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Human activity recognition (HAR) has become a significant area of research in human behavior analysis, human–computer interaction, and pervasive computing. Recently, deep learning (DL)-based methods have been applied successfully to time-series data generated from smartphones and wearable sensors to predict various activities of humans. Even though DL-based approaches performed very well in activity recognition, they are still facing challenges in handling time series data. Several issues persist with time-series data, such as difficulties in feature extraction, heavily biased data, etc. Moreover, most of the HAR approaches rely on manual feature engineering. In this paper, to design a robust classification model for HAR using wearable sensor data, a hybrid of convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) is used. The proposed multibranch CNN-BiLSTM network does automatic feature extraction from the raw sensor data with minimal data pre-processing. The use of CNN and BiLSTM makes the model capable of learning local features as well as long-term dependencies in sequential data. The different filter sizes used in the proposed model can capture various temporal local dependencies and thus helps to improve the feature extraction process. To evaluate the model performance, three benchmark datasets, i.e., WISDM, UCI-HAR, and PAMAP2, are utilized. The proposed model has achieved 96.05%, 96.37%, and 94.29% accuracies on WISDM, UCI-HAR, and PAMAP2 datasets, respectively. The obtained experimental results demonstrate that the proposed model outperforms the other compared approaches.

A bstract It is natural to expect a consistent inflationary model of the very early Universe to be an effective theory of quantum gravity, at least at energies much less than the Planck one. For the moment, R + R 2 , or shortly R 2 , inflation is the most successful in accounting for the latest CMB data from the PLANCK satellite and other experiments. Moreover, recently it was shown to be ultra-violet (UV) complete via an embedding into an analytic infinite derivative (AID) non-local gravity. In this paper, we derive a most general theory of gravity that contributes to perturbed linear equations of motion around maximally symmetric space-times. We show that such a theory is quadratic in the Ricci scalar and the Weyl tensor with AID operators along with the Einstein-Hilbert term and possibly a cosmological constant. We explicitly demonstrate that introduction of the Ricci tensor squared term is redundant. Working in this quadratic AID gravity framework without a cosmological term we prove that for a specified class of space homogeneous space-times, a space of solutions to the equations of motion is identical to the space of backgrounds in a local R 2 model. We further compute the full second order perturbed action around any background belonging to that class. We proceed by extracting the key inflationary parameters of our model such as a spectral index ( n s ), a tensor-to-scalar ratio ( r ) and a tensor tilt ( n t ). It appears that n s remains the same as in the local R 2 inflation in the leading slow-roll approximation, while r and n t get modified due to modification of the tensor power spectrum. This class of models allows for any value of r < 0.07 with a modified consistency relation which can be fixed by future observations of primordial B -modes of the CMB polarization. This makes the UV complete R 2 gravity a natural target for future CMB probes.

Human Activity Recognition (HAR) involves the recognition of human activities using sensor data. Most of the techniques for HAR involve hand-crafted features and hence demand a good amount of human intervention. Moreover, the activity data obtained from sensors are highly imbalanced and hence demand a robust classifier design. In this paper, a novel classifier “ICGNet” is proposed for HAR, which is a hybrid of Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU). The CNN block used in the proposed network derives its inspiration from the famous Inception module. It uses multiple-sized convolutional filters simultaneously over the input and thus can capture the information in the data at multiple scales. These multi-sized filters introduced at the same level in the convolution network helps to compute more abstract features for local patches of data. It also makes use of 1 × 1 convolution to pool the input across channel dimension, and the intuition behind it is that it helps the model extract the valuable information hidden across the channels. The proposed ICGNet leverages the strengths of CNN and GRU and hence can capture local features and long-term dependencies in the multivariate time series data. It is an end-to-end model for HAR that can process raw data captured from wearable sensors without using any manual feature engineering. Integrating the adaptive user interfaces, the proposed HAR system can be applied to Human-Computer Interaction (HCI) fields such as interactive games, robot learning, health monitoring, and pattern-based surveillance. The overall accuracies achieved on two benchmark datasets viz. MHEALTH and PAMAP2 are 99.25% and 97.64%, respectively. The results indicate that the proposed network outperformed the similar architectures proposed for HAR in the literature.

