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Abstract Background Recently, the concept of expanded terminal sedation emerged to describe using sedation at the end of life in cases beyond the usual use. Using this sedation could be a stressful ethical encounter for healthcare providers. Case In this paper, we describe a case of a Muslim palliative care nurse who cared for a patient with cancer who requested expanded terminal sedation. The palliative care nurse described that his initial response to the expanded terminal sedation order was refusing to start the sedation because he believed the patient was not terminally ill and was concerned about killing him, which is prohibited according to his religious beliefs. Further, the nurse perceived the patient’s psychological distress and his verbalization of wishing to die peacefully as a concealed request for euthanasia, especially since he was not imminently dying. Finally, the nurse reported being frustrated and uncertain about the care, especially since he did not receive appropriate psychological counseling from professional personnel. Conclusions any case beyond the usual conditions for terminal sedation should be carefully examined, especially when nurses’ religious beliefs or moral values contradict it. If sedation should be administered, adequate preparation of healthcare providers should be arranged, including discussing with them the goals of care and the rationale for sedation before and after initiating it. Generating a policy for conscientious objections, allowing nurses to express their own emotions and concerns in a supportive environment are suggested approaches to preserve their wellness.

Abstract The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Abstract In this study, we explore the transformation of $$D_p$$ D p -branes to $$D_{p-1}$$ D p - 1 -branes under T-duality when the D-brane is embedded in a spacetime with a boundary. Our goal is to derive the higher-derivative corrections to the Dirac–Born–Infeld (DBI) Lagrangian for both the bulk and boundary terms. For the bulk terms, we calculate the $$\alpha '$$ α ′ corrections for the massless open string fields, up to the 8th order in the dimensionless Maxwell field strength. We demonstrate that the bulk Lagrangian can satisfy the T-duality constraint without residual total derivative terms in the base space. This determines the most general independent couplings of the massless open string fields in the bulk Lagrangian, encompassing 145 coupling constants, up to three parameters. Two of these parameters are physical and are determined by disk-level S-matrix elements, while the third is unphysical and can be eliminated by field redefinitions and integration by parts. The final result for the bulk Lagrangian consists of 49 couplings. For the boundary terms, the application of T-duality symmetry to massless open and closed string fields enables us to extend the DBI Lagrangian to include the boundary unit normal vector field $$n_\mu $$ n μ and its first derivative.

Abstract A new release of the Monte Carlo event generator Herwig (version 7.3) has been launched. This iteration encompasses several enhancements over its predecessor, version 7.2. Noteworthy upgrades include: the implementation of a process-independent electroweak angular-ordered parton shower integrated with QCD and QED radiation; a new recoil scheme for initial-state radiation improving the behaviour of the angular-ordered parton shower; the incorporation of the heavy quark effective theory to refine the hadronization and decay of excited heavy mesons and heavy baryons; a dynamic strategy to regulate the kinematic threshold of cluster splittings within the cluster hadronization model; several improvements to the structure of the cluster hadronization model allowing for refined models; the possibility to extract event-by-event hadronization corrections in a well-defined way; the possibility of using the string model, with a dedicated tune. Additionally, a new tuning of the parton shower and hadronization parameters has been executed. This article discusses the novel features introduced in version 7.3.0.

Abstract The gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange. Results showed that, across scenarios with different initial species abundances, cross-feeding promotes species coexistence. Morphologically, competition and neutralism resulted in segregation, while mutualism and commensalism fostered high intermixing. In addition, cooperative relations resulted in community properties with little sensitivity to the selective uptake of metabolites produced by the host. Moreover, metabolic interactions strongly influenced colonization success following the invasion of newcomer species. These results provide important insights into the utility of ABM in deciphering complex microbiome patterns.

Abstract In a recent study, we have observed that by imposing a truncated T-duality transformation on the circular reduction of the bosonic couplings in the heterotic theory at four- and six-derivative orders, we can calculate these couplings in a particular YM gauge where the YM potential vanishes but its field strength remains non-zero. Importantly, the coupling constants are independent of the gauge choice, so these results are valid across different YM gauge choices. In this work, we explore the cosmological reduction of these couplings when the YM gauge fields belong to the Cartan subalgebra of SO(32) or E 8 × E 8. We demonstrate that after applying appropriate one-dimensional field redefinitions and total derivative terms, the couplings can be expressed in a proposed O(9, 25)-invariant canonical form, which is the extension of the canonical O(9, 9)-invariant form for just the NS-NS fields proposed by Hohm and Zwiebach. This O(9, 25)-invariant expression is in terms of the trace of the first time derivative of the generalized metric, which encompasses both the YM field and the NS-NS fields.

Abstract Objective This study aimed to evaluate the association of dynamic contrast enhancement (DCE) with clinically significant prostate cancer (csPCa, Gleason Grade Group ≥2) and compare biparametric magnetic resonance imaging (bpMRI) and multiparametric MRI (mpMRI) nomograms. Subjects/patients and methods We identified a retrospective cohort of biopsy naïve patients who underwent pre‐biopsy MRI separated by individual MRI series from 2018 to 2022. csPCa detection rates were calculated for patients with peripheral zone (PZ) lesions scored 3–5 on diffusion weighted imaging (DWI) with available DCE (annotated as − or +). bpMRI Prostate Imaging Reporting and Data System (PIRADS) (3 = 3−, 3+; 4 = 4−, 4+; 5 = 5−, 5+) and mpMRI PIRADS (3 = 3−; 4 = 3+, 4−, 4+; 5 = 5−, 5+) approaches were compared in multivariable logistic regression models. Nomograms for detection of csPCa and ≥GG3 PCa incorporating all biopsy naïve patients who underwent prostate MRI were generated based on available serum biomarkers [PHI, % free prostate‐specific antigen (PSA), or total PSA] and validated with an independent cohort. Results Patients (n = 1010) with highest PIRADS lesion in PZ were included in initial analysis with 127 (12.6%) classified as PIRADS 3+ (PIRADS 3 on bpMRI but PIRADS 4 on mpMRI). On multivariable analysis, PIRADS 3+ lesions were associated with higher csPCa rates compared to PIRADS 3− (3+ vs. 3−: OR 1.86, p = 0.024), but lower csPCa rates compared to PIRADS DWI 4 lesions (4 vs. 3+: OR 2.39, p

Abstract Predictive models for spatial correlation play an effective role in the assessment of seismic risk associated with distributed infrastructure and building portfolios. However, existing models often rely on simplified approaches, assuming isotropy and stationarity. This paper verifies these assumptions by presenting a comprehensive study using a database of 3D physics-based simulated broadband ground motions for Istanbul, generated by the SPEED software. The results reveal significant event-to-event variability and nonstationary and anisotropic characteristics of spatial correlation influenced by source, path, and site effects. The development of nonstationary correlation models requires exploring influential metrics beyond spatial proximity and gaining a deep understanding of their impact, which is the focus of this study. Analysis of the spatial correlations of peak ground displacement, peak ground velocity, peak ground acceleration, and response spectral accelerations at different periods, employing both stationary and nonstationary correlation modelling methods and considering the finite fault model, indicates that the slip distribution pattern, direction and distance of station pairs relative to earthquake rupture, soil softness, and homogeneity of soil properties significantly influence the spatial correlations of near-field earthquake ground motions. Implementation of the introduced parameters in predictive spatial correlation models enhances the precision of regional seismic hazard assessments.

