Search results for: regional features

Authors: Rajkumar Ghosh

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The Chaura Thrust, located in Himachal Pradesh, India, is a prominent geological feature that exhibits characteristics of an out-of-sequence thrust fault. This paper explores the geological setting of Himachal Pradesh, focusing on the Chaura Thrust's unique characteristics, its classification as an out-of-sequence thrust, and the implications of its presence in the region. The introduction provides background information on thrust faults and out-of-sequence thrusts, emphasizing their significance in understanding the tectonic history and deformation patterns of an area. It also outlines the objectives of the paper, which include examining the Chaura Thrust's geological features, discussing its classification as an out-of-sequence thrust, and assessing its implications for the region. The paper delves into the geological setting of Himachal Pradesh, describing the tectonic framework and providing insights into the formation of thrust faults in the region. Special attention is given to the Chaura Thrust, including its location, extent, and geometry, along with an overview of the associated rock formations and structural characteristics. The concept of out-of-sequence thrusts is introduced, defining their distinctive behavior and highlighting their importance in the understanding of geological processes. The Chaura Thrust is then analyzed in the context of an out-of-sequence thrust, examining the evidence and characteristics that support this classification. Factors contributing to the out-of-sequence behavior of the Chaura Thrust, such as stress interactions and fault interactions, are discussed. The geological implications and significance of the Chaura Thrust are explored, addressing its impact on the regional geology, tectonic evolution, and seismic hazard assessment. The paper also discusses the potential geological hazards associated with the Chaura Thrust and the need for effective mitigation strategies in the region. Future research directions and recommendations are provided, highlighting areas that warrant further investigation, such as detailed structural analyses, geodetic measurements, and geophysical surveys. The importance of continued research in understanding and managing geological hazards related to the Chaura Thrust is emphasized. In conclusion, the Chaura Thrust in Himachal Pradesh represents an out-of-sequence thrust fault that has significant implications for the region's geology and tectonic evolution. By studying the unique characteristics and behavior of the Chaura Thrust, researchers can gain valuable insights into the geological processes occurring in Himachal Pradesh and contribute to a better understanding and mitigation of seismic hazards in the area.

Keywords: chaura thrust, out-of-sequence thrust, himachal pradesh, geological setting, tectonic framework, rock formations, structural characteristics, stress interactions, fault interactions, geological implications, seismic hazard assessment, geological hazards, future research, mitigation strategies.

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Authors: Nabat Gojaeva, Mikayil Naghiyev, Sultan Jafarov, Gular Mikayilova

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Chovdar ore area is located in the contact of Dashkesan caldera and Shamkir horst-graben uplift, which comprises the central part of Lok-Karabakh Island arcs of South Caucasus metallogenic province in terms of regional tectonics. One of the main structural features of formation of the Mereh and Aghyokhush group of low sulfidation epithermal gold deposits, locating in the north peripheric part of the ore area, is involving the crossing areas of ore-hosting and ore-forming Pan-Caucasian-direction structurally-compound faults with the meridional, rhombically shaped faults. In addition, another significant feature is the temporally two- or three-stage ore formation. In the first stage -an early phase of Upper Bathonian age, sulfides are the dominant minerals, in the second stage- late ‘productive’ phase of Upper Bathonian age, mainly gold mineralization is formed. Also, in the Upper Jurassic – Lower Cretaceous ages, rarely-encountered Cu-polymetallic ore formations are documented. Finally, in the last stage, the re-dislocation of ore-formation is foreseen in the previously-formed mineralization areas. The faults in the strike and dip directions formed shearing, brecciation, sulfide mineralization aureoles, and hydrothermal alteration zones in the wall rocks along with the local depression blocks. The geological-structural analysis of the area shows that multiple and various morphogenetic volcano-tectonically fault systems have developed in the area. These fault systems have played a trap role for ore-formation in the intersected parts of faults mentioned above. Thus, in the referred parts, mostly predominance of felsic volcanism and metasomatic alteration (silicification, argillitic, etc.) of wall rocks, as well as the products of this volcanism, account for the inclusion of hydrothermal ore-forming fluids along these faults. It is possible to determine temporally and lithological-structural connection between the ore-formation along with local depression blocks and faults as borders for products of felsic volcanism of Upper Cretaceous-Lesser Jurassic ages, in the results of the replacement of hydrothermal alteration zones with relatively low-temperature metasomatic alterations while moving from the felsic parts to the margins, and due to being non-ore bearing intermediate and intermediate-felsic magmatic facies.

