Sandeep Kaur

Development of automatic disease detection and classification system is significantly explored in precision agriculture. In the past few decades, researchers have studied several cultures exploiting different parts of a plant. A similar study is performed for Soybean using leaf images. A rule based semi-automatic system using concepts of k-means is designed and implemented to distinguish healthy leaves from diseased leaves. In addition, a diseased leaf is classified into one of the three categories (downy mildew, frog eye, and Septoria leaf blight). Experiments are performed by separately utilising colour features, texture features, and their combinations to train three models based on support vector machine classifier. Results are generated using thousands of images collected from PlantVillage dataset. Acceptable average accuracy values are reported for all the considered combinations which are also found to be better than existing ones. This study also attempts to discover the best performing feature set for leaf disease detection in Soybean. The system is shown to efficiently compute the disease severity as well. Visual examination of leaf samples further proves the suitability of the proposed system for detection, classification, and severity calculation.

Abstract The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten–eleven translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type–specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model TET2 loss-of-function mutations in primary human hematopoietic stem and progenitor cells (HSPC). Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and in vivo competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of TET2-mutant clones in vivo. These results demonstrate the key role of 5hmC in normal hematopoiesis and TET2-mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of preleukemia and clonal hematopoiesis. Significance: We show that 5-hydroxymethylation profiles are cell type–specific and associated with transcriptional abundance and chromatin accessibility across human hematopoiesis. TET2 loss caused aberrant growth and differentiation phenotypes and disrupted 5hmC and transcriptional landscapes. Treatment of TET2 KO HSPCs with ascorbate or azacitidine reverted 5hmC profiles and restored aberrant phenotypes. This article is highlighted in the In This Issue feature, p. 265

Optically isotropic nature can open a new type of high-performance liquid crystal (LC) displays. The main features emerge from the interaction between LC and polymer network at the interface. At this point, we investigated the influence of cross-linking monomer concentration and functionality on electro-optic properties of optically isotropic liquid crystal (OILC) obtained by polymerisation-induced phase separation method. Interestingly, we obtained a pore-like network structure constructed by highly interlinked polymer beads in acrylate monomers and achieved fast decay response time (0.6 ms). We found that the voltage-dependent hysteresis was mostly eliminated (~0.25%), and the contrast ratio was enhanced (1:1550) for high functional monomers. The result inspires a simple way to optimise the materials to fabricate a high-performance OILC device and it shows high-transparency, low-driving voltage, hysteresis-free and sub-millisecond response time.

Climate change with multifaceted stressors and impacts is among the defining challenges for ecological sciences, human beings, and planet Earth in the twenty-first century. Nevertheless, evidence of scientific literature on climate change and the quality of climate models for predicting future climatic changes has become sophisticated in recent decades; the account of altered pest dynamics on crop production and other ecological cycles due to climate change demands significant attention as well. In this chapter, we discussed how climate change such as elevated temperatures, high CO2 levels, and erratic precipitation patterns leading to droughts, floods, and other extreme weather conditions may influence pests’ populations. For instance, climate change can trigger changes such as the expansion of pest distribution in spatial and temporal bases, increased pest infestation intensity, crop yield loss, increased risk of invasive pest species occurrence, increased transmission of vector-borne diseases, reduced success of biological control, reduced efficacy of current integrated pest management strategies, and changes in pest population dynamics, pest biology and their physiology such as the number of generations, life cycle, changes in overwintering patterns, and extinction. Recent data and studies projecting the impacts of climate change on pest scenarios based on climatic models are discussed. We also highlighted the role of climate models and their significance in predicting the pest outbreak under the changing climate scenarios to mitigate the damage to some extent. The climate change effects are studied using observations and experiments over gradients of elevation, latitude, and urbanization. This chapter provides a theoretical basis and reference for crop improvement and pest management under future climate changes.

Alzheimer's disease (AD) is the most widespread form of neurodegenerative disorder that causes memory loss and multiple cognitive issues. The underlying mechanisms of AD include the build-up of amyloid-β and phosphorylated tau, synaptic damage, elevated levels of microglia and astrocytes, abnormal microRNAs, mitochondrial dysfunction, hormonal imbalance, and age-related neuronal loss. However, the etiology of AD is complex and involves a multitude of environmental and genetic factors. Currently, available AD medications only alleviate symptoms and do not provide a permanent cure. Therefore, there is a need for therapies that can prevent or reverse cognitive decline, brain tissue loss, and neural instability. Stem cell therapy is a promising treatment for AD because stem cells possess the unique ability to differentiate into any type of cell and maintain their self-renewal. This article provides an overview of the pathophysiology of AD and existing pharmacological treatments. This review article focuses on the role of various types of stem cells in neuroregeneration, the potential challenges, and the future of stem cell-based therapies for AD, including nano delivery and gaps in stem cell technology.

Stocks are typically linked with companies that have commercialized operations and are establishing themselves in the business world. They can also be described as shares, a term that is frequently used in everyday language. Stocks are often viewed as a long-term investment strategy that provides a secure source of income during retirement. Within the realm of quantitative trading, accurately forecasting future security returns for stocks is a fundamental aspect of the industry, as trading strategies are developed and implemented based on our outlook of the financial market. However, conventional financial time series prediction techniques solely rely on price and volume to predict future prices. With the recent volatility of the stock market due to the COVID-19 pandemic, utilizing the time series prediction using RNN and ANN models using LSTM and Seq2Seq2 LSTM helps us analyze and visualize the stock volatility and risk associated with the stock and gain the maximum return with low risk without having to involve the human emotion.

Neurodegenerative disorders pose a significant burden on global healthcare systems, and the development of effective therapeutics and diagnostics remains a critical challenge. Nanotheranostics, the integration of nanotechnology-based diagnostic and therapeutic modalities, has emerged as a promising strategy to address these challenges. This review article provides a comprehensive analysis of the latest advancements in nanotheranostics for the treatment and monitoring of neurological disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD). The application of targeted drug delivery systems, gene therapy, and non-invasive imaging techniques are explored in-depth, highlighting the potential of nanotheranostics to revolutionize the management of neurological disorders. The article delves into the design and synthesis of various nanocarriers, such as liposomes, dendrimers, and polymeric nanoparticles, which enable the targeted delivery of therapeutic agents across the blood-brain barrier. Gene therapy approaches, including CRISPR/Cas9 and RNA interference demonstrating the potential of nanotheranostics to enable precise genetic modifications in the treatment of neurological disorders. Additionally, non-invasive imaging techniques, such as magnetic resonance imaging (MRI) and positron emission tomography (PET), are examined in the context of their integration with nanotheranostics for real-time monitoring of treatment efficacy and disease progression. The review also identifies current challenges and limitations in the field of nanotheranostics, such as toxicity, immunogenicity, and issues with large-scale production. Furthermore, it outlines future research directions and potential strategies to overcome these limitations, paving the way for the clinical translation of nanotheranostics as next-generation therapeutics in neurological disorders.

The need to produce more food has increased the amount of agro-industrial waste produced. Although this was generally recognized as a major problem in the past, it is now believed that the development of sustainable industrial processes depends heavily on this waste. Microbial transformations based on biotechnology provide effective, affordable, and sustainable approaches for producing goods with additional value. The production of nutrient-rich raw materials and biorefineries could use agricultural waste as a sustainable resource. The prospective use of agricultural residues for the synthesis of by-products such as levulinic acid, xylose, lactic acid, and sophorolipids, adsorbents, in the construction sector and for biofuels using numerous bioconversion methods is the main focus of this chapter. It is clear that the use of crop residues that have withstood bioconversion as fuel is an amazing area of research with enormous potential for massive-scale agro-industrial production to effectively meet growing energy needs.

