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It is a decentralised blockchain application created with the help of ReactJS. It is made up of SOLANA digital currency. Because we can update smart contracts in Solana far more readily than we can in Solidity, Solana is more trustworthy overall. Solana is one of the world's fastest blockchains, processing more than 65,000 transactions per second (TPS). Solana has maintained a spot in the top 10 cryptocurrencies by market cap for more than a year thanks to its speed, cheap transaction cost, and developer-friendly development strategy. This application is basically a clone of Instagram platform in this application we can create the post which is stored on cloud storage and when we add the post it will cost some SOL and it will be stored on the blockchain. Once the post is stored on the blockchain we cannot remove it. To do this process we need a cryptocurrency wallet so for this project we are using the Phantom cryptocurrency wallet. Phantom wallet is a non-custodial Web3.0 wallet, and it is the most popular cryptocurrency wallet for the Solana blockchain..

Background Pulmonary arterial hypertension (PAH) is a progressive disease with high morbidity and mortality. Risk stratification and initiation of dual or triple combination therapy has a better clinical response, especially in high-risk patients. Unfortunately, prostacyclin analogues are not marketed in India; hence, the use of these medications is limited. We report the benefits and difficulties of using iloprost inhalation in patients with advanced PAH in India. Methods In this prospective observational study, we included patients with group 1 PAH. Inhaled iloprost was initiated as an add-on therapy for patients who had clinical, echocardiographic or laboratory deterioration on dual oral medications. Patients with clinical instability were excluded. All patients underwent thorough clinical evaluation, detailed echocardiogram and laboratory investigations. Patients were started on inhaled iloprost 2.5 μg six times daily and closely followed up. The dose was escalated if necessary. On follow-up, clinical echocardiographic and laboratory evaluation was done on all patients. Results Fourteen patients (11 women) with a median age of 32 years (2–66 years) with group 1 PAH were started on inhaled iloprost as an add-on therapy. Improvement in clinical parameters, WHO functional class, echocardiographic-derived right ventricular function, and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) levels were observed in 10 of 14 patients. A median increase of 31% (4.2, 106%) in the distance travelled during 6-minute walk test, a median increase of 45% (–20, 120%) in right ventricular fractional area change, a median increase of 27% (–16.7, 60%) in tricuspid annular peak systolic excursion and a median decrease of 36.7% (–69.6, 17.2%) in NT-pro-BNP levels were observed after initiation of medication. Three patients had progression of symptoms and were then referred for lung/heart–lung transplant. One patient developed progression of symptoms after an excellent initial response and transitioned to subcutaneous treprostinil. Improvement in clinical, echocardiographic and laboratory features allowed us to successfully perform surgical Potts shunt in 2 patients. The medications were well tolerated with minimal and transient side-effects. There were no deaths. Conclusion Inhaled iloprost can be used with acceptable benefits and minimal side-effects in patients with PAH.

Object detection using Machine learning has achieved very good performance but there are many problems with images in real-world shooting such as noise, blurring or rotating jitter, etc. These problems effects the object detection. The main objective is to detect objects using You Only Look Once (YOLO) algorithm. The YOLO method has several advantages when compared to other object detection algorithms. In other algorithms like Convolutional Neural Network (CNN), Fast-Convolutional Neural Network the algorithm will not look at the image completely, but in YOLO, the algorithm looks the image completely by predicting the bounding boxes using convolutional network and finds class probabilities for these boxes and also detects the image faster as compared to other algorithms. We have used this algorithm for detecting different types of objects.

It is well-known that oral hygiene plays a role in the initiation and progression periodontal disease, for maintaining proper oral hygiene sufficient width of attached gingiva along with adequate depth of vestibule is necessary. This case report describes Clark’s technique for increasing the vestibular depth. In addition, Free gingival autograft (FGG) is done for treating Miller’s class II recession. A 17-year-old female patient referred from the Department of orthodontics, with the chief complaint of receding gums in the lower front region. On clinical examination there is shallow vestibule, Millers class II gingival recession and is also seen. So planed for the combined technique of vestibuloplasty along with free gingival graft to achieve dual benefits of increasing the vestibular depth and root coverage.

