Energy optimization for CAN bus and media controls in electric vehicles using deep learning algorithms

The Journal of Supercomputing - This study offers a neural network-based deep learning method for energy optimization modeling in electric vehicles (EV). The pre-processed driving cycle is...     

Topical delivery of paclitaxel for treatment of skin cancer

Context: Skin cancer represents the most growing types of cancer in human and ultraviolet radiation can be cited as one of the prime factor for its occurrence. Current therapy of skin cancer suffers from numerous side effects; for effective therapy, topical application of formulation of paclitaxel (PTX) can be considered as a novel approach.

Objective: The present study is an attempt to prepare formulation of solid lipid nanoparticles (SLN) of PTX for the effective treatment of various form of skin carcinoma.

Methods: The SLN were prepared by high-speed homogenization and ultrasonication method. The prepared SLN were characterized. The optimized PTX SLN were loaded in carbopol gel. The prepared gels were evaluated for its gelling properties and finally studied for in vivo anti-cancer efficacy and histopathological study.

Results: The particle size distribution was found to be in the range of 78.82–587.8?nm. The product yield (%) was found between 60% and 66% and showed a highest entrapment efficiency of 68.3%. The in vitro release of the drug from SLN dispersion was found to be biphasic with the initial burst effect, followed by slow release. SLN-loaded gel were subjected to permeability study and the results show steady-state flux (J_ss), permeability coefficient (K_p), and enhancement ratio were significantly increased in SLN-loaded gel formulation as compared with PTX-loaded gel. The histopathological study clearly reveals the efficacy of the SLN-F3 3G in the treatment of skin cancer.

Conclusion: The experimental formulations show controlled release of PTX and thus expected to show reduce dose-related side effects.     

On the effect of tool offset in hybrid-FSW of copper-aluminium alloy

Tool offset is one the most significant parameters in joining of dissimilar materials by friction stir welding (FSW) process. An investigation is carried out on the effect of tool offset toward thermal history, material flow pattern, mechanical properties, welding force, and weld joint morphology. It was found that offsetting toward aluminum side along with a plasma-assisted heat source is an efficient approach to address one of the most important apprehensions in aluminum-copper solid-state welding process. The offset influences the amount of intermetallic at the joint interface and in-effect impacts on final strength and material flow behavior. The optimum and continuous layer of intermetallic produces the maximum weld joint strength. The specimen welded with optimum tool offset shows the highest strength using 55 A plasma current in hybrid friction stir welding process.     

All‐Organic Dual Spin Valves with Well‐Resolved Four Resistive‐States

The formation of all‐organic dual spin valves (DSVs) with three organic spin‐selective layers, that is, spin‐injection, spin‐detection, and an additional spin‐filtering layer at the intermediate, is reported. As spin‐selective layers, manganese‐ and cobalt phthalocyanines, which are well‐known single‐molecule magnets, are used in their immobilized forms, so that all‐organic DSVs can be prefabricated for characterization. The three spin‐selective layers have provided four configurations with at most two spin‐flip interfaces enforcing spin‐flipping at the two nonmagnetic organic spacer layers, for which copper phthalocyanine is used. Since a couple of the four configurations have exhibited similar resistivities, the degeneracy in the resistive‐states is broken through asymmetric spin‐injection and spin‐detection layers and also through asymmetric thickness of the nonmagnetic spacer layers. When both the spin‐flip interfaces are made operative independently, a 2‐bit logic with four distinct resistive states can be achieved.     

Vibration data-driven machine learning architecture for structural health monitoring of steel frame structures

A vibration data-based machine learning architecture is designed for structural health monitoring (SHM) of a steel plane frame structure. This architecture uses a Bag-of-Features algorithm that extracts the speeded-up robust features (SURF) from the time-frequency scalogram images of the registered vibration data. The discriminative image features are then quantised to a visual vocabulary using K-means clustering. Finally, a support vector machine (SVM) is trained to distinguish the undamaged and multiple damage cases of the frame structure based on the discriminative features. The potential of the machine learning architecture is tested for an unseen dataset that was not used in training as well as with some datasets from entirely new damages close to existing (i.e., trained) damage classes. The results are then compared with those obtained using three other combinations of features and learning algorithms—(i) histogram of oriented gradients (HOG) feature with SVM, (ii) SURF feature with k-nearest neighbours (KNN) and (iii) HOG feature with KNN. In order to examine the robustness of the approach, the study is further extended by considering environmental variabilities along with the localisation and quantification of damage. The experimental results show that the machine learning architecture can effectively classify the undamaged and different joint damage classes with high testing accuracy that indicates its SHM potential for such frame structures.     

