Raman studies of structural rearrangements induced in human plasma lipoprotein carotenoids by malondialdehyde

Raman and resonance Raman spectra of plasma lipoproteins ± malondialdehyde were studied at concentrations which block the normal receptor-mediated uptake by cells. The strong resonance Raman bands at about 1010, 1162 and 1530 cm⁻¹, due to the presence of carotenoids in the lipoproteins, are envisaged as structural probes. High resolution resonance Raman spectra of the 1500–1600 cm⁻¹ region reveal multiple features suggesting the coexistence of several structural populations of β-carotene whose precise assignment is complex. When plasma lipoproteins are reacted with malondialdehyde, a complex change occurs in the resonance Raman banding of β-carotene in the 1500–1600 cm⁻¹ region. Malonaldehyde (MDA) also modifies the acoustical region (70–200 cm⁻¹ of low density lipoprotein (LDL) lipids. We suggest that malondialdehyde association with plasma lipoproteins alters the lipid structure via apoprotein or apoprotein/lipid associations.     

An analytical expression for the power coefficient of an ideal horizontal-axis wind turbine

The paper shows that an analytical evaluation of the power coefficient C_p for an ideal horizontal-axis wind turbine can be made via an expression giving the direct relationship of C_p and the axial induction factor a. The results obtained agree closely with those obtained numerically from the usual integral expression involving several variables.     

Multiperson interaction recognition in images: A body keypoint based feature image analysis

Most interaction recognition approaches have been limited to single‐person action classification in videos. However, for still images where motion information is not available, the task becomes more complex. Aiming to this point, we propose an approach for multiperson human interaction recognition in images with keypoint‐based feature image analysis. Proposed method is a three‐stage framework. In the first stage, we propose feature‐based neural network (FCNN) for action recognition trained with feature images. Feature images are body features, that is, effective distances between a set of body part pairs and angular relation between body part triplets, rearranged in 2D gray‐scale image to learn effective representation of complex actions. In the later stage, we propose a voting‐based method for direction encoding to anticipate probable motion in steady images. Finally, our multiperson interaction recognition algorithm identifies which human pairs are interacting with each other using an interaction parameter. We evaluate our approach on two real‐world data sets, that is, UT‐interaction and SBU kinect interaction. The empirical experiments show that results are better than the state‐of‐the‐art methods with recognition accuracy of 95.83% on UT‐I set 1, 92.5% on UT‐I set 2, and 94.28% on SBU clean data set.     

Correction to: EDVWDD: Event‑Driven Virtual Wheel‑based Data Dissemination for Mobile Sink‑Enabled Wireless Sensor Networks

The Journal of Supercomputing - A correction to this paper has been published: https://doi.org/10.1007/s11227-021-03790-9     

High-utility and diverse itemset mining

High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-utility with diversity to define a new pattern type called High-utility and Diverse pattern (HUD). The notion of diversity of a pattern captures the extent of the different categories covered by the selected items in the pattern. An application of diverse-pattern lies in the recommendation task where a system can recommend to a customer a set of items from a new class based on her previously bought items. Our notion of diversity is easy to compute and also captures the basic essence of a previously proposed diversity notion. The existing algorithm to compute frequent-diverse patterns is 2-phase, i.e., in the first phase, frequent patterns are computed, out of which diverse patterns are filtered out in the second phase. We, in this paper, give an integrated algorithm that efficiently computes high-utility and diverse patterns in a single phase. Our experimental study shows that our proposed algorithm is very efficient as compared to a 2-phase algorithm that extracts high-utility itemsets in the first phase and filters out the diverse itemsets in the second phase.

     

An efficient neural-network model for real-time fault detection in industrial machine

Neural Computing and Applications - Induction machines have extensive demand in industries as they are used for large-scale production and, therefore, vulnerable to both electrical and mechanical...     

Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient’s immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.     

Ionic liquid mediated nano-composite polymer gel electrolyte for rechargeable battery application

ABSTRACT

Nano-composite polymer gel electrolytes (NPGEs) based on polymer poly(vinylidene fluoride-co-hexafluoropropylene) PVdF-HFP, ionic liquid, 1-butyl-3- methylimidazolium bis(trifluoromethanesulfonyl)imide BMIMTFSI, Li-salt along with the addition of SiO₂ nanoparticles have been synthesized and characterized by various techniques. Prepared NPGEs show high room temperature ionic conductivity (~10^?3 S/cm) and have a wide electrochemical window (ECW) (~3.3–3.5 V). The galvanostatic charge/discharge profile was studied by sandwiching best performing NPGEs between a LiFePO₄ cathode and lithium metal anode. The specific discharge capacity of the cell (Li/NPGE/LiFePO₄) room temperature at 0.1C rate is found to be 138 mAh/g.