Search results for: local potential

Authors: Bahieddine. Bouabdellah, Benameur. Amiri, Abdelkader.nouri

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Europium-doped gallium nitride (EuGaN) is a promising material for optoelectronic and thermoelectric devices. This study investigates its optical properties using density functional theory (DFT) with the FP-LAPW method and MBJ+U correction. The simulation substitutes a gallium atom with europium in a hexagonal GaN lattice (6% doping). Distinct absorption peaks are observed in the optical analysis. These results highlight EuGaN's potential for various applications and pave the way for further research on rare earth-doped materials.

Keywords: eugan, fp-lapw, dft, wien2k, mbj hubbard

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Authors: Laura Álvarez Antón, Joaquín Díaz

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The construction industry is turning towards sustainability. It is a well-known fact that sustainability is based on a balance between environmental, social and economic aspects. In order to achieve sustainability efficiently, these three criteria should be taken into account in the initial project phases, since that is when a project can be influenced most effectively. Thus the aim must be to integrate important tools like BIM and LCA at an early stage in order to make full use of their potential. With the synergies resulting from the integration of BIM and LCA, a wider approach to sustainability becomes possible, covering the three pillars of sustainability.

Keywords: building information modeling (BIM), construction industry, design phase, life cycle assessment (LCA), sustainability

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Authors: Netanel Stern

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Artificial intelligence (AI) algorithms have emerged as powerful tools in the field of psychiatry, offering new possibilities for enhancing diagnosis and treatment outcomes. This article explores the utilization of AI algorithms in psychiatry, highlighting their potential to revolutionize patient care. Various AI algorithms, including machine learning, natural language processing (NLP), reinforcement learning, clustering, and Bayesian networks, are discussed in detail. Moreover, ethical considerations and future directions for research and implementation are addressed.

Keywords: AI, software engineering, psychiatry, neuroimaging

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Authors: Luojie Tang, Libin Ouyang, Yihang Gao

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The natural landscape and urban-rural structure, with their attractiveness in the Dali area around Erhai Lake, exhibit striking similarities with Howard's Garden City. With the emergence of the unique phenomenon of the first large-scale gathering of digital nomads in China in Dali, an analysis of Dali's natural, economic, and cultural representations and structures reveals that the Garden City model can no longer fully explain the current overall human living environment in Dali. By interpreting the bottom-up local construction process in Dali based on landscape identity, the transformation of production and lifestyle under new technologies such as ICT(Information and Communication Technology), and the values and lifestyle reshaping embodied in the "reverse urbanization" phenomenon of the middle class in Dali, it is believed that Dali has moved towards a "contemporary garden city influenced by new technology." The article summarizes the characteristics and connotations of this Garden City and provides corresponding strategies for its continued healthy development.

Keywords: dali, ICT, rural-urban relationship, garden city model

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Authors: Lucille Lok-Sun Ngan

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There are significant gaps in both the migration and family literatures regarding the gendered parenting of Chinese migrants. Evidence from the literature informs us that the child-focused parenting style of the West has altered, with positive consequences, parent–child relationships in migrant families. In particular, second-generation migrants have developed hybrid identities distinct from those of their overseas-born parents and the locals. On returning to their place of origin, they may undergo yet another process of change in values, and in behaviour, in order to adapt to the local culture. As migration changes values, personality and practice at personal, interpersonal and familial levels, the cross-cultural experiences of returnees inevitably affect their own fatherhood journeys in their country of origin. This paper reviews current literature on fatherhood and migration and identifies the gaps and limitations that pertain to understanding the paternal experiences of Chinese return migrants.

Keywords: Chinese returnees, cross-cultural experiences, fatherhood, hybridity, migration

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Authors: So-Jung Kim, Kyoung-Seok Kim, Yeong-Gyeong Choi

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Although there are many theories and discussion of leadership, the necessity of having a new leadership paradigm was emphasized. The existing leadership characteristic of instruction and control revealed its limitations. Market competition becomes fierce and economic recession never ends worldwide. Of the leadership theories, servant leadership was introduced recently and is in line with the environmental changes of the organization. Servant leadership is a combination of two words, 'servant' and 'leader' and can be defined as the role of the leader who focuses on doing voluntary work for others with altruistic ethics, makes members, customers, and local communities a priority, and makes a commitment to satisfying their needs. This leadership received attention as one field of leadership in the late 1990s and secured its legitimacy. This study discusses the existing research trends of leadership, the concept, behavior characteristics, and lower dimensions of servant leadership, compares servant leadership with the existing leadership researches and diagnoses if servant leadership is a useful concept for further leadership researches. Finally, this study criticizes the limitations in the existing researches on servant leadership.