Keywords: Aghyokhush, fault, gold deposit, Mereh

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Lawrence Ngalim

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In this paper, we investigate whether the adoption of recent technological advancements in delivering financial services, such as crowdfunding, assists the financially excluded across twenty-seven Sub Saharan Africa (SSA) through entrepreneurship. Results show that even after addressing potential endogeneity issues as much as possible, crowdfunding and entrepreneurial-ventures are strongly associated i.e., crowdfunding translates a 5 – 9 percentage increase on incumbent/prospective individuals who borrowed to enhance/embark on a venture across SSA economies between 2014 to 2017. The study has some implications for regional financial alliance if economies adopt this recent financial technology which offers another financing opportunity that’s unrestricted by territorial boundaries.

Keywords: fintech, finance, entrepreneurship, SSA

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Authors: Irakli Javakhishvili, Tamara Tsutsunava, Giorgi Beridze

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The Caucasus is a component of the Mediterranean collision belt. The Dizi series is situated within the Greater Caucasian region of the Caucasus and crops out in the core of the Svaneti anticlinorium. The series was formed in the continental slope conditions on the southern passive margin of the small ocean basin. The Dizi series crops out on about 560 square km with the thickness 2000-2200 m. The rocks are faunally dated from the Devonian to the Triassic inclusive. The series is composed of terrigenous phyllitic schists, sandstones, quartzite aleurolites and lenses and interlayers of marbleized limestones. During the early Cimmerian orogeny, they underwent regional metamorphism of chlorite-sericite subfacies of greenschist facies. Typical minerals of metapelites are chlorite, sericite, augite, quartz, and tourmaline, but of basic rocks - actinolite, fibrolite, prehnite, calcite, and chlorite are developed. Into the Dizi series, polyphase intrusions of gabbros, diorites, quartz-diorites, syenite-diorites, syenites, and granitoids are intruded. Their K-Ar age dating (176-165Ma) points out that their formation corresponds to the Bathonian orogeny. The Dizi series is well-studied geologically, but very complicated processes of its regional and contact metamorphisms are insufficiently investigated. The aim of the authors was a detailed study of contact metamorphism processes of the series rocks. Investigations were accomplished applying the following methodologies: finding of key sections, a collection of material, microscopic study of samples, microprobe and structural analysis of minerals and X-ray determination of elements. The Dizi series rocks formed under the influence of the Bathonian magmatites on metapelites and carbonate-enriched rocks. They are represented by quartz, biotite, sericite, graphite, andalusite, muscovite, plagioclase, corundum, cordierite, clinopyroxene, hornblende, cummingtonite, actinolite, and tremolite bearing hornfels, marbles, and skarns. The contact metamorphism aureole reaches 350 meters. Biotite is developed only in contact-metamorphosed rocks and is a rather informative index mineral. In metapelites, biotite is formed as a result of the reaction between phengite, chlorite, and leucoxene, but in basites, it replaces actinolite or actinolite-hornblende. To study the compositional regularities of biotites, they were investigated from both - metapelites and metabasites. In total, biotite from the basites is characterized by an increased of titanium in contrast to biotite from metapelites. Biotites from metapelites are distinguished by an increased amount of aluminum. In biotites an increased amount of titanium and aluminum is observed as they approximate the contact, while their magnesia content decreases. Metapelite biotites are characterized by an increased amount of alumina in aluminum octahedrals, in contrast to biotite of the basites. In biotites of metapelites, the amount of tetrahedric aluminum is 28–34%, octahedral - 15–26%, and in basites tetrahedral aluminum is 28–33%, and octahedral 7–21%. As a result of the study of minerals, including biotite, from the contact-metamorphosed rocks of the Dizi series three exocontact zones with corresponding mineral assemblages were identified. It was established that contact metamorphism in the aureole of the Dizi series intrusions is going on at a significantly higher temperature and lower pressure than the regional metamorphism preceding the contact metamorphism.

