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Recent years have witnessed a tremendous increasing of first-person videos captured by wearable devices. Such videos record information from different perspectives than the traditional third-person view, and thus show a wide range of potential usages. However, techniques for analyzing videos from different views can be fundamentally different, not to mention co-analyzing on both views to explore the shared information. In this paper, we take the challenge of cross-view video co-analysis and deliver a novel learning-based method. At the core of our method is the notion of "joint attention", indicating the shared attention regions that link the corresponding views, and eventually guide the shared representation learning across views. To this end, we propose a multi-branch deep network, which extracts cross-view joint attention and shared representation from static frames with spatial constraints, in a self-supervised and simultaneous manner. In addition, by incorporating the temporal transition model of the joint attention, we obtain spatial-temporal joint attention that can robustly capture the essential information extending through time. Our method outperforms the state-of-the-art on the standard cross-view video matching tasks on public datasets. Furthermore, we demonstrate how the learnt joint information can benefit various applications through a set of qualitative and quantitative experiments.

A gallium nitride (GaN)-based resonant step-up converter is proposed for the application in the satellite electric propulsion (EP) system. This converter consists of a full-bridge inverter, a resonant tank and a multi-stage Cockcroft-Walton (CW) voltage multiplier to provide a high gain. Additionally, the air-core transformer is introduced due to the megahertz switching frequency allowed by the GaN device. Thus, the limited magnetizing inductance of transformer and the remarkable junction capacitance of diode have to be carefully considered in the resonant tank design, especially after considering that this converter normally operates at the light load in the EP system. In this work, the 4-order LCLC resonant converter is investigated. The recommended parameter selection for the 4-order resonant tank is also provided. A 1.2-MHz, 23-V/2.5-kV, and 6-W prototype is demonstrated. It achieves a low harmonics distortion and a low power loss with the zero voltage switching (ZVS).

Peripheral nerve blocks are the regional techniques in orthopedic surgeries to control postoperative pain and have early discharge from hospital. However, anesthesia protocols for foot and ankle surgeries of institutes do not include multimodal analgesics including peripheral nerve blocks. The objective of the study was to compare spinal anesthesia with peripheral nerve block against general anesthesia with peripheral nerve block for elective foot and ankle surgeries. Patients have treated for elective foot and ankle surgery under general anesthesia (using propofol, 0.05 mg/kg dezocine, and 1 % sevoflurane; GA cohort, n = 112) or spinal anesthesia (using 0.5 % bupivacaine, propofol, and 0.05 mg/kg dezocine; SA cohort, n = 132) or patients have treated for elective for foot and ankle surgery under general anesthesia (GL cohort, n = 115) or spinal anesthesia (SL cohort, n = 160) with the use of peripheral nerve block (the sciatic nerve blocks and adductor canal nerve blocks using 0.25 % bupivacaine and 0.1 mg/kg dexamethasone). Propofol was administered in fewer amounts if anesthesia was used with the peripheral nerve block. Patients of the GL cohort were transferred to ward 36 min (mean) earlier than those of the SL cohort. None of the patients of the GL and the SL cohorts have received intraoperative opioid(s) for the management of pain. Patients of the GL and the SL cohorts have reported postoperative falls within 1 day after surgeries during movement. Patients of the SL cohort experienced more frequently difficulty with sleeping. Patients of the GL and the GA cohorts have reported nausea and vomiting. Only patients of the GL cohort were required usage of vasoactive drugs. The study provides information to anesthesiologists and surgeons regarding anesthesia techniques for elective foot and ankle surgeries for better surgical outcomes (Level of Evidence: 2; Technical Efficacy Stage: 4).

