Background: Teaching methods play a crucial role in the education and training of orthopaedics postgraduates. One innovative approach that has gained attention in recent years is the use of the SNAPPS (Summarize, Narrow down, Analyze, Probe, Plan, and Select) method.^[1] However, literature on SNAPPS in orthopaedics resident training is limited, and further research is warranted to explore its specific applications and benefits in this context. Aims and Objectives: To introduce SNAPPS as teaching learning method in PG teaching. To study the outcomes of implementation of SNAPPS as teaching learning method in PG teaching. To study challenges in implementation of SNAPPS as teaching learning method in PG teaching. Methodology: This interventional educational study was conducted at the Department of Orthopaedics, PGIMS Rohtak after obtaining institutional ethical clearance. After sensitization of students and faculty members,2 SNAPPS sessions per student were conducted. Feedback was taken at the end by students as well as faculty members. The question format included both open?ended and closed?ended questions. Rating was done on a five?point Likert scale. Results: 94% (n=31) Postgraduate students found SNAPPS as an effective tool to identify their learning needs while 76% students (n=25) felt confident in clinical reasoning skills after using SNAPPS. Similarly all the 18 teachers who conducted the SNAPPS sessions gave positive feedback. 83% (n=15) of them perceived that SNAPPS is an efficient way of case presentation and It helped students to acquire good clinical reasoning skills. 78 % (n=14) perceived that it helped them to identify and focus on students’ weak areas. Conclusions: Along with traditional teaching, SNAPPS can be supplemented to improve analytical skills of the postgraduate residents. Both residents and faculty perceived SNAPPS as an effective teaching tool in outpatient teaching of PG residents.

Background: Flexibility is the ability to move a single joint or a group of joints efficiently over a painless, unrestricted Range of Motion (ROM). Reduced flexibility may result in a diminished range of motion, which in turn alters the biomechanics and, as a result, the joints. Maintaining a prolonged forward bend sitting position causes strain on the hamstrings, which leads to decreased flexibility. Objectives: To examine the combined impact of static stretching, the suboccipital muscle inhibition technique (SMI), and the myofascial release technique (MFR) on hamstring flexibility, as measured by an active knee extension test, both before and after the intervention. Methodology: The 45 participants were divided into three groups according to the selection criteria. Myofascial release method was given to the 15 people in group A, while Sub occipital inhibition technique was administered to the 15 people in group B. And Group C was given Static stretching and had 15 participants. For four weeks, all of the groups underwent the interventions five times a week. Results: Active knee extension test was used to measure hamstring flexibility during the pre- and post-tests. For AKE(R), the pre-mean values of groups A, B, and C were 120.07, 120.65, and 119.43, respectively. The pre-mean value of group A, B, and C for AKE (L), where 119.27, 119.2, and 119.8, and AKE(R), where 140.47, 147.53, and 132.93, are the Post mean values for groups A, B, and C. The Post mean group A, B, and C for AKE (L) have values of 139.6, 146.4, and 131.73, respectively. Conclusion: In summary, the research found that the Sub occipital muscle inhibition method was more successful in increasing hamstring flexibility in IT workers who had hamstring tightness.

MSMEs have become one of the most vibrant sectors of the Indian economy, driving industrial growth and development. These enterprises have also contributed to the industrialization of backward and rural areas. In the north-eastern region of India, thousands of small and rural household industries operate within village communities and among different caste groups. These industries depend on local resources and the traditional skills of the rural population. Rural household industries have been a sustainable source of livelihood for the people of this region. Rural artisans play a vital role in preserving traditional crafts and boosting the regional economy which are crucial to a community's economic stability.  The cluster development strategy has become a prominent paradigm for fostering sustainable livelihoods among the tactics used to improve the performance of such businesses.  This research examines the socio-economic impact of cluster development on rural artisans to earn a sustainable living. The cluster development technique is becoming more and more popular as a way to help Micro, Small and Medium enterprises (MSMEs) become more innovative, productive, and competitive. Clusters provide knowledge exchange, common infrastructure, and group activities by bringing comparable enterprises together in close proximity, which can result in economies of scale and scope. The findings demonstrate that cluster-based development has a positive impact on the socio-economic development of the rural artisans.

This study examines the impact of corporate image and organizational performance in specific cement companies in Ethiopia. It's only natural that businesses today care about how they look to the public. A business needs to have a good image in order to be successful in the long run. The way people see a business as a whole is what impacts how well it does. There are many causes that could have caused the rise in importance of corporate image nowadays. Because the business environment is always evolving, many organizations have had to adjust their ideas a lot in order to stay in business and compete. Things are also falling out of style pretty quickly. Reputations can travel to markets that are quite far away; therefore, globalization has made business image increasingly crucial. Companies that have branches in different regions may also give off very diverse or even opposite impressions, which can damage how well the company works together. People in society have also upped the bar for businesses to be socially responsible. As a result of this discussion, businesses have recognized the substantial benefits of being both socially and environmentally responsible. The literature, however, does not agree on how corporate image affects business performance. The researchers used a quantitative methodology to create an explanatory and descriptive study design. The research employed a self-administered questionnaire to gather data from 367 employees at five cement companies in Ethiopia. We characterized the data using percentages, standard deviation, and mean scores. We performed regression analysis to see if the hypothesis was true. Organizational performance is the independent variable, and corporate image is the dependent variable shown to be statistically significant. The study indicates that cement companies in Ethiopia ought to prioritize the strategic development of a strong corporate image for the organization's long-term success.

Prompt engineering is one of the main parts which utilizes the power and capacity of large language models ie., LLMs efficiently. Large Language models (LLMs) are generally used to generate human-like text, summarization, solving the problems in various fields, understanding the language and translating the language and so on. The potential of LLMs is utilized by creation of effective prompt which is called as prompt engineering through the inputs are given properly. AI models are used for collecting the relevant information about the query. Extracting the relevant responses from various artificial intelligent models by almost all types of people from researchers to school going children. The challenge lies in crafting prompts which reduce ambiguity and give proper direction to the LLM for getting the desired responses. When we concentrate on prompts by adding the important words or using some key words, we can show better results which reflects the role of prompting techniques clearly. A technical document can be prepared by using a few short prompting techniques and creative writing and storytelling can be done effectively by using some key words in the prompts itself. LLMs such as chatGPT3, chatGPT3.5, chatGPT4, Gemini and other models are trained on huge volumes of data which can produce and generate human-like text easily. The conditional prompts allow the users to use some specific keys for extracting the information on the iterative refinement process can also be used to extract information from prompt engineering. The quality of LLM results is evaluated by using relevance, coherence, creativity and specificity. This work explores the strategies and methods of prompt engineering that could enhance the performance and reliability of the LLMs such as few-shot prompting, role assignment and prompt chaining. Effective prompt engineering is the foremost technique to maximize the utility of large language models in various applications. Advanced techniques such as control tokens and multimodal prompts that combine the text with other modalities such as images for optimizing the results of prompt engineering. Retrieval Augmented Generation gets queries from prompts and try to get relevant information from various sources such as search engines or knowledge graphs. Hencs, RAG extends the LLMs by incorporating external knowledge for enriching the model’s responses. The most popular prompt engineering approaches are CoT, ToT, self-consistency and reflection played a major role. Prompt design and engineering are critical and the innovation in the Automatic Prompt Engineering (APE) would dominate in the near future.  This work explores the effective utilization of Large Language Models for creating effective prompts for optimizing the responses so that we can solve complex problems easily and can reach better results in a stipulated time.