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In solar PV fields, solar photovoltaic panels are typically arranged in parallel rows one after the other. This arrangement introduces variations in the distribution of solar irradiance over the entire field, compared to measurements recorded at meteorological weather stations and data obtained from climatic database platforms. This is due to the difference in the view factors between the rows of the solar PV field and a single surface, as well as the presence of shade on rear sides and in the space separating the rows. These phenomena combined will reduce the intensity of solar irradiance incident on the PV solar field; consequently will reduce the energy yields. Accurate estimation of solar radiation on solar fields requires knowledge of the sky, ground, and rear side of the preceding row view factors, and an estimation of the time and space occupied by the row’s shadow. Prior literature has addressed this issue using two-dimensional (2-D) techniques such as the crossed-strings method (CSM). This study developed a novel three-dimensional (3-D) analysis in addition to numerical analysis to determine the view factors associated with solar fields. The study uses both isotropic and anisotropic transposition analyses to determine solar irradiance incident on the solar field with varying tilt angles of solar panels and distance separating the rows (distance aspect ratio) for several latitudes. The present research also tested the validity of the CSM for wide ranges of distance separating rows and length aspect ratios, the obtained results show that the CSM shows good agreements in both sky and ground view factor in the range of length aspect ratio greater than one. But the CSM fails in rear-side view factor in the design ranges of PV solar fields, where the error rate was found about 11%, this result is important in the case of bifacial PV solar systems. Also, the present work compared the solar irradiance calculated for a single surface with that incident on a PV solar field for wide range of sky conditions and latitudes. The obtained results ensure the accuracy of using the solar irradiance incident on a single surface data for low latitudes and for most sky conditions for PV rooftop solar systems as well as PV solar fields. While it has remarked a large error in the case of cloudy skies, where the error rate exceeded 17% in the case of aspect ratio equals to 1.5 and about 15.5% in the aspect ratio of 2.0.

Nonalcoholic fatty liver disease (NAFLD) is closely related to insulin resistance, metabolic syndrome, obesity, type 2 diabetes, and dyslipidaemia. Obesity and metabolic syndrome are associated with an increased cancer risk, and recent evidence demonstrated an association between NAFLD and colorectal cancer (CRC). The mechanism of how NAFLD can be associated with increased risk of CRC is not fully understood; however, NAFLD represents a condition of profound insulin resistance and a proinflammatory state. Insulin and insulin-like growth factors may promote the development of CRC through their proliferative and antiapoptotic effects. Patients with NAFLD have reduced expression of adiponectin, an adipokine with anti-inflammatory effects. Importantly, hypoadiponectinemia is associated with an increased risk of CRC. Decreased levels of adiponectin lead to increased insulin levels due to marked insulin resistance and in turn increased insulin growth factor-1 (IGF-1). Insulin binds to IGF-1 receptors and plays an important role in cell proliferation, apoptosis, and increased production of vascular endothelial growth factor, an angiogenic factor that supports cancer growth. Further studies are needed to establish (i) the pathophysiology of NAFLD with colorectal cancer, (ii) the benefit of early screening of CRC in NAFLD patients, and (iii) the impact of treatment of NAFLD in the modulation of the risk of colorectal cancer.

Abstract In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate predictors from noisy, heterogeneous, small sample sizes and data with limited annotations. This paper reviews how AI is being used to analyze extreme climate events (like floods, droughts, wildfires, and heatwaves), highlighting the importance of creating accurate, transparent, and reliable AI models. We discuss the hurdles of dealing with limited data, integrating real-time information, and deploying understandable models, all crucial steps for gaining stakeholder trust and meeting regulatory needs. We provide an overview of how AI can help identify and explain extreme events more effectively, improving disaster response and communication. We emphasize the need for collaboration across different fields to create AI solutions that are practical, understandable, and trustworthy to enhance disaster readiness and risk reduction.

This paper investigated the technical, economic, and environmental aspects of using six different power plant configurations powered by renewable energy sources (RES), namely photovoltaic (PV) and wind to provide electricity to operate a reverse osmosis brackish groundwater desalination plant (BWRO) with a capacity of 2 m3/hr, and load power of 6.5 kW. The BWRO plant is located at the Libyan Center for Solar Energy Research and Studies (LCSERS) in the city of Tajura. The six proposed power plants, backed-up with/out batteries and diesel generator were modeled and simulated using HOMER software. Optimal design configurations resulting from the simulation were then selected based on levelized cost of energy (LCOE) and net present cost (NPC) appropriate to the operating conditions at the site. The study showed that the Grid- Connected photovoltaic power plant (PVGC) yielded the lowest levelized cost of water (LCOW), a direct consequence of its lower cost of energy. [ABSTRACT FROM AUTHOR]

