“Research on the "Engineering of Nano-gel for delivery of Mometasone and Itraconazole on Scalp and Beard for the Treatment of Fungal Infection"

Scalp and beard fungal infection often treated with conventional dosage form like cream, gel, emul-gel, which causes various side effects, to overcome such problems this research was conducted to develop Itraconazole and Mometsone Anti-fungal Nano-Hydro- Gel that is effective in the treatment of fungal infections of the scalp and beard. Itraconazole belongs to Azole group, which inhibit Lanosterol 14 alfa demethylase, the enzyme that converts lanosterol to ergosterol. Ergosterol is a component of yeast and fungal membranes. Nano-formulation penetrates deeper into the skin. The gel formula retains its therapeutic effect as well as the soothing effect on the hair follicles for long time. Pre-formulation studies of Itraconazole and Mometasone particles were done, and then both the API particles were converted into nano- particles through solvent diffusion method. SEM, P-XRD, IR tests were performed for characterization of Nano-Particles. Nano- Hydrogel base, prepare by using Carbopol-940, Carbopol-934, Triethanolamine and Distilled Water and engineering done by adding drug. When both Carbopol grades (934 and 940) are used together in the formulation of gel, the drug will release over a longer period of time with a smaller dose and less chance of any dose-dependent harm.Various composition were engineered an evaluated for selection of model formulation. Result- Evaluated for these parameters: Physical appearance, pH, estimation of practical yield, homogeneity, drug content uniformity, spreadability, viscosity, Statistical analysis of experimental data by ANOVA using Excel, In-vitro-drug release study, release kinetic study, Particle size analysis, (SEM), FT-IR studies. In-Vitro Anti-fungal activity tested by using Nano-gel Franz diffusion cell (Make-Orchid scientific). Amount of drug released was determined using UV- spectrophotometer at 222 nm. Conclusion- Fungal infection is most common skin condition occurs on the scalp and chin. Under these skin conditions, the hair follicles become inflamed and the affected area becomes itchy, flaky or scaly, causing redness, swelling and irritation. So this research was done with focus for pathology, pathogenesis consequently treatment of scalp and beard fungal infectio

A Survey on Multi-AP Coordination Approaches over Emerging WLANs: Future Directions and Open Challenges

Recent advancements in wireless local area network (WLAN) technology include IEEE 802.11be and 802.11ay, often known as Wi-Fi 7 and WiGig, respectively. The goal of these developments is to provide Extremely High Throughput (EHT) and low latency to meet the demands of future applications like as 8K videos, augmented and virtual reality, the Internet of Things, telesurgery, and other developing technologies. IEEE 802.11be includes new features such as 320 MHz bandwidth, multi-link operation, Multi-user Multi-Input Multi-Output, orthogonal frequency-division multiple access, and Multiple-Access Point (multi-AP) coordination (MAP-Co) to achieve EHT. With the increase in the number of overlapping APs and inter-AP interference, researchers have focused on studying MAP-Co approaches for coordinated transmission in IEEE 802.11be, making MAP-Co a key feature of future WLANs. Moreover, similar issues may arise in EHF bands WLAN, particularly for standards beyond IEEE 802.11ay. This has prompted researchers to investigate the implementation of MAP-Co over future 802.11ay WLANs. Thus, in this article, we provide a comprehensive review of the state-of-the-art MAP-Co features and their shortcomings concerning emerging WLAN. Finally, we discuss several novel future directions and open challenges for MAP-Co.Comment: The reason for the replacement of the previous version of the paper is due to a change in the author's list. As a result, a new version has been created, which serves as the final draft version before acceptance. This updated version contains all the latest changes and improvements made to the pape

