457 research outputs found
Cyberbullying Framework and Trends on Social Media Platforms: An Analysis through Indian Perspectives from Real-World Data
Cyberbullying has become a prevalent problem that has deep effects on people's mental health and social interactions, especially on social media. This study presents an examination of cyberbullying examples and patterns inside the Indian setting, using genuine information removed from different virtual entertainment stages. The research aims to shed light on the distinct cultural, social, and technological factors that influence cyberbullying dynamics in the region by focusing on Indian perspectives. The study examines the prevalence, characteristics, and dynamics of cyberbullying incidents on social media platforms used by Indian users through a combination of descriptive, content, and network analysis. The findings shed light on the nature and extent of cyberbullying in India, as well as the types of cyberbullying behaviors, the demographics that are targeted, and popular platforms. Besides, the review investigates fleeting patterns, geological varieties, and social subtleties in cyberbullying designs, offering significant bits of knowledge for policymakers, teachers, and virtual entertainment organizations looking to address cyberbullying successfully. This research contributes to the development of targeted interventions and strategies aimed at creating a safer and more inclusive online environment for Indian users by comprehending the specific difficulties and dynamics of cyberbullying within the Indian framework
Association rule hiding using integer linear programming
Privacy preserving data mining has become the focus of attention of government statistical agencies and database security research community who are concerned with preventing privacy disclosure during data mining. Repositories of large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. In this paper, we present a constraint-based optimization approach for hiding a set of sensitive association rules, using a well-structured integer linear program formulation. The proposed approach reduces the database sanitization problem to an instance of the integer linear programming problem. The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive rules. We also present a heuristic sanitization algorithm that performs hiding by reducing the support or the confidence of the sensitive rules. The results of the experimental evaluation of the proposed approach on real-life datasets indicate the promising performance of the approach in terms of side effects on the original database
On Classes of Neighborhood Resolving Sets of a Graph
Let G=(V,E) be a simple connected graph. A subset S of V is called a neighbourhood set of G if G=\bigcup_{s\in S}<N[s]>, where N[v] denotes the closed neighbourhood of the vertex v in G. Further for each ordered subset S={s_1,s_2, ...,s_k} of V and a vertex , we associate a vector with respect to S, where d(u,v) denote the distance between u and v in G. A subset S is said to be resolving set of G if for all . A neighbouring set of G which is also a resolving set for G is called a neighbourhood resolving set (nr-set). The purpose of this paper is to introduce various types of nr-sets and compute minimum cardinality of each set, in possible cases, particulary for paths and cycles
A prospective study on prescribing pattern of drugs in geriatric patients in the department of medicine in a tertiary care center
Background: India stands at 3rd position with large elderly population in the world. Elderly population has special problems related to health, social support, and economic security. Comorbidities in elderly people are frequent, which require use of multiple medications which increases the number of inappropriate medications   noncompliance, economic burden, adverse drug reactions (ADRs), and drug interactions. The overall incidence of ADR is two to three times higher due to physiological and pharmacological variations. Currently used screening tools for inappropriate prescription in old age are: Beers criteria and inappropriate prescribing in the elderly tool (IPET).Methods: A prospective observational study of elderly patients of either sex admitted in the medicine ward, conducted from May 2019-November 2019. A total of 102 prescriptions were collected and analysed. Data was analysed using Microsoft excel.Results: In this study most of the patients (67 out of 102) were in the age group 65-70 years with male population (73%) dominance. Most of the patient were admitted due to cardiovascular (35.84%) and respiratory system (14.15%) disorder. Anti-diabetics (17.64%) followed by anti-microbials (14.24%) were the most commonly prescribed medicines in this study. Our study revealed poly pharmacy in geriatric patients with an average number of drugs per prescription being 6.07. According to BEER’s criteria 3.47% of total drugs prescribed were inappropriateConclusions:  In this study most of the patients had co morbid conditions, cardiovascular disease and diabetes being the common cause led to polypharmacy. A high number of potential prescription errors were found.
