems. However, current control methods for AWPs typically employ fixed gain settings, which are not ideal for the varying conditions of dynamic vehicle environments, potentially leading to overheating issues. To overcome the limitations of fixed gain control, this paper proposes the implementation of an artificial neural network (ANN) for managing the AWP in EHVs. The proposed ANN provides an intelligent, adaptive control strategy that enhances the performance of the AWP, supported through simulation work in MATLAB illustrated in this paper. The comparative analysis demonstrates that while the PID controller provides a fast response of 0.1sec, it has an overshoot of 51.4%. The FLC offers stability and zero overshoot but at the expense of a slower response of 6.7secs. The ANN controller outperforms both, delivering a rapid response of 0.1secs, zero overshoot, 0.0696 IAE, and high precision, making it the most effective control method for AWPs. The ANN’s adaptive learning capabilities allow it to manage the complexities and non-linearity of automotive systems more effectively than traditional control methods.

Keywords: automotive water pump, cooling system, electric hybrid vehicles, artificial neural networks, PID control, fuzzy logic control, IAE, MATLAB

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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: Anil Sharma, Ajay Kumar Mahur, R. G. Sonkawade, A. C. Sharma, R. Prasad

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In coal fired thermal power stations, large amount of fly ash is produced after burning of coal. Fly ash is spread and distributed in the surrounding area by air and may be deposited on the soil of the region surrounding the power plant. Coal contains increased levels of these radionuclides and fly ash may increase the radioactivity in the soil around the power plant. Radon atoms entering into the pore space from the mineral grain are transported by diffusion and advection through this space until they in turn decay or are released into the atmosphere. In the present study, Soil samples were collected from the region around a Kasimpur Thermal Power Plant, Kasimpur, Aligarh (U.P.). Radon activity, radon surface exhalation and mass exhalation rates were measured using “sealed can technique” using LR 115-type II nuclear track detectors. Radon activities vary from 92.9 to 556.8 Bq m-3 with mean value of 279.8 Bq m-3. Surface exhalation rates (EX) in these samples are found to vary from 33.4 to 200.2 mBq m-2 h-1 with an average value of 100.5 mBq m-2 h-1 whereas, Mass exhalation rates (EM) vary from 1.2 to 7.7 mBq kg-1 h-1 with an average value of 3.8 mBq kg-1 h-1. Activity concentrations of radionuclides were measured in these samples by using a low level NaI (Tl) based gamma ray spectrometer. Activity concentrations of 226Ra 232Th and 40K vary from 12 to 49 Bq kg-1, 24 to 49 Bq kg-1 and 135 to 546 Bq kg-1 with overall mean values of 30.3 Bq kg-1, 38.5 Bq kg-1 and 317.8 Bq kg-1, respectively. Radium equivalent activity has been found to vary from 80.0 to 143.7 Bq kg-1 with an average value of 109.7 Bq kg-1. Absorbed dose rate varies from 36.1 to 66.4 nGy h-1 with an average value of 50.4 nGy h-1 and corresponding outdoor annual effective dose varies from 0.044 to 0.081 mSv with an average value of 0.061 mSv. Values of external and internal hazard index Hex, Hin in this study vary from 0.21 to 0.38 and 0.27 to 0.50 with an average value of 0.29 and 0.37, Respectively. The results will be discussed in light of various factors.

Keywords: natural radioactivity, radium equivalent activity, absorbed dose rate, gamma ray spectroscopy

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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: Thanakorn Thanawat, Nomjit Nualnetr

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Background and Purpose: In Thailand, rice farmers have the most prevalence of low back pain when compared with other manual workers. Exercises have been suggested to be a principal part of treatment programs for low back pain. However, the programs should be tailored to an individual’s readiness to change categorized by a behavioral approach. This study aimed to evaluate a difference between the responses of rice farmers with chronic low back pain who received an exercise program integrated with the transtheoretical model of behavior change (TTM) and those of the comparison group regarding severity of pain and trunk muscle endurance. Materials and Methods: An 8-week exercise program was conducted to rice farmers with chronic low back pain who were randomized to either the TTM (n=62, 52 woman and 10 men, mean age ± SD 45.0±5.4 years) or non-TTM (n=64, 53 woman and 11 men, mean age ± SD 44.7±5.4 years) groups. All participants were tested for their severity of pain and trunk (abdominal and back) muscle endurance at baseline (week 0) and immediately after termination of the program (week 8). Data were analysed by using descriptive statistics and student’s t-tests. The results revealed that both TTM and non-TTM groups could decrease their severity of pain and improve trunk muscle endurance after participating in the 8-week exercise program. When compared with the non-TTM group, however, the TTM showed a significantly greater increase in abdominal muscle endurance than did the non-TTM (P=0.004, 95% CI -12.4 to -2.3). Conclusions and Clinical Relevance: An exercise program integrated with the TTM could provide benefits to rice farmers with chronic low back pain. Future studies with a longitudinal design and more outcome measures such as physical performance and quality of life are suggested to reveal further benefits of the program.

