Deflection Estimation of Un-Symmetric Isotropic Cam with Three Circular-Arc Contact Profiles

In this paper the principal objectives is to design a suitable profile that produces minimum value of jerk and contact stress keeping the acceleration within a limit especially in high-speed machine. Many works in the experimental part are done on the synthesis of cam profile in accuracy and system flexibility on the output follower motion; but there is a lack in the analytical part. The analytical formulation has been done with classical plate theory of un-symmetric cam with three circular-arc contact profiles using the equation of circular plate solution due to the distributed load comes from the perpendicular contact harmonic motion of the follower. The cam used in the paper can be found in cutting and metal forming tools, heavy duty of marine engine, and fast manufacturing equipment. The aim of the present paper is to calculate the maximum deflection on cam boundaries varying with (r and θ) coordinates between beginning and ending of contact follower loadings. The results were classified into mathematical model and finite element using software ANSYS

Stacking Sequence Optimization Based on Deflection and Stress using Genetic Algorithms and Finite Difference for Simply Supported Square Laminate Plate Under Uniform Distributed Load

In this paper, the optimization and increasing of the stiffness of squareplate, numerical simulation of laminate composite plate using genetic algorithms with finite difference analyses, in which applied to the design variables of the objective functions of the stacking sequence are studied. The plates have been evaluated with actual condition of problem such as distributed load,under simply supported boundary condition with different number of layers (5, 10, 20, 30, 50) and different stiffness ratios (E1/E2) 5, 10, 20, 30, 50. The effects of fiber orientation, number of layers and stiffness ratios on the deflection and stress response of symmetric of classical laminated composite plate subjected to uniformly pressure load (flexural loading) are presented. The maximum deflection and stress are the major parameters that were taken into account in the plate design. Then obtain the optimal suitable stacking sequence orientation of composite plate that gives a small maximum deflection and maximum stress of central point of the plate which represent the main aim in this work. The results were compared with ANSYS software results and obtain a good agreemen

Buckling Analysis of Stiffened and Unstiffened Laminated Composite Plates

The present study focused mainly on the analysis of stiffened and unstiffened composite laminated plates subjected to buckling load. Analytical, numerical and experimental analysis for different cases has been considered. The experimental investigation is to manufacture the laminates and to find mechanical properties of glass-polyester such as longitudinal, transverse young modulus, shear modulus. The compressive test was carried to find the critical buckling load of plate. The design parameters of the laminates such as aspect ratio, thickness ratio, boundary conditions and number of stiffeners were investigated using high order shear deformation theory (HOST) and Finite element coded by ANSYS .The main conclusion was the buckling load could increase and decrease depending on the boundary conditions, thickness ratio, and, the aspect ratio and number of stiffeners of the plate

Prevalence of Self-Medication of Psychoactive Stimulants and Antidepressants among Undergraduate Pharmacy Students in Twelve Pakistani Cities

Purpose: To evaluate the prevalence of self-medication of psychoactive stimulants and antidepressants among pharmacy students of Pakistan.Methods: A cross-sectional survey on self-medication of psychoactive stimulants and antidepressants among pharmacy students was conducted with a structured and validated questionnaire distributed to a total of 2981 final year undergraduate pharmacy students in 12 major Pakistani cities (Karachi, Lahore, Islamabad, Rawalpindi, Sargodha, Dera Ismail Khan, Abbottabad, Bahawalpur, Hyderabad, Faisalabad, Multan and Peshawar) of Pakistan. Out of this, 2516 (718 male and 1798 female) students completed and returned the questionnaire.Results: Prevalence of self-medication of psychoactive stimulants was 1.31 (1.13 – 1.75 for 95% CI) and antidepressants was 8.34 (8.03 – 8.85 for 95% CI). A majority of the students (63 %) identified academic competition as a driving force for indulging in self-medication of psychoactive stimulants while nearly all the students (96 %)admitted using antidepressants to obtain relief from the pressure of studies (p < 0.05).Conclusion: Pakistani pharmacy students, despite being aware of the hazards of psychoactive stimulants, indulge in self-medication. Prevalence of self-medication with antidepressants is very high among the students due to the pressure of studies. Primarily, academic competition is the major driving force for the use of psychoactive stimulants.Keywords: Self-medication, Psychoactive stimulants, Antidepressants, Pharmacy students, Academicpressur

Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages

AfriSenti-SemEval Shared Task 12 of SemEval-2023. The task aims to perform monolingual sentiment classification (sub-task A) for 12 African languages, multilingual sentiment classification (sub-task B), and zero-shot sentiment classification (task C). For sub-task A, we conducted experiments using classical machine learning classifiers, Afro-centric language models, and language-specific models. For task B, we fine-tuned multilingual pre-trained language models that support many of the languages in the task. For task C, we used we make use of a parameter-efficient Adapter approach that leverages monolingual texts in the target language for effective zero-shot transfer. Our findings suggest that using pre-trained Afro-centric language models improves performance for low-resource African languages. We also ran experiments using adapters for zero-shot tasks, and the results suggest that we can obtain promising results by using adapters with a limited amount of resources.Comment: SemEval 202

Chemokine-cytokine networks in the head and neck tumor microenvironment

Head and neck squamous cell carcinomas (HNSCCs) are aggressive diseases with a dismal patient prognosis. Despite significant advances in treatment modalities, the five-year survival rate in patients with HNSCC has improved marginally and therefore warrants a comprehensive understanding of the HNSCC biology. Alterations in the cellular and non-cellular components of the HNSCC tumor micro-environment (TME) play a critical role in regulating many hallmarks of cancer development including evasion of apoptosis, activation of invasion, metastasis, angiogenesis, response to therapy, immune escape mechanisms, deregulation of energetics, and therefore the development of an overall aggressive HNSCC phenotype. Cytokines and chemokines are small secretory proteins produced by neoplastic or stromal cells, controlling complex and dynamic cell–cell interactions in the TME to regulate many cancer hallmarks. This review summarizes the current understanding of the complex cytokine/chemokine networks in the HNSCC TME, their role in activating diverse signaling pathways and promoting tumor progression, metastasis, and therapeutic resistance development.This study was supported by Ramalingaswami Fellowship (Grant number: D.O.NO.BT/HRD/35/02/2006) from the Department of Biotechnology, Govt. of India, New Delhi to Muzafar A. Macha. Sidra Medicine Precision Program funded this research to Mohammad Haris (5081012001, 5081012001) and Ajaz A. Bhat (5081012003)

Understanding the influences on successful quality improvement in emergency general surgery: learning from the RCS Chole-QuIC project

Abstract: Background: Acute gallstone disease is the highest volume Emergency General Surgical presentation in the UK. Recent data indicate wide variations in the quality of care provided across the country, with national guidance for care delivery not implemented in most UK hospitals. Against this backdrop, the Royal College of Surgeons of England set up a 13-hospital quality improvement collaborative (Chole-QuIC) to support clinical teams to reduce time to surgery for patients with acute gallstone disease requiring emergency cholecystectomy. Methods: Prospective, mixed-methods process evaluation to answer the following: (1) how was the collaborative delivered by the faculty and received, understood and enacted by the participants; (2) what influenced teams’ ability to improve care for patients requiring emergency cholecystectomy? We collected and analysed a range of data including field notes, ethnographic observations of meetings, and project documentation. Analysis was based on the framework approach, informed by Normalisation Process Theory, and involved the creation of comparative case studies based on hospital performance during the project. Results: Chole-QuIC was delivered as planned and was well received and understood by participants. Four hospitals were identified as highly successful, based upon a substantial increase in the number of patients having surgery in line with national guidance. Conversely, four hospitals were identified as challenged, achieving no significant improvement. The comparative analysis indicate that six inter-related influences appeared most associated with improvement: (1) achieving clarity of purpose amongst site leads and key stakeholders; (2) capacity to lead and effective project support; (3) ideas to action; (4) learning from own and others’ experience; (5) creating additional capacity to do emergency cholecystectomies; and (6) coordinating/managing the patient pathway. Conclusion: Collaborative-based quality improvement is a viable strategy for emergency surgery but success requires the deployment of effective clinical strategies in conjunction with improvement strategies. In particular, achieving clarity of purpose about proposed changes amongst key stakeholders was a vital precursor to improvement, enabling the creation of additional surgical capacity and new pathways to be implemented effectively. Protected time, testing ideas, and the ability to learn quickly from data and experience were associated with greater impact within this cohort

MasakhaNEWS:News Topic Classification for African languages

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach