Search results for: Grey prediction model

Authors: Jessica Lynne Hicksted

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Disability discrimination is a long-standing issue that, despite protections, continues to result in unemployment, underemployment, and lack of advancement for disabled persons. Visible stigma is researched substantially; however, less is known about the impact of stigma associated with identities that can be concealed. Although researchers have investigated this issue, currently there is no tool to measure this phenomenon. The purpose of this quantitative study was to create and validate a new tool to measure stigma associated with invisible disabilities. The study is grounded by Roberts’ conceptual model of professional image construction integrating social identity, impression management, and organizational behavior; Meisenbach’s stigma management communication theory addressing the vulnerabilities and resilience to stigma communication by focusing on how individuals encounter and react to perceived stigmas; and Kelley and Michela’s causal attribution theory. Participants included 1,412 adults in the United States 18 years or older currently employed or who have been employed within the last 5 years. Confirmatory factor analysis of the new Workplace Invisible Disabilities Experience scale showed excellent fit of the factor structure to the data, X₂/df = 1.855, CFI = .955, RMSEA = .045, p = .0001. The scale has three subscales, Ableism, Advocacy, and Acceptance, with excellent internal consistency reliability. Total score, Advocacy, and Acceptance were associated with intention to disclose. Implications for positive social change include helping organizations to understand the extent of invisible disability stigma that can help improve workplace performance and satisfaction.

Keywords: invisible disabilities, accommodations, acceptance, social change, workplace inclusion

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Authors: Mehrnoosh Azimi Sanavi, Hamed Ghazvini, Mehryar Zargari, Hossein Ghalehnoei, Zahra Hosseini-khah

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Objectives: Calcium Voltage-Gated Channel Subunit Alpha1 C (CACNA1C) is one of the most important genes associated with schizophrenia. Methods: 45 male Wistar rats were divided into 5 groups: saline, control, ketamine, clozapine, and risperidone. Animals in ketamine, risperidone, and clozapine groups received ketamine (30 mg/ kg-i.p.) for 10 days. After the last injection of ketamine, we started injecting clozapine (7.5 mg/kg-i.p.) risperidone (1 mg/kg-i.p.) for up to 28 days. Twenty-four hours after the last injection, open field, social interaction, and elevated plus-maze tests, and gene expression in the hippocampus were performed. Results: The results of the social interaction test revealed a significant decrease in cumulative time with ketamine compared with the saline group and an increase with clozapine and risperidone compared with the ketamine group. Moreover, results from the elevated plus-maze test demonstrated a critical decrease in open-arm time and an increase in close-arm time with ketamine compared with saline, as well as an increase in open-arm time with risperidone compared with ketamine. Further results revealed a significant increase in rearing and grooming with ketamine compared to saline, as well as a decrease with risperidone and clozapine compared to ketamine. There were no significant differences in CACNA1C gene expression between groups in the rat hippocampus. In brief, the results of this study indicated that clozapine and risperidone could partially improve cognitive impairments in the rat. However, our findings demonstrated that this treatment is not related to CACNA1C gene expression.

Keywords: schizophrenia, ketamine, clozapine, risperidone

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Authors: H. M. Imam, H. M. Rezk, A. F. Tohamy

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Background: Human umbilical cord blood (HUCB) is considered as a unique source for stem cells. HUCB contain different types of progenitor cells which could differentiate into hepatocytes. Aims: To investigate the potential of rat's liver damage repair using human umbilical cord mesenchymal stem cells (hUCMSCs). We investigated the feasibility for hUCMSCs in recovery from liver damage. Moreover, investigating fibrotic liver repair and using the CCl4-induced model for liver damage in the rat. Methods: Rats were injected with 0.5 ml/kg CCl4 to induce liver damage and progressive liver fibrosis. hUCMSCs were injected into the rats through the tail vein; Stem cells were transplanted at a dose of 1×106 cells/rat after 72 hours of CCl4 injection without receiving any immunosuppressant. After (6 and 8 weeks) of transplantation, blood samples were collected to assess liver functions (ALT, AST, GGT and ALB) and level of Procollagen III as a liver fibrosis marker. In addition, hepatic tissue regeneration was assessed histopathologically and immunohistochemically using antihuman monoclonal antibodies against CD34, CK19 and albumin. Results: Biochemical and histopathological analysis showed significantly increased recovery from liver damage in the transplanted group. In addition, HUCB stem cells transdifferentiated into functional hepatocytes in rats with hepatic injury which results in improving liver structure and function. Conclusion: Our findings suggest that transplantation of hUCMSCs may be a novel therapeutic approach for treating liver fibrosis. Therefore, hUCMSCs are a potential option for treatment of liver cirrhosis.

