bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Characterization and Evaluation of 5α, 6β-Dihalo Androsterone
Derivatives as 5α-Reductase Inhibitors
Authors: Dhingra Neelima , Sharma Akansha , Rana Priyanka , Arora Poonam , Kaur Tanzeer
Published: May 2022

Background and Objective:

Testosterone under the influence of 5α-reductase enzyme gets converted to dihydrotestosterone and high levels are found to be causative for androgen dependent disease like benign prostatic hyperplasia. Thus, 5α-reductase has been recognised as an important target for discovering new drugs against Benign Prostatic Hyperplasia and Prostate Cancer.

Methods:

In the present study, a series of 5α, 6β-Dichloro-17-Oxoandrostan-3β-yl esters (7a-7f) were synthesized and characterized by analytical and spectroscopic methods. The compounds were evaluated for their 5α-reductase inhibitory activity in-vivo by their effect on serum androgen level.

Results:

The target compounds (7a-7f) showed increased anti-androgenic activity as compared to finasteride and control, which implies that the target compounds are effective in inhibiting 5α-reductase. Particularly, compound 7b showing highest inhibitory activity and noteworthy D-Score was further sorted by performing solubility and dissolution studies. Results of these studies when compared with finasteride showed increased solubility and dissolution of target compound 7b.

Conclusion:

These results demonstrated that enhancement of activity by the presence of electronegative group at position 3 of the steroidal nucleus makes 7b a lead compound for further exploration and optimal formulation.
M-CAMPTM: A Cloud-based Web Platform with a Novel Approach for
Species-level Classification of 16S rRNA Microbiome Sequences
Authors: Daniely Michal , Liu Yang , Schriefer Andrew E. , Kumar Brajendra , Zolty Avihai , Didier Adam , Nirmal M.G.  , Greeshma G.T.  , Nadiv Nofar , Perez Michael , Preetam R.  , Mahankuda Santosh Kumar , Kumar Pankaj , Tenney Aaron , Bourner Maureen , Lezer Shira , Zhong Fei
Published: May 2022

Background:

The M-CAMPTM (Microbiome Computational Analysis for Multi-omic Profiling) Cloud Platform was designed to provide users with an easy-to-use web interface to access best in class microbiome analysis tools. This interface allows bench scientists to conduct bioinformatic analysis on their samples and then download publication-ready graphics and reports.

Objective:

In this study we aim to describe the M-CAMPTM platform and demonstrate that the taxonomic classification is more accurate than previously described methods on a wide range of microbiome samples.

Methods:

The core pipeline of the platform is the 16S-seq taxonomic classification algorithm which provides species-level classification of Illumina 16s sequencing. This algorithm uses a novel approach combining alignment and kmer based taxonomic classification methodologies to produce a highly accurate and comprehensive profile. Additionally, a comprehensive proprietary database combining reference sequences from multiple sources was curated and contains 18056 unique V3-V4 sequences covering 11527 species.

Results and Discussion:

The M-CAMPTM 16S taxonomic classification algorithm was evaluated on 52 sequencing samples from both public and in-house standard sample mixtures with known fractions. The same evaluation process was also performed on 5 well-known 16S taxonomic classification algorithms including Qiime2, Kraken2, Mapseq, Idtaxa and Spingo using the same dataset. Results have been discussed in term of evaluation metrics and classified taxonomic levels.

Conclusion:

Compared to current popular public classification algorithms, M-CAMPTM 16S taxonomic classification algorithm provides the most accurate species-level classification of 16S rRNA sequencing data.
Amivantamab: A New Hope in Targeting Non-small Cell Lung Cancer
Authors: Chawla Pooja A. , Billowria Koushal , Das Gupta Ghanshyam
Published: May 2022

Background:

Amivantamab was approved on May 21st, 2021, by United States food and drug administration
with the brand name Rybervant, used particularly for adult patients with exon20 insertion of epithelial growth
factor receptor with locally advanced metastatic non-small cell lung cancer.

Objective:

In this review, we explain the non-small cell lung cancer and molecular distinctions between non-small cell
lung cancer and small cell lung cancer. We also conclude numerous components of non-small cell lung cancer, which
include signs and symptoms of Amivantamab in inhibiting the cancer cell growth, various clinical trials on Amivantamab,
adverse effects, and the contraindications of Amivantamab.

Methods:

A comprehensive literature search was conducted in the relevant databases like ScienceDirect, PubMed,
ResearchGate, and Google Scholar to identify studies.