Introduction: Reproductive health may be a vital area of concern in adolescent health. However traditional Indian society regards talks on such topics as taboos and discourages open discussions on reproductive health. Objective: This study assess the health seeking awareness and utilization of reproductive health services and determines the association between health seeking awareness and utilization of adolescence reproductive health service with selected demographic variables. Method: The descriptive study with non-experimental research design was used the analysis and interpretation was done using SPSS version 18 and excel 2010. Result: More than half (54.65%) adolescence boys and girls knew correctly about male and female reproductive system and more than half (46.94%) adolescence knew incorrectly about STD, contraception, pregnancy and abortion. However only (5%) of adolescence had ever used reproductive health services and majority of 74.2% adolescence had never used these services. Reproductive health knowledge was significantly associated with fathers qualification, fathers occupation and source of information. Reproductive health services utilization was significantly associated with age, class, source of information. Conclusion: This study clearly depicted that more than half adolescents were not utilizing the services. Lack of adolescent reproductive friendly clinics, fear/embarrassment and concealed service were reasons for not utilizing the service.Fear of social value and being embarrassed, misconception of adolescents about pregnancy, unsafe sex, shortage of supply, harmful traditional practices and lack of school based adolescent reproductive health services.

Rice grains quality estimation is important in fulfilling customer requirements.Geometric features of grains are used to check the quality of rice grains.Mechanical classification methods are being used largely by local industry to grade different size of food grains on basis of geometric parameters.Image processing techniques can be applied to extract various features of rice grains and classifies the grains based on geometric features.This study proposed a method that processes the captured still digital image of rice grains.The program has been developed using MATLAB technology.The compiler of this technology was used to convert the program into standalone application.Application was embedded with MATLAB compiler runtime that enables the execution of compiled application on computers that do not have this technology installed.In this method seven geometric features of individual rice grain were extracted from digital images and then grains of particular varieties were classified into three different classes.Calibration factor was calculated to make the method independent of camera position.The method was tested on five varieties of rice grains and compared to experimental results by measuring the geometric features of rice grains using digital vernier caliper.The error rate of measuring different geometric features between proposed method and experimental analysis was found between -1.39% and 1.40%.

Rice is one of the most important cereal grains.Rice is a good source of complex carbohydrates and is rich in several other essential nutrients.The paper presents a solution for quality analysis of Indian Basmati rice grains using Top-hat Transformation.In this paper the problem of Non-uniform Illumination for quality assessment is defined which show their effects in the process of extracting objects from the background and cause segmentation errors.The proposed method for quality assessment of Indian Basmati rice grains using Top-hat Transformation which achieves high degree of accuracy in correcting the effects of the Non-uniform Illumination than Computer Vision Inspection.The proposed method based on Morphological features is developed for counting the number of Indian Basmati rice grains with Normal grains, Long grains and Small grains.

Abstract We investigate the Beyond Standard Model discovery potential in the framework of the effective field theory (EFT) for the same-sign WW scattering process in purely leptonic W decay modes at the High-Luminosity and High-Energy phases of the Large Hadron Collider (LHC). The goal of this paper is to examine the applicability of the EFT approach, with one dimension-8 operator varied at a time, to describe a hypothetical new physics signal in the WWWW quartic coupling. In the considered process there is no experimental handle on the WW invariant mass, and it has previously been shown that the discovery potential at 14 TeV is rather slim. In this paper we report the results calculated for a 27 TeV machine and compare them with the discovery potential obtained at 14 TeV. We find that while the respective discovery regions shift to lower values of the Wilson coefficients, the overall discovery potential of this procedure does not get significantly larger with a higher beam energy.

Agriculture is an important sector that provides immense opportunities for development and livelihood for over half of the world’s population. Globally, India is the second leading country in the production of agricultural commodities. The agricultural sector is confronted with huge issues such as rapid climatic change, a decline in soil fertility, nutrient deficiency, excessive use of chemicals and pesticides, and the presence of toxic metals in soil. However, the world population growth has subsequently increased the food demand. Nanomaterials have gotten a lot of attention in recent decades due to their multiple applications in industries like health, chemistry, energy, and textiles. Nanomaterials have recently been explored as an alternative approach to control plant pests, provide nutrients to soil, and help in the protection of the environment. Several nanosensors have been used for the detection and monitoring of plant illnesses, pesticide residues, pH, and soil fertility. Therefore, in this chapter, we highlight the role of nanomaterials in disease management, crop protection, and the development of sustainable agricultural practices.

The utilization of adsorptive nonwovens as a pretreatment unit may lead to novel, cost-efficient wastewater treatment technologies with remarkable properties for environmental protection, such as efficient adsorption of antibiotics. This paper uses graphene-modified nonwoven (GMN) to examine (i) how the adsorption of tetracycline (TCY)—especially since this antibiotic is frequently detected in the environment—takes place on an environmentally relevant concentration scale, and (ii) what factors influence the antibacterial and antifungal properties profile of this material class. This study demonstrates that combining graphene particles with commercial textile auxiliaries clearly enhances the antibacterial and antifungal properties of the modified nonwoven materials. The enzyme-linked immunosorbent assay (ELISA) was used to detect the TCY residues at ng/mL scale. The adsorption results follow Henry and Redlich–Peterson isotherms and emphasize the adsorption process at low concentration levels of TCY. Therefore, the appropriately designed GMNs have a great potential application for wastewater treatment in sewage plants. Statistical analysis (skewness and kurtosis) of nonwovens and modified nonwovens morphology allowed us to determine the parameters influencing the growth of fungi in such structures. GMN structures are capable of adsorbing antibiotics; a two-fold reduction of TCY was obtained in the studies.

Oxygen based heterocyclic moieties hold an ample range of therapeutic activities. Heterocyclic molecules are nominated as vital components of an extensive array of structural motifs with both biological and pharmaceutical significance. The oxygen-based scaffolds act as anticancer candidates and are also present in numerous phytomolecules viz; irinotecan, camptothecin, topotecan, taxol, taxotere, podophylotoxin, etoposide, daunorubicin and teniposide. The architectural design of numerous structural motifs for amelioration of cancer has become progressively amplified in recent past years. Until now presently there is no strategic treatment which is so capable that can cure cancer from its roots. Henceforth, it is very indispensible to design novel anticancer structural motifs with least side effects. The oxygen containing heterocyclic scaffolds includes flavonoids, pyrans, xanthones and coumarins are of utmost importance in medical chemistry for the mitigation of cancer. This assemblage offers several recent developments as anticancer oxygen containing heterocyclic molecules all-round the globe and attracted the structural motifs of auspicious molecules, along with their mechanistic insights, IC50 values, structure–activity relationships, and molecular docking studies. The encouraging properties discovered by these oxygen-based scaffolds unconditionally engaging them at frontline in invention of potential drug candidates. Consequently, these probably will be of amazing attention to scientists working on the design and synthesis of antitumor candidates.