Identification of transmit-antenna number is of importance in cognitive Internet of Things with multiple-input multiple-output (MIMO). Previous studies on transmit-antenna number detection only consider Gaussian noise and ignore impulsive interference. In the practical wireless communication, impulsive interference may exist due to low-frequency atmospheric noise, multiple access and electromagnetic disturbance. Such interference can usually be modeled as symmetric alpha stable (SαS), which cause the performance degradation of conventional algorithms based on Gaussian model. In this paper, we present a novel scheme to detect the transmit-antenna number for MIMO systems in cognitive Internet of Things, assuming that signals are corrupted by both SαS interference and Gaussian noise. We first introduce a new approach to characterize the generalized correlation matrix, and provide its bound with SαS interference. Then, the discriminating feature vector is constructed by utilizing the higher-order moments (HOM) of eigenvalues of the generalized correlation matrix. Finally, an advanced clustering algorithm is employed to detect the transmit-antenna number, using the cluster where the minimum eigenvalue is located. The proposed algorithm avoids the need for a priori information about the transmitted signals, such as coding mode, modulation type and pilot patterns. Simulation experiments demonstrate the feasibility of the proposed transmit-antenna number detection scheme in MIMO systems with Gaussian noise and SαS interference.

Abstract: Hyperinsulinism-hyperammonemia syndrome (HHS) is a rare disease characterized by recurrent hypoglycemia and persistent elevation of plasma ammonia, and it can lead to severe epilepsy and permanent brain damage. It has been demonstrated that functional mutations of glutamate dehydrogenase (GDH), an enzyme in the mitochondrial matrix, are responsible for the HHS. Thus, GDH has become a promising target for the small molecule therapeutic intervention of HHS. Several medicinal chemistry studies are currently aimed at GDH, however, to date, none of the compounds reported has been entered clinical trials. This perspective summarizes the progress in the discovery and development of GDH inhibitors, including the pathogenesis of HHS, potential binding sites, screening methods, and research models. Future therapeutic perspectives are offered to provide a reference for discovering potent GDH modulators and encourage additional research that will provide more comprehensive guidance for drug development.

Objective: We aimed to investigate the feasibility of multi-acquisition with variable resonance image combination slab selectivity inversion recovery (MAVRIC SL IR) sequence on 3.0 T MRI in patients with anterior cervical discectomy and fusion (ACDF) surgery compared to bandwidth-optimized short tau inversion recovery (STIR) sequence. Methods: Paired sagittal MR images of MAVRIC SL IR and bandwidth-optimized STIR sequences were acquired and analyzed for 21 patients after ACDF surgery with PEEK cage-plate construct. Quantitative comparisons were made on the metal artifact areas of paired mid-sagittal images. In qualitative analysis, the consistency of fat suppression and visibility of anatomic structures (bonemetal interface, surrounding soft tissues, and spinal cord) were independently assessed, based on a five-point scale by two musculoskeletal radiologists, who were blind to the images and patient details. Results: The application of the MAVRIC SL IR sequence resulted in a significant reduction of 48% in the mean area of metal artifacts (t = -7.141, p < 0.001). Based on the comments received from both the reviewers, the MAVRIC SL IR sequence showed greater visibility of the bone-metal interface (p < 0.001), considerable visibility of the surrounding soft tissues (p > 0.05) but worse visibility of the spinal cord (p < 0.001), including the consistency of fat suppression (p < 0.001) relative to the bandwidth-optimized STIR sequence. Conclusion: With significantly reduced metal artifacts, the MAVRIC SL IR sequence can be implemented in patients undergoing ACDF surgery with PEEK cage-plate construct for 3.0 T MRI, despite the poor visibility of the spinal cord.