Keywords: leadership philosophy, leadership theory, servant leadership, traditional leadership

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Authors: Pomozova Kseniia, Gorlachev Gennadiy, Chernyaev Aleksandr, Golanov Andrey

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In clinical practice, and especially in stereotactic radiosurgery planning, the significance of diffusion-weighted imaging (DWI) is growing. This makes the existence of software capable of quickly processing and reliably visualizing diffusion data, as well as equipped with tools for their analysis in terms of different tasks. We are developing the «MRDiffusionImaging» software on the standard C++ language. The subject part has been moved to separate class libraries and can be used on various platforms. The user interface is Windows WPF (Windows Presentation Foundation), which is a technology for managing Windows applications with access to all components of the .NET 5 or .NET Framework platform ecosystem. One of the important features is the use of a declarative markup language, XAML (eXtensible Application Markup Language), with which you can conveniently create, initialize and set properties of objects with hierarchical relationships. Graphics are generated using the DirectX environment. The MRDiffusionImaging software package has been implemented for processing diffusion magnetic resonance imaging (dMRI), which allows loading and viewing images sorted by series. An algorithm for "masking" dMRI series based on T2-weighted images was developed using a deformable surface model to exclude tissues that are not related to the area of interest from the analysis. An algorithm of distortion correction using deformable image registration based on autocorrelation of local structure has been developed. Maximum voxel dimension was 1,03 ± 0,12 mm. In an elementary brain's volume, the diffusion tensor is geometrically interpreted using an ellipsoid, which is an isosurface of the probability density of a molecule's diffusion. For the first time, non-parametric intensity distributions, neighborhood correlations, and inhomogeneities are combined in one segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) algorithm. A tool for calculating the coefficient of average diffusion and fractional anisotropy has been created, on the basis of which it is possible to build quantitative maps for solving various clinical problems. Functionality has been created that allows clustering and segmenting images to individualize the clinical volume of radiation treatment and further assess the response (Median Dice Score = 0.963 ± 0,137). White matter tracts of the brain were visualized using two algorithms: deterministic (fiber assignment by continuous tracking) and probabilistic using the Hough transform. The proposed algorithms test candidate curves in the voxel, assigning to each one a score computed from the diffusion data, and then selects the curves with the highest scores as the potential anatomical connections. White matter fibers were visualized using a Hough transform tractography algorithm. In the context of functional radiosurgery, it is possible to reduce the irradiation volume of the internal capsule receiving 12 Gy from 0,402 cc to 0,254 cc. The «MRDiffusionImaging» will improve the efficiency and accuracy of diagnostics and stereotactic radiotherapy of intracranial pathology. We develop software with integrated, intuitive support for processing, analysis, and inclusion in the process of radiotherapy planning and evaluating its results.

Keywords: diffusion-weighted imaging, medical imaging, stereotactic radiosurgery, tractography

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Truong Xuan Lam, Nguyen Thị Phuong Lien, Nguyen Quang Cuong, Tran Thị Ngat

