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Our prior study focused on development of internet of things (IoT) and edge-compute enabled crop physiology sensing system (CPSS) for apple sunburn monitoring. Edge compute algorithm on CPSS estimated sunburn susceptibility as fruit surface temperature (FST) through pixel-by-pixel multiplication of captured thermal infrared images with segmented fruits binary mask. The segmentation was performed using color-based K means clustering approach. This limited CPSS applicability to monitor sunburn of red colored cultivars only and when fruits develop color, typically late growing season. This is a key research gap as recent weather patterns have shown that sunburn can occur during early growing season when fruits are green to yellow. Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. Season long field data were collected in 2021 using eight CPSS nodes (three in cv. WA38 [Cosmic crisp] and five in cv. Honeycrisp). Collected data were used to develop and validate mask R-CNN based fruit segmentation model. Developed mask R-CNN based model was able to segment fruits of two apple cultivars and of varying colors with 91.4 % average precision. In orchard evaluations (2022 season), the resulting algorithm ported on CPSS was able to accurately segment (dice similarity coefficient = 0.89) and estimate apple FST with 35 °C) on a warmer day resulted in multiple throttling errors caused by excessive CPU temperature; however, the CPSS performance was uncompromised in FST estimation. Ambient air temperature did not affect RAM utilization and CPU clock frequency. Overall, developed FST algorithm can potentially be used as input to actuate water-based cooling system.

Abstract Glaucoma is defined as progressive optic neuropathy that damages the structural appearance of the optic nerve head and is characterized by permanent blindness. For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. We proposed learning technique called fast discrete curvelet transform with wrapping (FDCT-WRP) to create feature set. This method is entitled extracting curve-like features and creating a feature set. The combined feature reduction techniques named as principal component analysis and linear discriminant analysis, have been applied to generate prominent features and decrease the feature vector dimension. Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. The effectiveness has been evaluated using two standard datasets called G1020 and ORIGA with the $$10 \times 5$$ -fold stratified cross-validation technique to ensure reliable evaluation. Our employed scheme achieved the best results for both datasets obtaining accuracy of 93.25% (G1020 dataset) and 96.75% (ORIGA dataset), respectively. Furthermore, we have utilized seven Explainable AI methodologies: Vanilla Gradients (VG), Guided Backpropagation (GBP ), Integrated Gradients ( IG), Guided Integrated Gradients (GIG), SmoothGrad, Gradient-weighted Class Activation Mapping (GCAM), and Guided Grad-CAM (GGCAM) for interpretability examination, aiding in the advancement of dependable and credible automation of healthcare detection of glaucoma.

Abstract Nature-based solutions are approaches that draw inspiration from and are supported by nature, offering environmental, social, and economic benefits for enhancing urban resilience and sustainability. One of the greatest land use changes affecting the urban landscape is agricultural land conversion which affects the food security. Urban agriculture will not only generate livelihood opportunity for the urban poor but be the urban lung and heat sink, allow solid and water waste disposal and facilitate eco-cultural community bonding. A vast majority of the global urban dwellers live in the small and medium sized cities. However very little study has been done on urban agriculture in these areas although agricultural loss is more pronounced here. The objective of this paper is to examine through remote sensing data, in a time series between 2011 to 2023, the loss in agricultural land in one such smaller city- Bhubaneswar, which lies on a very fertile agricultural belt. This paper examines the decline of agricultural land in comparison to the rise in built up area within the specified timeframe and goes on to suggest a nature-based solution which makes the city self-sufficient in terms of food security. The research methodology involves mapping the spatial distribution of both the supply and demand for ecosystem services and quantifying the impact of Agriculture land use conversion on agriculture production. It concludes by deriving a framework which will identify the policy and governance interventions required so that the SDG goals 2 and 11.3 are realized.

Our study aimed to explore the genetic variation in the Toll-like receptor 4 (TLR4) gene and establish its association with somatic cell score (SCS) and milk production traits in four Indian camel breeds namely Bikaneri, Kachchhi, Jaisalmeri and Mewari. TLR4 gene fragment of 573 bp spanning 5’ UTR, exon-1 and partial intron-1 region was amplified and genotyped using the PCR-sequence based typing method. Only one SNP located at position C472T was identified. Genotyping revealed two alleles (C and T) and three genotypes: CC, CT and TT. The genotype frequencies for CC, CT and TT were 0.116, 0.326 and 0.558 and allele frequencies for C and T alleles were 0.279 and 0.721, respectively. Association study inferred that the effect of genotype on SCS, lactation yield (LY) and peak yield (PY) was non-significant however heterozygote (CT) genotypes recorded lower SCS and higher LY and PY. It can be concluded that the TLR4 gene possesses limited genetic variation, depicting polymorphism at a single locus in Indian camel breeds with a predominance of the TT genotype. The association study indicated that heterozygote animals possess better udder health and production performance, the statistical significance of which needs to be established using a large data set.

High-throughput and objective color measurements of fish fillets are crucial for quality control and establishing pricing benchmarks. While fillet color scoring traditionally relies on subjective visual inspection using color reference cards or labor-intensive color measurement using a colorimeter, this study aims to develop a smart handheld device (FilletCam AI, hereafter referred to as ‘FilletCam’) for precise and rapid profiling of fish fillet color. FilletCam comprises an imaging sensor integrated with an embedded computing unit for image acquisition. A graphical user interface (GUI) was developed to streamline data collection, analysis, visualization, compilation, and data sharing with authorized users. An Artificial Intelligence (AI) model was developed and deployed on the edge for region-of-interest (ROI) detection. A single-stage YOLOv8 model was trained on a custom image dataset comprised of Atlantic salmon (Salmo salar) and rainbow trout (Oncorhynchus mykiss) fillet images to detect the fillet and color palette with their respective SalmonFan™ (SF) score on the reference card. Delta E metric was adopted to compare the color of the fillet and reference color shades on the SF card. The SF score corresponding to the lowest Delta E value was assigned to the fillet. The object detection model performed well and achieved a mean average precision (mAP0.5) of 99.5 % and an F1 score of 0.99. The FilletCam-predicted fillet color scores were compared with the expert ratings and colorimeter scores to evaluate the performance of the developed tool. The minimum Delta E values for FilletCam were consistently lower than those for the colorimeter, indicating FilletCam's ability to detect minor color differences accurately. FilletCam exactly predicted the color scores at 73 % of instances compared to 30 % of instances for the colorimeter. Additionally, for only 3 % of instances, the predicted SF score deviated by more than two points. Overall, the developed research prototype shows promise as a valuable digital tool for the fish processing and retail industries.