Conclusion:

Amivantamab is a new bispecific antibody that targets non-small cell lung cancer through two different
pathways, i.e., by binding to epithelial growth factor receptor and mesenchymal epithelial transition factor. Amivantamab
gets tightly bound to Fcγ3R, and thus, mediates the macrophage and NK-cell for the killing of cancer cells.
Biological treatment of Amivantamab shows effectiveness against the epithelial growth factor receptor Exon20 insertions
according to the preclinical data of the animal model.
Diagnostic Value of Potential MicroRNAs in CRC: A Meta-Analysis
Authors: Fathi Sofia , Guessous Fadila , Karkouri Mehdi
Published: May 2022

Background:

MicroRNAs (miRNAs) are small noncoding RNA molecules involved in the post-transcriptional regulation of genes. Deregulated expression of miRNAs is involved in different pathogenic mechanisms, particularly colorectal cancer (CRC) carcinogenesis. Due to their stability and accessibility, circulating miRNAs represent a new family of biomarkers with great potential. Therefore, certain miRNAs can be used as diagnostic biomarkers in CRC.

Objective:

This systematic analysis aimed to explore the individual efficacy of the most investigated blood-based miRNAs for CRC diagnosis, namely miR-21, miR-29a and miR-92a.

Methods:

Articles were retrieved from databases such as PubMed and Google Scholar, and studies designed to evaluate the diagnostic value of microRNAs in CRC were then selected. We subsequently explored the diagnostic accuracy of each miRNA using parameters such as (SE, SPE, PLR, NLR). The meta-analysis was performed using the Review Manager (Revman) 5.4 software and the Meta Disc software.

Results:

Our results suggested that serum miR-21 levels showed great potential as a diagnostic molecular marker. The overall pooled results for sensitivity, specificity, area under the curve (AUC), PLR, and NLR were 78%, 91%, 0.9519, 8.12 and 0.17 respectively.

Conclusion:

miRNAs have become increasingly important in the diagnosis of CRC. Based on these findings, circulating miR-21 levels may have a potential value for early detection and might be used as a novel diagnostic biomarker for CRC.
Potential of Polyphenolic Nutraceuticals in the Management of Glioblastoma
Multiforme
Authors: Raysing Swati Devendra , Gorle Ashish Prakash
Published: May 2022

Glioblastoma Multiforme (GBM) is a malignant central nervous system tumor. GBM is produced
by aggressive proliferation of cells and invasion of normal brain tissue. The current conventional
therapies for GBM include surgery, chemotherapy, and radiation therapies which are challenging and
produce adverse effects. Thus, polyphenolic nutraceuticals are effective natural compounds for preventing
and treating GBM due to their chemoprotective activity. Polyphenols are bioactive, non-nutrient plant
chemicals structurally sub-divided into 5 groups; among these groups, phenolics and flavonoids are
widely studied as they have lesser side effects and a more significant potential to pass the Blood-Brain
Barrier (BBB). These polyphenolic nutraceuticals have the potential to advance current GBM treatment
options. This review throws light on the anti-cancer efficacy of major polyphenol classes (Phenolic acid,
Flavonoids, Stilbenes, Lignans) and discusses their prospective mechanisms of action in GBM.
Polysaccharide-Fibrous Clay Bionanocomposites and their Applications
Authors: Ramesh M.
Published: May 2022

Bionanocomposites are multifunctional materials, which contain biological origin and particles, have nanometer-scale dimensions (1–100 nm) and can be employed in a vast range of applications in fields like tissue engineering, electronic appliances, biosensors, regenerative medicine, drug delivery systems and food packaging due to their remarkable advantage of exhibiting biocompatibility, antibacterial activity, and biodegradability. To develop naturally biodegradable materials like bionanocomposites, several biopolymers are employed in recent years. Polysaccharides are made up of sugar molecules linked together by glycosidic bonds. These polymeric carbohydrates, which are the most prevalent polymers in nature, are gaining interests as a feasible replacement for synthetic polymers in nanocomposite materials manufacturing. Polysaccharides are promising matrix for the production of green nanocomposites due to their biodegradable nature and biocompatible qualities, hierarchical structure, and high film-forming ability. This chapter discusses the processing, properties, characterisation, and applications of bio-based nanocomposites with various polysaccharides functionalized by various nanofillers.
Cellulose based Nano-Composites and Applications
Authors: Tetyana P.
Published: May 2022

Cellulose is an abundant, naturally occurring and bio-degradable material that has been examined as a possible replacement for conventional materials such as plastics which are known to be toxic to the environment. Cellulose nanomaterials, which can be produced directly from cellulose, offer unique properties and structures that have proven useful for a myriad of applications globally. Currently, cellulose nanomaterials have found widespread use in numerous fields including the biomedical, pharmaceutical, packaging, and the food technology industries. Thus, this chapter reports on the properties of cellulose nanomaterials and cellulose nanocomposites and their use in various fields or industries.
Nanomaterials Supported Enzymes: Environmental Applications for Depollution of Aquatic Environments
Authors: Maqbool F.
Published: May 2022