With the ever-increasing popularity of Internet of Things (IoT), massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces (APIs) that can be accessible remotely. In this context, finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile applications. However, the number and diversity of candidate IoT Web APIs places an additional burden on application developers’ Web API selection decisions, as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs selected. Considering this challenge and latest successful applications of game theory in IoT, a Diversified and Compatible Web APIs Recommendation approach, namely DivCAR, is put forward in this paper. First of all, to achieve API diversity, DivCAR employs random walk sampling technique on a pre-built “API-API” correlation graph to generate diverse “API-API” correlation subgraphs. Afterwards, with the diverse “API-API” correlation subgraphs, the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem. A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search problem. At last, a set of experiments are designed and implemented on a real dataset crawled from www.programmableweb.com. Experimental results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.

Abstract Greenhouses located at high latitudes and in cloudy areas often experience a low quality and quantity of light, especially during autumn and winter. This low daily light integral (DLI) reduces production rate, quality, and nutritional value of many crops. This study was conducted on Sakhiya RZ F1 tomato plants to evaluate the impact of LED lights on the growth and nutritional value of tomatoes in a greenhouse with low daily light due to cloudy weather. The treatments included LED growth lights in three modes: top lighting, intra-canopy lighting, and combined top and intra-canopy lighting. The results showed that although the combined top and intra-canopy lighting reached the maximum increase in tomato yield, exposure to intra-canopy LED lighting alone outperformed in tomato fruit yield increase (28.46%) than exposure to top LED lighting alone (12.12%) when compared to no supplemental lighting during the entire production year. Intra-canopy exposure demonstrated the highest increase in tomato lycopene (31.3%), while top and intra-canopy lighting exhibited the highest increase in vitamin C content (123.4%) compared to the control. The LED light treatment also had a very positive effect on the expression of genes responsible for metabolic cycles, including Psy1, LCY-β, and VTC2 genes, which had collinearity with the increase in tomato fruit production.

Background: Hyperkalemia is a potentially life-threatening electrolyte disturbance that if not diagnosed on time may lead to devastating conditions and sudden cardiac death. Blood sampling for potassium level checks is time-consuming and can delay the treatment of severe hyperkalemia on time. So, we propose a non-invasive method for correct and rapid hyperkalemia detection. Methods: The cardiac signal of patients referred to the Pediatrics Emergency room of Shahid Rejaee Hospital was measured by a 12-lead Philips electrocardiogram (ECG) device. Immediately, the blood samples of the patients were sent to the laboratory for potassium serum level determination. We defined 16 features for each cardiac signal at lead 2 and extracted them automatically using the algorithm developed. With the help of the principal component analysis (PCA) algorithm, the dimension reduction operation was performed. The algorithms of decision tree (DT), random forest (RF), logistic regression, and support vector machine (SVM) were used to classify serum potassium levels. Finally, we used the receiver operation characteristic (ROC) curve to display the results Results: In the period of 5 months, 126 patients with a serum level above 4.5 (hyperkalemia) and 152 patients with a serum potassium level below 4.5 (normal potassium) were included in the study. Classification with the help of a RF algorithm has the best result. Accuracy, Precision, Recall, F1, and area under the curve (AUC) of this algorithm are 0.71, 0.87, 0.53, 0.66, and 0.69, respectively Conclusions: A lead2-based RF classification model may help clinicians to rapidly detect severe dyskalemias as a non-invasive method and prevent life-threatening cardiac conditions due to hyperkalemia.

Abstract The fourth energy revolution is characterized by the incorporation of renewable energy supplies into intelligent networks. As the world is shifting towards cleaner energy sources, there is a need for efficient and reliable methods to predict the output of renewable energy plants. Hybrid machine learning modified models are emerging as a promising solution for energy generation prediction. Renewable energy generation plants, such as solar, biogas, hydropower plants, wind farms, etc. are becoming increasingly popular due to their environmental benefits. However, their output can be highly variable and dependent on weather conditions, making integrating them into the existing energy grid challenging. Smart grids with artificial intelligent systems have the potential to solve this challenge by using real-time data to optimize energy production and distribution. Although by incorporating sensors, analytics, and automation, these grids can manage energy demand and supply more efficiently, reducing carbon emissions, increase energy security, and improve access to electricity in remote areas. However, this research aims to enhance the efficiency of solar power generation systems in a smart grid context using machine learning hybrid models such as Hybrid Convolutional-Recurrence Net (HCRN), Hybrid Convolutional-LSTM Net (HCLN), and Hybrid Convolutional-GRU Net (HCGRN). For this purpose, this study considers various parameters of a solar plant such as power production (MWh), irradiance or plane of array (POA), and performance ratio (PR). The HCLN model demonstrates superior accuracy with the RMSE values of 0.012027 for MWh, 0.013734 for POA and 0.003055 for PR, along with the lowest MAE values of 0.069523 for MWh, 0.082813 for POA, and 0.042815 for PR. The obtained results suggest that the proposed machine learning models can effectively enhance the efficiency of solar power generation systems by accurately predicting the required measurements.

Abstract This study delves into the dimensional reduction of the classical effective action of heterotic string theory on a circle, along with its T-duality symmetry, with the aim of identifying the bosonic couplings. To achieve this, we propose a truncation scheme for the generalized Buscher rules and the reduced action, specifically targeting the truncation of the nonlinear appearance of the scalar component of the Yang-Mills field in the base space. By imposing this truncated T-duality on the reduced action, we successfully determine the four- derivative bosonic couplings in the minimal basis, where field redefinition is imposed. Notably, these couplings, which are associated with the Lorentz Chern-Simons coupling HΩ, exhibit an exact correspondence with the NS-NS couplings found in the Metsaev-Tseytlin action. Furthermore, we investigate the bosonic couplings in the maximal basis, where field redefinition is not imposed. In this scenario, the truncated T-duality fixes the effective action up to 17 arbitrary parameters. By assigning specific values to these parameters, we establish a framework in which the NS-NS couplings align with those in the Meissner action. Remarkably, within this scheme, the Yang-Mills couplings precisely coincide with those obtained through the S-matrix method.

Abstract Numerous strategies have been proposed for the detection and prevention of non‐technical electricity losses due to fraudulent activities. Among these, machine learning algorithms and data‐driven techniques have gained prominence over traditional methodologies due to their superior performance, leading to a trend of increasing adoption in recent years. A novel two‐step process is presented for detecting fraudulent Non‐technical losses (NTLs) in smart grids. The first step involves transforming the time‐series data with additional extracted features derived from the publicly available State Grid Corporation of China (SGCC) dataset. The features are extracted after identifying abrupt changes in electricity consumption patterns using the sum of finite differences, the Auto‐Regressive Integrated Moving Average model, and the Holt‐Winters model. Following this, five distinct classification models are used to train and evaluate a fraud detection model using the SGCC dataset. The evaluation results indicate that the most effective model among the five is the Gradient Boosting Machine. This two‐step approach enables the classification models to surpass previously reported high‐performing methods in terms of accuracy, F1‐score, and other relevant metrics for non‐technical loss detection.

