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Internet of things is an emerging technology that efficiently and effectively improve our daily life activities. It reduces the cost of living by automating the manual processes. It integrates physical objects and devices via internet for synchronized communication. Currently the cost of electricity is reaching the sky so there is a need for some sources that can produce electricity naturally without any cost. Here, solar panels and solar plants take place for producing electricity in natural manner with sun light. Photo voltaic cells are used in these systems that converts the sun light into electricity. Mostly the solar systems are configured in rural or agricultural areas where electricity mediums are still not available. These systems are manually operated by humans. So there is need of efficient approach which automatically control and monitor the current, voltage and other parameters of solar systems and provides real time statistics to users. This research paper proposes an IOT based approach for solar power consumption and monitoring that allow the users to monitor or control the obtained power and EV battery. Majorly, solar plants are built in the locations where people cannot reach on daily basis so this approach allows the people to virtually control their systems from faraway places.

Context-aware recommender systems (CARS) are a key component in businesses, notably in the e-transactions domain, since they assume that reviews, ratings, demographics, and other factors may determine customer preferences. On contrary, while evaluating the sentiment underlying the reviews and the rating score, consumers’ opinion is typically conflicting. As a result, a framework that employs either a review or a rating for top-N recommendation directs to produce unsatisfied recommendations in addition to a meager rating problem and high computation time. To overcome all the problems, a novel sentiment enhanced stacked autoencoder (SSAE) with context-specific hesitant fuzzy item hierarchical clustering (CHFHC) approach is proposed which employs online and offline phases. In the offline-phase, the meager user-item rating matrix is smoothed by learning the users’ concrete preference to a complete matrix by the SSAE approach. They are clustered offline using the CHFHC approach into context-based similar item clusters. In the online-phase, the active user gets context-based recommendations from the most similar cluster that matches the active users’ current context situation. Hence the SSAE_CHFHC approach improves the quality of Top-N recommendation corresponding to the exact contextual situation of the active user with a minimal recommendation computation time. Experiments on the (5-core) Amazon and yelp datasets proved that the intended SSAE_CHFHC framework consistently outperforms state-of-the-art recommendation algorithms on a variety of evaluation measures.

One in three persons experience low back discomfort, which could be the highest global burden of disease. NSLBP is outlined as the rear pain results from posture that is poor due to which apt function of the muscles alters, it becomes dysfunctional after undergoing back pain. Among various acquirable options for management of low rear pain, William’s flexion exertion is one among the known methods for treating back pain. The set of exertion referred to as William’s flexion exercises is used within the study to enhance lumbar flexion and to manage low back pain by strengthening the muscles within the gluteus and abdominal regions. The samples were collected from the physiotherapy outpatient department at AVMCH. The study comprised of patients who had non – specific LBP was chosen in accordance with the selection criteria for the study, pain prior to intervention was assessed using VAS and at the end of the final intervention of one week, the intensity of the pain was again noted. It is advised that other outcomes be added in the future to reach a higher level of dependability as this study was confined to one outcome and psychological elements were not taken into consideration. Results concluded that significant improvement in the reduction of pain following William’s flexion exercise. This study demonstrated the value of William's flexion exercises for people with generalized low back pain was effective

Content-based image retrieval (CBIR) is a method for searching that finds related images in a medical database. Furthermore, a clinical adaptation of CBIR is hampered in part by a contextual gap that is the disparity among the person characterization of the picture and the framework characterization of the image. This technique makes it tough for the user to validate the fetched images that are similar to the query image in addition to that it only fetches the images of top-ranked and ignores the low-ranking ones. Visual Analytics for Medical Image Retrieval is a novel procedure for medicinal CBIR proposed in this research (VAMIR). By integrating human and machine analysis, Visual Analytics provides the potential to address the above-mentioned significant challenges. The texture properties are retrieved using the shape features extraction and Gray Level Co-occurrence Matrix (GLCM) is performed by contour-based shape descriptor. Using the Euclidean distance correlation metric, related medical pictures will be fetched by distinguishing the query image's attribute vector with the database images' respective attribute vectors. A vector of multiple features outperforms a vector of a single feature in terms of quality. The VAMIR implementation demonstrates that the search outcome for the user is acquired with 90% of recall and precision.

In this study, monoclinic bismuth oxide (α-Bi2O3) was synthesized using in the presence and absence of surfactant, and its performance was compared for the photocatalytic degradation of methylene blue. The usage of surfactant alters the morphology of α-Bi2O3/P123 as nanorods. XRD and Raman Spectroscopy analysis confirms the monoclinic phase of the prepared catalyst and the SEM shows cubes with nano whiskers. TEM image confirms nanorods for the surfactant aided synthesis of α-Bi2O3/P123 which plays a significant role in the degradation of methylene blue. Nanorods of α-Bi2O3/P123 shows 95% photo catalytic degradation of methylene blue than compared to 84% for α-Bi2O3 and 78% for P25. The effect of catalyst loading, kinetics of degradation and the comparison of performance with the standard catalyst were reported.

