Search

Abstract This paper presents the exponentiated alpha-power log-logistic (EAPLL) distribution, which extends the log-logistic distribution. The EAPLL distribution emphasizes its suitability for survival data modeling by providing analytical simplicity and accommodating both monotone and non-monotone failure rates. We derive some of its mathematical properties and test eight estimation methods using an extensive simulation study. To determine the best estimation approach, we rank mean estimates, mean square errors, and average absolute biases on a partial and overall ranking. Furthermore, we use the EAPLL distribution to examine three real-life survival data sets, demonstrating its superior performance over competing log-logistic distributions. This study adds vital insights to survival analysis methodology and provides a solid framework for modeling various survival data scenarios.

Abstract Conservation Agriculture (CA) is an innovative approach that promotes sustainable farming while enhancing soil health. However, residue management challenges often hinder its adoption, causing farmers to burn crop leftovers in fields. This study aimed to evaluate the effectiveness of various furrow openers under simulated soil bin conditions. Three types of furrow openers were examined: single disk (SD), Inverted T-type furrow opener with a plain rolling coulter (ITRC), and double disc (DD) furrow opener. Tests were conducted at different forward speeds (1.5, 2, and 2.5 km h−1) and with three straw densities (1, 2, and 3 t ha−1) at a consistent working depth of 5 cm. Draft measurements were obtained using load cells connected to an Arduino-based data-logging system. Results indicated that draft requirements increased with forward speed and straw density, while straw-cutting efficiency decreased with these factors. Average draft values for SD, ITRC, and DD were 290.3 N, 420 N, and 368.5 N, respectively, and straw-cutting efficiencies were 53.62%, 59.47%, and 74.89%, respectively. The DD furrow opener showed the highest straw-cutting efficiency (81.36%) at a working speed of 1.5 km h−1 and a straw density of 1 t ha−1, demonstrating optimal performance compared to other furrow openers.

Abstract Background Different materials have been used as wound dressings after vital pulp therapies. Some of them have limitations such as delayed setting, difficult administration, slight degree of cytotoxicity, crown discoloration and high cost. Therefore, to overcome these disadvantages, composite scaffolds have been used in regenerative dentistry. This study aims to construct and characterize the physicochemical behavior of a novel injectable alginate hydrogel loaded with different bioactive glass nanoparticles in various concentrations as a regenerative pulpotomy filling material. Methods Alginate hydrogels were prepared by dissolving alginate powder in alcoholic distilled water containing mesoporous bioactive glass nanoparticles (MBG NPs) or boron-doped MBG NPs (BMBG NPs) at 10 and 20 wt% concentrations. The mixture was stirred and incubated overnight in a water bath at 50 0 C to ensure complete solubility. A sterile dual-syringe system was used to mix the alginate solution with 20 wt% calcium chloride solution, forming the hydrogel upon extrusion. Then, constructed hydrogel specimens from all groups were characterized by FTIR, SEM, water uptake percentage (WA%), bioactivity and ion release, and cytotoxicity. Statistical analysis was done using One-Way ANOVA test for comparisons between groups, followed by multiple pairwise comparisons using Bonferroni adjusted significance level (p

Abstract This study explores the fractional form of modified Korteweg-de Vries-Kadomtsev-Petviashvili equation. This equation offers the physical description of how waves propagate and explains how nonlinearity and dispersion may lead to complex and fascinating wave phenomena arising in the diversity of fields like optical fibers, fluid dynamics, plasma waves, and shallow water waves. A variety of solutions in different shapes like bright, dark, singular, and combo solitary wave solutions have been extracted. Two recently developed integration tools known as generalized Arnous method and enhanced modified extended tanh-expansion method have been applied to secure the wave structures. Moreover, the physical significance of obtained solutions is meticulously analyzed by presenting a variety of graphs that illustrate the behaviour of the solutions for specific parameter values and a comprehensive investigation into the influence of the nonlinear parameter on the propagation of the solitary wave have been observed. Further, the governing equation is discussed for the qualitative analysis by the assistance of the Galilean transformation. Chaotic behavior is investigated by introducing a perturbed term in the dynamical system and presenting various analyses, including Poincare maps, time series, 2-dimensional 3-dimensional phase portraits. Moreover, chaotic attractor and sensitivity analysis are also observed. Our findings affirm the reliability of the applied techniques and suggest its potential application in future endeavours to uncover diverse and novel soliton solutions for other nonlinear evolution equations encountered in the realms of mathematical physics and engineering.

AbstractContext Asthma presents a global health challenge. The main pharmacotherapy is synthetic chemicals and biological-based drugs that are costly, and have significant side effects. In contrast, use of natural products, such as onion (Allium cepa L., Amaryllidaceae) in the treatment of airway diseases has increased world-wide because of their perceived efficacy and little safety concerns. However, their pharmacological actions remain largely uncharacterized.Objective We investigated whether onion bulb extract (OBE) can (1) reverse established asthma phenotype (therapeutic treatment) and/or (2) prevent the development of the asthma phenotype, if given before the immunization process (preventative treatment).Materials and methods Six groups of male Balb/c mice were established for the therapeutic (21 days) and five groups for the preventative (19 days) treatment protocols; including PBS and house dust mite (HDM)-challenged mice treated with vehicle or OBE (30, 60, and 100 mg/kg/i.p.). Airways inflammation was determined using cytology, histology, immunofluorescence, Western blot, and serum IgE.Results Therapeutic (60 mg/kg/i.p.) and preventative (100 mg/kg/i.p.) OBE treatment resulted in down-regulation of HDM-induced airway cellular influx, histopathological changes and the increase in expression of pro-inflammatory signaling pathway EGFR, ERK1/2, AKT, pro-inflammatory cytokines and serum IgE.Discussion and Conclusion Our data show that OBE is an effective anti-inflammatory agent with both therapeutic and preventative anti-asthma effects. These findings imply that onion/OBE may be used as an adjunct therapeutic agent in established asthma and/or to prevent development of allergic asthma. However, further studies to identify the active constituents, and demonstrate proof-of-concept in humans are needed.

The proportional hazard regression models are widely used statistical tools for analyzing survival data and estimating the effects of covariates on survival times. It is assumed that the effects of the covariates are constant across the time. In this paper, we propose a novel extension of the proportional hazard model by incorporating an exponentiated-Weibull distribution to model the baseline line hazard function. The proposed model offers more flexibility in capturing various shapes of failure rates and accommodates both monotonic and non-monotonic hazard shapes. The performance evaluation of the proposed model and comparison with other commonly used survival models including the generalized log–logistic, Weibull, Gompertz, and exponentiated exponential PH regression models are explored using simulation results. The results demonstrate the ability of the introduced model to capture the baseline hazard shapes and to estimate the effect of covariates on the hazard function accurately. Furthermore, two real survival medical data sets are analyzed to illustrate the practical importance of the proposed model to provide accurate predictions of survival outcomes for individual patients. Finally, the survival data analysis reveal that the model is a powerful tool for analyzing complex survival data.

Abstract Idling brain activity has been proposed to facilitate inference, insight, and innovative problem-solving. However, it remains unclear how and when the idling brain can create novel ideas. Here, we show that cortical offline activity is both necessary and sufficient for building unlearned inferential knowledge from previously acquired information. In a transitive inference paradigm, male C57BL/6J mice gained the inference 1 day after, but not shortly after, complete training. Inhibiting the neuronal computations in the anterior cingulate cortex (ACC) during post-learning either non-rapid eye movement (NREM) or rapid eye movement (REM) sleep, but not wakefulness, disrupted the inference without affecting the learned knowledge. In vivo Ca2+ imaging suggests that NREM sleep organizes the scattered learned knowledge in a complete hierarchy, while REM sleep computes the inferential information from the organized hierarchy. Furthermore, after insufficient learning, artificial activation of medial entorhinal cortex-ACC dialog during only REM sleep created inferential knowledge. Collectively, our study provides a mechanistic insight on NREM and REM coordination in weaving inferential knowledge, thus highlighting the power of idling brain in cognitive flexibility.

Abstract In this work, we study the efficiency of N 1, N 3-dibenzyl-N 1, N1, N 3, N 3-tetramethylpropane-1,3-diaminium chloride, as anticorrosion. This compound exhibits potential as a prospective remedy to stop the deterioration of carbon steel caused by corrosion in 1.0 M HCl. The synthesis of this compound is described in a comprehensive manner, and its composition is supported by a range of precise analytical approaches such as elemental analysis, and mass spectroscopy. Based on the findings of the investigation, the synthesized Gemini ionic liquid demonstrates a robust capacity to slow down the rate at which the metal corrodes. The Prepared compound was evaluation by electrochemical and morphology study. Our results revealed that elevating the inhibitor concentration led to an augmentation in inhibition effectiveness, reaching up to 94.8% at 200 ppm of the synthesized compound at 298 K. It is crucial to emphasize that the recently prepared Gemini ionic liquid is consistent with the Langmuir adsorption model and function as a mixed inhibitor, participating in the physio-chemisorption process of adsorption.