Abstract Data on the association between social isolation, loneliness, and risk of incident coronary heart disease (CVD) are conflicting. The objective of this study is to determine the relationship between social isolation and loneliness, and the risk of developing cardiovascular disease (CVD) in middle age and elderly using meta-analysis. The purpose of the bibliometric analysis is to systematically evaluate the existing literature on the relationship between social isolation, loneliness, and the risk of developing cardiovascular disease (CVD) in middle-aged and elderly individuals. A comprehensive search through four electronic databases (MEDLINE, Google Scholar, Scopus, and Web of Science) was conducted for published articles that determined the association between social isolation and/or loneliness and the risk of developing coronary heart disease from June 2015 to May 2023. Two independent reviewers reviewed the titles and abstracts of the records. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline to conduct the systematic review and meta-analysis. Data for the bibliometric analysis was obtained from the Scopus database and analyzed using VOSviewer and Bibliometrix applications. Six studies involving 104,511 patients were included in the final qualitative review and meta-analysis after screening the records. The prevalence of loneliness ranged from 5 to 65.3%, and social isolation ranged from 2 to 56.5%. A total of 5073 cardiovascular events were recorded after follow-up, ranging between 4 and 13 years. Poor social relationships were associated with a 16% increase in the risk of incident CVD (Hazard Ratio of new CVD when comparing high versus low loneliness or social isolation was 1.16 (95% Confidence Interval (CI) 1.10–1.22). The bibliometric analysis shows a rapidly growing field (9.77% annual growth) with common collaboration (6.37 co-authors/document, 26.53% international). The US leads research output, followed by the UK and Australia. Top institutions include University College London, Inserm, and the University of Glasgow. Research focuses on "elderly," "cardiovascular disease," and "psychosocial stress," with recent trends in "mental health," "social determinants," and "COVID-19". Social isolation and loneliness increase the risk of and worsen outcomes in incident cardiovascular diseases. However, the observed effect estimate is small, and this may be attributable to residual confounding from incomplete measurement of potentially confounding or mediating factors. The results of the bibliometric analysis highlight the multidimensional nature of CVD research, covering factors such as social, psychological, and environmental determinants, as well as their interplay with various demographic and health-related variables.

The lengthy time required for conventional boilers to attain a steady state, their sizable size, the substantial pressure drop, and their high cost are all disadvantages. The objective of this study was to develop a novel design for a boiler to achieve better performance based on a sprayed water boiler (SWB) through injectors with a specific spray rate in a near-atomized form over tubes containing hot gases. As the water temperature in the SWB is equal to the temperature of the water sprayed by the injectors, the temperature difference between the hot gases and the water is higher than in the conventional boiler. A parametric study was conducted to investigate the main parameters affecting the boiler performance, such as the steam quantity and quality, the time required to reach the steady state condition, the size of the boiler, and the drop pressure on the hot-gas side. The results showed that the size of the SWB was significantly smaller than that of a conventional boiler. When generating steam of the same quantity and quality, the size of the SWB is one-third of the conventional size. This reduces the manufacturing costs of the boiler and the pressure drop of the hot gases inside the boiler. It was also found that the thermal efficiency of the SWB was higher, and the start-up time to reach a steady state of operation was less than 1% of the time required for the conventional boiler. To close the gaps in the theoretical design, an experimental test should be performed.

The desalination of salty water has become a necessary industrial process to overcome the next global shortage in freshwater. In this study, adding a Reheat Solar Collector Cycle (RSCC) to a multi-stage flash plant is used to increase the optimization of the desalination process, improving efficiencies, reducing energy, and increasing the production of freshwater demands to overcome the global crisis of shortage in freshwater. Two projects employ this numerical technique. The first project is conducted in the Al-Khafji multi-stage flash plant in Saudi Arabia with an input mass flow rate of 1 Mkg/h (277.78 kg/s), TDS of 35,000 ppm, and wind velocity of 1 m/s. The second project is conducted in the Gulf of Aqaba in Jordan with an input mass flow rate of 1 Mkg/h (277.78 kg/s), TDS of 40,000 ppm, and wind velocity of 1 m/s. The module of the LS-2 Parabolic Trough Collector (PTC) is used to gain the required energy to heat seawater. The results show that in the Al-Khafji project, an increase of 7.1% in the plant capacity per day and an increase in efficiency from 7.8 to 8.4 were observed. While, in the Gulf of Aqaba, an increase of 7.7% in the plant capacity per day and an increase in efficiency from 7.8 to 8.4 are observed.

Drought is the greatest threat to food security in the climate change scenario, which affects crop plants' growth and development by disturbing the plant's physiological and biochemical processes. Zinc (Zn) is an essential micronutrient in many metabolic processes and may improve plant tolerance to water deficit conditions besides its nutritional value.This study investigated the reaction of several wheat species with different ploidy levels to foliar Zn application under water stress. Water stress significantly reduced grain yield (GY), leaf relative water contents (RWC), chlorophyll (Chla and Chlb), and carotenoid (Car) contents. Water stress also impacted several other physiological characteristics by increasing leaf hydrogen peroxide (HP), free proline (Prl), malondialdehyde (MDA) contents, soluble protein (PC), sodium content (Na+), and antioxidant enzymes, including peroxidase (Pox), ascorbate peroxidase (Aes) and catalase (Cat). Remarkably, the Zn application alleviated yield reduction caused by water stress. Moreover, the Zn application increased grains' Zn, potassium content (K+), and K+/Na+ ratio, RWC, Chl, Car contents, Pox, Aes, and Cat activities while significantly reducing MDA, HP, and Na+ contents compared with the control treatment. Pox, Aes, and Cat activities increased to higher concentrations in 6x and 4x than in 2x, indicating that the 6x and 4x species responded better to water stress. Wild and landrace varieties of 4x, such as T. dicoccum, T. ispahanicum, and T. dicoccoides, showed better water stress tolerance than the landrace varieties of 2x and 6x species. These species may be a valuable genetic source for improving modern bread and durum wheat to water stress.

Abstract The Schockley–Quisser (SQ) limit of 28.64% is distant from the Sb2S3 solar cells’ record power conversion efficiency (PCE), which is 8.00%. Such poor efficiency is mostly owing to substantial interface-induced recombination losses caused by defects at the interfaces and misaligned energy levels. The endeavor of this study is to investigate an efficient Sb2S3 solar cell structure via accurate analytical modeling. The proposed model considers different recombination mechanisms such as non-radiative recombination, Sb2S3/CdS interface recombination, Auger, SRH, tunneling-enhanced recombination, and their combined impact on solar cell performance. This model is verified against experimental work (Glass/ITO/CdS/Sb2S3/Au) where a good coincidence is achieved. Several parameters effects such as thickness, doping, electronic affinity, and bandgap are scrutinized. The effect of both bulk traps located in CdS and Sb2S3 on the electrical outputs of the solar cell is analyzed thoroughly. Besides, a deep insight into the effect of interfacial traps on solar cell figures of merits is gained through shedding light into their relation with carriers’ minority lifetime, diffusion length, and surface recombination velocity. Our research findings illuminate that the primary contributors to Sb2S3 degradation are interfacial traps and series resistance. Furthermore, achieving optimal band alignment by fine-tuning the electron affinity of CdS to create a Spike-like conformation is crucial for enhancing the immunity of the device versus the interfacial traps. In our study, the optimized solar cell configuration (Glass/ITO/CdS/Sb2S3/Au) demonstrates remarkable performance, including a high short-circuit current (J SC ) of 47.9 mA/cm2, an open-circuit voltage (V OC ) of 1.16 V, a fill factor (FF) of 54%, and a notable improvement in conversion efficiency by approximately 30% compared to conventional solar cells. Beyond its superior performance, the optimized Sb2S3 solar cell also exhibits enhanced reliability in mitigating interfacial traps at the CdS/Sb2S3 junction. This improved reliability can be attributed to our precise control of band alignment and the fine-tuning of influencing parameters.