The lipomas in the palm are a rarity and are reported sporadically in the medical literature. Many smaller lesions may even go unnoticed due to minimal clinical symptoms. Clinical suspicion and judicious use of imaging may reveal lesions at an uncommon location. Histological confirmation, however, is the basis of the appropriate diagnosis. We describe two cases of lipoma at uncommon sites with the relevant description of both cases managed by surgical excision and histological confirmation. One case of a mid-palmar lipoma in a 42-year-old female and a lipoma adjacent to the right thumb base near the first web space in a 29-year-old male patient are described. The diagnosis was confirmed on histopathology in both cases. The excision biopsy resulted in complete removal; no recurrence or complication was noted in the follow-up of 6 and 8 months, respectively. Our case report highlights the importance of the early diagnosis and excision before involving adjacent vital structures or growing larger. Clinical suspicion and judicious use of imaging are important for the appropriate diagnosis at an uncommon location.

Aim: A series of benzylidene- and phenylethylidene-substituted acridone-2-carbohydrazide derivatives were designed, synthesized and evaluated for their cytotoxicity and response to p-AKT Ser473. Methods: The structures of the synthesized compounds were confirmed by spectroscopic techniques and evaluated for AKT enzyme inhibition activities. Molecular docking and in silico absorption, distribution, metabolism, elimination and toxicity studies were also performed. Results: Compounds 8k, 8v and 9h demonstrated good cytotoxicity against breast cancer cell lines. Especially, compounds 8v and 9h exhibited remarkable inhibition, with IC50 values of 1.75 and 2.40 μM, respectively. These compounds inhibited p-AKT Ser473 more specifically than total AKT in a dose-dependent manner. Moreover, they caused G0/G1-phase cell cycle arrest and cell apoptosis. Conclusion: This study identified compound 8v as a potent p-AKT Ser473 inhibitor.

In a rapidly evolving world, with a steep rise in breast cancer incidence, there has been many advances in imaging and therapeutic options of breast cancer care. In this review article, we are trying to cover imaging guideline for cancer detection and their therapeutic options. These help in the reduction of morbidity and mortality.

The Intravenous Bag Monitoring System is based upon the "Internet of Things" with the use of new technology of Artificial Intelligence and it issues flu for the Hardware as well as the software any type of project we can create using this technology and with the use of new technology today's world are grown up to the never possible conditions are also possible through the AI system So, we are looking forward to our application is used for the hospital purpose including small Clinics and Big Hospitals we had studied on it for which type of problems faced by Nurses and doctors so as we are looking for this problem then we r generating and finding a solution on it that is “Intravenous Bag Monitoring System”. This application works on the IV Bags weight sensor through this sensor the load cell sense the weight of the IV Bag and through cloud computing that data goes to the cloud and the Blynk IOT application fetches the data from the cloud and it will display the Blynk IOT dashboard like how much liquid is available in the bottle and the new feature added in this application is that when the liquid is coming up to the 15% then the Buzzer get started on the particular Hardware Kit and as well as on the mobile also alert notification sending if any nurse was busy in her another work and she can’t use her mobile that time Buzzer get started while the liquid is below 15% and as per the bottle we can set the percentage as the Buzzer will get started.

Background: Pediatric patients with multiple sclerosis (POMS) and related disorders, clinically isolated syndrome (CIS), myelin oligodendrocyte glycoprotein antibody disorder (MOGAD), and neuromyelitis optica spectrum disorder (NMOSD), are commonly treated with immunosuppressants. Understanding the impact of SARS-CoV-2 infection in patients may inform treatment decisions. Objective: Characterize SARS-CoV-2 infection prevalence and severity among a cohort of patients with POMS and related disorders, as well as the impact of disease-modifying therapies (DMTs). Methods: POMS and related disorders patients enrolled in a large, prospective registry were screened for COVID-19 during standard-of-care neurology visits. If confirmed positive of having infection, further analysis was undertaken. Results: Six hundred and sixty-nine patients were surveyed between March 2020 and August 2021. There were 73 confirmed COVID-19 infections. Eight of nine hospitalized patients (89%), and all patients admitted to the ICU were treated with B cell depleting therapy. The unadjusted odds ratio of hospitalization among those who tested positive of having had COVID-19 was 15.27 among those on B-cell-depleting therapy ( p = 0.016). Conclusions: B-cell-depleting treatment was associated with a higher risk of COVID-19, higher rates of hospitalization, and ICU admission, suggesting this therapy carries a higher risk of severe infection in POMS and related disorders.