The assessment of traits is important in determining production potential, reproductive performance, and overall health of dairy cows. The assessment of these traits typically involves visual inspection and manual measurement, which can be time-consuming, subject to bias, and potentially distressing for the animals. To address these challenges, convolutional neural networks (CNNs)-aided non-invasive computer vision system was developed in the present study. This system consists of a depth camera to acquire the RGB images and depth information of cows. The DeepLabV3+ model, having the ResNet50 model as a backbone, was utilized to segment the body parts of cows from RGB images. Image processing-based algorithms were developed to extract key pixel locations for each trait from these segmented images. The system estimated trait dimensions utilizing 3D data of respective key points. The mean-IoU (intersection-over-union) values for the developed segmentation models were 93.46%, 91.25%, and 99.27% for side-view, back-view traits, and stature, respectively. Additionally, the vision system was able to estimate the trait dimensions with mean absolute percentage error (MAPE) below 6.0%. For a few traits, MAPE, however, exceeded 10.0%, indicating higher error. Inaccurate segmentation, imprecise key point extraction, visual overlaps of specific body parts, and variations in cow postures contribute to such errors. The developed system attained a Ratio of Performance to Deviation (RPD) above 1.2 for all traits, indicating its ability to estimate the dimensions of traits efficaciously. Thus, the present study demonstrated the potential of a CNN-based computer vision-based system for automating the trait measurement process in cows.

The adoption of cloud computing has become increasingly widespread across various domains. However, the inherent security vulnerabilities of cloud computing pose significant risks to its overall safety. Consequently, intrusion detection systems (IDS) play a pivotal role in identifying malicious activities within a cloud system. The considerable volume of network traffic data may contain redundant and irrelevant features that can impact the classification performance of the classifier. In addition, the complexity and time consumption increase while processing such a substantial volume of data in the cloud intrusion detection process. To enhance the performance of the IDS, this study proposes a hybrid feature selection approach, combining two bio-inspired algorithms, namely the grasshopper optimization algorithm (GOA) and the genetic algorithm (GA). The combination of these two algorithms ensures a more efficient search for optimal solutions. A random forest (RF) classifier is trained using those optimal features. Moreover, the proposal addresses the challenge of imbalanced data by employing a hybrid approach: over-sampling the minority classes using an adaptive synthetic (ADASYN) algorithm, while implementing random under-sampling (RUS) for the majority class as needed. This integrated strategy significantly influences each category, enhancing the true positive rate (TPR) while minimizing the false positive rate (FPR), thus improving the overall system performance. The proposed approach was evaluated using three datasets: UNSW-NB15, CIC-DDoS2019, and CIC Bell DNS EXF 2021. The recorded accuracies for these datasets were 98%, 99%, and 92%, respectively. The hybrid feature selection-based IDS demonstrated superior performance in multi-class classification, along with exemplary results for individual classes within the datasets. The proposed strategy exhibited a marked superiority with the random forest classifier, especially when compared to other classifiers including SVM, LR, FLN, LSTM, AlexNet, DNN, DBN, DT, and XGBoost. Moreover, this performance remained consistent and commendable even when benchmarked against contemporary state-of-the-art methodologies across multiple evaluation metrics.

Accurate diagnosis and treatment of cardiovascular diseases require the integration of cardiac imaging, which provides crucial information about the structure and function of the heart to improve overall patient care. This review explores the role of Artificial Intelligence (AI) in advancing cardiac imaging analysis, with a focus on unsupervised learning methods. Unlike supervised AI systems, which rely on annotated datasets, the use of unsupervised learning proves to be a game-changer. It effectively tackles issues related to limited datasets and sets the stage for scalable and adaptive solutions in cardiac imaging. This paper gives a comprehensive overview of the limitations of traditional methods and the potential of unsupervised AI in overcoming challenges related to dataset scarcity through an extensive literature review and analysis of unsupervised algorithms, including clustering techniques, dimensionality reduction, and generative models. This review study highlights the contributions of unsupervised techniques for enhancing diagnostic accuracy and efficiency in cardiac imaging. By comparing unsupervised and supervised methods, the paper aims to explain the benefits and limitations of each approach, offering valuable insights for advancing AI integration in cardiac healthcare. The findings are expected to guide future research and development, leading to innovative advancements in cardiovascular diagnostics.

Ensuring the dependability of software before its public release is of utmost importance. Many software issues arise due to human errors made throughout the development process, highlighting the importance of addressing these errors early. It is crucial to incorporate testing resources at the beginning of development to minimize potential issues. Utilizing an approach that identifies modules susceptible to errors helps potential problems. With an understanding of the significance of precisely anticipating module failures, multiple automated solutions are already emerging. This work presents a refined software defect prediction model that utilizes a meta-heuristic optimization technique. The methodology integrates NASA’s data collection procedure, which involves data cleansing, reducing the dimensionality of features, and predicting defects. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used to decrease the feature dimensionality, while an Extreme Learning Machine (ELM) is utilized for forecasting defects. The ELM parameters, such as weight and biases, are ideally chosen using the suggested improved JAYA optimization (IMJAYA) method. The model’s validation involves assessing its accuracy, sensitivity, specificity, F1 score, and MCC metrics using a $10\times 5$ cross-validation. The model is verified using NASA datasets that consist of several classes, such as CM1, KC2, KC3, MC1, PC1, and JM1. The PCA-LDA+ IMJAYA-ELM model yields defect prediction accuracies of 95.73%, 98.08%, 94.87%, 96.23%, 97.10%, and 97.46% for the CM1, KC2, KC3, MC1, PC1, and JM1 datasets, respectively. The research outcomes show encouraging outcomes when using a meta-heuristic optimization technique with smaller feature sets for studies on predicting software defects.

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources.

Introduction: The eruption of teeth is considered to be a continuous phenomenon. Two types of eruption are possible namely, active and passive eruption. Failure in passive eruption (by the apical movement of gingiva from the enamel surface) generally results in a clinical condition known as altered passive eruption. It can result in the shortened crown height of a tooth and an esthetically unpleasant situation i.e., excessive gingival display or gummy smile. The main motto of this study was to find out the prevalence of altered passive eruption and associated gingival biotypes in adult patients visiting for dental treatment in tertiary centers along with strategically placed outreach centers. Methods: A descriptive cross-sectional study was done in the Department of Dentistry, Dhulikhel Hospital, and four outreach centers of the same hospital. The study was conducted from October 2022 to April 2023 after obtaining the ethical approval. Convenience sampling was done. Point estimate and 95% Confidence Interval were calculated. Results: Among 165 patients, the prevalence of altered passive eruption was 21 (12.72%) (7.62-17.78 at 95% Confidence Interval). Furthermore, among 21 patients, the altered passive eruption was seen in the thick biotype patients in 16 (76.19%) and thin biotype patients in 5 (23.81%). Conclusions: The prevalence of altered passive eruption appeared to be equivalent when compared with the previous studies.