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Introduction: Corn biomass is a feed for livestock including dairy cows. The Spodoptera frugiperda, Agrotis ypsilon, Heliothis armigera, Mythimna loreyi (Lepidoptera: Noctuidae) are key pests and very dangerous to Corn biomass crops. These pest species are very difficult to control in the field because of genetic resistance to insecticides. Furthermore, corn biomass is feed for livestock so the use of pesticides is always limited to the lowest level. In Vietnam, the assassin bug species Sycanus falleni and Sycanus croceouittatus (Hemiptera: Reduviidae) are the common predators on trees agricultural ecosystems. The reduviid S. falleni and S. croceouittatus have the potential for biological control of pest insects in cotton, corn and vegetable plants as this species attacks many lepidopteran larvae. Moreover, the nymphal instars and adults of S. falleni and S. croceouittatus can be easily reared in the laboratory by the rice meal moth Corcyra cephalonica (Stainton). To conserve the species S. falleni and S. croceouittatus in Corn biomass field in Northwest Vietnam. The results of this study report on the roles and relationships between S. falleni Stal and S. croceovittatus and their prey (key pests and dangerous to Corn) on Corn biomass to provide the basis for using and conserving the species S. falleni and S. croceouittatus as biological control agents on Corn biomass growing areas in Vietnam. Methods: The survey site is at the field of Corn biomass growing in Hoa Binh Province, Northwest Vietnam. The survey of the density of the assassin bugs species and their prey were conducted in 4 Corn biomass fields (each field = 10,000 m2), each point has an area of 1 m2. The survey was conducted every 10 days (3 times/month). The unit of measurement is individual/m2. The relationship between the density of assassin bug species and their prey is expressed through the correlation coefficient R Results: On Corn biomass in Northwest Vietnam, the S. falleni and S. croceouittatus species are such potential candidates for biocontrol of the fall armyworm S. frugiperda, black cutworm A. ypsilon, cotton bollworm H. armigera Hübner, maize caterpillar M. loreyi. Six species of assassin bugs belonging to the family Reduviidae were recorded on Corn biomass, of which S. falleni and S. croceovittatus were common. The relationship between the density of the group of assassin bugs and species S. fallen and S. croceovittatus had a close relationship with each other. The relationship between the density of the group of assassin bugs and the density of their prey in the Winter crops and Summer-Fall crops was a close relationship with each other. The relationship between the density of the S. falleni and S. croceovittatus species and the density of their prey on the Corn biomass were a close relationship in the Summer-Fall crops and the Winter crops. The S. falleni and S. croceouittatus species are such potential biocontrol of the pests on Corn. Possible to conserve and use them for biological control of the dangerous pests S. frugiperda, A. ypsilon, H. armigera , M. loreyi on Corn in Vietnam.

Keywords: corn biomass, prey, biocontrol, relationship

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Authors: Ismail Becenen

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Air pollution, a consequence of urbanization brought about by modern life, is as global as it is local and regional. Because of the adverse effects of air pollution on human health, air quality is given importance all over the world. According to the decision of the World Health Organization, clean air is the basic necessity for human health and well-being. It poses a very high risk especially for heart diseases and stroke cases. In this study, the positive effects of natural gas usage on air pollution in cities are explained by using literature scans and air pollution measurement values. Natural gas is cleaner than other types of fuel. It contains less sulfur and organic sulfur compounds. When natural gas burns, it does not leave ashes, it does not cause problems in the rubbish mountains. It's a clean fuel, it easily burns and shines. It is a burning gas that is easy and efficient. In addition, there is not a toxic effect for people in case of inhalation. As a result, the use of natural gas needs to be widespread to reduce air pollution around the world in order to provide a healthier life for people and the environment.

Keywords: natural gas, air pollution, sulfur dioxide, particulate matter, energy

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Authors: I. Ibrahim, A. Mann

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Phytochemical screening of crude Chrysanthlum Indicum revealed the presence of carbohydrates, flavonoids, saponins, tannins, alkanoids, steroidal nucleus and cardiac glycosides. The extract was evaluated against some pathogenic organisms by agar dilution method. The minimum inhibitory concentration and minimum bacteriocidal concentration (MBC) of the active extract of Chrysanthlum Indicum shows that its extract could be a potential source of antimicrobial agents.

Keywords: extract, phytochemicals, antimicrobial, antibacterial, Chrysanthlum indicum

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Authors: Md Abdullah Al Faruque

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A very large percentage of bridge failures are attributed to scouring around bridge piers and this directly influences public safety. Experiments are carried out in a 12-m long rectangular open channel flume made of transparent tempered glass. A 300 mm thick bed made up of sand particles is leveled horizontally to create the test bed and a 50 mm hollow plastic cylinder is used as a model bridge pier. Tests are carried out with varying flow depths and velocities. Data points of various scour parameters such as scour depth, width, and length are collected based on different flow conditions and visual observations of changes in the stream bed downstream the bridge pier are also made as the scour progresses. Result shows that all three major flow characteristics (flow depth, Froude number and densimetric Froude number) have one way or other affect the scour profile.