Keywords: carbon tetra chloride, liver fibrosis, mesenchymal stem cells, rat

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Authors: Prerna Mohan Saxena, Avni Joshi, Raju K Parasher

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Disability is a state of decreased functioning associated with disease, disorder, injury, or other health condition, which in the context of one’s environment is experienced as an impairment, activity limitation, or participation restriction. With the concept of disability evolving over the years, the current ICF model of disability has integrated this concept into a comprehensive whole of multiple dimensions of human functioning, including biological, psychological, social, and environmental aspects. Wheelchair basketball is one of the greatest examples of adapted sports for the disabled. Through this study, we aim to evaluate the functional performance and self-esteem levels in differently-abled pediatric wheelchair basketball players, providing an insight on their abilities and deficits and how they can be worked on at a larger level to improve overall performance. The study was conducted on 9 pediatric wheelchair basketball players at Amar Jyoti school for inclusive education Delhi their physical performance was assessed using a battery of tests, and physical self esteem was assessed using the Physical self-description instrument (PSDQ-S). Results showed that 9 participants age ranged between 10-21 years, mostly males with BMI ranging between 16.7 to 28.9 kg/m2 most of them had the experience of 5 to 6 years of playing the sport. The data showed physical performance in accordance to years of experience of playing, physical self esteem showed a different perspective, with experience players scoring less on it. This study supports a multidimensional construct of physical performance and physical self-esteem, suggesting that both may be applied on the wheelchair basketball players at competitive levels.

Keywords: ase series, physical performance, physical self-esteem, wheelchair basketball

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Authors: Sarina Zainab Shirazi

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Abstract— With the advent of globalization, different countries have liberalized their trade policies to enhance economic integration and developmental processes but the advantages accrued vary greatly from region to region. This study specifically examines European Union (EU) and Association for South East Asian Nations (ASEAN), two regions that show contrasting integration patterns. EU shows most successful integrations versus the slower paced integration in the ASEAN region. A comprehensive panel data empirical investigation of EU and ASEAN in the context of economy size, geographical distances, language, ethnicity, common border and regional trade agreements (RTA) is conducted for a period of 1985 – 2015. The empirical investigation through the augmented gravity equation shows that the real effectiveness for enhanced intra-regional trade is significant when specific examination of export and import components is conducted in the presence of non-tariff barriers. These barriers surface in the form of terms of trade openness, inflation, exchange rate, common borders, common language, ethnic similarity, and presence of a formal regional trade agreement (RTA). Thus, these factors can be utilized by the EU and ASEAN regions in order to formulate effective policy tools to enhance trade within their respective spheres of influence.

Keywords: Association for South East Asian Nations, European Union, Gravity Model, Regional Trade

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Authors: Khyamling Parane, B. M. Prabhu Prasad, Basavaraj Talawar

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Fast simulations are critical in reducing time to market in CMPs and SoCs. Several simulators have been used to evaluate the performance and power consumed by Network-on-Chips. Researchers and designers rely upon these simulators for design space exploration of NoC architectures. Our experiments show that simulating large NoC topologies take hours to several days for completion. To speed up the simulations, it is necessary to investigate and optimize the hotspots in simulator source code. Among several simulators available, we choose Booksim2.0, as it is being extensively used in the NoC community. In this paper, we analyze the cache and memory system behaviour of Booksim2.0 to accurately monitor input dependent performance bottlenecks. Our measurements show that cache and memory usage patterns vary widely based on the input parameters given to Booksim2.0. Based on these measurements, the cache configuration having least misses has been identified. To further reduce the cache misses, we use software optimization techniques such as removal of unused functions, loop interchanging and replacing post-increment operator with pre-increment operator for non-primitive data types. The cache misses were reduced by 18.52%, 5.34% and 3.91% by employing above technology respectively. We also employ thread parallelization and vectorization to improve the overall performance of Booksim2.0. The OpenMP programming model and SIMD are used for parallelizing and vectorizing the more time-consuming portions of Booksim2.0. Speedups of 2.93x and 3.97x were observed for the Mesh topology with 30 × 30 network size by employing thread parallelization and vectorization respectively.

