Volume 11 | Issue 6

 Abstract

Upper crossed syndrome is caused by weak lower and middle trapezius, tight upper trapezius and levator scapulae, weak deep-neck flexors, tight suboccipital muscles and sternocleidomastoid, weak serratus anterior, and tight pectoralis major and minor. Poor posture is the main driver of UCS. Classes going students generally assume variety of postures during their lectures. Being students who are studying for competitive exams it's imperative for them to sit for longer duration at a stretch. Now a days due to heavy competition student's studying hours hasn't reduced but has added a burden of improper posture maintained by the students. There is marked deterioration in the posture due to wrong sitting positions which can lead to Upper cross syndrome which can then lead to complications like pain in back, difficulty in activities of daily living, numbness, tingling and pain in upper limb. Method - Observational study was conducted on 114 subjects at several MPSC and UPSC classes. Individuals were selected according to the inclusion and exclusion criteria. Individuals were explained about the procedure and informed consent was taken from all the included subjects before starting the procedure of the study.. Pectoralis major contracture test and lower and middle trapezius weakness test were done. Upper trapezius tightness test and Cranio-cervical flexion test were performed Result - According to the tests performed as mentioned above 12 % population was tested positive for pectoralis major contracture test, 11 % tested positive for middle and lower trapezius weakness test, 53 % tested positive for upper trapezius tightness test and 43 % population showed values of performance index lower than average in cranio-cervical flexion test which suggests weakness of cervical flexors. Conclusion - According to result 11% participants studying for competitive exams have Upper Cross Syndrome.

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 Keywords

Upper cross syndrome, poor posture, Upper trapezius muscle length test, Lower and Middle trapezius weakness test, Cranio-cervical flexion test, Pectoralis major contracture test.

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The worshipping traditions of India are proliferated in every corner of the world. Its culture, its Heritage, its History talks about their 'SANSKRITI' (Their perception about Gods). The tradition of devadasi culture can be traced back to as early as the 6th 0r 7th century, particularly in Southern parts of India during the reigns of the Cholas, Chetas and Pandyas. It can also be traced from the figurines of Harppa and Mohenjodaro excavations of the Pre-vedic period. The 'Daasi' Pratha or the 'devadasi' system in India, was the only way to worship and Serve Gods for all the respected temples. As music and dance were the two most essential elements in praying, serving or worshipping Gods. Devadasis had to perform the religious rituals daily and sing and dance the verses in the temples and in front of the kings of respected Regions as well. This system was much voguish in Southern Indian States like Andhra Pradesh, Maharashtra, Karnataka, Odisha etc. As these women, were termed as Devadasis widely, they were known by different names on which Dr. K. Jamanadas elaborates further in his article "The Term Devadasi is a Sanskrit Term denoting female servant of deity, but they are known by different names in different areas, such as Mahari in Kerala, Natis in Assam, Muralis in Maharashtra, Basavis in Karnataka, Jogin in Andhra Pradesh".

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Contribution of Women in Dance with Special Reference to Devdasi System

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Problem with the automobile engines continues to increase in a very large scale. Every vehicle has its own emission but problem arises when the emission occurs beyond standard values. Even though lot of changes has been made in the consumption of fuel, increasing urbanization and industrialization contribute for the poor air quality. With the technical advancements in machine learning, it's been possible to build predictive models for monitoring and controlling pollution based on the real-time data. With this, we are using IoT techniques for monitoring the emission rates of vehicles. A predictive model is built on the real- time data available, predicting the values of carbon monoxide. Sensors are embedded in the vehicles to measure the pollutants levels. By using the monitoring techniques, vehicle details such as location, owner is notified with the current situation of pollution in his location and his vehicle emission rate contributing to environment. Machine learning model is used for the prediction of pollution level in the vehicle location based on the previous data and the current data obtained by the sensors. Here the pollutants level can be controlled using smart emission surveillance

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Machine learning , Internet of things , Emission rate ,Air quality index

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Darunaj Aqrabi is Potential medicinal rhizome of Unani Medicine which is obtained from Doronicum hookeri of Asteraceae family. It is used for the treatment of various diseases like palpitation, hemiplegia, nightmare, flatulence etc. It is also used as antidote in scorpion bite and snake bite. There are limited pharmacological studies like, Antimicrobial, antioxidant, hepatoprotective, have been evaluated which are attributed due to the chemical constituents present in the rhizome, but more studies required. This review provides detail about its identification therapeutic uses. It is hoped that it will be helpful to the research community for further studies.

