Energy Efficiency Optimization for D2D communications in UAV-assisted Networks with SWIPT

This paper investigates the energy efficiency (EE) optimization problem for device-to-device (D2D) communications underlaying non-orthogonal multiple access (NOMA) unmanned aerial vehicles (UAVs)-assisted networks with simultaneous wireless information and power transfer (SWIPT). Our aim is to maximize the energy efficiency of the system while satisfying the constraints of transmission rate and transmission power budget. However, the considered EE optimization problem is non-convex involving joint optimization of the UAV's location, beam pattern, power control and time scheduling, which is difficult to solve directly. To tackle this problem, we develop an efficient resource allocation algorithm to decompose the original problem into several sub-problems and solve them sequentially. Specifically, we first apply the Dinkelbach method to transform the fraction problem to a subtractive-form one, and propose a mulitiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to optimize the beam pattern. We then optimize UAV's location and power control by applying the successive convex optimization techniques. Finally, after solving the above variables, the original problem is transformed into a single-variable problem with respect to the charging time, which is a linear problem and can be solved directly. Numerical results verify that the significant EE gain can be obtained by our proposed method as compared to the benchmark schemes

Re-mine, Learn and Reason: Exploring the Cross-modal Semantic Correlations for Language-guided HOI detection

Human-Object Interaction (HOI) detection is a challenging computer vision task that requires visual models to address the complex interactive relationship between humans and objects and predict HOI triplets. Despite the challenges posed by the numerous interaction combinations, they also offer opportunities for multimodal learning of visual texts. In this paper, we present a systematic and unified framework (RmLR) that enhances HOI detection by incorporating structured text knowledge. Firstly, we qualitatively and quantitatively analyze the loss of interaction information in the two-stage HOI detector and propose a re-mining strategy to generate more comprehensive visual representation.Secondly, we design more fine-grained sentence- and word-level alignment and knowledge transfer strategies to effectively address the many-to-many matching problem between multiple interactions and multiple texts.These strategies alleviate the matching confusion problem that arises when multiple interactions occur simultaneously, thereby improving the effectiveness of the alignment process. Finally, HOI reasoning by visual features augmented with textual knowledge substantially improves the understanding of interactions. Experimental results illustrate the effectiveness of our approach, where state-of-the-art performance is achieved on public benchmarks. We further analyze the effects of different components of our approach to provide insights into its efficacy.Comment: ICCV202

Energy Efficiency Optimization for D2D Communications Underlaying UAV-assisted Industrial IoT Networks with SWIPT

The industrial Internet of Things (IIoT) has been viewed as a typical application for the fifth generation (5G) mobile networks. This paper investigates the energy efficiency (EE) optimization problem for the device-to-device (D2D) communications underlaying unmanned aerial vehicles (UAVs)-assisted IIoT networks with simultaneous wireless information and power transfer (SWIPT). We aim to maximize the EE of the system while satisfying the constraints of transmission rate and transmission power budget. However, the designed EE optimization problem is non-convex involving joint optimization of the UAV’s location, beam pattern, power control and time scheduling, which is difficult to tackle directly. To solve this problem, we present a joint UAV location and resource allocation algorithm to decouple the original problem into several sub-problems and solve them sequentially. Specifically, we first apply the Dinkelbach method to transform the fraction problem to a subtractive-form one, and propose a mulitiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to optimize the beam pattern. We then optimize UAV’s location and power control using the successive convex optimization techniques. Finally, after solving the above variables, the original problem can be transformed into a single-variable problem with respect to the charging time, which is linear and can be tackled directly. Numerical results verify that significant EE gain can be obtained by our proposed algorithm as compared to the benchmark schemes

Tensile behaviour of carbon fabric reinforced cementitious matrix composites as both strengthening and anode materials

Recently, a promising solution to corroded steel reinforced concrete structures was proposed in which a dual-functional carbon-fabric reinforced cementitious matrix (carbon-FRCM) composite is used for impressed current cathodic protection (ICCP) and structural strengthening (SS); this method is referred to as ICCP-SS. The tensile behaviour of carbon-FRCM must be understood for design purposes. In this study, the tensile characteristics of carbon-FRCM composites with different fabric reinforcement ratios were assessed to determine the strengthening capability of the materials. Then, using the composite as an anode material, the tensile behaviour of carbon-FRCM specimens subjected to anodic polarization in ICCP was evaluated. Direct tensile tests were conducted to obtain the tensile stress-strain behaviour of the carbon-FRCM specimens. By comparing the results from each case, the influences of different parameters on the tensile behaviour of the carbon-FRCM composites were evaluated, and useful information regarding the application of these materials in ICCP-SS was obtained

The reference intervals for thyroid hormones: A four year investigation in Chinese population