This comprehensive review assessed the integration of robotics and artificial intelligence (AI) in dentistry, offering a transparent overview of developments across dental fields. Covering articles in prosthodontics, orthodontics, implantology, surgery, and radiology, the review included 39 articles on robotics and 16 on AI. Screening adhered to PRISMA guidelines, with searches conducted on Medline, Google Scholar, and IEEE. Incorporating the search strategy, the review used keywords related to dentistry, robotics, and AI. For robotics, 296 articles were screened, resulting in 39 qualifying for qualitative synthesis. A separate AI search on PubMed identified 142 studies within the last decade, with 16 studies selected for a detailed full-text analysis, offering a consolidated overview of the current state-of-the-art knowledge in the AI domain. Geographic distribution highlighted East Asia as a major research contributor. The findings indicate an increasing trend in dentistry robotics since 2000 and, particularly since 2016, in AI dentistry. The majority of the literature fell under the category of basic research. The technology readiness level did not cross “three” (proof of concept) in 41% of all articles. Therefore, the overall literature quality remains low, particularly regarding clinical validation.

In this paper, we propose a parametric accelerated failure time (AFT) hazard-based regression model with the extended alpha-power exponential (EAPE) baseline distribution. The proposed model is called the extended alpha-power exponential-AFT (EAPE-AFT) regression model. We show that the EAPE distribution is closed under the AFT model. The parameters of the proposed EAPE-AFT model have been estimated by using the method of maximum likelihood estimation. An extensive simulation study was also conducted to examine the performance of the estimates under several scenarios based on the shapes of the baseline hazard function. Finally, real-life censored survival data has been used to illustrate the applicability of the proposed model.

Abstract Background The stability of resin–dentin interfaces is still highly questionable. The aim of this study was to evaluate the effect of Salvadora persica on resin–dentin bond durability. Materials and methods Extracted human third molars were used to provide mid-coronal dentin, which was treated with 20% Salvadora persica extract for 1 min after acid-etching. Microtensile bond strength and interfacial nanoleakage were evaluated after 24 h and 6 months. A three-point flexure test was used to measure the stiffness of completely demineralized dentin sticks before and after treatment with Salvadora persica extract. The hydroxyproline release test was also used to measure collagen degradation by endogenous dentin proteases. Statistical analysis was performed using two-way ANOVA followed by post hoc Bonferroni test and unpaired t-test. P-values 0.05). After 6 months, the bond strength of the control group decreased (p = 0.007), and nanoleakage increased (p = 0.006), while Salvadora persica group showed no significant difference in bond strength and nanoleakage compared to their 24 h groups (p > 0.05). Salvadora persica increased dentin stiffness and decreased collagen degradation (p

Abstract Background and Objectives We aim to characterize the sociodemographic and clinical factors associated with loss of jobs, income, and work hours in people with neuromyelitis optica spectrum disorder (NMOSD) in the United States. Methods A REDCap‐based survey was administered to working‐age NMOSD patients (18–70 years old) querying demographic information, symptoms, immunosuppression, work hours, income, and caregiver work (11/2022–07/2023). Regression models were developed using MATLAB. Results Of 127 participants (97 female; 55% AQP4‐antibody, 19% MOG antibody; 69% Caucasian, 7% Hispanic), with an average diagnosis age of 38.7 years, average disease duration of 6.4 years, mean 3.1 attacks, and 94% of whom were treated with immune system‐directed therapy (53% rituximab, 8% satralizumab, 7% eculizumab, 6% mycophenolate mofetil, 4% inebilizumab, 2% azathioprine, 10% IVIg, 10% other), 56% lost a job due to NMOSD. Employment decreased 12% (80% pre‐ to 68% post‐diagnosis). Thirty‐six percent of participants said they no longer worked outside the home. Significant predictors for post‐NMOSD diagnosis employment status included younger age, lower pain level, no walking aids, and having a job prediagnosis. Sixty‐eight percent of those employed prediagnosis reduced their work hours, dropping an average of 18.4 h per month since being diagnosed (±10.1 h). Average annual income grew slowly at $1998 during the average 6.4 years of disease duration (14% of the value predicted by the U.S. Bureau of Labor Statistics). Sixty percent of participants had a regular unpaid caregiver; 34% of caregivers changed their work hours or job to help manage NMOSD. Discussion We provide a structured analysis of the impact of NMOSD on employment, work hours, and income in the United States, demonstrating its major effect on the livelihoods of patients and their caregivers.

This study explores the course review process implemented by the College of Pharmacy at King Saud University for its Pharm.D. program. Through a qualitative research design, a dedicated course review committee was established to oversee the evaluation process. The committee gathered and analyzed data from various sources, including course reports, student evaluations, and exam center reports, to achieve a holistic understanding of each course’s effectiveness. The evaluation process was structured into a Four-Step Course Evaluation Approach: data collection, data review and recommendations, taking appropriate action, and communicating the outcomes. The “closing the loop” stage ensured that recommendations were effectively implemented, and course evaluation data were systematically archived for future reference. The results of this study, based on the evaluation of 25 courses, revealed significant improvements in course quality, alignment with program learning outcomes, and adherence to accreditation standards. Key findings included the identification of gaps and discrepancies, leading to targeted interventions and enhanced course content. Overall, this study highlights the effectiveness of a structured course review process in enhancing the quality of education and ensuring continuous improvement within the college. The committee focuses on refining evaluation criteria, conducting workshops, and providing training to stay current with emerging accreditation standards and best practices. This systematic course review process demonstrates the College’s commitment to providing high-quality education and preparing students for successful careers in pharmacy, with significant implications for the improvement of pharmacy education and the overall student learning experience.

We introduced a flexible class of continuous distributions called the generalized Kavya-Manoharan-G (GKM-G) family. The GKM-G family extended the Kavya-Manoharan class and provided greater flexibility to the baseline models. The special sub-models of the GKM-G family are capable of modeling monotone and non-monotone failure rates including increasing, reversed J shape, decreasing, bathtub, modified bathtub, and upside-down bathtub. Some properties of the family were studied. The GKM-exponential (GKME) distribution was studied in detail. Eight methods of estimation were used for estimating the GKME parameters. The performance of the estimators was assessed by simulation studies under small and large samples. Furthermore, the flexibility of the two-parameter GKME distribution was explored by analyzing five real-life data applications from applied fields such as medicine, environment, and reliability. The data analysis showed that the GKME distribution outperforms other competing exponential models.

Abstract Nitrogen (N) and phosphorus (P) are vital for crop growth. However, most agricultural systems have limited inherent ability to supply N and P to crops. Biochars (BCs) are strongly advocated in agrosystems and are known to improve the availability of N and P in crops through different chemical transformations. Herein, a soil-biochar incubation experiment was carried out to investigate the transformations of N and P in two different textured soils, namely clay loam and loamy sand, on mixing with rice straw biochar (RSB) and acacia wood biochar (ACB) at each level (0, 0.5, and 1.0% w/w). Ammonium N (NH4-N) decreased continuously with the increasing incubation period. The ammonium N content disappeared rapidly in both the soils incubated with biochars compared to the unamended soil. RSB increased the nitrate N (NO3–N) content significantly compared to ACB for the entire study period in both texturally divergent soils. The nitrate N content increased with the enhanced biochar addition rate in clay loam soil until 15 days after incubation; however, it was reduced for the biochar addition rate of 1% compared to 0.5% at 30 and 60 days after incubation in loamy sand soil. With ACB, the net increase in nitrate N content with the biochar addition rate of 1% remained higher than the 0.5% rate for 60 days in clay loam and 30 days in loamy sand soil. The phosphorus content remained consistently higher in both the soils amended with two types of biochars till the completion of the experiment.

Abstract The river stage is certainly an important indicator of how the water level fluctuates overtime. Continuous control of the water stage can help build an early warning indicator of floods along rivers and streams. Hence, forecasting river stages up to several days in advance is very important and constitutes a challenging task. Over the past few decades, the use of machine learning paradigm to investigate complex hydrological systems has gained significant importance, and forecasting river stage is one of the promising areas of investigations. Traditional in situ measurements, which are sometime restricted by the existing of several handicaps especially in terms of regular access to any points alongside the streams and rivers, can be overpassed by the use of modeling approaches. For more accurate forecasting of river stages, we suggest a new modeling framework based on machine learning. A hybrid forecasting approach was developed by combining machine learning techniques, namely random forest regression (RFR), bootstrap aggregating (Bagging), adaptive boosting (AdaBoost), and artificial neural network (ANN), with empirical mode decomposition (EMD) to provide a robust forecasting model. The singles models were first applied using only the river stage data without preprocessing, and in the following step, the data were decomposed into several intrinsic mode functions (IMF), which were then used as new input variables. According to the obtained results, the proposed models showed improved results compared to the standard RFR without EMD for which, the error performances metrics were drastically reduced, and the correlation index was increased remarkably and great changes in models’ performances have taken place. The RFR_EMD, Bagging_EMD, and AdaBoost_EMD were less accurate than the ANN_EMD model, which had higher R≈0.974, NSE≈0.949, RMSE≈0.330 and MAE≈0.175 values. While the RFR_EMD and the Bagging_EMD were relatively equal and exhibited the same accuracies higher than the AdaBoost_EMD, the superiority of the ANN_EMD was obvious. The proposed model shows the potential for combining signal decomposition with machine learning, which can serve as a basis for new insights into river stage forecasting.

Abstract In the context of degradation of soil health, environmental pollution, and yield stagnation in the rice–wheat system in the Indo-Gangetic Plains of South Asia, an experiment was established in split plot design to assess the long-term effect of crop residue management on productivity and phosphorus requirement of wheat in rice–wheat system. The experiment comprised of six crop residue management practices as the main treatment factor with three levels (0, 30 and 60 kg P2O5 ha–1) of phosphorus fertilizer as sub-treatments. Significant improvement in soil aggregation, bulk density, and infiltration rate was observed under residue management (retention/incorporation) treatments compared to residue removal or residue burning. Soil organic carbon (SOC), available nutrient content (N, P, and K), microbial count, and enzyme activities were also significantly higher in conservation tillage and residue-treated plots than without residue/burning treatments. The residue derived from both crops when was either retained/incorporated improved the soil organic carbon (0.80%) and resulted in a significant increase in SOC (73.9%) in the topsoil layer as compared to the conventional practice. The mean effect studies revealed that crop residue management practices and phosphorus levels significantly influenced wheat yield attributes and productivity. The higher grain yield of wheat was recorded in two treatments, i.e. the basal application of 60 kg P2O5 ha–1 without residue incorporation and the other with half the P-fertilizer (30 kg P2O5 ha–1) with rice residue only. The grain yield of wheat where the rice and wheat residue were either retained/incorporated without phosphorus application was at par with 30 and 60 kg P2O5ha–1. Phosphorus levels also significantly affected wheat productivity and available P content in the soil. Therefore, results suggested that crop residue retention following the conservation tillage approach improved the yield of wheat cultivated in the rice–wheat cropping system.

Implantation via an intercalary prosthetic method is a reliable solution for reconstructing a long defect in bones that has been damaged by severe disease or accidents. In the current study, using data from computed tomography (CT) scans, a novel costumed intercalary prosthesis design has been created. To achieve this purpose, the CT scan data of a patient in (DICOM) file format was converted into computer-aided design models and saved in stereolithography (STL) format using the 3D slicer (5.0.3) software. The STL files were loaded into Meshmixer software to design the models of the intercalary prosthesis. Finite element analysis (FEA) was applied to validate the strength of the prosthesis with impact, tensile testing, and torsional testing. According to the results of the impact tests, the highest recorded deformation was 8.8485e-002 m in the area where the implant body interfaces with the bone intramedullary canal, due to the high-stress (Von Mises Stress) value of 3.78 E9 PA. In the torsional loaded the highest deformation recorded was 1.3871e-008 m when the Von Mises stress reached 49006 PA, and with the application of the tensile test the largest deformation measured as 1.0458e-006 m at maximum Von Mises stress seen was recorded as 6.6012e+006 PA which caused that. A solid rod of Ti6Al4V alloy was selected. Finally, the analysis proved that the implant had enhanced mechanical properties. Based on the findings, it can be inferred that the prosthesis was successfully implanted, and a satisfactory result was obtained by using this design method.

This study examined the effects of nickel (Ni) at 0, 25, and 50 mg.L-1 concentrations, applied alone or in combination with salinity (represented by NaCl at 0, 100, and 200 mM concentrations), on the biochemical traits of date palm. Hydrogen peroxide (H2O2), malondialdehyde (MDA), membrane stability index (MSI), peroxidase (POD) activity, superoxide dismutase (SOD), and proline content were among the parameters evaluated. The results revealed significant effects of nickel and salinity on the studied biochemical markers. Nickel at 50 mg.L-1 significantly increased H2O2 (0.87 µmol. L-1) and MDA (2.46 nmol.g-1) levels, while decreasing MSI (75.85%). Moreover, it enhanced POD (25.09 U.min-1.g-1) and SOD (3.78 U. min-1.g-1) activity, as well as proline content (4.35 µmol.g-1). Salinity at 200 mM significantly increased H2O2 (0.90 µmol L-1) and MDA (2.54 nmol.g-1) levels, decreased MSI (77.69%), and increased POD (27.61 U. min-1.g-1) and SOD (3.77 U.min-1.g-1) activity, along with increased proline content (4.54 µmol.g-1). Additionally, the combined application of nickel and salinity, particularly at higher concentrations, resulted in significantly increased biochemical responses compared to individual treatments. The findings highlight the interactive effects of nickel and salinity on the oxidative and antioxidant mechanisms in date palm plants. This study contributes to our understanding of plant responses to abiotic stressors and provides insights for optimizing date palm cultivation under challenging environmental conditions.

Biochar is increasingly gaining popularity due to its extensive recommendation as a potential solution for addressing the concerns of food security and climate change in agroecosystems, with biochar application for increased carbon sequestration, enhanced soil fertility, improved soil health, and increased crop yield and quality. There have been multiple studies on crop yield utilizing various biochar types and application amounts; however, none have focused on the influence of diverse biochar types at various pyrolysis temperatures with different application amounts and the integration of fertilizer regimes in maize crops. Therefore, a two-year factorial field experiment was designed in a temperate Himalayan region of India (THRI) to evaluate the residual effect of different biochar on maize yield under different pyrolysis temperatures, various application rates and fertilizer regimes. The study included three factors viz., amendment type (factor 1), rate of application (factor 2) and fertilizer regime (factor 3). Amendment type included 7 treatments: No biochar- control (A1), apple biochar @ 400 °C pyrolysis temperature (A2), apple biochar @ 600 °C pyrolysis temperature (A3), apple residue biomass (A4), dal weed biochar @ 400 °C pyrolysis temperature (A5), dal weed biochar @ 600 °C pyrolysis temperatures (A6), and dal weed residue biomass (A7). The rate of application included 3 levels: Low (L- 1 t ha−1), medium (M- 2 t ha−1), and high (H- 3 t ha−1). At the same time, the fertilizer regimes included 2 treatments: No fertilizer (N) and recommended dose of fertilizer (F). The results revealed that among the various amendment type, rate of application and fertilizer regimes, the A3 amendment, H rate of application and F fertilizer regime gave the best maize growth and productivity outcome. Results revealed that among the different pyrolyzed residues used, the A3 amendment had the highest plant height (293.87 cm), most kernels cob−1 (535.75), highest soil plant analysis development (SPAD) value (58.10), greatest cob length (27.36 cm), maximum cob girth (18.18 cm), highest grain cob yield (1.40 Mg ha−1), highest grain yield (4.78 Mg ha−1), higher test weight (305.42 gm), and highest stover yield (2.50 Mg ha−1). The maximum dry weight in maize and the number of cobs plant−1 were recorded with amendments A4 (14.11 Mg ha−1) and A6 (1.77), respectively. The comparatively 2nd year of biochar application than the 1st year, the H level of the rate of application than the L rate and the application and integration of the recommended dose of fertilizer in maize results in significantly higher values of growth and productivity in maize. Overall, these findings suggest that the apple biochar @ 600 °C pyrolysis temperature (A3) at a high application rate with the addition of the recommended dose of fertilizer is the optimal biochar for enhancing the growth and productivity of maize in the THRI.