A NEW HIGH PERFORMANCE THIN LAYER CHROMATOGRAPHIC METHOD DEVELOPMENT AND VALIDATION OF DAPAGLIFLOZIN IN BULK AND TABLET DOSAGE FORM
ABSTRACT
Objective: To develop a new simple, selective and precise high-performance thin layer chromatographic method for determination of Dapagliflozin (DAPA) in bulk and tablet dosage form
Methods: The present study describes development and validation of High performance thin layer chromatographic method for DAPA. The chromatographic separation was carried out on Merck precoated silica gel aluminium plate 60 F254 using Chloroform: Methanol (9:1v/v) as mobile phase. Quantitative determination of drug was carried out by densitometric scanning of plates at 223 nm using Camag TLC Scanner.
Results: The chromatographic condition shows compact band with the retention factor for dapaglifloxin as 0.21 ± 0.004. The method was validated as per ICH guidelines for linearity, accuracy, precision and robustness. Response was found to be linear in the concentration range of 400 ng/ band to 1200 ng/band with linear regression value of 0.9953 with respect to peak area and concentration value The LOD and LOQ was found to be 1.2083 ng/band and 3.6616ng/ band. The percentage assay was found to be 100±0.05.
Conclusion: This method under statistical analysis proved a selective, repeatable and accurate analysis of the drug. This method can be used for quantitative analysis of dapaglifloxin in the bulk drug and in tablet.
 
Cerebro-placental ratio as a prognostic factor of fetal outcome in women with hypertensive disorders complicating pregnancy during third trimester
Background: CPR is emerging as an important predictor of adverse pregnancy outcome and helps in management of high risk pregnancy. Therefore we undertook the study to find the correlation of CPR with perinatal outcomes in women with hypertensive disorder complicating during third trimester.Methods: 128 patients with hypertensive disorder of pregnancy, ≥32 weeks of singleton gestation, were randomly selected during their hospital visit. They were subjected to USG Doppler study to calculate MCA/UA pulsatility index-CPR. The CPR1 as normal. These results were compared with the perinatal outcome and adverse fetal outcome.Results: The present study revealed that the incidence of adverse outcomes like Apgar score <7 (36.5%), still birth (15.9%), NICU admission (69.8%) and LBW i.e. <2500 gm (68.3%) were significantly higher in abnormal CPR than normal CPR.Conclusions: Abnormal CPR is valuable in predicting the outcome of hypertensive disorders in pregnancy. CPR is an easy procedure which can be included in the routine antenatal sonographic evaluation to predict poor perinatal outcome and to detect or recognize those fetuses at risk
Maternal pregnancy associated plasma protein-A (PAPP-A) and uterine artery Doppler changes as predictors of pre-eclampsia: a prospective observational study from a teaching hospital in Mysore, Karnataka, India
Background: Hypertensive disorder affects 10-12% of pregnancies. Identifying women, who are at risk is conducive to prompt gestational management. PAPP-A is a protein complex produced by the developing trophoblasts. Low levels of PAPP-A at 10–14 weeks is a marker of impaired placentation and a smaller placental mass. Doppler imaging permits non-invasive evaluation of the uteroplacental circulation and is invaluable in the management of high-risk pregnancies. The uterine artery Doppler screening identifies patients at risk for developing preeclampsia. To study the association of PAPP-A and the uterine artery Doppler changes as predictor of pre-eclampsia in pregnant women at 11-14 weeks of gestation.Methods: This was a prospective study of 150 pregnant women presenting at 11-14 weeks of gestation for a prenatal check-up. After considering the inclusion and exclusion criteria, serum samples for PAPP-A were assayed. Ultrasound Doppler was used to obtain uterine artery flow velocity waveforms and mean pulsatility index and resistance index of uterine arteries were calculated. Cases were followed up till term and observed for development of pre-eclampsia.Results: 48.6% had low serum PAPP-A levels, in which 77% developed PE. The Mean PI and RI is 2.34±1.16 and 0.58±0.1 respectively. 30% women with abnormal PI values and 24% of women with abnormal RI values developed PE.Conclusions: The combination of maternal history with low serum PAPP-A levels and abnormal uterine artery Doppler at 11-14 weeks can be used as predictor of pre-eclampsia