Keywords: biotite, contact metamorphism, Dizi series, the Greater Caucasus

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: A. Hameed, N. Upreti, P. Srivastava

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Main objective the present study is to investigate microscopic, sub-microscopic, clay mineralogical and geochemical characteristics of three calcic soil profiles from the western Thar Desert for the last 30 ka paleoclimatic information. Thin-sections of the soils show weakly to moderately developed pedofeatures dominated by powdery to well-indurated pedogenic calcium carbonate. Sub-microscopy of the representative calcretes show extensive growth of fibrous palygorskite in pore spaces of micritic and sparitic nodules. XRD of the total clay ( < 2 µm) and fine clay ( < 0.2 µm) fractions of the soils show dominance of smectite, palygorskite, chlorite, mica, kaolinite and small amounts of quartz and feldspar. Formation of the palygorskite is attributed to pedogenic processes associated with Bw, Bss and Bwk horizons during drier conditions over the last 30 ka. Formation of palygorskite was mainly favoured by strongly evaporating percolating water and precipitation of secondary calcite, high pH (9-10), high Mg, Si and low Al activities during pedogenesis. Age estimate and distribution of calcretes, palygorskite, and illuvial features indicate fluctuating monsoonal strength during MIS3-MIS1 stages. The pedogenic features in calcic soils of western Thar suggest relatively arid conditions during MIS3-MIS2 transition and LGM time that changed to relatively wetter conditions during post LGM time and again returned to dry conditions at ~4 ka in MIS1.

Keywords: palygorskite, clay minerals, Thar, aridisol, late quaternary

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Authors: Kambiz Teimour Najad

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The basic methodology of GPR involves the use of a transmitting antenna to send electromagnetic waves into the subsurface, which then bounce back to the surface and are detected by a receiving antenna. The transmitter and receiver antennas are typically placed on the ground surface and moved across the area of interest to create a profile of the subsurface. The GPR system consists of a control unit that powers the antennas and records the data, as well as a display unit that shows the results of the survey. The control unit sends a pulse of electromagnetic energy into the ground, which propagates through the soil or rock until it encounters a change in material or structure. When the electromagnetic wave encounters a buried object or structure, some of the energy is reflected back to the surface and detected by the receiving antenna. The GPR data is then processed using specialized software that analyzes the amplitude and travel time of the reflected waves. By interpreting the data, GPR can provide information on the depth, location, and nature of subsurface features and structures. GPR has several advantages over other geophysical survey methods, including its ability to provide high-resolution images of the subsurface and its non-invasive nature, which minimizes disruption to the site. However, the effectiveness of GPR depends on several factors, including the type of soil or rock, the depth of the features being investigated, and the frequency of the electromagnetic waves used. In environmental hazard assessments, GPR can be used to detect buried structures, such as underground storage tanks, pipelines, or utilities, which may pose a risk of contamination to the surrounding soil or groundwater. GPR can also be used to assess soil stability by identifying areas of subsurface voids or sinkholes, which can lead to the collapse of the surface. Additionally, GPR can be used to map the extent and movement of groundwater contamination, which is critical in designing effective remediation strategies. the methodology of GPR in environmental hazard assessments involves the use of electromagnetic waves to create high of the subsurface, which are then analyzed to provide information on the depth, location, and nature of subsurface features and structures. This information is critical in identifying and mitigating environmental hazards, and the non-invasive nature of GPR makes it a valuable tool in this field.

Keywords: GPR, hazard, landslide, rock fall, contamination

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Reshaa Alruwaili

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The primary aim of this study was to examine the hypothesis presented by Self Determination theory which suggests that autonomy impacts positively the expression of love. Other hypotheses were also examined which suggest that other variables explain the expression of love, including: dyadic adjustment (dyadic consensus, dyadic satisfaction and dyadic cohesion), couple satisfaction, age, gender, the length of marriage, number of children and attachment styles. The participants were Saudi couples, which provided the opportunity to consider the influence of Saudi culture on the expression of love. A questionnaire was employed to obtain measures of all the relevant variables, including a measure of expression of love that was built from 27 items, constituting verbal, physical and caring features, and a measure of autonomy based on three features: authorship, interest-taking and susceptibility. Data were collected from both members of 34 Saudi couples. Descriptive analysis of both expression of love and autonomy was conducted. Correlation and regression were used to assess the relationships between expression of love and autonomy and other variables. Results indicated that Saudi couples who most often express their love tend to be more than somewhat autonomous. Not much difference was found between husbands and wives in expressing love, although wives were slightly more autonomous than husbands. Expression of love was enhanced by the autonomy of the participants to a greater extent when dyadic satisfaction was controlled, since the latter was negatively correlated with autonomy and had no effect on the expression of love. Basic psychological needs, dyadic consensus and dismissive-avoidant attachment improve the expression of love, while it is decreased by the number of children.

