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Background: The accuracy of spelling in Electronic Health Records (EHRs) is a critical factor for efficient clinical care, research, and ensuring patient safety. The Persian language, with its abundant vocabulary and complex characteristics, poses unique challenges for real-word error correction. This research aimed to develop an innovative approach for detecting and correcting spelling errors in Persian clinical text. Methods: Our strategy employs a state-of-the-art pre-trained model that has been meticulously fine-tuned specifically for the task of spelling correction in the Persian clinical domain. This model is complemented by an innovative orthographic similarity matching algorithm, PERTO, which uses visual similarity of characters for ranking correction candidates. Results: The evaluation of our approach demonstrated its robustness and precision in detecting and rectifying word errors in Persian clinical text. In terms of non-word error correction, our model achieved an F1-Score of 90.0% when the PERTO algorithm was employed. For real-word error detection, our model demonstrated its highest performance, achieving an F1-Score of 90.6%. Furthermore, the model reached its highest F1-Score of 91.5% for real-word error correction when the PERTO algorithm was employed. Conclusions: Despite certain limitations, our method represents a substantial advancement in the field of spelling error detection and correction for Persian clinical text. By effectively addressing the unique challenges posed by the Persian language, our approach paves the way for more accurate and efficient clinical documentation, contributing to improved patient care and safety. Future research could explore its use in other areas of the Persian medical domain, enhancing its impact and utility. [ABSTRACT FROM AUTHOR]

Using exact algorithms in complex environments with multi-objective criteria cannot be considered an appropriate method. For this reason, nature-inspired meta-heuristic methods have been proposed to solve problems such as flexibility in the cloud computing environment. In this research, we use the particle swarm optimisation algorithm and auction approach for two-way load balancing. A cloud computing centre comprises several physical machines called data centres, and data centres consume a lot of energy. To increase efficiency, there is a need to increase flexibility in these systems. The researchers proposed Various methods such as static and dynamic management of virtual machines and automatic processor frequency change systems to reduce energy consumption. In this article, we presented an algorithm based on under-load hosts and particle swarm optimisation and mass movement of virtual machines according to the auction rule to reduce energy as the dynamic management of cloud resources. The proposed method has been evaluated by the cloudsim simulator with PlanetLab real dataset. The experimental results show that, in comparison to the other algorithms, energy consumption has improved and SLA violation has decreased. As well as migration of VMs decreased significantly. [ABSTRACT FROM AUTHOR]

Objective: This study explores the frequency of human leukocyte antigen (HLA) genes, particularly HLA-B alleles, within the Kuwaiti population. We aim to identify alleles with known associations to adverse drug reactions (ADRs) based on existing literature. We focus on the HLA-B gene due to its well-documented associations with severe cutaneous adverse reactions and the extensive pharmacogenetic research supporting its clinical relevance. Methods: We utilized the HLA-HD tool to extract, annotate, and analyse HLA-B alleles from the exome data of 561 Kuwaiti individuals, sequenced on the Illumina HiSeq platform. HLA typing was conducted using the HLA-HD tool with a reference panel from the IPD-IMGT/HLA database. The major HLA-B pharmacogenetic markers were obtained from the HLA Adverse Drug Reaction Database, focusing on alleles with significant ADR associations in published literature. Results: The distribution of HLA-B alleles in the Kuwaiti population revealed that the most frequent alleles were HLA-B*50:01 (10.52%), HLA-B*51:01 (9.89%), HLA-B*08:01 (6.06%), HLA-B*52:01 (4.55%), HLA-B*18:01 (3.92%), and HLAB* 41:01 (3.65%). Notably, alleles HLA-B*13:01, HLA-B*13:02, HLA-B*15:02, HLA-B*15:13, HLA-B*35:02, HLA-B*35:05, HLA-B*38:01, HLA-B*40:02, HLAB* 44:03, HLA-B*51:01, HLA-B*57:01 and HLA-B*58:01 were identified with known associations to various ADRs. For example, HLA-B*51:01 was associated with clindamycin, phenobarbital, and phenytoin, and was found in 18% of individuals. Conclusion: Our study enriches the regional genetic landscape by delineating HLA-B allele variations within Kuwait and across the Arabian Peninsula. This genetic insight, along with the identification of markers previously linked to drug hypersensitivity, provides a foundation for future pharmacogenetic research and potential personalized medicine strategies in the region. [ABSTRACT FROM AUTHOR]

Head lice infestations are the most prominent ectoparasitic infection in the world, including Iran, particularly among school children. Recently, numerous cases of infestation have been reported in various provinces of the country. This study aimed to investigate the prevalence of head louse infestations and analyze kdr gene sequences in terms of resistance mutations in the Torbat-e Heydarieh, Mahvelat, and Zaveh cities of Khorasan Razavi Province, Northeast Iran. The data related to the epidemiological and demographic history of head lice populations were extracted from their medical records and analyzed in Excel software. After extracting the genomic DNA, the kdr fragment was amplified using specific primers. The sequences were also analyzed using bioinformatics software. The prevalence of head louse infestations was 1.59% and 1.7% during 2016 and 2017, respectively. Sequence analysis revealed the frequency distribution of two kdr haplotypes, I and V, in the study areas. The increase in head louse infestations in recent years and the simultaneous presence of kdr mutations indicate the need for new treatments and monitoring/controlling resistance to head louse insecticides. [ABSTRACT FROM AUTHOR]

Surrogate optimisation holds a big promise for building energy optimisation studies due to its goal to replace the use of lengthy building energy simulations within an optimisation step with expendable local surrogate models that can quickly predict simulation results. To be useful for such purpose, it should be possible to quickly train precise surrogate models from a small number of simulation results (10–100) obtained from appropriately sampled points in the desired part of the design space. Two sampling methods and two machine learning models are compared here. Latin hypercube sampling (LHS), widely accepted in building energy community, is compared to an exploratory Monte Carlo-based sequential design method mc-intersite-proj-th (MIPT). Artificial neural networks (ANN), also widely accepted in building energy community, are compared to gradient-boosted tree ensembles (XGBoost), model of choice in many machine learning competitions. In order to get a better understanding of the behaviour of these two sampling methods and two machine learning models, we compare their predictions against a large set of generated synthetic data. For this purpose, a simple case study of an office cell model with a single window and a fixed overhang, whose main input parameters are overhang depth and height, while climate type, presence of obstacles, orientation and heating and cooling set points are additional input parameters, was extensively simulated with EnergyPlus, to form a large underlying dataset of 729,000 simulation results. Expendable local surrogate models for predicting simulated heating, cooling and lighting loads and equivalent primary energy needs of the office cell were trained using both LHS and MIPT and both ANN and XGBoost for several main hyperparameter choices. Results show that XGBoost models are more precise than ANN models, and that for both machine learning models, the use of MIPT sampling leads to more precise surrogates than LHS. [ABSTRACT FROM AUTHOR]