Abstract Amidst the global food shortage and the global climate change challenge, there is an urgent need to double food production by 2050. However, the modern crop production methods, including the use of fertilizers and pesticides, have adverse environmental consequences, exacerbating the climate crisis. To address this challenge, a transition to sustainable agriculture is imperative that can harmonize the issue. Biostimulants offer an eco‐friendly solution, especially bacterial biostimulants centred on plant growth‐promoting rhizobacteria (PGPRs). These biostimulants hold the promise of offering environmentally sustainable solutions to enhance crop productivity. The adoption of PGPR‐based biostimulants in agriculture has gained significant momentum in agricultural research. PGPRs enhance plant growth through multifaceted mechanisms. This review delves into the various modes of action employed by PGPRs to improve plant growth, including their impact on nutrient availability (such as nitrogen fixation and mineral solubilization) and stress mitigation. In addition, the practical implication of PGPR strains in field research has been discussed extensively. Besides, the review outlines the roadmap for commercializing PGPR‐based biostimulants and discusses the associated challenges and limitations. A balanced perspective on the practical implementation of PGPRs in modern agriculture is presented. Exploration of future strategies and directions rounds out the review, emphasizing the necessity of a comprehensive approach to address research gaps and unlock the full potential of PGPR‐based biostimulants for sustainable agriculture. In conclusion, this review underscores the applicability of PGPR‐based biostimulants as an innovative solution to address the current food crisis in the context of climate change.

Providing Internet access is still considered as one of the major challenges at global level. Still two third of population on globe does not have access to the Internet connectivity such as rural and remote areas. These areas do not have proper infrastructure to provision Internet services. In order to address these issues, Project Loon is launched by Google X which provides Internet connectivity to the users in remote or rural areas via special fabricated balloons which keeps on floating in the stratosphere. An overview of working and technology involved in this innovative technological boon is presented in this research article. Additionally, some commonly raised issues regarding the loon technology are also addressed.

In recent years, the biometrics has achieved a great attention on a world level.A Biometric System operates by getting biometric information from a personal that extracts a feature set from the data which is acquired, and helps in comparing this feature set against the template stored in the database.There are biometric technologies which could either be physiological or behavioral.Face Recognition is having the importance to provide biometric authentication with easy image acquisition that can be used for online and offline applications.There are number of existing approaches for biometric facial recognition and classification.This paper gives a review on some of the common and reliable approaches which include PCA, LDA, SVM, SIFT, SURF, etc.

Automatic Number Plate Recognition (ANPR) system is an image processing technology that identifies the vehicles by tracking their number plate without direct human intervention and an application of computer vision. ANPR is an important method used in Intelligent Transportation System (ITS). The four phases of the ANPR system: Image acquisition and pre-processing, number plate extraction, character segmentation and character recognition are discussed in this paper. Number Plate Extraction is most crucial step in the ANPR system which affects the overall accuracy and efficiency of whole ANPR system. The quality of acquired vehicle image is a major factor in the success of ANPR. In this paper we have proposed an efficient approach for ANPR in which the input vehicle image is firstly pre-processed using iterative bilateral filter and adaptive histogram equalization and number plate is extracted from pre-processed vehicle image using morphological operations, image subtraction, thresholding, sobel edge detection and boundary box analysis. We compared the result of our proposed approach with existing method of ANPR. Keywords - Automatic number plate recognition, histogram equalization, adaptive histogram equalization, iterative bilateral filter, median filter, number plate extraction, morphological operations, image subtraction, thresholding, sobel edge detection, connected component analysis, boundary box analysis, character segmentation, character normalization, template matching, character recognition.

Abstract Background Hospitals are globally an important place of care for dying people and the most frequent place of death in Germany (47%), but at the same time, the least preferred one – for both patients and their relatives. Important indicators and outcome variables indexing quality of care in the dying phase are available, and various proposals to achieve corresponding quality objectives exist. However, they are not yet sufficiently adapted to the heterogeneous needs of individual hospital wards. Methods This multi-centre single-arm pre-post study aims at the development and implementation of context-specific measures in everyday clinical practice, followed by evaluating this approach. Therefore, (1) already existing measures regarding optimal care in the dying phase are identified applying a systematic literature review as well as an online survey and a symposium with experts. Supported by the thereby generated collection of measures, (2) a stratified sample of ten teams of different wards from two university hospitals select suitable measures and implement them in their everyday clinical practice. Circumstances of patients’ deaths on the selected wards are recorded twice, at baseline before application of the self-chosen measures and afterwards in a follow-up survey. Retrospective file analysis of deceased persons, quantitative staff surveys as well as qualitative multi-professional focus groups and interviews with relatives form the data basis of the pre-post evaluation. (3) Results are reviewed regarding their transferability to other hospitals and disseminated (inter-)nationally. Discussion Measures that are easy to implement and appropriate to the specific situation are supposed to significantly improve the quality of care during the dying phase in hospitals and contribute to the well-being of dying patients and their relatives. Successful implementation of those measures requires consideration of the individual conditions and needs of patients and their relatives—but also of the health professionals—on the different hospital wards. Therefore, a bottom-up approach, in which the ward-specific situation is first analysed in detail and then the staff itself selects and implements measures to improve care, appears most promising for optimising care in the dying phase in hospitals. Trial registration The study is registered in the German Clinical Trials Register ( DRKS00025405 ).

The goal of recognizing handwritten numbers on paper is to extract the characteristics of the entered handwritten number. The human visual system is one of the wonders of the world. People can easily find and recognize the numbers as they are used for recognition and identification. Most people easily recognize numbers without effort. Humans are amazing at deciphering what our eyes show. All work is done subconsciously, and no additional training is required to recognize numbers. Generally, we do not need to assess the difficulty of a problem that our visual system solves. However, recognizing numbers for mechanical devices such as computers is not that easy. If we try to develop a computer program to detect numbers, the difficulty of visually recognizing patterns is significant. When it comes to coding, what seems simple when we see it will be quite complicated. Simple intuitions, for example, are for a system that recognizes strokes, circles, curves, straight lines, curves, and more. Example of recognizing a number like 9, you should recognize the loop at the top and a straight vertical bar at the bottom right. This is not easy to express algorithmically. That is why we came up with a prototype for number recognition. Although identification, classification and recognition are simple tasks with the help of machine learning, we are trying to develop a system that recognizes numbers as accurately as possible. The main goal of focusing on handwriting recognition is to learn about neural networks. Images are divided into pixels and recognized in pixel order.

Automatic Number Plate Recognition (ANPR) is an imageprocessing technology that identifies vehicles by their number plates without direct human intervention.It is an application of computer vision and important area of research due to its many applications.The main process of ANPR is divided into four stages.This paper presents a simple and efficient method for the extraction of number plate from the vehicle image based on morphological operations, thresholding and sobel edge detection, and the connected component analysis.

[This corrects the article DOI: 10.14740/wjon1049w.].

The Global Land Surface Temperature is the radiative skin temperature of ground, depending on factors, which includes the albedo, the vegetation covers and the soil moisture. To predict the changes in temperature in a particular region is becoming increasingly important to capture the future trends in that region. Machine Learning is a specialized branch of Artificial Intelligence (AI), which gives computers the power to learn and make predictions from the data, without being explicitly programmed. In this work, Ensemble Approach for Global Land Temperatures (EAGLT) is proposed. This approach will help to predict the temperature, which is of great requirement as the problem of global warming is increasing day by day. Temperatures are collected from different cities and prediction is done using this approach. The proposed ensemble approach is based on three models which provide good performance in terms of model evaluation parameters like Correlation, Accuracy, R-Squared (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), Root mean square (RMSE) and Total Time to detect the predicted temperatures. Cross Validation is performed on the best performing models to check the robustness of these selected models.