Artificial Intelligence (AI) and Machine Learning (ML) can assist producers to better manage recirculating aquaculture systems (RASs). ML is a data-intensive process, and model performance primarily depends on the quality of training data. Relatively higher fish density and water turbidity in intensive RAS culture produce major challenges in acquiring high-quality underwater image data. Additionally, the manual image annotation involved in model training can be subjective, time-consuming, and labor-intensive. Therefore, the presented study aimed to simulate fish schooling behavior for RAS conditions and investigate the feasibility of using computer-simulated virtual images to train a robust fish detection model. Additionally, to expedite the model training and automate the virtual image annotation, a process flow was developed. The ‘virtual model’ performances were compared with models trained on real-world images and combinations of real and virtual images. The results of the study indicate that the virtual model trained solely with computer-simulated images could not perform satisfactorily (mAP = 62.8%, F1 score = 0.61) to detect fish in a real RAS environment; however, replacing a small number of the virtual images with real images in the training dataset significantly improved the model’s performance. The M6 mixed model trained with 630 virtual and 70 real images (virtual-to-real image ratio: 90:10) achieved mAP and F1 scores of 91.8% and 0.87, respectively. Furthermore, the training time cost for the M6 model was seven times shorter than that for the ‘real model’. Overall, the virtual simulation approach exhibited great promise in rapidly training a reliable fish detection model for RAS operations.

Abstract Background PARP inhibitors (PARPi) have a well-established role in platinum-sensitive ovarian cancer (PSOC), in BRCA mutant (BRCAm), and homologous recombination deficiency (HRD) population. However, their role in wild type and homologous recombination proficient population is still not clear. Methods A meta-analysis of hazard ratios (HR) of randomized control trials (RCTs) was conducted to study the role of PARPi. The published RCTs comparing the efficacy of PARP inhibitors alone or in combination with chemotherapy and/or target therapies versus placebo/chemotherapy alone/target therapy alone in primary or recurrent ovarian cancer settings were selected. Progression-free survival (PFS) and overall survival (OS) were the primary endpoints. Results A total of 14 primary studies and 5 updated studies are considered, consisting of 5363 patients. Overall, HR for PFS was 0.50 [95% CI 0.40–0.62]. HR of PFS was 0.94 [95% CI 0.76–1.15] in the PROC group, 0.41 [95% CI 0.29–0.60] was in HRD with BRCA unknown (BRCAuk), 0.38 [95% CI 0.26–0.57] in HRD with BRCAm, and 0.52 [95% CI 0.38–0.71] in HRD with BRCAwt. In the HRP group, overall HR for PFS was 0.67 [95% CI 0.56–0.80], 0.61 [95% CI 0.38–0.99] in HRD unknown with BRCA wt, and 0.40 [95% CI 0.29–0.55] in BRCAm HR for PFS. Overall, HR for OS was 0.86 [95% CI 0.73–1.031]. Conclusions The results suggest that PARPi have a meaningful clinical benefit in PSOC, HRD, BRACm, and also in HRP and PROC; however, the evidence is not sufficient to recommend their routine use and further studies are needed to expand their role in the HRP and PROC groups.

The focus of cloud computing nowadays has been reshaping the digital epoch, in which clients now face serious concerns about the security and privacy of their data hosted in the cloud, as well as increasingly sophisticated and frequent cyberattacks. Therefore, it has become imperative for both individuals and organizations to implement a robust intrusion detection system (IDS) capable of monitoring packets in the network, distinguishing between benign and malicious behavior, and detecting the type of attacks. IDS based on ML are efficient and precise in spotting network threats. Yet, for large dimensional data sizes, the performance of these systems decreases. Thus, it is critical to building a suitable feature selection approach that selects necessary features without having an impact on the classification process or causing information loss. Furthermore, training ML models on unbalanced datasets show a rising false positive rate (FPR) and a lowering detection rate (DR). In this paper, we present an improved cloud IDS designed by incorporating the synthetic minority over-sampling technique (SMOTE) to address the imbalanced data issue, and for feature selection, we propose to use a hybrid approach that includes three techniques: information gain (IG), chi-square (CS), and particle swarm optimization (PSO). Finally, the random forest (RF) model is utilized for detecting and classifying various types of attacks. The suggested system has been verified by the UNSW-NB15 and Kyoto datasets, achieving accuracies of over 98% and 99% in the multi-class classification scenario, respectively. It was noticed that an intrusion detection system with fewer informative features would operate more effectively. The simulation results significantly outperform other methodologies proposed in the related work in terms of different evaluation metrics.

Abstract Background The debate surrounding systematic lymphadenectomy in the epithelial cancers of the ovary (EOC) was temporarily put to rest by the LION trial. However, there was a glaring disparity between the number of patients registered and the number of patients randomized suggesting inadvertent selection. A subsequent meta-analysis after this trial included all types of studies in the literature (randomized, non-randomized, case series, and, retrospective cohort), thus diluting the results. Methods We conducted a meta-analysis of hazard ratios of randomized controlled trials, to study the role of systematic para-aortic and pelvic lymph node dissection in the EOC. A detailed search of MEDLINE, Cochrane, and Embase databases was done to look for the published randomized controlled trials (RCT) comparing lymphadenectomy versus no lymphadenectomy in EOC. A meta-analysis of hazard ratios (HR) was performed for overall survival (OS) and progression-free survival (PFS) using fixed and random effect models. The quality of the RCTs was evaluated on Jadad’s score, and the risk of bias was estimated by the Cochrane tool. Results A total of 1342 patients with EOC were included for quantitative analysis. On meta-analysis, HR for PFS was 0.9 (95% CI 0.79–1.04) favoring lymphadenectomy. HR for OS was 1 (95% CI 0.84–1.18) signifying no benefit of systematic lymphadenectomy. Conclusion The results show a trend towards increased PFS which did not reach statistical significance nor translate into any meaningful benefit in OS. There is still a need for a greater number of well-conducted, suitably powered trials to convincingly answer this question.

Background: A characteristic feature of the cervical vertebrae (C1–C7) is the presence of a foramen tranversarium on the transverse process. The cervical vertebrae are the smallest in size as compared to the thoracic and lumbar vertebrae and are characterized by a foramen in each transverse process, which is not found in any other vertebra. Except for the seventh cervical vertebra, which transmits only the vertebral vein, this foramen transmits the vertebral artery, vein, and sympathetic nerves (a branch from the cervicothoracic ganglion) in all cervical vertebrae. Any deviation in the development of the foramen transversarium (FT) causes changes in the course, relationships, and structure (stenosis and lumen narrowing) of the vertebral artery and its associated structures. Aims and Objectives: The aims of this study were to establish the location, shape, size, and incidence of accessory FT in dry human cervical vertebrae of Eastern Indian population. Materials and Methods: An observational cross-sectional study was conducted on 170 dry cervical vertebrae (Typical-123 and Atypical-47) of unknown sex and age after getting approval from the Institutional Ethics Committee. Range, frequencies, percentage, mean, standard deviation, and P value were calculated. P