Keywords: cache behaviour, network-on-chip, performance profiling, vectorization

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Authors: Waqed H. Almohammed, Mohammed Y. Fattah, Sajjad E. Rasheed

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Dynamic traffic loads cause deformation of underground pipes, resulting in vehicle discomfort. This makes it necessary to reinforce the layers of soil above underground pipes. In this study, the subbase layer was reinforced. Finite element software (PLAXIS 3D) was used to in the simulation, which includes geocell reinforcement, vehicle loading, soil layers and Glass Fiber Reinforced Plastic (GRP) pipe. Geocell reinforcement was modeled using a geogrid element, which was defined as a slender structure element that has the ability to withstand axial stresses but not to resist bending. Geogrids cannot withstand compression but they can withstand tensile forces. Comparisons have been made between the numerical models and experimental works, and a good agreement was obtained. Using the mathematical model, the performance of three different pipes of diameter 600 mm, 800 mm, and 1000 mm, and three different vehicular speeds of 20 km/h, 40 km/h, and 60 km/h, was examined to determine their impact on surface settlement and vertical pressure at the pipe crown for two cases: with and without geocell reinforcement. The results showed that, for a pipe diameter of 600 mm under geocell reinforcement, surface settlement decreases by 94 % when the speed of the vehicle is 20 km/h and by 98% when the speed of the vehicle is 60 km/h. Vertical pressure decreases by 81 % when the diameter of the pipe is 600 mm, while the value decreases to 58 % for a pipe with diameter 1000 mm. The results show that geocell reinforcement causes a significant and positive reduction in surface settlement and vertical stress above the pipe crown, leading to an increase in pipe safety.

Keywords: dynamic loading, finite element, geocell-reinforcement, GRP pipe, PLAXIS 3D, surface settlement

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: M. S. Ahmed, F. A. Mohammad

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This paper focuses on the dynamic behavior of reinforced concrete (RC) slabs. Therefore, the theoretical modal analysis was performed using two different types of boundary conditions. Modal analysis method is the most important dynamic analyses. The analysis would be modal case when there is no external force on the structure. By using this method in this paper, the effects of freely and simply supported boundary conditions on the frequencies and mode shapes of RC square slabs are studied. ANSYS software was employed to derive the finite element model to determine the natural frequencies and mode shapes of the slabs. Then, the obtained results through numerical analysis (finite element analysis) would be compared with an exact solution. The main goal of the research study is to predict how the boundary conditions change the behavior of the slab structures prior to performing experimental modal analysis. Based on the results, it is concluded that simply support boundary condition has obvious influence to increase the natural frequencies and change the shape of mode when it is compared with freely supported boundary condition of slabs. This means that such support conditions have direct influence on the dynamic behavior of the slabs. Thus, it is suggested to use free-free boundary condition in experimental modal analysis to precisely reflect the properties of the structure. By using free-free boundary conditions, the influence of poorly defined supports is interrupted.

Keywords: natural frequencies, mode shapes, modal analysis, ANSYS software, RC slabs

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Authors: Lalit Kishore, Randhir Singh

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Diabetic nephropathy (DN) is the major cause of morbidity among diabetic patients. In this study, the effect of Bacopa monnieri Linn. (Brahmi, BM), was studied in a Streptozotocin (STZ)-induced experimental rat model of DN. Diabetic nephropathy was induced in Male Wistar rats (body weight- 300± 10 gms) by single intra-peritoneal injection of STZ (45mg/kg, i.p.) after 15 min of Nicotinamide (230 mg/kg) administration. Different doses of alcoholic extract i.e. 100, 200 and 400 mg/kg was given for 45 days by oral gavage after induction of DN. Blood glucose level, serum insulin, glycosylated haemoglobin, renal parameters (serum urea, uric acid, creatinine and BUN) and lipid profile (total cholesterol, triglycerides, HDL, LDL and VLDL levels) were measured. Concentration of thiobarbituric acid reactive species (TBARS) and levels of antioxidant enzymes of reduced glutathione (GSH), superoxide dismutase (SOD), and catalase (CAT) were evaluated in the kidney, liver and pancreas. At the end of treatment period the alcoholic extract of BM reduced the elevated level of blood glucose, serum insulin, renal parameters, lipid levels, TBARS, AGE’s in kidney and significantly increased body weight, HDL and antioxidant enzymes in dose dependent manner as compared to diabetic control animals. These results suggested the BM possesses significant renoprotective activity.