Abstract In this study, we thoroughly investigate the covariant and B-field gauge invariant odd-parity NS-NS couplings at order $$\alpha '^3,$$ α ′ 3 , while considering the removal of field redefinitions, Bianchi identities, and total derivative freedoms. Our comprehensive analysis reveals the existence of 477 independent couplings. To establish a specific basis, we construct it in such a way that none of the couplings contain terms involving structures such as R, $$R_{\mu \nu },$$ R μ ν , $$\nabla _\mu H^{\mu \alpha \beta },$$ ∇ μ H μ α β , $$\nabla _\mu \nabla ^\mu \Phi ,$$ ∇ μ ∇ μ Φ , or terms with more than two derivatives, except for one term that possesses three derivatives on H. Interestingly, the mentioned coupling with the four-derivative on the B-field is rendered zero by the sphere-level three-point S-matrix element. Furthermore, we demonstrate that the remaining 476 parameters in type II superstring theory are fixed to zero by imposing the requirement that the circular reduction of the couplings remains invariant under $$O(1,1,{\mathbb {Z}})$$ O ( 1 , 1 , Z ) T-duality transformations. This result is consistent with our expectations and highlights the crucial role played by the $$O(1,1,{\mathbb {Z}})$$ O ( 1 , 1 , Z ) symmetry in constraining the parameter space of the classical effective actions in string theory.

Abstract Background Sleep disturbances, a public health concern that may lead to critical physiological conditions, are associated with personal characteristics such as gender. Limited evidence is available from the Middle East population on the gender disparities in sleep quality. Therefore, the current study examined gender-specific differences in sleep quality and disturbances among Jordanian citizens. Method A cross-sectional design was used to recruit a convenient sample of 1,092 adults from different Jordanian cities. Data was collected using a self-reported questionnaire comprising the Pittsburgh Sleep Quality Index (PSQI), which was distributed online via social media networks. The participants were categorized according to their global PSQI scores into poor (PSQI ≥ 5) and good sleepers (PSQI

Abstract Ramadan fasting (RF) involves abstaining from food and drink during daylight hours; it is obligatory for all healthy Muslims from the age of puberty. Although sick individuals are exempt from fasting, many will fast anyway. This article explores the impact of RF on individuals with kidney diseases through a comprehensive review of existing literature and consensus recommendations. This study was conducted by a multidisciplinary panel of experts. The recommendations aim to provide a structured approach to assess and manage fasting during Ramadan for patients with kidney diseases, empowering both healthcare providers and patients to make informed decisions while considering their unique circumstances.

This study investigates the performance dynamics of a six-cylinder, inline compression ignition engine, focusing on its response to varying turbocharger compressor pressure ratios (TCPRs). At a constant speed of 1500 RPM, the engine's power output, braking mean effective pressure, and brake torque increase significantly, ranging from 280 kW, 11.7 bar, and 1779.7 N m at a TCPR of 2–1042.6 kW, 43.7 bar, and 6637.8 N m at a TCPR of 10. This demonstrates a direct relationship between TCPR and engine performance metrics. Additionally, mechanical efficiency improves with increasing TCPR, indicating enhanced adaptability and efficiency of the engine. The study analyzes the effects of turbochargers, exhaust and intake characteristics, NOx emissions, combustion dynamics, and compressor settings, providing a comprehensive understanding of the relationship between turbocharging and compression ignition engines. These insights can support future research aimed at optimizing engine performance across various TCPR settings.

The nuclear pore complex (NPC) is a critical gateway regulating molecular transport between the nucleus and cytoplasm. It allows small molecules to pass freely, while larger molecules require nuclear transport receptors to traverse the barrier. This selective permeability is maintained by phenylalanine-glycine-rich nucleoporins (FG-Nups), intrinsically disordered proteins that fill the NPC’s central channel. The disordered and flexible nature of FG-Nups complicates their spatial characterization with conventional structural biology techniques. To address this challenge, polymer physics offers a valuable framework for describing FG-Nup behavior, reducing their complex structures to a few key parameters. In this review, we explore how polymer physics models FG-Nups using these parameters and discuss experimental efforts to quantify them in various contexts, providing insights into the conformational properties of FG-Nups.

Abstract Background While previously considered a transient condition, with no lasting adverse impact, gestational diabetes mellitus (GDM) is now a well‐established risk factor for developing type 2 diabetes mellitus (T2DM). The risk of developing T2DM appears to be particularly high in the first few years after childbirth, providing a compelling case for early intervention. This review provides an up‐to‐date systematic review and meta‐analysis to assess the effectiveness of interventions to reduce incidence of T2DM in women with a recent history of GDM. Methods The search was conducted on October 20, 2023 with an annual surveillance planned for the next 5 years to maintain a living systematic review. The inclusion criteria were randomized controlled trials of any type in women within 5 years of GDM‐complicated pregnancy that reported outcomes of T2DM diagnosis or measures of dysglycemia with a follow‐up of at least 12 months. Results Seventeen studies met our inclusion criteria and have been included in this review. There were 3 pharmacological and 14 lifestyle interventions. Intervention was not associated with significant reduction in the primary outcome of T2DM (risk ratio, 0.78; 95% confidence interval [CI]: 0.43–1.41; p = 0.41; I2 = 79%) compared with the control group (placebo or usual care). However, meta‐analysis of the four studies reporting hazard ratios suggested a reduction in diabetes incidence (hazard ratio, 0.68; 95% CI: 0.48–0.97; p = 0.03; I2 = 31%). Conclusion This review provides equivocal evidence about the efficacy of interventions to reduce the risk of T2DM in women within 5 years of GDM‐complicated pregnancy and highlights the need for further studies, including pharmacotherapy.

Abstract Precisely tuning bicomponent intimacy during reactions by traditional methods remains a formidable challenge in the fabrication of highly active and stable catalysts because of the difficulty in constructing well‐defined catalytic systems and the occurrence of agglomeration during assembly. To overcome these limitations, a PtRuPNiO@TiOx catalyst on a Ti plate was prepared by ultrasound‐assisted low‐voltage plasma electrolysis. This method involves the oxidation of pure Ti metal and co‐reduction of strong metals at 3000°C, followed by sonochemical ultrasonication under ambient conditions in an aqueous solution. The intimacy of the bimetals in PtRuPNiO@TiOx is tuned, and the metal nanoparticles are uniformly distributed on the porous titania coating via strong metal‒support interactions by leveraging the instantaneous high‐energy input from the plasma discharge and ultrasonic irradiation. The intimacy of PtRuPNiO@TiOx increases the electron density on the Pt surface. Consequently, the paired sites exhibit a high hydrogen evolution reaction activity (an overpotential of 220 mV at a current density of 10 mA cm−2 and Tafel slope of 186 mV dec−1), excellent activity in the hydrogenation of 4‐nitrophenol with a robust stability for up to 20 cycles, and the ability to contrast stated catalysts without ultrasonication and plasma electrolysis. This study facilitates industrially important reactions through synergistic chemical interactions.

