Radiation-Induced Senescence Reprograms Secretory and Metabolic Pathways in Colon Cancer HCT-116 Cells

Understanding the global metabolic changes during the senescence of tumor cells can have implications for developing effective anti-cancer treatment strategies. Ionizing radiation (IR) was used to induce senescence in a human colon cancer cell line HCT-116 to examine secretome and metabolome profiles. Control proliferating and senescent cancer cells (SCC) exhibited distinct morphological differences and expression of senescent markers. Enhanced secretion of pro-inflammatory chemokines and IL-1, anti-inflammatory IL-27, and TGF-β1 was observed in SCC. Significantly reduced levels of VEGF-A indicated anti-angiogenic activities of SCC. Elevated levels of tissue inhibitors of matrix metalloproteinases from SCC support the maintenance of the extracellular matrix. Adenylate and guanylate energy charge levels and redox components NAD and NADP and glutathione were maintained at near optimal levels indicating the viability of SCC. Significant accumulation of pyruvate, lactate, and suppression of the TCA cycle in SCC indicated aerobic glycolysis as the predominant energy source for SCC. Levels of several key amino acids decreased significantly, suggesting augmented utilization for protein synthesis and for use as intermediates for energy metabolism in SCC. These observations may provide a better understanding of cellular senescence basic mechanisms in tumor tissues and provide opportunities to improve cancer treatment.     

Electric field assisted solid-state interfacial joining of TaC-HfC ceramics without filler

The application of ultra-high-temperature ceramics (UHTCs) demands effective ways of joining in overcoming the problems associated with the fabrication of complex-shaped components. In this study, we choose to investigate a new method of rapidly joining pre-sintered TaC and HfC ceramics without any filler material using the spark plasma sintering (SPS) technique. A well-bonded TaC–HfC interface was observed with no apparent cracking and porosity at the joint. The joining mechanisms were predominantly driven by solid-state diffusion and localized plastic deformation. The nanomechanical properties of the TaC-HfC joint are better than the HfC while comparable to that of the TaC. High-load indentation (up to 200 N) results suggest that the TaC–HfC interface is stronger than the parent UHTCs with no crack propagating at the interface. Upon comparison with the parent UHTCs, the damaged area and the average crack length at the interface, reduced up to ~94% and ~56%, respectively. This study shows that the SPS technique can also apply to joining other UHTCs without any filler, resulting in the new field of developing complex components for the thermal protection system (TPS).     

Alpha Fusion Adversarial Attack Analysis Using Deep Learning

The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN classification model is developed for classifying COVID-CT images. Secondly, an alpha fusion attack is generated to fool the classification model. The alpha fusion attack is tested in the last phase on a modified LSTM-based CNN (CNN-MLSTM) model and other pre-trained models. The results of CNN models show that the accuracy of these models dropped greatly after the alpha-fusion attack. The highest F1 score before the attack was achieved is 97.45 And after the attack lowest F1 score recorded is 22%. Results elucidate the performance in terms of accuracy, precision, F1 score and Recall.     

Design of backpropagated neurocomputing paradigm for Stuxnet virus dynamics in control infrastructure

Neural Computing and Applications - In the present study, a novel application of backpropagated neurocomputing heuristics (BNCH) is presented for epidemic virus model that portrays the Stuxnet...     

PIV investigations on particle velocity distribution in uniform swirling regime of fluidization

In this study, hydrodynamics of spherical particles in uniform swirling regime of a fluidized bed were investigated using MATLAB supported particle imaging velocimetry (PIV). A least investigated mesh-type distributor was used to fluidize the bed particles, at different air entry angles, for future applications in coating and granulation industry. A quarter of the bed was photographed using high speed imaging technique and the respective velocity fields of the swirling particles were produced using PIV technique. The Gaussian distribution of the particle velocity profiles was predicted at low superficial air velocity; particles near the border of the bed showed relatively low velocity than that swirled in the middle of the test section. However, at high superficial velocity, the particles near the central cone moved with velocity comparable to the particle velocity in the middle of the test section. Contrarily, the particles in the vicinity of the outer bed-wall maintained their steady state motion at all superficial air velocities. The average particle velocity experienced monotonic increase for more angular air intake. The magnitude of the particle velocity reduced by 6.35% for each \(3^{\circ }\) increment in the air entry angle.     

Low‐temperature synthesis of hierarchical structures of copper oxide and their superior biological activity

In this work, the authors report a facile low‐temperature wet‐chemical route to prepare morphology‐tailored hierarchical structures (HS) of copper oxide. The preparation of copper oxide collides was carried out using varying concentrations of copper acetate and a reducing agent at a constant temperature of 50°C. The prepared HS of CuO were characterised by powdered X‐rays diffraction that indicates phase pure having monoclinic structures. The morphology was further confirmed by field‐emission scanning electron microscope. It reveals a difference in shape and size of copper oxide HS by changing the concentration of reactants. In order to evaluate the effect of H₂ O₂ on CuO NPs, the prepared CuO are modified by treatment with H₂ O₂. In general trend, CuOH₂ O₂ collide showed enhanced protein kinase inhibition, antibacterial (maximum zone 16.34 mm against Staphylococcus aureus) and antifungal activities in comparison to unmodified CuO collides. These results reveal that CuO HS exhibit antimicrobial properties and can be used as a potential candidate in pharmaceutical industries.Inspec keywords: molecular biophysics, antibacterial activity, X‐ray diffraction, microorganisms, copper compounds, nanofabrication, nanoparticles, narrow band gap semiconductors, field emission scanning electron microscopy, enzymes, nanomedicine, particle size, semiconductor growthOther keywords: unmodified CuO collides, low‐temperature synthesis, morphology‐tailored hierarchical structures, copper acetate, reducing agent, monoclinic structures, copper oxide HS, CuO NPs, Staphylococcus aureus, biological activity, copper oxide, powdered X‐ray diffraction, field‐emission scanning electron microscopy, facile low‐temperature wet‐chemical method, protein kinase inhibition, antibacterial activity, antifungal activity, antimicrobial properties, pharmaceutical industries, temperature 50.0 degC, CuO     

A Service Level Agreement Aware Online Algorithm for Virtual Machine Migration

The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be designed. One specific area where energy efficient algorithms are required is virtual machine consolidation. With virtual machine consolidation, the objective is to utilize the minimum possible number of hosts to accommodate the required virtual machines, keeping in mind the service level agreement requirements. This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host. The online algorithm is analyzed using a competitive analysis approach. In addition, an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms. Our proposed online algorithm consumed 25% less energy and performed 43% fewer migrations than the benchmark algorithms.     

Comparative Review on Structure,Properties, Fabrication Techniques,and Relevance of Polymer Nanocomposites Reinforced with Carbon Nanotube and Graphite Fillers

Owing to their remarkable electrical, mechanical, thermal, catalytic, and optical properties as well as their unique structure, carbon nanotubes and graphite have been exploited to produce high performance and multifunctional composites. The resultant composites are differentiated on the basis of their properties to meet various applications. In the framework of this review article, we have mainly focused on the preparation, structure, and properties of two families of composite materials with an emphasis on the differences between them. Moreover, the current challenges, future prospectives, and applications of carbon nanotubes- and graphite-based materials in sensors and in photovoltaic and energy storage devices (Li-ion battery) have been discussed.