Keywords: autonomy, determination theory, expression of love, dyadic adjustment

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Authors: L. Bendifallah, S. Doumandji, K. Louadi, S. Iserbyt, F. Acheuk

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Due to their ecological key position and diversity, plant-bee relationships constitute excellent models to understand the processes of food specialisation. The purpose of this study is to define and identify the most important species of bees foraging broadbean flowers, we estimated morphological, phonological and behavioural features. We discuss the results by considering the food specialisation level of the visitor. In the studied populations (Algiers, Algeria), visiting bees belong to four different genus: Apis, Andrena, Eucera and Xylocopa. Eucera is foraging broad beans flowers during months of April, May. The genus Andrena and Xylocopa were found on weeds after the flowering period of beans. The two species have not a preferred type of vegetation compared to Eucera. The main pollinators were generalist bees such as Apis mellifera L. and Xylocopa pubescens Spinola (Apidae), and specialist bees such Eucera numida Lep. (Apidae). The results show that no one of the studied species, neither the specialist, nor the generalist ones, share adaptative morphological or behavioural features that may improve foraging on Vicia faba. However, there is a narrow synchronisation between the daily and yearly phenologies of Eucera numida and those of V. faba. This could be an adaptation of the specialist bee to its host plant. Thus, the food specialisation of Eucera numida, as for most specialist bees, would be more linked to its adapted phenology than to an adapted morphology.

Keywords: Vicia faba, bees, pollinators, Algeria

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Authors: Aleksandr S. Ermolenko

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Allometry is an important factor of morphological integration, contributing to the organization of the phenotype and its variability. The allometric change in the shape of the hand is particularly important in primate evolution, as the hand has important taxonomic features. Some of these features are known to parts with the shape, especially the ratio of the lengths of the index and ring fingers (2d: 4d ratio). The hand is a fairly well-studied system in the context of the evolutionary development of complex morphological structures since it consists of various departments (basipodium, metapodium, acropodium) that form a single structure –autopodium. In the present study, we examined the allometric variability of acropodium. We tested the null hypothesis that there would be no difference in allometric variation between the two components. Geometric morphometry based on a procrustation of 16 two-dimensional (2D) landmarks was analyzed using multivariate shape-by-size regressions in samples from 100 people (50 men and 50 women). The results obtained show that men have significantly greater allometric variability for the ring finger (variability in the transverse axis prevails), while women have significantly greater allometric variability for the index finger (variability in the longitudinal axis prevails). The influence of the middle finger on the shape of the hand is typical for both men and women. The influence of the little finger on the shape of the hand, regardless of gender, was not revealed. The results of this study support the hypothesis that allometry contributes to the organization of variation in the human hand.