Shoot and fruit borer (SFB), Earias spp. is the second major pest on okra after cotton jassid under Punjab conditions.High incidence of this pest has been reported mainly in the pre-and post-rainy seasons.The farmers are using indiscriminate sprays of insecticide on this crop.Since crop is harvested on every alternate day, thus, insecticide residues on this crop are of great concern.Therefore to develop more safe and eco-friendly management strategies involving the application of insecticides at right time to reduce the use of insecticides on okra for the quality vegetable production; the present studies on "Economic threshold level (ETL) of shoot and fruit borer, Earias spp. on okra" were carried during the year 2009.Cumulative percent fruit infestation on the basis of fruit numbers and weight was found to be significantly lower in the first three ETLs (12.89-14.15and 14.73-16.81%,respectively) than other ETLs (16.67-22.08 and 19.09-23.41%,respectively) standard check (20.14 and 22.67%, respectively) and control (23.13 and 24.22%, respectively).Marketable yield were significantly higher (95.49-96.17q/ha) in the former three ETLs, that is, 20% shoot infestation (6 sprays), 2% fruit infestation (5 sprays) and 4% fruit infestation (5 sprays) in comparison to other ETLs (65.64-85.25 q/ha), standard check (67.73 q/ha) and control (64.19 q/ha).Significantly higher economic returns (Rs.23059 -Rs.23378/-) were also achieved from first three ETLs.The lower number of sprays, higher marketable yield and economic returns were obtained in the two ETLs, that is, 2 and 4% fruit infestation level.Keeping in view the development of resistance to the insecticides, it is desirable to start the spray at 4% fruit infestation which will provide sufficient protection against pest.

Legumes are crucial species which are used by the community worldwide. In this manuscript, a two stage approach to identify infected leaf region percentage in legumes (particularly Groundnut and Soybean) is proposed. First stage classifies between a healthy and a diseased leaf sample. Second stage detects the diseased region and identifies the proportion of leaf infected area. The two stage approach provides high accuracy and also, shows that texture features plays an important role for classification of healthy and diseased leaves. The experimental results obtained on a self-collected leaf image dataset show that the proposed approach accurately identifies the diseased region in legumes. The proposed methodology can also be used for the classification of different disease types.

This paper presents an efficient algorithm based on SIFT (Scale Invariant Feature Transform), SURF (Speeded up Robust Features) and PCA. The method applies the SIFT and SURF algorithm in the detection and description for image features for a particular image and then applying PCA to the image for the better performance in matching in terms of rotation, expression and pose. The SURF technique is fast and robust interest point detector which is used in many computer vision applications. The basic process of face recognition system and improvement in matching the invariant faces is described in this paper. Performance can be seen on the basis of Recognition rate and Computation time. Image Processing Toolbox under MATLAB Software is used for the implementation of this proposed work.

The retrial bulk arrival queue with unreliable server and negative customers is considered. On arrival of the group of customers, one of the customers gets the service immediately if the server is idle and other customers join the retrial orbit. There is a provision to opt additional service after completion of the essential service of the customers. The server may fail due to arrival of negative customers during any stage of the service. After completion of the service, the customer may again join the queue as a feedback customer to get another regular/optional service or depart from the system. The non-persistent (impatient) phenomenon also occurs because of the delayed in repair/repair time of the failed server. By using the supplementary variable approach, various measures of queueing and reliability characteristics are analysed. To facilitate the comparative study of the performance metrics of the system, the maximum entropy principle is used. The numerical results for various performance indices and optimal cost are obtained.

We describe a rare case of a 20-year-old man who presented with an extensive facial and orbital venous malformation associated with multiple intracranial venous malformations. The co-existence of cerebrofacial venous malformations points towards a common final pathway in development of these malformations. Our findings are consistent with few previous similar case descriptions. In addition, we describe some novel observations which, to the best of our knowledge, have not been described in the literature. This case reinforces the concept of metameric and segmental distribution of cerebrofacial vasculature, and the aberrations thereof leading to the metameric venous malformations, as proposed by Lasjaunias et al.

Conventional energy sources of extraction of oil are nonrenewable and requires higher amount of energy. These conventional sources lead to increment in emission of greenhouse gases as well as solvent residues thus are not considerably good for environment. Meanwhile, increase in demand is an opportunity for oilseed industries. Development of innovative technology for extraction is currently encircled by two major factors, that is, to ensure adequate supply and efficient utilization of energy, time and material sources. Among many technologies, synergism of microwave and ultrasound technology leads to overall resource efficient technology for extraction. High heating and cavitation phenomenon result into cell bursting and facilitates release of oil in solvent matrix. Extraction efficiency is observed owing to increased yield by 50%–500% and reduced process time by 10 folds. Microwave ultrasound-assisted extraction (MUAE) is considered as resource efficient technology. Process time, cost, and environment impact have been significantly shifted toward progress. On the other hand, MUAE shows remarkable increase in phytochemical composition of oil and is no significant difference in fatty acid composition as compared to conventional methods. MUAE have many various other applications such as bioethanol, biodiesel, and bigas production in addition to extraction of oils. Beside all these advantages, process chemistry evaluation and understanding needs to be consider as important key point in MUAE.

Background: Breast carcinoma is the most common malignancy in women in the world.This study evaluated the expression of ER, PR and p53 in breast carcinoma and its correlation with age, size, lymph node status and other parameters.Methods: 103 histologically proven Breast carcinoma cases were subjected to IHC for ER,PR and p53.Result: Total cases of breast cancer were 103.All the cases were between 21-60 years with tumour size varying from 0.5->5cm.Maximum cases were of grade III.Metastatic carcinomatous deposits in lymph nodes were seen in 53 cases.Tumors were separated into 4 categories depending on ER/PR expression with ER-ve/PR-ve category having maximum number of cases.As the tumour grade increased lesser was the ER PR expression.P53 positivity was noted in 60 cases comprising of 58.3%.Significant correlation was noted while comparing p53 with lympho vascular invasion (p=0.042)but not with age, tumour size, tumour grade and lymph node status.Significant correlation was also noted while correlating p53 and ER/PR expression with tumour size (p = 0.036) but not with tumour grade, lympho vascular invasion and lymph node status. Conclusion:In the present study it was observed that ER PR status is inversely proportional to p53 expression.It is concluded that p53 has direct relationship with tumour grade, tumour size, lymphovascular invasion.Thus p53 helps to provide prognostic information and better treatment options

Bee products are known since ancient times for their nutritional value and beneficial effects. The present study was carried out to evaluate the phytochemical composition and therapeutic potential of bee pollen and beebread. Broth dilution method was used to observe the in vitro antibacterial activity. For in vivo antioxidant activities, BALB/c mice were divided into six groups; Gp1 was given normal saline only, Gp2 was injected intraperitoneally with Salmonella enterica serovar Typhimurium at 2×104 CFU/ml, Gp3 was administrated orally with bee collected pollen of Zea mays (250mg/kg bw) only, Gp4 was treated with the bee collected pollen of Z. mays (250mg/kg bw) in Salmonella infected mice, Gp5 was administrated orally with beebread of Z. mays (250mg/kg bw) only and Gp6 was treated with the beebread of Z. mays (250mg/kg bw) in Salmonella infected mice. The results obtained in the study suggested that various bioactive constituents were present in bee pollen and beebread and these phytochemical constituents were responsible for the antibacterial and antioxidant efficacy of these studied bee products. Beebread was found to possess high activity as compared to bee pollen reflecting its high polphenolic composition. Hence, it could be inferred that bee pollen could be seen as a potential source for designing a drug against S. typhimurium.