Abstract Defining end-to-end (or online) training schemes for the calibration of neural sub-models in hybrid systems requires working with an optimization problem that involves the solver of the physical equations. Online learning methodologies thus require the numerical model to be differentiable, which is not the case for most modeling systems. To overcome this, we present an efficient and practical online learning approach for hybrid systems. The method, called EGA for Euler Gradient Approximation, assumes an additive neural correction to the physical model, and an explicit Euler approximation of the gradients. We demonstrate that the EGA converges to the exact gradients in the limit of infinitely small time steps. Numerical experiments show significant improvements over offline learning, highlighting the potential of end-to-end learning for hybrid modeling.

Arabic biomedical question classification (ABQC) is a challenging task due to various reasons including, the specialized jargon expressed in Arabic language, complex semantics of Arabic vocabulary and the lack of specific datasets and corpora. When representing questions, only a few studies deal with ABQC by taking into account the word context. In this work, we propose a classification model designed for Arabic biomedical questions. We build vector representations capturing the contextual and semantic information of Arabic biomedical text, which presents numerous challenges, such as the derivational morphology of Arabic language, the specialized terminology of biomedical terms and the lack of capitalization in text. Our representation adapts the extensive knowledge encoded in BERT (Bidirectional Encoder Representations from Transformers) and other transformer models, to address the aforementioned challenges. Several experiments have been conducted on a dedicated Arabic biomedical dataset namely: MAQA, with well-known transformer models including BERT, AraBERT, BioBERT, RoBERTa, and DistilBERT fine-tuned for the classification task. Obtained results show that our method achieves remarkable performance with an accuracy of 93.31% and an F1-score of 93.35%. Doi: 10.28991/HIJ-2024-05-04-011 Full Text: PDF

IntroductionHarnessing plant growth-promoting rhizobia presents a sustainable and cost-effective method to enhance crop performance, particularly under drought stress. This study evaluates the variability of plant growth-promoting (PGP) traits among three strains of Rhizobium laguerreae LMR575, LMR571, and LMR655, and two native PGP strains Bacillus LMR698 and Enterobacter aerogenes LMR696. The primary objective was to assess the host range specificity of these strains and their effectiveness in improving drought tolerance in three legume species: Pisum sativum, Vicia faba, and Phaseolus vulgaris.MethodsIn-vitro experiments were conducted to assess the PGP traits of the selected strains, including phosphate solubilization, indole-3-acetic acid (IAA) production, and siderophore production. Greenhouse trials were also performed using a mixed inoculum of performing strains to evaluate their effects on plant physiological and biochemical traits under drought conditions.ResultsSignificant variability in PGP traits was observed among the strains. R. laguerreae LMR655 exhibited the highest phosphate solubilization (113.85 mg mL-1 PO42-), while R. laguerreae LMR571 produced the highest IAA concentration (25.37 mg mL-1). E. aerogenes LMR696 demonstrated 82% siderophore production. Symbiotic interactions varied, with R. laguerreae LMR571 and LMR655 forming associations with P. sativum and V. faba, but none establishing compatibility with P. vulgaris. Greenhouse experiments showed that a mixed inoculum of R. laguerreae LMR571, LMR655, and E. aerogenes LMR696 significantly improved proline, total soluble sugars, proteins, and chlorophyll content under drought stress, with V. faba showing the strongest response.DiscussionThese findings highlight the importance of strain selection based on host specificity and PGP potential. The enhanced drought tolerance observed suggests that tailored microbial inoculants can improve legume resilience in water-limited environments. This study provides valuable insights for optimizing bioinoculant formulations to enhance crop performance under drought stress.

In this study, specimens of AlSi10Mg fabricated by laser-powder bed fusion were exposed to 200, 220, 240, 260, 275, and 300 °C for various times to characterize the changes in mechanical properties over time. The duration of each isothermal treatment was varied from 15 min to 1000 h; one group of specimens was left in the "as-printed" condition as a control. The resulting microstructure and mechanical properties were characterized. Percent elongation, 0.2% offset yield strength, ultimate tensile strength, and hardness were measured and compared. The morphology of the silicon-rich phase was observed at several time and temperature conditions using optical and scanning electron microscopy. The strength and hardness decreased while the elongation increased 1) with increasing time at a given temperature and 2) with increasing temperature for any given time of exposure. The properties never reached a stable value for the durations of the exposures in this study, as indicated by the change in measurements after 300 °C and 1000-h exposure. The effects of time and temperature on mechanical properties are modeled well with the Larson–Miller parameter. The microstructure changes from having a fine network of silicon-rich precipitates to a coarse, equiaxed silicon particles with increased temperature of exposure. [ABSTRACT FROM AUTHOR]

