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Artificial neural networks (ANNs) is widely adopted by researchers for classification tasks due to their simplicity and superior performance. This study offerings the ANN and it variant such as Elman Neural Network (NN) model to address its strengths, although it faces with issues like local minima and slow convergence. This study presents a comprehensive evaluation of four distinct algorithms for classification tasks, focusing on their performance on both training and testing datasets. These algorithms such as Sine Cosine Algorithm is integrated with Artificial Neural Networks (SCA_ANN), Back Propagation Neural Networks (SCA_BP), Elman Neural Networks (SCA_ElmanNN), and Elman Neural Networks (ElmanNN). The evaluation employs two key performance metrics: Accuracy (ACC) and Mean Squared Error (MSE). The training dataset, representing 70% of the data, is used for algorithm training, and the testing dataset, constituting the remaining 30%, assesses the algorithms' ability to generalize to new, unseen data. Results indicate that SCA_ElmanNN in both training and testing datasets, achieving high accuracy and minimal MSE, showcasing its proficiency in classification and prediction precision. SCA_BP and SCA_ANN also demonstrate robust performance. Conversely, ElmanNN, while relatively accurate, exhibits a slightly higher MSE on the testing data, indicating some variability in its predictions. These findings offer valuable insights for researchers in selecting the most appropriate algorithm for specific classification tasks.

Abstract Background Guangxi is the leading sugarcane-producing area in China. Due to the Panama disease outbreak in banana gardens, sugarcane and banana rotation was recommended. A field experiment with the newly released sugarcane cultivar Zhongzhe 1 (ZZ1) was conducted to understand the role of the sugarcane–banana rotation system in shaping the rhizosphere microbiota. Fields in the region possess characteristics of red laterite soil. Results Using Illumina HiSeq sequencing to analyze soil samples’ 16S rRNA V3-V4 region, the preceding banana rotation field had relatively greater bacterial diversity than the monoculture sugarcane field. Proteobacteria, Chloroflexi, Actinobacteria, and Acidobacteria were the dominant phyla, with distinct taxa enriched in each environment. However, the preceding sugarcane monoculture field enriched functional groups related to nitrogen fixation and cellulolysis. Network analysis highlighted contrasting network structures between sugarcane and banana rhizospheres, suggesting differential stability and susceptibility to environmental influences. Furthermore, correlations between soil properties and bacterial alpha-diversity underscored the influence of preceding crops on rhizosphere microbial communities. Conclusion This research enhances our understanding of crop rotation effects on soil microbial ecology and provides insights into optimizing agricultural practices for enhanced soil health and crop productivity. Future studies should explore the underlying mechanisms driving these interactions and evaluate the long-term impacts of crop rotation on soil microbial dynamics. Graphical abstract

Abstract Objective Septic arthritis is an orthopedic emergency and if not evaluated and treated appropriately, it can lead to poor clinical outcomes. Previously several studies have been performed to identify the etiology of septic arthritis in the pediatric population in developed countries. The main objective of our study was to identify the etiology of septic arthritis in children in Qatar in previously healthy and fully vaccinated children. Methods We performed retrospective chart analysis of children presenting to our emergency department between July 2018 and June 2024, who were diagnosed and treated with septic arthritis. The study was conducted at a level 1 pediatric trauma center and the only children's hospital in the country. We used ICD 9 and ICD 10 codes to identify such cases. After using predefined exclusion criteria, children with positive blood cultures, blood titers for Brucella and/or synovial cultures were included in the analysis. Clinical symptoms and signs, ultrasound findings, and culture results were tabulated using descriptive statistics. Results A total of 45 patients were included. The median age of children was 5 years (interquartile range [IQR] 2–10 years). Majority (60%) were male. The most common clinical findings were limping/limitation of joint movement (100%), fever (80%), and swelling of joints (58%). The median C‐reactive protein and erythrocyte sedimentation rate were 94 mg/L and 47 mm/h. The knee and hip were the most common joints affected. The most common causative organisms were Staphylococcus aureus (56%), Streptococcus pyogenes (13%), and Brucella (11%). Pre‐intervention imaging, such as ultrasound and/or magnetic resonance imaging, was performed in 95% of patients. All patients recovered without any complications. One of the limitations of our study is that cases of Kingella kingae septic arthritis may be underreported as polymerase chain reaction (PCR) analysis of synovial fluid was not performed on all patients. Conclusion Gram‐positive cocci, especially S. aureus, remains the most common cause of septic arthritis in vaccinated children. We also identified Gram‐negative bacilli as causative organisms in our study. We suggest including empiric coverage for both Gram‐ and Gram‐negative bacilli when treating children with suspected septic arthritis till culture results are available.

Intraoperative positioning system (IOPS; Centerline Biomedical, Inc) is a novel technology that allows for real-time intravascular navigation of endovascular devices using an electromagnetic field. In this report, we describe the use of IOPS for effective treatment of bilateral common iliac artery aneurysms with endovascular aortoiliac repair using iliac branch endoprostheses. Our experience suggests that this technology has the potential to reduce radiation and contrast use in endovascular procedures, although its application is currently limited. To the best of our knowledge, this is the first reported case of bilateral internal iliac cannulations for iliac branch endoprosthesis placement using IOPS.

Abstract Background Saccharum spontaneum L. is a closely related species of sugarcane and has become an important genetic component of modern sugarcane cultivars. Stem development is one of the important factors for affecting the yield, while the molecular mechanism of stem development remains poorly understanding in S. spontaneum. Phenylalanine ammonia-lyase (PAL) is a vital component of both primary and secondary metabolism, contributing significantly to plant growth, development and stress defense. However, the current knowledge about PAL genes in S. spontaneum is still limited. Thus, identification and characterization of the PAL genes by transcriptome analysis will provide a theoretical basis for further investigation of the function of PAL gene in sugarcane. Results In this study, 42 of PAL genes were identified, including 26 SsPAL genes from S. spontaneum, 8 ShPAL genes from sugarcane cultivar R570, and 8 SbPAL genes from sorghum. Phylogenetic analysis showed that SsPAL genes were divided into three groups, potentially influenced by long-term natural selection. Notably, 20 SsPAL genes were existed on chromosomes 4 and 5, indicating that they are highly conserved in S. spontaneum. This conservation is likely a result of the prevalence of whole-genome replications within this gene family. The upstream sequence of PAL genes were found to contain conserved cis-acting elements such as G-box and SP1, GT1-motif and CAT-box, which collectively regulate the growth and development of S. spontaneum. Furthermore, quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis showed that SsPAL genes of stem had a significantly upregulated than that of leaves, suggesting that they may promote the stem growth and development, particularly in the + 6 stem (The sixth cane stalk from the top to down) during the growth stage. Conclusions The results of this study revealed the molecular characteristics of SsPAL genes and indicated that they may play a vital role in stem growth and development of S. spontaneum. Altogether, our findings will promote the understanding of the molecular mechanism of S. spontaneum stem development, and also contribute to the sugarcane genetic improving.

Abstract In recent years, the internet has not only enhanced the quality of our lives but also made us susceptible to high‐frequency cyber‐attacks on communication networks. Detecting such attacks on network traffic is made possible by intrusion detection systems (IDS). IDSs can be broadly divided into two groups based on the type of detection they provide. According to the established rules, the first signature‐based IDS detects threats. Secondly, anomaly‐based IDS detects abnormal conditions in the network. Various machine and deep learning approaches have been used to detect anomalies in network traffic in the past. To improve the detection of anomalies in network traffic, researchers have compared several machine learning models, such as support vector machines (SVM), logistic regressions (LRs), K‐Nearest Neighbour (KNN), Nave Bayes (NBs), and boosting algorithms. The accuracy, precision, and recall of many studies have been satisfactory to an extent. Therefore, this paper proposes an ensemble learning‐based stacking classifier (ELSC) to achieve a better accuracy rate. In the proposed ELSC algorithm, KNN, NB, LR, and Decision Trees (DT) served as the base classifiers, while SVM served as the meta classifier. Based on a Network Intrusion detection dataset provided by Kaggle.com, ELSC is compared to base classifiers such as KNN, NB, LR, DT, SVM, and Linear Discriminate Analysis. As a result of the simulations, the proposed ELBS stacking classifier was found to outperform the other comparative models and converge with an accuracy of 99.4%.