Keywords: bridge pier scour, densimetric Froude number, flow depth, Froude number, sand

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Juan A. G. Carrio, Prasad Talluri, Sergio G. Echeverrigaray, Antonio H. Castro Neto

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Hydrogen as a fuel and environmentally pleasant energy carrier is part of this transition towards low-carbon systems. The extensive deployment of hydrogen production, purification and transport infrastructures still represents significant challenges. Independent of the production process, the hydrogen generally is mixed with light hydrocarbons and other undesirable gases that need to be removed to obtain H₂ with the required purity for end applications. In this context, membranes are one of the simplest, most attractive, sustainable, and performant technologies enabling hydrogen separation and purification. They demonstrate high separation efficiencies and low energy consumption levels in operation, which is a significant leap compared to current energy-intensive options technologies. The unique characteristics of 2D laminates have given rise to a diversity of research on their potential applications in separation systems. Specifically, it is already known in the scientific literature that graphene oxide-based membranes present the highest reported selectivity of H₂ over other gases. This work explores the potential of a new type of 2D materials-based membranes in separating H₂ from CO₂ and CH₄. We have developed nanostructured composites based on 2D materials that have been applied in the fabrication of membranes to maximise H₂ selectivity and permeability, for different gas mixtures, by adjusting the membranes' characteristics. Our proprietary technology does not depend on specific porous substrates, which allows its integration in diverse separation modules with different geometries and configurations, looking to address the technical performance required for industrial applications and economic viability. The tuning and precise control of the processing parameters allowed us to control the thicknesses of the membranes below 100 nanometres to provide high permeabilities. Our results for the selectivity of new nanostructured 2D materials-based membranes are in the range of the performance reported in the available literature around 2D materials (such as graphene oxide) applied to hydrogen purification, which validates their use as one of the most promising next-generation hydrogen separation and purification solutions.

Keywords: membranes, 2D materials, hydrogen purification, nanocomposites

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Authors: Shunichiro Morishita

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This study examines the factors for attracting foreign guests in the Japanese lodging industry and discusses some measures taken for accepting foreign guests. It reviews three different accommodation providers acclaimed highly by foreign guests, Yamashiroya, Sawanoya and Fuji-Hakone Guest House, and identifies their characteristics. The common points for attracting foreign guests were: 1) making the best use of the old facilities, 2) multilingual signs, guidance and websites, 3) necessary and sufficient communication in English, 4) events and opportunities to experience Japanese culture, 5) omotenashi, warm and homely Japanese hospitality. These findings indicate that foreign guests’ dissatisfaction level can be decreased through internationalization utilizing ICT and by offering multilingual support. On the other hand, their satisfaction level can be increased by encouraging interaction with other guests and local Japanese people, providing events and opportunities to experience Japanese culture and omotenashi, home-style Japanese hospitality.

Keywords: hospitality management, foreign guests, Japanese lodging industry, Omotenashi

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Authors: Azri Yamina Mounia, Zitouni Dalila, Aziza Majda, Tou Insaf, Sadi Meriem

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To confront the fossil fuel crisis and the consequences of global warning, many efforts were devoted to develop alternative electricity generation and attracted numerous researchers, especially in the microbial fuel cell field, because it allows generating electric energy and degrading multiple organics compounds at the same time. However, one of the main constraints on power generation is the slow rate of oxygen reduction at the cathode electrode. This paper describes the potential of algal biomass (Chlorella vulgaris) as photosynthetic cathodes, eliminating the need for a mechanical air supply and the use of often expensive noble metal cathode catalysts, thus improving the sustainability and cost-effectiveness of the MFC system. During polarizations, MFC power density using algal biomass was 0.4mW/m², whereas the MFC with mechanic aeration showed a value of 0.2mW/m². Chlorella vulgaris was chosen due to its fastest growing. C. vulgaris grown in BG11 medium in sterilized Erlenmeyer flask. C. vulgaris was used as a bio‐cathode. Anaerobic activated sludge from the plant of Beni‐Messous WWTP(Algiers) was used in an anodic compartment. A dual‐chamber reactor MFC was used as a reactor. The reactor has been fabricated in the laboratory using plastic jars. The cylindrical and rectangular jars were used as the anode and cathode chambers, respectively. The volume of anode and cathode chambers was 0.8 and 2L, respectively. The two chambers were connected with a proton exchange membrane (PEM). The plain graphite plates (5 x 2cm) were used as electrodes for both anode and cathode. The cyclic voltammetry analysis of oxygen reduction revealed that the cathode potential was proportional to the amount of oxygen available in the cathode surface electrode. In the case of algal aeration, the peak reduction value of -2.18A/m² was two times higher than in mechanical aeration -1.85A/m². The electricity production reached 70 mA/m² and was stimulated immediately by the oxygen produced by algae up to the value of 20 mg/L.