Leptomeningeal metastasis (LM) is a disastrous complication in lung cancer. LM patients with oncogene-addicted non-small cell lung cancer (NSCLC) have a relatively better prognosis than those with the wild-type counterpart; however, overall post-LM survival is short. Additionally, the high heterogenicity of the LM entity creates a treatment challenge, and to date, no standard strategy has been established. This article describes a female lung adenocarcinoma patient with a resistant epidermal growth factor receptor (EGFR) exon20ins mutation who developed LM only 11 months after radical surgery IIIA (pT1bN2). Intrathecal chemotherapy (ITC), whole-brain radiotherapy (WBRT) with a simultaneous integrated boost (SIB) followed by Osimertinib was initiated. The cerebrospinal fluid (CSF) cytology turned negative. The first remission lasted 6 months, then bone metastases occurred, and the LM progressed. An Ommaya reservoir was implanted. ITC with pemetrexed and anlotinib was administered. A CSF next-generation sequencing (NGS) examination revealed EGFR exon20ins (p. A767_V769 dup 1.5%), which was different from that of the primary tumor (p. V769_D770 ins ASV 17.48%). The CSF cytology then turned negative again; however, the patient succumbed to the disease in December 2020. The patient's post-LM overall survival (OS) time was 13.5 months. This case is novel and of great value. Clinicians should pay special attention to populations at high risk of developing LM. Early detection followed by active intervention, including ITC, RT, and systemic treatment, will result in a better prognosis. The NGS of CSF is fundamental to understanding the genetic profiles of LM and providing effective and precise treatment.

In terms of multiple temporal and spatial scales, massive data from experiments, flow field measurements, and high-fidelity numerical simulations have greatly promoted the rapid development of fluid mechanics. Machine Learning (ML) provides a wealth of analysis methods to extract potential information from a large amount of data for in-depth understanding of the underlying flow mechanism or for further applications. Furthermore, machine learning algorithms can enhance flow information and automatically perform tasks that involve active flow control and optimization. This article provides an overview of the past history, current development, and promising prospects of machine learning in the field of fluid mechanics. In addition, to facilitate understanding, this article outlines the basic principles of machine learning methods and their applications in engineering practice, turbulence models, flow field representation problems, and active flow control. In short, machine learning provides a powerful and more intelligent data processing architecture, and may greatly enrich the existing research methods and industrial applications of fluid mechanics.

With the high penetration of the power electronic loads in the grid, the stability of static synchronous compensator (STATCOM) devices are greatly challenged. However, the conventional control methods for the modular multilevel converter (MMC) based STATCOM only consider the stability with small signal disturbances. This paper proposes a novel dual-layer back-stepping control (BSC) for the MMC based STATCOM. In the first layer, the BSC aims to regulate the sum of the capacitor energy and the reactive output current. In the second layer, the BSC aims to control the circulating current. Therefore, the proposed method possesses a fast dynamic response and accurate tracking with the Lyapunov stability of the MMC based STATCOM. Compared with the arm-control-based back-stepping control for MMC based inverters, the proposed method has a simplified structure and a reduced computation burden. In addition, the proposed method realizes the decoupled control between the output current and the circulating current. The simulation and experimental results verify the effectiveness of the proposed method. In addition, its robustness towards different circuit parameters and the operation ability under unbalanced grid fault is also verified.

This paper presents a shared-aperture dual-band dual-polarized antenna array for fifth-generation (5G) mobile communication. Within one radiating aperture, four higher-band (HB) patch antenna elements are placed over the lower-band (LB) full-wavelength slot antenna. The proposed array is miniaturized by bending the ground plane of the slot antenna. Suppression of cross-band mutual coupling and scattering is achieved by using the filtering performance of the slot antenna and a dual-function metasurface. The filtering performance of the slot antenna is realized using coupled microstrip lines inside the radiating slot and open-ended stubs on the feeding lines. The dual-function metasurface operates as an artificial magnetic conductor reflector in the LB and bandpass frequency selective surface in the HB. By placing the dual-function metasurface behind the slot antenna, the radiation of the slot antenna is enhanced in the LB but not HB, and the negative effect of its HB scattering on the HB antennas is reduced. The working mechanism is explained in detail. The measured and simulated results demonstrate that the proposed array has stable radiation patterns in the bands of 0.69-0.96 and 3.4-3.7 GHz with a high cross-band isolation of over 32 dB, and is more compact than the previous works.