IntroductionAnxiety and cognitive dysfunction are frequent, difficult to treat and burdensome comorbidities in human and canine epilepsy. Fecal microbiota transplantation (FMT) has been shown to modulate behavior in rodent models by altering the gastrointestinal microbiota (GIM). This study aims to investigate the beneficial effects of FMT on behavioral comorbidities in a canine translational model of epilepsy.MethodsNine dogs with drug-resistant epilepsy (DRE) and behavioral comorbidities were recruited. The fecal donor had epilepsy with unremarkable behavior, which exhibited a complete response to phenobarbital, resulting in it being seizure-free long term. FMTs were performed three times, two weeks apart, and the dogs had follow-up visits at three and six months after FMTs. Comprehensive behavioral analysis, including formerly validated questionnaires and behavioral tests for attention deficit hyperactivity disorder (ADHD)- and fear- and anxiety-like behavior, as well as cognitive dysfunction, were conducted, followed by objective computational analysis. Blood samples were taken for the analysis of antiseizure drug (ASD) concentrations, hematology, and biochemistry. Urine neurotransmitter concentrations were measured. Fecal samples were subjected to analysis using shallow DNA shotgun sequencing, real-time polymerase chain reaction (qPCR)-based Dysbiosis Index (DI) assessment, and short-chain fatty acid (SCFA) quantification.ResultsFollowing FMT, the patients showed improvement in ADHD-like behavior, fear- and anxiety-like behavior, and quality of life. The excitatory neurotransmitters aspartate and glutamate were decreased, while the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and GABA/glutamate ratio were increased compared to baseline. Only minor taxonomic changes were observed, with a decrease in Firmicutes and a Blautia_A species, while a Ruminococcus species increased. Functional gene analysis, SCFA concentration, blood parameters, and ASD concentrations remained unchanged.DiscussionBehavioral comorbidities in canine IE could be alleviated by FMT. This study highlights FMT’s potential as a novel approach to improving behavioral comorbidities and enhancing the quality of life in canine patients with epilepsy.

A combination of the dispersive liquid-liquid microextraction (DLLME) method based on the total vaporization procedure and cooling-assisted organic solvent-coated thin film microextraction (TFME) was applied for extracting chlorpyrifos (as the model compound). Based on the high thermal conductivity, a nickel foam thin film with the dimensions of 5.0 mm × 5.0 mm was used as a substrate for holding the organic solvent. Supporting thin film by organic solvent increases the thickness and contact area of the film relative to TFME or single drop microextraction (SDME) alone, resulting in a dramatic increase in the extraction efficiency. To protect the organic solvent and enhance the analyte distribution coefficient between the film and the vapor phase, a cooling system was applied. The proposed design was effective due to condensing the target analyte only on the uniform cooled thin film and not on the other regions in the extraction chamber. A corona discharge ionization source-ion mobility spectrometer was employed to identify the analyte. After optimizing the effective parameters, the limits of quantification (S/N = 10) and detection (S/N = 3) were calculated 0.1 and 0.03 μg L−1, respectively, and the dynamic range was measured between 0.1 and 7.0 μg L−1, with a determination coefficient of 0.9997. For three concentration levels of 0.1, 3.0, and 7.0 μg L−1, the relative standard deviations (n = 3) as the repeatability index were to be 6 %, 5 %, and 4 % for intra-day and 9 %, 6 %, and 5 % for inter-day, respectively. The enrichment factor was also calculated to be 3630 for the analyte concentration of 1.0 μg L−1. Well water, potato, and agricultural wastewater were analyzed as the real samples and the relative recovery values were measured between 92 % and 99 %. The accuracy of the proposed technique was validated by the European Standards EN 12393 method. In this approach, two steps of analyte extraction (DLLME and TFME) were used consecutively, resulting in better preconcentration and reduced matrix interference during cleaning-up.

Abstract Ricinus communis is one of the most important oilseed plants with many medicinal and industrial applications. Variation in 30 genotypes of castor bean collected from different regions of the world was evaluated for two consecutive years and the difference in seed production with two different reproductive modes (including apomixis and open-pollination) was compared based on yield components, agronomic traits, and phytochemical properties. Results of data analysis demonstrated that castor bean has the ability for a wide range of apomixis for seed production and the highest percentages of apomixis ability in the first and second years were 86.3% and 92.31%, respectively. Apomixis ability had a high positive correlation with yield components, seed oil content, and the amount of leaf rutin. Two genotypes from Brazil and Syria revealed the highest phenolic content in the first and second years, respectively. In addition, the Afghanistan genotype in two modes of apomixis and open-pollination in the first year and the Syria and Yazd genotypes in apomixis and open-pollination modes, respectively, in the second year showed the highest content of seed fatty acids. It is possible to maintain superior genotypes of castor bean in terms of phytochemical traits, yield, and oil quality through apomixis reproduction.

Abstract Background Deep learning has demonstrated significant advancements across various domains. However, its implementation in specialized areas, such as medical settings, remains approached with caution. In these high-stake environments, understanding the model's decision-making process is critical. This study assesses the performance of different pretrained Bidirectional Encoder Representations from Transformers (BERT) models and delves into understanding its decision-making within the context of medical image protocol assignment. Methods Four different pre-trained BERT models (BERT, BioBERT, ClinicalBERT, RoBERTa) were fine-tuned for the medical image protocol classification task. Word importance was measured by attributing the classification output to every word using a gradient-based method. Subsequently, a trained radiologist reviewed the resulting word importance scores to assess the model’s decision-making process relative to human reasoning. Results The BERT model came close to human performance on our test set. The BERT model successfully identified relevant words indicative of the target protocol. Analysis of important words in misclassifications revealed potential systematic errors in the model. Conclusions The BERT model shows promise in medical image protocol assignment by reaching near human level performance and identifying key words effectively. The detection of systematic errors paves the way for further refinements to enhance its safety and utility in clinical settings.

Recently, narrowband Internet-of-Things (NB-IoT) networks have been on the rise in the IoT field due to their features like low power consumption and high penetration rate. However, NB-IoT’s main drawbacks are its high delays and low data rates. To address these problems, in this paper, we present a two-tier cooperative solution to improve network throughput. Two-tier networks generally consist of cellular and device-to-device (D2D) communications. In this work, we use NB-IoT for cellular networks and Bluetooth low energy (BLE) for D2D communications. By leveraging these communications technologies, we enable idle nodes in a group to assist target nodes download and upload data. In doing this, we aim to maximize throughput, minimize consumed energy, and maximize the total remaining capacity of the node group batteries. To tackle the faced multi-objective optimization problem, we used the non-dominated sorting genetic algorithm (NSGA-II). Only one group gets selected from the candidate groups by adjusting the level of node participation. Simulation results show a 7.7-fold growth of throughput against only an 8 percent increase in energy consumption compared to the baseline download scenario and a 7.6-fold growth of throughput against just a 2 percent increase in energy consumption compared to the baseline upload scenario.