Keywords: human hand, size and shape, 2d:4d ratio, geometric morphometry

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Authors: Elisabeth Maidl

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The interdependence of climate change and natural hazard goes along with large uncertainties regarding future risks. Regional stakeholders, experts in natural hazards management and scientists have specific knowledge, resp. mental models on such risks. This diversity of views makes it difficult to find common and broadly accepted prevention measures. If the specific knowledge of these types of actors is shared in an interactive knowledge production process, this enables a broader and common understanding of complex risks and allows to agree on long-term solution strategies. Previous studies on mental models confirm that actors with specific vulnerabilities perceive different aspects of a topic and accordingly prefer different measures. In bringing these perspectives together, there is the potential to reduce uncertainty and to close blind spots in solution finding. However, studies that examine the mental models of regional actors on future concrete mass movement risks are lacking so far. The project tests and evaluates the feasibility of knowledge co-creation for the anticipatory prevention of climate change-induced mass movement risks in the Alps. As a key element, mental models of the three included groups of actors are compared. Being integrated into the research program Climate Change Impacts on Alpine Mass Movements (CCAMM2), this project is carried out in two Swiss mountain regions. The project is structured in four phases: 1) the preparatory phase, in which the participants are identified, 2) the baseline phase, in which qualitative interviews and a quantitative pre-survey are conducted with actors 3) the knowledge-co-creation phase, in which actors have a moderated exchange meeting, and a participatory modelling workshop on specific risks in the region, and 4) finally a public information event. Results show that participants' mental models are based on the place of origin, profession, believes, values, which results in narratives on climate change and hazard risks. Further, the more intensively participants interact with each other, the more likely is that they change their views. This provides empirical evidence on how changes in opinions and mindsets can be induced and fostered.

Keywords: climate change, knowledge-co-creation, participatory process, natural hazard risks

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Authors: Endalew Fufa Kufi

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Every married person aspires to be a parent regardless of the situation in which s/he lives. Such aspiration meets with reality when the destined parent is able to give adequate supports and services to his/her children, whether the latter are got by birth or through adoption. The adequacy of services parents provide their children is both enriched and tempted by the work on which they involve. On the one hand, parents need to work and earn a living in order to support their family. On the other hand, they must spend most of their time outside home to do the work, which shortens the time and might they spare to care for their children. Where the sufficiency of services parents owe their children could be ascertained by in terms of life skills, physical care and related provisions, the role of working fathers and mothers in providing such supports could be diverse across cultures and work traditions. Hence, this research deals with the investigation of working mothers’ parental practices, challenges they face in providing parental services and the implication for the future progress of the parents and their children. Target of the study will be Arsi University in Oromia Regional State of Ethiopia. Descriptive survey design in holding the research, and data for the research will be collected in the form of experiential self-report from 150 working mothers selected from the entire working women population of Colleges of Agriculture and Environmental Studies and College of Health Sciences through stratified random-sampling. Instruments of data collection will be closed and open-ended questionnaire. Complementary data will also be collected from purposively selected samples through semi-structured interview. Data for the research will be collected through questionnaire first and then through interview. Data analysis will also follow the same procedure. The collected data will systematically be organized and statistically and thematically analyzed in order to come up with indicative findings. The overarching thesis is that, working mothers in the study area bear a lot of responsibilities both at home and at work place which leave them very little time for parenting services. Unless due attention is given to the way they can spare time for their children, they are more likely to be tense between work-life and family care services, which tempt them in different directions.

Keywords: challenges, mothers, practices, university, working

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Authors: Mohamed Elhadi M. Sharif, Mona Masood

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The usage of e-health facilities is seen to be the first priority by the Libyan government. As such, this paper focuses on how the key factors or elements of working size in terms of technological availability, structural environment, and other competence-related matters may affect nurses’ sharing of knowledge in e-health. Hence, this paper investigates learning readiness assessment to raise e-health for Libyan regional hospitals by using e-health services in nursing education.

Keywords: Libyan nurses, e-learning readiness, e-health, nursing education

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Authors: Zdzisław Kobos, Robert Jędrys, Zbigniew Wochyński

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Motor activity and good health are sine qua non determinants of a proper practice of the profession, especially aviation. Therefore, candidates to the aviation are selected according their psychomotor ability by both specialist medical commissions. Moreover, they must past an examination of the physical fitness. During the studies in the air force academy, eye-hand coordination is formed in two stages. The future aircraft pilots besides all-purpose physical education must practice specialist training on SAGI. Training includes: looping, aerowheel, and gyroscope. Aim of the training on the above listed apparatuses is to form eye-hand coordination during the tasks in the air. Such coordination is necessary to perform various figures in the real flight. Therefore, during the education of the future pilots, determinants of the effective ways of this important parameter of the human body functioning are sought for. Several studies of the sport psychology indicate an important role of the temperament as a factor determining human behavior during the task performance and acquiring operating skills> Polish psychologist Jan Strelau refers to the basic, relatively constant personality features which manifest themselves in the formal characteristics of the human behavior. Temperament, being initially determined by the inborn physiological mechanisms, changes in the course of maturation and some environmental factors and concentrates on the energetic level and reaction characteristics in time. Objectives. This study aimed at seeking a relationship between temperamental features and eye-hand coordination formation during training on SAGI. Material and Methods: Group of 30 students of pilotage was examined in two situations. The first assessment of the eye-hand coordination level was carried out before the beginning of a 30-hour training on SAGI. The second assessment was carried out after training completion. Training lasted for 2 hours once a week. Temperament was evaluated with The Formal Characteristics of Behavior − Temperament Inventory (FCB-TI) developed by Bogdan Zawadzki and Jan Strelau. Eye-hand coordination was assessed with a computer version of the Warsaw System of Psychological Tests. Results: It was found that the training on SAGI increased the level of eye-hand coordination in the examined students. Conclusions: Higher level of the eye-hand coordination was obtained after completion of the training. Moreover, a relationship between eye-hand coordination level and selected temperamental features was statistically significant.

