HCU400: An Annotated Dataset for Exploring Aural Phenomenology Through Causal Uncertainty

The way we perceive a sound depends on many aspects-- its ecological frequency, acoustic features, typicality, and most notably, its identified source. In this paper, we present the HCU400: a dataset of 402 sounds ranging from easily identifiable everyday sounds to intentionally obscured artificial ones. It aims to lower the barrier for the study of aural phenomenology as the largest available audio dataset to include an analysis of causal attribution. Each sample has been annotated with crowd-sourced descriptions, as well as familiarity, imageability, arousal, and valence ratings. We extend existing calculations of causal uncertainty, automating and generalizing them with word embeddings. Upon analysis we find that individuals will provide less polarized emotion ratings as a sound's source becomes increasingly ambiguous; individual ratings of familiarity and imageability, on the other hand, diverge as uncertainty increases despite a clear negative trend on average

KNOWLEDGE OF GOVERNMENT AND PRIVATE PRIMARY HEALTH CARE WORKERS ON NEWBORN CARE COMPONENTS: A QUESTIONNAIRE-BASED CROSS-SECTIONAL COMPARATIVE STUDY

ABSTRACTObjective: This study was done to evaluate the knowledge of primary health-care workers about the newborn care components.Methods: The Institutional Ethics Committee approval was obtained, and a cross-sectional study was carried out among the primary health-careworkers of Karaikal using a pretested questionnaire from January 2015 to March 2015. The questionnaire contained questions on various domains ofnewborn care components. The study participants were explained about the study. Verbal informed consent was obtained, and the questionnaire wasintroduced to 383 health-care workers. The answered questionnaires were collected and analyzed.Results: A total of 349 participants (192-government employees; 157-private employees) were willing to take part in the study. Most (54.7%) of thegovernment participants were nurses and auxiliary nurse midwives (43.2%) whereas the private sector participants were predominantly (79%)nurses. The knowledge level about some of the newborn care components, namely, positioning and attachment, advice on discharge, time of follow-upcheckup, bad child rearing practices, and danger signs of newborn were assessed to be predominantly inadequate among a majority of health workersof both sectors. 22.29% and 41.1% of the private health-care workers and government health-care workers respectively, were having an overalladequate knowledge (overall score >75%) on newborn care components. Knowledge of the government health workers was significantly better thanprivate health-care staff (P < 0.001).Conclusion: Knowledge is found to be inadequate among health-care workers on some newborn care components which necessitate measures toimprove.Keywords: Newborn care, Nurses, Midwives, Inadequate knowledge, Training programs.Â

Contraceptive awareness in post-natal patients in KIMS, Bangalore

Background: Family planning can avert more than 30% of maternal deaths and 10% of child mortality if couples spaced their pregnancies more than two years apart. India was the first country in the world to launch the family planning programme in 1951. There exists a KAP gap i.e.  a gap between knowledge, attitude, and practices regarding contraception. Healthcare workers have an important role to play to acknowledge the importance and right concept of contraception among married couples. This study aimed to assess the knowledge, awareness, and perception of contraception among postnatal women.Methods: A questionnaire-based study was conducted among postnatal inpatients and outpatients from September 2021 to November 2021. All postnatal patients in this hospital, willing to participate in the study, after a thorough written informed consent, patients were given pre decided questions for answering. Answers were noted, counselling was done.Results:  Out of 200 women, 97% of the women were aware of at least 1 contraceptive method, the highest being of female sterilization (91%). The 22% of women have used contraception before. The 78% of women had never used contraception before, main reason was that they wanted to conceive (46%) followed by fear of side effects (29%). Regarding willingness to use the contraception after counselling, female sterilization (32%) was the preferred method followed by copper-T (22%). The most common source of information was by relatives was 33%.Conclusions: There is a large gap between the awareness and practice of contraception. Proper education of both partners, increasing female literacy, socio economic upliftment, effective health care system is needed. After delivery, during immediate postpartum period, maximum women wish for contraception Hence these women can be served by family planning services before discharge from hospital to ensure the acceptance of contraceptive practices among them. This would curb unwanted pregnancies and its future consequences

Smart grid-Power factor Correction and Maintenance in Consumer Side Using RFID Based Power Line Carrier