&lt;div&gt;Abstract&lt;p&gt;The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten–eleven translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type–specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model &lt;i&gt;TET2&lt;/i&gt; loss-of-function mutations in primary human hematopoietic stem and progenitor cells (HSPC). Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and &lt;i&gt;in vivo&lt;/i&gt; competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of &lt;i&gt;TET2&lt;/i&gt;-mutant clones &lt;i&gt;in vivo&lt;/i&gt;. These results demonstrate the key role of 5hmC in normal hematopoiesis and &lt;i&gt;TET2-&lt;/i&gt;mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of preleukemia and clonal hematopoiesis.&lt;/p&gt;Significance:&lt;p&gt;We show that 5-hydroxymethylation profiles are cell type–specific and associated with transcriptional abundance and chromatin accessibility across human hematopoiesis. &lt;i&gt;TET2&lt;/i&gt; loss caused aberrant growth and differentiation phenotypes and disrupted 5hmC and transcriptional landscapes. Treatment of &lt;i&gt;TET2&lt;/i&gt; KO HSPCs with ascorbate or azacitidine reverted 5hmC profiles and restored aberrant phenotypes.&lt;/p&gt;&lt;p&gt;&lt;i&gt;&lt;a href="https://aacrjournals.org/bloodcancerdiscov/article/doi/10.1158/2643-3230.BCD-3-4-ITI" target="_blank"&gt;This article is highlighted in the In This Issue feature, p. 265&lt;/a&gt;&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

&lt;div&gt;Abstract&lt;p&gt;The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten–eleven translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type–specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model &lt;i&gt;TET2&lt;/i&gt; loss-of-function mutations in primary human hematopoietic stem and progenitor cells (HSPC). Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and &lt;i&gt;in vivo&lt;/i&gt; competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of &lt;i&gt;TET2&lt;/i&gt;-mutant clones &lt;i&gt;in vivo&lt;/i&gt;. These results demonstrate the key role of 5hmC in normal hematopoiesis and &lt;i&gt;TET2-&lt;/i&gt;mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of preleukemia and clonal hematopoiesis.&lt;/p&gt;Significance:&lt;p&gt;We show that 5-hydroxymethylation profiles are cell type–specific and associated with transcriptional abundance and chromatin accessibility across human hematopoiesis. &lt;i&gt;TET2&lt;/i&gt; loss caused aberrant growth and differentiation phenotypes and disrupted 5hmC and transcriptional landscapes. Treatment of &lt;i&gt;TET2&lt;/i&gt; KO HSPCs with ascorbate or azacitidine reverted 5hmC profiles and restored aberrant phenotypes.&lt;/p&gt;&lt;p&gt;&lt;i&gt;&lt;a href="https://aacrjournals.org/bloodcancerdiscov/article/doi/10.1158/2643-3230.BCD-3-4-ITI" target="_blank"&gt;This article is highlighted in the In This Issue feature, p. 265&lt;/a&gt;&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;Abstract&lt;p&gt;PTOV1 is an oncogenic protein, initially identified in prostate cancer, that promotes proliferation, cell motility, and invasiveness. However, the mechanisms that regulate PTOV1 remain unclear. Here, we identify 14-3-3 as a PTOV1 interactor and show that high levels of 14-3-3 expression, like PTOV1, correlate with prostate cancer progression. We discover an SGK2-mediated phosphorylation of PTOV1 at S36, which is required for 14-3-3 binding. Disruption of the PTOV1–14–3-3 interaction results in an accumulation of PTOV1 in the nucleus and a proteasome-dependent reduction in PTOV1 protein levels. We find that loss of 14-3-3 binding leads to an increase in PTOV1 binding to the E3 ubiquitin ligase HUWE1, which promotes proteasomal degradation of PTOV1. Conversely, our data suggest that 14-3-3 stabilizes PTOV1 protein by sequestering PTOV1 in the cytosol and inhibiting its interaction with HUWE1. Finally, our data suggest that stabilization of the 14-3-3–bound form of PTOV1 promotes PTOV1-mediated expression of cJun, which drives cell-cycle progression in cancer. Together, these data provide a mechanism to understand the regulation of the oncoprotein PTOV1.&lt;/p&gt;Implications:&lt;p&gt;These findings identify a potentially targetable mechanism that regulates the oncoprotein PTOV1.&lt;/p&gt;&lt;/div&gt;

Supplementary Figure from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and &lt;i&gt;TET2&lt;/i&gt;-Mutant Preleukemia

Supplementary Table from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and &lt;i&gt;TET2&lt;/i&gt;-Mutant Preleukemia

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

Supplementary Data from SGK2, 14-3-3, and HUWE1 Cooperate to Control the Localization, Stability, and Function of the Oncoprotein PTOV1

Supplementary Table from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and &lt;i&gt;TET2&lt;/i&gt;-Mutant Preleukemia

Supplementary Figure from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and &lt;i&gt;TET2&lt;/i&gt;-Mutant Preleukemia

Background &amp; objectives: The affirmation about the prevalence of mosquito species at a particular place and time is very significant, not only to predict the danger of diseases or future outbreaks but also to control the vectors in time. Despite mosquitoes being medically important, the information about its faunal diversity is very scanty as far as Chandigarh in India and its nearby areas are concerned. So, this study was carried out to survey the mosquito fauna from areas in and around Chandigarh in northern India. Methods: Detailed mosquito surveys were carried out to explore the mosquito fauna from various habitats of developed urban areas, gardens, slums and surrounding villages of Chandigarh from June 2017–November 2019 using hand nets and oral aspirators. Results: A total of 34 mosquito species belonging to 8 genera viz; Anopheles, Aedes, Armigeres, Culex, Coquillet-tidia, Mansonia, Mimomyia and Verrallina were recorded, identified and preserved along with detailed collection data, of which eight are new records from Chandigarh. Interpretation &amp; conclusion: The present checklist of mosquito fauna comprising 34 species provides information on the occurrence of mosquito vectors in Chandigarh and its adjoining areas which will be beneficial for the health authorities to adopt appropriate measures in time for the control of these vectors.

Diversity of aquatic insects in relation to the physicochemical parameters of the two selected ponds of Bathinda region was studied from December, 2021 to May, 2022. A total of 430 individuals of aquatic insects belonging to five orders were collected and identified (upto genus level). More number of insects was recorded from the pond I as compared to pond II. Number of physical and chemical parameters such as temperature, pH, transparency, total alkalinity, water salinity, dissolved oxygen, total hardness, calcium, magnesium, free carbon dioxide, chloride, ammonium nitrogen and orthophosphate levels were also studied to demonstrate the quality of water.

Several human infections have emerged in the last three decades, most of them are attributed to wildlife origin. Two third of the emerging zoonotic infections are attributed to viruses. Emerging and re-emerging fatal viral diseases like Nipah virus disease, Hendra Virus disease, Severe Acute Respiratory Syndrome, Middle East Respiratory Syndrome, Ebola and Marburg haemorrhagic fever have been witnessed recently, causative agents of which have been associated with bats. Ecology of bats influences the host-pathogen interaction and is responsible for harbouring several viruses, which under favourable conditions spill over to intermediate hosts. Conditions and events, such as deforestation, agricultural and livestock practices, animal migration and trade, eco-tourism, urbanization and other anthropogenic factors, greatly influence the successful interspecies transmission and emergence/re-emergence of zoonoses. This review highlights, the bats ecological factors and human-bat interface, responsible for zoonotic outbreaks in past. The implementation of an integrated approach is needed for unravelling the host-virus dynamics as well as providing mutually beneficial solutions for bat conservation and safeguarding animal and public health at a global level.