Keywords: Chlorella vulgaris, cyclic voltammetry, microbial fuel cell, oxygen reduction

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Authors: M. E. Abou-Hashem El Dib, M. K. Swailem, M. M. Metwally, A. I. El Awady

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This paper presents the effect of stiffeners on the behavior of slender steel I-beams. Nonlinear three dimensional finite element models are developed to represent the stiffened steel I-beams. The well established finite element (ANSYS 13.0) program is used to simulate the geometric and material nonlinear nature of the problem. Verification is achieved by comparing the obtained numerical results with the results of previous published experimental work. The parameters considered in the analysis are the horizontal stiffener's position and the horizontal stiffener's dimensions as well as the number of vertical stiffeners. The studied dimensions of the horizontal stiffeners include the stiffener width, the stiffener thickness and the stiffener length. The results of the achieved numerical parametric study for slender steel I-beams show the significant effect of stiffeners on the beam behavior and its failure load.

Keywords: beams, local buckling, slender, stiffener, thin walled section

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Authors: Radhia Toujani, Jalel Akaichi

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In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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Authors: Bendjaballah Malek; Makhlouf Mohammed Rabeh; Boukerche Imane; Benhamza Mohammed El Hocine

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In this study, chitosan was derived from Parapenaeus longirostris shrimp shells sourced from a local market in Annaba, eastern Algeria. The extraction process entailed four chemical stages: demineralization, deproteinization, decolorization, and deacetylation. The degree of deacetylation was calculated to be 80.86 %. The extracted chitosan was physically altered to synthesize chitosan beads and characterized via FTIR and XRD analysis. These beads were employed to eliminate cadmium ions from synthetic water. The batch adsorption process was optimized by analyzing the impact of contact time, pH, adsorbent dose, and temperature. The adsorption capacity of and Cd+2 on chitosan beads was found to be 6.83 mg/g and 7.94 mg/g, respectively. The kinetic adsorption of Cd+2 conformed to the pseudo-first-order model, while the isotherm study indicated that the Langmuir Isotherm model well described the adsorption of cadmium . A thermodynamic analysis demonstrated that the adsorption of Cd+2 on chitosan beads is spontaneous and exothermic.

Keywords: Cd, chitosan, chitosanbeds, bioadsorbent

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Authors: Anthony J. Kondracki, Bonzo Reddick, Jennifer L. Barkin

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Background: Many pregnancies in the United States are affected each year with the most common sexually transmitted infections (STIs), including Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Treponema pallidum (TP, syphilis), and the rate of congenital syphilis has reached a 20-year high. We sought to estimate the prevalence of CT, NG, and TP in pregnancy and the risk of preterm birth (PTB) (<37 weeks gestation) and low birthweight (LBW) (<2500g) deliveries according to utilization of prenatal care (PNC) during the COVID-19 pandemic. Methods: This study was based on the 2020 National Center for Health Statistics (NCHS) Natality File restricted to singleton births (N=3,512,858). We estimated the prevalence of CT, NG, TP, PTBand LBW across timing and the number of prenatal care (PNC) visits attended. In multivariable logistic regression models, adjusted odds ratios of PTB and LBW were assessed according to STIs and PNC status. E-values, based on effect size estimates and the lower bound of the 95% confidence intervals (CIs) of the association, examined the potential impact of unmeasured confounding. Results: CT (1.8%) was most prevalent in pregnancy, followed by NG (0.3%) and TP (0.1%). The strongest predictors of PTB and LBW were maternal NG (12.2% and 12.1%, respectively), late initiation/no PNC (8.5% and 7.6%, respectively), and ≤10 prenatal visits (13.1% and 10.3%, respectively). The odds of PTB and LBW were 2.5- to 3-fold greater for each STI in women who received ≤10 compared to >10 prenatal visits. E-values demonstrated the minimum strength of potential unmeasured confounding necessary to explain away observed associations. Conclusions: Timely initiation and receipt of recommended number of prenatal visits benefits screening and treatment of all women for STIs, including NG to substantially reduce infant morbidity and mortality related to PTB and LBW among infants born during the COVID-19 pandemic.

