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Human body motion segmentation plays a major role in many applications, ranging from computer vision to robotics. Among a variety of algorithms, graph-based approaches have demonstrated exciting potential in motion analysis owing to their power to capture the underlying correlations among joints. However, most existing works focus on simpler single-layer geometric structures, whereas multi-layer spatial-temporal graph structure can provide more informative results. To provide an interpretable analysis on multilayer spatial-temporal structures, we revisit the emerging field of multilayer graph signal processing (M-GSP), and propose novel approaches based on M-GSP to human motion segmentation. Specifically, we model the spatial-temporal relationships via multilayer graphs (MLG) and introduce M-GSP spectrum analysis for feature extraction. We present two different M-GSP based algorithms for unsupervised segmentation in the MLG spectrum and vertex domains, respectively. Our experimental results demonstrate the robustness and effectiveness of our proposed methods.

The CRISPR/Cas9 system is a powerful genome editing tool that has made enormous impacts on next-generation molecular diagnostics and therapeutics, especially for genetic disorders that traditional therapies cannot cure. Currently, CRISPR-based gene editing is widely applied in basic, preclinical, and clinical studies. In this review, we attempt to identify trends in clinical studies involving CRISPR techniques to gain insights into the improvement and contribution of CRISPR/Cas technologies compared to traditional modified modalities. The review of clinical trials is focused on the applications of the CRISPR/Cas systems in the treatment of cancer, hematological, endocrine, and immune system diseases, as well as in diagnostics. The scientific basis underlined is analyzed. In addition, the challenges of CRISPR application in disease therapies and recent advances that expand and improve CRISPR applications in precision medicine are discussed.

The proliferation of artificial intelligence (AI) has opened up new avenues for the modeling of power electronics with ultra-fast transient responses, such as wide-bandgap (WBG) devices. This article highlights the significance of ultra-fast transient device-level hardware emulation for the DC railway microgrid (DRM) in real-time. To this end, the proposed approach partitions the DRM power system by transmission line method (TLM) and employs gated recurrent unit (GRU) and electromagnetic transient (EMT) modeling techniques for system-level subsystems. Meanwhile, for WBG devices, gallium nitride (GaN) high electron mobility transistors (HEMT) and silicon carbide (SiC) insulated gate bipolar transistors (IGBT) are modeled using a novel physical feature neuron network (PFNN), which offers high flexibility with a variable time-step (as low as 1 ns), thereby improving the accuracy, efficiency and accelerating the emulation on the field-programmable gate array (FPGA). The effectiveness of the proposed approach is confirmed by comparing the emulation results with offline simulation results obtained from PSCAD/EMTDC for system-level and SaberRD for device-level transients. The proposed PFNN approach provides strong versatility, ultra-fast transient emulation capability, and significantly improved accuracy, which bodes well for the future of power electronics device-level emulation.

Abstract Hyperspectral imaging has broad applications and impacts in areas including environmental science, weather, and geo/space exploration. The intrinsic spectral–spatial structures and potential multi-level features in different frequency bands make multilayer graph an intuitive model for hyperspectral images (HSI). To study the underlying characteristics of HSI and to take the advantage of graph signal processing (GSP) tools, this work proposes a multilayer graph spectral analysis for hyperspectral images based on multilayer graph signal processing (M-GSP). More specifically, we present multilayer graph (MLG) models and tensor representations for HSI. By exploring multilayer graph spectral space, we develop MLG-based methods for HSI applications, including unsupervised segmentation and supervised classification. Our experimental results demonstrate the strength of M-GSP in HSI processing and spectral–spatial information extraction.

Human papillomavirus (HPV) is one of the most common sexually transmitted infections (STIs). However, despite widespread under-vaccination amongst men and the importance of vaccinating both sexes to curb the spread of HPV, research has focused on promoting HPV vaccination predominantly amongst women. Therefore, the current study examines the effectiveness of different informational interventions in promoting vaccination intentions amongst heterosexual men. In a preregistered study of 583 unvaccinated adult men, we randomly assigned participants to one of four informational interventions aimed at promoting awareness of HPV risks and vaccine uptake: (1) risks to oneself (n = 145), (2) risks to their female partner (n = 144), (3) risks to oneself and their female partner (n = 153), and (4) general vaccine information (n = 153). Amongst participants reporting a sexual history (67%), intentions to get vaccinated significantly increased by 10.75 points on a 100-point scale (p < 0.01) after they received information about the risks of HPV for both themselves and their female partner, compared to receiving information about only their own HPV risk. These findings provide valuable guidance for public health officials and policymakers into the effectiveness of different messaging strategies in promoting HPV vaccination amongst adult male populations to increase vaccination rates.

