Effect of interface coupling between polarization and magnetization in La0.7Pb0.3MnO3 (LPMO)/P(VDF-TrFE) flexible nanocomposite films

Journal of Materials Science - La0.7Pb0.3MnO3(LPMO) nanoparticles (NPs) were prepared by sol–gel auto-combustion method. These were embedded in P(VDF-TrFE) to form (0–3) nanocomposite...     

Mobile data offloading based on minority game theoretic framework

Wireless Networks - Mobile data offloading is a current-day networking paradigm to channelize certain fraction of the cellular data traffic over unlicensed spectrum of WiFi. In this paper, we...     

E7766, a Macrocycle-Bridged Stimulator of Interferon Genes (STING) Agonist with Potent Pan-Genotypic Activity

A strategy for creating potent and pan-genotypic stimulator of interferon genes (STING) agonists is described. Locking a bioactive U-shaped conformation of cyclic dinucleotides by introducing a transannular macrocyclic bridge between the nucleic acid bases leads to a topologically novel macrocycle-bridged STING agonist (MBSA). In addition to substantially enhanced potency, the newly designed MBSAs, exemplified by clinical candidate E7766 , exhibit broad pan-genotypic activity in all major human STING variants. E7766 is shown to have potent antitumor activity with long lasting immune memory response in a mouse liver metastatic tumor model. Two complementary stereoselective synthetic routes to E7766 are also described.     

Interpretable semantic textual similarity of sentences using alignment of chunks with classification and regression

Applied Intelligence - The proposed work is focused on establishing an interpretable Semantic Textual Similarity (iSTS) method for a pair of sentences, which can clarify why two sentences are...     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

Modelling and kinetic aspects of a BTEX contaminated air-treating biofilter

In this study, the overall performance of a biofilter was evaluated in terms of its elimination capacity by using 3-D mesh techniques. The overall results indicate that the agreement between experimental data and model predictions is excellent for benzene, toluene, ethylbenzene and o-xylene (BTEX). In this study, the maximum removal rate (r _max) values for BTEX were 0.0117, 0.0126, 0.0081 and 0.0146 g m^–3 h^–1, and the half-saturation constant (K_S ) values were calculated to be 0.269, 0.297, 0.156 and 0.394 g m^–3, respectively. For this system, the coefficients of determination (r ²) of BTEX compounds were greater than 0.97. The BTEX concentration profiles along the depth were also determined using a convection–diffusion reactor (CDR) model. The sums of squares of the errors (SSEs) of BTEX were 0.0078, 0.0059, 0.0129 and 0.0269, respectively, with r ² values greater than 0.99 for all four compounds at low concentrations.     

Electricity Generation and Wastewater Treatment of Oil Refinery in Microbial Fuel Cells Using Pseudomonas putida

Microbial fuel cells (MFCs) represent a novel platform for treating wastewater and at the same time generating electricity. Using Pseudomonas putida (BCRC 1059), a wild-type bacterium, we demonstrated that the refinery wastewater could be treated and also generate electric current in an air-cathode chamber over four-batch cycles for 63 cumulative days. Our study indicated that the oil refinery wastewater containing 2213 mg/L (ppm) chemical oxygen demand (COD) could be used as a substrate for electricity generation in the reactor of the MFC. A maximum voltage of 355 mV was obtained with the highest power density of 0.005 mW/cm² in the third cycle with a maximum current density of 0.015 mA/cm² in regard to the external resistor of 1000 Ω. A maximum coulombic efficiency of 6 × 10⁻²% was obtained in the fourth cycle. The removal efficiency of the COD reached 30% as a function of time. Electron transfer mechanism was studied using cyclic voltammetry, which indicated the presence of a soluble electron shuttle in the reactor. Our study demonstrated that oil refinery wastewater could be used as a substrate for electricity generation.     

Using Singular Value Decomposition to Characterize Protein–Protein Interactions by In‐cell NMR Spectroscopy

Distinct differences between how model proteins interact in‐cell and in vitro suggest that the cytosol might have a profound effect in modulating protein–protein and/or protein–ligand interactions that are not observed in vitro. Analyses of in‐cell NMR spectra of target proteins interacting with physiological partners are further complicated by low signal‐to‐noise ratios, and the long overexpression times used in protein–protein interaction studies may lead to changes in the in‐cell spectra over the course of the experiment. To unambiguously resolve the principal binding mode between two interacting species against the dynamic cellular background, we analyzed in‐cell spectral data of a target protein over the time course of overexpression of its interacting partner by using single‐value decomposition (SVD). SVD differentiates between concentration‐dependent and concentration‐independent events and identifies the principal binding mode between the two species. The analysis implicates a set of amino acids involved in the specific interaction that differs from previous NMR analyses but is in good agreement with crystallographic data.     

Some studies on uncertainty management in dynamical systems using cybernetic approaches and fuzzy techniques with applications

Uncertain information processing by fuzzy if–then rules has received much attention. Here we have taken a different path to model a system, about which we do not have precise information, namely modelling the system by fuzzy-valued functions without resorting to fuzzy if–then rules. As a result, the phase (state) space of the system becomes a fuzzy set and the underlying fuzzy mapping becomes a fuzzy attainability set mapping. Uncertain or fuzzy dynamical systems have been defined in terms of fuzzy attainability set mappings. Fuzzy differentiable dynamical systems have been discussed with a particular emphasis on fuzzy differential inclusion (FDI) relations. An evolutionary algorithm for solving one-dimensional FDIs has been developed. A model of the creation of a tropical cyclone in the form of a vortex, created by winds coming from different directions and colliding under certain conditions, has been proposed in terms of FDIs. A model has been considered for the highly uncertain system of evolution of a tumour in a human body and an FDI relation model of the whole system has been proposed and simulated. The model of an evolution of turbulence, as a random occurrence of vortices in a three-dimensional dynamic fluid, has been proposed and simulated, where each vortex is modelled by a fuzzy-valued function, where uncertain parameter and variable values are fuzzy numbers. All the systems represented by FDI relations have been simulated with the help of the evolutionary algorithm mentioned above.