A rising non-inflammatory condition that affects older people is osteoarthritis. The most typical location for osteoarthritis is the knee. When a muscle contracts and generates forces during an isometric workout, there is no noticeable change in the length of the muscle. Exercises known as multiple angle isometrics require the user to manually apply resistance to a range of joint positions. So, the goal of this study is to assess how well multiple angle isometric exercise reduces pain in people with osteoarthritis. Ten samples were collected from the Aarupadai Veedu Medical College and Hospitals outpatient physiotherapy department in Kirumampakkam, Pondicherry. Between the ages of 45 and 65, both males and females were collected. Participants underwent seven sessions of multiple-angle isometric exercise over the course of one week. The NPRS scale was used to assess pain before and after therapy. The use of a single outcome and a limited sample size are study limitations; it is recommended that more outcomes, such as strength and endurance, be added in the future to achieve a better level of dependability. The findings of this study revealed a considerable improvement in patients with osteoarthritis of the knee in terms of pain reduction. The research found that multiple angle isometric training reduces pain in those with osteoarthritis.

In this paper, a novel Monogenic Sobel Directional Pattern (MSDP) using fractional order masks is proposed for extracting features. The MSDP uses fractional-order Sobel masks to identify thin edges along with color and texture-based information thereby increasing performance. Other edge-detection methods can identify only thick edges. There are three modules namely feature extraction, dimension reduction via a novel discriminant analysis method, and classification using a Convolutional Neural Network (CNN). The proposed MSDP is insensitive to the rotation and scaling changes existing in the images. The Bat Algorithm-based Optimization (BAO) is used for the selection of the best parameters of MSDP. The best value is modified by the Pearson Mutation (PM) operator in an effort to aid the algorithm in avoiding local optima and achieving a balance between global and local searches. The proposed work uses CNN for classification and achieves higher classification accuracy for six datasets.

Introduction: Dry eye is a common condition that affects 85 percent of adult students worldwide, has no effective treatment, and results in significant loss of productivity at work. Aim: This study aims to assess the knowledge and awareness of dental students about dry eye disease. Materials and Methods: An online google form was used to distribute a questionnaire based study with 12 questions to 100 people. The study began with the participants being briefed on the trial's details. The study used a 100-person sample size. The information was gathered and statistically examined. Results: In this study, 96% of the students were aware that lack of sleep causes Dry Eyes Disease and 4% of the students were unaware of it. Around 83% of the students were aware that dry eye is reversible and 17% of the students were not aware of it. The overall result was positive, most of them were aware of the dry eye disease. This proves an outright positive result. Conclusion: The present study shows that the students under 75% were aware of Dry Eyes Disease but 25% were unaware of dry eye disease. There is no sufficient awareness among dental students. So, by this survey, we create more awareness among dental students.

Mosquitoes are the vectors of many severe diseases like malaria, dengue, yellow fever, filariasis, chikunguniya, west nile virus, western equine encephalitis and considered as one of the life threatening creatures in the world. The present study aims to identify the phytochemical compounds and larvicidal activities of the two extracts, ethanol and chloroform, present in the leaves of Muntingia calabura against the filarial vector Culex quinquefasiatus and to compare the efficiency of these two extracts. The plant leaves were collected, dried and powdered and the extracts were prepared using chloroform and ethanol and then series of tests were conducted. The eggs were collected, hatched and reared in the laboratory. The colony of larval instars were kept in glass beaker along with dechlorinated water and added with desired concentrations of plant extract and the mortality rate were calculated. The mortality of larvae was observed at 48hrs. The LC50 and LC90 values of M.calabura leaf extracts were depicted and for the each test the concentration of the extract is increased. It was observed that the mortality increases as the concentration of extract increases. Among the two extracts, Muntingia calabura ethanol leaf extract was found to be more effective than the chloroform extract against the filarial vector Culex quinquefasiatus which is cost efficient and ideal ecofriendly approach for the control of mosquitoes.