This study aims to pharmacologically validate Haridra Khanda (HK) and Manjishthadi Kwatham (brihat) (MMK) in allergy management using invivo and invitro studies to rationalize the prescription of these two ayurvedic polyherbal drug formulations, which are currently used in Indian government hospitals. Experimental animals received HK and MMK orally from day 0 to day 14 and histamine (1 mg/kg b.w/i.v) and 1 % evans blue (EB) (0.1 mL) via tail vein on day 14. The compound 48/80 (intracutaneous) challenged mice model followed the same technique. The former mimicked acute anaphylaxis and the latter mast cell degranulation. For both models, EB dye leakage was quantified spectrophotometrically to determine vascular permeability. Plasma histamine was measured in Compound 48/80-induced animals using LC-ESI-MS/MS. The guineapig received HK and MMK p.o. and 0.6 % histamine sprayed in a histamine chamber to simulate allergic rhinitis. Blood eosinophil count and sneeze rate were measured in histamine-challenged guineapigs. Goat R.B.C. membrane stability assay (mammalian cell membrane toxicity) and intracellular histamine-induced cytosolic Ca2+ release assay in Chinese hamster ovary (CHO) cells were performed in vitro. For both histamine and Compound 48/80 challenged animals, HK (22.81 % and 14.58 %) and MMK (19.71 % and 22.40 %) significantly reduced EB dye leakage (p

Case Presentation: We present the case of a six-year-old child with autism who presented with persistent vomiting in the setting of a closed head injury (CHI). Computed tomography of the head was normal, but due to persistent vomiting a radiograph of the abdomen was done, which showed multiple, rare-earth magnets in the abdomen. There was no history of witnessed ingestion. These magnets had caused enteroenteric fistula formation leading to persistent vomiting. Discussion: In the setting of CHI, vomiting can be a sign of concussion or intracranial hemorrhage. In cases of CHI where intracranial pathology is ruled out and vomiting still persists, it is important to explore intra-abdominal causes of vomiting, especially in developmentally challenged children as they have higher incidence of unwitnessed foreign body ingestions.

Recent advancements in image processing and computer vision have brought significant transformations in healthcare technology, leading to significant improvements in diagnosis accuracy, cost-effectiveness, and time efficiency. Magnetic Resonance Imaging (MRI) is employed by the radiologist for its remarkable ability to detect even the most subtle brain abnormalities. This study considers a comprehensive analysis of the two prominent object identification frameworks, YOLOv5 and YOLOv7, leveraging state-of-the-art deep learning architectures to classify and detect brain cancers within MRI. The brain tumor dataset encompasses three distinct classes, including meningiomas, gliomas and pituitary tumors. To ensure precise segmentation of the tumor regions, the preprocessing phase incorporates advanced mask alignment techniques. This preprocessed dataset has been used to evaluate the performance of the deep learning models for brain tumor detection and classification. From the numerical results of YOLOv5, it was noticed that a recall score of 0.905 for box detection and 0.906 for mask segmentation, with a precision score of 0.94 and 0.936, respectively. At an IoU threshold of 0.5, both box detection and mask segmentation achieve a mAP of 0.947, whereas, at an IoU threshold of 0.5 to 0.95, they achieve mAPs of 0.666 and 0.657, respectively. In comparison, YOLOv7 exhibits strong performance with box detection accuracy of 0.936 and a mask segmentation accuracy of 0.935. The recall score are 0.904 for box detection and mask segmentation is 0.903. Notably, the mAP result at the IoU threshold of 0.5 are 0.94 for box detection and mask segmentation is 0.941. Over the broader IoU spectrum of 0.5 to 0.95, the mAP was 0.677 for box detection and 0.659 for mask segmentation. To underscore the novelty of the approach, the performance of the proposed framework is systematically compared with established methods such as RCNN, Faster RCNN, and Mask RCNN.

The current methods, while in use, continue to grapple with accuracy and effectiveness concerns. It is imperative to establish dependable solutions capable of distinguishing and categorizing people according to their assistive devices to tackle these issues. People with disabilities, such as those experiencing paralysis, limb deficiencies, or amputations, may encounter issues related to discrimination and inadequate support. Hence, this research was undertaken to detect and track people with conditions like paralysis, limb deficiency (Amelia), or amputation among the differently-abled population. Earlier investigations have predominantly focused on recognizing people and their mobility aids, utilizing a variety of methods such as Fast R-CNN, Faster R-CNN, RGB or RGB-D cameras, Kalman filters, and hidden Markov models. Modern deep learning models, including YOLO (You Only Look Once) and its variations, have gained substantial acceptance in current applications owing to their distinctive architectural designs and performance attributes. In this study, a substantial dataset comprising 4,300 images and 8,447 labels spanning five distinct categories is employed to assess the efficacy of YOLOv8, YOLOv5, and YOLOv7 models in the identification of people with disabilities. The evaluation findings show that YOLOv8, which achieved an overall precision of 0.907, performs better than both YOLOv5 (precision: 0.885) and YOLOv7 (precision: 0.906). Notably, YOLOv8 has the best wheelchair detection precision (0.998). Furthermore, YOLOv8 outperforms YOLOv5 (recall: 0.887) and YOLOv7 (recall: 0.925) in terms of recall performance (recall: 0.943). YOLOv8 achieves the greatest mean average accuracy (mAP@.5) value of 0.951, followed by YOLOv5 (mAP@.5: 0.942), and YOLOv7 (mAP@.5: 0.954). In a similar vein, of the three models, YOLOv8 has the best performance (mAP@.5:.95: 0.713). The analysis of detection time also shows that YOLOv8 performs best, processing 5,597 frames in just 5.9 milliseconds and achieving a remarkable frame rate of 169.49 frames per second.

Sugarcane smut, caused by the fungus Sporisorium scitamineum (Sydow), significantly affects sugarcane crops worldwide. Infected plants develop whip-like structures known as sori. Significant variations in these whip lengths are commonly observed, but the physiological and molecular differences causing these morphological differences remain poorly documented. To address this, we employed conventional microbe isolation, metagenomic, and metabolomic techniques to investigate smut-infected sugarcane stems and whips of varying lengths. Metagenomics analysis revealed a diverse fungal community in the sugarcane whips, with Sporisorium and Fusarium genera notably present (>1%) in long whips. Isolation techniques confirmed these findings. Ultra-performance liquid chromatography analysis (UHPLC-MS/MS) showed high levels of gibberellin hormones (GA3, GA1, GA4, GA8, and GA7) in long whips, with GA4 and GA7 found exclusively in long whips and stems. Among the prominent genera present within long whips, Fusarium was solely positively correlated with these gibberellin (GA) hormones, with the exception of GA8, which was positively correlated with Sporisorium. KEGG enrichment analysis linked these hormones to pathways like diterpenoid biosynthesis and plant hormone signal transduction. These findings suggest that Fusarium may influence GA production leading to whip elongation. Our study reveals fungal dynamics and gibberellin responses in sugarcane smut whips. Future research will explore the related molecular gibberellin synthesis mechanisms.

