Structural insights on Sucrose transport by Oryza sativa L. Sucrose/H+ Symporter1 (OsSUT1) through refined sequence - template alignment based structural modelling

283-290Sucrose/H+ Symporters (SUTs) play an important role in plant growth and yield. They are involved in long distance transport of sucrose from source leaves to filling grains of cereals through a process called phloem loading. However, the molecular mechanism of sucrose transport through SUTs is not yet known. Understanding the key residues involved in sucrose transport can be helpful in developing high yielding varieties through genetic engineering, gene editing or allele mining. Here, the molecular model of OsSUT1 developed based on refined target-template alignment using Modeller software provides structural insights on the sucrose transport mechanism. We propose 13 putative sucrose binding residues and 11 putative H+ binding residues involved in sucrose/H+ co-transport in OsSUT1

A Study on the Impact of Locality in the Decoding of Binary Cyclic Codes

In this paper, we study the impact of locality on the decoding of binary cyclic codes under two approaches, namely ordered statistics decoding (OSD) and trellis decoding. Given a binary cyclic code having locality or availability, we suitably modify the OSD to obtain gains in terms of the Signal-To-Noise ratio, for a given reliability and essentially the same level of decoder complexity. With regard to trellis decoding, we show that careful introduction of locality results in the creation of cyclic subcodes having lower maximum state complexity. We also present a simple upper-bounding technique on the state complexity profile, based on the zeros of the code. Finally, it is shown how the decoding speed can be significantly increased in the presence of locality, in the moderate-to-high SNR regime, by making use of a quick-look decoder that often returns the ML codeword.Comment: Extended version of a paper submitted to ISIT 201

Structural insights on Sucrose transport by Oryza sativa L. Sucrose/H+ Symporter1 (OsSUT1) through refined sequence - template alignment based structural modelling

Sucrose/H+ Symporters (SUTs) play an important role in plant growth and yield. They are involved in long distance transport of sucrose from source leaves to filling grains of cereals through a process called phloem loading. However, the molecular mechanism of sucrose transport through SUTs is not yet known. Understanding the key residues involved in sucrose transport can be helpful in developing high yielding varieties through genetic engineering, gene editing or allele mining. Here, the molecular model of OsSUT1 developed based on refined target-template alignment using Modeller software provides structural insights on the sucrose transport mechanism. We propose 13 putative sucrose binding residues and 11 putative H+ binding residues involved in sucrose/H+ co-transport in OsSUT1

Risk-Less Brokering System In Distributed Network Using Variable Key Technique

Most of the business startups and established business sectors approach third party marketing agents to extend their businesses. In this scenario many times marketing agents or brokers can use the other business owner’s crucial information for their illegal gains. So a big question arises for the trustworthiness of the brokers in these kind business arrangements. So a need of a strongly coupled business entity system is required in distributed paradigm to restrain the business relationship in between owners and brokers.Many systems are existed in the market where they deal with one or two aspects of the security issues in the system. So a proposed system put forwards an idea of providing 3600 security for the broker -less publisher and subscriber system using strong two tier key generation system which is powered by reverse circle cipher cryptographic technique. In addition to our previous work [1], this paper contributes 1) use of profile based key generation system 2) use of time based key generation system 3) use of two tier key generation combing 1 and 2 4) Powerful encryption technique using reverse circle cipher encryption 5) fine grained key management system 6 ) Enriched event distribution using Gaussian model. DOI: 10.17762/ijritcc2321-8169.150711

A Review on Detection of Traumatic brain Injury using Visual-Contextual model in MRI Images

Recently, there are various computational methods to analyze the traumatic brain injury (TBI) from magnetic resonance imaging (MRI).The detection of brain injury is very difficult task in the medical science. There are various soft techniques for the detection of the patch of brain injury on the basis of MRI image contents. This paper gives brief analysis about the different methods to determine the normal and abnormal tissues of the brain

Comparison of effects of benidipine and amlodipine on clinical and biochemical parameters in hypertensive patients: an observational study