India's sizable agricultural market provides the perfect conditions for cultivating a variety of products, including the tomato harvest. Detecting the transmission of diseases from unhealthy to healthy plants poses a severe threat to the agricultural industry because, if caught early enough, they can quickly spread and perhaps infest the entire farm. In terms of profit in good forming, early stage crop disease identification and severity monitoring is quite important. K-means clustering with fuzzy logic is used in the proposed study to evaluate the disease-affected region of the leaf and, as a result, assess the severity of the diseases. In this thesis, illnesses are detected using machine learning models for convolutional neural networks (CNN) and K-nearest neighbours (KNN).

Abstract: In recent years, deep learning has transformed computer vision, giving rise to automated image captioning systems bridging the gap between visual content and natural language. This paper presents an innovative approach to automated image captioning, combining deep learning models and methodologies. Our system employsConvolutional Neural Networks (CNNs) for robust image feature extraction and Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) networks, for generating coherent captions. It is trained on diverse image-caption datasets, learning intricate associations between visual content and textual descriptions.

The blood–brain barrier and the quick medication clearance into blood circulation following the administration of standard dosage form place restrictions on the treatment of brain-related disorders. The transport of drugs to the brain has been shown to increase with the use of block copolymers in past studies due to better stability, targetability and extensive circulation period. Owing to the complex formation, functionalisation, dosage mitigation and kinetics for the rate of release processes, improvements of block copolymers exhibit improved solubility and decreased cytotoxicity. The focus is on block copolymers that can be used as translational nanomedicines synthesised via complex multimolecular interactions among the polymers and the loaded pharmaceuticals. According to the sort of polymeric interaction with the biological interface, the elements associated with the creation of effective carriers are explained in depth, with a focus on the chemical engineering of the block copolymers. Block copolymers have such diverse functions that they purposefully pass through the biomembrane as polymeric nanoparticles, polymersomes and micelles utilising various pathways, including transcellular- and receptor-mediated transportation systems to achieve the targeted neural network, integration of stimuli-sensitive moieties, complexation of active ligands and imaging moieties in copolymers and the conjugation of cargo molecules with the core-forming block via responsive smart linkers. This chapter provides instances of corona-forming blocks for the transfer of drugs to the brain and brain imaging with neuroprotective effects.

This work aims to implement industrial automation landscape by developing efficient systems to connect disparate machines and devices in an industrial environment. By creating an automated, centralized platform accessible via the internet, users can control and monitor all machines in the industry from one place. This work particularly focusses on the conveyor belt application in industry and the implementation of Industry 4.0 in Industries. To achieve this, Cyber-Physical Systems (CPS), Internet of Things (IoT) and Internet of Services technologies are used. These technologies enable efficient operation and monitoring of conveyor systems, ultimately leading to increased productivity, reduced downtime and increased safety. The proposed system provides real-time data for decision-making and optimization, ultimately paving the way for the future of Industry 4.0 in the conveyor belt industry. IoT and Industrial automation is the technology that can be utilized to reduce human interventions and manual overhead in the system to monitor as well as to indicate any errors in the system. Artificial Intelligence could also be used to control and monitor the industry. IoT is not a technology basically it is an ecosystem with Industry Specific Implication. In many Industries monitoring of belt conveyor application is manual with an operator, particularly for sorting application based on color, shape and size of the object. Industry 4.0 leans towards the use of sensor and internet of things to achieve these functions with no errors. This work is an effort made to realize the use of IoT and Industry 4.0 for sorting and counting application in an industrial environment like conveyor belt applications.

&lt;div&gt;Abstract&lt;p&gt;PTOV1 is an oncogenic protein, initially identified in prostate cancer, that promotes proliferation, cell motility, and invasiveness. However, the mechanisms that regulate PTOV1 remain unclear. Here, we identify 14-3-3 as a PTOV1 interactor and show that high levels of 14-3-3 expression, like PTOV1, correlate with prostate cancer progression. We discover an SGK2-mediated phosphorylation of PTOV1 at S36, which is required for 14-3-3 binding. Disruption of the PTOV1–14–3-3 interaction results in an accumulation of PTOV1 in the nucleus and a proteasome-dependent reduction in PTOV1 protein levels. We find that loss of 14-3-3 binding leads to an increase in PTOV1 binding to the E3 ubiquitin ligase HUWE1, which promotes proteasomal degradation of PTOV1. Conversely, our data suggest that 14-3-3 stabilizes PTOV1 protein by sequestering PTOV1 in the cytosol and inhibiting its interaction with HUWE1. Finally, our data suggest that stabilization of the 14-3-3–bound form of PTOV1 promotes PTOV1-mediated expression of cJun, which drives cell-cycle progression in cancer. Together, these data provide a mechanism to understand the regulation of the oncoprotein PTOV1.&lt;/p&gt;Implications:&lt;p&gt;These findings identify a potentially targetable mechanism that regulates the oncoprotein PTOV1.&lt;/p&gt;&lt;/div&gt;

Abstract This paper outlines an introduction to dendrochronology. The tree rings are being identified through image processing and statistical simulations. The study of the tree rings is known as dendrochronology but the techniques do need to be modified for better performance. Image analyses convert the tree ring into digital data using imaging tools. This method involves the scaling, piling, width calculation. Technology is required to evaluate the factors of different tree ring pattern. In this review paper, literature survey has been provided which deals with the contribution of different researchers, which methodologies they preferred and what were their limitations. And two attributes are being calculated named MSE and PSNR, as these obtainable values indicates to work further with the enhanced image. Also, researcher can get idea what all the attributes are important to implement this technique.

Abstract Interminable surveillance and reconnaissance through various sophisticated multispectral detectors present threats to military equipment and manpower. However, a combination of detectors operating in different wavelength bands (from hundreds of nanometers to centimeters) and based on different principles raises challenges to the conventional single-band camouflage devices. In this paper, multispectral camouflage is demonstrated for the visible, mid-infrared (MIR, 3-5 and 8-14 μm), lasers (1.55 and 10.6 μm) and microwave (8-12 GHz) bands with simultaneous efficient radiative cooling in the non-atmospheric window (5-8 μm). The device for multispectral camouflage consists of ZnS/Ge multilayer for wavelength selective emission and Cu-ITO-Cu metasurface for microwave absorption. In comparison with conventional broadband low emittance material (Cr), the IR camouflage performance of this device manifests 8.4/5.9 °C reduction of inner/surface temperature, and 53.4/13.0 % IR signal decrease in mid/long wavelength IR bands, at 2500 W∙m-2 input power density. Furthermore, we revealed that the natural convection in the atmosphere can be enhanced by radiation in the non-atmospheric window, which increases the total cooling power from 136 W∙m-2 to 252 W∙m-2 at 150 °C surface temperature. This work may introduce the opportunities for multispectral manipulation, infrared signal processing, thermal management, and energy-efficient applications.