Keywords: COVID-19 pandemic, sexually transmitted infections, preterm birth, low birthweight, prenatal care

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Iruka C. Anugwo, Winston M. Shakantu

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The objective of this study is to uncover the basic business-forces that necessitated the survival and sustainable performance of the medium scale contractors in the South African construction market. This study is essential as it set to contribute towards long-term strategic solutions for combating the incessant failure of start-ups construction organizations within South African. The study used a qualitative research methodology; as the most appropriate approach to elicit and understand, and uncover the phenomena that are basic business-forces for the active contractors in the market. The study also adopted a phenomenological study approach; and in-depth interviews were conducted with 20 medium scale contractors in Port Elizabeth, South Africa, between months of August to October 2015. This allowed for an in-depth understanding of the critical and basic business-forces that influenced their survival and performance beyond the first five years of business operation. Findings of the study showed that for potential contractors (startups), to survival in the competitive business environment such as construction industry, they must possess the basic business-forces. These forces are educational knowledge in construction and business management related disciplines, adequate industrial experiences, competencies and capabilities to delivery excellent services and products as well as embracing the spirit of entrepreneurship. Convincingly, it can be concluded that the strategic approach to minimize the endless failure of startups construction businesses; the potential construction contractors must endeavoring to access and acquire the basic educationally knowledge, training and qualification; need to acquire industrial experiences in collaboration with required competencies, capabilities and entrepreneurship acumen. Without these basic business-forces as been discovered in this study, the majority of the contractors gaining entrance in the market will find it difficult to develop and grow a competitive and sustainable construction organization in South Africa.

Keywords: basic business-forces, medium scale contractors, South Africa, sustainable organisations

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Authors: Ana Handel, Jamal Ellerbe, Sarah Kanzaki, Natalie White, Nathan Ousey, Sean Gallagher

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A sense of belonging is the ability for individuals to feel they are a necessary part of whatever organization or community they find themselves in. In an academic setting, a sense of belonging is key to a student’s success. The collected research points to this sense of belonging in academic settings as a significant contributor of students’ levels of engagement and trust. When universities leverage the arts, students are provided with more opportunities to engage and feel confident in their surroundings. This allows for greater potential to develop within academic and social settings. The arts also call for the promotion of diversity, equity, and inclusion by showcasing works of artists from all different backgrounds, thus allowing students to gain cultural knowledge and be able to embrace differences. Equity, diversity, and inclusion are all emotional facets of belonging. Equity relates to the concept of making the conscious choice to recognize opportunities to incorporate inclusive and diverse ideals into different thought processes and collaboration. Inclusion involves providing equal access to opportunities and resources for people of all ‘ingroups. In an inclusive culture, individuals are able to maximize their potential with the confidence they have gained through an accepting environment. A variety of members in academic communities have noted it may be beneficial to make certain events surrounding the arts to be built into course requirements in order to ensure students are expanding their horizons and exposing themselves to the arts. These academics also recommend incorporating the arts into extracurricular activities, such as Greek life, in order to appeal to large groups of students. Once students have an understanding of the rich knowledge cultivated through exploring the arts, they will feel more comfortable in their surroundings and thus more confident to become involved in other areas of their university. A number of universities, including West Chester and Carnegie Mellon, have instituted programs aiming to provide students with the necessary tools and resources to feel comfortable in their educational settings. Different programs include references to hotlines for discrimination and office for diversity, equity, and inclusion. Staff members have also been provided with means of combating biases and increasing feelings of belongingness in order to properly support and communicate with students. These tools have successfully allowed universities to foster inviting environments for students of all backgrounds to feel belong as well as strengthening the community’s diversity, equity, and inclusion. Through demonstrating concepts of diversity, equity, and inclusion by introducing the arts into learning spaces, students can find a sense of belonging within their academic environments. It is essential to understand these topics and how they work together to achieve a common goal. The efforts of universities have made much progress in shedding light on different cultures and ideas to show students their full potential and opportunities. Once students feel more comfortable within their organizations, engagement will increase substantially.

Keywords: arts, belonging, engagement, inclusion

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Authors: Amjad Ali Khan, Muhammad Ishaq Saqi, Kashif Ali