Transmission systems are prone to contingency conditions that would either occur using a generator outage or line outage. Placing and sizing the flexible ac transmission systems (FACTS) devices appropriately can reduce the effects of the contingency condition. This paper optimally locates FACTS devices in a transmission system under the N-1 contingency condition. The genetic algorithm (GA) technique is used to locate different, multiple FACTS devices (thyristor-controlled series capacitor and static VAR compensator) optimally in a power system. This optimization technique is used to locate FACTS devices on the IEEE 9 bus system. MATLAB simulation is developed and checked for both single and multiple FACTS placements. Simulation results obtained for generator outage and line outage are tabulated with the type of FACTS device/rating, location, and generation cost with line loss reduction. The optimized results observed for the costoptimized FACTS placement problem are found to be satisfactory. The results obtained in the IEEE 9 bus system have shown improvement in a decrease of generation cost and system loss component while placement and sizing of both the FACTS devices.

Classification of grains according to their type becomes very much necessary because there are multiple grains available in the market today. Classification of Grains according their types manually is not efficient. Classification becomes a really wearisome task when it comes to doing it hand-operated instead of automating the process. Manually classifying would be a grueling task. There is a need for mentally keen and quick system which can get better of this difficulty by automating these processes. It should be able to recognize and label the every single grain according to their respective type automatically. Therefore we conducted a literature survey on how various seeds were classified and various analysis which were used to obtain the various desired result. Here we observed that various researchers used k-means, CNN and various other algorithms.

Two hydroelectric projects are operational in the upper and lower stretches of the river Alaknanda near Lambagarh and Srinagar that are respectively ~ 140 km apart. The health of the river ecosystem in the flowing stretches between and below these projects was bio-assessed, based on widely used diatom indices and van Dam ecologic values computed by OMNIDIA software. Samples were collected from Birahi, the semi-natural stretch - 53 km downstream of power-house, Narkota, the impacted stretch 27 km upstream Srinagar dam and Bagwan, the highly regulated stretch 22 km downstream Srinagar. IPS and IBD revealed mild pollution in upper and lower stretch compared to relatively elevate at Narkota. However TDI indicates moderate organic pollution at Birahi and Narkota, whereas the IDSE indicates low degradation at all stations. The prevalence of tolerant N-autotroph, β-mesosprobe, mesotrophic and aquatic to aerophilic categories of van Dam environmental variables indicate that a certain level of impact already persists due to organic-cum-nutrient load and perturbed flow-regime. The prevalence of eutrophic and moderate O2 categories shows that the ecosystem is in critical state at Narkota, causing a disrupted continuum.

Cloud computing has transformed user services by introducing a new model that allows for pay-per-use access to information technology services at any time and from any location. Numerous businesses are moving their operations to the cloud as a result of the flexibility offered by cloud services, and additional data centers are being set up by service providers to provide users with services. However, it is essential to ensure efficient resource utilization and cost-effective task execution. Based on load balancing, task scheduling, resource management, quality of service, and workload management, several methods to improve performance and resource use have been reported in the literature. Data centers can use load balancing in the cloud to prevent virtual machines from being overloaded or under loaded, which is a problem in and of itself in cloud computing. As a result, developers and researchers must develop and implement a suitable load balancer for distributed and parallel cloud environments. In order for researchers to develop algorithms that are more effective, this survey provides a cutting-edge review of issues and obstacles associated with existing load-balancing methods.

