Search

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.

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.

Biomedical multi-document summarization (BioMDSum) involves automatically generating concise and informative summaries from collections of related biomedical documents. While extractive summarization methods have shown promise, they often produce incoherent summaries. Onethe other hand, fully abstractive methods yield coherent summaries but demand extensive training datasets and computational resources due to the typically lengthy nature of biomedical documents. Toeaddress these challenges, weepropose a hybrid summarization method that combines the strengths of both approaches. The proposed method consists of two main phases: (i) an extractive summarization phase that uses k-means clustering to group similar sentences based on their cosine similarity between embeddings generated by the sentence-BERT model, followed by the PageRank algorithm for sentence scoring and selection; and (ii) an abstractive summarization phase that fine-tunes a Longform Encoder-Decoder (LED) transformer model to generate a concise and coherent summary from the sentences selected during the extractive phase. Weeconducted several experiments on the standard biomedical multi-document summarization datasets Cochrane and MS^2. The results demonstrate that the proposed method is competitive and outperforms recent state-of-the-art systems based on ROUGE evaluation measures. Specifically, our model achieved ROUGE-1, ROUGE-2, ROUGE-L, BERTScore, and METEOR scores of 29.41%, 6.57%, 18.31%, 85.95%, and 22.15% on the Cochrane dataset, and 28.79%, 8.22%, 17.93%, 85.51%, and 25.17% on the MS^2 dataset, respectively. Furthermore, aneablation analysis shows that integrating extractive and abstractive phases in our hybrid summarization method enhances the overall performance of the proposed approach.

Learner autonomy has attracted considerable scholarly attention in language learning. Research on this concept is abundant and continues to flourish. However, to date, scant attention has been paid to researching autonomy in the Moroccan context. Thus, the present mixed-methods study aimed to partially bridge the gap by investigating university EFL students’ beliefs and their perceived readiness level of autonomy. For this purpose, both quantitative and qualitative methods were employed to collect data. Questionnaires were administered (n=245), and interviews were conducted with selected participants (n=16). An autonomy scale consisting of five parameters (planning and goal-setting, learners’ expected teacher roles, learners’ beliefs and affect management, learners’ social behaviors, and learners’ self-assessment and learning strategies) was used to elicit and analyze data. The items that made up the learner autonomy scale were adopted and modified from different influentially existing scales. Three main themes were generated and analyzed in the qualitative strand following thematic analysis procedures. The results demonstrate that most students held positive beliefs towards autonomy and appeared ready to embrace it in their learning journey. Students exhibited a strong inclination towards using English outside the classroom (89.8%), displaying a willingness to take responsibility for their learning (85.3%), and setting learning goals (82%). The qualitative results highlight some aspects, such as participating in content creation within lessons and effectively managing their time. In light of these findings, this study suggests pedagogical implications for EFL teachers to enhance learner autonomy in their classrooms as well as a set of recommendations for future research.

Background/Objectives: This study investigates the chemical composition, antioxidant, antibacterial, and hemolytic properties of ylang-ylang (Cananga odorata) essential oil, with a focus on its potential therapeutic applications for dermatological diseases and the importance of transforming such bioactive properties into a stable, safe, and effective formulation. Methods/Rsults: Essential oils were extracted from flowers harvested in northern Grande Comore using hydro distillation at three different distillation times to examine the impact on yield and quality. Gas chromatographic analysis identified a complex mixture of compounds, including linalool, geranyl acetate, and benzyl benzoate. Antioxidant activity was assessed using DPPH, FRAP, TAC, and beta-carotene bleaching inhibition assays, revealing significant radical scavenging capabilities, with DPPH IC50 varying between 1.57 and 3.5 mg/mL. Antibacterial activity was tested against Escherichia coli, Staphylococcus aureus, Bacillus subtilis, and Pseudomonas aeruginosa, showing promising inhibition zones and minimum inhibitory concentrations. Hemolytic tests indicated varying degrees of red blood cell damage, emphasizing the need for careful concentration management in therapeutic applications. Molecular docking studies highlighted potential therapeutic targets for dermatological conditions, identifying high binding affinities for specific compounds against proteins involved in acne, eczema, and psoriasis. Conclusions: This comprehensive analysis underscores the potential of ylang-ylang essential oil (YEOs) as a natural alternative for antimicrobial treatments and dermatological applications, with its success dependent on optimized extraction methods and precise formulation to reduce cytotoxic effects. A formulation approach is crucial to ensure controlled release, improve bioavailability, and minimize skin irritation.