Abstract Background Anopheles pharoensis has a major role in transmitting several human diseases, especially malaria, in Egypt?. Controlling Anopheles is considered as an effective strategy to eliminate the spread of malaria worldwide. Galaxaura rugosa is a species of red algae found in tropical to subtropical marine environments. The presence of G. rugosa is indicative of the ecosystem's overall health. The current work aims to investigate UPLC/ESI/MS profile of G. rugosa methanol and petroleum ether extracts and its activity against An. pharoensis and non-target organisms, Danio rerio and Daphnia magna. Methods Galaxaura rugosa specimens have been identified using DNA barcoding for the COI gene and verified as G. rugosa. The UPLC/ESI/MS profiling of G. rugosa collected from Egypt was described. The larvicidal and repellent activities of G. rugosa methanol and petroleum ether extracts against An. pharoensis were evaluated, as well as the toxicity of tested extracts on non-target organisms, Dan. rerio and Dap. magna. Results The UPLC/ESI/MS analysis of methanol and petroleum ether extracts led to the tentative identification of 57 compounds belonging to different phytochemical classes, including flavonoids, tannins, phenolic acids, phenyl propanoids. Larval mortality was recorded at 93.33% and 90.67% at 80 and 35 ppm of methanol and petroleum ether extracts, respectively, while pupal mortality recorded 44.44 and 22.48% at 35 and 30 ppm, respectively. Larval duration was recorded at 5.31 and 5.64 days by methanol and petroleum ether extracts at 80 and 35 ppm, respectively. A decrease in acetylcholinesterase (AChE) level and a promotion in Glutathione-S-transferase (GST) level of An. pharoensis 3rd instar larvae were recorded by tested extracts. The petroleum ether extract was more effective against An. pharoensis starved females than methanol extract. Also, tested extracts recorded LC50 of 1988.8, 1365.1, and 11.65, 14.36 µg/mL against Dan. rerio, and Dap. magna, respectively. Conclusions Using red algae derivatives in An. pharoensis control could reduce costs and environmental impact and be harmless to humans and other non-target organisms.

Crop residue management and water saving are the two major issues for the sustainability of the rice-wheat cropping system. Therefore, a two-year field experiment was conducted in a split-plot design to study the combined effect of three rice residues (residue incorporation (RI), residue standing (RS) and residue removal (RR) and two wheat residue incorporation (WI) and residue removal (WR) management in main plots and two irrigation regimes, i.e., flood (F) and surface drip (SD) in subplots on the growth and water productivity of direct seeded rice (DSR). During both years, RI-WI resulted in significantly higher plant height (PH), leaf area index (LAI) and dry matter accumulation (DMA) than in other residue management treatments. Drip irrigation significantly increased PH, LAI, DMA grain yield, straw, and biological yield, along with a 9.6% irrigation water savings over flood irrigation. During both years, grain yield, straw and biological yield of DSR were significantly higher in RI-WI than in RR-WR and RR-WI. RI-WI had significantly greater apparent water productivity (AWP) and actual water productivity (RWP) of DSR. Drip irrigation had significantly higher AWP and RWP during both years than flood irrigation except RWP during 2017. Transpiration efficiency (TE) in rice residue incorporation was significantly higher than in rice residue standing and removal. During both years, the TE of drip irrigation was also significantly higher than flood irrigation. So, incorporating rice and wheat residues along with drip irrigation improves crop growth and water productivity.

Abstract Embryo development depends upon maternally derived materials. Mammalian oocytes undergo extreme asymmetric cytokinesis events, producing one large egg and two small polar bodies. During cytokinesis in somatic cells, the midbody and subsequent assembly of the midbody remnant, a signaling organelle containing RNAs, transcription factors and translation machinery, is thought to influence cellular function or fate. The role of the midbody and midbody remnant in gametes, in particular, oocytes, remains unclear. Here, we examined the formation and function of meiotic midbodies (mMB) and mMB remnants using mouse oocytes and demonstrate that mMBs have a specialized cap structure that is orientated toward polar bodies. We show that that mMBs are translationally active, and that mMB caps are required to retain nascent proteins in eggs. We propose that this specialized mMB cap maintains genetic factors in eggs allowing for full developmental competency.

Objective: The primary goal of this investigation was to ascertain the efficacy of the CALM® motion artifact reduction algorithm in diminishing motion-induced blurriness in Cone Beam Computed Tomography [CBCT] images. The assessment was conducted through Fractal Dimension [FD] analysis of the trabecular bone. Methods and Materials: A desiccated human mandible was subjected to Planmeca ProMax 3D® scanning under eight distinct protocols, marked by variations in motion presence [at 5, 10, and 15 degrees] and the deployment of CALM®. In every scan, five distinct regions of interest [ROIs] were designated for FD analysis, meticulously avoiding tooth roots or cortical bone. The FD was computed employing the box-counting method with Image-J 1.53 software. Results: Our findings reveal that a 5-degree motion does not significantly disrupt FD analysis, while a 10-degree motion and beyond exhibit statistical differences and volatility among the sites and groups. A decreased FD value, signifying a less intricate or “rough” bone structure, correlated with amplified motion blurriness. The utilization of CALM® software seemed to counteract this effect in some instances, reconciling FD values to those akin to the control groups. Nonetheless, CALM®’s efficacy differed across sites and motion degrees. Interestingly, at one site, CALM® application in the absence of motion resulted in FD values considerably higher than all other groups. Conclusion: The study indicates that motion, particularly at 10 degrees or more, can considerably impact the FD analysis of trabecular bone in CBCT images. In some situations, the CALM® motion artifact reduction algorithm can alleviate this impact, though its effectiveness fluctuates depending on the site and degree of motion. This underscores the necessity of factoring in motion and the employment of artifact reduction algorithms during the interpretation of FD analysis outcomes in CBCT imaging. More research is necessary to refine the application of such algorithms and to comprehend their influence on different sites under varying motion degrees.

Background: Morphological differences in the temporomandibular joint (TMJ) are crucial for the treatment of patients with cleft lip and palate (CLP). This study aims to evaluate and compare the TMJ parameters in patients with unilateral and bilateral CLP across growing and non-growing age groups using cone-beam computed tomography (CBCT). Methods: CBCT records from 57 patients (23 males and 34 females) aged 6–50 years with a diagnosed unilateral or bilateral CLP were analyzed. Patients were categorized into four groups: growing unilateral (UGCLP), growing bilateral (BGCLP), non-growing unilateral (UNGCLP), and non-growing bilateral (BNGCLP). Measurements of TMJ parameters, including the mandibular fossa, articular eminence inclination, joint spaces, and roof thickness of the glenoid fossa, were conducted using CBCT images. Results: Significant differences were observed in the anterior joint space (AJS) and the roof of the glenoid fossa (RGF) between growing and non-growing unilateral cleft patients. Additionally, significant discrepancies were found in the articular eminence angle when comparing the cleft and non-cleft sides within the unilateral growing group. No significant differences were observed in TMJ parameters between the right and left sides among bilateral cleft patients. Conclusions: The study highlights distinct TMJ morphological differences between growing and non-growing patients with CLP, emphasizing the importance of age-specific considerations in the treatment planning and growth monitoring of these patients.

Background: Down syndrome (DS) is a genetic condition characterized by an extra copy of chromosome 21, resulting in various physical and cognitive features. This study aimed to comprehensively analyze the dental and craniofacial morphology of individuals with DS using Cone Beam Computed Tomography (CBCT). Methods: Six individuals with DS, comprising five males and one female aged 17 to 35 years, underwent CBCT scanning. Radiographic assessments included dentition, occlusion, paranasal sinuses, airway, skull bones, and suture calcification. Linear and angular cephalometric measurements were performed, and airway analysis was conducted using Dolphin 3D imaging software v.11. Results: The study revealed prognathic maxilla in five patients, prognathic mandible in four, and bimaxillary protrusion in two. Dental findings included microdontia, enamel hypoplasia, and congenitally missing teeth, with maxillary and mandibular third molars most commonly absent. Sinus abnormalities, delayed suture closure, and cervical spine anomalies were also observed. Conclusion: These findings contribute to a deeper understanding of DS-related craniofacial characteristics and emphasize the importance of considering these morphometric features in clinical management strategies for individuals with DS. This study’s limited sample size underscores the significance of radiographic assessment in planning interventions such as cosmetic reconstructions, prosthetic rehabilitation, or orthodontic treatment for individuals with DS.