Keywords: chronic low back pain, transtheoretical model, rice farmers, exercise program

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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: Elham Jafari

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The aim of this study was to evaluate the effectiveness of emotional intelligence training on reducing marital conflict and marital adjustment in married students of the University of Tehran. This research is an applied type in terms of purpose and a semi-experimental design of pre-test-post-test type with the control group and with follow-up test in terms of the data collection method. The statistical population of the present study consisted of all married students of the University of Tehran. In this study, 30 married students of the University of Tehran were selected by convenience sampling method as a sample that 15 people in the experimental group and 15 people in the control group were randomly selected. The method of data collection in this research was field and library. The data collection tool in the field section was two questionnaires of marital conflict and marital adjustment. To analyze the collected data, first at the descriptive level, using statistical indicators, the demographic characteristics of the sample were described by SPSS software. In inferential statistics, the statistical method used was the test of analysis of covariance. The results showed that the effect of the independent variable of emotional intelligence on the reduction of marital conflicts is statistically significant. And it can be inferred that emotional intelligence training has reduced the marital conflicts of married students of the University of Tehran in the experimental group compared to the control group. Also, the effect of the independent variable of emotional intelligence on marital adjustment was statistically significant. It can be inferred that emotional intelligence training has adjusted the marital adjustment of married students of the University of Tehran in the experimental group compared to the control group.

Keywords: emotional intelligence, marital conflicts, marital compatibility, married students

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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: 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: Sarinra Thongmee, Krittaporn Prakobsaeng, Adithep Mingsuan, Chanyapak Polkhet, Supattra Wongsuk

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The purposes of this research and developmentwasto develop and evaluation of the clinical nursingpractice guideline (CNPG) for the prevention infection during intubation in patient with suspected or confirmedCOVID-19 patient. This study was developed by using the evidencebased practice model of Soukup (2000) asa conceptual framework. The study consisted of 4 steps: 1) situational analysis of intubation service in patientswith confirmed COVID-19; 2) development of the CNPG; 3) apply the NPG to trial; and 4) evaluation of the CNPG. The sample consisted of 52 nurse anesthetists and 25 infected or suspected COVID-19 patients. The research instrument consisted of 1) the CNPG, which was developed by the researchers; 2) the nurses anesthetist opinion questionnaire to the guideline; 3) the evaluation practice form; and 4) the nurse anesthetist knowledge test on nursing care of patients infected with COVID-19. Data were analyzed by using descriptive statistics, and Wilcoxon matched-pairs signed rank test. The results revealed this developed CNPG consists of 4 sections: 1)the CNPG for airborne precautions2) the preparation of anesthetic and intubation equipments3) the roles and duties of the intubation team, 4) the guidelines for intubation in suspected or confirmed COVID-19 patients. The results of CNPG use found that 1)the provider: using NPG in providers revealed that nurse anesthetist had a higher mean of knowledge scores than before using CNPG statistically significant at the 0.05 level (p<0.01) and able to follow the NPG 100% inall activities. The anesthetic team was not infected with COVID-19 from intubation outside the operating room. 2)the client: the patient was safe, with no complications from intubation. Summary CNPG to prevent infection during reintubation of suspected or confirmedCOVID-19patient was appropriate and applicable to practice.

Keywords: clinical nursing practice guideline, prevention of infection, endotracheal intubation, COVID-19

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Authors: Rosa Nadine Danenberg