The rapid spread of the novel coronavirus disease 2019 (COVID‐19) causes a significant impact on public health. It is critical to diagnose COVID‐19 patients so that they can receive reasonable treatments quickly. The doctors can obtain a precise estimate of the infection's progression and decide more effective treatment options by segmenting the CT images of COVID‐19 patients. However, it is challenging to segment infected regions in CT slices because the infected regions are multi‐scale, and the boundary is not clear due to the low contrast between the infected area and the normal area. In this paper, a coarse‐refine segmentation network is proposed to address these challenges. The coarse‐refine architecture and hybrid loss is used to guide the model to predict the delicate structures with clear boundaries to address the problem of unclear boundaries. The atrous spatial pyramid pooling module in the network is added to improve the performance in detecting infected regions with different scales. Experimental results show that the model in the segmentation of COVID‐19 CT images outperforms other familiar medical segmentation models, enabling the doctor to get a more accurate estimate on the progression of the infection and thus can provide more reasonable treatment options.

Bayer red mud (RM) is a solid waste in alumina production, and the main components is Fe2O3. To investigate the effect of Fe2O3 in RM on pyrolysis of low-rank coal and catalytic upgrading mechanism on tar quality, pyrolysis experiments of pure Fe2O3 and RM mixed with a lignite, Baiyinhua (BYH) coal, were carried out. The results indicate that RM exhibits a similar catalytic effect to Fe2O3 in terms of product distribution and tar composition of coal pyrolysis. At 20% addition of RM or Fe2O3 in coal, the yield of gas and water increases, while that of char decreases; the yield of H2 increases by 38.6% or 37.1%, and the yields of CO and CO2 increase by 58.9%, 78.1% and 24.6%, 44.1%, respectively. GC and GC-MS results prove that the existence of RM or Fe2O3 improve the tar quality, and RM shows a better effect, as the content of heavy components decreases by 11.7% with RM and 5.1% with Fe2O3. Besides, the content of bisphenol, aliphatic hydrocarbon, oxygenated compounds and heteroatomic compounds decrease simultaneously, thus generating more monophenol and naphthalene. Several characterizations show that Fe2O3, as an active component of RM, provides lattice oxygen species to participate in the reaction and changes to Fe3O4 by partial oxidation during the pyrolysis process. TGA results and kinetic analysis of coal pyrolysis illustrate that RM can promote BYH coal pyrolysis and increase the yield of gas and liquid.

This study aimed to comprehensively evaluate whether income affects long-term health outcomes for older patients who underwent percutaneous coronary intervention (PCI) provided by a universal health coverage system. Data were from the Latter Stage Elderly Healthcare Insurance database in Fukuoka Prefecture, Japan. A total of 5625 individuals aged ≥65 years who underwent PCI in 2014-2016 were included. Cox proportional hazards models were used to assess the association between income status and the incidence of health outcomes. With a median follow-up of 1095 days, 554 acute myocardial infarction (AMI) cases, 1075 stroke cases, 1690 repeat revascularization cases, and 1094 deaths were observed. Risk of all-cause mortality decreased significantly with increasing income level in both unadjusted and adjusted Cox regression models. Patients in the low-income level had a significantly higher rate of AMI (log-rank

Spatiotemporal fusion (STF) aims at generating remote-sensing data with both high spatial and temporal resolution. In the literature, one of the most widely used strategies to accomplish this goal is to fuse high temporal resolution images collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) with images with finer spatial resolution than those provided by MODIS (e.g., those collected by other satellite instruments such as Landsat or Sentinel-2). Current STF methods generally fuse an upsampled MODIS image with finer spatial resolution images. This leads to two main problems. First of all, the model uncertainty errors (resulting from the ill-posed upsampling problem) will be propagated into the fusion results, leading to spatial and spectral distortion. Furthermore, the spatial details of the upsampled MODIS image may be significantly different from those of the finer spatial resolution images, making the STF problem even more challenging. In order to tackle these issues, in this work, we develop a new linear regression-based STF strategy (LiSTF), which performs the reconstruction from a MODIS-like image (instead of from an upsampled MODIS image), thus reducing the model uncertainty errors and preserving better the spatial information. The MODIS-like images are built from the finer spatial resolution images via downsampling. Our experimental results, conducted using two publicly available datasets of Landsat-MODIS image pairs and one publicly available dataset of Sentinel-MODIS image pairs, reveal that our newly proposed LiSTF approach can significantly enhance the quantitative and qualitative performance of STF, particularly in terms of preserving the spatial information.