Automatic spelling correction stands as a pivotal challenge within the ambit of natural language processing (NLP), demanding nuanced solutions. Traditional spelling correction techniques are typically only capable of detecting and correcting non-word errors, such as typos and misspellings. However, context-sensitive errors, also known as real-word errors, are more challenging to detect because they are valid words that are used incorrectly in a given context. The Persian language, characterized by its rich morphology and complex syntax, presents formidable challenges to automatic spelling correction systems. Furthermore, the limited availability of Persian language resources makes it difficult to train effective spelling correction models. This paper introduces a cutting-edge approach for precise and efficient real-word error correction in Persian text. Our methodology adopts a structured, multi-tiered approach, employing semantic analysis, feature selection, and advanced classifiers to enhance error detection and correction efficacy. The innovative architecture discovers and stores semantic similarities between words and phrases in Persian text. The classifiers accurately identify real-word errors, while the semantic ranking algorithm determines the most probable corrections for real-word errors, taking into account specific spelling correction and context properties such as context, semantic similarity, and edit-distance measures. Evaluations have demonstrated that our proposed method surpasses previous Persian real-word error correction models. Our method achieves an impressive F-measure of 96.6% in the detection phase and an accuracy of 99.1% in the correction phase. These results clearly indicate that our approach is a highly promising solution for automatic real-word error correction in Persian text. [ABSTRACT FROM AUTHOR]

The ongoing increase in wild boar populations across Europe has fostered human–wildlife conflicts, including the transmission of emerging pathogens with zoonotic importance. Blastocystis is a ubiquitous, faecal-oral transmitted protist that can cause gastrointestinal illnesses and is observed in humans and animals worldwide. The role of wildlife in the epidemiology of Blastocystis is insufficiently understood. Thus, we investigated the occurrence and subtype diversity of Blastocystis in free-ranging wild boars from the Iberian Peninsula using conventional PCR and next-generation amplicon sequencing of a fragment of the ssu RNA gene. A total of 459 wild boar faecal samples were collected across Spain (n = 360) and Portugal (n = 99) between 2014 and 2021. Blastocystis was present in 15.3% (70/459; 95% CI 12.1–18.9) of the wild boars analysed, and its occurrence was significantly higher in Portugal (34.3%, 34/99; 95% CI 25.1–44.6) than in Spain (10.0%, 36/360; 95% CI 7.1–13.6). Seven Blastocystis subtypes (ST5, ST10b, ST13–ST15, ST24b, and ST43) were detected among the surveyed wild boar populations, with greater variability detected in Portuguese samples. ST5 was identified in all the Blastocystis-positive animals, whereas 14.3% of them harboured ST mixed colonisations. Our results demonstrate that Blastocystis ST5 is particularly adapted to infect wild boars. The additional identification of zoonotic STs reinforces the role of wild boars as spreaders of zoonotic infections with public health significance. [ABSTRACT FROM AUTHOR]

Background: Despite successful efforts to eliminate measles in Iran, imported measles cases continue to be reported. Because measles is endemic in neighboring countries. This research aims to evaluate the risk of measles transmission in different regions of Iran. Methods: Measles case-based surveillance data of the Expanded Program of Immunization containing 31 provinces and 463 districts from 2019 to 2021 were assessed. The WHO Measles Programmatic Risk Assessment tool was used to evaluate the risk of disease transmission in four domains: population immunity, surveillance quality, program delivery performance, and threat assessment. scores were categorized as low, medium, high, or very high risk. Results: During 2019–2021, the average incidence of measles was 1.9 per 1 million. Chabahar and Mashhad with 76 and./6per million reported the highest and lowest incidence respectively. All 463 districts were categorized as low risk in risk assessment. Andimeshk, Chabahar, and Bojnurd obtained the highest risk scores with 27, 24, and 25 respectively. All districts were classified as low risk for population immunity. The average coverage of (MMR1) and (MMR2) was 95% or higher. All districts received the minimum points for surveillance quality. Conclusion: All regions are placed at a low level of disease transmission risk. However, the tool is not able to assess the risk at the rural or peripheral sectors level. The indicators used in this tool are the same for all countries with different epidemiological features (elimination, endemic). Sensitivity analysis can optimize the use of this tool for countries with different disease conditions. [ABSTRACT FROM AUTHOR]

Purpose: The objective examination of the Post-COVID syndrome (PCS) remains difficult due to heterogeneous definitions and clinical phenotypes. The aim of the study was to verify the functionality and correlates of a recently developed PCS score. Methods: The PCS score was applied to the prospective, multi-center cross-sectoral cohort (in- and outpatients with SARS-CoV-2 infection) of the "National Pandemic Cohort Network (NAPKON, Germany)". Symptom assessment and patient-reported outcome measure questionnaires were analyzed at 3 and 12 months (3/12MFU) after diagnosis. Scores indicative of PCS severity were compared and correlated to demographic and clinical characteristics as well as quality of life (QoL, EQ-5D-5L). Results: Six hundred three patients (mean 54.0 years, 60.6% male, 82.0% hospitalized) were included. Among those, 35.7% (215) had no and 64.3% (388) had mild, moderate, or severe PCS. PCS severity groups differed considering sex and pre-existing respiratory diseases. 3MFU PCS worsened with clinical severity of acute infection (p =.011), and number of comorbidities (p =.004). PCS severity was associated with poor QoL at the 3MFU and 12MFU (p <.001). Conclusion: The PCS score correlated with patients' QoL and demonstrated to be instructive for clinical characterization and stratification across health care settings. Further studies should critically address the high prevalence, clinical relevance, and the role of comorbidities. Trail registration number: The cohort is registered at www.clinicaltrials.gov under NCT04768998. [ABSTRACT FROM AUTHOR]

An aqueous two-phase system (ATPS) composed of PEG35000, Na2CO3, K2CO3, and their mixtures at 298 K was studied. The liquid–liquid equilibrium (LLE) of these systems, including binodal curves, tie-lines, tie-line length, and slope of the tie-line, were obtained. Additionally, for the first time, salt mixtures with different initial mass ratios of 1:3, 1:1, and 3:1 were used to prepare the aqueous two-phase systems. The effect of electrolyte and salting-out power for these systems was examined and compared. Consistent with the literature, it was found that the salting-out power of Na+ is higher than that of the K+ cation. Furthermore, in Na2CO3 and K2CO3 mixtures, increasing the amount of sodium ions resulted in stronger salting-out power. The LLE data was correlated with the Othmer-Tobias, Bancroft, and Setschenow models, and good agreement was found with all three models. [ABSTRACT FROM AUTHOR]

Budesonide (BDS) a steroid-based anti-inflammatory drug widely prescribed for various diseases, has a low aqueous solubility. In this study, we investigated cosolvency approach to study the thermodynamic specifications related to the solubility of BDS at the temperature range of 293.2–313.2 K in (1-propanol + water) mixtures applying the shaking flask method. The predictive power of different mathematical models for experimental data in the cosolvency systems was evaluated. For this purpose, the linear and nonlinear mathematical equations such as van't Hoff model (as a linear model), Buchowski-Ksiazczak equation (as a non-linear), CNIBS/R–K and MRS models (as a linear model for solvent composition at an isothermal condition), modified Wilson model (as a non-linear model for isothermal condition), the Jouyban-Acree model (as a model that considers temperature and solvent composition), and Jouyban-Acree-van't Hoff model (as a model with no further input data) were studied. Also, the Williams-Amidon excess Gibbs energy model was investigated. In addition, the related apparent thermodynamics of the BDS dissolution process in the desired temperature such as Gibbs free energy, enthalpy, and entropy, were computed by the corresponding equations. Moreover, based on the inverse Kirkwood-Buff integrals, it is demonstrated that BDS is preferentially solvated by water in water-rich mixtures. The accuracy of the fitness was evaluated with mean relative deviations (MRDs%) for back-calculated molar BDS solubility data. The result showed that the maximum solubility of BDS was obtained at 0.7 mass fraction of 1-propanol at all temperatures. Thermodynamic studies demonstrated that BDS dissolution procedures were obtained as endothermic and entropy-driven in almost all cases. The overall MRDs% values for the back-computed BDS solubility in the aqueous mixture of 1-propanol based on van't Hoff model, Buchowski-Ksiazczak equation, CNIBS/R–K model, modified Wilson model, Jouyban-Acree model, Jouyban-Acree-van't Hoff model, MRS model, and Williams-Amidon excess Gibbs energy model were found 1.93%, 1.80%, 11.68%, 33.32%, 12.30%, 9.24%, 10.70%, and 6.57%, respectively. Highlights: Study of BDS solubility profile in 1-propanol + water mixtures at 293.2 -313.2 K Prediction solubility with two Jouyban-Acree models: Jouyban-Acree equation and Jouyban-Acree-van't Hoff model Representation of BDS solubility data with some linear and nonlinear cosolvency models Utilize the van't Hoff and Gibbs equations to compute thermodynamic parameters [ABSTRACT FROM AUTHOR]