The solution of compressible flow equations is of interest with many aerospace engineering applications. Past literature has focused primarily on the solution of Computational Fluid Dynamics (CFD) problems with low-order finite element and finite volume methods. High-order methods are more the norm nowadays, in both a finite element and a finite volume setting. In this paper, inviscid compressible flow of an ideal gas is solved with high-order spectral/hp stabilized formulations using uniform high-order spectral element methods. The Euler equations are solved with high-order spectral element methods. Traditional definitions of stabilization parameters used in conjunction with traditional low-order bilinear Lagrange-based polynomials provide diffused results when applied to the high-order context. Thus, a revision of the definitions of the stabilization parameters was needed in a high-order spectral/hp framework. We introduce revised stabilization parameters, τsupg, with low-order finite element solutions. We also reexamine two standard definitions of the shock-capturing parameter, δ: the first is described with entropy variables, and the other is the YZβ parameter. We focus on applications with the above introduced stabilization parameters and analyze an array of problems in the high-speed flow regime. We demonstrate spectral convergence for the Kovasznay flow problem in both L1 and L2 norms. We numerically validate the revised definitions of the stabilization parameter with Sod’s shock and the oblique shock problems and compare the solutions with the exact solutions available in the literature. The high-order formulation is further extended to solve shock reflection and two-dimensional explosion problems. Following, we solve flow past a two-dimensional step at a Mach number of 3.0 and numerically validate the shock standoff distance with results obtained from NASA Overflow 2.2 code. Compressible flow computations with high-order spectral methods are found to perform satisfactorily for this supersonic inflow problem configuration. We extend the formulation to solve the implosion problem. Furthermore, we test the stabilization parameters on a complex flow configuration of AS-202 capsule analyzing the flight envelope. The proposed stabilization parameters have shown robustness, providing excellent results for both simple and complex geometries.

Globally, head and neck cancer is estimated to occur in more than 700,000 patients a year and cause 400,000 deaths and second most common cancer in India among both sexes and all ages. Even after optimal treatment for primary cancer, there are cases where second primary cancers develop around the previously treated areas. This occurrence is explained by the concept of field cancerization, which refers to a term where a carcinogen such as tobacco when chewed, exposes the mucosa to the carcinogen starting from the oral cavity to the upper aerodigestive tract. Combinations of two primary malignancies are seen in around 3% to 5% of patients, combinations of three cancers in about 0.5%, and combinations of four malignant tumors in about 0.3% of patients with a previous history of cancer. Early diagnosis and detection of these cancers are necessary for optimal treatment as with each occurrence the tolerability and the response rates gets poorer.

Sushant Kumar et. al. report the 3.6 Å resolution crystal structure of NorC, a 14-transmembrane major facilitator superfamily member that is implicated in fluoroquinolone resistance in drug-resistant Staphylococcus aureus strains. The NorC structure was determined in complex with a single-domain camelid antibody that blocks access to the transporter and thus constitutes a new mode of inhibition.

Plants are one of the most abundant sources of biomolecules on the planet. Researchers and academics have become more interested in the antibacterial and therapeutic characteristics of plants over the last decade. The introduction and combination of nanotechnology and phytochemistry brought up new possibilities. The synthesis of metallic nanoparticles mediated by plant extracts developed quickly and has been extensively researched. In this paper, we describe the manufacture of silver nanoparticles from Cuscuta reflexa aqueous and alcoholic extracts. For characterisation, the nanoparticles were subjected to X-ray diffraction (XRD) examination. XRD analysis offers concrete information about the structure and crystalline size of nanoparticles, and it can play an important role in nanoparticle characterisation. The observation includes findings for matched phases, search-match, selection criteria, peak list, crystallite size estimation, crystallinity analysis, diffraction pattern graphics, and so on. The nano size of the crystals was disclosed by XRD examination, which proved to be 38.55 nm and 66.27 nm in the case of nanoparticles synthesised using aqueous and alcoholic extracts of Cuscuta reflexa, respectively. The crystal system was reported to be cubic with side length of 0.4 nm, the calculated density of silver in nanoparticles was calculated to be 10.506 g/cm3 which corresponds with the density of silver element, i.e., 10.49 g/cm3.

Tuberculosis (TB) is a serious public health problem worldwide, especially in tropical developing countries. Nevertheless, reports on congenital TB in humans and animals are extremely rare. In this study, abortion was reported in an 8-year-old she-camel at the 9th month of gestation. The she-camel appeared healthy in clinical examination, had a good body condition score, normal appetite, and had no signs of respiratory disease and fever. The expelled placenta was dark red-colored, thickened, and edematous with multifocal to coalescing ecchymotic hemorrhages on the allantoic surface. The striking finding was multiple, white-yellow, solid nodular lesions in the fetal lung, the pleura, and the liver. On histopathology, typical granulomatous lesions were detected in the lung and the liver characterized by caseous necrosis surrounded by lymphocyte and macrophage infiltration and concentric layers of fibrosis. The Ziehl-Neelsen staining detected scarce acid-fast bacilli in lung and liver tissues. The DNA extracted from tubercular lesions from the lung and liver showed amplification of the IS6110 region of the Mycobacterium tuberculosis complex by PCR. The sequencing and phylogenetic analysis revealed a close association of these sequences with Mycobacterium tuberculosis. The she-camel was detected positive for a single intradermal tuberculin test performed 24 h after abortion. This is the first report on congenital TB caused by M. tuberculosis in a dromedary camel fetus with a possible vertical transmission.

Punica granatum leaf extracts have been used since time immemorial in traditional medicines. It is used for its antioxidant properties. Green nanoparticle synthesis is an emerging field which has opened an entirely different scope for medicinal formulations. It has been reported by many users that the green nanoparticles are more effective medicines as compared with their simple extracts. Thus, in order to evaluate these speculations, the present work was undertaken to assess the hepatoprotective activity of silver nanoparticles synthesized using aqueous leaf extract of Punica granatum in comparison with the aqueous extract. After CCl4 intoxication the serum bilirubin total increased significantly (p

Pleurotus tuber-regium has been used as fodder and traditionally used as medicinal supplement. The aim of this study was to screen in vitro proximate biochemical composition and nutritional potentiality of P. tuber-regium extract for further in vivo analysis of impact of the extract on serum lipid and testosterone profile of rats. Total cholesterol, HDL cholesterol, LDL cholesterol were measured photometrically. Testosterone was measured by chemiluminescence immune assay. P. tuber-regium extract contains different biochemicals such as proteins, carbohydrates, tannins, flavonoids, phenols etc. and showed highly quantified calorific value (297.89±1.92 calori/100g). Acute toxicity test showed no mortality and toxic behavioural symptoms. Significant decrease in total cholesterol (75.52±0.39mg/dL), LDL cholesterol (34.58±1.69mg/dL) and triglyceride (81.31±1.25) were observed in rat group treated with 200mg/kg dose of extract. 400mg/kg dose of extract showed higher efficacy than 200mg/kg dose of extract and significantly decreased total cholesterol (72.25±1.11mg/dL), LDL cholesterol (26.37±1.21mg/dL) and triglyceride (69.42±0.72). The extract showed testosterone enhance efficacy. 400mg/kg dose of extract showed high level testosterone (178.96±0.68 ng/dL) enhance efficacy than 200mg/kg dose (174.64±0.64ng/dL). Due to hypocholesterolaemia and testosterone elevating properties of P. tuber-regium extract, it can be said that, mushroom P. tuber-regium can be consumed as healthy diet supplement to maintain cholesterol level and to maintain good male reproductive health.