For being the world’s largest low voltage direct current (LVDC) microgrid (MG) in space, the power generation and distribution systems aboard the International Space Station (ISS) employ a hierarchical assortment of electric power sources, energy storage, control devices, power electronics, and loads operating cooperatively at multifarious system dispositions and multi-stage configurations. At the early phase of design, for such time-critical systems, the trade-off between reliability and convergence rate of device modeling, varying accuracy requirements of control flows, and especially the implementation for real-time performance have brought new challenges and problems for testing and validation of the MG. One of the solutions presented by this paper is to use the hardware-in-the-loop (HIL) emulation, where the MG is emulated using the field-programmable gate array (FPGA) hardware platform. In parallel with the emulation effort, comprehensive modeling solutions for both large-scale photovoltaic (PV) solar array wings (SAWs) and nonlinear behavior model (NBM) of insulated-gate bipolar transistors (IGBTs) have been utilized based on machine learning (ML) concepts of artificial neural network (ANN) and recurrent neural network (RNN). Both system-level (validated by Matlab/Simulink) and device-level (validated by SaberRD) transient simulations are carried out, and the results exhibit high accuracy and fidelity of the models and significant improvements in execution speed and hardware resource consumption.

How ROS levels are regulated in cancer stem cells and their contribution to cancer resistance is currently not clear. Here, the authors show that prohibitin regulates mitochondrial ROS production stabilizing the peroxidase PRDX3 and this accounts for radiotherapy resistance in glioma stem-like cells.

A systematic comparison of fiber-based gas pressure sensors using different types of hollow-core photonic crystal fibers (PCFs) is conducted. The sensor was fabricated by splicing a segment of hollow-core silica capillary between a single mode fiber (SMF) and a hollow-core PCF. A Fabry-Perot (FP) cavity configuration is thus formed with the capillary tube as the sensing cavity, while the PCF acts as gas passage to the external environment. External pressure change would lead to the variation in the refractive index of air in the sensing cavity, resulting in a wavelength shift of the interference dips. The pressure sensitivity is measured to be around 4 nm/MPa, with a high linearity of 99.7% or above, regardless of the type of the PCFs we used as gas inlet. Among the four different PCFs, the large-mode-area (LMA) PCF shows the highest fringe contrast in the reflection spectrum. Modal analysis reveals that this is due to the high reflectivity caused by the solid core of LMA-PCF. Our experimental results also indicate that the length of the sensing cavity, as well as the offset fusion splice will influence the fringe contrast. The sensor has potential application in gas pressure sensing for advantages of high sensitivity, compact size and ease of fabrication.

It is still a challenging task to provide satisfactory quality of experience (QoE) to users by traditional routing mechanism in current public Internet for real-time multimedia services with high bandwidth and strict end-to-end latency constraint. Multipath transmission is a promising way to improve the performance of data delivery, due to its advantage in bandwidth aggregation capacity over multiple paths to speed up high volume transfers between endpoints. However, existing multipath transmission has many disadvantages such as the requirements for end-host support (i.e. the necessary multi-homed network setting, and operating system or upper applications updates of user devices), and blindingly pursuing maximum of transmission throughput. Path allocation and end-to-end transmission control are two important factors affecting the quality of multipath transmission. As an emerging network architecture, software-defined networking (SDN) is flexible, manageable, and responsive to rapid changes in traffic requirements. In this paper, we propose a multipath transport scheme based on SDN with segment routing (SR) which can meet the bandwidth and low end-to-end transmission latency requirements of real-time interactive multimedia services. The centralized SDN controller is extended to allocate multiple disjoint paths meeting bandwidth requirement meanwhile balancing the network load. The proprietary multipath media server (MMS) dynamically controls the assignment between subflows and routing paths to reduce the end-to-end transmission latency and thus improve QoE of end-users. To show the feasibility of our approach, we construct an SDN platform using Mininet. Simulation results show that our approach performs better compared to the conventional approaches in terms of traffic balancing and end-to-end transmission delay.