Life cycle sustainability assessment of crops in India

In India, the modernization in the agricultural sector is continuously growing to meet the food demand of rising population. However, along with addressing hunger, modern agriculture impacts the ecosystem, human health, and resources, due to huge consumption of agrochemicals, and emission-intensive farming hence urges sustainable assessment. Till now, no impact assessment is reported on world's second-largest agricultural country- India. This paper is the first of its kind in evaluating the impact of the cultivation of 21 commonly grown crops that possess high production and emissions in India. The results were discussed in the order of impact parameters in respective years with possible causes and remedial measures. The results showed that rice has topped in maximum indices followed by sugarcane, wheat, and banana. The study forecasted that coconut played a concentrated role in global warming, while potato and sugarcane have a higher impact on water and ozone depletion, respectively. The outcomes of this study suggested appropriate improvements in farming practices, which can bring the emissions down and make the system more sustainable. Besides, these 18 indices were individually assessed for their connection with the 17 sustainable development goals (SDGs) in the aspects of agricultural activities to select the appropriate indices to measure the agricultural sustainability along with the identification of gaps to upgrade the existing indices or formulate a new one. Subsequently, this helps in achieving the SDGs in India with the least impact on the environment without compromising the socio-economic aspects involved in crop production and agricultural systems. © 2021 The Author

Smart Handover with Predicted User Behavior using Convolutional Neural Networks for WiGig Systems

WiGig networks and 60 GHz frequency communications have a lot of potential for commercial and personal use. They can offer extremely high transmission rates but at the cost of low range and penetration. Due to these issues, WiGig systems are unstable and need to rely on frequent handovers to maintain high-quality connections. However, this solution is problematic as it forces users into bad connections and downtime before they are switched to a better access point. In this work, we use Machine Learning to identify patterns in user behaviors and predict user actions. This prediction is used to do proactive handovers, switching users to access points with better future transmission rates and a more stable environment based on the future state of the user. Results show that not only the proposal is effective at predicting channel data, but the use of such predictions improves system performance and avoids unnecessary handovers.Comment: Submitted to IEEE Networ

Pharmacological screening of ethanolic extract of Pithecellobium dulce for antiarthritic activity in Rats

418-424Arthritis is an inflammatory joint disorder in which cartilage of the joint is gradually lost and categorized by swelling of joints, pain, and loss of function. The present study was conducted to explore the antiarthritic activity of ethanolic extract of Pithecellobium dulce against formaldehyde induced at sub plantar region of the left hind paw during days 1 and 3 of the study period. The changes observed in paw diameter during the study period, various biochemical, and haematological parameters were monitored. The Radiographic analysis and histopathology significantly improved after treatment with test extract P. dulce (250 mg/kg, b.w., p.o.) as compared to the standard treatment with indomethacin (10 mg/kg, b.w., p.o.).The results of the current investigation concluded that ethanolic extract of P. dulce possesses significant anti-arthritic activity against formaldehyde induced arthritis model, justifying its therapeutic role in arthritic conditions. The observed antiarthritic activity may be due to the presence of phytoconstituents such as alkaloids and flavonoids. P. dulce significantly suppressed the paw oedema in formaldehyde models (P <0.001). The Histopathological and radiographic studies of joints also showed a protective effect of P. dulce

Pharmacological screening of ethanolic extract of Pithecellobium dulce for antiarthritic activity in Rats

Arthritis is an inflammatory joint disorder in which cartilage of the joint is gradually lost and categorized by swelling of joints, pain, and loss of function. The present study was conducted to explore the antiarthritic activity of ethanolic extract of Pithecellobium dulce against formaldehyde induced at sub plantar region of the left hind paw during days 1 and 3 of the study period. The changes observed in paw diameter during the study period, various biochemical, and haematological parameters were monitored. The Radiographic analysis and histopathology significantly improved after treatment with test extract P. dulce (250 mg/kg, b.w., p.o.) as compared to the standard treatment with indomethacin (10 mg/kg, b.w., p.o.).The results of the current investigation concluded that ethanolic extract of P. dulce possesses significant anti-arthritic activity against formaldehyde induced arthritis model, justifying its therapeutic role in arthritic conditions. The observed antiarthritic activity may be due to the presence of phytoconstituents such as alkaloids and flavonoids. P. dulce significantly suppressed the paw oedema in formaldehyde models (P &lt;0.001). The Histopathological and radiographic studies of joints also showed a protective effect of P. dulce