The bacterial strains were isolated from landfill soil contaminated with phthalate, collected from dump yard near Byepass, Patna. Thestrain named T23 was chosen among the isolated strains due to its high efficacy towards the degradation. We observed the effects ofvarious environmental and chemical factors for optimising the conditions for degradation. The strain T23 was identified as Lysinibacillusxylanilyticus based on its phenotypic as well as phylogenetic characteristics by performing 16S rRNA gene sequencing and for thedetermination of the metabolic end products after degradation. Gas chromatography and mass spectrometry (GC-MS) analysis was doneand the degradable intermediates obtained were 7, 10, 13-Hexadecatrienoic acid, Cyclotrisiloxane, n-Hexadecanoic acid, Oleic Acid andErucic acid. The strain T23 showed maximum degradation at pH 8.5 and temperature was 10.5 and it could tolerate up to 0-15% NaCl.Maximum degradation was exhibited at the carbon source, dextrose, and nitrogen source, casein. The 23 strain was having maximumpotential for degradation which can be used for various remediation purposes.

The WHO advises using the Defined Daily Dose (DDD) as a unit of measurement and the Anatomical Therapeutic Chemical (ATC) classification system for tracking and researching drug use. The main objective of the study is to examine changes in drug utilization. Evaluate interventions on prescribing patterns of antibiotics at The Oxford medical college hospital and research Centre. Patient demographics and drug charts are collected using specified case report form for a period of 6 months using random sampling method. Case report form includes patient demographics, laboratory data, diagnosis, and drug chart with frequency, dose, dosage and route of administration. Out of 183 cases analyzes 45.4% were female and 54.7% were male. Most of the cases were in the group of 20 to 31. Average duration of hospitalization in our study population was around 5 days. A total of 299 antimicrobial were prescribed in 183 cases. Cephalosporins were the most preferred antibiotic followed by other antibiotic class. Ceftriaxone was the most common drug among the cephalosporin. Antibiotic prescribing in the hospital is empirical, we would like to recommend that antibiotic selection should be based on the results of cultural and sensitivity testing whenever possible. The percentage of drug prescribed in generic form was found to be less. We recommend larger scope prospective study to emphasize on ensuring of rational use of antibiotics.

The current research work describes the development of a simple, fast, sensitive and efficient bioanalytical UPLC/MS–MS method for the simultaneous estimation of diclofenac and resveratrol in mice skin samples. Quetiapine was used as an internal standard (IS). Analytical separation was performed on ACQUITY UPLC C18 Column (2.1 × 100 mm; 1.7 μm) using ammonium acetate (5 mM) in water and methanol (B) with isocratic elution at ratio of (50, 50 v/v) and flow rate of 0.4 mL/min. The duration of separation was maintained for 3 min. Electrospray ionization mass spectrometry in a positive and negative ionization mode was used for detection. Selective ion mode monitoring was used for the quantification of m/z 296.025> 249.93 for diclofenac, m/z 229.09 > 143.03 for resveratrol and MRM/ES+ve mode applied in m/z 384.25> 253.189 for IS transitions from parent to daughter ion. The lower detection and quantification limits were accomplished, and precision (repeatability and intermediate precision) with a coefficient of variation below 10% produced satisfactory results. The developed bioanalytical method was found to be useful for its suitability for the dermatokinetic evaluation of treatments through rat skin. Improvement in AUC (1.58-fold for diclofenac and 1.60-fold for resveratrol) and t1/2 in the dermis (2.13 for diclofenac and 2.21-fold for resveratrol) followed by epidermis was observed for diclofenac and resveratrol-loaded liposomal gel formulation over the conventional gel. Overall, the developed method for the dermatokinetic studies of the above-mentioned dual drugs-loaded liposome gel was found to be reproducible and effective for bioanalytical.