Keywords: AGE's, lipid profile, oxidative stress, renal parameters

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Authors: Long Guo, Hong Liu, Hongyu Yang, Hu Chen, Wenchao Du, Yu Liu

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Alzheimer’s disease (AD) is an incurable neurodegenerative disorder, underscoring the need for early diagnosis and intervention. Traditional clinical approaches pose challenges due to their inconvenience and high costs. In contrast, automatic AD screening systems based on speech analysis provide a noninvasive and scalable alternative. These systems commonly rely on extensively annotated datasets to fine-tune pre-trained language models for classification. Nevertheless, the diversity and complexity of the AD patient population, compounded by the limited availability of data for diverse groups, often result in suboptimal detection across various demographics. This research explores the effectiveness of large language models in zero-shot and few-shot learning scenarios for AD detection. Specific prompt engineering techniques have been developed for these scenarios, and large language models, including GPT-3.5 and GPT-4, have been employed on the ADReSSo test set. The models achieved an accuracy rate of 83.3%, which exceeds the results of traditional, data-intensive methods. Additionally, a ’thought chain’ mechanism was designed to guide the models in a step-by-step analysis of AD symptoms, yielding not only accurate but also interpretable results. The findings suggest that minimal data, when strategically applied through disease-specific prompt engineering and large language models, can significantly improve AD detection, presenting a viable direction for future medical diagnostic research.

Keywords: Alzheimer’s disease, few-shot, interpretability, large language model, zero-shot

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Authors: Susan P. Teru, Jerome Nyameh

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Many contemporary organizations are placing a greater emphasis on business enterprise systems as a means of generating higher levels of economic development and sustainability. Many business research and literature has also concur that enterprise drive economic development, giving little or no credit to social enterprise, whose profit is reinvest to the community development compare to the business enterprise that share their profit to shareholders. Economic development and corporate sustainability includes economic policies that affect the beneficiaries of the economic entity and how it support corporate sustainability as a multifaceted concept that requires organizational change and adaptation on different levels. In this paper, we provide a closer examination of this suggested link between the social enterprise orientation of an organization and the pursuit of corporate sustainability. We suggest that producing social enterprise increments may be best achieved by orienting social enterprise entrepreneurs system to promote economic development and corporate sustainability, which is the new approach to organizational excellent. To this end, we describe a new approach to the social enterprise process that includes social entrepreneur and the key drivers of economic development and corporate sustainability at each stage. We present a model of social enterprise that incorporates the main ideas of the paper and suggests a new perspective for thinking about how to foster and manage social enterprise to achieve high levels of economic development and corporate sustainability as a new ways of achieving organizational excellence. Specifically, we seek to assess (1) what constitutes a corporate sustainability-oriented organization culture, (2) whether it is possible for organizations to display a unified corporate sustainability as a result of social enterprise (3) whether organizations can become more sustainable through social enterprise change.

Keywords: social enterprise orientation, organization, the pursuit of corporate sustainability, business and management

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Authors: Bongs Lainjo

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The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics.

Keywords: sharing program, historical data, parameters, ridership dynamics, trip duration

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Authors: Vildan Kistik, Tuncay Can

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From a business perspective, cost and profit are two key factors for businesses. The intent of most businesses is to minimize the cost to maximize or equalize the profit, so as to provide the greatest benefit to itself. However, the physical system is very complicated because of technological constructions, rapid increase of competitive environments and similar factors. In such a system it is not easy to maximize profits or to minimize costs. Businesses must decide on the competence and competence of the personnel to be recruited, taking into consideration many criteria in selecting personnel. There are many criteria to determine the competence and competence of a staff member. Factors such as the level of education, experience, psychological and sociological position, and human relationships that exist in the field are just some of the important factors in selecting a staff for a firm. Personnel selection is a very important and costly process in terms of businesses in today's competitive market. Although there are many mathematical methods developed for the selection of personnel, unfortunately the use of these mathematical methods is rarely encountered in real life. In this study, unlike other methods, an exponential programming model was established based on the possibilities of failing in case the selected personnel was started to work. With the necessary transformations, the problem has been transformed into unconstrained Geometrical Programming problem and personnel selection problem is approached with geometric programming technique. Personnel selection scenarios for a classroom were established with the help of normal distribution and optimum solutions were obtained. In the most appropriate solutions, the personnel selection process for the classroom has been achieved with minimum cost.

