Immediate placement of dental implants in non vascularised iliac graft after resection of anterior mandible : A case report

This case report presents a combination of surgical and prosthetic rehabilitation applied to a case in postsurgical reconstructed mandible. We report a patient suffering from desmoplastic ameloblastoma of mandible, who underwent Enbloc resection and reconstruction with iliac bone graft with simultaneous placement of dental implant in anterior mandible. Two dental implants were placed at both ends of the graft. At five years follow up, favourable osseointegration with healthy peri-implant tissue was reported

Awareness, knowledge, and barriers to low vision services among eye care practitioners in Maharashtra

Background: Visual impairment is an important global health issue. 90% of the world's blind people reside in underdeveloped countries. According to population-based statistics, India has the most visually impaired persons (about 9 million). The world health organization (WHO) estimates that 285 million people worldwide are blind or have impaired eyesight. Hence it is necessary to have information about knowledge and awareness of low vision services among eye care practitioners to improve the low vision care in the world.Methods: A prospective cross-sectional survey was done at Dr. D. Y. Patil medical college and research centre (Ophthalmology department) between eye care practitioners practicing in Maharashtra, India, through a pre-tested standardized questionnaire.Results: In this study, retinal problems (76.1%) and glaucoma (11.1%) were reported as two major causes of low vision. Provision of best spectacle correction, rehabilitation, and referral to other hospitals/specialized centers was considered by 31.7%, 4.7%, and 23.8% practitioners, respectively. Magnifiers were found to be the most commonly prescribed low vision device (73%).Conclusions: Low eyesight is a big health issue all over the world. Low vision services assist patients in improving and maintain their functional vision. It also enhances the quality of life and everyday living skills. There are many barriers and a lack of understanding about low vision services. They assess eye care providers' awareness, knowledge, and challenges to poor vision services in Maharashtra. This study results showed a lack of awareness (33.3%) and training (33.3%) among the practitioners were the significant barriers restricting low vision services

Impact of air–sea coupling on the simulation of Indian summer monsoon using a high-resolution Regional Earth System Model over CORDEX-SA

A new high-resolution Regional Earth System Model, namely ROM, has been implemented over CORDEX-SA towards examining the impact of air–sea coupling on the Indian summer monsoon characteristics. ROM's simulated mean ISM rainfall and associated dynamical and thermodynamical processes, including the representation of northward and eastward propagating convention bands, are closer to observation than its standalone atmospheric model component (REMO), highlighting the advantage of air–sea coupling. However, the value addition of air–sea coupling varies spatially with more significant improvements over regions with large biases. Bay of Bengal and the eastern equatorial Indian Ocean are the most prominent region where the highest added value is observed with a significant reduction up to 50–500% precipitation bias. Most of the changes in precipitation over the ocean are associated with convective precipitation (CP) due to the suppression of convective activity caused by the negative feedback due to the inclusion of air–sea coupling. However, CP and large-scale precipitation (LP) improvements show east–west asymmetry over the Indian land region. The substantial LP bias reduction is noticed over the wet bias region of western central India due to its suppression, while enhanced CP over eastern central India contributed to the reduction of dry bias. An insignificant change is noticed over Tibetan Plateau, northern India, and Indo Gangetic plains. The weakening of moisture-laden low-level Somalia Jets causes the diminishing of moisture supply from the Arabian Sea (AS) towards Indian land regions resulting in suppressed precipitation, reducing wet bias, especially over western central India. The anomalous high kinetic energy over AS, wind shear, and tropospheric temperature gradient in REMO compared to observation is substantially reduced in the ROM, facilitating the favourable condition for suppressing moisture feeding and hence the wet bias over west-central India in ROM. The warmer midlatitude in ROM than REMO over eastern central India strengthens the convection, enhancing precipitation results in reducing the dry bias. Despite substantially improved ROM’performance, it still exhibits some systematic biases (wet/dry) partially associated with the persistent warm/cold SST bias and land–atmosphere interaction

An Efficient method of image compression by merging IWPT transform coding with index vector Quantization through FNN

Abstract--By the use of Neural Network, it was found that the reconstructed image has least image complexity and the image size has been reduced considerably by reducing the number of samples. This causes a remarkable increase in quality of the reconstructed image. A new quantization method is proposed in this paper. This method is useful for enhancement of compression quality when each kind of neural network is used to compress the image. Quantization, involved in image processing is achieved by compressing a range of values to a single quantum value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. For example, reducing the number of colors required to represent a digital image makes it possible to reduce its file size. This causes a remarkable enhancement in quality of the reconstructed image. For testing the proposed method we use IWPT transform coding and by merging it with the proposed quantization method a new compression algorithm is obtained. Then results of compression by the merged method are compared with some other transform methods. Compression time and complexity in the merged method is also better than JPEG and make it suitable for the systems with low processor and hardware implementation. Obtained results show that the proposed compression algorithm increases the compression quality of the images remarkably

A Hybrid Convolutional Network and Long Short-Term Memory (HBCNLS) model for Sentiment Analysis on Movie Reviews

This paper proposes a hybrid model (HBCNLS) for sentiment analysis that combines the strengths of multiple machine learning approaches. The model consists of a convolutional neural network (CNN) for feature extraction, a long short-term memory (LSTM) network for capturing sequential dependencies, and a fully connected layer for classification on movie review dataset. We evaluate the performance of the HBCNLS on the IMDb movie review dataset and compare it to other state-of-the-art models, including BERT. Our results show that the hybrid model outperforms the other models in terms of accuracy, precision, and recall, demonstrating the effectiveness of the hybrid approach. The research work also compares the performance of BERT, a pre-trained transformer model, with long short-term memory (LSTM) networks and convolutional neural networks (CNNs) for the task of sentiment analysis on a movie review dataset.