Tambourissa comorensis (TC) is a member of the Monimiaceae family endemic to the Comoros Islands where it is regarded as a medicinal plant. In this study, the fatty acids (FA) composition and profile of air-dried powdered fruits of TC were examined by GC-MS. Based on the results, four major common fatty acids were tentatively identified as well as five other minor fatty acids. The analysis revealed the presence of both saturated and unsaturated fatty acids. The dried fruits exhibited oleic acid (30.64%) and linoleic acid (29.13%) as the dominant fatty acids, while palmitic acid (17.95%) and stearic acid (4.25%) were the main saturated FA identified. These fatty acids were isolated as pure compounds, with the exception of stearic acid, which was obtained as a mixture from crude lipid n-hexane extract fractionation on a silica gel column chromatography and identified in their free form by 2D-1H-NMR (300 MHz), 13C-NMR (75 MHz) and infrared (IR) spectroscopies. The average oil content in dried powdered fruits of T. comorensis species was estimated to be approximately 8%, with saturated fatty acids, monounsaturated, and polyunsaturated ones constituting about 22.67%, 32.07%, and 29.13%, respectively. T. comorensis fruits were found to be rich in health-promoting compounds, suggesting potential applications in the food, cosmetic, or pharmaceutical industries. This study is the first to profile the fatty acids in T. comorensis fruits, laying foundations for further exploration into their nutritional and therapeutic properties, as well as their potential roles in regional biodiversity and chemodiversity.

Privacy and efficient data processing are crucial research areas in the field of outsourcing computing. Thus, the contribution of the paper is twofold. First of all, we develop a secure offloading technique that can process data while preserving privacy. Although RSA and Paillier cryptosystems are highly beneficial for mathematical operations on basic encrypted data due to their homomorphic properties, images are processed using permutation-ordered binary (POB) and Shamir's secret sharing (SSS). Second, a non-cooperative game theory model was formulated to examine the interactions between service providers, characterizing each edge as an M/M/1 system with an infinite queue. Through formal verification using rigorous mathematical reasoning, the suggested strategies for task offloading and resource allocation are shown to be effective in terms of security, quality of service (QoS), and energy consumption. The best-response dynamics approach is used to calculate the final strategy for each participant and assess how fairly resources are allocated. Finally, the potential of our approach is demonstrated numerically, revealing a faster convergence towards attaining Nash equilibrium in a duopoly cloud-edge data center market, granted that the necessary and sufficient conditions are met.

Research on writing strategies has defined their characteristics and focused on their contribution to writing gains over the last few decades. However, little has been written about how Moroccan EFL students perceive and use these strategies in their attempts to produce an essay. This paper seeks to fill that gap by investigating the employment of writing strategies by 245 students majoring in English at a university. The data were collected through a questionnaire, inspired by some related existing scales, and interviews were conducted with a group of participants. The participants were sampled adhering to the convenience type of sampling since the data collection was completed in one of the students’ usual classes. Combining both quantitative and qualitative analyses, findings demonstrated that writing strategies were used to a higher extent, with the students’ strong tendency to deploy memory and compensation strategies. It was also found that there is a positive and significant correlation between students’ use of writing strategies and argumentative writing. The qualitative findings added that the although the participants said they practiced writing strategies, the majority did not know how to use them. Some implications and recommendations are also discussed. The current study has provided useful insights into students’ readiness to use writing strategies in the Moroccan context and how their use may mitigate their difficulties in producing a well-argued essay.

Le texte revient sur le rôle du Congrès en tant que branche principale du gouvernement, bénéficiant d’un statut prééminent dans la hiérarchie constitutionnelle. Le Congrès détient un pouvoir de contrôle particulier sur les autres branches du gouvernement. Cependant, malgré son rôle puissant en théorie, le Congrès n’a pas activé les leviers dont il dispose pour agir après les événements entourant l'élection présidentielle de 2020 et l’attaque du Capitole en janvier 2021. La réflexion soulève les défis auxquels le Congrès est confronté pour coordonner une réponse efficace et suggère que des réformes pourraient être nécessaires pour renforcer son rôle dans la protection et la préservation de la démocratie américaine. En fin de compte, une réflexion sur le fonctionnement des institutions et leur capacité à faire face aux défis politiques majeurs semble nécessaire.