Optimization of process variables in drilling of carbon fiber reinforced plastics using various multi criteria decision making approaches

Carbon fiber-reinforced polymers are one of the lightweight materials used in structural design due to their exceptional mechanical performances. The drilling operation is indispensable as it facilitates the assembling of various manufactured components. However, drilling of fibrous laminates is deemed difficult in comparison to the traditional metals because of the anisotropic and non-homogeneous nature. The present work addresses the parametric effect on the drilled hole delamination and further reduces it with an optimal combination of parameters for multi-objectives using different multi-criterion decision-making techniques. Initially, the response surface-based regression model of delamination as a function of three static inputs has been developed, further revised with induced thrust as well as mean torque for the improvisation of the prediction capability. Finally, for the overall improvement, a decision-making model has been used that includes grey relation analysis, technique for order performance by similarity to ideal solution, and VIšekriterijumsko Kompromisno Rangiranje method. The delamination was found to be minimum at a low drill point angle (100°), high spindle rotation (2150 min⁻¹ ), and low feed rate (0.025 mm/rev) due to reduced thrust force. The mean absolute prediction error was significantly improved considering root mean square torque rather than axial thrust with process variables.     

Gains and losses of the XII-VII component of the "baby-sitter" procedure: a morphometric analysis

The classic hypoglossal transfer to the facial nerve is invariably followed by complications caused by tongue atrophy. In 1984, Terzis introduced the "baby-sitter" procedure which involved a formal cross-facial procedure, in addition to partial neurectomy of the hypoglossal nerve, and an end-to-side coaptation with the ipsilateral facial nerve. This reported study provides, for the first time, quantification of the number of hypoglossal motor fibers needed to successfully restore eye sphincter function, using an end-to-side coaptation with preservation of the tongue. Thirty adult Sprague-Dawley rats were divided into six groups: control, denervated, perineurial window, 20 percent partial neurectomy (PN), 40 percent PN, and 80 percent PN. The procedure involves interposing a nerve graft (saphenous) between the partially severed XII nerve and the upper zygomatic branch of the facial nerve. Evaluation of the behavioral data (blink reflex) revealed good-to-superb return of the blinking mechanism in the 40 percent group, without significant tongue atrophy. Electrophysiologic data in the 40 percent neurectomy group demonstrated superiority to the other groups. Quantitative axonal morphometry of the coaptation sites and graft, as well as motor end-plates of the orbicularis oculi muscle and tongue showed the 40 percent partial neurectomy group to be the optimal group.     

Exploring the genetic and environmental etiology of high general cognitive ability in fourteen- to thirty-six-month-old twins

Two definitions of normality ("isolated" or "correlated") are considered. The boundaries of "isolated" normality were determined by a statistical procedure, whereas the "correlated" approach was related to a clinical or predictive definition. In the latter case, the biological variations were considered abnormal if they implied a hazard with some significant future ailment as a risk factor. In this pragmatic approach, the upper limit of normal/abnormal variations is the point beyond which medical strategy is related to the most expected benefit when applied to a definite population or to an individual patient. The capacity of a diagnostic test to discriminate between patients with a defined risk and those without risk depends strictly on the value of the parameter chosen. In medical care for the prevention of vascular complications in diabetic patients or with foetal risks in pregnant women, the limits of the so-called normal range of glycaemia and other parameters should be determined according to the objective of the preventive and/or therapeutic measures to be prescribed.     

Gender-related differences in susceptibility of A/J mouse to benzo[a]pyrene-induced pulmonary and forestomach tumorigenesis

A commercial patient dose verification system utilizing non-invasive metal oxide semiconductor field effect transistor (MOSFET) dosimeters originally designed for radiotherapy applications has been evaluated for use at diagnostic energy levels. The system features multiple dosimeters that may be used to monitor entrance or exit skin dose and intracavity doses in phantoms in real time. We have characterized both the standard MOSFET dosimeter designed for radiotherapy dose verification and a newly developed "high sensitivity" MOSFET dosimeter designed for lower dose measurements. The sensitivity, linearity, angular response, post-exposure response, and physical characteristics were evaluated. The average sensitivity (free in air, including backscatter) of the radiotherapy MOSFET dosimeters ranged from 3.55 x 10(4) mV per C kg(-1) (9.2 mV R(-1)) to 4.87 x 10(4) mV per C kg(-1) (12.6 mV R(-1)) depending on the energy of the x-ray field. The sensitivity of the "high sensitivity" MOSFET dosimeters ranged from 1.15 x 10(5) mV per C kg(-1) (29.7 mV R(-1)) to 1.38 x 10(5) mV per C kg(-1) (35.7 mV R(-1)) depending on the energy of the x-ray field. The high sensitivity dosimeters demonstrated excellent linearity at high energies (90 and 120 kVp) and acceptable linearity at lower energies (60 kVp). The angular response was significant for free-in-air exposures, as illustrated by the sensitivity differences between the two sides of the dosimeter, but was excellent for measurements within a tissue equivalent cylinder. The post-exposure drift response is a complicated but reproducible function of time. Real-time monitoring requires little if any corrections for the post-exposure drift response. The MOSFET dosimeter system brings some unique capabilities to diagnostic radiology dosimetry including small size, real-time capabilities, nondestructive measurement, good linearity, and a predictable angular response.