Background: One of the most dangerous problems that the world faced recently is viral respiratory pathogens. Marine creatures, including Echinodermata, specially Asteroidea class (starfish) have been extensively studied due to their miscellaneous bioactivities, excellent pharmacological properties, and complex secondary metabolites, including steroids, steroidal glycosides, anthraquinones, alkaloids, phospholipids, peptides, and fatty acids. These chemical constituents show antiviral activities against a wide range of viruses, including respiratory viruses. Results: The present study aimed at the identification of potential antiviral compounds from some starfish species. The bioactive compounds from Pentaceraster cumingi, Astropecten polyacanthus, and Pentaceraster mammillatus were extracted using two different solvents (ethyl acetate and methanol). The antiviral activity against influenza A/H1N1 virus showed that ethyl acetate extract from Pentaceraster cumingi has the highest activity, where the selective index was 150.8. The bioactive compounds of this extract were identified by GC/MS analysis. The molecular docking study highlighted the virtual mechanism of binding of the identified compounds towards polymerase basic protein 2 and neuraminidase for H1N1 virus. Interestingly, linoleic acid showed promising binding energy of −10.12 Kcal/mol and −24.20 Kcal/mol for the selected two targets, respectively, and it formed good interactive modes with the key amino acids inside both proteins. Conclusion: The molecular docking analysis showed that linoleic acid was the most active antiviral compound from P. cumingi. Further studies are recommended for in-vitro and in-vivo evaluation of this compound against influenza A/H1N1 virus.

The exponential distribution is one of the most widely used statistical distribution for reliability issues. In this paper, we introduce a novel family based on the exponential model, called the new exponential-H (NEx-H) family. The sub-models of the NEx-H family are capable of accommodating variable failure rates, as well as unimodal, bimodal, left-skewed, symmetric, right-skewed, and J-shape densities. The mathematical features of the NEx-H family are derived. The parameters of the NEx-Weibull distribution are estimated by using seven estimation methods. Detailed numerical simulations are presented. Based on our study, the maximum likelihood is the best estimation method for estimating the NEx-Weibull parameters. Three real-life data sets are fitted using the NEx-Weibull distribution. The NEx-Weibull model provides better fit as compared to some competing Weibull models.

Autism spectrum disorder (ASD) is a complex neurodevelopmental illness that often emerges in early childhood. The incidence of ASD has shown a notable rise in recent years. ASD is defined by deficits in social communication, and presence of rigid and repetitive behaviors and interests. The underlying mechanisms of ASD remain elusive. Multiple studies have documented the presence of neuroinflammation and increased levels of inflammatory cytokines, specifically, IL-6, TNF, and NF-κB, in various brain regions, including the prefrontal cortex (PFC) and hippocampus in individuals with ASD. Noradrenergic neurons play a crucial role in brain development and the regulation of motor, behavioral, and memory functions. This study sought to examine the impact of intracerebroventricular (icv.) injection of the neurotoxin, 6-hydroxydopamine (6-OHDA), in the caudal dorsal vagal complex A2 neurons on various neuroinflammatory pathways at the hippocampus and PFC in valproic acid (VPA) autistic animal model. This was done in conjunction with an intraperitoneal (i.p.) injection of Lipopolysaccharides (LPS) in animal models with VPA-induced autism. We specifically examined the impact of the caudal fourth ventricle 6-OHDA icv. injection and LPS (i.p.) injection on self-grooming behavior. We measured the mRNA expression of IL-6, TNF-a, and NF-κB using qRT-PCR, and the protein expression of COX-2, GPX-1, p-AMPK, and AMPK using western blot analysis. The self-grooming activity was considerably higher in the combined treatment group (6-OHDA icv. + LPS i.p.) compared to the control group. A substantial increase observed in the expression of IL-6, TNF-α, and NF-κB genes in the PFC of the treatment group that received icv. Administration of 6-OHDA, compared to the control group. The VPA-autism rats that received the combo treatment exhibited a slight increase in the expression level of NF-κB gene in the hippocampus, compared to the control group. At the PFC, we noticed a substantial drop in the expression of the antioxidant protein GPX-1 in the group that received the combo treatment compared to the control group. Our data investigates a novel aspect that the 6-OHDA-induced inhibition of hindbrain A2 neurons could be influencing the neuroinflammatory pathways in the PFC and hippocampus of autistic animal models.

In this study, we propose a new zero-inflated regression model as an alternative to zero-inflated regression models, such as the zero-inflated Poisson, zero-inflated negative binomial, zero-inflated hurdle-Poisson, and zero-inflated hurdle negative binomial models. In this regard, we take benefit of the flexibility of the Poisson–Bilal distribution and some of its notable properties. More concretely, it is employed as the baseline distribution to generate a new regression model called the zero-inflated Poisson-Bilal regression model. It is designed to be a good alternative for modeling overdispersed data quite effectively. This aspect is emphasized using two real-world data sets from the medicine and education fields. Furthermore, these data sets are analyzed to compare the goodness-of-fit of the suggested zero-inflated regression model with some of its direct competitors.

Abstract The design and selection of ideal emitter discharge rates can be aided by accurate information regarding the wetted soil pattern under surface drip irrigation. The current field investigation was conducted in an apple orchard in SKUAST- Kashmir, Jammu and Kashmir, a Union Territory of India, during 2017–2019. The objective of the experiment was to examine the movement of moisture over time and assess the extent of wetting in both horizontal and vertical directions under point source drip irrigation with discharge rates of 2, 4, and 8 L h−1. At 30, 60, and 120 min since the beginning of irrigation, a soil pit was dug across the length of the wetted area on the surface in order to measure the wetting pattern. For measuring the soil moisture movement and wetted soil width and depth, three replicas of soil samples were collected according to the treatment and the average value were considered. As a result, 54 different experiments were conducted, resulting in the digging of pits [3 emitter discharge rates × 3 application times × 3 replications × 2 (after application and 24 after application)]. This study utilized the Drip-Irriwater model to evaluate and validate the accuracy of predictions of wetting fronts and soil moisture dynamics in both orientations. Results showed that the modeled values were very close to the actual field values, with a mean absolute error of 0.018, a mean bias error of 0.0005, a mean absolute percentage error of 7.3, a root mean square error of 0.023, a Pearson coefficient of 0.951, a coefficient of correlation of 0.918, and a Nash–Sutcliffe model efficiency coefficient of 0.887. The wetted width just after irrigation was measured at 14.65, 16.65, and 20.62 cm; 16.20, 20.25, and 23.90 cm; and 20.00, 24.50, and 28.81 cm in 2, 4, and 8 L h−1 , at 30, 60, and 120 min, respectively, while the wetted depth was observed 13.10, 16.20, and 20.44 cm; 15.10, 21.50, and 26.00 cm; 19.40, 25.00, and 31.00 cm, respectively. As the flow rate from the emitter increased, the amount of moisture dissemination grew (both immediately and 24 h after irrigation). The soil moisture contents were observed 0.4300, 0.3808, 0.2298, 0.1604, and 0.1600 cm3 cm−3 just after irrigation in 2 L h−1 while 0.4300, 0.3841, 0.2385, 0.1607, and 0.1600 cm3 cm−3 were in 4 L h−1 and 0.4300, 0.3852, 0.2417, 0.1608, and 0.1600 cm3 cm−3 were in 8 L h−1 at 5, 10, 15, 20, and 25 cm soil depth in 30 min of application time. Similar distinct increments were found in 60, and 120 min of irrigation. The findings suggest that this simple model, which only requires soil, irrigation, and simulation parameters, is a valuable and practical tool for irrigation design. It provides information on soil wetting patterns and soil moisture distribution under a single emitter, which is important for effectively planning and designing a drip irrigation system. Investigating soil wetting patterns and moisture redistribution in the soil profile under point source drip irrigation helps promote efficient planning and design of a drip irrigation system.