MoNuSAC2020:A Multi-Organ Nuclei Segmentation and Classification Challenge

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public

Water, Sanitation, and Hygiene: A Global Imperative for Health

Clean water, proper sanitation, and hygiene (WaSH) can have a significant impact on human health. Lack of financial resources prevent developing nations from making investments in WASH infrastructure, such as water treatment plants and sanitation facilities. Achieving universal access to clean water and sanitation is hampered by poor governance and insufficient policy frameworks. Governments, civil society organisations, and the private sector need&nbsp;to collaborate to invest in infrastructure and technology, promote good hygiene practises, and undertake education and awareness-raising programmes in order to ensure that everyone has access to clean water and sanitation

Exam Assessor Tool: An Automated System for Efficient Answer Sheet Evaluation

With Education 4.0 and four quadrant approach number of innovations have gone into academics for efficient, experiential, and outcome-based education however assessment schemes are still very much dependent on manual assessment methods which are time-consuming and cumbersome. The grading system can sometimes be irrational, with diversified schemes for the same course and can also be biased. Covid 19 pandemic caused a global economic avalanche like we’ve never experienced in our lifetime. Many countries have implemented control measures such as blockades and curfews. The education system in this chaos saw a silver lining with academics shifting to online mode, with paradigm shift in teaching, assessment techniques too need to evolve. Work done is an effort to ease the process of assessment, a machine learning assisted model is developed that automates subjective answer evaluation in the education sector. Our project involved several crucial steps, including grayscale conversion, Natural Language Processing (NLP) for data cleansing, data splitting, and training an artificial neural network (ANN) to predict scores based on extracted features. ANN-based system grades subjective responses without human intervention, reducing the workload of teachers and professors. Model constructed an ANN architecture with three layers using Rectified Linear Activation Unit (ReLU) and Sigmoid activation functions. Trained model was incorporated into a user-friendly web application using the Streamlit library. Model design gives a major boost in grading efficiency and accuracy while providing valuable feedback to students. Research surveys were conducted, and a dataset was constructed for training and testing the model. study yielded an accuracy of 83.14% after employing techniques such as text cleaning, preprocessing, and feature extraction

Effect of Zn and B on Lentil (Lens culinaris) Growth Characteristics, Yield, and Available Nutrients in the Soil

To assess the effects of Zn and B treatment, a field experiment was carried out during the rabi seasion 2020–21 at the Crop Research Center of the Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut (U.P.). Ten treatments, each with a different combination of control, RDF, Zn, and B, were examined using a randomised block design with three replications. The experimental results revealed that growth attributing traits viz. Plant population (ha-1), Plant height (cm), Number of branches plant-1, Dry matter accumulation (g m-2), Effective nodules (No. plant-1), Nodules dry weight (mg plant-1), yield viz. grain yield, straw yield, biological yield and harvest index and Available nutrient in soil N, P, K, Zn, S and B in lentil differed significantly among different treatments. Growth parameters and yield were significantly better in the treatment T10 (RDF + Boron 2 kg ha-1 + Zinc 5 kg ha-1). The highest grain yield was recorded in T10 RDF + Boron 2 kg ha-1 + Zinc 5 kg ha-1 was applied with Zn and B and was statistically at par with T8. From the study it may be concluded that the application of RDF + Boron 2 kg ha-1 + Zinc 5 kg ha-1 with Zn and B (T10) gave best results (Grain yield increased by 26.7%, 25.7%, 21%, 22.9%, 17.2% and 59.1% over T1, T3, T4, T5, T6 and T1, respectively) and proved to be beneficial for rabi lentil followed by&nbsp; RDF + Boron 2 kg ha-1 + Zinc 5 kg ha-1 (T9) also gave better results. Zn and B, together with N, P, K, and S, were used in lentils in a balanced manner to preserve soil fertility while also improving growth characteristics and yield