ABSTRACTSugarcane is a critical sugar and bioenergy crop in China. However, numerous factors, including root rot disease, hamper its yield. Root rot disease is a severe agricultural issue, reducing yield and threatening sustainable crop production. The current study aimed to explore the fungal community structure, identify and characterize the primary pathogen for sugarcane root rot in Guangzhou, China. Eighty-nine samples of sugarcane root, stalk, rhizosphere soil, and irrigation water were collected from five sites in Guangzhou, China. Subsequently, 276 fungal strains were isolated to identify the primary pathogens. The five most common genera identified were Penicillium, Fusarium, Gongronella, Trichoderma, and Cladosporium. Fusarium was more prevalent in the infected soil samples than in healthy ones. Pathogenic assays of the strains revealed that the strain GX4-46 caused 80% of the disease. The strain was confirmed as Fusarium commune through phylogenetic and genome sequence analysis. Rhizosphere soil samples from different regional crops were collected to better understand the fungal community structure and the primary pathogen. We observed a significant presence of Fusarium in irrigation water, indicating that the root rot disease could originate from the irrigation water and then spread as a soil-borne disease. This research is pioneering and one of the most comprehensive investigations on the occurrence and prevalence of sugarcane root rot disease. This study will serve as a reference for expanding the sugarcane industry and a foundation for further exploration and control of root rot.IMPORTANCESugarcane, a significant economic crop, faces challenges due to root rot pathogens that accumulate each year in plants and soil through ratoon planting. This disrupts soil microbial balance and greatly impedes sugarcane industry growth. Symptoms range from wilting and yellowing leaves to stunted growth and reduced seedling tillers. The rhizosphere microbiota plays an important role in plant development and soil health. Little is known about root rot fungal community structure, especially in sugarcane. Here, we focused on exploring the main causative pathogen of root rot in the area alongside a detailed survey of the rhizosphere soil of different severity sugarcane cultivars and rotation crops of the region. To validate the findings, we also investigated the irrigation water of the area. Our study revealed Fusarium commune as the causative pathogen of root rot in the area, primarily originating from water and later as soil-borne. Using Trichoderma can control the disease effectively.

Soil erosion is a natural geomorphic process with the potential to damage fertile land. In this study, soil erosion risk is spatially estimated in District Swat by applying Revised Universal Soil Loss Equation (RUSLE). The RUSLE parameters that trigger soil erosion including rainfall erosivity, soil erodibility, topography, cover management, and support practices were derived from monthly rainfall data obtained from Pakistan Metrology Department, soil texture map from Soil Survey of Pakistan and Digital Soil Map of the World database, land use land cover extracted from SPOT 5 satellite image, whereas slope and digital terrain extracted from Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). It was found from the analysis that out of the total reported area, 34.5% falls in the area affected by very high soil erosion. The results of spatial pattern and erosion proneness of the study region have been further classified into very low (45%), low (8.5%), moderate (7%), high (5.2%), and very high zones (34.5%). The results show that the study area requires effective mitigation strategies to curtail the precious soil. This study has the potential to assist the decision makers and planners for soil loss risk reduction. HIGHLIGHTS Soil offers a wide range of crucial ecosystem services.; But the deterioration of land and soils has increased rapidly.; In the study area, the intensity of erosion is relatively high.; In this study, an assessment has been made of the soil erosion in the study area which is unique of its kind because no such assessment has been made before.; This paper will be the base for further research studies in the entire basin.;

Abstract Stunted growth is an emerging global challenge affecting children under the age of 5 years in low- and middle-income countries. Despite such a high global prevalence of stunting, the mechanism of pathogenesis and the role of associated gut microbiota is poorly understood. The present study was designed to investigate the association of pathogenic strains of E. coli with the residential gut microbiota of stunted growth children. A total of 64 stool sample were collected from children aged ≤ 5 years, and were processed for isolation and molecular characterization of diarrheagenic E. coli. Selected stool samples (n = 39 including three normal controls) were then analysed for microbial community profiling using 16S ribosomal RNA (rRNA) gene sequencing. Furthermore, associations between changes in the microbiota in the presence of different E. coli strains was explored. Pathotyping of the isolated E. coli (n = 64) has shown that 39.68% belonged to one of the five pathotypes of E. coli whilst the remaining ones were non-typeable. Amongst the different pathotypes, EPEC was found to be the most prevalent (52%; n = 13), followed by EAEC (20%; n = 5), EIEC (12%; n = 3), EHEC (8%; n = 2) and ETEC 2 (8%; n = 2). Phylogrouping analysis has shown that majority of the strains belonged to B2 (28.12%). Microbial diversity is shown to be significant and varied when the samples are organized under the recovered phylogroups. Moreover, based on predictive metabolism, the colonization of these strains were found to be significantly associated with energy utilization pathways such as Denovoprine-2 and glyoxylate-by. Differential analysis has shown that Escherichia-Shigella and Enterococcus were altered for the children with stunted growth.

Abstract Background Relapsed or refractory Hodgkin lymphoma (R/R HL) is a challenging disease with limited treatment options beyond brentuximab vedotin and checkpoint inhibitors. Herein we present the time‐trend analysis of R/R HL patients who received allogeneic hematopoietic cell transplantation (allo‐HCT) at our center from 2001–2017. Methods The patients were divided into two distinct treatment cohorts: era1 (2001–2010), and era2 (2011–2017). The primary endpoint was overall survival (OS). Secondary endpoints included progression‐free survival (PFS), non‐relapse mortality (NRM), and cumulative incidence of acute and chronic graft versus host disease (GVHD). Results Among the 51 patients included in the study, 29 were in era1, and 22 were in era2. There was decreased use of myeloablative conditioning in era2 (18% vs. 31%) compared to era1 and 95% of patients in era2 previously received brentuximab Vedotin (BV). Haploidentical donors were seen exclusively in era2 (0% vs. 14%) and more patients received alternative donor transplants (7% vs. 32%) in era2. The 4‐year OS (34% vs. 83%, p

Sugarcane is a globally significant crop for sugar and energy production, and developing high light-efficiency sugarcane varieties is crucial for enhancing yield and quality. However, limited research is available on the screening of sugarcane germplasm with high photosynthetic efficiency, especially with different leaf positions. The present study, conducted in Guangxi, China, aimed to analyze the photosynthetic characteristics of 258 sugarcane varieties at different leaf positions over three consecutive years in field experiments. The results showed significant differences in photosynthetic characteristics among genotypes, years, and leaf positions. Heritability estimates for various photosynthetic parameters ranged from 0.76 to 0.88. Principal component analysis revealed that the first three principal components accounted for over 99% of the cumulative variance. The first component represented photosynthetic efficiency and light utilization, the second focused on electron transfer and reaction center status, and the third was associated with chlorophyll content. Cluster and discriminant analysis classified sugarcane genotypes into three categories: high photosynthetic efficiency (HPE) with 86 genotypes, medium photosynthetic efficiency (MPE) with 60 genotypes, and low photosynthetic efficiency (LPE) with 112 genotypes. Multi-year trials confirmed that HPE sugarcane genotypes had higher single-stem weight and sucrose content. This study provides valuable insights into the photosynthetic physiological characteristics of different sugarcane varieties, which can contribute to further research regarding high yields and sugar breeding.