This study aimed to determine whether or not developmental potential impacts clinical outcomes, when good grade blastocysts from Days 5 and 6 were transferred in frozen embryo transfer (FET) cycles.654 women, including 460 (70.33%) on Day 5 and 194 (29.66%) on Day 6 were analyzed, in which 905 Day-5 and 274 Day-6 blastocysts were transferred. Only grade AA, AB, BA, BB quality and expansion grade between 3-6 (Gardner grading system) blastocysts survived and were included.The implantation rate was higher, 41.9% (379/905) in normal Day-5 compared to delayed Day-6 blastocyst transfers - 36.5% (100/274), but not significant (p=0.1). The clinical pregnancy rate was similar and not significant (p=0.4) in normal Day-5 (32.4%), compared to delayed Day-6 (35%). Miscarriage rates were higher in normal Day-5 (13.3%) compared to delayed Day-6 (6.3%) blastocyst transfers but were not significant (p=0.06). On the other hand, the biochemical pregnancy rate was significantly higher (p=0.001) in the delayed Day-6 blastocysts (16.7%) transfer group compared to patients with normal Day-5 (2.4%) blastocyst transfers. Two patients had ectopic pregnancies from the delayed Day-6 blastocyst transfer group. Live-Birth rates were significantly higher in Day-5 blastocysts compared to Day-6 (p=0.03).The developmental potential of embryos should not be considered a negative influence on pregnancy outcomes, especially good grade blastocysts vitrified on Days 5 and 6. Fully expanded blastocysts on Day-5 are considered similar in terms of outcomes to delayed Day-6 blastocysts; however, live-birth rates are significantly higher in Day-5 blastocysts.

In order to efficiently handle the increased luminosity that will be provided by the High-Luminosity LHC (HL-LHC) [1], the ATLAS [2] Muon System was upgraded by replacing its first end-cap station (Small Wheel system) with a New Small Wheel (NSW) detector [3].The NSW detector provides high-precision muon track reconstruction, as well as information to the ATLAS Level-1 (L1) trigger for data recording.The data collected by the NSW along with other subsystems must be scrutinized to ensure the integrity of the detector, before making it available as "certified data" for "Physics Analyses".This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain, using several Data Quality (DQ) tools.This paper, therefore, summarizes the development of the NSW DQ system and presents preliminary DQ monitoring results obtained from the early detector operation during the preparation of the Run3.

The National Payments Corporation of India (NPCI) has invested a sizable amount of money in the country's massive payment infrastructure in an effort to enhance the user experience. However, in order for investments to be profitable, NPCI must guarantee the ongoing use of technological solutions and post-adoptive behaviors like continuance and recommendation intention. The impact of cognitive factors (i.e. Performance expectancy, effort expectancy, social influences, facilitating conditions; personal innovativeness) and affective factors (such as satisfaction) on conative factors (such as continuation and recommendation intention) in the perspective of UPI applications (apps) was investigated using the UTAUT model. Partial Least Square Structural Equation Modeling when applied on 651 users (PLS-SEM) showed that satisfaction had a direct impact on continuation intentions, which in turn had an impact on recommendations intentions. It was discovered that all cognitive factors, including performance expectations, effort expectations, and facilitating conditions, have an impact on satisfaction. According to the study, adding a significant individual difference variable—personal innovativeness with regard to information technology—would aid in our understanding of the role that these factors play in the development of continuous intention. It further examines the influence of trust and security, and the pace of innovation on continued intentions. Through the mediating function of user satisfaction, it also looked at the impact of performance expectancy, effort expectancy, social influence, facilitating variable, and personal innovativeness on the continuance intentions of the UPI system. All factors have been shown to be significant. Future researchers will find it extremely helpful that the study used a validated instrument to better understand user adherence and referral intentions. Therefore, this study adds to the limited body of knowledge in the payment industry literature by examining how users perceive UPI apps and post-adoption behaviors.

Planting methods and nutrient management are the most important factors in increasing the productivity of crop plants.Broadcasting and line sowing are common planting methods for rapeseed-mustard.Among nutrients, nitrogen (N), phosphorus (P) and potassium (K) are vital nutrients along with sulphur (S) and boron (B) that play key roles in plants.In present research the effect of planting methods and nutrient management in mustard (Brassica rapa L.) was studied.A field experiment was conducted in the Research Field of the Department of Agriculture at Maharishi Markandeshwar University, Sadopur (Haryana) during the Rabi season 2020-21.A treatment combination of line sowing + T 5 gave results with maximum benefits in most of the parameters.At the same time it was also observed that boron and sulphur can also influence most of the traits if applied in an optimum dose.On the basis of the experimental findings, it may be concluded that the application of RDF along with boron and sulphur in deficient areas is recommended to increase the growth and productivity of mustard along with line sowing as an appropriate method of sowing.

In current years, very huge collections of images and videos have grown swiftly. In parallel with this boom, content-based image retrieval and querying the indexed collections of images from the large database are required to access visible facts and visual information. Three of the principle additives of the visual images are texture, shape and color. Content based image retrieval from big sources has a wide scope in many application areas and software’s. To accelerate retrieval and similarity computation, the database images are analyzed and the extracted regions are clustered or grouped together with their characteristic feature vectors. As a result of latest improvements in digital storage technology, it's easy and possible to create and store the large quantity of images inside the image database. These collections may additionally comprise thousands and thousands of images and terabytes of visual information like their shape, texture and color. For users to make the most from those image databases, efficient techniques and mechanisms of searching should be devised. Having a computer to do the indexing primarily based on a CBIR scheme attempts to deal with the shortcomings of human-based indexing. Since an automated process on a computer can analyze and process the images at a very quick and efficient rate that human can never do alone. In this paper, we will discuss the structure of CBIR with their feature vectors.

Page segmentation is an important field to analyse patterns from the OCR Systems. In this paper we tried to present how page segmentation is done on the OCR systems. We discussed the XY Cut page segmentation algorithm. The result of XY Cut page segmentation is evaluated on scanned OCR document.

Members of the Fusarium oxysporum species complex include pathogenic and non-pathogenic isolates and infect a broad range of plant species. F. oxysporum f. sp. cubense (Foc) causes the destructive Fusarium wilt of banana, and the recently emerged Foc tropical race 4 strain threatens the global banana industry. Secreted in xylem (SIX) genes encode for F. oxysporum effector proteins that are associated with virulence in pathogenic F. oxysporum, however they have rarely been reported from non-pathogenic F. oxysporum isolates. Our recent survey of asymptomatic banana plants grown in Foc-infested fields in Queensland and northern NSW revealed that diverse Fusarium spp, including F. oxysporum, reside in the plant roots and pseudostem without causing obvious damage to the plant. Intriguingly, we amplified SIX genes from several of the putative endophytic F. oxysporum isolates identified in the survey and found that they differ in their profile to known Foc SIX genes. To study the role of the endophytic F. oxysporum isolates in planta and the biological function of their SIX genes in more detail, we will re-inoculate cultivated and wild diploid banana lines with the endophytic F. oxysporum strains under glasshouse conditions to assess if they are non-pathogenic on banana. Secondly, we will determine whether the endophytic F. oxysporum SIX genes are expressed in planta and/or in vitro and look at the transcriptome changes occurring in the host following infection. Finally, endophytic F. oxysporum strains transformed with GFP will be used to investigate the extent of fungal colonisation in the plant.