A multiplex, delay‐and‐sum (MDAS) architecture is proposed to implement a fixed‐focus receive beamformer such as the first stage of the synthetic aperture sequential beamforming (P‐SASB) and synthetic transmit beams combined with the P‐SASB (STB‐P‐SASB) beamforming methods. The output image of this architecture has a resolution and contrast‐to‐noise ratio (CNR) almost similar to that of the delay‐and‐sum (DAS) architecture. In the analog part of this architecture, there is no need to use any analog memory and in the digital part, the need to use high‐speed memories and interpolation filter is eliminated. In this architecture for each input channel, the power consumption in the mixed‐signal part is increased by approximately 1.14 mW in comparison to that of the DAS architecture. On the other hand, due to the elimination of the power consumption related to the interpolation filter in the digital part, the total power consumption of the MDAS architecture increases by a maximum of 9.2% compared to the DAS architecture. Also, the silicon area required to implement the mixed‐signal part of the MDAS architecture when implementing the first stage of P‐SASB and STB‐P‐SASB beamforming methods is reduced by about 3 times and increased by a maximum of 25%, respectively, compared to that of the DAS architecture. [ABSTRACT FROM AUTHOR]

The time it takes for an ecosystem to recover from a disturbance is a key to environmental management. Conventionally, recovery is defined as a return to the pre‐disturbance state, assuming ecosystem stationarity. However, this view does not account for the impact of external forces like climate change, imposing non‐stationarity and trends. Alternatively, the counterfactual approach views recovery as the state the ecosystem would have achieved if the disturbance had not occurred, accounting for external forces. Here, we present a simple method to estimate the counterfactual recovery time. By implementing our method to the greening of the Arctic region, we showed that counterfactual greening recovery is twice as long as conventional recovery over the region. We argue that the well‐documented greening of the region acts as an external force, leading to such a large difference. We advocate for embracing the counterfactual definition of recovery, as it aligns with realistic decision‐making processes. Plain Language Summary: The time required for an ecosystem to recover from a disturbance is a crucial factor in many areas, such as decision‐making. Traditionally, this recovery time has been considered as the period for a disturbed ecosystem to either bounce back to its pre‐disturbance state or reach a new stable state. However, the assumption of stability may not hold true in light of climate change and other external factors. These forces make ecosystems dynamic, potentially with upward or downward trends, rather than reaching a stable state. To account for these external forces, an alternative definition is presented: the time for an ecosystem to reach its potential state, as if the disturbance had not occurred, termed the "counterfactual recovery." In this study, we propose a simple method based on time series analyses to calculate the counterfactual recovery time. We showcase the difference between the two definitions by implementing our approach to the case of greening in the Arctic and boreal regions post‐disturbance. Our method is generalizable to any ecological system, and we envision its contribution to decision‐making processes, such as conservation efforts. Key Points: The conventional definition to recovery as return to pre‐disturbance state ignores the impact of external forces on the recovery processWe proposed a method to estimate the time to recover using counterfactual approach which considers the impact of external forcesImplementing our approach over the greening of the arctic region showed the large difference between the two approaches [ABSTRACT FROM AUTHOR]

Objective: The integration of artificial intelligence (AI) in healthcare education is inevitable. Understanding the proficiency of generative AI in different languages to answer complex questions is crucial for educational purposes. The study objective was to compare the performance ChatGPT-4 and Gemini in answering Virology multiple-choice questions (MCQs) in English and Arabic, while assessing the quality of the generated content. Both AI models' responses to 40 Virology MCQs were assessed for correctness and quality based on the CLEAR tool designed for evaluation of AI-generated content. The MCQs were classified into lower and higher cognitive categories based on the revised Bloom's taxonomy. The study design considered the METRICS checklist for the design and reporting of generative AI-based studies in healthcare. Results: ChatGPT-4 and Gemini performed better in English compared to Arabic, with ChatGPT-4 consistently surpassing Gemini in correctness and CLEAR scores. ChatGPT-4 led Gemini with 80% vs. 62.5% correctness in English compared to 65% vs. 55% in Arabic. For both AI models, superior performance in lower cognitive domains was reported. Both ChatGPT-4 and Gemini exhibited potential in educational applications; nevertheless, their performance varied across languages highlighting the importance of continued development to ensure the effective AI integration in healthcare education globally. [ABSTRACT FROM AUTHOR]

The power line insulators are permanently exposed to various environmental pollutants such as dust and fine particles. This may lead to flashovers and therefore widespread power blackouts and heavy economic damage. One way to overcome this problem is to make the insulator surface superhydrophobic. In this research, the superhydrophobic properties of the insulators were improved by applying room-temperature cured composite coatings consisting of epoxy and hydrophobic nano-silica particles. Either octadecyl trichlorosilane (ODTS) or hexamethyldisilazane (HMDS) was used to coat the silica nanoparticles and make them hydrophobic. Then, the hydrophobic silica was added to a mixture of epoxy resin and hardener. The suspension was applied on the surfaces of a commercial porcelain insulator and cold-cured at ambient temperature. The coating increased the water contact angle from 50° to 149°. The samples preserved their hydrophobic properties even after 244 h exposure to the UV light. The coating adhesion was rated as 4B according to the ASTM D3359 standard. The coating decreased the leakage current by 40% and increased the breakdown voltage by 86% compared to the uncoated sample, and it showed promise for making power line insulators self-clean. [ABSTRACT FROM AUTHOR]

This paper presents a particular tunneling method, the new Austrian tunneling method (NATM), which plays an important role in reducing subsidence of the surface and damage to structures in urban areas. It has a wide range of applications in shallow tunneling projects all over the world. In this study, numerical modeling of the third-line Metro tunnel in Tehran, which is designed and stabilized by the NATM, is under discussion. The foregoing tunnel is excavated manually with a one-meter advancing step. In this project, the constructors use a lattice girder and spray concrete with 31 cm thickness as the initial lining. A suitable numerical software for this modeling is PLAXIS 3D Tunnel, which allows high-resolution finite element modeling (FEM) of the studied object. The performance of this method is investigated and compared with that of other NATMs. The numerical modeling yielded a value of 30.01 mm for earth subsidence in the most damaged area of the settlement, which was confirmed with a dramatically low difference by earth surface monitoring. Moreover, this tunnel was drilled and excavated using various methods, among which the least settlement was obtained by the proposed method. The results are promising, and they indicate that tunneling with this method should continue to be used to expand the subway line in the city. [ABSTRACT FROM AUTHOR]