Increased pollution of worldwide water sources as well as difficulties in detecting and treating a wide range of contaminants impose significant health risks. Enzymes with their high activity and selectivity for chemical substrates are one of the promising options among the several technologies for the purification and depollution of aquatic environment. The operational performance of the enzymes is optimized through the immobilization process. Because of the unique physio-chemical properties of nanoparticles, they have become novel and attractive matrices for enzyme immobilization. Variety of composites consist of nanomaterials and enzymes have been discovered in order to improve enzyme stability, activity and functionality making nanosupported enzymes easier to use in depollution of aquatic environment. This chapter reveal different immobilization methods, nanosupports for immobilization and their uses in the depollution of aquatic environments.
Perspectives of Patients and Therapists on Social Media and Digital Data Use in Mental Health Therapy: Thematic Analysis
Authors: Southwick Lauren , Suh Rebecca , Kranzler Elissa , Bradley Megan , Merchant Raina M
Published: May 2022

Background

Incorporating insights from social media into the patient-provider encounter is increasingly being explored in health care settings. Less is known about the utility of these data in mental health therapy.

Objective

This study aims to prospectively investigate and characterize how social media and digital data are used in mental health therapy from both the patient and mental health therapist perspective.

Methods

Patients enrolled in mental health therapy and mental health therapists were interviewed using a semistructured interview guide. All interviews were transcribed and coded using a deductive framework analysis. Themes and subthemes were identified. Participants completed a sociodemographic survey, while mental health therapists also completed a behavioral norms and elicitation survey.

Results

Seventeen participants, that is, 8 (48%) mental health therapists and 9 (52%) patients were interviewed. Overall, participants identified 4 themes and 9 subthemes. Themes were current data collection practices, social media and digital data in therapy, advantages of social media and digital data in therapy, and disadvantages of social media and digital data in therapy. Most subthemes were related to the advantages and disadvantages of incorporating digital data in mental health therapy. Advantage subthemes included convenience, objective, builds rapport, and user-friendliness while disadvantage subthemes were nonreflective, ethically ambiguous, and nongeneralizable. The mental health therapists' behavioral norms and elicitation survey found that injunctive and descriptive normative beliefs mapped onto 2 advantage subthemes: convenience and objectivity.

Conclusions

This qualitative pilot study established the advantages and disadvantages of social media and digital data use in mental health therapy. Patients and therapists highlighted similar concerns and uses. This study indicated that overall, both patients and therapists are interested in and are comfortable to use and discuss social media and digital data in mental health therapy.
Estimating Cardiorespiratory Fitness Without Exercise Testing or Physical Activity Status in Healthy Adults: Regression Model Development and Validation
Authors: Sloan Robert , Visentini-Scarzanella Marco , Sawada Susumu , Sui Xuemei , Myers Jonathan
Published: May 2022

Background

Low cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. Most health care settings use some type of electronic health record (EHR) system. However, many EHRs do not have CRF or physical activity data collected, thereby limiting the types of investigations and analyses that can be done.

Objective

This study aims to develop a nonexercise equation to estimate and classify CRF (in metabolic equivalent tasks) using variables commonly available in EHRs.

Methods

Participants were 42,676 healthy adults (female participants: n=9146, 21.4%) from the Aerobics Center Longitudinal Study examined from 1974 to 2005. The nonexercise estimated CRF was based on sex, age, measured BMI, measured resting heart rate, measured resting blood pressure, and smoking status. A maximal treadmill test measured CRF.

Results

After conducting nonlinear feature augmentation, separate linear regression models were used for male and female participants to calculate correlation and regression coefficients. Cross-classification of actual and estimated CRF was performed using low CRF categories (lowest quintile, lowest quartile, and lowest tertile). The multiple correlation coefficient (R) was 0.70 (mean deviation 1.33) for male participants and 0.65 (mean deviation 1.23) for female participants. The models explained 48.4% (SE estimate 1.70) and 41.9% (SE estimate 1.56) of the variance in CRF for male and female participants, respectively. Correct category classification for low CRF (lowest tertile) was found in 77.2% (n=25,885) of male participants and 74.9% (n=6,850) of female participants.

Conclusions

The regression models developed in this study provided useful estimation and classification of CRF in a large population of male and female participants. The models may provide a practical method for estimating CRF derived from EHRs for population health research.
Peer Review of “Mask Use to Curtail Influenza in a Post–COVID-19 World: Modeling Study” (Preprint)
Authors:   Anonymous
Published: May 2022

UNSTRUCTURED

This is a peer review report related to MS# 31955.
Development of a Density Gauge for Measuring Water and Mud Density based on a Radioactive Technique
Authors: Aloysius Bagyo Widagdo
Published: May 2022