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Darunaj Aqrabi, Doronicum hookeri, Rhizome, Cardio tonic, Antidote

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Abstract: Learning disabilities can significantly impact the academic, social, and emotional development of individuals. It is essential to understand the different types of learning disabilities and their effects to provide appropriate support and interventions. This paper explores the diverse varieties of learning disabilities and their influence on academic, social, and emotional progress. It provides an overview of the types of learning disabilities, their symptoms, and how they impact various areas of development. The paper also discusses the importance of early identification and intervention for individuals with learning disabilities. By understanding the diverse varieties of learning disabilities, we can identify effective strategies to support individuals with learning disabilities and help them reach their full potential.

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Keywords: Learning disabilities, Academic, Social, Emotional development, Intervention Support, Strategies

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Language, being the carrier of information, holds utmost importance for human communication and information sharing. Difficulties arise when individuals from different language backgrounds try to interact, leading to language barriers. To address this issue, the need for efficient and rapid translators becomes evident. At first, human translators played this function, but they are not a lasting answer. Consequently, scholars have carried out numerous tests and attempts, leading to the emergence of machine translation technology. This technology has been widely utilized, exploring diverse languages, and employing various methodologies like Rule-Based, Statistical-Based, and more recently, Neural Machine Translation. Machine Translation has been a familiar notion for the last five decades, falling within the domain of Natural Language Processing (NLP), a subfield of Machine Learning. The effectiveness of machine translation heavily relies on the quality of the datasets and the training the machine has undergone. However, many challenges have emerged due to the lack of adequate datasets for certain languages, often referred to as low-resource languages. Our project primarily focuses on translating sentences, poems, and proverbs from South East Indian Languages, specifically Telugu, into English. As previously mentioned, Telugu is considered a low-resource language and is notoriously challenging for human learners. It boasts a wide array of proverbs and poems, but unlike English and other languages, Telugu has not been extensively translated. Previous attempts to translate Telugu poems and proverbs have yielded unsatisfactory results. Our main objective, therefore, is to develop a machine translation model using OpenNMT that can accurately translate Telugu sentences, poems, and proverbs into English.

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Machine Translation, Natural Language Processing, OpenNMT

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Network security has become a vital issue in present scenario, as it is very important to maintain high-level security to ensure safety and trusted communication of information in a computer network. Presently data communication between network and host is leading to a different number of intrusion activities and misuses. Thus, to provide a solution for such malicious attacks, the Intrusion Detection System (IDS) came into existence and held the attention of the computer science field. There are various approaches to design an IDS. Though there is several existing literature on IDS issues, still they pose some disadvantages. It is important for IDS, to detect previously known attacks with high accuracy and unseen attacks to minimize the losses and their impact at an early stage. The process of selecting the best feature is a vital role to ensure the performance, speed, accuracy, and reliability of the detector. Here, in this research study we will try to improve detection accuracy and efficiency for hybrid IDS model based on feature optimization method using multilayer neural network (ML-NN).

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Intrusion Detection System (IDS), Neural Network, Feature Optimization

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The Covid-19 pandemic may be the year 2020's most well-known memory, but US researchers also made history this year by creating the first living robot. While it is now smaller than a grain of salt, it has some bright prospects. This biorobot is what scientists refer to as a xenobot. A xenobot is a little robot, in contrast to regular robots. It is not constructed of plastic, metal, or another synthetic substance. In contrast, it is made entirely of organic cellular matter. Xenobots may move quickly or spin in circles. Like an insect, it can flip back over if you flip it onto its back. In essence, it is a robot that was engineered, yet it is ALIVE!. Xenobots represent a new frontier in biological robotics, with the potential to revolutionize fields such as healthcare, environmental monitoring and drug delivery. This paper provides an overview of the current state of xenobot research, including their fabrication methods, capabilities and ethical implications. It also discusses the challenges and future directions of xenobot research, highlighting their potential applications and impact on society.

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Xenopus Laevis, Evolutionary AI, genetic algorithm, Bioengineering, CRISPR1.

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Homemade fertilizers are prepared using kitchen scraps or waste like grass, dry leaves, neem leaves, onion peel, potato peel, carrot peel, turnip peel, and papaya peel were compared with commercial fertilizers on coriander and fenugreek plants. The plants were kept in small pots and were grown in pot mixing at favorable condition. Seed were studied for germination and growth studies as well as wet and dry weights were compared between commercial fertilizer, homemade fertilizer and tap water treated seeds. There was no significant difference between commercial and homemade fertilizers tested on fenugreek plants. However, there was a significant difference between the homemade and commercial fertilizers on coriander plants.

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homemade fertilizers, kitchen waste, Pot pourri fertilizer, Coriander seeds, Fenugreek seeds, seed germination, seed vigor

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In regards to NEP 2020, experiential learning is gaining popularity in India. Students who participate in experiential learning gain knowledge by becoming fully involved in an experience and by reflecting on it. They acquire new knowledge, attitudes, and abilities in this way. The aim of the current study was to compare the efficacy of the experiential learning approach with the traditional method for teaching mathematics to primary school students. Instructional treatment was carried out for three days in both experimental as well as control group. The sample consisted of 40 sixth-grade students of govt. senior secondary school of district Gurugram (Haryana, India). A pretest-posttest control group design was employed in the investigation. The sample for the research replied to the achievement test and experiential learning program on three topics of geometry constructed by investigator. The two-way ANOVA (2x2 factorial design) and t-test were used for data analysis. The findings showed that (a) students who were exposed to experiential learning programs learned more than those who were taught using traditional method, and (b) low achievers were more likely to benefit from experiential learning approach than high achievers.

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Experiential Learning, Primary school students

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Good governance and internal control are critical components of organizational success. Effective governance ensures that an organization is managed in a transparent, accountable, and responsible manner, while internal control ensures that processes and procedures are in place to minimize risks and prevent fraud. The use of technology has revolutionized the way organizations operate, and it has become an essential tool for improving governance and internal control. Technology can be used to improve governance by enhancing transparency and accountability. This increased transparency helps to build trust and confidence among stakeholders, which is essential for effective governance. In conclusion, the use of technology is essential for improving governance and internal control. By enhancing transparency, automating processes, improving risk management, and promoting communication and collaboration, organizations can create a culture of accountability and responsibility, which is essential for long-term success.

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Governance, Internal Control, Risk Management, Technology

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The sense of one's identity or self is an important dimension of individual's personality giving each one of us unique individuality. Women and depression is holding a relationship of much interest over the last two decades. As more and more women enter the work force, they are increasingly exposed not only of the same work environment as men, but also to unique pressure created by multiple roles and conflicting expectations. The main purpose of the research was to find out the difference in marital adjustment and depression of working and non working married women. The total sample consisted of 100 working and non-working married women (working married women = 50, non-working married women = 50). The Marital Adjustment Questionnaire and Mental Depression Scale were used for collection of data. Obtained data treated with the help of Mean, SD, t and Correlation statistical techniques. Results indicated that employment status affect significantly on depression of married women. Besides it, there was negative correlation found between marital adjustment and depression of working and non-working married women.

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Marital Adjustment, Depression, Married Women, Working and Non-Working.

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When electricity is intentionally turned off for extended periods of time over a certain distribution region, this is known as load shedding. In these situations, dynamic load shedding optimizes the power distribution. The connected loads are prioritized by microcontroller units called NodeMCU and Arduino NANO based on a predetermined threshold for power consumption. Current sensors provide input to the microprocessor, which are used to compute power usage. In a 16x2 LCD module, the overall power consumption of various loads is displayed. The microcontroller unit determines whether or not the power usage falls within the parameters. The alarm buzzer functions to alert the user for a set amount of time if the NodeMCU module detects overuse. A signal is sent to the relay to shut off the power supply if the overuse persists. A Wi-Fi module is integrated into the NodeMCU module. Consequently, it is possible to connect this load system to the authority server. After that, control over policing energy use will be in the hands of authority. The power supply might be manually shut off if the authority notices excessive usage. Similar to this, different loads can be tracked, and when there is an excessive use, or above the threshold, the power supply can be shut off. Power-consuming loads that are below the threshold may continue to function uninterrupted. Proteus 8 Professional is used to complete the simulation of the arrangement. Hardware circuit is completed and the model measures the power consumed and performs the load shedding procedure accordingly. The data collected is then send to the server through the ESP8266 module. The website for both the admin side and the consumer side was designed using HTML and PHP. The website receives data like the power consumed, peak hour setting, consumer details and energy billing.