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The focus of hydrocarbon exploration in Pakistan has been primarily on conventional hydrocarbon resources. Directorate General Petroleum Concessions (DGPC) has taken the lead on the assessment of indigenous unconventional oil and gas resources, which has resulted in a ‘Shale Oil/Gas Resource Assessment Study’ conducted with the help of USAID. This was critically required in the energy-starved Pakistan, where the gap between indigenous oil & gas production and demand continues to widen for a long time. Exploration & exploitation of indigenous unconventional resources of Pakistan have become vital to meet our energy demand and reduction of oil and gas import bill of the country. This study has attempted to bridge a critical gap in geological information about the potential of shale gas & oil in Pakistan in the four formations, i.e., Sembar, Lower Goru, Ranikot and Ghazij in the Middle and Lower Indus Basins, which were selected for the study as for resource assessment for shale gas & oil. The primary objective of the study was to estimate and establish shale oil/gas resource assessment of the study area by carrying out extensive geological analysis of exploration, appraisal and development wells drilled in the Middle and Lower Indus Basins, along with identification of fairway(s) and sweet spots in the study area. The Study covers the Lower parts of the Middle Indus basins located in Sindh, southern Punjab & eastern parts of the Baluchistan provinces, with a total sedimentary area of 271,795 km2. Initially, 1611 wells were reviewed, including 1324 wells drilled through different shale formations. Based on the availability of required technical data, a detailed petrophysical analysis of 124 wells (21 Confidential & 103 in the public domain) has been conducted for the shale gas/oil potential of the above-referred formations. The core & cuttings samples of 32 wells and 33 geochemical reports of prospective Shale Formations were available, which were analyzed to calibrate the results of petrophysical analysis with petrographic/ laboratory analyses to increase the credibility of the Shale Gas Resource assessment. This study has identified the most prospective intervals, mainly in Sembar and Lower Goru Formations, for shale gas/oil exploration in the Middle and Lower Indus Basins of Pakistan. The study recommends seven (07) sweet spots for undertaking pilot projects, which will enable to evaluate of the actual production capability and production sustainability of shale oil/gas reservoirs of Pakistan for formulating future strategies to explore and exploit shale/oil resources of Pakistan including fiscal incentives required for developing shale oil/gas resources of Pakistan. Some E&P Companies are being persuaded to make a consortium for undertaking pilot projects that have shown their willingness to participate in the pilot project at appropriate times. The location for undertaking the pilot project has been finalized as a result of a series of technical sessions by geoscientists of the potential consortium members after the review and evaluation of available studies.

Keywords: conventional resources, petrographic analysis, petrophysical analysis, unconventional resources, shale gas & oil, sweet spots

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Authors: Rafenomananjara Tsinjo Nirina, Tomoo Sekito, Andrianaivoravelona Jaconnet Oliva

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Manufacturing a composite material from post-consumer bottles is an interesting outlet since Madagascar is still facing the challenges of managing plastic waste on the one hand and appropriate waste treatment facilities are not yet developed on the other hand. New waste management options are needed to divert End-Of-Life (EOL) soft plastic wastes from landfills and incineration. Waste polyethylene terephthalate (PET) bottles might be considered as a valuable resource and recovered into polymer concrete. The methodology is easy to implement and appropriate to the local context in Madagascar. This approach will contribute to the production of ecological building materials that might be profitable for the environment and the construction sector. This work aims to study the feasibility of using the post-consumer PET bottles as an alternative binding agent instead of the conventional Portland cement and water. Then, the mechanical and physical properties of the materials were evaluated.

Keywords: PET recycling, polymer concrete, ecological building materials, pollution mitigation