Keywords: geometric programming, personnel selection, non-linear programming, operations research

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Authors: K. Rasool

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Sulfate-reducing bacteria (SRBs) induced biofilm formation is a global industrial concern due to its role in the development of microbial-induced corrosion (MIC). Herein, we have developed a biodegradable chitosan/lignosulfonate nanocomposite (CS@LS) as an efficient green biocide for the inhibition of SRBs biofilms. We investigated in detail the inhibition mechanism of SRBs by CS@LS in seawater media. Stable CS@LS-1:1 with 150–200 nm average size and zeta potential of + 34.25 mV was synthesized. The biocidal performance of CS@LS was evaluated by sulfate reduction profiles coupled with analysis of extracted extracellular polymeric substances (EPS) and lactate dehydrogenase (LDH) release assays. As the nanocomposite concentration was increased from 50 to 500 µg/mL, the specific sulfate reduction rate (SSRR) decreased from 0.278 to 0.036 g-sulfate/g-VSS*day showing a relative sulfate reduction inhibition of 86.64% as compared to that of control. Similarly, the specific organic uptake rate (SOUR) decreased from 0.082 to 0.039 0.036 g-TOC/g-VSS*day giving a relative co-substrate oxidation inhibition of 52.19% as compared to that of control. The SRBs spiked with 500 µg/mL CS@LS showed a reduction in cell viability to 1.5 × 106 MPN/mL. To assess the biosafety of the nanocomposite on the marine biota, the 72-hours acute toxicity assays using the zebrafish embryo model revealed that the LC50 for the CS@LS was 103.3 µg/mL. Thus, CS@LS can be classified as environmentally friendly. The nanocomposite showed long-term stability and excellent antibacterial properties against SRBs growth and is thus potentially useful for combating the problems of biofilm growth in harsh marine and aquatic environments.

Keywords: green biocides, chitosan/lignosulfonate nanocomposite, SRBs, toxicity

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Authors: Rachida Houssa, Hassan Rhinane, Fadoumo Ali Malouw, Amina Oulmaalem

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Since the early 70s, the Moroccan Atlantic sea was subjected to the pressure of the bottom trawling, one of the most destructive techniques seabed that cause havoc on fishing catch, nonselective, and responsible for more than half of all releases of fish around the world. The present paper aims to map and assess the impact of the activity of the bottom trawling of the Moroccan Atlantic coast. For this purpose, a dataset of thirty years, between 1962 and 1999, from foreign fishing vessels using bottom trawling, has been used and integrated in a GIS. To estimate the extent and the importance of the geographical distribution of the trawling effort, the Moroccan Atlantic area was divided into a grid of cells of 25 km2 (5x5 km). This grid was joined to the effort trawling data, creating a new entity with a table containing spatial overlay grid with the polygon of swept surfaces. This mapping model allowed to quantify the used fishing effort versus time and to generate the trace indicative of trawling efforts on the seabed. Indeed, for a given year, a grid cell may have a swept area equal to 0 (never been touched by the trawl) or 25 km2 (the trawled area is similar to the cell size) or may be 100 km2 indicating that for this year, the scanned surface is four times the cell area. The results show that the total cumulative sum of trawled area is approximately 28,738,326 km2, scattered throughout the Atlantic coast. 95% of the overall trawling effort is located in the southern zone, between 29°N and 20°30'N. Nearly 5% of the trawling effort is located in the northern coastal region, north of 33°N. The center area between 33°N and 29°N is the least swept by Russian commercial vessels because in this region the majority of the area is rocky, and non trawlable.

Keywords: GIS, Moroccan Atlantic Ocean, seabed, trawling

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Bernardo Cortez, Florian Peter, Thomas Lausenhammer, Paulo Oliveira

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Designing missiles’ autopilot controllers have been a complex task, given the extensive flight envelope and the nonlinear flight dynamics. A solution that can excel both in nominal performance and in robustness to uncertainties is still to be found. While Control Theory often debouches into parameters’ scheduling procedures, Reinforcement Learning has presented interesting results in ever more complex tasks, going from videogames to robotic tasks with continuous action domains. However, it still lacks clearer insights on how to find adequate reward functions and exploration strategies. To the best of our knowledge, this work is a pioneer in proposing Reinforcement Learning as a framework for flight control. In fact, it aims at training a model-free agent that can control the longitudinal non-linear flight dynamics of a missile, achieving the target performance and robustness to uncertainties. To that end, under TRPO’s methodology, the collected experience is augmented according to HER, stored in a replay buffer and sampled according to its significance. Not only does this work enhance the concept of prioritized experience replay into BPER, but it also reformulates HER, activating them both only when the training progress converges to suboptimal policies, in what is proposed as the SER methodology. The results show that it is possible both to achieve the target performance and to improve the agent’s robustness to uncertainties (with low damage on nominal performance) by further training it in non-nominal environments, therefore validating the proposed approach and encouraging future research in this field.