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In recent years, bottom-up urban development has started growing as an alternative to conventional top-down planning. In large proportions, citizens and communities initiate small-scale interventions; suddenly seeming to form a trend. As a result, more and more cities are witnessing not only the growth of but also an interest in these initiatives, as they bear the potential to reshape urban spaces. Such alternative city-making efforts cause new dynamics in urban governance, with inevitable consequences for the controlled city planning and its administration. The emergence of enabling relationships between top-down and bottom-up actors signals an increasingly common urban practice. Various case studies show that an enabling relationship is possible, yet, how it can be optimally realized stays rather underexamined. Therefore, the seemingly growing worldwide phenomenon of ‘municipal bottom-up urban development’ necessitates an adequate governance structure. As such, the aim of this research is to contribute knowledge to how municipalities can enable citizen-led urban initiatives from a governance innovation perspective. Empirical case-study research in Stockholm and Istanbul, derived from interviews with founders of four citizen-led urban initiatives and one municipal representative in each city, provided valuable insights to possibilities and constraints for enabling practices. On the one hand, diverging outcomes emphasize the extreme oppositional features of both cases (Stockholm and Istanbul). Firstly, both cities’ characteristics are drastically different. Secondly, the ideologies and motifs for the initiatives to emerge vary widely. Thirdly, the major constraints for citizen-led urban initiatives to relate to the municipality are considerably different. Two types of municipality’s organizational structures produce different underlying mechanisms which demonstrate the constraints. The first municipal organizational structure is steered by bureaucracy (Stockholm). It produces an administrative division that brings up constraints such as the lack of responsibility, transparency and continuity by municipal representatives. The second structure is dominated by municipal politics and governmental hierarchy (Istanbul). It produces informality, lack of transparency and a fragmented civil society. In order to cope with the constraints produced by both types of organizational structures, the initiatives have adjusted their organization to the municipality’s underlying structures. On the other hand, this paper has in fact also come to a rather unifying conclusion. Interestingly, the suggested possibilities for an enabling relationship underline converging new urban governance arrangements. This could imply that for the two varying types of municipality’s organizational structures there is an accurate governance structure. Namely, the combination of a neighborhood council with a municipal guide, with allowance for the initiatives to adopt a politicizing attitude is found as coinciding. Especially its combination appears key to redeem varying constraints. A municipal guide steers the initiatives through bureaucratic struggles, is supported by coproduction methods, while it balances out municipal politics. Next, a neighborhood council, that is politically neutral and run by local citizens, can function as an umbrella for citizen-led urban initiatives. What is crucial is that it should cater for a more entangled relationship between municipalities and initiatives with enhanced involvement of the initiatives in decision-making processes and limited involvement of prevailing constraints pointed out in this research.

Keywords: bottom-up urban development, governance innovation, Istanbul, Stockholm

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Authors: Camilo Andrés Agudelo Vélez, Lina María Martínez Sánchez, Isabel Cristina Ortiz Trujillo, Evert Armando Jiménez Cotes, Natalia Perilla Hernández, María de los Ángeles Rodríguez Gázquez, Daniel Duque Restrepo, Felipe Hernández Restrepo, Dayana Andrea Quintero Moreno, Juan José Builes Gómez, Camilo Ruiz Mejía, Ana Lucia Arango Gómez

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Preeclampsia is a clinical complication during pregnancy with high incidence in Colombia; therefore, it is important to evaluate the influence of external conditions and medical interventions, in order to promote measures that encourage improvements in the quality of life. Objective: Determine clinical and sociodemographic variables in women with preeclampsia. Methods: This cross-sectional study enrolled 50 patients with the diagnosis of preeclampsia, from a private institution in Medellin, during 2015. We used the software SPSS ver.20 for statistical analysis. For the qualitative variables, we calculated the mean and standard deviation, while, for ordinal and nominal levels of quantitative variables, ratios were estimated. Results: The average age was 26.8±5.9 years. The predominant characteristics were socioeconomic stratum 2 (48%), students (55%), mixed race (46%) and middle school as level of education (38%). As for clinical features, 72% of the cases were mild preeclampsia, and 22% were severe forms. The most common clinical manifestations were edema (46%), headache (62%), and proteinuria (55%). As for the Gyneco-obstetric history, 8% reported previous episodes of this disease and it was the first pregnancy for 60% of the patients. Conclusions: Preeclampsia is a frequent condition in young women; on the other hand, headache and edema were the most common reasons for consultation, therefore, doctors need to be aware of these symptoms in pregnant women.

Keywords: pre-eclampsia, hypertension, pregnancy complications, pregnancy, abdominal, edema

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), CO2 emissions and gross domestic product (GDP) for Egypt using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests some negative impacts of the CO2 emissions and the coal and natural gas use on the GDP. Conversely, a positive long-run causality from the electricity consumption to the GDP is found to be significant in Egypt during the period. In the short-run, some positive unidirectional causalities exist, running from the coal consumption to the GDP, and the CO2 emissions and the natural gas use. Further, the GDP and the electricity use are positively influenced by the consumption of petroleum products and the direct combustion of crude oil. Overall, the results support arguments that there are relationships among environmental quality, energy use, and economic output in both the short term and long term; however, the effects may differ due to the sources of energy, such as in the case of Egypt for the period of 1980-2010.

Keywords: CO2 emissions, Egypt, energy consumption, GDP, time series analysis

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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: 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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