Keywords: temperament, eye-hand coordination, pilot, SAGI

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Authors: Yahya Toyin Muritala, Nonglaksana Kama, Ahmad Yani

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The aim of the paper is to investigate various linguistic techniques in enhancing and facilitating the acquisition of the practical knowledge of Arabic grammatical structuring among non-Arab learners of the standard classical Arabic language in non-Arabic speaking academic settings in the course of the current growth of the internationalism and cultural integration in some higher institutions. As the nature of the project requires standard investigations into the unique principal features of Arabic structurings and implications, the findings of the research work suggest some principles to follow in solving the problems faced by learners while acquiring grammatical aspects of Arabic language. The work also concentrates on the the structural features of the language in terms of inflection/parsing, structural arrangement order, functional particles, morphological formation and conformity etc. Therefore, grammatical aspect of Arabic which has gone through major stages in its early evolution of the classical stages up to the era of stagnation, development and modern stage of revitalization is a main subject matter of the paper as it is globally connected with communication and religion of Islam practiced by millions of Arabs and non-Arabs nowadays. The conclusion of the work shows new findings, through the descriptive and analytical methods, in terms of teaching language for the purpose of effective global communication with focus on methods of second language acquisitions by application.

Keywords: language structure, Arabic grammar, classical Arabic, intercultural communication, non-Arabic speaking environment and prospects

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Authors: Chuan-Ming Tung, Jin-Cheng Fu, Chia-En Feng

Abstract:

In recent years, the rapid development of urban land in Taiwan has led to the constant increase of the areas of impervious surface, which has increased the risk of waterlogging during heavy rainfall. Therefore, in recent years, promoting runoff allocation responsibilities has often been used as a means of reducing regional flooding. In this study, the single catchment area covering both urban and rural land as the study area is discussed. Based on Storm Water Management Model, urban and rural land in a single catchment area was explored to develop the runoff allocation responsibilities according to their respective control regulation on land use. The impacts of runoff increment and reduction in sub-catchment area were studied to understand the impact of highly developed urban land on the reduction of flood risk of rural land at the back end. The results showed that the rainfall with 1 hour short delay of 2 years, 5 years, 10 years, and 25 years return period. If the study area was fully developed, the peak discharge at the outlet would increase by 24.46% -22.97% without runoff allocation responsibilities. The front-end urban land would increase runoff from back-end of rural land by 76.19% -46.51%. However, if runoff allocation responsibilities were carried out in the study area, the peak discharge could be reduced by 58.38-63.08%, which could make the front-end to reduce 54.05% -23.81% of the peak flow to the back-end. In addition, the researchers found that if it was seen from the perspective of runoff allocation responsibilities of per unit area, the residential area of urban land would benefit from the relevant laws and regulations of the urban system, which would have a better effect of reducing flood than the residential land in rural land. For rural land, the development scale of residential land was generally small, which made the effect of flood reduction better than that of industrial land. Agricultural land requires a large area of land, resulting in the lowest share of the flow per unit area. From the point of the planners, this study suggests that for the rural land around the city, its responsibility should be assigned to share the runoff. And setting up rain water storage facilities in the same way as urban land, can also take stock of agricultural land resources to increase the ridge of field for flood storage, in order to improve regional disaster reduction capacity and resilience.