The revolution of artificial intelligence (AI) is transforming major industries worldwide. With accurate inferencing, AI has caught the attention of many engineers and scientists. Promisingly, hardware-in-the-loop (HIL) emulation can adopt this type of modeling method as one of the alternatives after comprehensive investigation. This paper proposes an approach for emulating power electronic motor drive transients for advanced transportation applications (ATAs) using machine learning building blocks (MLBBs) without any traditional circuit-oriented transient solver. The more electric aircraft (MEA) power system is chosen as a case study to validate the real-time emulation performance of MLBBs. Inside MLBBs, neural networks (NNs) have been applied to build component-level, device-level, and system-level models for various equipment. These models are well trained in a cluster and transplanted into the field-programmable gate array (FPGA) based hardware platform. Finally, MLBB emulation results are compared with PSCAD/EMTDC for system-level and SaberRD for device-level, which showed high consistency for model accuracy and high speed-up for hardware execution.

Glioma stem-like cells (GSCs) are a subset of tumor cells that initiate malignant growth and promote the therapeutic resistance of glioblastoma, the most lethal primary brain tumor. Ribosome biogenesis is an essential cellular process to maintain cell growth, but its regulatory mechanism in GSCs remains largely unknown. Here, we show that WD repeat domain 12 (WDR12), a component of the Pes1-Bop1 complex (PeBoW), is required for ribosome biogenesis in GSCs. WDR12 is preferentially expressed in GSCs compared to non-stem tumor cells and normal brain cells. High levels of WDR12 are associated with glioblastoma progression and poor prognosis. Silencing WDR12 results in the degradation of PeBoW complex components and prevents the maturation of 28S rRNA, thereby inhibiting ribosome biogenesis in GSCs. Subsequently, WDR12 depletion compromises GSC proliferation, inhibits GSC-derived orthotopic tumor growth, and extends animal survival. Together, our results suggest that WDR12 is crucial for ribosome biogenesis in GSCs, and is thus a potential target for GSC-directed therapy of glioblastoma.

During aircraft braking, the change of ground adhesion forces can cause forward and backward vibration of the landing gear, and the performance of the brake disc may exacerbate this vibration. In order to solve this problem, a rigid–flexible coupling dynamic model of a two-wheel strut landing gear considering the friction characters of brake discs with different materials and a hydraulic brake system model is established in this paper. The brake disc friction characteristics effect on the low-frequency brake-induced vibration of the landing gear given different brake disc materials and ambient temperatures is studied. It is shown that the C/SiC brake disc has a “negative slope” phenomenon between the friction coefficient of the brake disc and the wheel speed, and this variable friction characteristic has a great effect on the low-frequency braking-induced vibration of the landing gear. In addition, the variable friction characteristics of the C/SiC brake disc are easily affected by ambient temperature, while the friction coefficient of the C/C brake disc changes stably.

Real time video traffic has stringent delay requirement and is bandwidth demanding when streaming over the internet. Single path transmission may provide unsatisfactory picture quality to users due to packet loss, jitter, and low bandwidth. Multipath transmission is another option to achieve better service by aggregating bandwidth and exploiting path diversity. As utility maximization theory shows, to achieve better satisfaction is to provide higher throughput and lower frame delivery delay for real time video traffic. The congestion control is responsible to probe maximum available bandwidth and packet scheduling is to take advantages of path diversity, which are two key research points in multipath context and are also the main concern in this paper. Given the BBR congestion control algorithm causes high-packet loss rate and large transmission delay when BBR flows competing for bandwidth resource, a delay response BBR (Delay-BBR) algorithm is proposed for real time video transmission. The main idea is that the sender will actively reduce the rate to let intermediate routers drain the excess occupied buffer once round trip delay signal exceeds a certain threshold. The results show that the delay-BBR can achieve lower transmission delay and lower packet loss rate when compared with QUIC-BBR and WebRTC-BBR. The rate stable feature makes delay-BBR appropriate for real time video transmission. Moreover, a packet scheduling algorithm works in coordination with the rate control algorithm achieves lower frame delivery delay further compared with the benchmark algorithms.