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NodeMCU, Arduino NANO, IoT-Internet of Things, Dynamic Load Shedding, Load Management

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The conflict between modernity and tradition and the reciprocal relationship between authority and gender is the main topic of the drama The Lion and the Jewel. The article looks at the main disputes between traditionalists and modernists. Additionally, it highlights on how the author explores the conflict between tradition and modernization in Nigeria by using personality, and structure. where Baroka, Sidi, and the rest of the illiterate Ilunjule population serve as a representation of the ancient civilization. collide with a contemporary society being headed by Lakunle, a professional school teacher who has been inspired by Western culture.

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Tradition, western, old, new, domination, modernity, bride price, marriage.

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Introduction:- Volleyball has become one of the most widely played participant sports in the world. In Volleyball balance, agility and lower limb explosive strength plays important role. In the absence of optimal balance, sport performance can be negatively influenced in repetitive jumping, sprint and in activities involving agility. For this reason , balance and jumping should be considered together in athletes. The purpose of proprioceptive training is to advance the complex activity of the neuromuscular system. Effect of proprioceptive training on sports performance is minimally studied so it is importance to check where Proprioceptive exercise training can improve the balance, agility and lower limb explosive strength in amateur volleyball players. Method:- 32 male amateur volleyball players in age group of 18-25 years were included and divided into two groups. Players having lower limb injury, Musculoskeletal problems and any medical condition that would impair their playing activities were excluded. Intervention group (Group A) followed Proprioceptive training programme for 5 weeks and control group (Group B) does not perform any exercise they continue to do their daily activities. Proprioceptive exercise training consist of five weeks ( 3 days / week , 10 reps / exercise) . After 5 weeks star excursion balance test, T- test of agility, vertical jump test was performed again and paired t -test and Unpaired t-test is performed to compare results in intragroup and intergroup respectively. Results :- Both groups improved significantly at the end of 5th week but intervention group showed highly significant difference for balance , agility and lower limb explosive strength as compared to Control group (p<0.05). Conclusion:- Proprioceptive exercise training is effective in improving dynamic balance, agility and lower limb explosive strength in amateur volleyball players.

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Balance, Agility, Lower limb explosive strength , Proprioception

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Task scheduling is a fundamental problem in computer science that involves allocating computational resources to a set of tasks in an efficient and timely manner. The optimization of task scheduling is crucial in improving system performance, reducing execution time, and maximizing resource utilization. Particle Swarm Optimization (PSO) is a metaheuristic algorithm inspired by the collective behavior of bird flocking or fish schooling. This abstract presents a novel approach to task scheduling using Particle Swarm Optimization. The proposed method aims to find an optimal scheduling solution by leveraging the inherent parallelism and exploration capabilities of PSO. The problem is formulated as a multi-objective optimization task, considering objectives such as minimizing makespan, load balancing, and energy consumption. In the proposed approach, a population of particles represents potential task schedules, where each particle's position corresponds to a specific scheduling solution. The particles collaborate by sharing information about their best-known positions, called personal bests, and the overall best-known position, called the global best. Through a series of iterations, particles update their positions based on their own experience and the collective knowledge of the swarm. To guide the search process, a fitness function is defined that evaluates the quality of a scheduling solution based on the specified objectives. The fitness function considers factors such as task dependencies, resource constraints, and system characteristics. By iteratively evaluating and updating the fitness values, the PSO algorithm gradually converges towards an optimal or near-optimal scheduling solution. Experimental results on benchmark task scheduling problems demonstrate the effectiveness of the proposed PSO-based approach. It achieves significant improvements in terms of makespan reduction, load balancing, and energy efficiency compared to traditional scheduling algorithms. The approach also exhibits robustness and scalability, allowing it to handle larger problem instances efficiently.

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Cloud Computing, Task Scheduling, Particle Swarm Optimization(PSO), Best-Fit(BF), Global-Fit, Cloud Sim Tool, Virtual Machines.