The Cairns-distributed electrons and positive ions in a plasma made up of a negative dust fluid are taken into account to examine the presence of arbitrary amplitude dust-acoustic solitons. It has previously been noted that nonthermal ions and thermal electrons generate both compressive and rarefactive solitons. In this paper, we noticed that nonthermal electrons together with nonthermal ions are responsible for producing the rarefactive solitons. It is found that the Sagdeev potential strongly depends on plasma parameters, such as nonthermal index α and Mach number, which, in turn, influence the Sagdeev potential and solitons significantly. We also found that the critical match number and height of soliton increase with the nonthermal parameter α. We further note that the Sagdeev potential as a function of potential φ becomes more negative and the amplitude of the soliton also enhances as the value of Mach number rises. It is concluded that the model presented here based on nonthermal ions and electrons in a negative dust fluid provides a worthy interpretation for electrostatic solitons observed in space plasmas.

Background: Giant segmental dilatation of jejunum (SDJ) is rare in small infants where it often presents with intestinal obstruction. Occasionally, the giant SDJ may twist resulting in volvulus. Case Presentation: A 1-month-old female infant presented with intestinal obstruction. At surgery, isolated giant segmental dilatation of the jejunum causing volvulus of the bowel was found. The gut was viable. The SDJ was excised and jejuno-jejunal anastomosis was performed. Ladd’s procedure was also performed for the associated malrotation. Postoperative recovery remained uneventful. Conclusion: Giant SDJ is a rare entity, rarer still is its presentation with volvulus secondary to its twist. Early diagnosis and prompt management result in a good outcome.

Objectives: This study aimed to analyze the general public’s awareness of medicine information, safety, and adverse drug reactions in Quetta, Pakistan.Methods: A cross-sectional descriptive study was conducted using random sampling from April 2020 to April 2021 in Quetta. Samples were collected from respondents who met the inclusion criteria and had visited community pharmacies. The analysis was done using SPSS version 23. Bivariate and multivariate analyses were performed to assess factors associated with good knowledge.Results: Multivariate analysis revealed that purchase on prescription was a determining factor of knowledge regarding knowledge of pharmaceutical products and their provided information, medicines usage and safety, and Medication ADRs. Patients who bought medicines on prescriptions were more likely to have better knowledge. Patients having education were more likely to have better knowledge.Conclusion: Public awareness about medicine information, safety, and the information provided by manufacturers is crucial to ensuring that patients have access to accurate information about their medications and can make informed decisions about their health. Healthcare providers and regulatory bodies must work together to improve access to information and promote safe medication practices.

Ratooning in sugarcane often leads to soil problems such as degradation, acidification, and soil-borne diseases that negatively impact agriculture output and sustainability. Understanding the alteration in bacterial communities, activities, and their diversity connected to the plant and soil under consecutive ratooning still needs to be clarified. To address this gap, multidisciplinary approaches such as Illumina sequencing and measurement of soil nutrients and enzymes were used in this study to analyze soil samples in a field with three consecutive ratooning sugarcane crops. The results revealed a decline in crop yield and significant changes (P < 0.05) in soil nutrients and bacterial diversity. Ratooning resulted in an acidic environment that potentially affected soil nutrients and enzyme activity responsible for the cycling of carbon, nitrogen, and phosphorous. Non-metric dimensional scaling (NMDS) confirmed the effect of ratooning on soil attributes. Moreover, a positive correlation between soil physiochemical properties and soil enzymes was observed. Alpha diversity indices indicated greater bacterial diversity in ratooning sugarcane. Bacterial diversity varied throughout the ratooning crop, and significant (P < 0.05) changes in the relative abundance of specific phyla were observed. For example, the relative abundance of Proteobacteria was decreased, and Acidobacteria was increased. Furthermore, the relative abundance of bacterial phyla was strongly correlated with soil attributes (enzymes and nutrients). Additionally, ratooning results in the depletion or enrichment of important agriculture microbial genera such as Sphingomonas, Burkholderia, and Acidothermus (P < 0.05), respectively. In conclusion, ratooning led to soil acidification, decreased fertility, and altered microbial structure and activity. Thus, restraining soil acidity by means of liming or biofertilizers to maintain soil nutrients, enzymatic activities, and microbial structure could benefit plants and soil to help create a long-term eco-friendly sugarcane cropping system.

Classification is a common problem in various fields of life, and the key challenging task in data mining. The primary objective of the classification process is to classify the given dataset in a defined class label for all data. Many research papers widely used classification in the medical sector. Various researches have been carried out to classify medical data using different techniques, such as High Order Neural Network (HONN) combined with Back-Propagation Neural Network (BPNN) as a learning algorithm. Due to the increased data complexity, the back-propagation algorithm faced problems of slow convergence. The Back-Propagation (BP) using the gradient descent technique has the possibility of getting stuck in local minima. So, the BP algorithm may cause difficulties in finding the global minima of the error function. This paper proposed a high-order Functional Link Neural Network (FLNN). The proposed FLNN model is integrated with a metaheuristic-based searching algorithm called Accelerated Particle Swarm Optimization (APSO). The performance of the proposed Accelerated Particle Swarm Optimization Functional Link Neural Network (APSOFLNN) model is validated with various medical datasets and compared to traditional techniques such as Accelerated Particle Swarm Optimization Functional Link Back-Propagation (APSOFLBP), and Artificial Bee Colony Functional Link Neural Network (ABCFLNN). The simulation results showed that the proposed APSOFLNN algorithm for the used benchmarked datasets shows good results in terms of the mean square error (MSE) and accuracy in comparison to the traditional techniques.

Image denoising is a vital pre-processing phase, used to refine the image quality and make it more informative. Many image-denoising algorithms have been proposed with their own pros and cons. This paper presents a comprehensive study of the median filter and its different variants to reduce or remove the impulse noise from gray scale images. These filters are compared with respect to their functionality, time complexity and relative performance. For performance evaluation of the existing algorithms, extensive MATLAB based simulations have been carried out on a set of images. For benchmarking the relative performance, we have used Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE), Universal Image Quality Index (UQI), Structural Similarity Index (SSIM) and Edge-strength Similarity (ESSIM) as quality assessment metrics. The Extended median filter (EMF) and Modified BDND are best in terms of relative statistical ratios and pleasant visual results where IAMF is having the best time complexity among existing algorithms.

Abstract Background Ratooning in sugarcane is a crucial strategy for ensuring the long-term sustainability of the sugarcane industry. Knowledge gap relating to the interaction between rhizosphere microbiome and ratooning crop, particularly the impact of different sugarcane cultivars on the rhizosphere microbiome in consecutive ratooning, requires additional research. The response of two different sugarcane cultivars, viz ZZ-1 and ZZ-13, were evaluated in consecutive ratooning towards the rhizosphere microbial community and cane morphological characters. Results Significant changes in the rhizosphere microbiome were observed in the second ratooning over the years. Several important genera were observed in high abundance during the second ratooning, including Burkholderia, Sphingomonas, Bradyzhizobium, and Acidothermus. Cultivar ZZ-13 caused more alterations in the rhizosphere microbiome than ZZ-1, resulting in a more favorable rhizosphere environment for sugarcane growth. The genotypes also varied in terms of nutrients and enzyme activity over the years. There were significant differences between the genotypes and year for number of stalks and yield was significant for genotypes, years and genotype × year. Conclusion This finding will help to understand thorough interactions between rhizosphere microorganisms and ratoon sugarcane and lay the foundation for promoting and maximizing yield as far as possible. In the future, this work can serve as guidance in sugarcane husbandry, mainly in Guangxi, China.