Background: The prevalence of mental health problems in adolescents has been identified as a global concern. Early screening and identification can offer benefits in terms of primary prevention and reduced healthcare costs. This study aimed to develop a tool to assess the risk of developing mental health problems in adolescents. Methods: The study followed an exploratory sequential design and was divided into five phases. The Multidimensional Psychosocial Risk Screen (MPRS) is a newly developed self-report measure. The various steps in its development and validation have been elaborated. The MPRS was evaluated with a sample of 934 adolescents aged 12-18, spread across the 8th-12th grade. Results: Exploratory and confirmatory factor analyses revealed a robust factor structure. The extracted five factors were named as Parent–Child Relationship (PCR), Self-Concept (SC), Teacher–Student Dynamics (TSD), Social Media Use (SMU), and Peer Interaction (PI). The reliability of the subscales ranged from 0.60 to 0.80. The overall reliability of the scale was good (a = 0.87). Convergent validity of the scale was established using standard measures of risk factors and emotional and behavioural problems. Conclusions: The MPRS can be considered an effective tool with an adequate factor structure and good psychometric properties. It can be beneficial in the early detection of vulnerabilities to mental health problems in adolescents and, therefore, seen as a key element in primary prevention and fostering individualized interventions.

The binding studies of DNA with small molecules have been an emerging field of research all the time since DNA as the genetic material is a major biological target for various drugs. Interpretation of small molecule-DNA binding helps in understanding their interactions with designing new drugs of greater medicinal activity. Posaconazole is an antifungal drug in the class of triazoles which are known to possess numerous pharmacological properties. In this work, the nature of the binding of posaconazole with calf-thymus DNA has been studied using spectroscopic techniques and molecular docking studies. A binding constant of the order of 10

Zn (II) complexes of Schiff bases have potential applications in biomedical sciences as imaging agents, cancer therapeutics and diagnostics. Thus, it is important to understand their interaction with carrier proteins, like serum albumins. The present paper focuses on the binding interactions between Human serum albumin (HSA) and Znsalampy, making use of fluorescence spectroscopic techniques at ensemble as well as at single molecular level. An idea about the binding constant is obtained from the quenching of the single Trp (Tryptophan) residue of HSA by Znsalampy. Fluorescence correlation spectroscopy (FCS) has also been used to monitor the protein-ligand binding. The location of Znsalampy in its complex with HSA is determined by competitive binding experiments and molecular docking calculations. The binding constant obtained from the Znsalampy-HSA interaction falls in the ideal range for biological applications and the location is found to be in the proximity of Sudlow's site I. The esterase activity of HSA is retained in the presence of the Znsalampy. Hence, it is concluded that this Znsalampy may be a potential probe and biomarker in biomedical applications.

The Cayley graph, signed graph and line graph are well known in the literature. Now, our focus is to study line signed graphs of Cayley signed graphs. In this paper, we have characterized the Cayley sets and generating sets for which line signed graphs of Cayley signed graphs are canonically consistent(C-consistent).

“Teaching competency has different dimensions such as mastery of subject matter, enhancement of motivation of students, planning, presentation and evaluation skills and classroom managerial skills. Teacher possessing all these skills to reasonable extent can be a competent teacher”. The success of teaching mostly depends on some psychological and demographical factors of teachers. The relationship between teacher efficiency and intelligence was also the subject of study of many researchers. Many researchers indicated highly positive correlation between teaching success and intelligence. On the other the investigators concluded that the correlation between intelligence and teaching success in certain cases were positive, in some others negative, while in the rest non-significant. Therefore, it reveals to the need for further investigation and research, to find out the co-relationship between teacher efficiency and intelligence. In the present study, multi-stage stratified random sampling technique was adopted to draw the sample. The study was conducted on a sample of 589 teachers, selected from the 46 secondary schools of Bareilly region in U.P. For the purpose of measuring teaching efficiency and intelligence, the Teaching Efficiency Scale (TES)), were used. The results of the study indicate a significant and positive co-relation between intelligence and teacher efficiency.

Pyrido[2,3-d]pyrimidines against various types of cancer.