Abstract Purpose Conservative treatment is the first step in the management of coccydynia. However, surgical treatment is required in cases where conservative treatment fails. The aim of this study was to compare the effect of traumatic and atraumatic etiologies on functional outcomes in patients who underwent coccygectomy for chronic coccydynia. Methods Ninety-seven patients who underwent partial coccygectomy between October 2010 and December 2018 for the diagnosis of chronic coccygodynia were evaluated retrospectively. The patients were divided into two groups according to etiologies as atraumatic (group AT) and traumatic (group T). Concomitant disorders of the patients were recorded as psychiatric and musculoskeletal diseases. Visual Analog Scale (VAS) for low back pain, the Oswestry Disability Index (ODI) scale, Short Form-36 Physical Component Summary and Short Form-36 Mental Component Summary were used to evaluate the clinical outcomes pre- and postoperative at the last follow-up. Results The mean follow-up time was 67.3 ± 13.9 (range; 44–115) months. Group AT and group T included 48 (mean age 37.1 ± 11.3 and 36 (75%) female) and 49 patients (mean age 36 ± 11 and 35 (71.4%) female), respectively. The groups were statistically similar in terms of age (p = 0.614), gender (p = 0.691), body mass index (p = 0.885), tobacco usage (p = 0.603) and duration of pain (p = 0.073). However, the rate of musculoskeletal and total concomitant disorders was higher in the Group AT than in Group T (p

The last twenty years have been marked by the emergence of social mobilizations, notably Occupy Wall Street (OWS) in the United States. These mobilizations have been interpreted differently. In particular OWS has been seen by some as a “moment” rather than a “movement”. However, the evaluation of OWS raises complex questions about the nature and effectiveness of social mobilizations, particularly in terms of duration and tangible results. OWS's demands, focused on social justice and wealth redistribution, did not yield the desired outcomes, leading to debates about the success or failure of the movement. Nevertheless, some observers argue that OWS has had a lasting impact by changing political discourse and by inspiring other progressive movements. In conclusion, the legacy of OWS remains a subject of debate, but it has contributed to reshaping the American political landscape and fueling a new wave of social mobilization.

Écrivain méconnu pendant un demi-siècle, Victor Segalen a dû attendre les années 1960 pour que son œuvre soit exhumée, éditée et commentée. Parmi les raisons de cette méconnaissance, figure en tête de liste le parcours quelque part typique de l’auteur. De formation scientifique, destiné à être un médecin de la marine, Segalen n’a pourtant épargné aucun effort pour donner suite à ses ambitions littéraires et artistiques. Son attachement indéfectible à la littérature et à l’art l’amène à lutter pour s’affranchir des règles contraignantes de son milieu familiale, réfractaire au monde littéraire. C’est dans ce contexte que cet article se propose d’examiner les débuts littéraires de l’auteur, de façon à montrer comment est né l’homme de lettres qu’il est devenu.

Since the global COVID-19 pandemic, traditional classrooms have no longer become accessible for everyone. Most teaching and learning process is conducted virtually. The use of interactive and dynamic pedagogy is needed to maintain the quality of learning, especially that enhance argumentation and literacy skills. This research aims to examine whether there are differences in literacy and argumentation skills of Indonesian university students before and after the implementation of Collaborative Reasoning (CR) approach during online learning. A quasi-experimental one-group pretest-and posttest design was employed. A total of 30 students taking Communication and Gender course were involved in this research. We developed a Reading Comprehension Test (RCT) to collect the literacy scores of the students and Cognitively Based Assessment of, for, and as Learning (CBAL) Argumentation Progression to measure argumentation scores. Using a paired samples t-test, the literacy and argumentation scores of the students before participating in CR were compared to their scores after participating in CR. The literacy and argumentation scores were significantly higher after participating in CR. This finding indicates that there is an increase in literacy and argumentation scores over time that was not likely to be due to chance. It is pivotal then for language educators to consider CR in their classrooms.

The orthophosphate BaNi2Fe(PO4)3 has been synthesized by a solid-state reaction route and characterized by single-crystal X-ray diffraction and energy-dispersive X-ray spectroscopy. The crystal structure comprises (100) sheets made up of [Ni2O10] dimers that are linked to two PO4 tetrahedra via common edges and vertices and of linear infinite [010] chains of corner-sharing [FeO6] octahedra and [PO4] tetrahedra. The linkage of the sheets and chains into a framework is accomplished through common vertices of PO4 tetrahedra and [FeO6] octahedra. The framework is perforated by channels in which positionally disordered Ba2+ cations are located.

Offensive communications have invaded social media content. One of the most effective solutions to cope with this problem is using computational techniques to discriminate offensive content. Moreover, social media users are from linguistically different communities. This study aims to tackle the Multilingual Offensive Language Detection (MOLD) task using transfer learning models and the fine-tuning phase. We propose an effective approach based on the Bidirectional Encoder Representations from Transformers (BERT) that has shown great potential in capturing the semantics and contextual information within texts. The proposed system consists of several stages: (1) Preprocessing, (2) Text representation using BERT models, and (3) Classification into two categories: Offensive and non-offensive. To handle multilingualism, we explore different techniques such as the joint-multilingual and translation-based ones. The first consists in developing one classification system for different languages, and the second involves the translation phase to transform all texts into one universal language then classify them. We conduct several experiments on a bilingual dataset extracted from the Semi-supervised Offensive Language Identification Dataset (SOLID). The experimental findings show that the translation-based method in conjunction with Arabic BERT (AraBERT) achieves over 93% and 91% in terms of F1-score and accuracy, respectively.