Introduction: During the pandemic, sedentary behaviors, anxiety, and boredom caused by confinement at home could affect lifestyle patterns, degrade diet quality, and promote overconsumption. This cross-sectional study aimed to identify the impact of lockdowns on lifestyle behaviors among Pakistan's population and changes in the nutritional and eating patterns. Materials and Methods: This is an online, questionnaire-based, cross-sectional study. The study collected demographic information, dietary habits, and lifestyle patterns. Descriptive and summary statistics were used to describe data, and Chi-square or Fisher's exact tests were used for associations. Results: Most respondents were females (82.1%) aged 18–29 years (98.1%). 90.3% of them were students. 16.0% were overweight pre-pandemic, which increased to 20.0% during the pandemic. The majority ate more during the pandemic (P < 0.001). 47.9% reported a physical activity duration of 0.5–2 h pre-pandemic, and 50.6% reported decreased physical activity during the pandemic, with increased food intake (P = 0.007). Screen time was

Fathul Munhim is a great work in the area of Hadith Sciences and its Explanations which was initiated by a Renowned Scholar Allama Shabbir Ahmad Usmani. “Due to demise of the Author that was accomplished by a well-known scholar of this age. Mufti Muhammad Taqi Usmani, who is famous for his Contributions to Fiqh, Hadith, Islamic Banking & Finance, etc. his explanatory work in Hadith literature has been appreciated and acknowledged by great scholars. This article elaborates and analysis his different methods and styles in Hadith explanations regarding lexical and literal meaning of Hadith words, juristic opinions and arguments preferred opinions and arguments preferred opinions “Clarifications of ambiguities and his explanation of many modern & contemporary issues".

Abstract Background Plant microbiomes and soil are bridged by rhizobacteria, maintaining and improving plant health and growth in different aspects. This study was conducted in the field station of the Guangxi University, Fusui, China. We investigated soil nutrients, root morphology and rhizosphere bacterial composition, and community structures in 18 sugarcane genotypes concerning sugar content under the same environmental condition. Results Most of the rhizosphere microbiomes of these genotypes exhibited similar bacterial compositions. However, the evaluated genotypes harbored a significant effect and difference in the abundance of operational taxonomic units and bacterial composition in the rhizosphere compartments. Alpha diversity analysis on the rhizosphere microbiome showed a significant difference in the bacterial diversity (Shannon index, p

Cancer is one of the most prevalent diseases worldwide. The most prevalent condition in women when aberrant cells develop out of control is breast cancer. Breast cancer detection and classification are exceedingly difficult tasks. As a result, several computational techniques, including k-nearest neighbor (KNN), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), and genetic algorithms, have been applied in the current computing world for the diagnosis and classification of breast cancer. However, each method has its own limitations to how accurately it can be utilized. A novel convolutional neural network (CNN) model based on the Visual Geometry Group network (VGGNet) was also suggested in this study. The 16 layers in the current VGGNet-16 model lead to overfitting on the training and test data. We, thus, propose the VGGNet-12 model for breast cancer classification. The VGGNet-16 model has the problem of overfitting the breast cancer classification dataset. Based on the overfitting issues in the existing model, this research reduced the number of different layers in the VGGNet-16 model to solve the overfitting problem in this model. Because various models of the VGGNet, such as VGGNet-13 and VGGNet-19, were developed, this study proposed a new version of the VGGNet model, that is, the VGGNet-12 model. The performance of this model is checked using the breast cancer dataset, as compared to the CNN and LeNet models. From the simulation result, it can be seen that the proposed VGGNet-12 model enhances the simulation result as compared to the model used in this study. Overall, the experimental findings indicate that the suggested VGGNet-12 model did well in classifying breast cancer in terms of several characteristics.

Assessment of organic carbon content (TOC) by geophysical logs has been a challenging task in the formation evaluation of shale gas. This research is conducted to estimate the unconventional hydrocarbon (shale-gas) potential of Talhar Shale in the Southern Indus Basin (SIB), Pakistan. In this study, total organic carbon content (%) was estimated through well logs by different methods and then correlated with well cuttings/core data to determine the best method for estimation of TOC content especially when well cuttings/core data are not available. The Talhar Shale’s thermal maturity, as well as the organic content, were assessed from geochemical analyses. Talhar Shale of Dangi-01 well has good to very good source potential whereas Chak7A-01 well has fair-good. According to Ven Krevalen cross-plot, Talhar Shale of Dangi-01 well has type III kerogen; it can only produce gas while Chak7A-01 has type II/III kerogen which produces both oil and gas. The TOC was estimated using two methods i.e., Schmoker’s and Hester’s and Multivariate Fitting methods. The estimated TOC is then correlated with well cuttings data and concluded that the Multivariate Fitting method is selected as an optimized method for estimation of TOC because it shows strong correlation values of 0.93 and 0.91 in both wells respectively for Talhar Shale SIB, Pakistan.

Horizontal-axis wind turbines are the most popular wind machines in operation today. These turbines employ aerodynamic blades that may be oriented either upward or downward. HAWTs are the most common non-conventional source of energy generation. These turbine blades fail mostly due to fatigue, as a large centrifugal force acts on them at high rotational speeds. This study aims to increase a turbine’s service life by improving the turbine blades’ fatigue life. Predicting the fatigue life and the design of the turbine blade considers the maximum wind speed range. SolidWorks, a CAD program, is used to create a wind turbine blade utilizing NACA profile S814. The wind turbine blade’s fatigue life is calculated using Morrow’s equation. A turbine blade will eventually wear out due to several forces operating on it. Ansys software is used to analyze these stresses using the finite element method. The fatigue study of wind turbine blades is described in this research paper. To increase a turbine blade’s fatigue life, this research study focuses on design optimization. Based on the foregoing characteristics, an improved turbine blade design with a longer fatigue life than the original one is intended in this study. The primary fatigue parameters are the length of a chord twist angle and blade length. The experimental data computed with the aid of a fatigue testing machine are also used to validate the numerical results, and it is found that they are very similar to one another. By creating the most effective turbine blades with the longest fatigue life, this research study can be developed further. The most effective turbine blades with the longest fatigue life can be designed to further this research investigation.

Different parts of Ficus religiosa are the common components of various traditional formulations for the treatment of several blood disorders. The new-fangled stem buds’ powder was extracted with 80% ethanol and successively fractionated by chloroform and methanol. Chloroform and methanol fractions of Ficus religiosa (CFFR and MFFR) were tested for antiplatelet, antithrombotic, thrombolytic, and antioxidant activity in ex vivo mode. The MFFR was particularly investigated for GC-MS and toxicity. The antiplatelet activity of the CFFR, MFFR, and standard drug aspirin at 50 μg/mL was 54.32%, 86.61%, and 87.57%, and a significant delay in clot formation was noted. CFFR at different concentrations did not show a significant effect on the delay of clot formation, antiplatelet, and free radical scavenging activity. The most possible marker compounds for antiplatelet and antioxidant activity identified by GC-MS in the MFFR are salicylate derivatives aromatic compounds such as benzeneacetaldehyde (7), phenylmalonic acid (13), and Salicylic acid (14), as well as Benzamides derivatives such as carbobenzyloxy-dl-norvaline (17), 3-acetoxy-2(1H)-pyridone (16), and 3-benzylhexahydropyrrolo [1,2-a] pyrazine-1,4-dione (35). A toxicity study of MFFR did not show any physical indications of toxicity and mortality up to 1500 mg/kg body weight and nontoxic up to 1000 mg/kg, which is promising for the treatment of atherothrombotic diseases.