Acid lime (Citrus aurantifolia Swingle) is one of the commercial fruit crops which occupies important place in the fruit industry, but yield levels of citrus orchards are still very low. Alternate nutrient management system could help in achieving high yield and quality of acid lime. Thus, an investigation was undertaken on the “Effect of nutrient management through bio-organic manures on quality of acid lime (Citrus aurantifolia Swingle)” in the Department of Horticulture, Faculty of Agriculture, Annamalai University, Annamalainagar, Tamil Nadu, India during 2016 – 2018. The experiment was laid out in randomized block design with twelve treatments, various organic manures, biofertilizers along with inorganic fertilizers including recommended dose of fertilization @ 100%, 75%, 50%, farm yard manure @ 100%, 50%, Vermicompost @ 100%, 50%, Biofertilizers ( 25g Azotobacter + 25g phosphate solubilising bacteria + 150g vesicular arbuscular mycorrhizal) were applied. The quality characters of acid lime were studied at different stages. The observations recorded viz., plant height (m), canopy spread east-west (m), canopy spread north-south (m), canopy height (m), no. of leaves per canopy, leaf area (cm2). The results revealed that plants treated with of T8 -75% RDF + 50% FYM + 50% Vermicompost + Biofertilizers (25g Azotobacter + 25g PSB + 150g VAM) was observed maximum plant height (m), canopy spread east-west (m), canopy spread north-south (m), canopy height (m), no. of leaves per canopy, leaf area (cm2).

In this paper, we present existence and uniqueness of special random impulsive differential evolution equations with nonlocal condition in Hilbert spaces. Moreover we study the stability results for the same evolution equations. Existence and uniqueness results are proved using Banach fixed point theorem where as stability results using fixed point approach and semi group theory. Finally we give some applications of the nonlocal impulsive differential equations as well as evolution equations, which shows the importance of our theoretical results.

Acid lime (Citrus aurantifolia Swingle) is one of the commercial fruit crops which occupies an important place in the fruit industry, but yield levels of citrus orchards are still very low. An alternate nutrient management system could help in achieving a high yield and quality of acid lime. Thus, an investigation was undertaken on the “Effect of nutrient management on productivity and quality of acid lime (Citrus aurantifolia Swingle)” during 2016 – 2018. The experiment was laid out in randomized block design with twelve treatments, various organic manures, biofertilizers along with inorganic fertilizers including recommended dose of fertilization @ 100%, 75%, 50%, farm yard manure @ 100%, 50%, Vermicompost @ 100%, 50%, Biofertilizers (25 g Azotobacter + 25 g phosphate solubilising bacteria + 150 g vesicular arbuscular mycorrhizal) were applied. The yield and quality characters of acid lime were studied at vegetative and reproductive stages. The observations recorded viz., fruit setting (%), fruit diameter (cm), number of fruits per plant, fruit weight (g), yield per tree (kg) and yield per hectare (tonnes). The results revealed that plants treated with T12 ( 50% RDF+ 75% Vermicompost + Biofertilizers (25 g Azotobacter +25 g PSB +150 g VAM) was observed maximum fruit setting (%), fruit diameter (cm), number of fruits per plant, fruit weight (g), yield per tree (kg), yield per hectare (tonnes). The maximum net income (Rs. 281511.5 / ha) and benefit:cost ratio (4.72: 1) was observed in the treatment T12-50% RDF + 75% FYM + 75% Vermicompost + Biofertilizers (25 g Azotobacter + 25 g PSB + 150 g VAM) which was superior to other treatments.

Introduction: Periodontal disease is an infection of the tissues that hold your teeth in place. It's typically caused by poor brushing and flossing habits that allow plaque, a sticky film of bacteria, to build up on the teeth and harden. Elimination of these pathogens from the site of infection remains a perplexing task, which demands the use of antibiotics. The emergence of drug resistant forms has spurred interest into identifying novel therapeutic targets against these pathogens. Aim: The present study employs virtual screening method to identify the protein network interaction of berberine with red complex pathogens. Materials and Methods: Computational tools were used to identify the targets, assess their functional role and virulence property. Further, the peptide epitopes present in the virulence factors were identified using the BepiPred tool. The subcellular location of the virulence proteins was also elucidated using PSORTb. Results: Berberine was found to target vital protein transporters such as TetR family transcriptional regulator and MerR family transcriptional regulator, which is known to play a crucial role in the survival of bacterial cells. Conclusion: Hence the present study provides preliminary data on the protein targets of berberine against red complex pathogens. However, in vitro studies using the compound is warranted to further confirm the efficacy of the compound.

An Investigation was conducted to study the effect of organic inputs and growth regulators on yield and quality of goldenrod (Solidago canadensis) was conducted at the floricultural unit, Department of Horticulture, Faculty of Agriculture, Annamalai University during 2018. The experiment was laid out in randomized block design with twelve treatments, various organic inputs and growth regulators including panchagavya @ 3%, vermiwash 1:5 dilutions, humic acid @ 0.2%, GA3 @ 250 ppm, NAA @ 250 ppm were applied. The yield and quality characters were studied at different stages. The observations recorded viz., yield of flower stalks/ha, days to first flowering, length of flower stalks and weight of individual flower stalks. The results revealed that plants treated with NAA @ 250 ppm + panchagavya @ 3% (T9) was observed highest flower stalk yield (1140.02 flower stalks/ha), No. of flower stalks/plant (24.48), weight of individual flower stalks, days to first flowering. Considering the overall performance, it was found that the plants treated with NAA @ 250ppm + Panchagavya @ 3% recorded better performance with regard to growth, yield and quality characters.