IntroductionThe reference intervals (RIs) are of great importance for physicans to determine whether or not an individual is healthy. However, many clinical laboratories in China still adopted the default RI provided by the manufacturers; and these “uncalibrated” RIs might lead to the misdiagnosis of diseases. In the present study, we enroll reference people with the purpose of determining the RIs of serum triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) in Chinese population, and explore the possible roles of age and sex on the levels of biomarkers.MethodsSerum samples from 66,609 individuals who met the inclusion criteria were analyzed using an Roche Cobas E 601 hormone analyzer. The dynamic trends of biomarker were visually assessed by their concentrations over age and sex. Specific partitions were determined by the method of Harris and Boyd. RIs, corresponding to the 2.5th and 97.5th percentiles, as well as the 0.5th, 25th, 50th, 75th and 99.5th percentiles were calculated for each reference partition using a non-parametric rank approach.ResultsThe serum level of T3, T4, FT4 or TSH showed a right-skewed distribution in both males and females while FT3 presented an approximate normal distribution. Females had a higher mode value of serum T3 or T4, but a lower mode value of serum TSH, FT3 or FT4. All five biomarkers did not need age partitioning according to the approach of harris and boyd, while T3 and FT3 need sex partitioning.ConclusionsThe present study not only determined the age- and sex-specific trends of the five thyroid hormones, but provided sex-stratified RIs for T3 and FT3, valuably contributing to the current literature and timely evaluation of thyroid health and disease

N,N′-Di-p-tolyl­ethyl­enediamine

The asymmetric unit of the title compound, C16H20N2, contains two independent mol­ecules. The rings in each mol­ecule are oriented at dihedral angles of 78.94 (3) and 77.76 (3)°

Electronic Structure, Surface Doping, and Optical Response in Epitaxial WSe2 Thin Films

High quality WSe2 films have been grown on bilayer graphene (BLG) with layer-by-layer control of thickness using molecular beam epitaxy (MBE). The combination of angle-resolved photoemission (ARPES), scanning tunneling microscopy/spectroscopy (STM/STS), and optical absorption measurements reveal the atomic and electronic structures evolution and optical response of WSe2/BLG. We observe that a bilayer of WSe2 is a direct bandgap semiconductor, when integrated in a BLG-based heterostructure, thus shifting the direct-indirect band gap crossover to trilayer WSe2. In the monolayer limit, WSe2 shows a spin-splitting of 475 meV in the valence band at the K point, the largest value observed among all the MX2 (M = Mo, W; X = S, Se) materials. The exciton binding energy of monolayer-WSe2/BLG is found to be 0.21 eV, a value that is orders of magnitude larger than that of conventional 3D semiconductors, yet small as compared to other 2D transition metal dichalcogennides (TMDCs) semiconductors. Finally, our finding regarding the overall modification of the electronic structure by an alkali metal surface electron doping opens a route to further control the electronic properties of TMDCs

Tanshinone IIA attenuates ovalbumin-induced airway inflammation and hyperresponsiveness in a murine model of asthma

Objective(s): Tanshinone IIA (T. IIA), one of the most pharmacologically active components extracted from Salviae miltiorrhiza, has anti-inflammatory and antioxidant features. The aim of the present study is to investigate the benefit of T. IIA on asthma using a murine model of asthma induced by ovalbumin (OVA). Materials and Methods: Male BALB/c mice were used in the present study. The mice were sensitized by OVA intraperitoneal injection on days 0 and 14, and received aerosolized OVA challenge for 30 min daily on days 21-23Results: T. T. IIA (10 mg/kg twice daily) intraperitoneal injection was performed on days 18-23. Results: Treatment of T. IIA reduced the levels of interleukin (IL)-4, IL-5, and IL-13 in bronchoalveolar lavage fluid (BALF) (PConclusion: T. IIA inhibits OVA-induced airway inflammation and hyperresponsiveness. T. IIA is a potential therapeutic agent for asthma

ESC-Derived Basal Forebrain Cholinergic Neurons Ameliorate the Cognitive Symptoms Associated with Alzheimer’s Disease in Mouse Models

SummaryDegeneration of basal forebrain cholinergic neurons (BFCNs) is associated with cognitive impairments of Alzheimer’s disease (AD), implying that BFCNs hold potentials in exploring stem cell-based replacement therapy for AD. However, studies on derivation of BFCNs from embryonic stem cells (ESCs) are limited, and the application of ESC-derived BFCNs remains to be determined. Here, we report on differentiation approaches for directing both mouse and human ESCs into mature BFCNs. These ESC-derived BFCNs exhibit features similar to those of their in vivo counterparts and acquire appropriate functional properties. After transplantation into the basal forebrain of AD model mice, ESC-derived BFCN progenitors predominantly differentiate into mature cholinergic neurons that functionally integrate into the endogenous basal forebrain cholinergic projection system. The AD mice grafted with mouse or human BFCNs exhibit improvements in learning and memory performances. Our findings suggest a promising perspective of ESC-derived BFCNs in the development of stem cell-based therapies for treatment of AD