The density or concentration of mud is one of the key variables in studying cohesive sediments, due to being accumulated through settlement and consolidation, as well as resuspended through erosion. This indicates that the proper measurement of sediment density is important. Therefore, this study aims to evaluate the accuracy of density measurement by using the gamma-ray attenuation method as a non-intrusive technique. For Compton Scattering, gamma-ray attenuation was effectively independent of mineralogy, subsequently depending on only the electron density of the material, which is directly related to the bulk density of the mixture. Based on the results, the advantages of utilizing the nucleonic density gauge indicated that the technique was non-intrusive and very flexible for many experimental arrangements, as well as the high accuracy of measurements with errors less than 1%.
Finite Element Analysis of Bi-directional Shear Panel Damper with Square Hollow Section under Monotonic Loading
Authors: Ali Awaludin  , Angga Fajar Setiawan  , Satyarno Imam , Wu Shuanglan  , Haroki Yusuf
Published: May 2022

This study aims to determine the finite element analysis of a BSPD-SHS (bi-directional shear panel damper with a square hollow section) device, to dissipate the seismic excitation energy through the lateral relative displacement between the pier and girder of the simple support bridge. The configuration of the square hollow section is also performed for a double role, such as web panel and flange, indicating the expectations to reduce the seismic force within the lateral and longitudinal directions. In the preliminary development phase, the finite element analysis was conducted under monotonic loading, to examine the skeleton curve characteristics and internal stress action on resisting seismic force. The characteristics of this curve include elastic stiffness, shear strength, post-yield behavior, and internal stress distributions. Based on the evaluation of the BSPD-SHS slenderness effect, the variation of depth-thickness ratio was considered between 25 to 67. To investigate the fitness of the theoretical shear strength formulation, two different hardening roles of the metal plasticity model were subsequently compared in this study, including the elastic-perfectly plastic and isotropic/kinematic techniques. Furthermore, the effect of the restrained degree of freedom idealization on the top base plate was captured. This indicated that all specimens model with the restrained top base plate achieved stable post-yield stiffness. In implementing the unrestrained top base plate, this stiffness was achieved when the web slenderness ratio equaled 25. The differences observed between the hardening roles also generated a slight yield shear strength discrepancy. However, significant differences occurred in the post-yield shear strength. The shear resistance proportion of the stress components was also accurately quantified with an analytical stress integration. Based on the restrained top base plate, the flange tension field generated a significant contribution to the post-yield shear resistance.
Private Datapods: Web 3.0 does not Automatically Mean Blockchain Decentralization
Authors: Castell Dr. Stephen
Published: May 2022

ICT and blockchain professionals must be careful not to equate Web 3.0 automatically with blockchain, or vice versa. That is an incorrect equivalence. Blockchain is certainly one possible architecture on which to base a Web 3.0 implementation. However, the essence of Sir Tim Berners-Lee’s decentralized Web 3.0 concept is nothing automatically or implicitly to do with blockchain, but, rather, is focused on the important idea of Private Datapods. The author’s own Zykme / ZykPass invention is an available working hybrid App (beta test version) compliant with this Web 3.0 Private Datapod fundamental design principle, ushering-in a new era of decentralized user-controlled and user-owned social media based on secure P2P personal data communications, implemented using edge computing. This article describes the architecture and future development of this invention. This includes potential addition of a future blockchain-based ‘social media’ ZykToken, awarded to, and owned and tradeable by, each Zykme / ZykPass user, implementing the author’s novel CapChere (Customer Corporation) IP and business ownership structure. This contends to be a transformative, socially useful re-purposing of traditional industrial capitalism in which all are winners.
Corporative Governance in an International Context
Authors: Jwmaa Swran Jawamir , Kanabi Idrees Sadeq , Younus Saif Qudama , Ismail Zaid Saad , Faieq Hawta Tareq , Othman Baban Jabbar , Mahmood Rozhgar Khorsheed , Gardi Bayar , Jamil Diyar Abdulmajeed
Published: May 2022

The purpose of this research is to investigate the impact of corporative governance on international context in private business in Erbil. A random sampling technique was used, where all employees had equal chances of being selected for the sample. The study was carried out at private business in Erbil. The researchers distributed 170 questionnaires, only 156 questionnaires were received and from 156 questionnaires only 144 questionnaires were completed properly. Corporative governance can be an effective tool that many countries across the world can use to reduce such disparities evident in most firms. The findings revealed that the correlation between corporative governance factor as independent factor and International Context as dependent factor. The value of R for the Corporative governance = .386** which indicates that turnover is significantly but has weak correlation with International Context. Moreover, it was found that the value Beta for turnover = .386> 0.01, this indicates that turnover factor was positively and weak correlation with corporative governance.
¿Es necesaria la filosofía en las escuelas? Percepción de docentes y estudiantes de escuelas públicas
Authors: Gutiérrez Rojas Eliana , Morón Castro Camilo
Published: May 2022