Smart grid is a grouping of information and communication technology and intelligent common infrastructure. Talking about smart grid the  consumers and suppliers are very much important inorder to manage,monitor and control all energy issuses smartly. Easy instalation and high reliablity data communication over power line carrier is an important  requirment to make a smart grid more constructive than fixed grid system.Therefore  a latest RFID based power line technology has been developed unlike conventional system carrying data through antenna. RFID based power line carrier technology is used for detection and payment inorder to keep up the grid smart. With this technology, power factor correction and maintanance techniques are included inorder to improve the power system stability. Whenever the non-linear load is connected in load side, the proposed system will automatically detect and connect the power factor correction circuit(capacitor bank) for maintain the  power factor in consumer side

MITIGATE THE REAL POWER LOSSES IN RADIAL DISTRIBUTED NETWORK USING DG BY ABC ALGORITHM

Recently, integration of Distributed generation (DG) in distribution system has increased to high penetration levels. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss depend highly on DG location in distribution feeder .Optimal DG placement plays an important role . This project presents a new methodology using Artificial Bee Colony  algorithm (ABC) to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses .The proposed technique is tested on standard IEEE-33 bus test system

UNSUPERVISED CHANGE DETECTION FOR MULTISPECTRAL IMAGES

This paper presents a novel approach to unsupervised change detection in multispectral remote-sensing images. The proposed approach aims at extracting the change information by jointly analyzing the spectral channels of multitemporal images without any training data. This is accomplished by using a selective Bayesian thresholding for deriving a pseudo training set that is necessary for initializing an adequately defined binary semisupervised support vector machine (S3VM) classifier. Starting from these initial seeds, the S3VM performs change detection in the original multitemporal feature space by gradually considering unlabeled patterns in the definition of the decision boundary between changed and unchanged pixels according to a semisupervised learning algorithm. The values of the classifier parameters are then defined according to a novel unsupervised model-selection technique based on a similarity measure between change-detection maps obtained with different settings

Comparative analysis of salivary microbiome in oral squamous cell carcinoma patients and healthy individuals using 16S rRNA sequencing

BACKGROUND: Oral microbiome and chronic inflammation are known to influence carcinogenesis. Many studies are ongoing to ascertain the relationship between oral microbiome, inflammation and oral cancer. This study was done to ascertain the oral microbiome in the saliva of Oral Squamous Cell Carcinoma (OSCC) and healthy individuals using 16S rRNA gene sequencing. AIM AND OBJECTIVES: To ascertain the oral microbiome in saliva samples of OSCC patients and healthy individuals using 16S rRNA gene sequencing of bacteria with BLAST (Basic Local Alignment Search Tool) analysis in NCBI (National Centre for Biotechnology Information) database and to quantify the concentration of DNA extracted from bacterial cells using QUBITTM Fluorometer. MATERIALS AND METHODS: Saliva from ten OSCC patients and ten healthy individuals (controls) were collected. DNA was extracted from the saliva samples and then subjected to 16S rRNA gene sequencing to assess the oral microbiome between the two groups. RESULTS: A total of 19 phyla were identified of which Proteobacteria (39%), Firmicutes (22%), Actinobacteria (15%) and Bacteroidetes (12%) were the major phyla. The most prevalent bacteria present in OSCC patients were Bacillus, Bacterium, Buchnera, Caulobacter, Clostridium, Corynebacterium, Desulfutomaculum, Enterococcus, Flavobacterium, Gemmata, Hymenobacter, Lactobacillus, Listeria, Lysinibacillus, Marinifilum, Ruminococcus, Streptococcus, Streptomyces, Thermoanaerobacter. In healthy individuals the prevalent bacteria were Bacillus, Enterococcus, Lactobacillus, Massilia, Paenibacillus, Streptococcus. The predominant bacteria that were common in OSCC patients and in healthy individuals are Bacillus, Enterococcus, Lactobacillus and Streptococcus. CONCLUSION: The oral microbiome is complex and our study shows that there are differences in the microbiome of OSCC subjects and healthy individuals. The data from this study will help us to identify the species which need to be studied further to ascertain their role in oral carcinogenesis