The safety and biological effect of protein isolate and protein hydrolysate were compared with casein based standard diet in Swiss albino mice in the present study. Animals were fed a 14% protein casein-based AIN-93M diet (control), isolate 14%,or hydrolysate 14% for 28 days and daily weight changes were recorded. After mild anesthesia, blood samples were collected from the retro-orbital area for biochemical and haematological analyses. Mice were sacrificed and the major organ tissues were examined. Serum biomarkers such ascreatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), alkaline phosphatase, blood urea, serum creatinine, lipid profile parameters, and random blood glucose levels, were analyzed. Statistical analysis was performed using one-way analysis of variance followed by Tukey's post hoc test. All observed values remained within normal physiological ranges, indicating normal organ function and metabolic status. Overall, the findings suggest that dietary supplementation with Lemna minor protein isolate and hydrolysate does not elicit adverse biochemical or haematological effects in Swiss albino mice, thereby supporting their safety for potential nutritional and functional food applications.
In the era of Big Data, Textual data is expanding quickly and is accessible in a wide variety of languages. This text collection is an invaluable source of information and understanding that must be effectively compiled. This is challenging to read all the text information in the world that moves quickly. Thus, the importance of text summary is being highlighted. A method called Automatic Text Summarizing (ATS) shrinks lengthy texts into shorter ones that nevertheless contain the essential information. This research work provides an overview of the available most well-known ATS systems. The purpose of this paper is to discuss the advantages and potential future applications of text summarizing techniques. This work guides about procedures that have been recommended in several research studies. Researchers can better grasp the implications, application, and efficacy of these methods by examining a variety of text summarizing techniques. This research also highlights the requirement for an enhanced text summarization architecture. The research work offers a survey of the numerous types of text summarizing methods, ranging from simple to complex methods.
Asthma, which impacts around 262 million individuals worldwide [1], is a condition marked by persistent inflammation of the airways leading to altered breathing mechanics and increased diaphragmatic tension. Meta-analyses indicate a strong link between asthma and the tendency to breathe through the mouth, with odds ratios of 2.46 (95% CI 1.78-3.39) in children/adolescents and 4.60 (95% CI 1.49-14.20) in adults [2]. This pioneering randomized controlled pilot study explores the integration of Sectional Breathing and Nabho Mudra to assess their effectiveness in reducing oral breathing, improving breath-holding time, and optimizing BMI in 20 adults (aged 30-45) with mild to moderate asthma as per GINA 2024 guidelines. Participants were divided into two groups: Group 1 practiced sectional breathing with Nabho Mudra for 15 minutes once daily, while Group 2 practiced the same intervention twice every day. The intervention was conducted 5 days per week, lasting 8 weeks in total. Breath Holding Time (BHT) and Body Mass Index (BMI) were measured pre-and post-intervention. Analysis of the collected data was done using a paired t-test with SPSS Version 26. Both groups showcased statistically significant improvements in BHT, with Group 2 demonstrating better outcomes. In Group 1, BHT increased from a pre-intervention mean of 19.6 (SD = 2.9) to a post-intervention mean of 20.7 (SD = 2.7), t (9) = 3.9, p = 0.004. Group 2 improved from a mean of 19.3 (SD = 3.3) before intervention to 23.4 (SD = 1.9) afterward, t (9) = 04.3, p = 0.002. An independent t-test revealed a notable post-treatment difference between the two groups, t (18) = 3.20, p = 0.0120. Additionally, BMI improvements were noted in Group 1, with 1 participant transitioning from the overweight category to the normal weight category. The integration of sectional breathing with Nabho Mudra represents a breakthrough in non-pharmacological asthma management, effectively improving the respiratory functions of those who practice twice a day. This novel intervention promotes nasal breathing over mouth breathing patterns, reduces tension of the diaphragm, enhances pulmonary capacity, and provides additional metabolic improvements.