Este estudio se centra en analizar la situación de la enseñanza de la filosofía en las aulas de educación media en la ciudad de Barranquilla (Atlántico, Colombia), teniendo en cuenta la percepción de docentes y alumnos en el año 2021. La muestra constó de 8 docentes y 8 estudiantes que fueron entrevistados por medio de un guion de preguntas validado por expertos. Para el análisis de la información, se siguió una metodología de diseño fenomenológico y enfoque cualitativo. Los hallazgos muestran una serie de obstáculos en la formación derivados del desconocimiento de estrategias didácticas en filosofía, la conservación del paradigma educativo histórico-filosófico y doctrinal y el perfil de los encargados de la asignatura de filosofía, además de estar alejada de los lineamientos de las autoridades educativas gubernamentales fundamentados en la enseñanza por problemas.
Different Exercise Intensity Associates with Varied Disease Biomarkers of Guts-Microbiome Genera Change in Rats: Preliminary Study
Authors: Tansathitaya Vimolmas , Sarasin Witchana , Phakham Tanapati , Sawaswong Vorthon , Chanchaem Prangwalai , Payungporn Sunchai
Published: May 2022

The microbiome, a community of microorganisms in the body, is currently used as a biomarker in many disease prognoses. Prevotella, Turicibacte, Bacteroides, Firmicutes/Bacteroidetes are frequently used as a biomarker for rheumatoid arthritis, colorectal cancer, and obesity in ordered. The amount of gut microbiota can be changed depending on various factors such as diet, lifestyle, and exercise. However, there is unclear on how the exercise is really effective to be a disease prevention. The present study aims to investigate the different exercise intensities on gut microbiome abundance changes that could be used as a disease biomarker. Eighteen Sprague-Dawley rats were arranged (n=6 per group) into 3 exercise intensity levels on treadmills including non-exercise group, high -exercise group (20 – 25 m/min for 60 min), and light-exercise group (10 – 15 m/min for 60 min). Rats were weighted every 2 days and stools were collected and preserved in DNA/RNA shield each week. The bacterial 16S rDNA of microbiome in feces samples was sequenced and analyzed. After week eighth of the interventions, from operational taxonomic unit (OTUs) abundance, we found that the relative abundance in bacterial genera in Prevotella and Firmicutes/Bacteroidetes were significantly correlated with the experiment timepoints in different exercise intensities (Pearson’s correlation, P<0.05) compare to other genera. The exercise intensities and exercise durations can affect the relative abundance in the bacteria genus which the abundance genus Prevotella and Firmicutes/Bacteroidetes could be used as a new standard biomarker in exercise as a disease prevention and exercise prescriptions. From the funding limitations, we could conclude the research results based on our data and statistic. Future research should utilize a longer investigation period.
Optical Character Recognition for Image & Handwriting to Text Conversion
Authors: Pathak Vasundhara , Sharma Shriyansh , Goel Tanishka
Published: May 2022

Abstract: This paper combines the functionality of Optical Character Recognition and speech synthesizer. The idea is to develop stoner friendly operation which performs image to text conversion. Objective The advantage of proposed system that overcomes the disadvantage of the prevailing system is that it supports multiple functionalities like editing and searching. It also adds benefit by providing heterogeneous characters recognition
To Count the Person in The Classroom with Identity by Using IoT Technique
Authors: Srivastava Vaibhav , Sundevesha Manish , Shrivastav Pradeep , Randhe Prof. Kirti
Published: May 2022

Abstract: In Todays time, when maintaining the classes and scheduling time for students of respective subject is dynamically hard, Colleges can’t able to give their 100% because the data of student attendance is not perfectly arranged, hence unable to provide guest lecture, external workshop, and many more extra circular activities to its peak (as much as possible). If we do such task manually then the management will become a very time consuming and difficult task. In today’s modern days algorithm like HOG, CNN, fisherfaces, Eigenfaces, and etc. are examples of one of the many algorithms that are used in these modern days and our system take the count the number of students in a digital format. Our system is used to identify the person who is going in a class and count total number of persons present in a classroom. The count is stored into the person profile or attendance ledger of that person we use google cloud platform as our Database. We use a Raspberry Pi which make our system portable and hence, it’s easy to setup our system anywhere and very easily in the classroom. Our Raspberry Pi is connected to either College WIFI or College Ethernet so that our Realtime system send email to person that are present, if he enters late in the class then a mail will also come that you are late, if the person wants more detail about their attendance, then he/she check our android app where its shows no. of days present, percentage of person attendance and which days he/she is present and absent and etc. Keywords: IOT, Machine Learning, Pi Module Camera, Raspberry Pi &OpenCV
IoT Based Emergency Button for Women Safety
Authors: Chikhale Sanket , Yadav Aniket , Shaikh Faraz , Dounde Prajakta , Raskar Ishwari
Published: May 2022