Abstract Background Wilms tumor is the most common pediatric renal cancer. However, genetic bases behind Wilms tumor remain largely unknown. H19 is a critical maternally imprinted gene. Previous studies indicated that single nucleotide polymorphisms (SNPs) in the H19 can modify the risk of several human malignancies. Epigenetic errors at the H19 locus lead to biallelic silencing in Wilms tumors. Genetic variations in the H19 may be related to Wilms tumor susceptibility. Methods We conducted a four‐center study to investigate whether H19 SNP was a predisposing factor to Wilms tumor. Three polymorphisms in the H19 (rs2839698 G > A, rs3024270 C > G, rs217727 G > A) were genotyped in 355 cases and 1070 cancer‐free controls, using Taqman method. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the strength of the associations. Results We found that all of these three polymorphisms were significantly associated with Wilms tumor risk alterations. The rs2839698 G > A polymorphism (AG vs. GG: adjusted OR = 0.74, 95% CI = 0.57–0.96, p = 0.024; AA vs. GG: adjusted OR = 1.52, 95% CI = 1.05–2.22, p = 0.027), the rs3024270 C > G polymorphism (CG vs. CC: adjusted OR = 0.61, 95% CI = 0.46–0.81, p = 0.0007; and the rs217727 polymorphism (AG vs. GG: adjusted OR = 0.76, 95% CI = 0.58–0.99, p = 0.035). The Carriers of 1, 2, and 1–2 risk genotypes were inclined to develop Wilms tumor compared with those without risk genotype (adjusted OR = 1.36, 95% CI = 1.02–1.80, p = 0.037; adjusted OR = 1.84, 95% CI = 1.27–2.67, p = 0.001; adjusted OR = 1.50, 95% CI = 1.17–1.92, p = 0.002, respectively). The stratified analysis further revealed that rs2839698 AA, rs217727 AA, and 1–2 risk genotypes could strongly increase Wilms tumor risk among children above 18 months of age, males, and with clinical stage I+II disease. Conclusion Our findings indicate that genetic variations in the H19 may confer Wilms tumor risk.

Hyperhomocysteinemia (HHcy) is related to liver diseases, such as nonalcoholic fatty liver (NAFL). Although the precise pathogenesis of NAFL is still largely unknown, the links between organs seem to play a vital role. The current study aimed to explore the role of white adipose tissue in homocysteine (Hcy)-induced NAFL. Blood samples from nonhyperhomocysteinemia or hyperhomocysteinemia individuals were collected to assess correlation between Hcy and triglyceride (TG) or free fatty acids (FFAs) levels. C57BL/6 mice were maintained on a high-methionine diet or administered with Hcy (1.8 g/L) in the drinking water to establish an HHcy mouse model. We demonstrated that Hcy activated adipocyte lipolysis and that this change was accompanied by an increased release of FFAs and glycerol. Excessive FFAs were taken up by hepatocyte, which resulted in lipid accumulation in the liver. Treatment with acipimox (0.08 g kg −1 day −1), a potent chemical inhibitor of lipolysis, markedly decreased Hcy-induced NAFL. Mechanistically, hypoxia-inducible factor 1α (HIF1α)-endoplasmic reticulum oxidoreductin 1α (ERO1α) mediated pathway promoted H2O2 accumulation and induced endoplasmic reticulum (ER) overoxidation, ER stress and more closed ER-lipid droplet interactions, which were responsible for activating the lipolytic response. In conclusion, this study reveals that Hcy activates adipocyte lipolysis and suggests the potential utility of targeted ER redox homeostasis for treating Hcy-induced NAFL.

The problem of vibration and noise in the iron core of power transformers remains quite topical. Insofar as the state-of-the-art iron core and binding production adopt the lamination method and weft-free adhesive tape, respectively, the transformer core vibration is mainly attributed to the silicon steel sheet (SSS) magnetostriction. In this paper, based on the magnetostriction of grain-oriented SSS, an in-depth analysis of the vibration generation mechanism in the transformer core was performed. The SSS microstructure was observed, its magnetostrictive properties at different magnetic flux densities were tested, and a core-simulating four-corner iron core model was constructed to analyze the vibration characteristics. Modal, vibration, and noise tests were performed on an actual 110 kV transformer core under no-load conditions. The results show that the core vibration is related to SSS's deformation mechanism. The vibration magnitude in different core parts varies due to the magnetostriction anisotropy. The vibration in vertical to the core plane is the largest, and its magnitude in the core center is lower than those at the seams in the same plane. The core vibration and noise exhibit a significant correlation, while modal characteristics strongly influence the core vibration and noise intensity. [ABSTRACT FROM AUTHOR]

Buried depth of grounding grids is one of the important factors to determine the grounding performance in substations, however, the real buried depth of grounding grids is changed and unknown due to the drawing loss and backfill during the reconstruction of the grounding grids. This paper proposes a derivative-based method to detect the buried depth of different metal conductors. First, the theoretical basis for the derivative-based method to detect the buried depth is described, and an example calculation on buried depth detection according to the magnetic derivation characteristic is carried out for a single conductor case. The results indicate that the main-side-peaks characteristic of the derivative method can determine the buried depth of metal conductor effectively. Then, the analysis of grounding grids is carried out to verify its validation in grounding grid buried depth detection, and results indicate that the method is effective in the cases of magnetic field superimposing, different buried depths of grounding grid, and nonuniform distribution of current in grounding grid. Finally, the experimental results prove that the derivative method works well with low error. [ABSTRACT FROM AUTHOR]