Conventional farming systems are highly reliant on chemical fertilizers (CFs), which adversely affect soil quality, crop production and the environment. One of the major current challenges of current agriculture is finding ways to increase soil health and crop yield sustainably. Manure application as a substitute for CF is an alternative fertilization strategy for maintaining soil health and biodiversity. However, little is known about the complex response of soil bacterial communities and soil nutrients to manure and CFs application. This study reports the response of soil nutrients, rice yield, and soil microbial community structure to 2 years of continuous manure and CFs application. The study consisted of six treatments: no N fertilizer control (Neg-Con); 100% CF (Pos-Con); 60% cattle manure (CM) + 40% CF (High-CM); 30% CM + 70% CF (Low-CM); 60% poultry manure (PM) + 40% CF (High-PM), and 30% PM + 70% CF (Low-PM). We used high-throughput sequencing of 16S ribosomal RNA gene amplicons to characterize the soil bacterial communities. Results revealed that the addition of manure significantly altered the soil bacterial community composition and structure; and enhanced the relative abundance of phyla Proteobacteria, Chloroflexi, Firmicutes, Acidobacteria, and Planctomycetes. Organic fertilizer treatments, particularly high CM and PM had the highest measured soil bacterial diversity of all treatments. Similarly, integrated application of manure and CFs increased the soil biochemical traits [i.e., pH, total N (TN), soil organic C (SOC), microbial biomass N (MBN), and microbial biomass C (MBC)] and rice grain yield. Average increases in SOC, TN, MBN, and MBC were 43.66, 31.57, 24.34, and 49.45%, respectively, over the years in the High-PM compared with Pos-Con. Redundancy analysis showed that the dominant bacteria phyla were correlated with soil pH, SOC, TN, and microbial biomass, but the relative abundance of Proteobacteria was strongly correlated with environmental factors such as soil pH, SOC, TN, and MBC. We employed a structural equation model to examine the relationship between microbial biomass, soil nutrients and grain yield among treatments. This analysis supported the hypothesis that soil nutrient content and availability directly affect rice grain yield while soil bacteria indirectly affect grain yield through microbial biomass production and nutrient levels. Overall, the findings of this research suggest that the integrated application of CF and manure is a better approach for improving soil health and rice yield.

ObjectivesThis study was conducted to evaluate COVID-19 vaccine booster dose willingness and identify predictors and factors of willingness and hesitance in the vaccinated population of Pakistan.MethodsA cross-sectional web-based survey was undertaken between January and February 2022 to highlight the public perceptions regarding the COVID-19 booster dose and evaluate the willingness to get the additional dose. Demographic information and booster dose willingness were recorded through the questionnaire. Additionally, a 5-point Likert scale was employed to explore fears and beliefs regarding COVID-19 vaccinations. Univariate and multivariate regression was performed to identify booster dose willingness and hesitance factors.ResultsOf the 787 respondents, 69.6% were females, 75.3% fell in the 18–30 years age group, 53.5% were university students or had a Bachelor's degree. Overall, a 77.8% booster dose willingness was reported. Participants showed absence or low fear levels associated with a booster dose (47.3%). 60.1% agreed it was safe to receive an additional vaccine dose, with 44.1% agreeing that boosters are effective against coronavirus variants. Independent predictors of willingness included the absence of comorbidities, whereas not being willing to pay for the booster dose was a predictor of hesitance.ConclusionThis study showed a suboptimal willingness level of booster dose uptake among the vaccinated Pakistani population. Public health policymakers must undertake necessary awareness campaigns to strategize vaccination drives and dispel myths.

Abstract Background Systemic light chain (AL) amyloidosis is a clonal plasma‐cell neoplasm that carries a poor prognosis. Although AL amyloidosis and Multiple Myeloma (MM) can co‐exist and share various cytogenetic chromosomal abnormalities, little is known about Fluorescent in situ hybridization (FISH) and its prognostic relevance in AL amyloidosis. Aim: The study aims to evaluate the most prevalent FISH cytogenetic abnormalities in AL patients as independent prognostic factors, and assess the impact of cytogenetics on the survival of high‐risk cardiac AL patients. Materials & Methods This retrospective study reviewed 113 consecutive AL patients treated at The Ohio State University (OSU). Patients were divided into subgroups based on FISH data obtained within 90 days of diagnosis. Hyperdiploidy was defined as trisomies of at least 2 chromosomal loci. Primary endpoints were progression free survival (PFS) and overall survival (OS). Kaplan Meier curves were used to calculate PFS and OS. The log‐rank test and Cox proportional hazard models were used to test the equality of survival functions and further evaluate the differences between groups. Results FISH abnormalities were detected in 76% of patients. Patients with abnormal FISH trended toward lower overall survival (OS) (p=0.06) and progression free survival (PFS) (p=0.06). The two most prevalent aberrations were translocation t(11;14) (39%) and hyperdiploidy‐overall (38%). Hyperdiploidy‐overall was associated with worsening PFS (p=0.018) and OS (p=0.03), confirmed in multivariable analysis. Patients with del 13q most frequently had cardiac involvement (p=0.006) and was associated with increased bone marrow plasmacytosis (p=0.02). Cardiac AL patients with no FISH abnormalities had much improved OS (p=0.012) and PFS (p=0.018) Conclusions Our findings ultimately reveal the association of hyperdiploidy on survival in AL amyloidosis patients, including the high‐risk cardiac AL population.

Biochar is an important soil amendment that can enhance the biological properties of soil, as well as nitrogen (N) uptake and utilization in N-fertilized crops. However, few studies have characterized the effects of urea and biochar application on soil biochemical traits and its effect on paddy rice. Therefore, a field trial was conducted in the early and late seasons of 2020 in a randomized complete block design with two N levels (135 and 180 kg ha−1) and four levels of biochar (0, 10, 20, and 30 t ha−1). The treatment combinations were as follows: 135 kg N ha−1 + 0 t B ha−1 (T1), 135 kg N ha−1 + 10 t B ha−1 (T2), 135 kg N ha−1 + 20 t B ha−1 (T3), 135 kg N ha−1 + 30 t B ha−1 (T4), 180 kg N ha−1 + 0 t B ha−1 (T5), 180 kg N ha−1 + 10 t B ha−1 (T6), 180 kg N ha−1 + 20 t B ha−1 (T7) and 180 kg N ha−1 + 30 t B ha−1 (T8). The results showed that soil amended with biochar had higher soil pH, soil organic carbon content, total nitrogen content, and mineral nitrogen (NH4+-N and NO3−-N) than soil that had not been amended with biochar. In both seasons, the 20 t ha−1 and 30 t ha−1 biochar treatments had the highest an average concentrations of NO3–-N (10.54 mg kg−1 and 10.25 mg kg−1, respectively). In comparison to soil that had not been treated with biochar, the average activity of the enzymes urease, polyphenol oxidase, dehydrogenase, and chitinase was, respectively, 25.28%, 14.13%, 67.76%, and 22.26% greater; however, the activity of the enzyme catalase was 15.06% lower in both seasons. Application of biochar considerably increased the abundance of ammonia-oxidizing bacteria (AOB), which was 48% greater on average in biochar-amended soil than in unamended soil. However, there were no significant variations in the abundances of ammonia-oxidizing archaea (AOA) or nitrite-oxidizing bacteria (NOB) across treatments. In comparison to soil that had not been treated with biochar, the average N content was 24.46%, 20.47%, and 19.08% higher in the stem, leaves, and panicles, respectively. In general, adding biochar at a rate of 20 to 30 t ha−1 with low-dose urea (135 kg N ha−1) is a beneficial technique for improving the nutrient balance and biological processes of soil, as well as the N uptake and grain yield of rice plants.