Study of anti-inflammatory activity of Ficus racemosa linn stem bark extract in albino rats
Background: Inflammation is part of the complex biological response of vascular tissues to harmful stimuli. Though there are standard anti-inflammatory drugs like aspirin, diclofenac, etc., these are not free of side effects. This has led to an increase in demand for natural products with anti-inflammatory activity having less side effects. Hence the study was conducted to evaluate the anti-inflammatory activity of ethanolic extract of Ficus racemose (EEFR) in albino rats.Methods: Healthy albino rats of either sex were divided into 4 groups of 6 animals each. Group1-control, group 2-diclofenac sodium 2 mg/kg and group 3 and 4 EEFR (200 and 400 mg/kg respectively), anti-inflammatory activity was evaluated by Carrageenan induced paw oedema: formalin induced-peritonitis and cotton pellet induced granuloma model for in vivo activity and protein denaturation test for in vitro activity.Results: EEFR exhibited significant in vitro (p<0.001) anti-inflammatory effect at the dose of 200 and 400 mg/kg. EEFR produced 61.37% inhibition at the dose of 400 mg/kg and diclofenac (standard drug) produced 62.95% of inhibition after 3 hours of drug treatment in carrageenan induced paw oedema. The exudate volume was decreased in formalin induced peritonitis by EEFR and diclofenac significantly (p<0.001). In cotton pellet induced granuloma EEFR (400 mg/kg) and diclofenac showed decreased formation of granuloma by 28.36% and 28.00% (p<0.001) respectively.Conclusions: EEFR has significant anti-inflammatory activity in both acute and chronic model in a dose dependant manner in comparison with standard drug
Multivariate analysis of genetic diversity in Phytophthora pod rot resistant exotic cocoa germplasm
The current research work was carried out to evaluate the genetic diversity associated with thirty cocoa accessions resistant to Phytophthora. The cluster analysis and principal component analysis evaluated the genetic variability among the different genotypes. The highest number of genotypes were observed in cluster III (8) when qualitative traits were considered. In quantitative cluster analysis, most of the genotypes were placed in separate clusters due to high variability in the germplasm. Principal component (PC) analysis showed that the first three PCs with more than one Eigen-value contributed to 79.9 per cent of variability for different traits. When qualitative and quantitative characters were considered along with resistant reaction, clusters with genotypes highly resistant to Phytophthora pod rot were observed. Hybridization programme involving these resistant hybrids belonging to diverse clusters will result in high yielding hybrids with ample resistance
DYNAMIC DETECTION OF DESIGN INCONSISTENCY DURING SOFTWARE DEVELOPMENT USING DAID APPROACH
Evolution of software has lead to the fast growth of technology whose impact can be witnessed in all the domains of scientific and engineering applications. Hence engineering high quality software is one of the core challenges of all IT industries. The software models which are being used for the development of the software products may lead to inconsistencies. Nevertheless, theexistence of several methodologies during the development process in order to overcome inconsistencies operates at static mode leading towards expensive nature of rework on those inconsistencies. Therefore, this paper presents a dynamic model which resolves the aforementioned issue by capturing inconsistencies dynamically in an automated mode using Dynamic automated inconsistency detection (DAID) model. The implementation results of DAID capture the design inconsistencies dynamically at the time of their injection points in lieu of inconsistency detection during validation testing. This approach of dynamic design inconsistency detection reduces cost, time and its associated overheads. Further implementation of DAID in an automated mode increases productivity, quality and sustainability in IT industries
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