Keywords: runoff allocation responsibilities, land use, flood mitigation, SWMM

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Authors: Ashfaq Khan, Aftab Khan, Mushtaq Khan, Sarem Sattar, Mohammad A Sheikh, Lin Li

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Chip removal processes are one of key processes of the manufacturing industry where chip removal is conducted by tool inserts of exceptionally hard materials. Tungsten carbide has been extensively used as tool insert for machining processes involving chip removal processes. These hard materials are generally fabricated by single step sintering process as further modification after fabrication in these materials cannot be done easily. Advances in tool surface modification have revealed that advantages such as improved tribological properties and extended tool life can be harnessed from the same tool by texturing the tool rake surface. Moreover, it has been observed that the shape and location of the texture also influences the behavior. Although texturing offers plentiful advantages the challenge lies in the generation of textures on the tool surface. Extremely hard material such as diamond is required to process tungsten carbide. Laser is unique processing tool that does not have a physical contact with the material and thus does not wear. In this research the potential of utilizing laser for texturing of tungsten carbide to develop custom features would be studied. A parametric study of texturing of Tungsten Carbide with a femtosecond laser would be conducted to investigate the process parameters and establish the feasible processing window. The effect of fluence, scan speed and number of repetition would be viewed in detail. Moreover, the mechanism for the generation of features would also be reviewed.

Keywords: laser, texturing, femtosecond, tungsten carbide

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Authors: Justyna Skrzyńska, Zdzisław Kobos, Zbigniew Wochyński

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The assessment of characterologic type is an essential element which decides about the proper task performance in the Air Forces. The aim of the research was to specify the percentage distribution of characterologic features by cadets studying particular courses in Polish Air Force Academy with the use of questionnaire. 34 first-year cadets chosen by lot and disunited into aircrafts pilots (N-10), helicopter pilots (N-13) and navigators(N-11) participated in the research. All of the questioned have had their psychomotor education examined in Military Aviation Medicine Institute in Warsaw, Poland. Moreover all of them are characterised by very good fitness. In the research, an anonymous poll(based on Myers-Briggs Type Indicator) appraising cadets’ characterologic type has been used. Cadets were provided with the same accommodation and nutrition. The findings have shown that percentage distribution was diversified, however it could be distinctly observed that most of future helicopter pilots (69%) are introverts whereas the majority of aircrafts pilots (70%) and navigators (100%) are extraverts. Moreover, it was also observed that 70% of cadets studying aircrafts pilotage run regular lifestyle and have judging skill according to Myers-Briggs Type Indicator. In future navigators group, 73% of students do not have this characteristic. The research has shown that cadets studying pilotage are more likely to demonstrate the characteristics which are essential for a performance of the important tasks in pilots environment than the cadets studying navigation.

Keywords: pilot, Myers-Briggs Type indicator, questionnaire research, cadets, psychomotor education

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Authors: Isaac Owusu Asante, Yushi Jiang, Hailin Tao

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Live streaming marketing, the new electronic commerce element, became an optional marketing channel following the COVID-19 pandemic. Many sellers have leveraged the features presented by live streaming to increase sales. Studies on live streaming have focused on gaming and consumers’ loyalty to brands through live streaming, using interview questionnaires. This study, however, was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during live streaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study introduces a new way of measuring interactions in live streaming commerce and proposes a way to manually gather data on consumer behaviors in live streaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

Abstract:

Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Zameerpal Kaur

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Ecocriticism comes into existence in 1990s, it tries to explore the relationship of literature with the natural world and further it examines the role that natural surroundings and environment play in the minds of the creative writers during their imagination and creative process. The present study is an attempt to focus on the comparative ecocritical analysis of Shiv Kumar Batalvi and Surjit Patar’s selected poetry in the theoretical framework of ecocriticism in order to shed light on the poet’s vigilant views about the relationship of human life and nature. Shiv Kumar Batalvi is a renowned modern Punjabi poet. He is essentially a poet of nature and love. His opinions towards nature support his position to be considered as a major representative of recent environmental issues and ecocritical concerns in Punjabi literature. He is one of the most outstanding modern Punjabi poets, is endowed with the most artistic temperament in whose poetry nature always has a dominating existence. He seems to consciously portray the scenes of natural surroundings into his poetry; in fact the titles of his poems in themselves signify his love for the nature. Surjit Patar, an imminent modern Punjabi poet tries to present a different picture of nature into his poems; he also uses to write poems about contemporary problems. Surjit Patar’s radical quarrel with the modern cultural context makes him reject all the absolutes and finalities in the form of transcendental reason and religion, history and evolution, he freely writes about the deterioration of nature at selfish materialistic society. He is modern poet who weaves the natural imagery with the syntax of his poems. Patar’s work reflects a universal voice that is dribbled with nuanced humanism and a sense of modernity that seemed neither dated, nor trapped in regional boundaries. Through his poetry he has given a voice to the fragile, disrupting borders, disturbing the status quo. An attempt to analyse the poetic works of above said poets from ecocritical perspective as well as especially focussing on various aspects of ecocriticism like ecocentric ethics, ecoaesthetics, anthropomorphism etc. has been made throughout the comparative study of the selected works.

Keywords: anthropocentrism, degradation, environment and literature, nature

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Taerim Kim, Shin Ahn, Chang Hwan Sohn, Dong Woo Seo, Won Young Kim

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Object: Reversible cerebral vasospasm syndrome (RCVS) remains an underrated cause of thunderclap headache which shares similar history of the ‘worst-ever’ headache with subarachnoid hemorrhage (SAH) to the emergency physicians. This study evaluated the clinical manifestations, radiological features, and outcomes of patients with RCVS so that the physicians could raise the high index of suspicion to detect RCVS in more patients with thunderclap headache before having life-threatening complications. Methods: The electric medical records of 18 patients with diagnostic criteria of RCVS at the emergency department (ED) between January 2013 and December 2014 were retrospective reviewed. Results: The mean age was 50.7 years, and 80% were women. Patients with RCVS visit an average of 4.7 physicians before receiving an accurate diagnosis and mean duration of symptom until diagnosis is 9.3 days. All patients except one experienced severe headache, from 8 to 10 pain intensity on a numerical rating scale (NRS). 44% of patients had nausea as an associated symptom, 66% of patients experienced worsening of headache while gagging, leaning forward, defecating, urinating or having sex. The most frequently affected vessels are middle cerebral arteries demonstrating the characteristic diffuse “string of beads” appearance. Four patients had SAH as a complication. Conclusion: Patients with RCVS have a unique set of clinical and imaging features. Emergency physicians should raise the high index of suspicion to detect RCVS in more patients with thunderclap headache before life-threatening complications.

Keywords: headache, thunderclap, subarachnoid haemorrhage, stroke

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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Authors: Sarah Hamdan Al-Jahdali, Khaled Alsaad, Abdullah Al-Sayyari

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Objectives: To study the prevalence, clinicopathological features, risk factors and outcome of biopsy proven polyoma (BK) virus infection among Saudi kidney transplant recipients and compare them to negative BK virus group. Methods: We retrospectively reviewed the charts of all the patients with biopsy-proven polyoma (BK) virus infection in King Abdulaziz Medical City in Riyadh between 2005 and 2011. The details of clinical presentation, the indication for kidney biopsy, the laboratory findings at presentation, the natural history of the disease, thepathological findings, the prognosis as well as the response to therapy were all recorded. Results: Kidney biopsy was performed in 37 cases of unexplained graft dysfunction. BK virus was found in 10 (27%). Out of those 10, 3 (30%) ended with graft failure. BK virus occurred in all patients who received ATG induction therapy 100% versus 59.3% in the non BK virus patients (p=0.06). Furthermore, the risk of BK virus was much less in those who received acyclovir as an anti-viral prophylaxis as compared to those who did not receive it (p=0.01). Also, patients with BK virus weighed much less (mean 46.7±20.6 Kgs) than those without BK virus at time of transplantation (mean 64.3±12.1). Graft survival was better among deceased donor kidneys compared to living ones (P=0.016) and with older age (P=0.005). Conclusion: Our findings suggest the involvement of ATG induction therapy, the lack of antiviral prophylaxis therapy and lower weight at transplant as significant risk factors for the development of BK virus infection.

Keywords: BKVAN, BKV, kidney transpant, Saudi Arabia

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