Abstract: Fundamental to IoT is the instant collaboration that happens between these smart devices. The beauty behind having a network of interconnected devices is that they can all work together to provide real solutions that are much greater than the sum of their parts. IOT based products are always connected and constantly communicating with each other. They regularly exchange information using wired and wireless networks, which helps make our lives easier and safer. When IoT based smart home security systems are used to safeguard our home or possessions, it’s akin to having our favorite reliable friend dutifully watching over our home or pets in our absence. Except it’s actually way better than that, because unlike our well-meaning friend or neighbor, smart home security systems are always present and are ready to instantly alert us of any signs of danger. Smart products, like Nest Lab’s smoke and carbon monoxide alarm, sounds an alert when it detects high levels of CO, and then warns us of the location of the danger. It’s no wonder that Google acquired Nest Labs for a whopping $3.2 billion! Other companies like Canary offer connected smart home security systems that are now a part of a growing trend: using IoT technology to create safety solutions to protect what’s most valuable to us.
Detection of VPNs using Machine Learning
Authors: Srivastava Ms. Shipra , H Harigovind , Modi Devvrat , Salim Bassam , Mathur Yashraj
Published: May 2022

Abstract: The nature of the tools used by criminal actors to hide their identities has made it is very challenging to detect unauthorized users. Network security is any move an association makes to forestall vindictive use or coincidental harm to the organization's private information, its clients, or their gadgets. The objective of organization security is to keep the organization running and valid for every authentic client. Since there are such countless ways that an organization’s security can be compromised, network security includes a wide scope of rehearses. Most of normal assaults against networks are intended to acquire admittance to data, by keeping an eye on the correspondences and information of clients, rather than to harm the actual organization. However, assailants can do more than taking the information. They might have the option to harm clients' gadgets or control frameworks to acquire actual admittance to offices. This leaves the association's property and individuals in danger of damage. Network security extensively comprises of approaches, cycles and practices embraced to forestall, recognize and screen unapproved access, abuse, change, or disavowal of organization available assets. This work presents computational model that can detect the use of virtual private networks to gain unauthorized access.
Institute Recommendation System Using ML
Authors: Orse Asmita , Suryawanshi Nikhil , Shrivastav Harsh , Bajpai Pratik , Patil Prof. Megha
Published: May 2022

Abstract: To choose any educational organization is one of the major or foremost decision for every student because it plays a vital role for growth and development of students and it also helps to boosts their career. SSC is one of the crucial stage of every student’s life in India. It decides the future of every student career. SSC decides in which stream the student will make his career. SSC scores of the student decides in which college the student will take admission. College selection is second step after SSC in student’s career. The college selection plays an important role as college selection requires a lot of searching work. Students search for the various aspects like college campus, teaching staffs, extracurricular activities in colleges, infrastructure of colleges, etc., even the reviews of college is searched to get extra confirmation about the genuinely of details. Searching all the details requires a large amount of time. Hence, it’s important to reduce this manual work and automate this with help of software.
An approach for Preserving Privacy in Public Auditing of Cloud data
Authors: Mugal Shreya , Chhajed Prof. K. K.
Published: May 2022

Abstract: Cloud users can remotely store their data and appreciate the on demand high quality applications and services from a shared pool of configurable computing resources, regardless of local data storage and maintenance. However, the fact that users no longer have physical possession of the out sourced data makes the data integrity protection in Cloud computing a formidable task, especially for users with constrained computing resources. This paper study the problem of ensuring the integrity of data storage in Cloud Computing. In particular, wet ask of allow in gathird party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic datastored in the cloud. To securely introduce an effective third-party auditor (TPA), and determine various techniques and algorithms for strengthen the Security. Keywords: TPA, Cloud Computing, CSP, RSA
Enhanced Super-Resolution Using GAN
Authors: Kumar Chandan , Choudhary Amzad , Singh Gurpreet , Gupta Ms. Deepti
Published: May 2022

Abstract: Super-resolution reconstruction is an increasingly important area in computer vision. To eliminate the problems that super-resolution reconstruction models based on generative adversarial networks are difficult to train and contain artifacts in reconstruction results. besides the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks. However, the hallucinated details are often accompanied with unpleasant artifacts. This paper presented ESRGAN model which was also based on generative adversarial networks. To further enhance the visual quality, we thoroughly study three key components of SRGAN – network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN). In particular, we introduce the Residual-in-Residual Dense Block (RRDB) without batch normalization as the basic network building unit. Moreover, we borrow the idea from relativistic GAN to let the discriminator predict relative realness instead of the absolute value. Finally, we improve the perceptual loss by using the features before activation, which could provide stronger supervision for brightness consistency and texture recovery. Benefiting from these improvements, the proposed ESRGAN achieves consistently better visual quality with more realistic and natural textures than SRGAN.
COVID-19 Future Forecasting using Machine Learning
Authors: Samani Nidhi , Yadav Komal , Bhamare Yash , Patil Meghana , Halkarnikar Dr. P P
Published: May 2022