Heat and light stress causes sunburn to the maturing apple fruits and results in crop production and quality losses. Typically, when the fruit surface temperature (FST) rises above critical limits for a prolonged duration, the fruit may suffer several physiological disorders including sunburn. To manage apple sunburn, monitoring FST is critical and our group at Washington State University is developing a noncontact smart sensing system that integrates thermal infrared and visible imaging sensors for real time FST monitoring. Pertinent system needs to perform in-field imagery data analysis onboard a single board computer with processing unit that has limited computational resources. Therefore, key objective of this study was to develop a novel image processing algorithm optimized to use available resources of a single board computer. Algorithm logic flow includes color space transformation, k-means++ classification and morphological operators prior to fruit segmentation and FST estimation. The developed algorithm demonstrated the segmentation accuracy of 57.78% (missing error = 12.09% and segmentation error = 0.13%). This aided successful apple FST estimation that was 10–18 °C warmer than ambient air temperature. Moreover, algorithm reduced the imagery data processing time cost of the smart sensing system from 87 s to 44 s using image compression approach.

Abstract Nanotechnology has been used in the field of medicine and pharmacology for its greater efficacy of drug delivery than crude molecules of drugs. In the present study medicinal mushroom Ganoderma applanatum extract mediated silver nanoparticles (AgNPs) were synthesized, characterized by Ultraviolet-visible (UV-Vis.) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction, Dynamic light scattering (DLS) and Furior transform-infrared (FTIR) spectroscopy. Maximum absorbance was recorded at 435nm by UV-Vis. The synthesized nanoparticles of 13.54nm-255nm in size with an average particle size of 58.77nm were analyzed by DLS. FTIR-Spectroscopy provided high transmission at 3606cm-1 corresponds for phenolic capping biochemical. Thus G. applanatum extract can be used for synthesis of silver nanoparticles and the synthesized nanoparticles may be used for development of future therapeutic agent for treatment of diseases.

The present study was conducted in mid October 2019 to compare the chewing dynamics and nutritional analysis of feed, fodder and concentrate fed to Bactrian camel raised under semi-intensive and intensive management systems in Leh and Nubra valley, Ladakh. Number of chews per bolus was significantly (P

BackgroundTreatment for coronavirus disease 2019 (COVID-19) pneumonia remains largely supportive till date and multiple clinical trials took place within the short span of time to evaluate the role of investigational therapies. The anti-inflammatory effect of low dose whole lung radiation in treating pneumonia has been documented earlier. This clinical trial analyzed the effect of low dose radiation therapy (LDRT) in a moderately affected COVID-19 pneumonia patient cohort and has evaluated its effect in stopping the conversion of moderate disease into severe disease.MethodsPatients with moderate COVID-19 pneumonia as characterized by the Ministry of Health and Family Welfare (MOHFW), Government of India, were randomized (1:1) to low dose whole lung radiation versus no radiation. All treatment of patients was concurrently being given as per institutional protocol. Patients were followed up with clinical and laboratory parameters monitored on Days 1, 3, 7, and 14. Computed tomography scan (CT scan) of thorax was performed on Days 1 and 7. Patients were evaluated for conversion of moderate into severe disease as per National Early Warning Score-2 (NEWS-2 score) as the primary end point. The secondary endpoints included changes in ratio between peripheral capillary oxygen saturation and fraction of inspired oxygen (SpO2/FiO2), biochemical markers, 25-point CT severity score, and radiation induced acute pulmonary toxicities.FindingsAt the interim analysis, there were seven patients in the radiation arm and six in the control. A whole lung LDRT improved the outcome of SpO2/FiO2 at Day 3; however it did not convert into a statistically significant improvement for the NEWS-2 score. The serum levels of LDH, CRP, Ferritin and D-dimer were significantly reduced on 14 days in the LDRT arm in comparison to the baseline value but were not significant between the two groups.InterpretationLDRT seems to have the potential to prevent moderate COVID-19 pneumonia from a deteriorating to severe category. However, further randomized clinical trial with an adequate number of such patients is warranted to establish the definitive role of LDRT in the management of COVID-19 pneumonia.FundingAn intramural research project bearing code: I-27/621, was sanctioned from the All India Institute of Medical Sciences, Patna, India.Clinical Trial RegistrationClinical Trials Registry-India (CTRI/2021/06/033912, 25th May 2021) ctri.nic.in/Clinicaltrials/login.php

Background: With increasing incidence of cancer worldwide and increasing burden of treatment over the patients with cancer, the caregivers of those patients with cancer also suffer from psychological distress which ultimately affects their Quality of Life (QOL). This aspect is often overlooked which may ultimately lead to compromised patient care. Purpose: To translate the Caregiver Quality of Life Index-Cancer (CQOLC) Scale in Hindi and assess its association with Kesslers's psychological distress scale (K-10) for determining the quality of life (QoL) of caregivers of patients with cancer in India. Methods: This is a single institute, hospital based cross sectional study performed from July 2020 to March 2021. Caregiver Quality of Life Index-Cancer (CQOLC) Scale, employing standard ‘forward–backforward’ translation procedure, the English-language version of the questionnaire was translated into Hindi-language by experts and administered to each caregiver. Cronbach's alpha was used for internal consistency. Kesslers's psychological distress scale (K-10) was analysed on interview basis. Results: A total evaluated responders were 264. The hindi versions of the CQOLC was validated by cronbach's alpha method with internal consistency between 0.8 and 0.91. The majority of the caregivers were of the age group 31-40 yrs (42.05%). The male to female ratio was 6.54:1. CQOLC good score(0-45) was obtained in 27.27%, fair(46-90) in 55.30% and poor(91-140) in 17.42%. For K-10 distress scale very mild(10-19), mild(20-24), moderate(25-29) and severe(30-50) was observed in 47.73%, 11.74%, 11.74% and 28.79% respectively. A strong relation was found between the caregivers with poor CQOLC score and severe K-10 score(p

Nanobiotechnology, an emerging stream, is an amalgamation of nanotechnology and biology. It involves synthesis of metallic nanoparticles mediated by biological materials of both plant and animal origins. The biological process of synthesis of nanoparticles is ecofriendly, requires less labor, and has many unique properties, derived from the biological matter used in their synthesis. The synthesis of metallic nanoparticles has to be followed by the characterization for different properties such as size, shape, capping materials, stability etc, which helps in clearly defining the synthesized nanoparticles on the basis of the observied properties. Keeping our past works, synthesis and characterization of nanoparticles in the background, we have reviewed different techniques utilized for characterization of metallic nanoparticles synthesized using biological agents. This review will serve as a comprehensive guide, assisting in better understanding techniques for characterization of metallic nanoparticles synthesized using biological agents.

