Detection of spinal cord injury (SCI) is one of the major problems in MRI images to detect the affected portion of spinal cord regions using feature sets. Automatic detection of spinal cord atrophy is complex due to change in structure, size, and white matter. Delineating gray matter and white matter are the essential factors that influence the detection of spinal cord atrophy and its severity. Automatic segmentation and classification are accurate methods for detecting the severity of the SCI. Hierarchical segmentation, partitioning segmentation, graph, and watershed segmentation methods are used to find the SCI segments in static fixed positions. Also, these segmentation models result in a high false positive rate due to over segmentation features and noise in the segmented regions. Furthermore, these classification methods fail to segment and detect the severity level in the affected region due to over segmentation. In order to overcome these issues, a novel segment-based classification model is required to find the severity of the injury and to predict the disease patterns on the over segmented regions and features. In the present model, a hybrid image threshold technique is used to segment the spinal cord regions for non-linear SVM classification approach. Among the traditional feature segmentation-based classification models, the proposed threshold-based non-linear SVM has better accuracy for SCI detection. The results proved that the present model is more efficient than the earlier approaches in terms of true positive rate ( $\text {TP}=0.9783$ ) and accuracy (0.9683).

The maximum benefit out of the recent developments in sensor networking can be achieved via the integration of sensors with Internet. The real-time specific sensor data must be processed and the action must be taken instantaneously. The integration controller module of the proposed architecture integrates the sensor network and Internet using Cloud Technology which offers the benefit of reliability, availability and extensability.

Paraquat is a bipyridilium herbicide used widely in our country and is a highly toxic compound. A 16-year-old female patient was admitted to the emergency department of our tertiary care hospital in South India with the history of alleged consumption of paraquat poison. Since there is dearth of high quality evidence- based treatment for this poisoning, different treatment modalities have been tried to manage patient's condition. In this case, none of the strategies could work well. Most of the patients reported with paraquat intoxication are from agricultural background; usually such patients cannot afford the treatment expenses. This paper presents a fatal case of acute poisoning with paraquat who succumbed to acute respiratory distress syndrome (ARDS).

In the field of convective energy transfer, natural convection is one of the most studied phenomena, with applications ranging from heat exchangers and geothermal energy systems to hybrid nanofluids. The aim of this paper is to scrutinize the free convection of a ternary hybrid nanosuspension (Al₂O₃-Ag-CuO/water ternary hybrid nanofluid) in an enclosure with a linearly warming side border. The ternary hybrid nanosuspension motion and energy transfer have been modelled by partial differential equations (PDEs) with appropriate boundary conditions by the single-phase nanofluid model with the Boussinesq approximation. The finite element approach is applied to resolve the control PDEs after transforming them into a dimensionless view. The impact of significant characteristics such as the nanoparticles’ volume fraction, Rayleigh number, and linearly heating temperature constant on the flow and thermal patterns combined with the Nusselt number has been investigated and analyzed using streamlines, isotherms, and other suitable patterns. The performed analysis has shown that the addition of a third kind of nanomaterial allows for intensifying the energy transport within the closed cavity. The transition between uniform heating to non-uniform heating of the left vertical wall characterizes the heat transfer degradation due to a reduction of the heat energy output from this heated wall.