Buried pipelines subjected to permanent ground deformations (through, e.g., earthquake-induced liquefaction or fault rupture) often experience widespread damage. Regardless of the direction of ground movement, pipelines tend to respond and experience damage axially due to their directional stiffness characteristics. In addition, case studies and previous testing have shown that damage is concentrated at the pipe joints due to their lower strength compared with a pipe barrel. Previous testing has also shown that axial forces increase significantly when pipe connections have jointing mechanisms, such as coupling restraints, with larger diameters than the pipe barrel alone. These enlarged joints act as anchors along the pipe, increasing the soil resistance at these locations. Current methods for predicting the axial force along a pipe underpredict the force demands and oversimplify the mechanics of soil resistance on the joint face. This study conducts a series of 12 pipe-pull tests in a centrifuge, varying joint diameter and burial depth, to quantify the axial forces developed. A strong linear correlation was observed between the soil resistance on a joint face and the joint surface area and burial depth. The study also proposes an analytical solution based on pullout capacity design equations for vertical anchor plates as a function of soil and pipe joint properties. The proposed solution to calculate joint resistance is in good agreement with the centrifuge tests performed for this study and previous full- and model-scale experiments. The proposed prediction equation is anticipated to have future applications to other buried structures because it is based on mechanisms of passive resistance commonly encountered in underground structures and lifelines. [ABSTRACT FROM AUTHOR]

To improve the efficiency of hydrophilic polymers in oil reservoirs, a method encapsulates the polymer within a protective shell, safeguarding the core polymer and enabling controlled release in demanding, high-temperature conditions. Poly(N-isopropylacrylamide) nanoparticles are encapsulated with polystyrene shells through emulsion polymerization in this study. Varying the amounts of shell monmer and crosslinking agents resulted thick, sphere-shaped shells with homogeneous morphology, which protects the core polymer and enabling controlled release. Structural and morphological properties are characterized using Fourier transform infrared spectroscopy (FTIR), proton nuclear magnetic resonance (H1NMR), dynamic light scattering (DLS), and scanning electron microscope (SEM) imaging. Increasing the styrene amounts lead to larger particles, while higher crosslinker amounts result in a narrower size distribution. Thermal testing indicates heat resistance up to 300 °C, suitable for enhanced oil recovery (EOR) applications. Rheological tests determine an optimal 30-day release for the PNIPAM core, with the CS polymer showing increased viscosity under harsh conditions. The colloidal stability model estblished by Derjaguin, Landau, Verwey, and Overbeek (DLVO theory) and experimental results demonstrate good stability and energy barriers at room temperature, but decreased stability and increased agglomeration at higher temperatures. Thickening the styrene shell leads to particle agglomeration and unsuitable stability. The study confirms the effectiveness of the model in analyzing CS colloidal latex systems. [ABSTRACT FROM AUTHOR]

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs. Plain Language Summary: The arctic‐boreal zone is warming rapidly, impacting regional and global carbon cycles. The Community Land Model (CLM) can be used to project future carbon uptake and storage in this region. However, CLM is biased in estimating leave area index (LAI) and aboveground biomass that can significantly affect model projections of carbon uptake and storage. We forced the model estimates of LAI and the aboveground biomass to be consistent with satellite‐derived LAI observations and a high‐quality machine learning product of aboveground biomass in Alaska and Western Canada using data assimilation. The change of aboveground biomass resulted in model estimates of vegetation height consistent with independent estimates at regional and site levels. The assessment using the International Land Model Benchmarking System showed that CLM's performance in simulating carbon and hydrologic cycles was improved. Fixing the model bias in LAI only removed partial bias in carbon uptake, and a new parameterization allowing two key parameters in photosynthesis to vary with leaf temperature was introduced into CLM, to further remove the remaining bias in carbon uptake. Combining data assimilation with this new parameterization yielded more accurate model estimates of carbon uptake. Key Points: Assimilating leaf area index and aboveground biomass observations into CLM reduced model bias in estimating themData assimilation significantly improved CLM's performance in carbon and hydrologic cycles, as well as the functional relationshipsImplementation of a new parameterization of photosynthesis in CLM further reduced model bias in estimating the gross primary productivity [ABSTRACT FROM AUTHOR]

Jacket structures play an ever-increasing role in meeting the world's burgeoning energy demand by providing support structure for exploiting offshore wind energy and oil and gas resources. Many of these structures are past their design lifetimes, and thus may have suffered significant degradation, highlighting the importance of investigating their earthquake response in seismically active regions. This study investigates the seismic performance of a typical offshore jacket platform, denoted as baseline structure, as well as four versions with two longer (25% and 50% larger) and two shorter (25% and 50% smaller) natural vibration periods accounting for two levels of degradation and retrofit effects on structural performance. For each case, eleven ensembles of ground motions compatible with the site's seismic hazard are selected using the generalized conditional intensity measure methodology. The loading uncertainty is incorporated in the performance assessment procedure via probabilistic seismic demand analysis and the demand hazard is quantified. The results provide valuable information regarding reliability of these structures both at design stage and during service life, which can aid decision-making around rehabilitation of older platforms, the suitability of reusing obsolete platforms beyond service lifetime, and risk-based design of new platforms. [ABSTRACT FROM AUTHOR]

Waning immunity and emergence of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlight the need for further research in vaccine development. A recombinant fusion protein containing the receptor-binding domain (RBD) fused to the human IgG1 Fc (RBD-Fc) was produced in CHO-K1 cells. RBD-Fc was emulsified with four adjuvants to evaluate its immunogenicity. The RBD-specific humoral and cellular immune responses were assessed by ELISA. The virus neutralizing potency of the vaccine was investigated using four neutralization methods. Safety was studied in mice and rabbits, and Antibody-Dependent Enhancement (ADE) effects were investigated by flow cytometry. RBD-Fc emulsified in Alum induced a high titer of anti-RBD antibodies with remarkable efficacy in neutralizing both pseudotyped and live SARS-CoV-2 Delta variant. The neutralization potency dropped significantly in response to the Omicron variant. RBD-Fc induced both TH2 and particularly TH1 immune responses. Histopathologic examinations demonstrated no substantial pathologic changes in different organs. No changes in serum biochemical and hematologic parameters were observed. ADE effect was not observed following immunization with RBD-Fc. RBD-Fc elicits highly robust neutralizing antibodies and cellular immune responses, with no adverse effects. Therefore, it could be considered a promising and safe subunit vaccine against SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Herein, superhydrophilic polyester textiles were fabricated via plasma modification with a view to their application in the separation of oil–water mixtures. The research delved into the impact of fabric treatment and variations in grammage, including 77, 104, and 132 g/m2 on separation performance and flux. The surface characteristics of the prepared polyester textiles were assessed through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) analyses. Additionally, the antifouling properties and reusability of both fabrics without treatment and treated fabrics were examined. Notably, employing a five-layer treated fabric substantially improved separation efficiency up to 99.78%, and even after 5 cycles, it remained at 91.80%, attributable to the enhanced hydrophilicity conferred by APP treatment. In addition, after 20 abrasion cycles, the oil contact angle (OCA) of the five-layer treated polyester fabric decreased by 36 °. [ABSTRACT FROM AUTHOR]

The study of an Arabic newspaper published by the British during World War II shows how photographs played an important role in the propaganda campaign to gain Arab support in the Middle East. While the newspaper purported to cover the war, in actuality, the content contained mostly cultural photographs that contributed to the Allies' implementation of psychological warfare, particularly emphasizing Arab identity, lifestyle in England, development in the Arab World, and the solid Arab–Allies relationship. The results of this study demonstrate how photographs played an important role in the propaganda machine, which, in this case, was intended to positively impress Arabs and Muslims in the Arabian Peninsula and turn them against the Axis. [ABSTRACT FROM AUTHOR]