The topology and breakpoints of the grounding grid will directly affect its working performance. This paper proposed a resistivity reconstruction method based on magnetic detection electrical impedance tomography (MDEIT) to measure the topology and breakpoints of the grounding grid. First, this paper describes the forward problem of grounding grid detection in MDEIT, and calculates the magnetic-field distribution above the grounding grid. Then, the resistivity reconstruction method based on the least squares method is proposed. Finally, this paper verifies the feasibility of the proposed method by a numerical example, which shows that the proposed method can be applied to measure the topology and breakpoints of the grounding grid. [ABSTRACT FROM AUTHOR]

The charged haze particles will affect the electric field of a high-voltage direct current (HVDC) transmission line and insulator contamination, and even result in pollution flashover. Based on the meshless local Petrov–Galerkin method, the influence of ionized electric field on haze particles’ motion is investigated using numerical calculation and experiments. Example of a coaxial electrode model is studied to verify the validation of the proposed method at first. It is proven that the proposed method agrees well with the measurements. Then, the motion principle of haze particles around an actual HVDC insulator is calculated under different ionized field levels. The result shows that the path of the charged haze particles will deflect along the electric field line driven by the electric field force, accelerating the precipitation of the haze particles on the dc insulators. Also, the contamination accumulation gets worse under severe pollution weather and high-voltage side of insulator. [ABSTRACT FROM AUTHOR]

Total organic carbon (TOC) is an important parameter for characterizing shale gas and oil reservoirs. Estimation of TOC from well logs has previously been achieved by an empirical model. The radial basis function (RBF) neural network is a new quantitative method that can generate a smooth and continuous function of several input variables to approximate the unknown forward model. We investigated the basic principles of the RBF including network structure, basis function, network training method, and its application in the TOC prediction. The nearest neighbor algorithm was selected for the network training. Then, the Gaussian width was investigated to improve the TOC prediction accuracy through leave-one-out cross-validation. Finally, field cases of organic shale were studied for the TOC prediction, and the prediction results using the RBF method were compared with those of the ΔlogR method. Furthermore, according to sensitive attribute ranking, the impacts of different input logs on the predicted results were also investigated through various experiments, and the best network model was finally chosen. The error analysis between the prediction results and lab-measured TOC in some examples indicated that the new approach is more accurate than a single empirical regression method and more flexible than the ΔlogR method. [ABSTRACT FROM AUTHOR]

Hyperhomocysteinemia (HHcy) is a condition characterized by an abnormally high level of homocysteine, an inflammatory factor. This condition has been suggested to promote insulin resistance. To date, the underlying molecular mechanism remains largely unknown, and identifying novel therapeutic targets for HHcy-induced insulin resistance is of high priority. It is well known that intermedin (IMD), a calcitonin family peptide, exerts potent anti-inflammatory effects. In this study, the effects of IMD on HHcy-induced insulin resistance were investigated. Glucose tolerance and insulin tolerance tests were performed on mice treated with IMD by minipump implantation (318 ng/kg/h for 4 weeks) or adipocyte-specific IMD overexpression mice (Adipo-IMD transgenic mice). The expression of genes and proteins related to M1/M2 macrophages and endoplasmic reticulum stress (ERS) was evaluated in adipose tissues or cells. The expression of IMD was identified to be lower in the plasma and adipose tissues of HHcy mice. In both IMD treatment by minipump implantation and Adipo-IMD transgenic mice, IMD reversed HHcy-induced insulin resistance, as revealed by glucose tolerance and insulin tolerance tests. Further mechanistic study revealed that IMD reversed the Hcy-elevated ratio of M1/M2 macrophages by inhibiting AMP-activated protein kinase activity. Adipo-IMD transgenic mice displayed reduced ERS and lower inflammation in adipose tissues with HHcy. Soluble factors from Hcy-treated macrophages induced adipocyte ERS, which was reversed by IMD treatment. These findings revealed that IMD treatment restores the M1/M2 balance, inhibits chronic inflammation in adipose tissues, and improves systemic insulin sensitivity of HHcy mice. [ABSTRACT FROM AUTHOR]