Application of ameliorated Harris Hawks optimizer for designing of low-power signed floating-point MAC architecture

Neural Computing and Applications - Recently established Harris Hawks optimization (HHO) has natural behaviour for finding an optimum solution in global search space without getting trapped in...     

A semi-supervised domain adaptation assembling approach for image classification

Automatic annotation of images is one of the fundamental problems in computer vision applications. With the increasing amount of freely available images, it is quite possible that the training data used to learn a classifier has different distribution from the data which is used for testing. This results in degradation of the classifier performance and highlights the problem known as domain adaptation. Framework for domain adaptation typically requires a classification model which can utilize several classifiers by combining their results to get the desired accuracy. This work proposes depth-based and iterative depth-based fusion methods which are basically rank-based fusion methods and utilize rank of the predicted labels from different classifiers. Two frameworks are also proposed for domain adaptation. The first framework uses traditional machine learning algorithms, while the other works with metric learning as well as transfer learning algorithm. Motivated from ImageCLEF’s 2014 domain adaptation task, these frameworks with the proposed fusion methods are validated and verified by conducting experiments on the images from five domains having varied distributions. Bing, Caltech, ImageNet, and PASCAL are used as source domains and the target domain is SUN. Twelve object categories are chosen from these domains. The experimental results show the performance improvement not only over the baseline system, but also over the winner of the ImageCLEF’s 2014 domain adaptation challenge.     

The Intratumor Bacterial and Fungal Microbiome Is Characterized by HPV,Smoking, and Alcohol Consumption in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) tumor phenotypes and clinical outcomes are significantly influenced by etiological agents, such as HPV infection, smoking, and alcohol consumption. Accordingly, the intratumor microbiome has been increasingly implicated in cancer progression and metastasis. However, few studies characterize the intratumor microbial landscape of HNSCC with respect to these etiological agents. In this study, we aimed to investigate the bacterial and fungal landscape of HNSCC in association with HPV infection, smoking, and alcohol consumption. RNA-sequencing data were extracted from The Cancer Genome Atlas (TCGA) regarding 449 tissue samples and 44 normal samples. Pathoscope 2.0 was used to extract the microbial reads. Microbe abundance was compared to clinical variables, oncogenic signatures, and immune-associated pathways. Our results demonstrated that a similar number of dysregulated microbes was overabundant in smokers and nonsmokers, while heavy drinkers were characterized by an underabundance of dysregulated microbes. Conversely, the majority of dysregulated microbes were overabundant in HPV+ tumor samples when compared to HPV- tumor samples. Moreover, we observed that many dysregulated microbes were associated with oncogenic and metastatic pathways, suggesting their roles in influencing carcinogenesis. These microbes provide insights regarding potential mechanisms for tumor pathogenesis and progression with respect to the three etiological agents.     

Enhancement in Creep Strength of Modified 9CR–1MO Steel Through Thermo-Mechanical Treatment

In the present investigation, microstructure of the modified 9Cr–1Mo (T91) steel was refined through thermo-mechanical treatment (TMT). The finer precipitation of M₂₃C₆ and MX precipitates were observed in the TMT processed T91 steel. Creep deformation behaviour of T91 steel and TMT processed T91 steel was carried out at 923 K. The minimum creep rate of the TMT processed steel was significantly lowered as compared to T91 steel. The TMT processing of modified 9Cr–1Mo steel resulted in enhancement of creep strength due to presence of finer precipitates which relatively delayed the recovery of dislocation structure and coarsening of sub-boundaries than the steel in the normalized and tempered condition.     

低VOC涂料用成膜助剂

随着环保法规的日益严格和人们环境质量意识的增强,研发新型材料,采用新工艺是降低VOC的有效途径。本文介绍了新型油酸类无溶剂型成膜助剂,能有效降低涂料中的VOC含量以及提高涂料相应性能。     

Earthworm coelomocytes as nanoscavenger of ZnO NPs

Earthworms can ‘biotransform’ or ‘biodegrade’ chemical contaminants, rendering them harmless in their bodies, and can bioaccumulate them in their tissues. They ‘absorb’ the dissolved chemicals through their moist ‘body wall’ due to the interstitial water and also ingest by ‘mouth’ while soil passes through the gut. Since the advent of the nanotechnology era, the environmental sink has been continuously receiving engineered nanomaterials as well as their derivatives. Our current understanding of the potential impact of nanomaterials and their natural scavenger is limited. In the present investigation, we studied the cellular uptake of ZnO nanoparticles (NPs) by coelomocytes especially by chloragocytes of Eisenia fetida and their role as nanoscavenger. Results from exposure to 100- and 50-nm ZnO NPs indicate that coelomocytes of the earthworm E. fetida show no significant DNA damage at a dose lower than 3 mg/l and have the potential ability to uptake ZnO NPs from the soil ecosystem and transform them into microparticles.     

Neuroprotective Strategies for Traumatic Brain Injury: Improving Clinical Translation

Traumatic brain injury (TBI) induces secondary biochemical changes that contribute to delayed neuroinflammation, neuronal cell death, and neurological dysfunction. Attenuating such secondary injury has provided the conceptual basis for neuroprotective treatments. Despite strong experimental data, more than 30 clinical trials of neuroprotection in TBI patients have failed. In part, these failures likely reflect methodological differences between the clinical and animal studies, as well as inadequate pre-clinical evaluation and/or trial design problems. However, recent changes in experimental approach and advances in clinical trial methodology have raised the potential for successful clinical translation. Here we critically analyze the current limitations and translational opportunities for developing successful neuroprotective therapies for TBI.     

Non-equilibrium Thermodynamics of Rayleigh–Taylor Instability

Here, the fundamental problem of Rayleigh–Taylor instability (RTI) is studied by direct numerical simulation (DNS), where the two air masses at different temperatures, kept apart initially by a non-conducting horizontal interface in a 2D box, are allowed to mix. Upon removal of the partition, mixing is controlled by RTI, apart from mutual mass, momentum, and energy transfer. To accentuate the instability, the top chamber is filled with the heavier (lower temperature) air, which rests atop the chamber containing lighter air. The partition is positioned initially at mid-height of the box. As the fluid dynamical system considered is completely isolated from outside, the DNS results obtained without using Boussinesq approximation will enable one to study non-equilibrium thermodynamics of a finite reservoir undergoing strong irreversible processes. The barrier is removed impulsively, triggering baroclinic instability by non-alignment of density, and pressure gradient by ambient disturbances via the sharp discontinuity at the interface. Adopted DNS method has dispersion relation preservation properties with neutral stability and does not require any external initial perturbations. The complete inhomogeneous problem with non-periodic, no-slip boundary conditions is studied by solving compressible Navier–Stokes equation, without the Boussinesq approximation. This is important as the temperature difference between the two air masses considered is high enough (\(\Delta T = 70\) K) to invalidate Boussinesq approximation. We discuss non-equilibrium thermodynamical aspects of RTI with the help of numerical results for density, vorticity, entropy, energy, and enstrophy.