The uncertainty of the COVID-19 virus outbreak triggered chaos, panic and fear worldwide. During the outbreak, many humorous posts tweeted and retweeted addressed the virus with a laugh. Humour is a way to escape reality, but at the same time it may have negative outcomes. In Kuwait, many such posts spread on social media, especially Twitter. They reduced panic, educated the public or made people ignore the seriousness of the pandemic. This study investigates the negative implications of using humorous text, images and video messages on Twitter. A qualitative discourse analysis of 907 humorous texts, images and videos posted on Twitter during the crisis revealed that humorous posts may foster negative attitudes concerning sectarianism, tribalism, racism, sexism and hatred. Interestingly, humorous posts in less emotionally charged categories, such as sports, family and children, also include many negative connotations and denotations. This study is unique in addressing an understudied area; humour on social media in the Arab and Gulf region. Its findings show that humorous posts can produce negative outcomes and cause fear and hatred in society. There may be a need for self-censorship and moral behaviour to prevent social tension. The notion that jokes are only jokes and people should not be offended may have unforeseen negative repercussions. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is one of the deadliest cancers worldwide with low survival rates and poor outcomes. The treatment landscape for PC is fraught with obstacles, including drug resistance, lack of effective targeted therapies and the immunosuppressive tumor microenvironment (TME). The resistance of PC to existing immunotherapies highlights the need for innovative approaches, with the TME emerging as a promising therapeutic target. The recent advancements in understanding the role of macrophages, this context highlight their significant impact on tumor development and progression. There are two important types of macrophages: M1 and M2, which play critical roles in the TME. Therapeutics strategies including, depletion of tumor-associated macrophages (TAMs), reprogramming TAMs to promote anti-tumor activity, and targeting macrophage recruitment can lead to promising outcomes. Targeting macrophage-related pathways may offer novel strategies for modulating immune responses, inhibiting angiogenesis, and overcoming resistance to chemotherapy in PC treatment. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is one of the deadliest cancers worldwide with low survival rates and poor outcomes. The treatment landscape for PC is fraught with obstacles, including drug resistance, lack of effective targeted therapies and the immunosuppressive tumor microenvironment (TME). The resistance of PC to existing immunotherapies highlights the need for innovative approaches, with the TME emerging as a promising therapeutic target. The recent advancements in understanding the role of macrophages, this context highlight their significant impact on tumor development and progression. There are two important types of macrophages: M1 and M2, which play critical roles in the TME. Therapeutics strategies including, depletion of tumor-associated macrophages (TAMs), reprogramming TAMs to promote anti-tumor activity, and targeting macrophage recruitment can lead to promising outcomes. Targeting macrophage-related pathways may offer novel strategies for modulating immune responses, inhibiting angiogenesis, and overcoming resistance to chemotherapy in PC treatment. [ABSTRACT FROM AUTHOR]

Background: The development of heart failure is a turning point in the natural course of aortic stenosis (AS). Pulmonary oedema and elevated left ventricular pressure (LVP) are cardinal features of heart failure. Evaluating pulmonary oedema by lung ultrasound involves taking the upper hand with a bedside noninvasive tool that may reflect LVP. Aim: We sought to assess the correlation between sonographic pulmonary congestion, invasive LV pre-A pressure, and echocardiographic LV end-diastolic pressure (LVEDP) in symptomatic AS patients receiving transcatheter aortic valve replacement. Methods: Forty-eight consecutive patients with severe AS and planned transcatheter aortic valve implantation (TAVI) were enrolled. LVEDP was estimated to be normal or elevated using the ASE/EACVI algorithm and transmitral Doppler indices, the E/A ratio, the E/e′, and the left atrial volume index. Invasive LV pre-A pressure was used as a reference, with > 12 mm Hg defined as elevated. Results: Forty-eight patients (25 women (52%), mean age 75 years, standard deviation (SD) ± 7.7 years) were enrolled in the study. We detected severe B-lines (≥ 30) in 13 (27%) patients and moderate B-lines (15–30) in 33 (68.6%) patients. The number of B-lines increased significantly with the severity of New York Heart Association (NYHA) functional classes (Fig. 1). The B-line count was 14 ± 13 in NYHA class I patients, 20 ± 20 in class II patients, and 44 ± 35 in class III patients (p < 0.05, rho = 0.384). The number of B-lines was correlated with the E/E' ratio (R = 0.664, p < 0.0001) and the proBNP level (R = 0. 882, p < 0.008). We found no significant correlation with the LVEDP or LVEF. The LVEDP correlated well with the E/E' ratio (R = 0.491, p < 0.001) but not at all with E/A, DT, or LAVI. All patients had an elevated LVEDP > 12, with a mean pressure of 26 mmHg, a minimum of 13 mmHg, and a maximum of 45 mmHg, with an SD of 7.85. Conclusion: Assessing lung ultrasonic B-lines is a straightforward and practical approach to identifying pulmonary oedema in AS patients. The number of B-lines correlated with the E/E' ratio and the functional status of patients but did not correlate with invasive LVEDP or LVEF. All patients had elevated LVEDP that correlated with E/E'. [ABSTRACT FROM AUTHOR]

Background and Objectives: Zygomycosis, a severe form of fungal infection, is classified into two categories: Mucorales and Entomophthorales. Within the Entomophthorales category, Basidiobolomycosis is a rarely recognized genus that can have significant health implications. Prompt diagnosis and appropriate treatment, which includes the use of antifungal medication and surgical procedures, are vital for enhancing the prognosis of patients. The objective of this study is to investigate the response to treatment in patients hospitalized due to basidiobolomycosis. Methods: We carried out a retrospective study, in which we analyzed data from 49 patients who were diagnosed with Entomophthorale, Zygomycosis, and Basidiobolomycosis at Namazi Hospital, Shiraz, between the years 1997 and 2019. The data included parameters such as demographic information, clinical symptoms, imaging findings, treatment methods, and patient outcomes. Results: Out of 49 patients, 24 children, predominantly male (83.3%), were definitively diagnosed with basidiobolomycosis. The ages of the patients ranged from 1 to 16 years, with an average of 5.75 years. The most frequently observed clinical manifestations included abdominal pain (70.8%), fever (54.2%), hematochezia (41.7%), vomiting (20.8%), and anorexia (16.7%). Half of the patients exhibited failure to thrive (FTT), while abdominal distension was present in 25% of the cases, and a palpable abdominal mass was found in 37% of the patients. The primary treatment strategy incorporated surgical interventions complemented by a comprehensive antifungal regimen. This regimen included medications such as amphotericin B, cotrimoxazole, itraconazole, potassium iodide, and voriconazole. These were mainly administered in a combination therapy pattern or as a monotherapy of amphotericin B. Twenty-two patients were discharged, while two patients died due to complications from the disease. Conclusion: Our findings indicate that the prevailing treatment modalities generally involve surgical intervention supplemented by antifungal regimens, including Amphotericin B, Cotrimoxazole, Potassium Iodide, and Itraconazole. [ABSTRACT FROM AUTHOR]