Abstract Overproduction of desired native or nonnative biochemical(s) in (micro)organisms can be achieved through metabolic engineering. Appropriate rewiring of cell metabolism is performed by making rational changes such as insertion, up-/down-regulation and knockout of genes and consequently metabolic reactions. Finding appropriate targets (including proper sets of reactions to be knocked out) for metabolic engineering to design optimal production strains has been the goal of a number of computational algorithms. We developed FastKnock, an efficient next-generation algorithm for identifying all possible knockout strategies (with a predefined maximum number of reaction deletions) for the growth-coupled overproduction of biochemical(s) of interest. We achieve this by developing a special depth-first traversal algorithm that allows us to prune the search space significantly. This leads to a drastic reduction in execution time. We evaluate the performance of the FastKnock algorithm using various Escherichia coli genome-scale metabolic models in different conditions (minimal and rich mediums) for the overproduction of a number of desired metabolites. FastKnock efficiently prunes the search space to less than 0.2% for quadruple- and 0.02% for quintuple-reaction knockouts. Compared to the classic approaches such as OptKnock and the state-of-the-art techniques such as MCSEnumerator methods, FastKnock found many more beneficial and important practical solutions. The availability of all the solutions provides the opportunity to further characterize, rank and select the most appropriate intervention strategy based on any desired evaluation index. Our implementation of the FastKnock method in Python is publicly available at https://github.com/leilahsn/FastKnock .

Abstract Recent studies have highlighted the significant role of utilizing O(1, 1) symmetry in the circular reduction of effective actions to determine NS–NS couplings in the effective action of string theory. However, these calculations often result in residual terms as total derivatives that do not conform to O(1, 1) transformations. In this paper, we present explicit calculations at $$\alpha '$$ α ′ order, demonstrating the enforceability of this symmetry on effective Lagrangians to establish the parameters governing covariant couplings in any scheme. Notably, we discover the O(1, 1)-invariant Lagrangians corresponding to the Metsaev–Tseytlin action and the Meissner action.

Abstract The integration of biology, computer science, and statistics has given rise to the interdisciplinary field of bioinformatics, which aims to decode biological intricacies. It produces extensive and diverse features, presenting an enormous challenge in classifying bioinformatic problems. Therefore, an intelligent bioinformatics classification system must select the most relevant features to enhance machine learning performance. This paper proposes a feature selection model based on the fractal concept to improve the performance of intelligent systems in classifying high-dimensional biological problems. The proposed fractal feature selection (FFS) model divides features into blocks, measures the similarity between blocks using root mean square error (RMSE), and determines the importance of features based on low RMSE. The proposed FFS is tested and evaluated over ten high-dimensional bioinformatics datasets. The experiment results showed that the model significantly improved machine learning accuracy. The average accuracy rate was 79% with full features in machine learning algorithms, while FFS delivered promising results with an accuracy rate of 94%.

SIRT4, together with SIRT3 and SIRT5, comprises the mitochondrially localized subgroup of sirtuins. SIRT4 regulates mitochondrial bioenergetics, dynamics (mitochondrial fusion), and quality control (mitophagy) via its NAD+‐dependent enzymatic activities. Here, we address the regulation of SIRT4 itself by characterizing its protein stability and degradation upon CoCl2‐induced pseudohypoxic stress that typically triggers mitophagy. Interestingly, we observed that of the mitochondrial sirtuins, only the protein levels of SIRT4 or ectopically expressed SIRT4‐eGFP decrease upon CoCl2 treatment of HEK293 cells. Co‐treatment with BafA1, an inhibitor of autophagosome–lysosome fusion required for autophagy/mitophagy, or the use of the proteasome inhibitor MG132, prevented CoCl2‐induced SIRT4 downregulation. Consistent with the proteasomal degradation of SIRT4, the lysine mutants SIRT4(K78R) and SIRT4(K299R) showed significantly reduced polyubiquitination upon CoCl2 treatment and were more resistant to pseudohypoxia‐induced degradation as compared to SIRT4. Moreover, SIRT4(K78R) and SIRT4(K299R) displayed increased basal protein stability as compared to wild‐type SIRT4 when subjected to MG132 treatment or cycloheximide (CHX) chase assays. Thus, our data indicate that stress‐induced protein degradation of SIRT4 occurs through two mechanisms: (a) via mitochondrial autophagy/mitophagy, and (b) as a separate process via proteasomal degradation within the cytoplasm.

In this work, we present a comprehensive analysis of the structure of six-derivative bosonic couplings in heterotic string theory. First, we determine the maximal covariant and Yang-Mills gauge invariant basis, which consists of 801 independent coupling constants. By imposing T-duality constraints on the circular reduction of these terms, we obtain 468 relations between the coupling constants at the six-derivative order and the known couplings at lower derivative orders. Through the use of field redefinitions, we are able to eliminate the remaining 333 coupling constants. Remarkably, we find that the Yang-Mills field strength only appears through the trace of two field strengths or their derivatives. Finally, we perform further field redefinition to rewrite the remaining couplings in a canonical form characterized by 85 independent couplings.

Recent work has proposed a method for imposing T-duality on the metric, B-field, and dilaton of the classical effective action of string theory without using Kaluza-Klein reduction. Specifically, the D-dimensional effective action should be invariant under global O(D,D) transformations, provided that the partial derivatives along the β-parameters of the non-geometrical elements of the O(D,D) group become zero. In this paper, we speculate that the global β-symmetry can be utilized to identify both bulk and boundary couplings.We demonstrate that the Gibbons-Hawking term at the leading order of α′ is reproduced by this symmetry. Additionally, for closed spacetime manifolds at order α′, we show that the 20 independent geometrical couplings at this order are fixed by this symmetry up to field redefinitions. Specifically, we show that the invariance of the most general covariant and gauge invariant bulk action at order α′ under the most general covariant deformed β-transformation at order α′ fixes the action up to 13 parameters. These parameters reflect the field redefinitions freedom for the closed spacetime manifolds. For particular values of these parameters, we recover the effective action in the Metsaev-Tseytlin and in the Meissner schemes.

IntroductionReinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, reinfection is defined as a positive test occurring at least 90 days after a previous infection diagnosis. Yet, this extended time window may lead to an underestimation of reinfection occurrences. This study investigated the prospect of adopting an alternative, shorter time window for defining reinfection.MethodsA longitudinal study was conducted to assess the incidence of reinfections in the total population of Qatar, from February 28, 2020 to November 20, 2023. The assessment considered a range of time windows for defining reinfection, spanning from 1 day to 180 days. Subgroup analyses comparing first versus repeat reinfections and a sensitivity analysis, focusing exclusively on individuals who underwent frequent testing, were performed.ResultsThe relationship between the number of reinfections in the population and the duration of the time window used to define reinfection revealed two distinct dynamical domains. Within the initial 15 days post-infection diagnosis, almost all positive tests for SARS-CoV-2 were attributed to the original infection. However, surpassing the 30-day post-infection threshold, nearly all positive tests were attributed to reinfections. A 40-day time window emerged as a sufficiently conservative definition for reinfection. By setting the time window at 40 days, the estimated number of reinfections in the population increased from 84,565 to 88,384, compared to the 90-day time window. The maximum observed reinfections were 6 and 4 for the 40-day and 90-day time windows, respectively. The 40-day time window was appropriate for defining reinfection, irrespective of whether it was the first, second, third, or fourth occurrence. The sensitivity analysis, confined to high testers exclusively, replicated similar patterns and results.DiscussionA 40-day time window is optimal for defining reinfection, providing an informed alternative to the conventional 90-day time window. Reinfections are prevalent, with some individuals experiencing multiple instances since the onset of the pandemic.