The present study investigated the characteristics of carbonaceous species in an urban background site. Real-time measurements of inorganic (sulfate, nitrate, ammonium, chloride, and black carbon [BC]) and organic submicron aerosols (OA) were carried out at the urban background site of Vilnius, Lithuania, during January–February 2014. An aerosol chemical speciation monitor (ACSM, Aerodyne Research Inc., Billerica, MA, USA) and co-located 7-λ aethalometer (AE-31, Magee Scientific, Berkeley, CA, USA) were used to analyze the chemical compositions, sources, and extinction characteristics of the PM1. Extremely contrasting meteorological conditions were observed during the studied period due to the transition from moderately cold (~2 °C) conditions to extremely cold conditions with a lowest temperature of −25 °C; therefore, three investigation episodes were considered. The identified periods corresponded to the transition time from the moderately cold to the extremely cold winter period, which was traced by the change in the average temperature for the study days of 1–13 January, with T = −5 °C and RH = 92%, in contrast to the period of 14–31 January, with T = −14 °C and RH = 74%, and the very short third period of 1–3 February, with T = −8 °C and RH = 35%. On average, organics accounted for the major part (53%) of the non-refractory submicron aerosols (NR-PM1), followed by nitrate (18%) and sulfate (9%). The source apportionment results showed the five most common OA components, such as traffic and heating, to be related to hydrocarbon-like organic aerosols (HOAtraffic and HOAheating, respectively), biomass-burning organic aerosols (BBOA), local organic aerosol (LOA), and secondary organic aerosol (SOA). Traffic emissions contributed 53% and biomass burning 47% to the BC concentration level. The highest BC and OA concentrations were, on average, associated with air masses originating from the southwest and east–southeast. Furthermore, the results of the PSCF and CWT methods indicated the main source regions that contributed the most to the BC concentration in Vilnius to be the following: central–southwestern and northeastern Poland, northwestern–southwestern and eastern Belarus, northwestern Ukraine, and western Russia. However, the potential sources of OA were widely distributed.

T-Cell malignancies are a group of heterogeneous disorders composed of primary cutaneous T-cell lymphomas (CTCLs), peripheral T-cell lymphomas (PTCLs), and T-cell leukemias, including T-cell large granular lymphocytic leukemia (T-LGLL). Cases of patients with combined T-cell malignancies and plasma cell dyscrasias (PCD) are reported in the literature, but these are mostly limited to case reports or small case series with

Background and ObjectivesDuring the pandemic, the growing influence of social media, accessibility of over-the-counter medications, and fear of contracting the virus may have led to self-medication practices among the general public. Medical students are prone to such practices due to relevant background knowledge, and access to drugs. This study was carried out to determine and analyze the prevalence of self-medication practices among medical students in Pakistan.Materials and MethodsThis descriptive, cross-sectional study was conducted online in which the participants were asked about the general demographics, their self-medication practices and the reasons to use. All participants were currently enrolled in a medical college pursuing medical or pharmacy degree. Non-probability sampling technique was used to recruit participants.ResultsA total of 489 respondents were included in the final analysis. The response rate was 61%. Majority of the respondents were females and 18–20 years of age. Self-medication was quite prevalent in our study population with 406 out of 489 individuals (83.0%) were using any of the drugs since the start of pandemic. The most commonly utilized medications were Paracetamol (65.2%) and multivitamins (56.0%). The reasons reported for usage of these medications included cold/flu, or preventive measures for COVID-19. The common symptoms reported for self-medication included fever (67.9%), muscle pain (54.0%), fatigue (51.7%), sore throat (46.6%), and cough (44.4%). Paracetamol was the most commonly used drug for all symptoms. Female gender, being in 3rd year of medical studies, and individuals with good self-reported health were found more frequent users of self-medication practices.ConclusionOur study revealed common self-medication practices among medical and pharmacy students. It is a significant health issue especially during the pandemic times, with high consumption reported as a prevention or treating symptoms of COVID-19.

Minimizing the use of chemical fertilizers and investigating an appropriate ecofriendly level of nitrogen fertilizer is the key to sustainable agriculture. Sugarcane is the main cash crop of China, especially in the Guangxi region. Information regarding the effect of different nitrogen levels on sugarcane rhizosphere microbiota is still limited. In this study, we evaluated the effect of four different levels of nitrogen fertilizers on rhizosphere bacterial composition using high throughput sequencing, along with soil physiochemical properties, sugarcane agronomic and yield performance. The four treatment combinations were CK (no fertilizers), L (Low, 100 kg ha–1), M (Medium, 150 kg ha–1), and H (High, 200 kg ha–1). The results showed that M nitrogen application significantly altered the rhizosphere bacterial community, soil properties, and sugarcane yield. The richness and evenness of the bacterial community were higher in M treatment than CK. In M treatment important bacterial phyla Acidobacteria and Proteobacteria increased by 47 and 71%, respectively; and at genus level, Acidothermus and Bradyrhizobium increased by 77.2 and 30.3%, respectively, compared to CK. Principal component analysis (PCA) and cluster analysis further confirmed the level of differences among the treatments. The PCA analysis explained 80% of the total variation among the treatments. Spearmen correlation heatmap showed that environmental factors such as pH, AP (available phosphorous), AK (available potassium), and SCAT (soil catalase) were the key factors impacting sugarcane rhizosphere microbiome composition. The H and L nitrogen application alter the bacterial community and sugarcane performance but the M nitrogen application appears to be ecofriendly, productive, and an appropriate nitrogen application rate that could be further used in the Guangxi region.

Background and ObjectivesThe purpose of this study was to draw the attention toward the implications of COVID-19 and the related restrictions imposed worldwide especially in Pakistan. The primary objective was to highlight the levels of psychological distress, anxiety, family violence, suicidality, and well-being due to COVID-19 and the secondary objective was to associate it to social demographic factors.Materials and MethodsIt is designed as a cross-sectional study by employing an online questionnaire in the English language and obtaining responses using a snowball sampling technique. We used three validated measures including Kessler Psychological Distress Scale (K10), Generalized Anxiety Disorder (GAD-7) index and World Health Organization Well-Being Index (WHO-5).ResultsA sample of 420 participants was recruited from across Pakistan, with most participants were females (79%), students (89.8%) and belonging to Punjab (54%). Nearly one-fourth of the participants (23.8%) scored above the minimum value set for moderate or high psychological distress (K10 > 12). There was a higher prevalence of distress among females and resident of province Punjab. The majority of individuals reported that they were living with their family (94.5%) and more than half (52.6%) were neutral regarding their satisfaction with their living conditions. 40.5% believed that the lockdown has had a negative impact on their mental health. 31.4% have reported that they themselves have experienced abuse from a family member. 48.6% scored high on the GAD-7 scale and low wellbeing score was found among 80.2%. Students were found to be more vulnerable to mental illness and anxiety.ConclusionWith the lockdown restrictions, psychosocial distress has become prevalent in Pakistan.

Biochar amendment can influence the abundance, activity, and community structure of soil microbes. However, scare information is present about the effect of the combined application of biochar with synthetic nitrogen (N) fertilizer under paddy field condition. We aimed to resolve this research gap in rice field conditions through different biochar in combination with N fertilizers on soil nutrients, soil microbial communities, and rice grain yield. The present study involves eight treatments in the form of biochar (0, 10, 20, and 30 t ha–1) and N (135 and 180 kg ha–1) fertilizer amendments. The soil microbial communities were characterized using high-throughput sequencing of 16S and Internal transcribed spacer (ITS) ribosomal RNA gene amplicons. Experiential findings showed that the treatments had biochar amendments along with N fertilizer significantly advanced soil pH, soil organic carbon (SOC), total nitrogen (TN), soil microbial carbon (SMBC), soil microbial nitrogen (SMBN), and rice grain yield in comparison to sole N application. Furthermore, in comparison with control in the first year (2019), biochar amendment mixed with N fertilizer had more desirable relative abundance of microorganism, phyla Acidobacteria, Actinobacteria, Proteobacteria, and Verrucomicrobia with better relative abundance ranging from 8.49, 4.60, 46.30, and 1.51% in T7, respectively. Similarly, during 2020, bacteria phyla Acidobacteria, Actinobacteria, Bacteroidetes, Gemmatimonadetes, Planctomycetes, and Verrucomicrobia were resulted in higher and ranging from 8.69, 5.18, 3.5, 1.9, 4.0, and 1.6%, in biochar applied treatments, respectively, as compared to control (T1). Among the treatments, Sphingopyxis and Thiobacillus bacterial genus were in higher proportion in T7 and T3, respectively, as compared to other treatments and Bacillus was higher in T6. Interestingly, biochar addition significantly decreased the soil fungi phyla Ascomycota, Basidiomycota, Chytridiomycota, and Rozellomycota, in 2020 as compared to 2019. Whereas biochar addition to soil decreased Echria, Kohlmeyeriopsis, and Westerdykella fungal genus as compared to non-biochar treatments. The redundancy analysis showed that soil biochemical traits were positively correlated with soil bacteria. In addition, correlation analysis showed that soil bacteria including Acidobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, and Proteobacteria strongly correlated with rice grain yield. This study demonstrated that soil nutrients and bacteria contribute to an increase in rice yield in combined biochar amendment with lower N treatments.