Abstract: Machine learning (ML) based forecasting mechanisms have proved their significance to anticipate in perioperative outcomes to improve the decision making on the future course of actions. The ML models have long been used in many application domains which needed the identification and prioritization of adverse factors for a threat. Several prediction methods are being popularly used to handle forecasting problems. This study demonstrates the capability of ML models to forecast the number of upcoming patients affected by COVID-19 which is presently considered as a potential threat to mankind. In particular, four standard forecasting models, such as linear regression (LR), least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and exponential smoothing (ES) have been used in this study to forecast the threatening factors of COVID-19. Three types of predictions are made by each of the models, such as the number of newly infected cases, the number of deaths, and the number of recoveries in the next 10 days.
Vibration Analysis of Composite Internal Door Panel of a Car
Authors: Jadhav Ashish R , Jagtap Aniket P , Jagtap Nandini G , Surve Rutav S , Kaldate Prof. A. P.
Published: May 2022

Abstract: The main objective behind this paper is to develop a suitable model of internal door panel for cars, to conduct a static structural analysis of internal door panel by finite element method and to compare the performance of glass fiber material with previously recommended materials of internal door panel. This paper deals with the mechanical behavior and vibration analysis of glass fiber-based polymer composite beam structures. Glass fiber has been widely used for many applications due to its high strength, flexibility, stiffness and resistance to chemical this extended work the inactive basic Limited Component Investigation of inside entryway board of a vehicle by considering glass fiber composite materials was conducted. The entryway board of the vehicle was utilized to create the geometric show of the inward entryway board by CATIA V5 R20 modeling program. This 3-D geometric demonstration was imported to utilize ANSYS Workbench 19.0. Model analysis of the internal door panel has been done using ANSYS software.
Survey Paper on Rolling Barrier System
Authors: Patil Prof. Rajvardhan , Pawar Devesh , Walke Abhishek , Tenkale Vaibhav , Patil Sohan
Published: May 2022

Abstract: India is emerging country in all sector India’s transport sector is large and diverse. The latest emerging technologies for road safety working on waysto avoid orreduced road accidentsto road userswith special concern by minimizing the causes of road accidents. So in this paper study is carried out to minimize or reduce adverse effects of road accidents with the help of rolling barrier system. The roller barriers are extremely effective and it’s implementation has given manifested results in minimizing the road accidents. Rolling barriers provides cushioning effect during crash and reducesthe high speed effect constitutes material resilience with stiffness and have other performance characteristics that reduces injury to individuals and damage to their vehicles. Keywords: Accidents, Rolling Barrier, Stiffness, Resilience,Crash Cushioning
Construction of Network Security enforcement Virtual Simulation Experiment and Teaching Platform
Authors: Premchander Dr. Tudi
Published: May 2022

Abstract: In view of the issues in virtual simulation experiment teaching of network security enforcement, this paper analyzes the need of construction of the virtual simulation experiment teaching platform, that expounds the construction content of virtual simulation experiment platform from 3 aspects of virtual simulation course system, experimental area and teaching mode. Network security enforcement virtual simulation experiment and teaching platform is made with 3 core experimental modules of network security scene enforcement, electronic data scene forensics, and investigation of cyber-crime cases. The coaching of students’ higher order thinking and actual combat ability is reinforced publically security schools. Keywords: Virtual simulation, Experimental teaching platform, Network security law enforcement.
Stock Price Prediction and Analysis using Machine Learning Techniques
Authors: Deshpande Rucha , Lunkad Divyank , Kunjir Madhura , Ingle Samiksha
Published: May 2022

Abstract: Stock market is one of the most sought-after investment options today. Investing in the stock market has the potential to multiply people's money in a short period of time, but it also carries many risks. To be successful in the stock market, it is necessary to conduct extensive research about the market and the forces influencing it. This examination involves a review of historical stock prices as well as real-time market developments. When deciding the position in the market, investors need to make an informed choice. Market-related information may be obtained from a variety of sources, including news articles, stock research websites, apps, and television channels. However, stock movement prediction by taking into consideration the elements influencing it would undoubtedly assist investors in making sound decisions. The research area of stock movement prediction has seen numerous advancements throughout the years. In the domain of machine learning, various methods of stock price prediction have been introduced. In this paper, we have discussed different approaches to stock movement prediction based on diverse factors and technical indicators. We also propose a method for detecting market trends, which is a critical aspect in maintaining long-term market positions. Keywords: Machine Learning, Stock Market, Prediction, Classification, Technical Indicators, Trend prediction
Design and Fabrication of Automatic Coe Feeding Machine
Authors: Patil Kshitij , Pardeshi Sanketsing Sunilsing , Lokare Swapnil Sharad , Jadhavar Sanket Shivaji , Patil Mrs. R. S.
Published: May 2022

Abstract: Conventionally the feeding of the cattle is manual which is time consuming. In this project, an automatic cattle feeding system is introduced where food feeder follows the path through a predetermined distance and places the feed to the cattle by the side of the feed fence. The prototype is developed using Arduino circuit for the operation of feed mechanism with certain time space. The motors are interfaced to operate in either direction. A rail bogie is operated by a DC motor to feed the cattle at certain time space. This mechanism is basically controlled by pulling mechanism by winding the rope around the motor operated shaft.
Research Paper on AI in Driving
Authors: Shukla Bhavesh Ajaykumar , Khose Prathamesh Gorakhnath
Published: May 2022