To meet user's functional requirements, cloud computing and big data have become the most commonly used computing and data resources. Based on analysis, conversion, extraction and refinement for the big data, a disease can be prevented and group behavior can be predicted. However, each user's private data is also an element in big data. Users must provide private data to the service providers to meet their functional requirements. To gain economic benefits, some SaaS service providers have not been authorized to collect and analyze the user's sensitive private data, as a result, the user's private data is disclosed. In this paper, we propose a private data chain disclosure discovery method, to prevent a user's sensitive privacy information from being illegally disclosed. Firstly, we measure the similarity degree and cost of the disclosure of the private data. Secondly, according to the similarity degree and cost of disclosure, the disclosure chain and key private data are detected in the process of interaction between user and SaaS service. Thirdly, we propose a discovery framework for the private data chain and demonstrate its feasibility and effectiveness by experiments.

Validation of satellite albedo products is an essential step because their quantitative application lie in their ability to record the real state of the earth surface. Upscaling in situ measurements to the corresponding pixel scale is necessary due to the spatial scale mismatch between in situ and satellite measurements. Machine learning-based models have been increasingly used for upscaling because they can yield more reliable results than traditional methods. Nevertheless, the main controlling factors on upscaled results have rarely been discussed. This article explores the control factors that bring uncertainties to the upscaled results based on machine learning models. Three machine learning models, including random forest (RF), k-nearest neighbor (KNN), and Cubist models, were selected to upscale single site in situ-based albedo to the coarse pixel scale. The upscaled results were carefully assessed through comparison with pixel scale albedo reference. The results indicate that the accuracy of upscaled results depends on the machine learning models, the inclusion of key variables related to albedo, the dataset selection of these variables, the amount of training data, and the sensitivity of machine learning models to these factors. Despite the dependence on control factors, the machine learning-based upscaling methods generally have excellent applicability across different spatial scales and over other untrained areas. Therefore, they open the door to generating a time series of globally, spatially continuous distributed reference datasets with sufficient length, consistency, and continuity to adequately fulfill the requirement of a comprehensive validation.

We put forward a focusing formula to describe the guided waves periodical focusing phenomenon, which, apart from being a fundamental problem in the guided waves propagation in the pipes, has essential applications in the field of nondestructive evaluation. Due to the partial circumferential loads or non-axisymmetric defects, the guided waves are not only in the zeroth-order axisymmetric forms but also in the higher-order non-axisymmetric forms. When multiple orders of the same mode exist simultaneously, the angular profile is adopted to describe the circumferential energy distribution of the superposed wave field. However, the angular profile varies in the propagation process. In our finding, this variation is periodic, meaning that the circumferential energy will repeat the process of dispersing and focusing. Thus, we put forward a focusing formula to describe the phenomenon. The proposed formula indicates that the angular profile varies periodically with the ratio of propagation distance to wave number, and this period is only related to the pipe radius. Thus, three factors, including propagation distance, excitation frequency, and pipe radius, will affect the angular profile. Moreover, we established an experimental system to verify this phenomenon, based on which we have designed three groups of experiments to investigate these three factors. The experimental results are in good agreement with the theoretical predictions.