The Islamic Maghreb, encompassing modern-day North African countries, was a vast land. It had a rich history of medical practice. Since the beginning of the arrival of Islam in the Maghreb lands, the medical profession was common and the healers who came to this land with the Islamic armies called “fuqaha al-badan” (lit. “body jurists”), practiced the profession of medicine. The Bani Aghelab Muslim rulers pioneered hospital establishments in the Islamic Maghreb, founding the Damneh Qairwan. After them, the Touloni and Akhshidi rulers and others continued the tradition of building hospitals by building Damneh in Tripoli, Fes, Sousse, and Safaqas in today’s eastern Tunisia. Ibn Tulun also founded Atiq Hospital and Al-Asfal Hospital in Fostat, Egypt. The Muslim rulers stationed great doctors, such as Yohanna bin Maswayh, Ishaq bin Imran Israeli, Ain bin Ain, Ahmad bin Jazzar, Muhammad Jabali, Saeed bin Noufal, and Muhammad bin Abdulrahman Masri in these hospitals. This article employs a descriptive-analytical approach to examine the role and contributions of Muslims in advancing medical knowledge, institutions, and hospitals within the Islamic Maghreb. The primary research question explores the extent of Muslim influence in this development. The findings of the study show that medicine in the Islamic Maghreb was predominantly experimental from the Muslims’ arrival until the third century of Hijri. However, between the third and fourth centuries of Hijri, in the light of the efforts of doctors, medical knowledge evolved into a science-based practice. This contributed to significant improvements in medical care, facilities, and services, as hospitals expanded and became increasingly effective. [ABSTRACT FROM AUTHOR]

Increasing level of employee satisfaction is one of the constant concerns of managers in all organizations. Based on this, during the last few decades, various models have been prepared and designed to identify the main factors affecting the job satisfaction of employees. The diversity of these models can cause confusion for managers of organizations to choose appropriate strategies. The current researchers are trying to investigate the components of employee satisfaction patterns to provide a relatively comprehensive model in Iranian organizations. The current research method is qualitatively comparative using the content analysis approach, the research population includes all models of job satisfaction and the purposeful sampling method was used to select the models. The findings reveal that the ten components of work-life balance, demographic factors, respect, relationship with colleagues, job stability, payment system, success & progress, diversity in work methods, effective leadership and health insurance are common in most of the selected models. Another finding indicates that the payment system and diversity in ways of doing work are the most important components from the point of view of designers. According to the findings, a proposed model for Iranian organizations with six components of payment system, respect, relationship with colleagues, job stability, success and progress, and diversity in ways of doing work was prepared and designed. [ABSTRACT FROM AUTHOR]

Objective: Accurate nationwide epidemiological evidence is vital to study the seasonal, geographic, and ethnic influence on the trends of orofacial cleft prevalence in Kuwait. Design: Data obtained from the National Center for Health Information and Ministry of Health Hospital digital records were reviewed retrospectively to identify patients with orofacial clefts (OFC) using the ICD-10 diagnostic codes. The Jonckheere-Terpstra test was used to assess the trend of birth prevalence across the different years. The associations of types of OFC with ethnic and geographic influences were tested with chi-square or Fisher's exact tests, while the strength of that association was tested with multi-nominal logistic regression. Results: Birth prevalence in Kuwait ranged from 0.75–2.55 per 1000 live births (0.73- 2.73 among Kuwaitis, 0.60–3.27 among non-Kuwaitis), with no statistically significant change observed during the past 28 years. The risk of unilateral cleft lip and palate was eight times higher during summer compared to Autumn, while the risk of cleft lip and palate remained lower during winter. Jahra (OR-7.76, CI- 1.51–39.80), Farwaneya (OR-6.65, CI- 1.34–33.06), and Hawalli (OR-6.72, CI- 1.26–35.98) governorates had higher odds of bilateral cleft lip when compared to Mubarak Alkabeer. Conclusions: The study outcome is an indicator to improve patient care and customize healthcare infrastructure in the Ministry of Health. It also provides insight to develop projections of future needs. Future studies should focus on understanding the factors that might be a potential contributor to the seasonal change observed in the prevalence of OFC. [ABSTRACT FROM AUTHOR]

This article examines the research carried out regarding the failure rate in electricity distribution systems. It introduces a comprehensive framework for managing failure rates in power distribution systems. This framework highlights that studies on failure rates in power distribution systems can be categorized into three distinct groups: modifying asset management activities in order to reduce failure rate, evaluate and control threats and risks, emergency measures after failure. In this article, all the studies conducted on the failure rate of electricity distribution systems are listed and presented, and categorized in the form of a comprehensive and conceptual framework. The relation of each category with the failure rate is explained and by studying the process of studies, the research gaps and the roadmap of future studies in the field of failure rate in electricity distribution systems are determined. [ABSTRACT FROM AUTHOR]

Creating stable oscillations in the nonlinear dynamic of thermoacoustic stirling engines is an essential challenge for researchers. Hence, investigating this challenge is the main objective of this paper. In this regard, a novel systematic and parametric method using the practical stability theory is presented to investigate the stable oscillations (sufficient condition) of thermoacoustic stirling engines for the first time. In this regard, the goals of the problem, which included stable oscillations of the pistons are determined. In the following, based on the desired objectives of the nonlinear dynamic equations, the engine error is extracted. Based on the practical stability theory, a Lyapunov function is selected according to the dynamics of the problem. Then, a time derivative of the Lyapunov candidate function and its sign is determined later. According to the conditions presented for the practical stable theory (the positive definiteness of the Lyapunov function and the negative definiteness of its derivative), nine parametric conditions for the error dynamics of the thermoacoustic stirling engine are presented. Once these nine conditions are met, sufficient conditions (stable motion) will occur in engine dynamics. The noteworthy point is that the presented method is completely parametric, and this will make it possible to easily evaluate the effect of each parameter of the engine to reach sufficient conditions. Another interesting feature of the presented idea is to determine the accuracy of the design process, which can be determined using the value of the ultimate bound. In other words, the lower the value of the ultimate bound, the better the accuracy of the design. As a result, the design is close enough to the problem's objectives. Hence, in this work, the effect of the important parameters of the engine on the value of the ultimate bound is also evaluated. It is worth mentioning that in order to verify the effectiveness of the presented method, the data extracted from the constructed engine is used to check the sufficient condition and the effect of the parameters on the ultimate bound. The obtained results showed that the presented parametric method can examine the mentioned cases appropriately. In the end, it can be said that the main innovation and finding of this work is to investigate the sufficient condition of the thermoacoustic stirling engines using a parametric method (presenting nine parametric conditions). Through the utilization of this method, researchers can not only assess the sufficient condition but also investigate the impact of engine parameters on its performance before construction. This approach helps in reducing costs and time associated with the study. [ABSTRACT FROM AUTHOR]