This study aims to analyze the nutrient composition of black soil obtained from Salem District and evaluate its therapeutic suitability and potential application in Mud therapy for treating Type 2 Diabetes Mellitus, as an adjunct therapy in the course of Diabetes management. The selected soil sample underwent a comprehensive analysis, revealing significant levels of essential physico and chemical analysis of micronutrients, like magnesium, calcium, potassium, and sulfur, which are known for their therapeutic benefits and also analysis of pH, electrical conductivity, cation exchange and organic matter contents, through the test method based on ANR-81, FAO, HLS, and FCDO. Results indicated that the black soil sample from Salem District is rich in magnesium, potassium, calcium, and other essential nutrients, making it a potential candidate for therapeutic applications through the experimental study by incorporating Mud therapy also with other lifestyle intervention such as Yoga for the managing Diabetes. Mud Therapy is a traditional naturopathic treatment modality. It utilizes the organic properties of the Black soil for its purifying and therapeutic outcomes. The above discovery gives scientific evidence for incorporating Black Soil obtained from Salem District that may improve the effectiveness of mud therapy treatment modality, especially for T2DM by accentuating the metabolic health and well-being and in enhancing the Glycemic Regulation.
In addition to endangering patient safety, the ongoing occurrence of clinical incidents, errors, avoidable adverse events, and hazards raises patient burden, expenses, and length of stay, all of which may contribute to higher patient mortality. The purpose of this study was to evaluate staff nurses' awareness, self-perceived reporting behaviors, and obstacles regarding patient safety incident reporting. A descriptive non-experimental design was employed with 240 nurses in a few Hyderabad hospitals. A checklist was used to gauge awareness of incident reporting, and a Likert scale was used to Knowledge of how to report incidents With a mean score of 9.3 (SD = 4.5), the knowledge of incident reporting scores were remarkably high, accounting for 90.4% of the maximum score. With a mean score of 4.23, nurses rated their existing reporting methods as modest. Among the main obstacles to reporting were worries about disciplinary action, blame, avoiding difficulty, and not submitting a report. The kind of hospital was associated with statistically significant differences in the mean for total awareness of the incident reporting system scores (p <.005*). The kind of hospital was associated with statistically significant differences in the mean for total awareness of the incident reporting system scores (p <.005*). There were statistically significant variations in the self-perceived reporting practices of nurses employed in recognized hospitals (t = 0.73, p <.005).The study allowed the researcher to evaluate staff nurses' awareness, self-perceived reporting behaviors, and impediments regarding patient safety event reporting at a few Hyderabad hospitals.
Diabetes mellitus is a chronic condition that disrupts metabolic functions, resulting in elevated glucose levels within the bloodstream. This ailment can lead to significant complications that may adversely affect the heart, eyes, kidneys, and nervous system over time. Recent statistics signpost that the type 2 diabetes is prevalence among 35 to 44 of age has increased from 18.3% to 22.5%. The aggregate prevalence of Type II diabetes, mainly related to abdominal problems in India, underscores the requirement to initiate effective management strategies. This research is to evaluate the impact of yoga therapy on FBS, glycated hemoglobin (HbA1c), glucose test, Low Density Lipids, Body Mass Index (BMI), Waist Circumference and Perceived Stress Scale, physiological and clinical parameters in middle-aged men of Chennai. The outcomes showed a significant reduction in postprandial glucose levels from 200 mg/dL to 160 mg/dL, and also decreased the low-density lipoprotein levels from 130 mg/dL to 110 mg/dL, and were statistically significant. These results suggest that the addition of yoga therapy in managing diabetes can be beneficial, and would like to recommended healthcare providers to include yoga in treatment plans to improve the quality of life and well being
One of the most common chronic metabolic disorders in the world is undeniably the Type 2 diabetes mellitus. With middle-aged individuals and mostly women largely impacted, the current state of type 2 diabetes poses serious health hazards to millions of people globally, every year. The onset and course of diabetes are significantly influenced by high levels of perceived stress, which frequently results in deteriorating glycaemic control. Apart from the contemporary medical treatments, traditional therapies like yoga and mud therapy concentrate on controlling blood glucose levels, as they are believed to enhance our physical and mental well-being. The study looks at how middle-aged women with type 2 diabetes see the effects of mudpack therapy and yoga on their stress levels. Thirty people between the ages of 45 and 55 were randomly assigned to each group ,10 of which had yoga and mud therapy, and other one doing yoga alone, while other were in control group with active rest. Before and after the intervention, a Sheldon Cohen's Perceived Stress Scale (PSS-10) was administered to measure feelings of perceived stress. Compared to Group C of control group, the Group A and B of Yoga and Mudpack therapy, and Yoga alone showed a significant decrease in perceived stress levels. These outcome measurements indicate that the use of yoga and mudpack therapy has been effective in improving the physical and mental health of women who are T2DM. To improve outcomes, additional research on the long-term effects of perceived stress levels can be conducted.