Osama Mahmoud Momtaz,1 Omar M Said,2 Amany Mahmoud Mohamed,1 Tamer Sayed Abdel Mawla1 1Critical Care Department, Fayoum University, Fayoum, Egypt; 2Ophthalmology Department, Fayoum University, Fayoum, EgyptCorrespondence: Omar M Said, Ophthalmology Department, Fayoum University, Fayoum, Egypt, Email Oms01@fayoum.edu.egBackground: Ultrasonographic measurement of optic nerve sheath diameter is a simple, non-invasive, and reliable method of detecting elevated intracranial pressure (ICP) in critical patients. Optic nerve sheath communicates with the dura mater covering the brain and contains cerebrospinal fluid, allowing pressure transmission from the cranium. Therefore, changes in cerebrospinal fluid (CSF) pressure have been shown to produce changes in ONSD.Objective: This study aimed to assess the accuracy of optic nerve sheath diameter (ONSD) in diagnosis and follow-up patients with disturbed conscious levels compared with CT brain and fundus examination.Patients and Methods: One hundred forty-one participants were included in the study, classified into 76 cases admitted with disturbed conscious levels due to elevated ICP and 65 controls. All patients were subjected to CT brain and optic nerve US and fundus examination at the time of admission and follow-up after 48 h after proper management.Results: The current study showed that ONSD is significant in predicting elevated ICP at the cut-off point of average ONSD of 5.19 mm with 97% sensitivity and 98% specificity, and the area under the curve (AUC) was 0.996. The present study revealed a significant inverse correlation between ONSD and GCS in patients with increased ICP.Conclusion: Ultrasonic measurement of ONSD is a promising technique in diagnosing and following patients with disturbed conscious levels.Keywords: ultrasonographic, optic nerve sheath diameter, disturbed conscious level

Single crystals of β-KCoFe(PO4)2, potassium cobalt(II) iron(III) bis(orthophosphate), were grown from the melt under atmospheric conditions. This phosphate crystallizes isotypically with KZnFe(PO4)2 in space group C2/c, adopting a zeolite-ABW type of structure. The structure of the present phosphate is distinguished by an occupational disorder of the two transition-metal sites with ratios Fe:Co of 0.5725:0.4275 for the first and 0.4275:0.5725 for the second site. In the crystal structure, PO4 and (Co,Fe)O4 tetrahedra are linked through vertices to form elliptical rings with the sequence DDDDUUUU of up (U) and down (D) pointing vertices. Each eight-membered ring is surrounded by four other rings of the same type, delimiting interstices with rectangular shape. This arrangement leads to the formation of [(Co/Fe)(PO4)]−∞ sheets parallel to (001). Stacking of the sheets into a three-dimensional framework results in the formation of two types of channels. The first one is occupied by potassium cations, whereas the second one remains vacant. Calculations of bond-valence sums and charge distribution were used to confirm the structure model.

Abstract Background Typhlodromus setubali Dosse (Acari: Phytoseiidae) is an indigenous predatory mite in Morocco. This study aimed to evaluate its efficacy, through 3 release rates on 2 apple varieties, namely Skarlet and Golden delicious, with different initial densities of the European red spider mite, Panonychus ulmi Koch (Acari: Tetranychidae). Results The efficacy of the predator was significantly influenced by the initial P. ulmi density. Furthermore, the release rate of 50 individuals/tree did not provide effective control of P. ulmi. When it was released at 100 and 200 individuals per tree, T. setubali maintained the P. ulmi population below the economic threshold of 5 motile stages per leaf. Conclusions When the initial P. ulmi density is above the economic threshold, the lower release rate of T. setubali must be applied with high frequency or conciliated with a selective miticide treatment at a suitable dose for a successful biological control program. Further field-based studies are needed for perfect conclusions.

Abstract Accurate epidemiological models are necessary for governments, organizations, and individuals to respond appropriately to the ongoing novel coronavirus pandemic. One informative metric epidemiological models provide is the basic reproduction number ( $$R_0$$ R 0 ), which can describe if the infected population is growing ( $$R_0 > 1$$ R 0 > 1 ) or shrinking ( $$R_0 < 1$$ R 0 < 1 ). We introduce a novel algorithm that incorporates the susceptible-infected-recovered-dead model (SIRD model) with the long short-term memory (LSTM) neural network that allows for real-time forecasting and time-dependent parameter estimates, including the contact rate, $$\beta$$ β , and deceased rate, $$\mu$$ μ . With an accurate prediction of $$\beta$$ β and $$\mu$$ μ , we can directly derive $$R_0$$ R 0 , and find a numerical solution of compartmental models, such as the SIR-type models. Incorporating the epidemiological model dynamics of the SIRD model into the LSTM network, the new algorithm improves forecasting accuracy. Furthermore, we utilize mobility data from cellphones and positive test rate in our prediction model, and we also present a vaccination model. Leveraging mobility and vaccination schedule is important for capturing behavioral changes by individuals in response to the pandemic as well as policymakers.