Background: Hypertension is a widespread public health problem and a major risk factor for cardiovascular disease. Amlodipine, a calcium channel blocker, dilates arterioles by blocking L-type calcium channels. Benidipine inhibits L, N, and T type calcium channels. We compared the efficacy of Amlodipine and benidipine on blood pressure, pulse rate, proteinuria and lipid profile in hypertensive patients.Methods: The study was an observational, prospective, open label comparison. Eligible hypertensives were given either amlodipine (5mg/d) or benidipine (4mg/d). Clinical features and laboratory parameters were recorded initially and after 3 months. Adverse events were recorded with the help of a questionnaire. Compliance was assessed by return pill count.Results: Out of 35 patients, recruited for study, 16 received amlodipine and 17 were treated with benidipine and two were lost during follow up. Both the groups were well matched in terms of age, body weight, clinical findings and laboratory values. Both the drugs significantly (P <0.05) reduced systolic (142±16 to 138±15 vs.148±16 to 134±14mmHg) and diastolic blood pressure (81±9 to 79±7). In the Amlodipine group the pulse rate after treatment tended to be higher than before (70±9 to 72±10bpm). In the Benidipine group there was decrease in pulse-rate after treatment (69±9 to 67±9). Unlike Amlodipine, Benidipine significantly (P<0.05) decreased urinary protein excretion (1.0±1.2 to 1.1±1.4 vs. 1.4±2.5 to 1.1±1.7g/g-Cr) and serum triglycerides (125±25 to 120±23 vs 130±26 to 115±21mg/dl).Conclusions: In this study, amlodipine and benidipine were found to be be equally effective anti-hypertensive in patients with stage 1 hypertension. However, there was significant reduction in proteinuria and serum triglycerides in Benidipine group as compared to Amlodipine group. Benidipine may be a better alternative to existing calcium channel blockers

Heart Disease Prediction using Different Machine Learning Algorithms

Identifying a person's potential for developing heart disease is one of the most challenging tasks medical professionals faces today. With nearly one death from heart disease every minute, it is the leading cause of death in the modern era [4]. The database is taken from Kaggle. Various machine learning algorithms are used for prediction of heart disease detection here are Random Forest, XG-Boost, K- Nearest Neighbors (KNN), Logistic Regression, Support Vector Machines (SVM). All these algorithms are implemented using Python programming with Google collab.&nbsp; The performance evaluation parameters used here are Accuracy, precision, recall and Fi-score. Training and testing are implemented for different ratios such as 60:40, 70:30 and 80:20. From the analysis and comparisons of evaluation parameters of all the above algorithms, XG-Boost is having the highest accuracy and recall value. KNN having worst accuracy and recall amongst all. XG-Boost is having a training accuracy of 98.86, 98.74 and 97.68 for training and testing ratio of 60:40, 70:30 and 80:20 respectively. XG-Boost is having a testing accuracy of 95.85, 95.45 and 96.09 for training and testing ratio of 60:40, 70:30 and 80:20 respectively. So, XG-Boost algorithm can be used for obtaining the best prediction for heart disease.&nbsp; This type of heart disease prediction can be used as a secondary diagnostic tool for doctors, for best and fast prediction. This can help the early prediction of heart disease thus increasing the chances of the saving the life heart patient

Thin layer drying of long pepper (Piper longum L.)

The effect of drying air temperatures on the drying kinetics of long pepper was investigated during 2010 using a hot-air tray dryer. In order to select the appropriate drying model, twelve mathematical drying models were fitted to the experimental data. Result indicated that the drying took place in the falling rate period. Considering the statistical criteria such as coefficient of determination (R2), Chi square (X2), sum of square error (SSE) and root mean square error (RMSE), Midilli et al. model was found to fit well to describe the drying behaviour of long pepper. Multiple regression analysis was used to find the correlation of the model coefficients with temperatures. Model coefficient equations predicted the moisture ratio (MR) well at various drying temperatures for long pepper with an R2=1 and SE=0. Effective moisture diffusivity (Deff) was observed in the range of 1.397 × 10-10 to 6.190 × 10-10 m2s-1 for the temperature range of 40° to 80°C. The overall acceptability (OA) (90%) was highest in tray drying method at 60°C air temperature and the drying time was reduced to 50% against sun drying. This study will be useful to optimize drying process parameters for commercial production of dried long pepper. &nbsp

Department of Pathology, Government Medical College and Cancer Hospital, Aurangabad, Maharashtra, India

Background: The intrauterine existence of fetus is dependent on one vital organ 'the placenta’. The placenta reflects the status of maternal hypertension as it is the mirror of maternal and fetal health. The hypertensive disorders complicate 5-10% of all pregnancies and form a dangerous triad with haemorrhage and infection that contributes greatly to maternal morbidity and mortality. The fetus is dependent on placenta for growth and development. Many disorders of pregnancy like hypertension are accompanied by gross and histological changes in placenta. Aim of the study was to study the various morphological lesions of placenta in pregnancy induced hypertension and compare them with normal pregnanciesMethods: Gross and microscopic examination was conducted on 70 placentas. These included 15 normal placentas and 55 placentas from pregnancy induced hypertension.Results: In PIH, on gross the placenta showed areas of infarction, perivillous fibrin deposition and basal decidual haematoma, while microscopically showed increased syncytial knotting, cytotrophoblasitc proliferation, basement membrane thickening, vasculosyncytial membrane deficiency, infarction and fibrinoid necrosis.Conclusions: Maternal disorders affect the placental histology and can be detected by morphological examination of such placentae. The placenta from hypertensive pregnant women show significant morphological changes as compared to control, which may alter the perinatal outcome