Abstract The present research work focused on predicting the electrical conductivity (EC) of surface water in the Upper Ganga basin using four machine learning algorithms: multilayer perceptron (MLP), co-adaptive neuro-fuzzy inference system (CANFIS), random forest (RF), and decision tree (DT). The study also utilized the gamma test for selecting appropriate input and output combinations. The results of the gamma test revealed that total hardness (TH), magnesium (Mg), and chloride (Cl) parameters were suitable input variables for EC prediction. The performance of the models was evaluated using statistical indices such as Percent Bias (PBIAS), correlation coefficient (R), Willmott’s index of agreement (WI), Index of Agreement (PI), root mean square error (RMSE) and Legate-McCabe Index (LMI). Comparing the results of the EC models using these statistical indices, it was observed that the RF model outperformed the other algorithms. During the training period, the RF algorithm has a small positive bias (PBIAS = 0.11) and achieves a high correlation with the observed values (R = 0.956). Additionally, it shows a low RMSE value (360.42), a relatively good coefficient of efficiency (CE = 0.932), PI (0.083), WI (0.908) and LMI (0.083). However, during the testing period, the algorithm’s performance shows a small negative bias (PBIAS = − 0.46) and a good correlation (R = 0.929). The RMSE value decreases significantly (26.57), indicating better accuracy, the coefficient of efficiency remains high (CE = 0.915), PI (0.033), WI (0.965) and LMI (− 0.028). Similarly, the performance of the RF algorithm during the training and testing periods in Prayagraj. During the training period, the RF algorithm shows a PBIAS of 0.50, indicating a small positive bias. It achieves an RMSE of 368.3, R of 0.909, CE of 0.872, PI of 0.015, WI of 0.921, and LMI of 0.083. During the testing period, the RF algorithm demonstrates a slight negative bias with a PBIAS of − 0.06. The RMSE reduces significantly to 24.1, indicating improved accuracy. The algorithm maintains a high correlation (R = 0.903) and a good coefficient of efficiency (CE = 0.878). The index of agreement (PI) increases to 0.035, suggesting a better fit. The WI is 0.960, indicating high accuracy compared to the mean value, while the LMI decreases slightly to − 0.038. Based on the comparative results of the machine learning algorithms, it was concluded that RF performed better than DT, CANFIS, and MLP. The study recommended using the current month’s total hardness (TH), magnesium (Mg), and chloride (Cl) parameters as input variables for multi-ahead forecasting of electrical conductivity (ECt+1, ECt+2, and ECt+3) in future studies in the Upper Ganga basin. The findings also indicated that RF and DT models had superior performance compared to MLP and CANFIS models. These models can be applied for multi-ahead forecasting of monthly electrical conductivity at both Varanasi and Prayagraj stations in the Upper Ganga basin.

Abstract Clonal tracking of cells using somatic mutations permits exploration of clonal dynamics in human disease. Here, we perform whole genome sequencing of 323 haematopoietic colonies from 10 individuals with the inherited ribosomopathy Shwachman-Diamond syndrome to reconstruct haematopoietic phylogenies. In ~30% of colonies, we identify mutually exclusive mutations in TP53, EIF6, RPL5, RPL22, PRPF8, plus chromosome 7 and 15 aberrations that increase SBDS and EFL1 gene dosage, respectively. Target gene mutations commence in utero, resulting in a profusion of clonal expansions, with only a few haematopoietic stem cell lineages (mean 8, range 1-24) contributing ~50% of haematopoietic colonies across 8 individuals (range 4-100% clonality) by young adulthood. Rapid clonal expansion during disease transformation is associated with biallelic TP53 mutations and increased mutation burden. Our study highlights how convergent somatic mutation of the p53-dependent nucleolar surveillance pathway offsets the deleterious effects of germline ribosomopathy but increases opportunity for TP53-mutated cancer evolution.

Clefts of the lip or palate (CLPs) are the most common craniofacial birth defect, with a worldwide incidence of ~1 in 700 live births. The objective of this study is to assess the characteristics of the nasopharyngeal airway in growing vs. non-growing cleft lip/palate subjects and compare them with normal subjects. This retrospective study analyzed eighty-seven scans of three groups from cone beam computed tomography (CBCT). The cone beam computed tomography (CBCT) scans were coded and landmarks were identified using a Dolphin three-dimensional (3D) imaging software server (version 11.7; Patterson Dental Supply, Chatsworth, Calif). All values showed strong measurement reliability (>80), except for the nasopharynx measurement. Regarding gender difference, for the nasopharynx, female subjects (1261.32 ± 713.94) showed the lowest significant values in non-growing unilateral compared to males (6496.8 ± 2987) at p = 0.008. For oropharynx, in the growing bilateral cleft group, male subjects (13,046.79 ± 5521.89) showed a significant difference (p = 0.046) compared to females (8468.98 ± 4279.99). MP-SN, B, A, SNA., SN.B., and ANS-ME showed significant differences for cephalometric parameters (p < 0.05). Despite significant differences in linear and angular measurements, volumetric airway measurements showed no significant differences in the growing groups. For non-growing cleft subjects, the cleft anomaly significantly affected the nasal cavity and left maxillary sinus volumes.

The present study compares the six crop residue management techniques in main plots (since 2008) and three split nitrogen (N) levels, i.e., 75, 100 and 125 kg N/ha in subplots for rice crops for two years, i.e., 2019 and 2020, in sandy loam soil under field conditions. This experiment evaluated the long-term effect on rice productivity, soil organic carbon content and nutrient requirement in rice-wheat cropping system. The results revealed that different crop residue management practices and N levels significantly influenced rice growth, yield and yield attributes and improved nutrient uptake by grain and straw. Maximum grain yields of 20.8% and 17.8% higher over the conventional (no straw) treatment during 2019 and 2020, respectively, were recorded where the rice and wheat residue was retained or incorporated. The rice grain yield without residue responded significantly up to 125 kg N/ha. Whereas, with rice and wheat residue, rice grain yield did not respond to the application of N beyond 75 kg N/ha during both years.

Gliomas are a type of brain tumor that requires accurate monitoring for progression following surgery. The Brain Tumor Reporting and Data System (BT-RADS) has emerged as a potential tool for improving diagnostic accuracy and reducing the need for repeated operations. This prospective multicenter study aimed to evaluate the diagnostic accuracy and reliability of BT-RADS in predicting tumor progression (TP) in postoperative glioma patients and evaluate its acceptance in clinical practice. The study enrolled patients with a history of partial or complete resection of high-grade glioma. All patients underwent two consecutive follow-up brain MRI examinations. Five neuroradiologists independently evaluated the MRI examinations using the BT-RADS. The diagnostic accuracy of the BT-RADS for predicting TP was calculated using histopathology after reoperation and clinical and imaging follow-up as reference standards. Reliability based on inter-reader agreement (IRA) was assessed using kappa statistics. Reader acceptance was evaluated using a short survey. The final analysis included 73 patients (male, 67.1%; female, 32.9%; mean age, 43.2 ± 12.9 years; age range, 31–67 years); 47.9% showed TP, and 52.1% showed no TP. According to readers, TP was observed in 25–41.7% of BT-3a, 61.5–88.9% of BT-3b, 75–90.9% of BT-3c, and 91.7–100% of BT-RADS-4. Considering >BT-RADS-3a as a cutoff value for TP, the sensitivity, specificity, and accuracy of the BT-RADS were 68.6–85.7%, 84.2–92.1%, and 78.1–86.3%, respectively, according to the reader. The overall IRA was good (κ = 0.75) for the final BT-RADS classification and very good for detecting new lesions (κ = 0.89). The readers completely agreed with the statement “the application of the BT-RADS should be encouraged” (score = 25). The BT-RADS has good diagnostic accuracy and reliability for predicting TP in postoperative glioma patients. However, BT-RADS 3 needs further improvements to increase its diagnostic accuracy.

Cognitive Impairment (CI) is one of the most common and devastating manifestations in patients with Multiple Sclerosis (MS), which directly impacts the quality of life (QOL) and increases the burden of the disease. Years ago, CI was underrated but recently has gained far more attention from scientists in this field. The baseline pathophysiology and exact brain changes leading to CI are yet to be known. Both inflammatory and neurodegenerative processes could be contributing to CI. As a result, the diagnosis of subtle changes, especially in the early phases of the disease, along with the detection of changes throughout the disease course, is of utmost challenging debate among healthcare providers. Conventional Imaging techniques and usual neuropsychiatric screening tests may not detect early CI, rendering some cases missed. Serum or cerebrospinal fluid biomarkers are promising surrogates to detect the CI in these patients. The field of biomarkers in MS is evolving, and growing evidence indicates its applicability in decision-making. In this review, we focused on serum and CSF biomarkers that correlate with the CI in MS. In the end, we briefly discussed the future path in this regard.

Abstract Nowadays, Combine Harvesters are the most commonly used device for harvesting crops; as a result, a large amount of plant material and crop residue is concentrated into a narrow band of plant material that exits the combine, challenging the residue management task. This paper aims to develop a crop residue management machine that can chop paddy residues and mix them with the soil of the combined harvested paddy field. For this purpose, two important units are attached to the developed machine: the chopping and incorporation units. The tractor operates this machine as the main source, with a power range of about 55.95 kW. The four independent parameters selected for the study were rotary speed (R1 = 900 & R2 = 1100 rpm), forward speed (F1 = 2.1 & F2 = 3.0 Kmph), horizontal adjustment (H1 = 550 & H2 = 650 mm), and vertical adjustment (V1 = 100 & V2 = 200 mm) between the straw chopper shaft and rotavator shaft and its effect was found on incorporation efficiency, shredding efficiency, and trash size reduction of chopped paddy residues. The incorporation of residue and shredding efficiency was highest at V1H2F1R2 (95.31%) and V1H2F1R2 (61.92%) arrangements. The trash reduction of chopped paddy residue was recorded maximum at V1H2F2R2 (40.58%). Therefore, this study concludes that the developed residue management machine with some modifications in power transmission can be suggested to the farmers to overcome the paddy residue issue in combined harvested paddy fields.