The pinto bean is one of widely consumed legume crop that constitutes over 42% of the U.S dry bean production. However, limited studies have been conducted in past to assess its quantitative and qualitative yield potentials. Emerging remote sensing technologies can help in such assessment. Therefore, this study evaluates the role of ground-based multispectral imagery derived vegetation indices (VIs) for irrigated the pinto bean stress and yield assessments. Studied were eight cultivars of the pinto bean grown under conventional and strip tillage treatments and irrigated at 52% and 100% of required evapotranspiration. Imagery data was acquired using a five-band multispectral imager at early, mid and late growth stages. Commonly used 25 broadband VIs were derived to capture crop stress traits and yield potential. Principal component analysis and Spearman’s rank correlation tests were conducted to identify key VIs and their correlation (rs) with abiotic stress at each growth stage. Transformed difference vegetation index, nonlinear vegetation index (NLI), modified NLI and infrared percentage vegetation index (IPVI) were consistent in accounting the stress response and crop yield at all growth stages (rs > 0.60, coefficient of determination (R2): 0.50–0.56, P

Mycochemical composition, calorific value, the antioxidant activity of Pleurotus tuber- regium was analyzed and impact of P. tuber- regium extract on rat model especially glycemic, vitamins and blood parameters were explored to validate its medicinal importance. Mycochemical screening showed the presence of biochemicals such as phenols, flavonoids, proteins, carbohydrates etc. The extract showed good antioxidant activity (33.62% total antioxidant activity equivalent to 21.30 µg ascorbic acid). The extract showed dose -dependent hypoglycaemic activity by significant decreased average blood glucose level at high dose (100.62 ± 1.04mg/dL) compare to control (124.40 ± 1.45 mg/dL), haematinic activity by elevation of hemoglobin (14.75 ± 0.24 g/dL) at a high dose of extract compared to control (11.66 ± 0.21 g/dL). P. tuber-regium extract elevated vitamin B12 of rats at high dose of extract (449.60 ± 3.12 pg/mL) compared to control (420.00 ± 2.86pg/mL). P. tuber-regium extract showed a positive response to hypoglycemic, haematinic, and vitamin level of the body and posses high calorific value. Hence P. tuber-regium can be used as good fodder, medicinal and nutritional supplement.

Traditionally, Ganoderma applanatum was used as medicinal supplement for treatment of different diseases. In this study, biochemical screening, acute toxicity, and impact of G. applanatum aqueous extract on liver and renal parameters were studied. Qualitative screening of G. applanatum aqueous extract showed presence of various biochemicals such as tannin, phenolics, proteins, flavanoids and other biochemicals. FTIR analysis also showed spectrum transmission peaks for different mycochemicals such as3248. 13cm-1 for phenol O-H stretch, 1597.06cm-1 for primary amine N-H stretch, 783.10cm-1 for aromatic (meta disub benzene) C-H stretch. The extract increased body weight (Initial body weight: 181.74g; final body weight: 185.08g) when compared to control group (Initial body weight: 178.61 g; final body weight: 181.14 g) in acute toxicity test dose (2000mg/kg). Similar insignificant in final body weight of animals of different groups were observed when compared to initial body weight of animals used for the study of live and renal profile. The extract had no significant effect on organ weight. Low dose (200mg kg-1) of extract insignificantly decrease AST (51.71±0.61 mg dL-1), ALT (146.07±0.89 mg dL-1), ALP (174.68±0.65 mg dL-1) and bilirubin (0.61±0.01 mg dL-1) level and significantly elevated serum albumin level (6.63±0.22 g dL-1) compare to control group. Low dose (200mg kg-1) extract showed similar insignificant decrease in serum urea (61.30±1.05 mg dL-1) and creatinine level (0.90±0.02 mg dL-1) and significantly decreased serum uric acid level (19.52±1.14 mg dL-1) compare to control group of rats. Thus, dose-oriented application of G. applanatum extract can be beneficial for treatment of hepatic and renal diseases.

The aim of the work was to provide synthesis and characterization of silver nanoparticles loaded with P. tuber-regium extract and to assess their acute toxicity and haemotoxicity activity on rats. Acute toxicity of silver nanoparticles was studied by up-and-down-procedure and haemotoxicity was analyzed by differential red bload cell (RBC) count. UV-visible spectroscopy analysis provided peak at 463.9 nm. Scanning electron microscopy analysis showed nanoparticles of 60.8 nm to 94.9 nm in size and spherical in shape. X-ray diffraction analysis showed 125.7 nm average sizes of the silver nanoparticles. Dynamic light scattering analysis provided the average diameter 71.4 nm and zeta potential of –11.2 mV of the synthesized nanoparticles. Fourier transform infrared spectroscopy analysis showed major transmission peaks at 3295.6 cm–1 corresponds to O-H stretch for alcohol and phenol 1602.2 cm–1 corresponds to N-H and C=C stretch for primary amine and conjugated alkene. Acute toxicity test showed no mortality, gross behavioural changes and decreased body weight. Significant increase in total RBC (4.30 ± 0.05 х 106/μL), phenotypic coefficient of variation paked cell volume (PCV 26.46 ± 0.01%) and total white blood cell (WBC 8.12 ± 0.27 х 103/μL) was observed in 400 mg/kg extract dose treatment group compared to control group. Thus, synthesized silver nanoparticles loaded with mediated by P. tuber-regium aquous extrac had no acute toxic, haemotoxic effect but they showed dose dependent haematinic and immune modulation activity.

We obtain exact solutions to the field equations for five-dimensional locally rotationally symmetric (LRS) Bianchi type-I spacetime in the f(R,T) theory of gravity, where specifically, the following three cases are considered: (i) f(R,T)=μ(R+T), (ii) f(R,T)=Rμ+RTμ2, and (iii) f(R,T)=R+μR2+μT, where R and T, respectively, are the Ricci scalar and trace of the energy–momentum tensor. It is found that the equation of state (EOS) parameter w is governed by the parameter μ involved in the f(R,T) expressions. We fine-tune the parameter μ to obtain the effect of phantom energy in the model. However, we also restrict this parameter to obtain a stable model of the universe.