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Administration of drugs through skin received great attention through the last decade. Transdermal drug delivery systems are dosage forms designed to deliver a therapeutically effective amount of drug across a patient's skin. Hence this study aims to formulate an anti-inflammatory transdermal patch using different polymers such as ethyl cellulose, hydroxy propyl methylcellulose with plasticizers poly-ethyl glycol 400. Patches were prepared through solvent casting method. The backing membrane was a non-permeable aluminium foil laminated and evaluated for thickness, physical appearance, folding endurance, moisture content, moisture uptake, weight uniformity, drug content determination, skin irritation studies. Drug content uniformity effects on inflammation and in-vitro release study, patches exhibited controlled release over more than 2 hrs. It was concluded from the research that, a herbal extract of the plant with HPMC showed moderate anti-inflammatory action and controlled drug release, thus can be selected for the development of transdermal patches for effective uses. The moisture content of batch B1 was measured and found to be 3.70%. The drug content of batch B1 was measured and found to be 84.79%.

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Transdermal Patches, Inflammation, C. esculenta, HPMC, Drug Content Uniformity.

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The simultaneous impact of globalization, the spread of English and technological development have transformed our teaching and learning English as a lingua franca in a new way (Warschauer, 2004). As a result, both English and ICT have become essential literacy skills for a growing number of non-native speakers of English to ensure full participation in the information society. In the digital world, where everything is under control of the Internet and Brand-New Technological Inventions, it is difficult to undermine their contribution to foreign language teaching. In teaching and learning a language like English, we have a lot to choose from the world of technology. Artificial Intelligence and Machine Learning are rapidly changing our world. Whether it's teaching new languages in a personalized way or translating speech and text in real-time, AI-powered language tools from Duolingo to Skype are bridging social and cultural divides in our workplaces, classrooms and everyday lives. Digital translation services are not "perfect," admits Microsoft Education Leader Mark Sparvell, but "they offer a means of understanding" that might not otherwise be possible. This rapid rising and development of information technology has offered a better pattern to explore the new teaching model. As a result, technology plays a very prominent role in English teaching. Using multimedia to create a context to teach English has its unique advantages. This paper tries to analyze the necessity of multimedia technology to language teaching and the challenges to be encountered by using these technologies. It discusses different approaches and techniques which can assist students to improve their learning skills by using technology and to upgrade the technical skills and knowledge of teachers as well.

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ELT, Lingua franca, Global Village, Internet, Multimedia Technology, Creativity, E-mailing, Presentation, Graphics, Animation, Gamification, Pronunciation, Application, Artificial Intelligence.

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Teaching is a process by which one interacts with another person to influence the learning of that person. It is the interplay between the teacher and the learners. As a valuable and practical art, teaching calls for intuition, creativity, improvisation, and expressiveness. Though many teaching methods and techniques are associated with integrated Social Science, there is no single mode of teaching which fits all the learning situations. A Social Science teacher must be abreast of the innovations in teaching methods. To be effective, a teacher of Social Science has to be a source of information, a guide, an organizer of learning opportunities, and a person who can stimulate any environment for effective learning using the following teaching modes, among others, available to Social Science teachers.

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Discussion Method, Lecture Method, Observation Method, Source Method, Story Telling Method, Laboratory Method, Field-Trips, Deductive and Inductive Method, Dramatization Method, and Question and Answer Method

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Does mood can cause inability to detect deception? Are the different states of mood can influence our tendency to believe or disbelieve another person? Based on past and recent work on deceptive communication mood and social cognition, in our research we predicted and found that negative mood increased and positive mood decreased our skepticism ability to detect deception. After inducing various mood conditions by showing positive, neutral or negative films, participants were instructed to view deceptive or truthful interviews with of actors who denied about committing a theft. The participants were told to make Judgments of the target person in video is guilty of the theft and choose "guilty" or "not guilty if they believe the person is not lying take their denial as truth as "not guilty". As predicted, negative mood condition increased judges' skepticism towards the targets, on the other hand judges in positive mood condition were found to be more trusting and gullible. The importance of findings in everyday judgments of trust and the detection of deception are mentioned, and their practical implications are discussed.

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Deception Detection, Social cognition, mood, Skepticism, Gullibility.

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