Effectiveness of Breast Crawl Technique to Initiate Breast Feeding in Newborn and to Find out Its Impact on Newborn and Maternal Outcome during Early Postpartum Period – An Experimental Study

Background: Breast crawl technique is keeping the newborn directly on the mother’s abdomen (nose inthe midline of the mother’s chest, eyes at the level of the nipples) soon after birth and allowed to crawlon their own up to the breast and then latch on. The aim of this study was to evaluate the effectivenessof breast crawl technique to initiate breast feeding in newborn and to find out its impact on newborn andmaternal outcome during early postpartum periodMethods: The mothers admitted in labor room were selected by purposive sampling technique and randomassignment to experimental and control groups was done. The breast crawl technique was introduced tothe experimental group after normal labor outcome. Effectiveness of breast crawl technique was assessedby the modified LATCH breast feeding assessment tool and a structured proforma was used to observetime of initiation of breast feeding in newborn. The newborn outcome, temperature and heart rate wereassessed at zero, 1 and 2 hours after birth. Blood glucose of newborn was monitored at 2 hours afterbirth. The maternal outcome, establishment of lactation and maternal infant attachment was assessedby an observation checklist administered 12 hours after delivery. The statistical analysis was done usingdescriptive and inferential statistics.Results: The newborn with breast crawl technique had early initiation of breast feeding than the newbornin the control group. The results were statistically better in experimental group and breast crawl techniquemade a difference in early metabolic adaptation of newborn and promoted early establishment of lactationand maternal infant attachment.Conclusion: Breast crawl technique was effective to initiate breast feeding in newborn and had positiveimpact on newborn and maternal outcome in early postpartum period

The Relationship Between Loneliness, Ethnic Identity, and Dimensions of Membership Across First, Second, and Third Generation Americans

The current study sought to explore the relationship between loneliness, ethnic identity, and dimensions of membership across generational statuses in the United States. One hundred ninety-four first, second, and third generation Americans participated in an online study which questioned the degree to which they participated in their native culture, their level of loneliness, and their experiences of discrimination, perceived inclusion, and how positively they view their ethnic group. As hypothesized, the more first generations participated in their native culture, the less loneliness they experienced. The more second generation Americans were educated about their native culture from their parents, the less loneliness they experienced, and the greater they participated in their culture. The more third generations identified with American culture, the less lonely they felt. Overall, there were significant differences in discrimination, perceived inclusion, and how positively participants viewed their ethnic group within the United States. This study emphasizes a cross-cultural phenomenon existing within differing generational statuses. Further analysis and implications of the study are discussed

Decision Support Machine - A Hybrid Model for Sentiment Analysis of News Headlines of Stock Market

Forecasting and making speculations about the financial market is intriguing and enticing for many of us. Predicting sentiments in the field of finance is a difficult thing as there is a special language that is used in financial markets and the data is unlabeled. Generalized models are not sufficient because the words that are used in financial markets have a completely different meaning when compared to their regular use. This paper represents the study of the stock price fluctuations and forecasting of the future stock prices using financial news about the big IT giants. NLP techniques should be applied to extract the correct sentiments out of the statements. This paper proposes a hybrid Machine Learning model DSM i.e. Decision Support Machine based on Support Vector Machine and Decision Tree. In this study news headlines dataset is preprocessed and then used for making predictions. The results show that the proposed model DSM got an accuracy of 79.75%. Results are then compared with the real-time stock market data for the same time duration, thus giving us a better picture of the actual changes. DSM is also compared with BERT, TextBlob, Decision Tree, Naïve Bayes, NLTK-Vader, SVM and KNN. The proposed model can further be extended if more datasets associated with investors’ sentiments can be used for training

E-learning by Time Dynamic Model Using Data Mining

The object of this paper is to build up Just in Time Dynamic Learner Models to analyze learners' behaviors and to evaluate learners' performance in online education systems by using rich data collected from e-learning systems. The goal is to create metrics to measure learners' characteristics from usage data. To achieve this goal we need to use data mining methods, especially clustering algorithms, to second patterns from which metrics can be derived from usage data. In this paper, we propose a six layer models(raw data layer, fact data layer, data mining layer, measurement layer, metrics layer and pedagogical application layer) to create a just in time learner model which draws inferences from usage data. In this approach, we collect raw data from online systems, latter fact data from raw data, and then use clustering mining methods to create measurements and metrics