Many clinical studies have evaluated the role of biochemical mediators like insulin-like growth factor 1 (IGF-1) in assessment of skeletal maturity. But still the reliability of IGF‑1 as an indicator of skeletal maturity remains controversial. To assess the correlation between IGF‑1 and different radiographic skeletal maturity indicators. Seven electronic databases (PubMed, Scopus, EMBASE, Medline, Cochrane CENTRAL, Web of Science and SciELO) were searched until January 2020 without any restriction based on language or date of publication. The study design included cross-sectional and longitudinal studies comparing IGF‑1 and other skeletal maturity indicators (SMIs). Data extraction was done by two reviewers independently; 15 studies were eligible to be included in the quantitative synthesis. There was significant positive correlation between IGF‑1 and different SMIs until puberty which was 0.95 (confidence interval [CI] = 0.89, 1.02) for males and 0.87 (CI = 0.77, 0.97) for females. A negative correlation between IGF‑1 and different SMIs was found after puberty which was −0.86 (CI = −0.97, −0.75) for males and −0.89 (CI = −0.98, −0.81) for females. The type of SMI compared and type of IGF‑1 sample used accounted for the high heterogeneity found across the studies. Chronological age and number of months passed after puberty showed moderate negative correlation with mean IGF‑1 levels which were −0.57 (CI = −0.67, −0.47) and −0.54 (CI = −0.66, −0.42). Annual increments in mandibular length showed significant positive correlation of 0.69 (CI = 0.48, 0.90). IGF‑1 would serve as a promising alternative to conventional radiographic skeletal maturity indicators and in predicting the amount of residual mandibular growth.

Context-aware recommender systems (CARS) are intended primarily to consider the circumstances under which a user encounters an item to provide better-personalized recommendations. Users acquire point-of-interest, movies, products, and various online resources as suggestions. Classical collaborative filtering algorithms are shown to be satisfactory in a variety of recommendation activities processes, but cannot often capture complicated interactions between item and user, along with sparsity and cold start constraints. Hence it becomes a surge to apply a deep learning-based recommender model owing to its dynamic modeling potential and sustained success in other fields of application. In this work, a Trust-based Attentive Contextual Denoising Autoencoder(TACDA) for enhanced Top-N context-aware recommendation is proposed. Specifically, the TCADA model takes the sparse preference of the user that is integrated with trust data as input into the autoencoder to prevail over the cold start and sparsity obstacle and efficiently accumulates the context condition into the model via attention framework. Thereby, the attention technique is used to encode context features into a latent space of the user's trust data that is integrated with their preferences, which interconnects personalized context circumstances with active user's choice to deliver recommendations suited to that active user. Experiments conducted on Epinions and Caio dataset make obvious the efficiency of the TACDA model persistently outperforms the state-of-the-art methods.

Bemisia tabaci (Hemiptera: Aleyrodidae) is a polyphagous invasive insect pest in the world that infests over 1000 plant species, spreads 300 plant viruses and associated with different endosymbiotic bacteria. In the current study, we looked at the genetic variation of B. tabaci populations and their association with endosymbiotic bacteria in Bihar (29 populations: 16 interhost and 13 interlocations). For this purpose, we conducted an inter-host survey and discovered that Brinjal was highly infested by B. tabaci, so, an interlocation survey was planned. The genetic variability among 29 populations were explored using nuclear markers i.e., Random Amplified Polymorphic DNA (RAPD), Simple Sequence Repeats (SSR) along with extra-nuclear marker (Cytochrome c oxidase subunit I -COI) for their molecular characterization. Interestingly, Bayesian phylogenetic analysis of 657 bp mtCOI sequences showed the existence of four cryptic species belonging to two genetic groups (Asia and China) viz., Asia I, Asia II 1, Asia II 7 and China 3. In this study we have reported different bacterial endosymbionts associated with 29 B. tabaci populations in Bihar. By amplifying of 16S rRNA of specific bacteria we were able to identify Portiera sp, the primary endosymbiont of B. tabaci, and other secondary endosymbionts like Arsenophonus sp, Wolbachia sp, Rickettsia sp, Hamiltonella sp and Cardinium sp. Overall, this study found that Asia II 7 and China 3 cryptic species were reported for the first time in Bihar region and Asia I was the dominant cryptic species and that secondary endosymbionts were not uniformly distributed in all the populations. Furthermore, our findings in mapping the distribution of B. tabaci populations and their associated endosymbionts in various ecosystems paved the way for future research and the development of area-wide management tactics for B. tabaci cryptic species in Bihar.