Mental Imagery also called as mental rehearsal or visualization of something is a cognitive process where a person imagines about any event, behavior or real life experiences. This study which is based on mental Imagery is aimed in finding the effectiveness of mental imagery techniques in improving football player’s performance and enhancement of overall quality of life. MIQ-R scale was administered to 30 participants who were then divided into control and experimental group based on the scoring. The intervention protocol for control group consisted of routine physical training whereas experimental group had mental imagery techniques added on with the later. WHO QOL was used to assess the quality of life whereas skill performance was evaluated by professional coaches. The findings show that the experimental group, which gains from using mental imagery in their training, makes noticeably more development in their ability to do a skill than the control group, which just uses conventional physical training techniques. Also better quality of life was found in experimental group then control group.. These results shows the benefits of using mental imagery exercises while practicing football. This study promotes the use of mental imagery techniques as a part of training regime in various sports as it enhances overall satisfaction of players.
Regular physical activity levels have been shown to reduce morbidity and mortality from many chronic diseases. Aerobic exercise is advised for health promotion and prophylaxis for many cardiovascular diseases. But the strength and intensity of the aerobic training is not well appreciated to the young students. AIM: Determine the effect of cardiovascular adaptation to aerobic training in students: pre & post 6-minutes' walk test an investigating exercises tool. Objectives: To compare pre and post exercise Heart rate, blood pressure, SpO2 levels before and after aerobic exercise training among young adults. Materials & Methods: The study is designed as a cohort study conducted at SVIMS University, utilizing a random voluntary sampling technique with a sample size of 40 participants. The aerobic exercise training was given for 5 days/week and duration of 30 minutes per day was given in the SVIMS University by a certified trainer for a period of 6 weeks. The study participants were attended the exercise programme from 6am to 7am before the breakfast. RESULTS: The baseline values of HR & BP of 6MWT showed statistically decrease between before & after aerobic training (P0.001). The post values of HR & BP of 6MWT showed statistically decrease between before & after aerobic training (P0.001). SpO2 was not statistically significant in all this incidence. Conclusion: The results indicate that heart rate and blood pressure decrease significantly pre &post 6MWT before & after aerobic training. Oxygen saturation does not show any change with aerobic exercise training. All these changes help to improve aerobic fitness of a person.
This study investigates the impact of self-regulation through Rajyoga lifestyle on anger, irrational beliefs, interpersonal relations, and mental health among adults. Non-communicable diseases (NCDs) cause approximately 41 million deaths annually, primarily driven by stress and unhealthy lifestyle choices. Rajyoga, emphasizing self-regulation and emotional management, offers a holistic approach to improving mental and physical health. A quasi-experimental post-test only design was employed with 68 participants in the Rajyoga intervention group and 49 in the control group, aged 25-50 years. Standardized questionnaires assessed anger (STAXI), interpersonal relations (FIRO-F), irrational beliefs, and mental health, with data collected in person and online. Results indicated that the intervention group exhibited significantly lower State Anger (SA) and Trait Anger (TA) scores compared to the control group (p < .001), highlighting improved anger management. FIRO-F scores showed significant improvements in expressed importance, confidence, and affection, reflecting enhanced interpersonal relations. Although differences in irrational beliefs were observed, only catastrophizing showed a statistically significant reduction (p = 0.014). Mental health scores were significantly higher in the Rajyoga group (p = 0.004), demonstrating a positive impact on psychological well-being. These findings suggest that Rajyoga's self-regulation practices effectively reduce anger, enhance interpersonal skills, and improve mental health, though effects on irrational beliefs appear selective. The study underscores Rajyoga’s potential as a complementary therapy to enhance emotional and psychological health in adults.
In various regions of India, universities and colleges face challenges in providing effective counseling services due to difficulties in identifying the needs of the students, providing need-based Counseling services, demonstrating benefits to the stakeholders and limited awareness. To address these issues, the Student Self-Regulation Needs Inventory (SSRNI) was developed, aiming to evaluate the psychological, biological, and social needs of College students using DSM (Diagnostic and Statistical Manual of Mental Disorders) - based domains. This study included students from colleges in Rajasthan and TamilNadu, involving the formulation of assessment items based on inputs from Experts. A total of 549 students completed the questionnaire, and a test-retest analysis was conducted with a subset of students. The SSRNI questionnaire addressed self-regulation categories like Depression, Dependency and Study skills, adapted from established tools, aligned with DSM-5 criteria. The SSRNI exhibited strong internal reliability (alpha coefficient of 0.853) and construct validity. The SSRNI is a valuable tool for enhancing counseling services. This tool responds to the regional challenges and limitations in counseling services, ultimately benefiting students' well-being and the efficacy of counseling efforts.