The present study was aimed to assess the genetic polymorphism of growth hormone (GH) gene in Jaisalmeri and Sindhi camels using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) technique. Genomic DNA were isolated from venous blood samples collected from 93 Indian camels (Jaisalmeri- 38 and Sindhi-55 camels) and 613-base pair fragment of GH gene was amplified from each genomic DNA sample by polymerase chain reaction. The PCR-RFLP was done using restriction enzyme MspI which revealed three genotypes, viz. CC, CT and TT in both the breeds. Our result indicated that both the breeds were polymorphic in nature. The corresponding genotype frequency in Jaisalmeri and Sindhi breeds were 0.474 and 0.345 for the CC, 0.395 and 0.564 for CT, 0.131 and 0.091 for TT genotypes and the corresponding C allele frequency was 0.671 and 0.627 and T allele frequency was 0.329 and 0.373. The CT genotype was found predominant in the Sindhi breed, whereas CC genotype was predominant in Jaisalmeri breed. The frequency of C allele was higher than the T allele in both of the breeds. These camel populations were in Hardy-Weinberg Equilibrium indicating that the populations meet the HWE assumptions and genetic variations were conserved. It could be concluded that Jaisalmeri and Sindhi camels having different genetic variants of GH gene might be investigated for production a DNA marker for growth and production traits in Indian camels.

Camelpox is a wide-spread infectious viral disease of camelids. An outbreak of camelpox was reported in 15 adult male dromedary camels aged between 10 to 16 years of an organized herd in winter season. The infected camels showed clinical signs of fever, anorexia, lachrymation, pendulous lips, excessive salivation and pock lesions on the skin of head, neck, mouth, lips, extremities, thigh, abdomen, scrotum and inguinal region. Mortalities were recorded in three infected camels after 10–12 days of infection and showed systemic pox lesions characterized by vesicles, papules, ulcerations and raised pock lesions in the mucous membranes of the mouth, tongue, tracheal mucosa, lung, abomasum and liver. Histopathology study revealed characteristic pox lesions with intracytoplasmic eosinophilic inclusion bodies in tongue. Lung showed lesion of interstitial pneumonia (n = 2) and bronchointerstitial pneumonia (n = 1). Liver showed infiltration of mononuclear cells around central veins and degenerative changes of hepatocytes. The abomasum and intestine showed ulcerations, marked capillary congestion and areas of lymphocyte infiltration in mucosa and submucosa. The presence of camelpox virus (CMLV) was confirmed in viral DNA isolated from formalin fixed paraffin embedded (FFPE) tissues of tongue, lung, abomasum, liver, heart and intestine of infected camels by C18L gene PCR. The sequencing of viral DNAs showed phylogenetic relatedness with other CMLV isolates from India and other countries. Thus, our study confirmed the rare severe form of systemic camelpox outbreak in adult male dromedary camels hence future attention should be given for studies on virulence, strain identification and molecular epidemiology of CMLV for planning of effective preventive and control strategies.

Abstract Background Susceptibility to pepsin digestion of candidate transgene products is regarded an important parameter in the weight-of-evidence approach for allergenicity risk assessment of genetically modified crops. It has been argued that protocols used for this assessment should better reflect physiological conditions encountered in representative food consumption scenarios. Aim To evaluate whether inclusion of more physiological conditions, such as sub-optimal and lower pepsin concentrations, in combination with pancreatin digestion, improved the performance of digestibility protocols used in characterization of protein stability. Methods Four pairs of established allergens and their related non/weakly-allergenic counterparts (seed albumins, muscle tropomyosins, plant lipid transfer proteins [LTP] and collagens) plus fish parvalbumin, were subjected to nine combinations of pH (1.2–2.5–4.0) and pepsin-to-protein ratio (PPR: 10–1–0.1 U/µg) for pepsin digestion, followed by pancreatin digestion in the presence of bile salts. Digestion was monitored by SDS-PAGE in conjunction with Coomassie staining and immunoblotting using rabbit antisera and human IgE. Results At pH 4.0 and at PPR 0.1 most proteins, both allergen and non-allergen, were highly resistant to pepsin. Under conditions known to favor pepsin proteolysis, the established major allergens Ara h 2, Pru p 3 and Pen a 1 were highly resistant to proteolysis, while the allergen Cyp c 1 was not. However, this resistance to pepsin digestion only made Ara h 2 and to a lesser extent Pen a 1 and Pru p 3 stand out compared to their non-allergenic counterparts. Largely irrespective of preceding pepsin digestion conditions, pancreatin digestion was very effective for all tested proteins, allergens and non-allergens, except for Cyp c 1 and bovine collagen. Conclusions Sub-optimal pH, low pepsin-to protein ratio, and sequential pepsin and pancreatin digestion protocols do not improve the predictive value in distinguish allergens from non-allergens. Digestion conditions facilitating such distinction differ per protein pair.

Ganoderm applanatum is a polypore macrofungi and traditionally used as medicine rather than fodder. Silver nanoparticles mediated by G. applanatum extract were synthesized, characterized and toxicity impacts were investigated for their pharmacological and medicinal uses. The synthesized silver nanoparticles were of average 58.78 nm in diameter with -13.8 mV zetpotential, analysed by dynamic light scattering method. Fourier transform infrared spectroscopy analysis of synthesized nanoparticles confirmed the capping and stabilizing with mycochemicals, that showed transmittance at 3606 cm-1 corresponds to O-H stretch for phenol, 2430 cm-1 corresponds to N-H stretch for primary and secondary amines. 2000 mg kg-1, 200 mg kg-1 and 400 mg kg-1 doses of silver nanoparticles showed non-significant (p

The blasting operation plays a pivotal role in the overall economics of opencast mines. The blasting sub-system affects all the other associated sub-systems, i.e. loading, transport, crushing and milling operations. Fragmentation control through effective blast design and its effect on productivity are the challenging tasks for practicing blasting engineer due to inadequate knowledge of actual explosive energy released in the borehole, varying initiation practice in blast design and its effect on explosive energy release characteristic. This paper describes the result of a systematic study on the impact of blast design parameters on rock fragmentation at three mines in India. The mines use draglines and shovel–dumper combination for removal of overburden. Despite its pivotal role in controlling the overall economics of a mining operation, the expected blasting performance is often judged almost exclusively on the basis of poorly defined parameters such as powder factor and is often qualitative which results in very subjective assessment of blasting performance. Such an approach is very poor substitutes for accurate assessment of explosive and blasting performance. Ninety one blasts were conducted with varying blast designs and charging patterns, and their impacts on the rock fragmentation were documented. A high-speed camera was deployed to record the detonation sequences of the blasts. The efficiency of the loading machines was also correlated with the mean fragment size obtained from the fragmentation analyses.

