Limp Wrists, Clenched Fists: An Analysis of Queer Performance Art as a Tool for Political Resistance

This paper explores the use of queer performance art as a tool for community mobilization and resistance to socio-legal oppressions. This essay is grounded in movements for queer liberation in the Global South, racialized working-class queer communities, and queer disability justice. As queer culture and aesthetics are often misappropriated for wider cisheteronormative audiences, this work reminds the revolutionary nature of queer performance art

Merging Text Transformer Models from Different Initializations

Recent work on one-shot permutation-based model merging has shown impressive low- or zero-barrier mode connectivity between models from completely different initializations. However, this line of work has not yet extended to the Transformer architecture, despite its dominant popularity in the language domain. Therefore, in this work, we investigate the extent to which separate Transformer minima learn similar features, and propose a model merging technique to investigate the relationship between these minima in the loss landscape. The specifics of the architecture, like its residual connections, multi-headed attention, and discrete, sequential input, require specific interventions in order to compute model permutations that remain within the same functional equivalence class. In merging these models with our method, we consistently find lower loss barriers between minima compared to model averaging for several models trained on a masked-language modeling task or fine-tuned on a language understanding benchmark. Our results show that the minima of these models are less sharp and isolated than previously understood, and provide a basis for future work on merging separately trained Transformer models

A Hybrid Machine Learning Approach for Breast Cancer Detection

Now a day, cancer is one of most common and internecine disease among all disease present in the world. A cancer disease is classified into different types based on the body location like breast cancer, kidney cancer, liver cancer etc. but breast cancer is one of the most common cancer in woman and 8% of woman were diagnosed breast cancer in 2016. It is found that if the cancer is diagnosed in the early stage than the probability of the survival is higher. Now a day, Machine learning play a vital role in order to detect cancer in the early stage. Lots of work has been done previously which uses machine learning approach like support vector machine, Naïve Bayes, logistic regression etc. In this paper w proposed hybrid approach for detecting cancer in the early stage. This hybrid approach is the combination of Support vector machine and Naïve Bayes approach. In order to evaluate the performance of the proposed approach uses Wisconsin Breast Cancer (WBC) which is downloaded from the UCI machine learning repository. Performance of the proposed approach is measured in term of accuracy, F- value. Experiment results shows that proposed approach gives better result as compare to the competitive approach

An evidence based review on effect of oral motor therapy on feeding in preterm infants

Present study was done to know the effect of Oral Motor Therapy on preterm infants for feeding and related issues. Most preterm infants have low body weight, immature brain development, sucking and swallowing problems, and decreased oral motor ability, which affects infants' growth and normal development. Oral Motor Therapies are used to increase functional strength and control of movement for feeding, to promote the onset of oral feeding, and to improve oral feeding performance. The study started with the search articles on Google Scholar, ResearchGate, Cochrane and PubMed with keywords in range of year 2012-2023. 250 articles were found from the sources. 46 articles were studied which were related to aim of the study. From all of them 10 articles were selected on the basis of inclusion criteria. All the articles suggested improvement in all the post intervention outcomes which showed clinical significance of the Oral Motor Therapy. The study hereby concluded that Oral Motor Therapy is useful in preterm infants for feeding initiation and progression, weight gain as well as in dysphagia rehabilitation and reduced hospital stay

Transfer Learning for Low-Resource Part-of-Speech Tagging

Neural network approaches to Part-of-Speech tagging, like other supervised neural network tasks, benefit from larger quantities of labeled data. However, in the case of low-resource languages, additional methods are necessary to improve the performances of POS taggers. In this paper, we explore transfer learning approaches to improve POS tagging in Afrikaans using a neural network. We investigate the effect of transferring network weights that were originally trained for POS tagging in Dutch. We also test the use of pretrained word embeddings in our POS tagger, both independently and in conjunction with the transferred weights from a Dutch POS tagger. We find a marginal increase in performance due to transfer learning with the Dutch POS tagger, and a significant increase due to the use of either unaligned or aligned pretrained embeddings. Notably, there is little difference in performance when using either unaligned or aligned embeddings, even when utilizing cross-lingual transfer learning