Dendritic Cell Endocytosis Essential for Viruses and Vaccines

Protective immune defences are dependent upon critical roles played by dendritic cells (DCs), rendering them important targets for both vaccine delivery and virus infection. Studies in these areas led to successful development of targeted vaccine delivery, including synthetic virus-like particle (SVLP) and nanoparticulate RNA vaccines. A major consideration is DC endocytosis, whereby the different endocytic routes influencing the outcome. Rapid clathrin-mediated endocytosis likely favours degradative pathways. Slower processes such as macropinocytosis, caveolar endocytosis and retrograde transport to endoplasmic reticulum relate more to the processing rates leading to antigen presentation by DCs. These pathways are also influential in promoting the initiation of virus replication following infection. DC endocytosis of RNA viruses and RNA vaccines must lead to cytosolic translocation of the RNA for translation, relating to the process of antigen cross-presentation. One can learn from observations on both virus infections and cross-presentation for delivering RNA vaccines. Accordingly, recent advances in nanoparticulate delivery have been applied with self-amplifying replicon RNA (RepRNA), providing efficient delivery to DCs and promoting replicon-encoded antigen translation. Through realising the important relationships between DC endocytic pathways and induction of immune responses, delivery of SVLP and RepRNA vaccines to DCs offers high value for the development of future synthetic vaccine platforms

Complexity Measure in Simple Type Food Chain System

Study of complexities arising during evolution of a food chain system has been investigated. Regular and chaotic motions have been observed for certain sets of values of a parameter of the system. For some detailed further study, the continuous model of food chain has been transformed into discrete model by using Euler's method. Various measurable quantities for emergence of chaos, like Lyapunov exponents, topological entropies, correlation dimensions, have been numerically calculated and represented through plots. Finally, the chaos indicator, named Dynamic Lyapunov Indicator (DLI), has been used to identify clearly chaotic and regular motion

PREDICTING POLICY: EXAMINING PERCEPTIONS OF ECONOMIC INEQUALITY, COLOR-EVASIVE RACIAL ATTITUDES, AND BELIEFS ABOUT CAPITALISM

This study examines how beliefs about capitalism, color-evasive racial attitudes, and perceptions about wealth distribution predict redistributive economic policy preferences. I hypothesized that beliefs about capitalism, perceptions of wealth distribution, and color-evasiveness predict policy preferences when controlling for Satisfaction With Life (SWLS) and that critical consciousness action (CA) will moderate this relationship. Approximately 510 individuals completed the Costs of United States Corporate Capitalism (CCC) scale, Colorblind Racial Attitudes Scale (COBRAS), the Critical Action subscale of the Critical Consciousness Scale, ratings of wealth distribution, and questions about their policy preferences through an online survey distributed through MTurk. Results indicated that the CCC and COBRAS subscales predicted policy preferences, over and above demographic variables. Findings from this project may inform how individuals make decisions about policy preferences and on a broader scale, inform solutions for decreasing inequity in the U.S. Implications for research and clinical practice are discussed

Assessment of Preschool Education Component of ICDS Scheme in Jammu District

Non formal Preschool education is an important component of Integrated Child Development Services scheme currently operational in more than 6506 projects in India The present research paper is based on an investigation of this component in ICDS centres of Jammu district of Jammu and Kashmir state A random sample of 60 Anganwadi centres AWCs was selected for this study Using observation and interview schedule the infrastructural facilities available and the conduct of preschool education activities were evaluated The results indicate lack of adequate facilities in terms of space both indoor and outdoor quality of accommodation drinking water and toilet facilities furniture and fixtures and teaching learning material in AWCs Preschool education activities were being planned and conducted by the AWWs on a routine basis but the activities were mostly repetitive and lacked novelty Non availability of adequate infrastructure was found to be an active deterrent in conduct of activities It is thus suggested that better infrastructural facilities be made available to bring about qualitative change in the ICDS programm

The Development and Validation of the Costs of United States Corporate Capitalism Scale

Within the field of counseling psychology, which promotes values of social justice, the discussion of United States corporate capitalism (USCC) is limited. I provide evidence for the development and validation of the Costs of USCC Scale (CCC), a 24-item, self-report measure assessing the degree to which an individual attributes the cause of social problems in the U.S. to be structural (i.e. USCC) or individualistic (i.e. individual failure regarding work ethic, lack of motivation, effort, or ability). 1,010 individuals completed the CCC scale through an online survey distributed through MTurk. A three-factor structure emerged: a) USCC as Structural Cause of Costs, b) Individual Failure as Cause of Costs, c) Disagreement with Temporary Solutions to Costs. The CCC has acceptable criterion and discriminant validity, and reliability estimates for the full scale. Findings from this project may help inform future research on attitudes regarding USCC and their relationship with economic policy change