Keywords: Reinforcement Learning, flight control, HER, missile autopilot, TRPO

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Authors: Mariella Pinna

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Sustainable entrepreneurship is an innovative corporate approach to create value combining economic, social and environmental goals over time. In the last two decades, the interest in sustainable entrepreneurship has flourished thanks to its potential to answer the current challenges of sustainable development. As a result, scholars are increasingly interested in understanding the determinants of the intentions to become a sustainable entrepreneur and consistent behavior. To date, prior studies provided empirical evidence for the influence of attitudes, perceived feasibility and desirability, values, and personality traits on the decision-making process of becoming a sustainable entrepreneur. Conversely, scant effort has been provided to understand which factors inhibit sustainable entrepreneurial intentions and behaviors. Therefore a global understanding of the sustainable entrepreneurship decision-making process is missing. This paper contributes to the debate on sustainable entrepreneurship by proposing a conceptual model that combines the factors which are predicted to facilitate and hinder the proclivity of individuals to become sustainable entrepreneurs. More in particular, the proposed framework theorizes about the role of the characteristics of the prospective sustainable entrepreneur (e.g., socio-demographic, psychological, cultural), the positive antecedents (e.g., attitude, social feasibility and desirability, among others) and the negative precursors (e.g., neutralization) in influencing sustainable entrepreneurship intentions and subsequent behavior. The proposed framework is expected to shed further light on the decision-making process of becoming a sustainable entrepreneur, which in turn, is of practical relevance for public policy institutions and the society as a whole to enhance the favorable conditions to create new sustainable ventures.

Keywords: sustainable entrepreneurship, entrepreneurial intentions, entrepreneurial decision-making, antecedents of entrepreneurial intention and behavior

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Authors: Fouzieh Rouzmehr, Mehdi Mousavi

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Hot mix asphalt concrete (HMAC) is a mixture of aggregates and bitumen. The primary ingredient that determines the mechanical properties of HMAC is the bitumen in it, which displays viscoelastic behavior under normal service conditions. For simplicity, asphalt concrete is considered an elastic material, but this is far from reality at high service temperatures and longer loading times. Viscoelasticity means that the material's stress-strain relationship depends on the strain rate and loading duration. The goal of this paper is to simulate the mechanical response of flexible pavements using linear elastic and viscoelastic modeling of asphalt concrete and predict pavement performance. Falling Weight Deflectometer (FWD) load will be simulated and the results for elastic and viscoelastic modeling will be evaluated. The viscoelastic simulation is performed by the Prony series, which will be modeled by using ANSYS software. Inflexible pavement design, tensile strain at the bottom of the surface layer and compressive strain at the top of the last layer plays an important role in the structural response of the pavement and they will imply the number of loads for fatigue (Nf) and rutting (Nd) respectively. The differences of these two modelings are investigated on fatigue cracking and rutting problem, which are the two main design parameters in flexible pavement design. Although the differences in rutting problem between the two models were negligible, in fatigue cracking, the viscoelastic model results were more accurate. Results indicate that modeling the flexible pavement with elastic material is efficient enough and gives acceptable results.

Keywords: flexible pavement, asphalt, FEM, viscoelastic, elastic, ANSYS, modeling

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

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Authors: Afy Syahidan Achmad

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Tangkuban Perahu is located in West Java, Indonesia. It is active stratovolcano type and still showing hidrothermal activity. The main purpose of this study is to find correlation between subsurface structure and hidrothermal activity on the surface. Using topographic map, SRTM images, and field observation, geological condition and alteration area was mapped. Alteration sample analyzed trough petrographic analysis and X-Ray Diffraction (XRD) analysis. Altered rock in study area showing white-yellowish white colour, and texture changing variation from softening to hardening because of alteration by sillica and sulphur. Alteration mineral which can be observed in petrographic analysis and XRD analysis consist of crystobalite, anatase, alunite, and pyrite. This mineral assemblage showing advanced argillic alteration type with West-East alteration area orientation. Alteration area have correlation with manifestation occurance such as steam vents, solfatara, and warm to hot pools. Most of manifestation occured in main crater like Ratu Crater and Upas crater, and parasitic crater like Domas Crater and Jarian Crater. This manifestation indicates permeability in subsurface which can be created trough structural process with same orientation. For further study geophysics method such as Magneto Telluric (MT) and resistivity can be required to find permeability zone pattern in Tangkuban Perahu subsurface.