Phytochemical Screening and Evaluation of Antiulcer Activity of Hydroalcoholic Extract of Lilium Candidum Flowers

Peptic disorders like gastro esophageal reflux disease, gastritis, peptic ulcer, duodenal ulcer etc., are the common in today’s life style. This may be due to stressful life style or improper balance diet. The pathology behind these disorders may be discrepancy between offensive and defensive mechanisms either by excess secretion of acid and pepsin or diminished ability of the gastro-duodenal mucosal barrier to protect against stomach acid-pepsin secretion. Non-steroidal anti-inflammatory drugs (NSAIDs) are a class of the most commonly used medicines and proven to be effective for certain disorders. Some people use NSAIDs on daily basis for preventive purpose. But a variety of severe side effects can be induced by NSAIDs. Studies have shown that edible natural ingredients exhibit preventive benefit of gastric ulcer. Therefore present study was designed to evaluate antiulcer activity of hydroalcoholic extract of Lilium candidum flowers in rats. Qualitative analysis of various phytochemical constituents and quantitative analysis of total phenolics and flavonoids were determined by the well-known test protocol available in the literature. The in vivo anti-ulcer activity of hydroalcoholic extract was assessed against Aspirin-induced gastric ulcer in rats. Depending on the model, outcome measures were pH of gastric fluid and ulcer index as well as percent inhibition of ulcer index. Preliminary phytochemical screening revealed the presence of flavonoids, carbohydrates, saponins, polyphenols and amino acids. The total phenolics content of L. candidum extract was (1.039mg/100mg), followed by flavonoids (0.941mg/100mg) respectively. Further hydroalcoholic extract of 100 and 200mg/kg/p.o significantly (p˂0.01) reduced the gastric pH, ulcer index in aspirin induced ulcer models in rats. The findings of this study confirmed that L. candidum extract has anti-ulcer pharmacologic activity due to one or more of the secondary metabolites present in it. Therefore, this study validates its anti-ulcer use in Indian folk medicine. Further investigations on isolation of specific phytochemicals and elucidating mechanisms of action are needed. Keywords: Lilium candidum, Phytochemical constituents, Antiulcer, Non-steroidal anti-inflammatory drugs, Aspirin-induced gastric ulcer

Prevalence of dry eye among paramedical students of Teerthankar Mahaveer University, Moradabad, Uttar Pradesh

Background: The prevalence of dry eye is 32% in India which is higher than global prevalence. Dry eye is not a disease but a symptom complex occurring as a deficiency and abnormalities of the tear film. Dry eye infection (DED) is perhaps the most pervasive visual sickness on the planet. The point of our investigation was to acquire the pooled pervasiveness of DED in students and investigate its expected relates. Methods: It was a cross-sectional questionnaire-based qualitative and observational study was conducted among the students of the paramedical college of Teerthankar Mahaveer university. The pre-validated questionnaire was divided into three main sections involving the demographic data including the information about gender, age, students studying stream in the second section the questions about general health and question related to dryness in the eye. Results: Out of a total of 40 participants, 65% (26) were male and 35% (35) were female with the average age of the participants was 21.40 with the average age 21.40. During day how often feeling dryness for this we got the responses of 15% (06) for never, 82.50% (33) for some time and 2.50% (01). Further we have assessed the about dryness in their eyes by presenting the question During day how often feeling dryness for this we got the responses of 15% (06) for never, 82.50% (33) for some time and 2.50% (01). Concussions: The finding that dry eye symptoms are particularly common in young adults is concerning, and warrants further study.

Detecting Crop Health using Machine Learning Techniques in Smart Agriculture System

699-706The crop diseases can’t detected accurately by only analysing separate disease basis. Only with the help of making comprehensive analysis framework, users can get the predictions of most expected diseases. In this research, IOT and machine learning based technique capable of processing acquisition, analysis and detection of crop health information in the same platform is introduced. The proposed system supports distinguished services by monitoring crop and also managed its data, devices and models. This system also supports data sharing and communication with the help of IOT using unmanned aerial vehicle (UAV) and maintains high communication standards even in bad communication environment. Therefore, IOT and machine learning ensures the high accuracy of disease prediction in crop. The proposed integrated system is capable of detecting health of crop through analysis of multi-spectral images captured through the IOT associated UAV. The various machine learning is also applied to test the performance of our system and compared with the existing disease detection methods

Detecting Crop Health using Machine Learning Techniques in Smart Agriculture System

The crop diseases can’t detected accurately by only analysing separate disease basis. Only with the help of making comprehensive analysis framework, users can get the predictions of most expected diseases. In this research, IOT and machine learning based technique capable of processing acquisition, analysis and detection of crop health information in the same platform is introduced. The proposed system supports distinguished services by monitoring crop and also managed its data, devices and models. This system also supports data sharing and communication with the help of IOT using unmanned aerial vehicle (UAV) and maintains high communication standards even in bad communication environment. Therefore, IOT and machine learning ensures the high accuracy of disease prediction in crop. The proposed integrated system is capable of detecting health of crop through analysis of multi-spectral images captured through the IOT associated UAV. The various machine learning is also applied to test the performance of our system and compared with the existing disease detection methods