Buoyancy Effect on MHD Flow Past a Permeable Bed

In this paper, the effect of buoyancy force on the parallel flows bounded above by a rigid permeable plate which may be moving or stationary and below, by a permeable bed has been investigated. To discuss the solution, the flow region is divided into two zones. In Zone 1, the flow is laminar and is governed by the Navier-Stokes equations from the impermeable upper rigid plate to the permeable bed. In Zone 2, the flow is governed by the Darcy law in the permeable bed below the nominal surface. The expressions for velocity and temparature distributions, Slip velocity, slip temperature, mass flow rate and the rates of heat transfer coefficients are obtained. The effects of magnetic, porous, slip and buoyancy parameters and Biot number on the above physical quantities are investigated. The thickness of the boundary layer in Zone 2 has been evaluated

Enumeration of Triangles in a Divisor Cayley Graph

In this paper a new class of arithmetic Cayley graphs, namely, divisor Cayley graphs associated with the divisor function d ƒvnƒw , n „d1,an integer is introduced. It is shown that this graph is regular, hamiltonian, connected and not bipartite, and when n is odd it is eulerian. The enumeration of triangles in this graph is also presentedKey words: Arithmetic graph, Cayley graph, Hamilton cycle, Fundamental triangle and Triangle

Discussion of Potential Dangers of Simplifying Combined Sewer Hydrologic/Hydraulic Models” by Joshua P. Cantone and Arthur R. Schmidt

The authors of this paper provide a valuable discussion on the potential dangers of conduit skeletonization and subcatchment aggregation. For assessing these potential dangers, a base model (includes all sewers, nodes, inlets and gutters) and simplified models (successive removal of elements) of two catchments were used. The discussers congratulate the authors for their work on this relevant issue and for presenting their results in a clear and well organized way. The discussers however would like to raise some questions and comments regarding the results and their interpretation as presented in the paper

Optimization of Deep CNN Techniques to Classify Breast Cancer and Predict Relapse

Breast cancer is a fatal disease that has a high rate of morbidity and mortality. Finding the right diagnosis is one of the most crucial steps in breast cancer treatment. Doctors can use machine learning (ML) and deep learning techniques to aid with diagnosis. This work makes an effort to devise a methodology for the classification of Breast cancer into its molecular subtypes and prediction of relapse. The objective is to compare the performance of Deep CNN, Tuned CNN and Hypercomplex-Valued CNN, and infer the results, thus automating the classification process. The traditional method used by doctors to detect is tedious and time consuming. It employs multiple methods, including MRI, CT scanning, aspiration, and blood tests as well as image testing. The proposed approach uses image processing techniques to detect irregular breast tissues in the MRI. The survivors of Breast Cancer are still at risk for relapse after remission, and once the disease relapses, the survival rate is much lower. A thorough analysis of data can potentially identify risk factors and reduce the risk of relapse in the first place. A SVM (Support Vector Machine) module with GridSearchCV for hyperparameter tuning is used to identify patterns in those patients who experience a relapse, so that these patterns can be used to predict the relapse before it occurs. The traditional deep learning CNN model achieved an accuracy of 27%, the tuned CNN model achieved an accuracy of 92% and the hypercomplex-valued CNN achieved an accuracy of 98%. The SVM model achieved an accuracy of 89% and on tuning the hyperparameters by using GridSearchCV it achieved and accuracy of 98%

An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation

Improvements and acceleration in software development have contributed towards high-quality services in all domains and all fields of industry, causing increasing demands for high-quality software developments. The industry is adopting human resources with high skills, advanced methodologies, and technologies to match the high-quality software development demands to accelerate the development life cycle. In the software development life cycle, one of the biggest challenges is the change management between the version of the source codes. Various reasons, such as changing the requirements or adapting available updates or technological upgrades, can cause the source code's version. The change management affects the correctness of the software service's release and the number of test cases. It is often observed that the development life cycle is delayed due to a lack of proper version control and due to repetitive testing iterations. Hence the demand for better version control-driven test case reduction methods cannot be ignored. The parallel research attempts propose several version control mechanisms. Nevertheless, most version controls are criticized for not contributing toward the test case generation of reduction. Henceforth, this work proposes a novel probabilistic rule-based test case reduction method to simplify the software development's testing and version control mechanism. Software developers highly adopt the refactoring process for making efficient changes such as code structure and functionality or applying changes in the requirements. This work demonstrates very high accuracy for change detection and management. This results in higher accuracy for test case reductions. The outcome of this work is to reduce the development time for the software to make the software development industry a better and more efficient world

Neuroprotective Effects of Bikaverin on H2O2-Induced Oxidative Stress Mediated Neuronal Damage in SH-Sy5y Cell Line

The generation of free radicals and oxidative stress has been linked to several neurodegenerative diseases including Parkinson's disease, Alzheimer's disease, Huntington's disease, and Amyotrophic lateral sclerosis. The use of free radical scavenging molecules for the reduction of intracellular reactive oxygen species is one of the strategies used in the clinical management of neurodegeneration. Fungal secondary metabolism is a rich source of novel molecules with potential bioactivity. In the current study, bikaverin was extracted from Fusarium oxysporum f. sp. lycopersici and its structural characterization was carried out. Further, we explored the protective effects of bikaverin on oxidative stress and its anti-apoptotic mechanism to attenuate H2O2-induced neurotoxicity using human neuroblastoma SH-SY5Y cells. Our results elucidate that pretreatment of neurons with bikaverin attenuates the mitochondrial and plasma membrane damage induced by 100 µM H2O2 to 82 and 26 % as evidenced by MTT and LDH assays. H2O2 induced depletion of antioxidant enzyme status was also replenished by bikaverin which was confirmed by Realtime Quantitative PCR analysis of SOD and CAT genes. Bikaverin pretreatment efficiently potentiated the H2O2-induced neuronal markers, such as BDNF, TH, and AADC expression, which orchestrate the neuronal damage of the cell. The H2O2-induced damage to cells, nuclear, and mitochondrial integrity was also restored by bikaverin. Bikaverin could be developed as a preventive agent against neurodegeneration and as an alternative to some of the toxic synthetic antioxidants

Impact of recent cyclone on the marine fishery sector along the east Godavari and Visakhapatnam districts of Andhra Pradesh

A cyclone which lashed along the coastal Andhra Pradesh on the night of 6-11-'96 resulted in the loss of thousands of human lives and materials. The coast of East Godavari and parts of Visakhapatnam districts were the worst hit areas with high velocity winds bringing in huge tidal waves which inundated the fish landing centres

Botox in periodontics - Exploring new avenues

From a periodontal point of view, various factors contribute to facial aesthetics. In the recent past, studies have revealed that excessive gingival display is a factor that influences an individual’ smile line. Some literature exists to support that more than excessive gingival display of more than 3mm is considered unaesthetic and termed a ‘gummy smile’ (GS). The prevalence of 'gummy smile’ has been 10% and to be more common in females. Gingival hyperplasia altered passive eruption, vertical maxillary excess, and upper-lip hypermobility can all result in excessive gingival display when a patient smile.To select the correct treatment protocol, accurate diagnosis is essential. Various techniques have been used to treat gummy smile which includes surgical and non-surgical methods. Recently a non-surgical method using Botulinum toxin gained popularity considering that the method is minimally invasive