الملخص: أهداف البحث: تهدف هذه المراجعة إلى تلخيص الدراسات العلمية حول مدى انتشار الكرب، والاحتراق النفسي، والقلق، والاكتئاب بين مقدمي الرعاية الصحية في دول مجلس التعاون الخليجي (المملكة العربية السعودية، البحرين، الكويت، سلطنة عمان، قطر، الإمارات العربية المتحدة) خلال جائحة كوفيد-١٩. طرق البحث: قمنا بالبحث في قواعد البيانات ببميد، سايك إنفو، سكوبس، وقوقل سكولار للتعرف على الدراسات ذات الصلة المنشورة في الفترة ما بين يناير ٢٠٢٠ إلى أبريل ٢٠٢١، وقمنا بعمل مراجعة منهجية وتحليل تلوي. النتائج: تم العثور على ١٨١٥ ورقة في قواعد البيانات، من بينها ٢٩ دراسة استوفت معايير الاشتمال، ومنها ١٩ دراسة قمنا بتضمينها في التحليل التلوي. التقدير المجمع للقلق المتوسط إلى الشديد باستخدام مقياس ''جاد-7'' كان ٣٤.٥٧٪ (فترة الثقة: ١٩.٧٣٪ إلى ٥١.١٢٪)، بينما للاكتئاب المتوسط إلى الشديد باستخدام مقياس ''استبانة صحة المريض-9'' كان٥٣.٢١٪ (فترة الثقة: ٣٢.٧٦٪ إلى ٧٢.٩٦٪)، وللكرب باستخدام '' مقياس إدراك الكرب-10'' كان ٨١.١٢٪ (فترة الثقة: ٧٢.١٥٪ إلى ٨٨.٧٠٪).أما بالنسبة للاحتراق النفسي، فلم يتم عمل التحليل التلوي لقلة الدراسات التي تم العثور عليها، غير أن أعلى نسبة بين الدراسات كانت ٪٧٦ (فترة الثقة: ٪٦٤ إلى ٪٨٥).وبشكل عام، فقد لوحظ وجود اتجاه موجب مع تقدم الوقت للجائحة بالنسبة للقلق والاكتئاب المتوسطين إلى شديدي الدرجة. مع ملاحظة بأن هناك عدم تجانس عال بين الدراسات، وكثير من الدراسات كانت منخفضة الجودة. الاستنتاجات: معدل انتشار الاضطرابات النفسية بين العاملين في الرعاية الصحية في دول مجلس التعاون الخليجي خلال الجائحة الحالية عال. على الرغم من ذلك، قد تتأثر النتائج بعدم التجانس العالي بين الدراسات وانخفاض جودتها. Abstract: Objectives: The aim of this study was to summarize the available evidence on the prevalence of stress, burnout, anxiety and depression among healthcare providers in the Gulf Cooperation Council (GCC) countries (KSA, Bahrain, Kuwait, Oman, Qatar, and the United Arab Emirates) during the COVID-19 pandemic. Methods: We searched PubMed, PsycINFO, Scopus, and Google scholar for related studies published between January 2020 and April 2021 and conducted a systematic review and meta-analysis. Results: Of the 1815 identified studies, 29 met the inclusion criteria, and 19 studies were included in the meta-analysis. The pooled estimate of prevalence for moderate to severe anxiety as reported using GAD-7 was 34.57% (95% CI = 19.73%, 51.12%), that for moderate to severe depression using PHQ-9 was 53.12% (95% CI = 32.76%, 72.96%), and that for moderate to severe stress using the 10-item Perceived Stress Scales was 81.12% (95% CI = 72.15%, 88.70%). Meta-analysis was not performed for burnout due to the small number of identified studies and the different tools used; however, the highest prevalence was reported at 76% (95% CI = 64%, 85%). Overall, a positive trend was observed over time for moderate to severe anxiety and depression, p = 0.0059 and 0.0762, respectively. Of note, the heterogeneity was significant among the studies, and many studies were of poor quality. Conclusion: The prevalence of mental health disorders during the current pandemic among healthcare workers in GCC countries is high. However, the results could be affected by the high heterogeneity and low quality studies.

Green infrastructure (GI) is increasingly linked to urban water management and can contribute to achieving water security in communities. This research uses a variation-finding comparative approach to recognize how far GI solutions are currently used to address water security in the urban developments of Monterrey City, Mexico, and Brussels-Capital Region, Belgium. A comparative content analysis of seven related urban development/sectoral plans is conducted using ATLAS.ti 9 software. The results depict the overall distribution of GI implementations, their typologies and spatial scales, water-security aspects that are addressed by GI, and the related definitions in the plans. In general, our analysis does not present a promising situation for the Monterrey case, although it reveals that policymakers have started to use GI in urban plans to address water security. Considering Brussels’ conditions, although GI solutions are much more frequent and advanced than in Monterrey plans, the region cannot be considered a frontrunner of GI policies. Comparing these two remarkably diverse areas is beneficial to illuminate universal aspects of planning, as the method provides an opportunity to gain insight from a multi-city perspective, whether developed or developing, showing the potential areas to advance urban policies.

This study addresses the crucial role of temperature forecasting, particularly in agricultural contexts, where daily maximum (Tmax) and minimum (Tmin) temperatures significantly impact crop growth and irrigation planning. While machine learning (ML) models offer a promising avenue for temperature forecasts, the challenge lies in efficiently training multiple models and optimizing their parameters. This research addresses a research gap by proposing advanced ML algorithms for multi-step-ahead Tmax and Tmin forecasting across various weather stations in Bangladesh. The study employs Bayesian optimization and the asynchronous successive halving algorithm (ASHA) to automatically select top-performing ML models by tuning hyperparameters. While both the Bayesian and ASHA optimizations yield satisfactory results, ASHA requires less computational time for convergence. Notably, different top-performing models emerge for Tmax and Tmin across various forecast horizons. The evaluation metrics on the test dataset confirm higher accuracy, efficiency coefficients, and agreement indices, along with lower error values for both Tmax and Tmin forecasts at different weather stations. Notably, the forecasting accuracy decreases with longer horizons, emphasizing the superiority of one-step-ahead predictions. The automated model selection approach using Bayesian and ASHA optimization algorithms proves promising for enhancing the precision of multi-step-ahead temperature forecasting, with potential applications in diverse geographical locations.

Incremental sheet forming (ISF) process offers a high degree of flexibility in the manufacturing of different sheet parts, which makes it an ideal candidate for prototype parts as well as efficient at fabricating various customized products at low production costs compared to traditionally used processes. However, parts produced in this process exhibit notable geometrical inaccuracy and considerable thickness reduction. In this paper, the single point incremental sheet forming variant of the process has been implemented to manufacture a highly customized cranial implant starting from the computed tomography (CT) scan data of the patient's anatomy. A methodology, from the modeling to the realization of the implant, is presented and discussed. The primary aim of the research was to analyze and study the effect of the multistage toolpath strategy compared to the traditional single-stage toolpath in terms of geometrical accuracy and thickness distribution. The final results show that the part formed in the multistage toolpath strategy exhibited a more uniform thickness distribution compared to the single-stage approach. Regarding the geometrical accuracy, the deviation analysis between the nominal and actual data has revealed that the multistage forming has significantly enhanced the final geometrical accuracy of the formed part.

The purpose of the current article is to numerically and theoretically examine the flow of two-dimensional (2D) steady Hiemenz with the transfer of heat of carbon nanotubes (CNTs) hybrid base C2H6O2+H2O (Ethylene glycol + water) nanofluid across a linear shrinking/stretching surface. The equations of Navier–Stokes have been converted into equations of self-similar applying suitable transformations of similarity variables, and then numerically resolved using the three-stage Labatto-three-A formula. In addition, an endeavor is made to extend the behavior of asymptotic of the solution to massive stretching. The comparison between the found asymptotic solutions and previously reported numerical results is rather impressive. Observations indicate that equations of self-similar display double solutions within the restricted shrinking parameter range. There exists one solution for every case of stretching. In the first solution, the impacts of nanoparticle solid volume fraction and shrinking parameters on velocity and thermal fields exhibit an increasing trend. Consequently, the linear analysis of temporal stability has been performed to establish the most fundamentally viable option. The smallest eigenvalue sign determines whether a solution is unstable or stable for the purposes of stability analysis. The analysis of stability demonstrates that the first solution describing the primary flow is stable.