A bstract Spontaneous breaking of conformal symmetry has been widely exploited in successful model building of both inflationary cosmology and particle physics phenomenology. Conformal Grand Unified Theory (CGUT) inflation provides the same scalar tilt and tensor-to-scalar ratio as of Starobinsky and Higgs inflation. Moreover, it predicts a pro- ton life time compatible with the current experimental bound. In this paper, we extend CGUT to account for the production of dark matter and the reheating of the Standard Model. To this end, we introduce a hidden sector directly coupled to the inflaton, whereas the reheating of the visible sector is realized through a portal coupling between the dark particles and the Higgs boson. The masses and interactions of the dark particles and the Higgs boson are determined by the form of the conformal potential and the non-vanishing VEV of the inflaton. We provide benchmark points in the parameter space of the model that give the observed dark matter relic density and reheating temperatures compatible with the Big Bang nucleosynthesis.

FTIR analysis for five selected green leafy vegetables (GLVs) viz., Hibiscus cannabinus L., (kenaf), H. sabdariffa L., (roselle), Basella alba L., (vine spinach), B. rubra L. (malabar spinach) and Rumex vesicarius L., (sorrel) confirmed the presence of free alcohol, intermolecular bonded alcohol, intramolecular bonded alcohol, alkane, aromatic compounds, imine or oxime or ketone or alkene, phenol and amine stretching. The chlorophyll content was higher in native leaves of B. alba (2.96 g/kg) than defatted samples (1.11 g/kg). Total phenolic content (TPC) in H. sabdariffa native methanol extractives is more (17.6 g/kg) than defatted leaves (9.67 g/kg). Native B. rubra methanol extractives exhibited highest total flavonoid content (TFC) (21.59 g/kg), while that of R. vesicarius was lowest (3.21 g/kg). In general, antioxidant activities showed a significant reduction in retention of antioxidants in both native and defatted GLVs samples of ethanol and methanol extractives. Methanol extractives showed significantly stronger antioxidant activity probably due to greater solubility of phenolics and destruction of cellular components.

Hydrogen spillover involves the migration of H atom equivalents from metal nanoparticles to a support. While well documented, H spillover is poorly understood and largely unquantified. Here we measure weak, reversible H 2 adsorption on Au/TiO 2 catalysts, and extract the surface concentration of spilled-over hydrogen. The spillover species (H*) is best described as a loosely coupled proton/electron pair distributed across the titania surface hydroxyls. In stark contrast to traditional gas adsorption systems, H* adsorption increases with temperature. This unexpected adsorption behaviour has two origins. First, entropically favourable adsorption results from high proton mobility and configurational surface entropy. Second, the number of spillover sites increases with temperature, due to increasing hydroxyl acid–base equilibrium constants. Increased H* adsorption correlates with the associated changes in titania surface zwitterion concentration. This study provides a quantitative assessment of how hydroxyl surface chemistry impacts spillover thermodynamics, and contributes to the general understanding of spillover phenomena. Spillover phenomena are crucial in heterogeneous catalysis, yet remain elusive to quantitative characterization. Here the authors measure the surface concentration of hydrogen spilling-over onto TiO 2 using Au/TiO 2 catalysts and explain the underlying factors governing the process.

When laser speckle program technology is used to measure the blood flow distribution of deep tissues (such as subcutaneous tissue) in sports injuries, the deep blood flow characteristics of sports injuries contain a large amount of turbid tissue fluid. Laser passing through turbid tissue fluid will produce strong interference static speckle, masking the dynamic speckle of blood flow distribution, resulting in poor imaging effect of blood flow characteristics. Propose laser speckle imaging optimization technology and apply it to the measurement of deep tissue blood flow distribution in sports injuries. Based on the principle of laser speckle imaging technology, the problems in laser speckle imaging of deep blood flow distribution characteristics in sports injuries are analyzed. An exponential Laplace loss function is introduced to reduce the amplitude of changes in blood flow characteristics in intra class sports injuries and collect deep blood flow distribution characteristics in sports injuries; On the basis of calculating the laser speckle contrast ratio, the blood volume flow rate is determined, and the blood volume flow rate data is combined with the laser speckle contrast ratio to achieve imaging of deep blood flow distribution in sports injuries. The experimental results show that the improved laser speckle imaging technology has better imaging effects in imaging the deep blood flow distribution of sports injuries; Compared with the comparison method, the DICE coefficient, average accuracy MPA, and global imaging index have all improved, indicating that this method can effectively improve the imaging effect and is feasible.