Objectives: We assessed short-, medium-, and long-term all-cause mortality risks after a primary SARS-CoV-2 infection. Methods: A national, matched, retrospective cohort study was conducted in Qatar to assess risk of all-cause mortality in the national SARS-CoV-2 primary infection cohort compared with the national infection-naïve cohort. Associations were estimated using Cox proportional-hazards regression models. Analyses were stratified by vaccination status and clinical vulnerability status. Results: Among unvaccinated persons, within 90 days after primary infection, the adjusted hazard ratio (aHR) comparing mortality incidence in the primary-infection cohort with the infection-naïve cohort was 1.19 (95% confidence interval 1.02-1.39). aHR was 1.34 (1.11-1.63) in persons more clinically vulnerable to severe COVID-19 and 0.94 (0.72-1.24) in those less clinically vulnerable. Beyond 90 days after primary infection, aHR was 0.50 (0.37-0.68); aHR was 0.41 (0.28-0.58) at 3-7 months and 0.76 (0.46-1.26) at ≥8 months. The aHR was 0.37 (0.25-0.54) in more clinically vulnerable persons and 0.77 (0.48-1.24) in less clinically vulnerable persons. Among vaccinated persons, mortality incidence was comparable in the primary-infection versus infection-naïve cohorts, regardless of clinical vulnerability status. Conclusions: COVID-19 mortality was primarily driven by an accelerated onset of death among individuals who were already vulnerable to all-cause mortality, but vaccination prevented these accelerated deaths.

Purpose: With the constant increase in food demand, agriculture became the second-highest waste-generating industry. Crop residues and wastewater from livestock farming are the major contributors and irrational disposal of them has a serious impact on ecosystems as well as human health. In this study, corncob as agriculture waste was used as a treatment agent, after converting it to biochar that adsorbs ammonia nitrogen in swine wastewater. Method: The biochar was prepared by pyrolysis at two different temperatures 350 °C and 450 °C. The physical properties of the biochar were investigated using scanning electron microscopy (SEM) analysis. The ammonia adsorption capacities and removal efficiencies of the two biochars were investigated using batch experiments by changing the pH of the wastewater solution as well as the contact time. Results: The highest ammonia removal efficiency of 83.98% was recorded at 450 °C after 90 min of contact time under alkaline pH (12) wastewater conditions whereas the lowest removal efficiency of 34.64% was obtained for 350 °C after 30 min exposure to wastewater at normal pH (7.32) condition. Conclusion: This study contributed to the ongoing research on the potential of feedstock-derived biochar to remove pollutants from wastewater. Highlights: A higher temperature (450 °C) in the processing of corncob biochar had more potential to adsorb ammonia from livestock wastewater than a lower temperature (350 °C). Increased pH (12) caused increased ammonia from 3.06 to 6.2 mg/l from normal pH (7.32) of wastewater samples; it was not saturated by corncob and showed higher adsorption rate by biochar. This study encourages the usage of agricultural waste (corncob) in beneficiary effects of wastewater treatment with the lowest expenses and being highly environmentally friendly.

Abstract Given the importance of specialized vocabulary in scientific communication and academic discourse, there is a growing need to create wordlists to address the vocabulary-learning needs of university students and researchers in different subject areas. The current study analyzed a corpus of chemistry research articles (with 278 million running words) to establish a mid-frequency vocabulary list for this field. Using frequency, range, and dispersion criteria, the study identified 560 lemmas in the fourth to the ninth British National Corpus/Corpus of Contemporary American English (BNC/COCA) lists that provided 6.4% coverage of all words in the corpus. The list was validated using specialized and general corpora, and the results confirmed the value and relevance of the items for chemistry. Moreover, for using the list for pedagogical goals, the vocabulary items were divided into five bands based on their coverage and importance. The 100 words in the first band were the most important mid-frequent vocabulary in chemistry, as they provided 3.05% coverage. The study highlights the significant contribution of mid-frequency words in research articles and the findings have implications for using large corpora as a big data source in identifying specialized and field-specific vocabulary.

Pesticide is one of the top chemical substances that pose a serious risk to public health. Imidacloprid (IMI) is a widely used broad-spectrum insecticide over the past decade. Here, oral IMI-contaminated green grass (at the dose rate of 100 mg/liter and sprayed) was fed to adult male rabbits (n=6), every alternate day for up to 90 days. The control rabbits (n=6) were fed pesticide-free green grass, wheat bran, and water ad libitum. For gross and histopathology, spleen, lymph nodes, and mucosa-associated lymphoid tissues were collected by ventromedial opening. No evident gross changes were found during the collection of the organs. Histopathologically, lymph nodes showed atrophy and degenerative lymphoid follicles. The cortex and medulla of the lymph nodes were less differentiated. The size and number of the lymphoid follicles in the cortex were also reduced in IMI-exposed rabbits. The spleen exhibited atrophic changes in the white pulps. The white pulp revealed degenerative changes with the depletion of the lymphoid tissues. As for the red pulp, it showed an irregular and depleted mesh network of reticular fibers in IMI-exposed rabbits compared to the control. The trachea and esophagus of IMI-exposed rabbits showed infiltration of the mononuclear cells in the propria-submucosa and tunica adventitia, respectively. The infiltration of mononuclear cells population was loaded in the core of the villi, tunica mucosa, and propria-submucosa of the duodenum, jejunum, and ileum of the IMI-exposed rabbits compared to the control. The present study findings suggest that IMI has toxic effects on the lymphoid organs and tissues of adult rabbits.

Abstract This study evaluated the interaction effects of irrigation level (well-watered and water stress conditions) and inoculation by different mycorrhizal species (non-inoculated, Funneliformis mosseae, Rhizophagus irregularis, Claroideoglomus claroideum, and Glomus fasciculatum) on mycorrhizal colonization, antioxidant activity, seed yield and oil quality of two sesame cultivars (Yekta and Naz). Water deficit decreased mycorrhizal colonization, seed yield and oil concentration but increased antioxidant activity and seed total phenol and flavonoid concentrations. However, mycorrhizal inoculation increased antioxidant activity, seed yield, oil concentration and total phenolic and flavonoids. The lowest reduction by water stress and the highest increase by inoculation in seed yield were observed in Naz plants inoculated by Cl. claroideum. Principal component analysis showed the highest differentiation effect of water stress compared to mycorrhizal inoculation on both cultivars, indicating the relative sensitivity of the two cultivars to water deficit. However, the application of different species of mycorrhizal fungi versus the non-inoculation conditions was somewhat discriminative. In terms of fatty acids, in most cases, water stress increased oleic, palmitic and stearic acids and decreased linoleic and linolenic acids but inoculation increased oleic and linoleic acids and decreased linolenic, palmitic and stearic acids. Regarding phenolic and flavonoids components, the contents of chlorogenic and caffeic acids were increased by water stress but no consistent trend was noted in response to water stress for the other compounds. Mycorrhizal inoculation generally decreased chlorogenic acid but increased gallic, caffeic, p-coumaric, and ferulic acids. In conclusion, the results of the present study may help to increase the level of valuable compounds in sesame for further pharmaceutical purposes under water stress conditions and mycorrhizal symbiosis.