Plums is one of the most cultivated stone fruits due to its fast growing popularity. It has various traditionally recognized health benefits. There are two main commercial types of plums: the European plum (Prunus domestica) and the Japanese plum (Prunus salicina), each having many varieties. Researchers are gathering further evidence of pharmacological effects for plums by scientifically studying its anti-inflammatory, antioxidant properties. A systematic review analysing the literature related to the effects of plums on prevention and treatment of cancer is warranted. This is the first review examining the cancer-related effects of plums. Antioxidation properties of the active constituents of plum were also compared. Scopus, Google Scholar, PubMed, Medxriv and Cochrane Library databases, from their date of inception until July 2021 were utilized. The risk of bias was assessed using CONSORT checklist. A total of 6639 studies were screened and eventually only 54 studies were included. Full-text review of included studies revealed that plum extracts were rich in antioxidants. Overall, most of the studies that fulfilled the eligibility criteria were in vitro and a few clinical studies involving in vivo work. Therefore, it would be beneficial to perform more studies on animals or humans, to confirm that the result obtained from these in vitro studies are able to be extrapolated in a wider range of applications. Further clinical and in vivo studies are warranted to validate plums as a functional food for treatment and prevention of cancer.

BackgroundAllogeneic hematopoietic stem cell transplant (allo-HCT) is a potential curative therapy for a variety of hematologic disorders. However, it requires highly specialized care that is only available at select centers across the country. Thus, minority populations are at risk for healthcare disparities in access to and outcomes of allo-HCT. Our study aimed to assess the impact of race and location of residence on outcomes of allo-HCT.MethodsWe performed a retrospective analysis of all patients who underwent allo-HCT at the Ohio State University from 1984 to 2018. Patients were divided by race (Caucasian, African American, and other) and grouped by zip code into rural, suburban, and urban groups. Primary endpoints included progression-free survival (PFS) and overall survival (OS).ResultsOf the 1,943 patients included in the study, 94.3% self-identified as Caucasian, 4.6% African American, and 1.1% other. In total, 63.4% lived in rural areas, 22.9% suburban, and 13.8% urban. There was no significant difference in OS or PFS by race (p = 0.15, 0.21) or place of residence (p = 0.39, 0.17). In addition, no difference in nonrelapse mortality, acute and chronic graft-versus-host disease (GVHD), and GVHD-free relapse-free survival (GRFS) was seen among the race or place of residence.ConclusionOur study suggests that when appropriate access to HCT is given, there is no difference in outcomes based on race, ethnicity or place of primary residence. Further research is needed to further evaluate barriers for these patients to undergo transplant and help mitigate these barriers.

Abstract Foreign body ingestion and aspiration can present as a life‐threatening emergency in children. These foreign bodies are diagnosed based on history, physical exam, and focused radiography to reduce the risk of excessive radiation. We describe a case of a 3‐year‐old child who ingested magnetic beads and presented to the emergency department with no symptoms. On a single view x‐ray of chest and abdomen, the magnetic beads were identified in the abdomen but a closer look at these single view x‐rays raised a suspicion of additional foreign bodies in the larynx. A dedicated x‐ray of the neck identified 2 more magnetic beads locked with each other on either side of the epiglottis. These laryngeal magnetic beads were nearly missed on initial x‐rays, especially because the child had no symptoms of upper airway obstruction. This case report provides further evidence that in the evaluation of radiopaque foreign bodies in children we should strongly consider “nose to rectum” x‐rays.

In modern wind turbine blades industry, fiber-reinforced composites are mostly used for their good mechanical characteristics: high stiffness, low density and long fatigue life. Wind turbine blades are constructed in different structural elements from a variety of composite laminates, often including Unidirectional (UD) material in spars and multiple forms of Multidirectional (MD) in skins and webs. The purpose of this paper is to identify materials that have appropriate fiber orientations to improve fatigue life. By using Cuckoo Search-based Neural Network (CSNN), we have developed a model to predict fatigue life under tension-tension charges for five composite materials, with different fiber stacking sequences embedded in three types of resin matrices (epoxy, polyester and vinylester), which are all appropriate for the design of wind turbine blades. In the CSNN approach used in this work, the cost function was assessed using the Mean Square Error (MSE) computed as the squared difference between the predicted values and the target values for a number of training set samples, obtained from an experimental fatigue database. The results illustrate that the CSNN can provide accurate fatigue life prediction for different MD/UD composite laminates, under different angles of fiber orientation.

Shell and tube heat exchangers are used to transfer thermal energy from one medium to another for regulating fluid temperatures in the processing and pasteurizing industries. Enhancement of a heat transfer rate is desired to maximize the energy efficiency of the shell and tube heat exchangers. In this research work, we performed computational fluid dynamics (CFD) simulations and experimental analysis on the shell and tube heat exchangers using round and hexagonal tubes for a range of flow velocities using both parallel flow and counter flow arrangements. In the present work, the rate of heat transfer, temperature drop, and heat transfer coefficient are computed using three turbulence models: the Spalart–Allmaras, the k-epsilon (RNG), and the k-omega shear stress transport (SST). We further utilized the logarithmic mean temperature difference (LMTD) method to compute the heat transfer and mass flow rates for both parallel and counter flow arrangements. Our results show that the rate of heat transfer is increased by introducing the hexagonal structure tubes, since it has better flow disruption as compared to the round tubes. We further validated our simulation results with experiments. For more accurate results, CFD is performed in counter and parallel flow and it is deduced that the rate of heat transfer directly depends upon the velocity of fluids and the number of turns of the tube.

The bullet head plays a principal role in the modern enlargement of an efficient bullet. A bullet’s main design parameters depend upon the lift and drag forces acting on the head. The factors in a bullet’s shape design that affect bullets’ lift and drag forces are essential in aerodynamics, especially in ballistics. Therefore, the effect of wind on the lift and drag forces acting on the bullet, and the role of the bullet head to allow the bullet to travel efficiently through the wind, need to be investigated. This work discusses the parameters that affect the lift and drag force on the bullet. Simulations are performed in Ansys Fluent by varying the key parameters of the bullet head, i.e., the length and angle of attack, while keeping the air velocity at 5.2 m/s. The simulation outcome shows that the size of the bullet and the angle of attack are important factors related to the drag force. Therefore, this work predicts the inspection of a bullet under distinct wind conditions. An evaluation is performed to scrutinize the effect of design factors on the system execution of the bullet and its constructive flight path. It is concluded that when increasing the length of the bullet and its angle of attack (AOA), the drag force and lift forces increase drastically, contributing to the inefficiency of the bullet’s accuracy and penetrating power. A new design is also proposed in which the drag forces are reduced to the minimum.