Due to Corona Virus Pandemic (Covid-19), several countries across the world resorted to lockdowns in order to protect their people from getting infected from the virus. But these lockdowns confined millions of citizens to their homes restricting their mobility. Restricted mobilization resulted in shutting down businesses and ceasing almost all economic activities. According to the International Monetary Fund (IMF), the global economy is expected to shrink by over 3 per cent in 2020, the steepest slowdown since the Great Depression of the 1930s. Another analysis by International Monetary Fund reveals that demand in the manufacturing sector has gone down in many countries of the world that further resulted in unemployment. During the lockdown, an estimated 14 crore (140 million) people lost employment while salaries were cut for many others. More than 45 per cent of households across the nation have reported an income drop as compared to the previous year. Thus, Covid-19/ Crona virus outbreak has presented new and significant downside risks to the global economic outlook. In the case of India too, some economists revealed that during lockdown there is ajoblossof40millionpeople(MRD report) in the country, that’s too in the unorganized sectors. Moreover, with the advent of the lockdown most of the sector shifted their functioning online or work from home in order to sustain their working. During shutdown it is also observed that the digital world got a push, sale of mobile phones and related gadgets increased. The small as well as big traders, businessmen started using apps like watsepp, Face book, Twitter, YouTube, and Instagram, PayTM etc more frequently. Undoubtedly, social media has helped in sustaining economy and business during the Corona Virus Pandemic. The present research work is an effort to look upon the role of social media in sustaining business during lockdown. Data were collected empirically again with the help of social media. Results revealed that impacts of lockdown were different on different types of businesses.

During present investigations the detailed morphotaxonomic studies of Culex bitaeniorhychus revealed that it exists in two forms i.e typical and tenax in and around Chandigarh. Various intraspecific variations in the morphology and male genitalia were observed in both these forms. The main aim of this study is to distinguish these two forms of Cx. bitaeniorhynchus and their separation from other closely related species. The intraspecific variants of these forms have been studied further with respect to phallosome regions of the male genitalia. For assessing the significant differences among their phenotypic characteristics one–way ANOVA was done along with pair-wise comparisons of samples means. Some of the earlier workers have considered tenax form, a synonym of Cx. infula which is another closely related species of Cx. bitaeniorhynchus. But, on the basis of remarkable differences observed between tenax and infula, it is suggested that these two are separate taxons and should not be synonymised.

Face recognition is an assignment that people perform routinely and easily in their everyday lives.The most recent decade has seen a pattern towards an inexorably universal nature, where compelling and minimal effort registering frameworks are, no doubt coordinated into cell telephones, autos, therapeutic instruments and very nearly every part of our lives.In the previous work, few researchers have focused on detection of face using some methodology.In this research paper, the face recognition system proposed the Detection time, false negative in missed faces and optimality of the face.This proposed research work has been focused on optimality features of the neural network for the face images and detection time.In this paper, we have applied the neural network for three parameters suchdetection time, false acceptance rate, successful rates, no. of failure, and cross correlation.Our proposed parameters provide better result as compared to the previous methodology.

23Nov 2016 EMBRYO VITRIFICATION ON DAY2 AT 4-CELL STAGE USING CRYOLOOP DEVICE: OUR EXPERIENCE. VDS Jamwal , Mohanlal K , Sandeep K , Nikita Naredi and Mohan Angadi.

Present work demonstrates the simple, chemical free, fast, and energy efficient method to produce reduced graphene oxide (r-GO) solution at RT using visible light irradiation with plasmonic nanoparticles. The plasmonic nanoparticle is used to improve the reduction efficiency of GO. It only takes 30 min at RT by illuminating the solutions with Xe-lamp, the r-GO solutions can be obtained by completely removing gold nanoparticles through simple centrifugation step. The spherical gold nanoparticles (AuNPs) as compared to the other nanostructures is the most suitable plasmonic nanostructure for r-GO preparation. The reduced graphene oxide prepared using visible light and AuNPs was equally qualitative as chemically reduced graphene oxide, which was supported by various analytical techniques such as UV-Vis spectroscopy, Raman spectroscopy, powder XRD and XPS. The reduced graphene oxide prepared with visible light shows excellent quenching properties over the fluorescent molecules modified on ssDNA and excellent fluorescence recovery for target DNA detection. The r-GO prepared by recycled AuNPs is found to be of same quality with that of chemically reduced r-GO. The use of visible light with plasmonic nanoparticle demonstrates the good alternative method for r-GO synthesis.

BackgroundThe generation of electric power is an important source of pollutants such as mercury, sulphur dioxide, nitrogen oxides and fine particulate matter, which affects the respiratory, cardiovascular and central nervous system.ObjectiveThe objective of the study was to determine the effects of occupation on the health of the thermal power plant workers.Peak expiratory flow rate (PEFR) and acute changes in oxygen saturation were measured in 100 healthy male workers, aged 30–45 years, of two different units of power plant exposed to coal and coal combustion products and compared with 50 non-exposed attendants working at the hospital.ResultsThe mean peak expiratory flow rate of the attendants in the hospital was found to be 443.4 ± 13.29 l/min, which was significantly more than workers of both the units of the thermal power plant. Acute changes in oxygen saturation were within normal limits (96–98%) in all workers, but the mean oxygen saturation of the coal ash unit workers of the thermal power plant was significantly lower (<italic>P</italic> &lt; 0.001) than the attendants at the hospital.Although there was little evidence of pollution-related hypoxia, impaired PEFR could reflect changes in the respiratory system of the thermal plant workers.

In the given paper I present the information regarding quality metrics. Different quality factors can be imposing with relation to cost, schedule and rework. It’s very important to make quality assurance plans. For that you have to cover many milestones which can be represented in time sheets. The main characteristics of the quality models have covered in this paper

The study has been designed to investigate the effect of aqueous extract of rind of Punica granatum in sciatic nerve ligation induced-neuropathic pain in rats.Surgical procedure was performed with sciatic nerve ligation to develop neuropathic pain in rats.The development of neuropathic pain was assessed by employing behaviour parameters such as hyperalgesia and allodynia.Further, the functionality of sciatic nerve was assessed using the histopathological study of myelinated and unmyelinated fibers in sciatic nerve.Moreover, the oxidative stress was assessed by estimating serum thiobarbituric acid reactive substances (TBARS), catalase, glutathione and tissue TBARS and Superoxide dismutase (SOD).Rats exposed to sciatic nerve ligation produced marked increase in oxidative stress, which was assessed in terms of TBARS and SOD along with decrease in the level of catalase and glutathione.Moreover, it develops neuropathic pain by impairing the normal functions of myelinated and unmyelinated fibers in sciatic nerve.Treatment with aqueous extract of Punica granatum extract (100mg/kg, p.o) markedly prevented sciatic nerve ligation-induced neuropathy and oxidative stress by increasing the pain threshold, by improving the functionality of sciatic nerve, by decreasing serum and tissue TBARS and tissue SOD, by increasing levels of serum glutathione and catalase.It may be concluded that Punica granatum extract reduced the oxidative stress via inhibiting p 38 MAPK and alleviates neuropathic symptoms and consequently improved the functionality of sciatic nerve and prevents sciatic nerve ligation-induced neuropathic pain.Various reports indicate that neuropsychologic and neuroanatomic changes too are responsible in the progression of NP 9,10 .Nerve damage due to NP results in allodynia (Pain due to stimulus that does not normally provoke pain, it can be provoked by touch stimulation or cooling) and Hyperalgesia (Provoked by heat stimulation) 11 .Various mediators are implicated in the pathogenesis of NP such as neuropeptides 12 ,

Global commodity markets have gone through a long journey. In India, the emergence and augmentation of the organised commodity derivative market is relatively a recent phenomenon. Since its inception in June 2000, derivative exchanges have exhibited exponential growth in terms of volume and value of trade. The setting up of the three exchanges was the turning point in the history of commodity market of India. Hence, the study is undertaken to analyse the trends and progress of the national commodity exchanges of India and comparing the value of the trade of the selected agricultural commodities (soybean, mustard seed, soy oil, guarseed and channa). Data for the commodities under study covers period from the year 2004-2005 till the year 2014-2015. The study is based on the secondary data related to exchanges, i.e., MCX, NCDEX, NMCE, ICEX and ACE.