A crucial area of research that can reveal numerous useful insights is emotional recognition. Several visible ways, including speech, gestures, written material, and facial expressions, can be used to portray emotion. Natural language processing (NLP) and DL concepts are utilised in the content-based categorization problem that is at the core of emotion recognition in text documents.This research propose novel technique in linguistic based emotion detection by social media using metaheuristic deep learning architectures. Here the input has been collected as live social media data and processed for noise removal, smoothening and dimensionality reduction. Processed data has been extracted and classified using metaheuristic swarm regressive adversarial kernel component analysis. Experimental analysis has been carried out in terms of precision, accuracy, recall, F-1 score, RMSE and MAP for various social media dataset.

Sexual harassment has gained global attention and has been recognized as a critical public health concern with significant negative impacts on victims ‘physical and mental health. This study aimed to find out the awareness of sexual harassment among secondary school students in Nawalparasi District, Nepal. The descriptive cross-sectional research design was used to find out the awareness of sexual harassment among secondary-level students in Devchuli Municipality, Nawalparasi. Students studying in grades eight, nine, and ten were identified from two conveniently selected schools out of the 12 private schools in the study area. In total, 150 students took part in the study, and every one of them completed the questionnaire in its entirety. Data entry and analysis were done in Statistical Package for Social Science (SPSS) version 20. The obtained data we reanalyzed using descriptive statistical methods like frequency, percentage, mean, and chi-square to ascertain the relationship between the level of awareness of sexual harassment and the selected socio-demographic characteristics. The findings showed that, among 150 respondents, most (82.0%) had a good level of awareness regarding sexual harassment. According to respondents ‘suggestions for preventing sexual harassment (SH) can be stopped by enacting strict rules, regulations, and policies against those who engage in the practice (85.3%), running awareness campaigns about the issue (83.3%), and offering training on how to handle sexual harassment (75.3%).There was no statistically significant relationship between the level of awareness of sexual harassment and the selected socio-demographic variables. It can be recommended that schools conduct an ongoing sensitization program or awareness campaign to teach students about sexual harassment periodically.

One of the top computer vision technologies at the moment is facial recognition. In computer vision, recognising faces is always an extremely challenging process due to lighting, stance, and facial expression. Target objects are tracked by face recognition in live streaming or through video. It is a system application that, in simplest terms, automatically recognises a person from a live capture through camera or video frame. We suggested an automatic face recognition system in this project. When the person in front of the camera recognises him, this application, which is based on face detection, feature extraction, and recognition algorithms, automatically detects the human face. Although the camera is continuously identifying the face in every frame, we employed the Haar cascade classifier to detect human faces. We have utilised the CNN method to train the system using the dataset that is currently accessible, and using real-time face capture, we will store the face data in a database. It was trained using the LBPH recognizer. Face recognition has done through Harr cascade algorithm.

Water pollution is a critical issue in India with a negative impact on water resources sustainability which can cause an inadequate water supply to all people even though a large number of water resources are available. Every year a large number of people are being affected with various diseases due to drinking polluted water. This project uses the python libraries to analyse and predict the water quality using Machine Learning based upon the dataset fed to the model. This project helps us to know whether the water is potable or not. The dataset consists of various parameters which impact the purity of the water like ph., conductivity, hardness, solids, turbidity, chloramines, sulphates, trihalomethanes, organic carbons.

For delivering the cloud services over the internet, cloud computing has become proficient infrastructural model for hosting cloud services. Server virtualization is key technology that enables cloud computing as a service, which authorizes dynamic sharing of physical resources. Virtualization introduces the problem of virtual machine placement that increases the overheads in load balancing. Existing infrastructure needs the strategy for the VM Placement as it may create poor allocation and load balancing issues. In most of the cases, due to lack of input parameters physical machines are partially loaded that creates issue of fragmentation which leads to in sufficient resources that causes more utilization of physical machines in any infrastructure. We did extensive survey in the said domain and found that, In load balancing approach, when VM place mentis done without measuring its lifetime, that creates fragments on PM. So we propose dynamic priority based spill over technique and add the concept of short life/long life container for solving the fragmentation issue.