Background: Patients receiving home parenteral nutrition (HPN) are known to experience psychological distress and have profoundly disrupted sleep. The aim of this analysis was to examine the relationship between sleep patterns with depressive symptoms and HPN characteristics. Methods: The study was a secondary analysis of cross‐sectional data examining sleep patterns using subjective and objective measures. Sleep was assessed by surveys and 7‐day actigraphy. The Patient Health Questionnaire‐8 was used to evaluate depressive symptoms. Participants provided information on HPN. Spearman correlations were calculated between sleep measures with depressive symptoms and HPN characteristics. Correlations were further examined in multivariable linear regression models. Results: Thirty‐two adults (age = 53 years; 75% female; 94% White) were included. Lower sleep quality (r = 0.54–0.60; P < 0.001) and later sleep timing (r = −0.35; P = 0.049) were correlated with higher depressive symptoms. Sleep patterns were also correlated with several HPN characteristics (r = −0.47 to 0.51). In linear regression models, rate of infusion was associated with sleep duration (β = −0.004 [0.002] h; P = 0.046) in which each 100 mL/h was associated with 24‐min shorter duration. Higher total energy was associated with lower sleep quality (β = 0.0004 [0.0002] log‐unit; P = 0.042), and higher volume was associated with longer sleep onset latency (β = 0.0006 [0.0003] log‐min; P = 0.049). Conclusions: We provide evidence supporting the link between poor and later sleep with higher depressive symptoms and identify potentially modifiable infusion characteristics (notably, slower rate of infusion and lower total energy and volume) that, on further verification, may support sleep among those receiving HPN. [ABSTRACT FROM AUTHOR]

Background. Nurse protection is a multifaceted concept that has become increasingly relevant in recent years. Despite its importance in effectively managing pandemics, there is still a gap in knowledge about how nurses achieve protection in hospitals. Objective. To describe the process of seeking protection among nurses during the COVID‐19 pandemic. Methods. A grounded theory approach from 2020 to 2022, employing purposive and theoretical sampling. Face‐to‐face and online interviews were conducted with 25 participants, resulting in 29 interviews. Data analysis was carried out using Corbin and Strauss's method (2015). Results. The analysis revealed that nurses encountered numerous obstacles related to patients, nurses themselves, organizations, and the passage of time during the COVID‐19 pandemic. These challenges were intertwined with three key concepts: transformations, inequalities, and emotional challenges, highlighting the multifaceted nature of nurses' protection concerns. In response, nurses employed a protective strategy bolstered by catalysts to address these challenges. This strategy encompassed both optimistic outlooks ("Bright horizon") and somber reflections ("Unpleasant reflection"). Ultimately, seeking protection in the heart of the storm emerged as the core concept, representing the multifaceted process through which nurses navigate and seek protection amidst the unique challenges posed by the pandemic. Conclusions. This study presents a comprehensive theory that explicitly explains the multifaceted process of seeking protection among hospital‐employed nurses during a pandemic. The theory captures the interconnectedness of challenges faced by nurses and the protective strategies they employ while acknowledging the nuanced balance between hopeful prospects and sobering reflections. Implications for Nursing Management. Policymakers, managers, and educators can utilize the findings to improve nursing management and support systems. By increasing awareness, addressing challenges, and providing robust support, they can enhance the well‐being and effectiveness of nurses during healthcare crises, ultimately improving patient care quality. [ABSTRACT FROM AUTHOR]

Chronic interstitial lung diseases (ILDs) require frequent point-of-care monitoring. X-ray-based methods lack resolution and are ionizing. Chest computerized tomographic (CT) scans are expensive and provide more radiation. Conventional ultrasound can detect severe lung damage via vertical artifacts (B-lines). However, this information is not quantitative, and the appearance of B-lines is operator- and system-dependent. Here we demonstrate novel ultrasound-based biomarkers to assess severity of ILDs. Lung alveoli scatter ultrasound waves, leading to a complex acoustic signature, which is affected by changes in alveolar density due to ILDs. We exploit ultrasound scattering in the lung and combine quantitative ultrasound (QUS) parameters, to develop ultrasound-based biomarkers that significantly correlate (p = 1e−4 for edema and p = 3e−7 for fibrosis) to the severity of pulmonary fibrosis and edema in rodent lungs. These innovative QUS biomarkers will be very significant for monitoring severity of chronic ILDs and response to treatment, especially in this new era of miniaturized and highly portable ultrasound devices. [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in reproductive age and the most common cause of infertility due to anovulation. PCOS in adolescents is concerning. Nigella sativa is effective in improving gonadotropins and sex hormones. The current study was designed to investigate the effect of Nigella sativa supplementation on PCOS symptoms and their severity in adolescents. Methods: The current randomized clinical trial was conducted on 114 adolescents with PCOS who were referred to gynecologist offices and clinics in Gonabad, Iran from March 2022 to March 2023. Participants were randomly allocated to the intervention (Nigella sativa 1000 mg/day) and control (10 mg/day medroxyprogesterone from the 14th day of the cycle for 10 nights) groups. The study duration was 16 weeks. Ovarian volume (measured by ultrasound), anthropometric and blood pressure; serum testosterone, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEA-S), luteinizing hormone (LH), hirsutism severity (Ferriman–Gallwey score) levels were evaluated before and after the study. Results: Data from 103 participants (control group = 53, intervention group = 50) were analyzed. The mean age of participants was 17.0 (Interquartile range [IQR]:2.0). The mean difference in hirsutism score changes (p < 0.001), right (p = 0.002), and left (p = 0.010) ovarian volume, serum LH (p < 0.001) and testosterone (p = 0.001) were significantly higher in the intervention group compared to the control group. The frequency of oligomenorrhea, menometrorrhagia, and amenorrhea, were significantly reduced after the study in the intervention group compared to the control group (ps < 0.001). Conclusions: Short-term Nigella sativa supplementation may be effective in reducing ovarian volume and improving hormonal balance, and menstrual irregularities in adolescents with PCOS. Further research and long-term studies are warranted to validate the potential therapeutic effects of Nigella sativa in adolescents with PCOS. IRCT registration number: IRCT20221017056209N1 Registration date: 2022-11-22. [ABSTRACT FROM AUTHOR]

Background: Burnout is an increasing public health concern. Its prevalence has extended across diverse professions globally, posing significant challenges to individuals, organizations, and society. This phenomenon has undermined employee well-being, productivity, and organizational effectiveness, making it a critical concern in contemporary work environments. The present study aimed to examine the adaptation and assess the validity of the Persian version of the Burnout Assessment Tool (BAT). Methods: The adaptation process included the translation and back-translation of the BAT. Data were collected on a sample of 580 teachers using the convenience sampling. The BAT-Persian and Utrecht Work Engagement Scale were administered to collect the data. The reliability, factorial structure of the BAT-C and BAT-S, and the convergent and discriminant validity of BAT-C and work engagement were explored. Results: Confirmatory factor analysis supported a four-factor structure for the core dimensions (BAT-C; exhaustion, mental distance, emotional impairment, cognitive impairment), and a two-factor structure for the secondary dimensions (BAT-S; psychological distress, psychosomatic complaints). In the second-order model, the item loadings on the four factors of BAT-C ranged from 0.35 to 0.85, and on two factors of BAT-S ranged from 0.63 to 0.89. The Persian versions of the BAT-C and BAT-S showed good internal consistency (respectively, α = 0.95 and 0.90). Additional evidence supports the convergent and discriminant validity of the BAT-GR. the BAT‐C and its scales were negatively correlated with work engagement and dimensions (i.e., vigor, dedication, and absorption). Moreover, the BAT‐S and its scales negatively correlated with work engagement and dimensions. Conclusions: This study provided evidence that the Iranian version of BAT represents a reliable and valid tool for measuring burnout in the work context. A reliable and valid tool for assessing burnout in the Iranian workplace enables early detection of employee distress, allowing for timely intervention and support. This means that identifying the signs and symptoms of burnout in the early stages can prevent more severe consequences such as absenteeism, reduced productivity, or turnover. [ABSTRACT FROM AUTHOR]