Keywords: alteration, advanced argillic, Tangkuban Perahu, XRD, crystobalite, anatase, alunite, pyrite

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Authors: F. A. Gdhaidh, K. Hussain, H. S. Qi

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A numerical study of natural convection heat transfer in water filled cavity has been examined in 3D for single phase liquid cooling system by using an array of parallel plate fins mounted to one wall of a cavity. The heat generated by a heat source represents a computer CPU with dimensions of 37.5×37.5 mm mounted on substrate. A cold plate is used as a heat sink installed on the opposite vertical end of the enclosure. The air flow inside the computer case is created by an exhaust fan. A turbulent air flow is assumed and k-ε model is applied. The fins are installed on the substrate to enhance the heat transfer. The applied power energy range used is between 15- 40W. In order to determine the thermal behaviour of the cooling system, the effect of the heat input and the number of the parallel plate fins are investigated. The results illustrate that as the fin number increases the maximum heat source temperature decreases. However, when the fin number increases to critical value the temperature start to increase due to the fins are too closely spaced and that cause the obstruction of water flow. The introduction of parallel plate fins reduces the maximum heat source temperature by 10% compared to the case without fins. The cooling system maintains the maximum chip temperature at 64.68℃ when the heat input was at 40 W which is much lower than the recommended computer chips limit temperature of no more than 85℃ and hence the performance of the CPU is enhanced.

Keywords: chips limit temperature, closed enclosure, natural convection, parallel plate, single phase liquid

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Authors: Rishabh Ambavanekar

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Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

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Authors: Jihad Daba, Jean-Pierre Dubois

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Multi path fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper have utilized a Poisson modulated and weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multi-diversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent specular Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: cellular communication, femto and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process

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Authors: Zhenxiang Zhou

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The triose phosphate utilisation (TPU) limitation to leaf photosynthesis is a biochemical process concerning the sub-foliar carbon sink-source (im)balance, in which photorespiration-associated amino acids exports provide an additional outlet for carbon and increases leaf photosynthetic rate. However, whether this process is regulated by whole-plant sink-source relations and nitrogen budgets remains unclear. We address this question by model analyses of gas-exchange data measured on leaves at three growth stages of rice plants grown at two-nitrogen levels, where three means (leaf-colour modification, adaxial vs abaxial measurements, and panicle pruning) were explored to alter source-sink ratios. Higher specific leaf nitrogen (SLN) resulted in higher rates of TPU and also led to the TPU limitation occurring at a lower intercellular CO2 concentration. Photorespiratory nitrogen assimilation was greater in higher-nitrogen leaves but became smaller in cases associated with yellower-leaf modification, abaxial measurement, or panicle pruning. The feedback inhibition of panicle pruning on rates of TPU was not always observed because panicle pruning blocked nitrogen remobilisation from leaves to grains, and the increased SLN masked the feedback inhibition. The (sub)foliar TPU limitation can be modulated by whole-plant source-sink ratios and nitrogen budgets during rice grain filling, suggesting a close link between sub-foliar and whole-plant sink limitations.

Keywords: triose phosphate utilization, sink limitation, panicle pruning, oryza sativa

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Authors: Nikk Leavitt, Peter Kellett, Cheryl Currie, Richard Larouche

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Background: Masculinity has been associated with poor mental health outcomes in adult men and is colloquially referred to as toxic. Masculinity is traditionally measured using the Male Role Norms Inventory, which examines behaviors that may be common in men but that are themselves associated with poor mental health regardless of gender (e.g., aggressiveness). The purpose of this study was to examine if masculinity is associated with generalized anxiety among men using this inventory vs. a man’s personal definition of it. Method: An online survey collected data from 1,200 men aged 18-65 across Canada in July 2022. Masculinity was measured using: 1) the Male Role Norms Inventory Short Form and 2) by asking men to self-define what being masculine means. Men were then asked to rate the extent they perceived themselves to be masculine on a scale of 1 to 10 based on their definition of the construct. Generalized anxiety disorder was measured using the GAD-7. Multiple linear regression was used to examine associations between each masculinity score and anxiety score, adjusting for confounders. Results: The masculinity score measured using the inventory was positively associated with increased anxiety scores among men (β = 0.02, p < 0.01). Masculinity subscales most strongly correlated with higher anxiety were restrictive emotionality (β = 0.29, p < 0.01) and dominance (β = 0.30, p < 0.01). When traditional masculinity was replaced by a man’s self-rated masculinity score in the model, the reverse association was found, with increasing masculinity resulting in a significantly reduced anxiety score (β = -0.13, p = 0.04). Discussion: These findings highlight the need to revisit the ways in which masculinity is defined and operationalized in research to better understand its impacts on men’s mental health. The findings also highlight the importance of allowing participants to self-define gender-based constructs, given they are fluid and socially constructed.