Solid Set Canopy Delivery Systems (SSCDS) are fixed agrochemical delivery systems composed of a network of micro-sprayers/nozzles distributed in perennial crop canopies. A previous SSCDS design composed of a 3-tier configuration using hollow cone sprayer nozzles has been shown to provide excellent coverage and deposition in high-density apple orchards. However, the hollow cone nozzles substantially increases the initial system installation costs. This study evaluated the effect of irrigation micro-emitters replacement on spray deposition, coverage and off-target drift. A micro-emitter used in greenhouse irrigation systems was duly modified to enhance its applicability with SSCDS. After laboratory assessment and optimization of the micro-emitters, a replicated field study was conducted to compare 3-tier SSCDS configured with either of modified irrigation micro-emitters or traditional hollow cone nozzles. Canopy deposition and off target drift were evaluated using a 500 ppm fluorescent tracer solution sprayed by the field installed systems and captured on mylar collectors. Spray coverage was evaluated using water sensitive papers. The overall canopy deposition and coverage for treatment configured with modified irrigation micro-emitters (955.5 ± 153.9 [mean ± standard error of mean] ng cm−2 and 22.7 ± 2.6%, respectively) were numerically higher than the hollow cone nozzles (746.2 ± 104.7 ng cm−2 and 19.0 ± 2.8%, respectively). Moreover, modified irrigation micro-emitter SSCDS had improved spray uniformity in the canopy foliage and on either side of leaf surfaces compared to a hollow cone nozzle. Ground and aerial spray losses, quantified as deposition, were numerically lower for the modified irrigation micro-emitter (121.8 ± 43.4 ng cm−2 and 0.7 ± 0.1 ng cm−2, respectively) compared to the traditional hollow cone nozzle (447.4 ± 190.9 ng cm−2 and 3.2 ± 0.4 ng cm−2, respectively). Overall, the modified irrigation micro-emitter provided similar or superior performance to the traditional hollow cone nozzle with an estimated 12 times reduction in system installation cost.

The present study aimed to compare the calcium absorption from calcium carbonate and calcium phosphate in nano and micro-sized forms using everted gut sac technique. It was found that calcium concentrations in sac fluid were higher after incubation in nano-sized calcium carbonate than micro-sized calcium carbonate by 18.23% at 45 min and 21.39% at 75 min. Likewise, Ca concentration in sac fluid was 20.50 and 15.13% higher in nano-sized calcium phosphate than those incubated in micro-sized forms at 45 and 75 min, respectively. Present study revealed that calcium carbonate and calcium phosphate are more extensively absorbed in nano-sized forms than in microsized forms, suggesting their possible use as calcium supplements in poultry and livestock farming.

Heat stress and resulting sunburn is a major abiotic stress in perineal specialty crops. For example, such stress to the maturing fruits on apple tree canopies can cause several physiological disorders that result in considerable crop losses and reduced marketability of the produce. Thus, there is a critical technological need to effectively monitor the abiotic stress under field conditions for timely actuation of remedial measures. Fruit surface temperature (FST) is one of the stress indicators that can reliably be used to predict apple fruit sunburn susceptibility. This study was therefore focused on development and in-field testing of a mobile FST monitoring tool that can be used for real-time crop stress monitoring. The tool integrates a smartphone connected thermal-Red-Green-Blue (RGB) imaging sensor and a custom developed application (‘AppSense 1.0’) for apple fruit sunburn prediction. This tool is configured to acquire and analyze imagery data onboard the smartphone to estimate FST. The tool also utilizes geolocation-specific weather data to estimate weather-based FST using an energy balance modeling approach. The ‘AppSense 1.0’ application, developed to work in the Android operating system, allows visual display, annotation and real-time sharing of the imagery, weather data and pertinent FST estimates. The developed tool was evaluated in orchard conditions during the 2019 crop production season on the Gala, Fuji, Red delicious and Honeycrisp apple cultivars. Overall, results showed no significant difference (t110 = 0.51, p = 0.6) between the mobile FST monitoring tool outputs, and ground truth FST data collected using a thermal probe which had accuracy of ±0.4 °C. Upon further refinements, such tool could aid growers in real-time apple fruit sunburn susceptibility prediction and assist in more effective actuation of apple fruit sunburn preventative measures. This tool also has the potential to be customized for in-field monitoring of the heat stressors in some of the sun-exposed perennial and annual specialty crops at produce maturation.

Aim: Chital and sambar are the common wild small herbivores, which are vulnerable to poaching for their meat. Many times poachers claim the wild meat to be that of goat or sheep. Hence, authentic evidences are required to stop such wildlife crime. The present investigation was carried out to study the species specific PCR-RFLP patterns for meat identification of chital and sambar and then differentiation from the meat of goat and sheep. Materials and Methods: Extracted DNA from meat samples were subjected to PCR using the universal primers of 12S rRNA gene. The PCR products were subjected to RFLP and sequencing. Results: The size of amplified PCR products was similar (440 bp) in each species and sequence alignment showed more than 89 % similarities among these species. However, phylogenetic analysis revealed that Chital and Sambar are in one cluster while Goat and sheep are in other cluster. To differentiate between species, restriction digestion of the PCR products was carried out to produce characteristic PCR-RFLP patterns for each species. Restriction digestion with RsaI and AluI enzymes produced distinct PCR-RFLP patterns that differentiated the meat of wild species (chital-sambar) from that of domestic species (goat-sheep). BsrI restriction digestion revealed unique PCR-RFLP pattern in chital differentiating it from the meat of other three species. Restriction digestion with DdeI enzyme led to the production of distinct PCR-RFLP patterns for chital and sambar to identify their meat individually. Conclusion: This study showed the effectiveness of 12S rRNA gene polymorphism in meat identification. The data can be used as evidence against the poachers to convict the wildlife crime in the court of law [Vet World 2013; 6(5.000): 254-259]

Tubercular abscess of the pituitary fossa is rare and may lead to diagnostic uncertainty in a patient with absence of tuberculosis elsewhere in the body. We present a rare case report of a young lady who presented with sellar and suprasellar cystic mass. She was diagnosed as a case of pituitary macroadenoma and was intraoperatively found to harbor pus in the lesion. She did not have any symptoms of infection. The case underlines the importance of considering such a possibility in the differential diagnosis of cystic sellar lesions and further diagnostic tests should be done for confirmation and treatment of this rare and potential life threatening illness.

Phytochemical investigations of Annona squamosa seeds have led to the isolation of three lignans consisting of coumarin moiety, cleomiscosin A (1), cleomiscosin B (2) and cleomiscosin C (3). Their structures were arrived at by detailed spectroscopic analysis. Cleomiscosin A and cleomiscosin B are position isomer.

The common sites of metastasis from a urinary bladder carcinoma include lymph nodes, bones, lung, liver, and peritoneum. Only a few cases of small bowel metastasis from urinary bladder malignancy have been reported in the English literature. Only one of these cases presented with bowel intussusception. We report a case of an adult small bowel intussusception due to metastasis from a urinary bladder carcinoma which is extremely rare as small bowel metastasis occur mostly from breast, lungs or melanomas.