The analysis aimed for analyzing health status and quality of life (HRQOL) among early middle-aged individuals (ages 34–45) using the self-reported outcome measure assessing the impact of well-being on an individual’s day to day life. A sample of 50 participants from MAHER, Chennai, was selected through convenience sampling. Participants meeting inclusion criteria provided informed consent and completed a proforma and the SF-12 questionnaire, which evaluates HRQOL across eight physical and mental health domains. The questionnaire, requiring less than two minutes to complete, was shared via Google Forms through what’s app or email. The findings indicate a complex relationship between cardiovascular risk and HRQOL, with lower HRQOL linked to increased susceptibility to cardiovascular disease due to behavioral, physiological, and psychological factors. Lifestyle modifications, such as physical activity, time management, and dietary changes, enhance HRQOL, reduce cardiovascular risk, and improve overall health outcomes.
Activated carbon (AC) is a valuable material utilized in multiple sectors owing to its versatility and ability to absorb various compounds effectively. Its adsorption characteristics are due to a large surface area and extensive porous network. Metal impregnation into activated carbon is for the improvement of its adsorption capacity and the elimination of specific contaminants like heavy metals, organic pollutants, or gases assessing with long-term performance. The chitosan derived from shrimp shells has the property of dye adsorption. Such a polymer chitosan with adsorption property is reformed into activated carbon by pyrolysis to enhance its adsorption ability in the removal of hazardous dyes. Field Emission Scanning Electron Microscopy (FESEM) of the AC showed a porous surface. Aluminium (Al), Iron (Fe), and Silver (Ag) were incorporated into the activated carbon individually by simple chemical method, at low temperatures. The structural investigation results give the Ag-imposed AC forms in a polycrystalline phase with crystallite size in the nanoscale. FTIR data of metal-imposed AC proves that chemical modification occurs in activated carbon by the inclusion of metals. The adsorption of Rhodamine 6G and Amaranth dyes by AC/Al, AC/Fe, and AC/Ag were investigated by UV analysis. This work shows that about 47% concentration of Amaranth dye was adsorbed by AC/Al composite, and to the maximum 21% of Rhodamine was adsorbed by AC/Ag sample in an experiment time of 10 hours at room temperature.
Title of the Article: "Indoors Fitness Training Monitoring based on OpenPose"Author(s): J.Haoran, S. Karungaru, & K. Terada DOI: https://doi.org/10.46947/joaasr632024947 We regret to announce the retraction of the article titled "Indoors Fitness Training Monitoring based on OpenPose" by J.Haoran, S. Karungaru, & K. Terada, which was originally published in volume Vol. 6 No. 3 (2024): JOURNAL OF ADVANCED APPLIED SCIENTIFIC RESEARCH-ICKE-2023 on 30-05-2024. This retraction follows several unresolved issues that arose after publication: Failure to Provide Valid Justification for Reference Changes: The author(s) requested significant changes to the references in the article but failed to provide the necessary and valid justification for these changes in the required format. Despite multiple requests for clarification, the justification provided was insufficient. Given the importance of proper referencing for the accuracy and credibility of academic work, this issue raised serious concerns. Image Duplication Detected: During the post-publication review, it was discovered that some images in the article had been duplicated from previously published papers. This raised significant concerns regarding the integrity and originality of the data presented in the publication. The authors had previously requested retraction of the article if their proposed reference changes were not accepted. Given this request and the issues identified, we have decided to proceed with the retraction of the article. We sincerely apologize to our readers for any inconvenience caused by this retraction. Our commitment to maintaining the highest standards of scholarly publication remains steadfast, and we will continue to ensure that all content published in JOURNAL OF ADVANCED APPLIED SCIENTIFIC RESEARCH adheres to these rigorous standards.