Effect of an acute bout strength training on executive function among college students: a pilot study

Executive functions are built such as reasoning, problem solving and planning. Even mild form of executive dysfunction might hamper everyday activities depending on the work and situation, which requires various cognitive domains. Strength exercises are able to increase the anti-inflammatory balance with an increase in cognition and better physical performance. Aim of the study was to evaluate the acute bout effect of strength training on executive function among college students. 10 participants were divided into control and intervention group for experimental study performed at SPB physiotherapy college. Consent was taken from the participants. Only one session of 30 minutes was performed by intervention group. Intervention group performed 10 repetitions of 12 exercise per set and 2 sets per session. Warm up and cool down was performed by participants. Pre and post measures of trail making test B was recorded as outcome measure for executive function. Trail making test score was significantly improved immediately after strength training with p value <0.05 suggesting improvement in executive function. The study concluded that Strength training has greater immediate impact on executive function among college student

On sharp third Hankel determinant for certain starlike functions

In this paper, we provide an estimation for the sharp bound of the third Hankel determinant of starlike functions of order $\alpha$, where $\alpha$ ranges in the interval $[0, 1/6]\cup \{1/2\}$ and thereby extending the result of Rath et al. (Complex Anal Oper Theory: No. 65, 16(5), 8 pp 2022).Comment: The paper has been updated from the previous versio

Differential Subordination of Certain Class of Starlike Functions

This paper presents several results concerning second and third-order differential subordination for the class $\mathcal{S}^{*}_{e}:=\{f\in \mathcal{A}:zf'(z)/f(z)\prec e^z\}$, which represents the class of starlike functions associated with exponential function.Comment: Updated versio

Evaluation of echocardiographic systolic parameters in pre eclamptics and normotensives women

Background: Early detection of changes in cardiovascular echocardiographic systolic parameters and their comparison with normotensives women.Methods: This was a hospital based prospective case control study carried out in department of obstetrics and gynaecology in S.M.S Medical College, Jaipur during the period from February 2013 to December 2014. 100 women were enrolled in the study after applying inclusion and exclusion criteria. All women underwent two dimensional echocardiography at rest. Cardiac systolic parameters were recorded and studied.Results: Mean LVEDV in PIH group was 75.71 ± 4.8 ml v/s 71.08 ± 5.6 ml in control group and the difference was statistically significant. Mean stroke volume was higher in PIH group as compared to the control group and the difference was statistically significant (59.83 ± 7.4ml/min v/s 52.48 ± 6.4ml/min). Mean Aortic Root Diameter in PIH group was 2.188 ± 1.04 cm as compared to the 1.866 ± 1.06 cm in the control group which was statistically significant. Mean Left Ventricular outflow Tract diameter was slightly higher in the PIH group as compared to the controls although the P-value was not significant (2.37 ± 1.06 cm and 1.99 ± 1.08 cm). Mean Total Vascular Resistance in PIH group was found to be higher in PIH group as compared to the controls and the difference was statistically significant (1389 ± 57.04 dynes/sec/cm-5 v/s 1286 ± 45.01 dynes/sec/cm-5).Conclusions: Systolic parameters get worsened in pre eclamptics. Early detection of change in these parameters could help to identify high risk women who are prone to develop cardiovascular morbidity in later life

Examining the Need of Digital Citizenship Education for Adolescents in the Current Digital Landscape

Adolescents are growing up in a digital era, and the increasing role of technology in our lives presents both challenges and opportunities. A survey study was conducted to address the need for Digital Citizenship Education (DCE) in school-going adolescents, as they need to learn how to make sound judgments when navigating the digital world. The study found that 79% of students have digital access at home, 83% purchase products online, and 73% have social media accounts, with 24% talking to strangers online. However, only 21% use the internet at school, and 78% are unaware of the term DCE. The survey also revealed that many students lack awareness of cyber laws, struggle to determine the reliability of online information, and believe everything they see online is true. This research emphasizes the importance of developing a customized DCE curriculum for adolescents to participate safely, ethically, effectively, and responsibly in the digital community