Abstract Background IBD is considered an inflammatory disease with abnormal and exaggerated immune responses. To control the symptoms, different theraputic agents could be used, however, utilizing the agents with the least side effects could be important. Probiotics as beneficial microorganisms are one of the complementory theraputic agents that could be used to modulate inflammatory signaling pathways. In the current study, we aimed to identify the precise molecular effects of potential probiotics on signaling pathways involved in the development of inflammation. Methods A quantitative real-time polymerase chain reaction (qPCR) assay was used to analyze the expression of JAK /STAT (JAK1, JAK2, JAK3, TYK2, STAT1, STAT2, STAT3, STAT4, STAT5 and STAT6) and inflammatory genes (NEMO, TIRAP, IRAK, and RIP) after the HT -29 cell line treatment with the sonicated pathogens and potential probiotics. A cytokine assay was also used to evaluate IL -6 and IL -1β production after potential probiotic treatment. Results The potential probiotic cocktail downregulated the JAK genes and TIRAP, IRAK4, NEMO, and RIP genes in the NF-kB pathway compared with cells that were treated with sonicated gram negative pathogens. The expression of STAT genes was different after potential probiotic treatment. The production of IL -6 and IL -1β decreased after potential probiotic treatment. Conclusions Considering the importance of controlling the symptoms of IBD to improve the life quality of the patients, using probiotic could be crucial. In the current study the studied native potential probiotic cocktails showed anti-inflammatory effects via modulation of JAK /STAT and NF-kB signaling pathways. This observation suggests that our native potential probiotics consumption could be useful in reducing intestinal inflammation.

Abstract This paper investigates the β-symmetry of the heterotic string theory at order α′ in the context of open spacetime manifolds. Our analysis reveals that the parity-odd component of the effective action at this order remains invariant under β-transformations. Furthermore, we demonstrate that the corresponding β-transformations leave the Gibbons-Hawking boundary term invariant.

Abstract Upon examining the effective action of the heterotic string theory at order α′2, an inconsistency between the Chern-Simons coupling Ω2 and T-duality has been discovered. To address this issue, we introduce 60 parity-even independent geometrical couplings involving the B-field, metric, and dilation at the same order, each with arbitrary coefficients. To ensure the invariance of these couplings under T-duality, we consider the Miessner action for the couplings at order α′ and rigorously determine the coefficients of the 60 couplings in terms of the Chern-Simons coupling. Notably, it is found that the coefficients of the Riemann cubed terms must be zero, which aligns with the results of S-matrix calculations. Additionally, the parity odd couplings at order α′2 are obtained through T-duality. Overall, our analysis successfully resolves the inconsistency between the Chern-Simons coupling and T-duality, providing a more comprehensive understanding of the behavior of the heterotic string theory at order α′2.

The relatively rapid expansion of protected areas (PAs) has outpaced their effective governance, monitoring, and evaluation processes, resulting in a knowledge gap, particularly in relation to the impact and efficacy of co-managed protected areas in conserving biodiversity globally. Bangladesh, like numerous other nations, is expanding its existing co-management model to incorporate additional PAs while simultaneously making only limited modifications to the management of these protected areas. Evaluations, however, are relatively rare throughout the world, including Bangladesh, despite their potential to improve PA quality and effectiveness. The purpose of this article is to examine current co-management practices at two sites in Bangladesh’s Sundarbans to identify significant challenges and the efficacy of co-management initiatives through the establishment of a novel evaluative framework. The primary empirical data collection methods included key informant interviews, stakeholder consultation in focus group discussions, and uncontrolled personal observation. Despite significant progress in terms of policy and legislative reforms, many issues remained unattended, such as a goal of balancing conservation and development, increasing locals’ say in decision making, access to resources, and establishing strong institutions. This addition is believed to aid in reconciling the local community and the government. We also need to give more weight to such things as accounting and transparency, income diversification, and showing respect for preexisting social norms. The problems raised in this article are thought to be significant in bridging the gap between management plans and actual management of PAs, not just in Bangladesh but also in other regions of the world that use co-management to achieve sustainability.

Abstract Noonan syndrome (NS), the most common among RASopathies, is caused by germline variants in genes encoding components of the RAS-MAPK pathway. Distinct variants, including the recurrent Ser257Leu substitution in RAF1, are associated with severe hypertrophic cardiomyopathy (HCM). Here, we investigated the elusive mechanistic link between NS-associated RAF1S257L and HCM using three-dimensional cardiac bodies and bioartificial cardiac tissues generated from patient-derived induced pluripotent stem cells (iPSCs) harboring the pathogenic RAF1 c.770 C > T missense change. We characterize the molecular, structural, and functional consequences of aberrant RAF1–associated signaling on the cardiac models. Ultrastructural assessment of the sarcomere revealed a shortening of the I-bands along the Z disc area in both iPSC-derived RAF1S257L cardiomyocytes and myocardial tissue biopsies. The aforementioned changes correlated with the isoform shift of titin from a longer (N2BA) to a shorter isoform (N2B) that also affected the active force generation and contractile tensions. The genotype-phenotype correlation was confirmed using cardiomyocyte progeny of an isogenic gene-corrected RAF1S257L-iPSC line and was mainly reversed by MEK inhibition. Collectively, our findings uncovered a direct link between a RASopathy gene variant and the abnormal sarcomere structure resulting in a cardiac dysfunction that remarkably recapitulates the human disease.

Selecting a stable and high-yielding hybrid of maize requires an efficient method of evaluation. Evaluating hybrids in multi environments is crucial in breeding process to identify the optimal genotype adapted to different kind of environments. Two promising white grain three way crosses i.e. TWC-SK-330 and TWC-SK-331 and two promising yellow grain three way crosses TWC-Nub 8 and TWC-Nub 10 plus four commercial three way cross hybrids were assessed during Summer, 2021 in five different environments in Egypt, i.e. Sakha, Gemmiza, Nubaria, Sids and Mallawy laid out in a randomized complete block design. The data showed that environments (E), hybrids (H) and their interaction (HEI) mean squares were significant or highly significant for all the studied traits except (HEI) for 50% silking. E, H, HEI explained 86.41, 5.46 and 8.13 % of the total grain yield variations, respectively. The two promising white grained three way crosses, TWC-SK-330 and TWC-SK-331 recorded 9.03 and 9.07 t ha-1 of grain yield, respectively which exceeded insignificantly the two white checks TWC-321 and TWC-324 and showed stable by 7, 8 stability statistics, respectively. Therefore, these hybrids are considered as stable genotypes and high yielding.