Keywords: masculinity, generalized anxiety disorder, race, intersectionality

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Authors: Soumya Sajjan

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Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

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Authors: Fatemeh Saadat Ghareh Bagh, Srimanta Ray, Jerald Lalman

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Lignin, the largest inventory of organic carbon with a high caloric energy value is a major component in woody and non-woody biomass. In pulping mills, a large amount of the lignin is burned for energy. At the same time, the phenolic structure of lignin enables it to be converted to value-added compounds.This study has focused on extracting lignin from black liquor using deep eutectic solvents (DESs). Therefore, three choline chloride (ChCl)-DESs paired with lactic acid (LA) (1:11), oxalic acid.2H₂O (OX) (1:4), and malic acid (MA) (1:3) were synthesized at 90oC and atmospheric pressure. The kinetics of lignin recovery from black liquor using DES was investigated at three moderate temperatures (338, 353, and 368 K) at time intervals from 30 to 210 min. The extracted lignin (acid soluble lignin plus Klason lignin) was characterized by Fourier transform infrared spectroscopy (FTIR). The FTIR studies included comparing the extracted lignin with a model Kraft lignin. The extracted lignin was characterized spectrophotometrically to determine the acid soluble lignin (ASL) [TAPPI UM 250] fraction and Klason lignin was determined gravimetrically using TAPPI T 222 om02. The lignin extraction reaction using DESs was modeled by first-order reaction kinetics and the activation energy of the process was determined. The ChCl:LA-DES recovered lignin was 79.7±2.1% at 368K and a DES:BL ratio of 4:1 (v/v). The quantity of lignin extracted for the control solvent, [emim][OAc], was 77.5+2.2%. The activation energy measured for the LA-DES system was 22.7 KJ mol⁻¹, while the activation energy for the OX-DES and MA-DES systems were 7.16 KJ·mol⁻¹ and 8.66 KJ·mol⁻¹ when the total lignin recovery was 75.4 ±0.9% and 62.4 ±1.4, % respectively.

Keywords: black liquor, deep eutectic solvents, kinetics, lignin

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Authors: Bersufekad Wubie

Abstract:

Introduction: Near visual impairment is presenting near visual acuity of the eye worse than N6 at a 40 cm distance. Teachers' regular duties, such as reading books, writing on the blackboard, and recognizing students' faces, need good near vision. If a teacher has near-visual impairment, the work output is unsatisfactory. Objective: The study was aimed to assess the prevalence and associated factors near vision impairment among school teachers at Gondar city Northwest Ethiopia, August 2022. Methods: To select 567 teachers in Gondar city schools, an institutional-based cross-sectional study design with a multistage sampling technique were used. The study was conducted in selected schools from May 1 to May 30, 2022. Trained data collectors used well-structured Amharic and English language questionnaires and ophthalmic instruments for examination. The collected data were checked for completeness and entered into Epi data version 4.6, then exported to SPSS version 26 for further analysis. A binary and multivariate logistic regression model was fitted. And associated factors of the outcome variable. Result: The prevalence of near visual impairment was 64.6%, with a confidence interval of 60.3%–68.4%. Near visual impairment was significantly associated with age >= 35 years (AOR: 4.90 at 95% CI: 3.15, 7.65), having prolonged years of teaching experience (AOR: 3.29 at 95% CI: 1.70, 4.62), having a history of ocular surgery (AOR: 1.96 at 95% CI: 1.10, 4.62), smokers (AOR: 2.21 at 95% CI: 1.22, 4.07), history of ocular trauma (AOR : 1.80 at 95%CI:1.11,3.18 and uncorrected refractive error (AOR:2.01 at 95%CI:1.13,4.03). Conclusion and recommendations: This study showed the prevalence of near vision impairment among school teachers was high, and it is not a problem of the presbyopia age group alone; it also happens at a young age. So teachers' ocular health should be well accommodated in the school's eye health.

Keywords: Gondar, near visual impairment, school, teachers

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