Abstract: AI in driving is introduced as a self-driving in automobile industries. This research paper is presents a scient metric and bibliometric analysis on self-driving cars. A self-driving car (sometimes called an autonomous car or driverless car) is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use. Companies developing and/or testing autonomous cars include Audi, BMW, Ford, Google, General Motors, Tesla, Volkswagen and Volvo, Tata Motors and Mahindra. Google's test involved a fleet of self-driving cars -- including Toyota Prii and an Audi TT -- navigating over 140,000 miles of California streets and highways. Through an examination of quantitative empirical evidence, we explore the importance of Artificial Intelligence (AI) as machine learning, deep learning and data mining on self-driving car research and development as measured by patents and papers. Alongside the exponential growth in the rate of inventive activities and scholarly efforts, we find evidence for a rapid and meaningful shift in the application of the technologies related to data gathering and processing for the purpose of self-driving cars after 2009. We show that this shift mirrors major changes in the landscape of innovators as well as increasing scholarly attention to the ethical, legal and social aspects of self-driving cars. Research and innovation relating to self-driving seem to be increasingly defined in terms of artificial intelligence, which neglects some aspects of future sociotechnical systems that may be required to realise the potential of the technology. Keywords: AI car, self-driving, Simulation test, autonomous cars, autopilot car.
Handwritten Letter Recognition using Artificial Intelligence
Authors: D Jeevitha , S Muthu Geethalakshmi , I Nila , V Santhoshi
Published: May 2022

Abstract: Images are easily processed and analysed by the human brain. When the eye sees a particular image, the brain is able to instantly segment it and recognize its numerous aspects. This project proposes the Deep Learning conceptual models based on Convolutional Neural Network (CNN). A comparison between the algorithms reveals that the handwritten alphabets, classified based on CNNs outperforms other algorithms in terms of accuracy. In this project, different architectures of CNN algorithm are used: Manual Net, Alex Net, LeNet Architecture. These architectures contain a convolution layer, max pooling, flatten, feature selection, Rectifier Linear Unit and fully connected softmax layer respectively. The image dataset with 530 number of training images and 2756 numbers of testing images are used to experiment the proposed network. The best accuracy and loss efficient model will be deployed in the Django framework in order to create a user interface for giving the character to be identified and receiving the output result of identified character. Keywords: Handwritten Recognition, Alphabets, Deep Learning, TensorFlow, CNN, Django.
2D Nanomaterials: A Potent Antiviral Agent
Authors: Mukherjee Nivedita
Published: May 2022

Abstract: In this study, we have thoroughly studied the potentiality of 2D nanomaterials against different viruses. The extremely high surface-volume ratio is beneficial for surface-related reactions like catalysis, this provides flexibility and other intrinsic properties. The antimicrobial activity of nanomaterials is well established. Here we go through different 2D nanomaterials, showing a variety of antiviral actions through the generation of ROS and oxidative stress. The antiviral action of nanosheets has been attributed to their negative surface charge and the presence of a layered nanoscale morphology with sharp edges and corners. Due to their strong electrostatic activity with envelope and non-envelop viruses the sharp edge causes physical damage, and protein disruption causes virus damage. 2D nanomaterials have a wide opening in the field of research and development. Keywords: Nanomaterials, Antiviral agent, 2D nanoparticles, Nanosheets, Graphene
French Phraseological Units Numerological Component
Authors: Akmalovna Shukurova Rano , Aziza Khayrullaeva
Published: May 2022

Annotation: Components in the phraseological units of the French language. A comparative analysis of French and Russian phraseological units with a numerological component from zero to nine, the results of which are presented in the article, makes it possible to judge the similarities and differences in the cultural connotation of numbers. Keywords: Phraseological units; numerological component; French; Intercultural connotation.
Donald Trump’s grammar: How to trivialize facts on coronavirus
Authors: Fanani Achmad
Published: May 2022

This current research reveals how President Trump grammatically constructed his clauses to trivialize the coronavirus (COVID-19). This research uses a discourse analysis approach with a qualitative design. The research data are President Trump’s trivializing clauses (192 main clauses) taken from his speeches, press interviews, remarks, and tweets from January 2020 to June 2020. Hallidayan SFL and Straker’s technique of trivialization are used as the basis of analysis. The result shows that most of the trivializing clauses are declarative while the others are interrogative and imperative. It is also identified that the declarative mood (statements of opinion and fact) reflects the techniques of sneaking through, trivializing the target, and discounting the target. The interrogative mood (rhetorical questions) demonstrates the technique of discounting the target. In addition, the imperative mood (directives) reflects the technique of sneaking through. Finally, the result also shows that oversimplification, severity decrease, and exaggeration characterize President Trump’s trivializing clauses.