Procedia PDF Downloads 86

Authors: Ricardo Alberto Chiong Zevallos, Eduardo Moraes Rego Reis

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Pancreatic adenocarcinoma (PDAC) patients have a less than 10% 5-year survival rate. PDAC has no defined diagnostic and prognostic biomarkers. Gemcitabine is the first-line drug in PDAC and several other cancers. Long non-coding RNAs (lncRNAs) contribute to the tumorigenesis and are potential biomarkers for PDAC. Although lncRNAs aren’t translated into proteins, they have important functions. LncRNAs can decoy or recruit proteins from the epigenetic machinery, act as microRNA sponges, participate in protein translocation through different cellular compartments, and even promote chemoresistance. The chromatin remodeling enzyme EZH2 is a histone methyltransferase that catalyzes the methylation of histone 3 at lysine 27, silencing local expression. EZH2 is ambivalent, it can also activate gene expression independently of its histone methyltransferase activity. EZH2 is overexpressed in several cancers and interacts with lncRNAs, being recruited to a specific locus. EZH2 can be recruited to activate an oncogene or silence a tumor suppressor. The lncRNAs misregulation in cancer can result in the differential recruitment of EZH2 and in a distinct epigenetic landscape, promoting chemoresistance. The relevance of the EZH2-lncRNAs interaction to chemoresistant PDAC was assessed by Real Time quantitative PCR (RT-qPCR) and RNA Immunoprecipitation (RIP) experiments with naïve and gemcitabine-resistant PDAC cells. The expression of several lncRNAs and EZH2 gene targets was evaluated contrasting naïve and resistant cells. Selection of candidate genes was made by bioinformatic analysis and literature curation. Indeed, the resistant cell line showed higher expression of chemoresistant-associated lncRNAs and protein coding genes. RIP detected lncRNAs interacting with EZH2 with varying intensity levels in the cell lines. During RIP, the nuclear fraction of the cells was incubated with an antibody for EZH2 and with magnetic beads. The RNA precipitated with the beads-antibody-EZH2 complex was isolated and reverse transcribed. The presence of candidate lncRNAs was detected by RT-qPCR, and the enrichment was calculated relative to INPUT (total lysate control sample collected before RIP). The enrichment levels varied across the several lncRNAs and cell lines. The EZH2-lncRNA interaction might be responsible for the regulation of chemoresistance-associated genes in multiple cancers. The relevance of the lncRNA-EZH2 interaction to PDAC was assessed by siRNA knockdown of a lncRNA, followed by the analysis of the EZH2 target expression by RT-qPCR. The chromatin immunoprecipitation (ChIP) of EZH2 and H3K27me3 followed by RT-qPCR with primers for EZH2 targets also assess the specificity of the EZH2 recruitment by the lncRNA. This is the first report of the interaction of EZH2 and lncRNAs HOTTIP and PVT1 in chemoresistant PDAC. HOTTIP and PVT1 were described as promoting chemoresistance in several cancers, but the role of EZH2 is not clarified. For the first time, the lncRNA LINC01133 was detected in a chemoresistant cancer. The interaction of EZH2 with LINC02577, LINC00920, LINC00941, and LINC01559 have never been reported in any context. The novel lncRNAs-EZH2 interactions regulate chemoresistant-associated genes in PDAC and might be relevant to other cancers. Therapies targeting EZH2 alone weren’t successful, and a combinatorial approach also targeting the lncRNAs interacting with it might be key to overcome chemoresistance in several cancers.

Keywords: epigenetics, chemoresistance, long non-coding RNAs, pancreatic cancer, histone modification

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Authors: Sergey V. Vinogradov

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Coastal communities are presently facing increased vulnerabilities due to rising sea levels and shifts in global climate patterns, a trend expected to escalate in the long run. To address the needs of government entities, the public sector, and private enterprises, there is an urgent need to thoroughly investigate, assess, and manage the present and projected risks associated with coastal flooding, including storm surges, sea level rise, and nuisance flooding. In response to these challenges, a practical approach to evaluating storm surge inundation risks has been developed. This methodology offers an integrated assessment of potential flood risk in targeted coastal areas. The physical modeling framework involves simulating synthetic storms and utilizing hydrodynamic models that align with projected future climate and ocean conditions. Both publicly available and site-specific data form the basis for a risk assessment methodology designed to translate inundation model outputs into statistically significant projections of expected financial and operational consequences. This integrated approach produces measurable indicators of impacts stemming from floods, encompassing economic and other dimensions. By establishing connections between the frequency of modeled flood events and their consequences across a spectrum of potential future climate conditions, our methodology generates probabilistic risk assessments. These assessments not only account for future uncertainty but also yield comparable metrics, such as expected annual losses for each inundation event. These metrics furnish stakeholders with a dependable dataset to guide strategic planning and inform investments in mitigation. Importantly, the model's adaptability ensures its relevance across diverse coastal environments, even in instances where site-specific data for analysis may be limited.

Keywords: climate, coastal, surge, risk

Procedia PDF Downloads 52

Authors: Yumi Okano

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The low level of English proficiency among Japanese people has been a problem for a long time. Japanese non-native English language teachers, under social or ideological constraints, feel a gap between government policy and their language proficiency and cannot maintain high self-esteem. This paper focuses on current Japanese policies and the social context in which teachers are placed and examines the measures necessary for their positive identity formation from a macro-meso-micro perspective. Some suggestions for achieving this are: 1) Teachers should free themselves from the idea of native speakers and embrace local needs and accents, 2) Teachers should be involved in student discussions as facilitators and individuals so that they can be good role models for their students, and 3) Teachers should invest in their classrooms. 4) Guidelines and training should be provided to help teachers gain confidence. In addition to reducing the workload to make more time available, 5) expanding opportunities for investment outside the classroom into the real world is necessary.

Keywords: language teacher identity, native speakers, government policy, critical pedagogy, investment

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Authors: Md. Nazmul Haque, Mahinur Rahman

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The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

Procedia PDF Downloads 280