Plants and microbes are closely associated with each other in their ecological niches. Much has been studied about plant–microbe interactions, but little is known about the effect of phytochemicals on microbes at the molecular level. To access the products of cryptic biosynthetic gene clusters in bacteria, we incorporated an organic extract of hibiscus flowers into the culture media of different Actinobacteria isolated from plant rhizospheres. This approach led to the production of broad-spectrum dithiolopyrrolone (DTP) antibiotics, thiolutin (1) and aureothricin (2), by Streptomyces sp. MBN2-2. The compounds from the hibiscus extract responsible for triggering the production of these two DTPs were found to be hibiscus acid dimethyl ester (3) and hydroxycitric acid 1,3-dimethyl ester (4). It was subsequently found that the addition of either Fe2+ or Fe3+ to culture media induced the production of 1 and 2. The Chrome Azurol S (CAS) assay revealed that 3 and 4 can chelate iron, and therefore, the mechanism leading to the production of thiolutin and aureothricin appears to be related to changes in iron concentration levels. This work supports the idea that phytochemicals can be used to activate the production of cryptic microbial biosynthetic gene clusters and further understand plant–microbe interactions. [ABSTRACT FROM AUTHOR]

Rice is a crucial agricultural product, and enhancing its productivity is essential for increasing production. This study aims to analyze the total factor productivity growth of rice production in Iran from 2000 to 2020. Using parametric (stochastic frontier analysis) approaches, the research evaluated the rice productivity growth and its components, including scale and technological changes. Based on the estimated Translog Cost Function, the annual total factor productivity growth was 2.1%, with positive technological change as the primary driver of these improvements. To further enhance productivity, the study recommends utilizing improved seeds, modern machinery, fertilizers, and nutritional solutions during rice cultivation. Additionally, the research suggests the application of parametric approaches in future studies to assess the impact of technological changes on crop yields. [ABSTRACT FROM AUTHOR]

Introduction: Pregnant women and their fetuses are considered as high-risk groups during the COVID-19 pandemic. The aim of this study was to identify the risk factors of adverse pregnancy outcomes among women with COVID-19. Methods: This case-control study was conducted among pregnant women who delivered live infants at least 60 days before data collection in Hormozgan Province, south of Iran, 2021. The case and control groups included women with and without the history of COVID-19, respectively. A 47-item checklist including demographic information of the mothers, maternal current and past medical history, maternal and fetal prenatal and post-natal outcomes; and other COVID-19 related outcomes was used. The logistic regression analysis was used for data analysis. Results: A total of 1337 women (668 in case and 669 in control groups) participated in this study. The mean (SD) gestational age in the case and control groups were 32.83 (84.64) and 23.75 (6.93) weeks respectively. Maternal age and the incidence of abortion, obesity, and multiple pregnancies was higher in the COVID-19 group compared with the control group. The most common COVID-19 symptoms were myalgia (24.8%), cough (19.3%), fever (17.5%) and olfactory disorder (14.3%). The preventive factors against COVID-19 adverse pregnancy outcomes were low and normal body mass index, influenza vaccination history, and multivitamin consumption, while the risk factors were multiple pregnancies, abortion and preterm labor. Conclusion: This study showed that pregnant women were to COVID-19. The identified risk factors for COVID-19 adverse pregnancy outcomes can be used to prioritized pregnant women in receiving COVID-19 related health services. [ABSTRACT FROM AUTHOR]

Targeted maximum likelihood estimation (TMLE) is increasingly used for doubly robust causal inference, but how missing data should be handled when using TMLE with data-adaptive approaches is unclear. Based on data (1992-1998) from the Victorian Adolescent Health Cohort Study, we conducted a simulation study to evaluate 8 missing-data methods in this context: complete-case analysis, extended TMLE incorporating an outcome-missingness model, the missing covariate missing indicator method, and 5 multiple imputation (MI) approaches using parametric or machine-learning models. We considered 6 scenarios that varied in terms of exposure/outcome generation models (presence of confounder-confounder interactions) and missingness mechanisms (whether outcome influenced missingness in other variables and presence of interaction/nonlinear terms in missingness models). Complete-case analysis and extended TMLE had small biases when outcome did not influence missingness in other variables. Parametric MI without interactions had large bias when exposure/outcome generation models included interactions. Parametric MI including interactions performed best in bias and variance reduction across all settings, except when missingness models included a nonlinear term. When choosing a method for handling missing data in the context of TMLE, researchers must consider the missingness mechanism and, for MI, compatibility with the analysis method. In many settings, a parametric MI approach that incorporates interactions and nonlinearities is expected to perform well. [ABSTRACT FROM AUTHOR]

Blastocystis is an intestinal protist frequently identified in humans and other animals, though its clinical significance remains controversial. This study aimed to determine the prevalence and genetic diversity of Blastocystis in faecal samples from symptomatic (n = 55) and asymptomatic (n = 50) individuals seeking medical care in Meknes, Morocco. Detection of the protist was accomplished through coproparasitological examination and culture in Jones medium. Culture-positive samples were subjected to molecular analyses (PCR and Sanger sequencing) based on sequences of the small subunit ribosomal RNA gene. Epidemiological questionnaires on demographics and potential risk factors were collected from participating patients. The overall Blastocystis infection rate was 51.4% (54/105), with no differences between symptomatic (52.7%, 29/55) and asymptomatic (50.0%, 25/50) individuals. Sequence analyses identified three Blastocystis subtypes, with ST3 being the most prevalent (42.0%), followed by ST1 (34.0%), and ST2 (12.0%). Regarding intra-subtype diversity, allele 4 was found within ST1; alleles 11/12 and alleles 34/36 (alone or in combination) were identified within ST2 and ST3 respectively. Allele 34 in ST3 (40.8%) and allele 4 in ST1 (34.7%) were the most common genetic variants circulating in the surveyed clinical population. A statistically significant association between ST2 and the presence of flatulence was observed. This is the first study assessing the epidemiology and genetic diversity of Blastocystis sp. in the Meknes region, Morocco. [ABSTRACT FROM AUTHOR]

Summary: Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear.We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for > 700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits.While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R2 (0.12–0.49, 0.15–0.42, and 0.25–0.56) and increased NRMSE (3.58–18.24%, 6.27–11.55%, and 7.0–33.12%) compared with nonspatial random cross‐validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability.These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications. [ABSTRACT FROM AUTHOR]

Polyolefins, composed of carbon and hydrogen atoms, dominate global polymer production. This stems from the wide range of physical and mechanical properties that various polyolefins can cover. Their versatile properties are largely tuned by chain microstructure, including molar mass distribution, comonomer content, and long‐chain branching (LCB). Specifically, LCB imparts unique characteristics, notably enhances processability crucial for downstream applications. Tailoring LCB structural features has encouraged academic and industrial efforts, chronicle in this review from a chemistry standpoint. While encompassing post‐reaction modification based traditional methods like peroxide grafting, ionizing beam irradiation, and coupling reactions, the main focus is given to catalyst‐centric strategies and innovative polymerization schemes. The advent of single‐site catalysts—metallocenes and late transition metals catalysts—amplifies interest in tailored chemical methods, but the progress in LCB formation flourishes via tandem catalytic systems and bimetallic catalysts under controlled reaction conditions. Specifically, the breakthrough in coordinative chain transfer polymerization unveils a novel avenue for controlled LCB synthesis by sequential chain propagation, transfer, liberation, and enchainment. This short review highlights recent approaches for the production of LCB polyolefins that can provide a roadmap crucial for researchers in academia and industry, steering their efforts toward further advancements in the production of tailored polyolefin. [ABSTRACT FROM AUTHOR]