In this paper, we generalize Coleman–Weinberg (CW) inflation in grand unified theories (GUTs) such as \\[\\text {SU}(5)\\] and \\[\\text {SO}(10)\\] by means of considering two complex singlet fields with conformal invariance. In this framework, inflation emerges from a spontaneously broken conformal symmetry. The GUT symmetry implies a potential with a CW form, as a consequence of radiative corrections. The conformal symmetry flattens the above VEV branch of the CW potential to a Starobinsky plateau. As a result, we obtain \\[n_{s}\\sim 1-\\frac{2}{N}\\] and \\[r\\sim \\frac{12}{N^2}\\] for \\[N\\sim \\] 50–60 e-foldings. Furthermore, this framework allow us to estimate the proton lifetime as \\[\\tau _{p}\\lesssim 10^{40}\\] years, whose decay is mediated by the superheavy gauge bosons. Moreover, we implement a type I seesaw mechanism by weakly coupling the complex singlet, which carries two units of lepton number, to the three generations of singlet right handed neutrinos (RHNs). The spontaneous symmetry breaking of global lepton number amounts to the generation of neutrino masses. We also consider non-thermal leptogenesis in which the inflaton dominantly decays into heavy RHNs that sources the observed baryon asymmetry. We constrain the couplings of the inflaton field to the RHNs, which gives the reheating temperature as \\[10^{6}\\text { GeV}\\lesssim T_{R}<10^{9}\\] GeV.

Introduction. HIV-1 infection in cell culture is typically characterized by certain cytopathic effects such as vacuolization of cells and development of syncytia, which further lead to cell death. In addition, the majority of drugs during HIV treatment exhibit serious adverse effects in patients, apart from their beneficial role. During the screening of cytoprotective agents to protect the cells from HIV-1-associated cell death and also drug-associated toxicity, antioxidants from a natural source are assumed to be a choice. A well-known antioxidant, ethyl gallate (EG), was selected for cytoprotection studies which have already been proven as an anti-HIV agent. Objective. The main objective of the study was to explore the cytoprotective potential of EG against HIV-1-induced cytopathic effect and antiretroviral drug toxicity. Methods. DPPH free radical scavenging assay was performed with EG to find the effective concentration for antioxidant activity. HIV-1infection-associated cytopathic effects and further rescue by EG were studied in MT-2 lymphocytes by the microscopic method and XTT cytopathic assays. The cellular toxicity of different antiretroviral drugs in different cell lines and the consequent cytoprotective effectiveness of EG were investigated using an MTT cell viability assay. Results. Like ascorbic acid, EG exhibited promising antioxidant activity. HIV-1 infection of MT2 cells induces cell death often referred to as the cytopathic effect. In addition, the usage of antiretroviral drugs also causes severe adverse effects like cytotoxicity. In this context, EG was tested for its cytoprotective properties against HIV-1-induced cytopathic effect and drug-mediated cellular toxicity. EG reclaimed back the MT2 cells from HIV-1-induced cell death. Antiretroviral drugs, such as ritonavir, efavirinz, AZT, and nevirapine, were tested for their toxicity and induced more cell death at higher concentrations in different tissue models such as the liver (THLE-3), lung (AEpiCM), colorectal (HT-29), and brain (U87 MG). Pretreated cells with EG were rescued from the toxic doses of ART. Conclusion. EG was found to be exhibited cytoprotection not only from HIV-1-linked cell death but also from the chemotoxicity of antiretroviral drugs. Evidently, EG could be a cytoprotective supplement in the management of AIDS along with its enormous antioxidant benefits.