Previous investigations have shown that D. viscosa herbal extract is often used to treat a variety of diseases. Therefore, the purpose of this study was to investigate any additional potential impacts on rat liver and kidney damage induced by diabetes. Streptozotocin (STZ) (60 mg/kg/day) was given as a single dosage to cause type 1 diabetes. After then, diabetic rats received oral doses of D. viscosa for four weeks at 150 and 300 mg/kg/day. Blood, liver, and kidney tissues were collected at the end of the treatment and examined. Analysis was made of the serum lipid profile, liver, and kidney functions, as well as blood biochemistry. Moreover, the levels of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), prostaglandin E-2 (PGE-2), and nitric oxide (NO) were estimated in serum. In liver and kidney samples, thiobarbituric acid reactive substances (TBARs) and reduced glutathione (GSH), as well as the pro-inflammatory cytokines and enzymatic activities of glutathione peroxidase (GPx), glutathione reeducates (GR), glutathione-S-transferase (GST), catalase (CAT), and superoxide dismutase (SOD) were analyzed. Histological changes in liver and kidney cross-sections were also observed. Our findings demonstrated that D. viscosa dramatically decreased pro-inflammatory indicators in blood, kidney, and liver tissues as well as blood glucose, and restored insulin levels, and lipid profiles. Additionally, it significantly raises the antioxidant enzyme activity SOD, CAT, GPx, and GST, while significantly lowering TBARs levels. The above-mentioned biochemical changes that took place in tissues were further supported by histological alterations. These findings imply that D. viscosa protects against STZ-induced hyperglycemia, aberrant lipid synthesis, and oxidative stress and that these benefits may be mediated by interacting with various targets to increase the levels of antioxidant enzymes in the liver and kidneys. Its mode of action and safety for use as medicine against various metabolic problems caused by diabetes require more research.

Abstract. Background. Prostatic epithelial cells synthesize the active form of vitamin D (1,25-dihydroxyvitamin D3), which participates in regulating prostate growth. Calcitriol, a synthetic form of vitamin D3, exhibits antiproliferative and prodifferentiation activities in prostate cancer. The function of 1,25-dihydroxyvitamin D3 is mediated by its binding to vitamin D receptor (VDR). VDR forms a heterodimer, typically with retinoid X receptor, to regulate vitamin D target genes. We evaluated the relationship between VDR polymorphism and clinical characteristics associated with prostate cancer risk and prognosis among Egyptian men. Materials and methods. This case-control study included 2 groups of patients: group A, a control group of 50 subjects with benign prostate hyperplasia, and group B, 50 subjects newly diagnosed with prostate cancer. All participants performed complete blood count, liver and kidney function tests, prostate specific antigen measurement, histopathological analysis and immunohistochemistry for Dickkopf Homolog 3. Restriction fragment length polymorphism-polymerase chain reaction as performed to detect VDR polymorphism. Results. Patients with prostate cancer and controls showed a significantly different CA genotype frequency (p = 0.007). Furthermore, prostate-specific antigen levels were significantly different in different genotypes in patients with prostate cancer (p < 0.001). Finally, T stage and the VDR ApaI C/A polymorphism were significantly associated (p < 0.041). Conclusion. The VDR ApaI C/A polymorphism may be a diagnostic and prognostic marker for prostate cancer in Egyptian men.

Gefitinib is a tyrosine kinase inhibitor (TKI) of the epidermal growth factor receptor (EGFR), used for the treatment of advanced or metastatic non-small cell lung cancer. Recently, studies proved that Gefitinib-induced cardiotoxicity through induction of oxidative stress leads to cardiac hypertrophy. The current study was conducted to understand the mechanisms underlying gefitinib-induced cardiac hypertrophy through studying the roles of angiotensin II (AngII), oxidative stress, and mitogen-activated protein kinase (MAPK) pathway. Male Wistar albino rats were treated with valsartan, gefitinib, or both for four weeks. Blood samples were collected for AngII and cardiac markers measurement, and hearts were harvested for histological study and biochemical analysis. Gefitinib caused histological changes in the cardiac tissues and increased levels of cardiac hypertrophy markers, AngII and its receptors. Blocking of AngII type 1 receptor (AT1R) via valsartan protected hearts and normalized cardiac markers, AngII levels, and the expression of its receptors during gefitinib treatment. valsartan attenuated gefitinib-induced NADPH oxidase and oxidative stress leading to down-regulation of JNK/p38-MAPK pathway. Collectively, AT1R blockade adjusted AngII-induced NADPH oxidase and JNK/p38-MAPK leading to attenuation of gefitinib-induced cardiac hypertrophy. This study found a pivotal role of AngII/AT1R signaling in gefitinib-induced cardiac hypertrophy, which may provide novel approaches in the management of EGFRIs-induced cardiotoxicity.

Abstract Background People with multiple sclerosis (PwMS) have balance deficits while ambulating through environments that contain moving objects or visual manipulations to perceived self-motion. However, their ability to parse object from self-movement has not been explored. The purpose of this research was to examine the effect of medial–lateral oscillations of the visual field and of objects within the scene on gait in PwMS and healthy age-matched controls using virtual reality (VR). Methods Fourteen PwMS (mean age 49 ± 11 years, functional gait assessment score of 27.8 ± 1.8, and Berg Balance scale score 54.7 ± 1.5) and eleven healthy controls (mean age: 53 ± 12 years) participated in this study. Dynamic balance control was assessed while participants walked on a treadmill at a self-selected speed while wearing a VR headset that projected an immersive forest scene. Visual conditions consisted of (1) no visual manipulations (speed-matched anterior/posterior optical flow), (2) 0.175 m mediolateral translational oscillations of the scene that consisted of low pairing (0.1 and 0.31 Hz) or (3) high pairing (0.15 and 0.465 Hz) frequencies, (4) 5 degree medial–lateral rotational oscillations of virtual trees at a low frequency pairing (0.1 and 0.31 Hz), and (5) a combination of the tree and scene movements in (3) and (4). Results We found that both PwMS and controls exhibited greater instability and visuomotor entrainment to simulated mediolateral translation of the visual field (scene) during treadmill walking. This was demonstrated by significant (p

Based on the ab-initio calculations, we have investigated the electronic, optical, and thermal properties of pristine SnSe and doped with oxygen (O) and sulphur (S) at the Se-site at concentration of 3.125%. The calculated negative formation energy indicates the stability of the pristine SnSe and doped system. We find that pristine SnSe possesses a direct bandgap value of 0.90 eV having good comparable to experimental value. The doping of O and S tunes the bandgap of SnSe, which can be promising for photovoltaic devices. Further, for the technological applications of O-/S-doped SnSe, we have analyzed optical properties in terms of absorption of photon energy and polarization. Strong absorption peaks confirms the direct transition of electrons from valence band to conduction band. Moreover, the thermal properties are calculated in terms of electrical/thermal conductivities, Seebeck coefficient, and figure of merit (ZT). At room temperature the ZT values are calculated round about 0.41 for O- and S-doped SnSe, respectively. We expect that our calculated thermoelectric parameters of the O- and S-doped SnSe could pave a new route for the application in the thermoelectric devices.

Sporadic burning of rice straw and the particulate air pollution caused consequently have created a pressing need for identification of practical environmentally sound in situ rice residue management methods. However, the agronomic interventions associated with the agri-inputs particularly the type of nitrogen fertilizer source must be worked out for these interventions. In a two-year field study performed at two different locations representing sandy loam and clay loam soil types, zero tillage with application of nitrophosphate (applied as basal dose through drilling) in combination with urea (applied at 1st irrigation + 3 foliar sprays of urea at weekly interval) significantly enhanced the grain and straw yield of wheat. The soil microbial viable cell counts and dehydrogenase and urease enzyme activities were also recorded to be highest in this treatment indicating the occurrence of higher living microbial population. The treatment × response variable Principle component analysis (PCA) biplot depicted relative variation among the residue management treatments/Nitrogen fertilizer sub-treatments and the enzyme activities as response variables. A variation in the soil organic content components was recognized through Fourier transform infra-red spectroscopy (FT-IRS) studies. Irrespective of the soil types under study, the FT-IR spectra exhibited presence of the aromatic carbon functional groups in residue incorporated treatments as compared to the no residue incorporation treatment.