Feelings are incredibly vital in the internal actuality of humans. It's a means of communicating one's point of view or emotional condition to others [12]. The birth of the speaker's emotional state from his or her speech signal is appertained to as Speech Emotion Recognition (SER) [2]. There are a many universal feelings that any intelligent system with finite processing coffers can be trained to honour or synthesize as demanded, including Neutral, wrathfulness, Happiness, and Sadness. Because both spectral and prosodic traits contain emotional information, they're utilized in this study for speech emotion identification. One of the spectral parcels is Mel- frequency cepstral portions (MFCC). Prosodic variables similar as abecedarian frequency, loudness, pitch, and speech intensity, as well as glottal factors, are utilized to model colorful feelings. For the computational mapping between feelings and speech patterns, possible features are recaptured from each utterance. The named features can be used to identify pitch, which can also be used to classify gender. In this study, the gender is classified using a Support Vector Machine (SVM) on Ravdess dataset. The Radial Base Function and Back Propagation Network are used to honour feelings grounded on specified features, and it has been shown that the radial base function produces more accurate results for emotion recognition than the reverse propagation network.
With the continuation of the COVID-19 pandemic, people's daily life has changed. The changing life habits are reflected in the increasing number of hours working at home. Mostly affected is physical fitness, because of limitations or fear of the gym/outdoors or effective exercise indoors. However, with the arrival of the post-pandemic era, although working at home has improved, the fitness problem still haunts people. Some people have become accustomed to home fitness and are no longer limited to the traditional gym or gymnasium. However, proper and safe exercising is still a challenge due to the lack of live coaching. With the advent of artificial intelligence and the improvement of virtual reality (VR) and augmented reality (AR) capabilities, the options for live off-site coaching have become feasible. This study is based on OpenPose technology in artificial intelligence to monitor the standard of people's movements in-home fitness. The study results are encouraging.
Rice blight has a great impact on rice yield and can lead to yield reduction of up to 70% in severe cases. Traditional detection methods require professional technicians to operate and are costly and inefficient, and cannot detect rice diseases in real-time. In this paper, we applied image detection technology to study rice blast disease based on the Matlab platform. Firstly, a basic rice blast database is built, and then a discussion is made on how to effectively improve the recognition success rate of rice blast images by two aspects: image pre-processing and feature extraction. The main research contents are as follows. (1) After studying the existing plant disease database, a basic rice blast database was constructed by field photography and other means. (2) Preprocessing of the collected rice blight images. Using the algorithm of rgb2gray function in Matlab, the images were grayed out; based on this, median filtering was used for noise reduction; then histogram equalization technique was used for image enhancement to increase the contrast and make the images clear; finally, various segmentation algorithms were used for image segmentation. (3) For the pre-processed rice blight images, feature extraction was performed in terms of the color of the disease to pave the way for feature selection.
The AMCL (Adaptive Monte Carlo Localization) algorithm with visual provision of initial values is proposed to address the slow localization speed caused by conventional laser SLAM (Simultaneous Localization and Mapping) without initial poses and the global localization failure after a robot abduction event. In the initial map building phase, the ORB (Oriented FAST and Rotated BRIEF) feature values are extracted from the camera and the wall corners are identified, and then the pose information is stored in the database and a feature dictionary is constructed. After restarting, the dictionary is called to perform loopback detection by receiving the images captured by the current camera, and a successful detection results in a rough initial pose. If the detection fails, the initial pose is roughly calculated by identifying the wall corners. Finally, the particle filtering algorithm scatters particles in a small area near the obtained pose and converges to obtain a relatively accurate pose.
Crop loss caused by diseases that result from a range of insects, bacteria, viruses, and fungi has been a severe concern for generations that demands global attention. As a result, diagnosing crop diseases as soon as feasible can dramatically reduce production loss and enhance monetary value. The Self-governing Feedback Network (SGFN) model is suggested in this paper for producing Super Resolution images from low-resolution bean leaf images and recognizing disease. On the bean leaf dataset, the proposed SGFN model is tested for super-resolution factors 2, 4, and 6. PSNRs of 31.27, 35.653, and 37.721 are achieved for super-resolution factors 2, 4, and 6, respectively, with classification accuracies of 99.54, 98.73, and 97.64.
India is a large country with over a billion populations who speak numerous languages. 43% of Indians speak Devanagari Hindi script, followed by Bengali, Telugu, Marathi, and other languages. The widespread generation of content and accessibility would therefore greatly benefit from text-to-speech systems for such languages. In this research work we improve the already available Text-to-Speech (TTS) system using advance preprocessing techniques to the Hindi corpus database and applied various feature extraction techniques for better result. Finally we got the accuracy as 98% using MFCC and LPC feature extraction techniques. The developed model is capable for getting the input from audio file and read it loudly using developed TTS system.