BACKGROUND: Lenvatinib with everolimus (“Len/Eve”) is approved for advanced/metastatic RCC following one antiangiogenic therapy. OBJECTIVE: This study evaluated patient characteristics, treatment patterns and overall survival (OS) with second-line or later (2L+) Len/Eve for advanced/metastatic RCC. METHODS: A retrospective observational study was conducted using electronic health records. Adult patients who initiated 2L+ Len/Eve for advanced/metastatic RCC from May 13, 2016 to July 31, 2019 were included. Patient characteristics and treatment patterns were assessed across the overall population and by post-immuno-oncology (IO) and post-tyrosine kinase inhibitors (TKI) groups. OS was estimated from Len/Eve initiation (i.e., index date) using Kaplan-Meier. RESULTS: Among the study population (n = 152), 44.1%received 2L/3L Len/Eve and median number of prior therapies was 3 (range:1–8). Median age was 63.2 years, 78.9%were Caucasian, 73.7%were male, and 56.6%had ECOG performance status 0/1. At initial diagnosis, 65.8%had stage IV disease. At index, 53.3%had an International Metastatic RCC Database Consortium risk score of intermediate/poor, 15.1%favorable, and 31.6%missing score. Sixty-five (42.8%) received IO-based regimens and 49.3%received TKIs directly before index. Median OS from index was 13.9 (95%CI: 9.5–16.5) months and 2L/3L and 4L+ were 12.1 (95%CI: 8.4–17.0) and 14.8 (95%CI: 8.9–22.5) months, respectively. Median OS for Len/Eve post-IO and post-TKI were 13.9 (95%CI: 8.4–21.3) and 14.8 (95%CI: 7.8–16.5) months, respectively. Conclusion: This study suggested that 2L+ Len/Eve has clinical effectiveness for advanced/metastatic RCC in a US community oncology setting. Future studies are needed to confirm the association of improved survival with 2L+ Len/Eve.

As an alternative to indium tin oxide (ITO), aluminum-doped zinc oxide (AZO) has been actively investigated due to its low cost. In this study, different transparent conductive oxide (TCO) structur...

In this letter, two novel broadband circularly polarized slot-microstrip antennas (SMPA) with circular and square structures are elaborated. The circular SMPA is composed of four crown patches as parasitic elements, four crown slots etched on a circular ground plane, and a circular loop sequential phase feeding structure. However, the square SMPA consists of four parasitic rectangular patches, four square slots with cut corners, and a square-loop feeding structure. In the circular SMPA, the parasitic crown patches and crown slots are used to excite multiple circularly polarized (CP) resonant modes, which are fed by a circular loop sequential phase feeding structure through capacitive coupling. Combined with these CP modes, the CP bandwidth of the presented antenna could be improved. Eventually, the proposed circular SMPA has a broad 3-dB axial ratio bandwidth (ARBW) of 20.6% (5.206.40, 5.8 GHz) and a wide 10-dB impedance bandwidth (IBW) of 25.8% (4.926.38, 5.65 GHz), which could occupy the WLAN (5.7255.85 GHz), ITS (5.8 GHz), and WIFI (5.85-5.925 GHz) bands.

Introduction Few studies have evaluated real-world effectiveness of lenvatinib (Len)/everolimus (Eve) for advanced/metastatic renal cell carcinoma (a/mRCC). This study evaluated patient profiles and clinical outcomes of second- and subsequent-line (≥ 2L) Len/Eve for a/mRCC. Patients and Methods A longitudinal retrospective study examined adult patients initiating ≥ 2L Len/Eve for a/mRCC from May 13, 2016, to July 31, 2019. Len/Eve clinical trial participants or those treated for other primary tumors were excluded. Outcomes included objective response rate, duration of response, progression-free survival (PFS), time to treatment discontinuation, and overall survival. Time-to-event outcomes were estimated using Kaplan-Meier methods. Results Seventy-nine patients were assessed: the median age was 64.8 years, 78.5% were Caucasian, 73.4% were male, 78.5% had an Eastern Cooperative Oncology Group performance status score of 0/1, 29.1% received 2L/3L Len/Eve, and the median number of prior lines of therapy was 3 (range, 1-8). At initial diagnosis, 55.7% had stage IV disease, 65.8% had International Metastatic risk scores of intermediate/poor, 19.0% favorable, and 15.2% with missing score. Thirty-one (39.2%) patients received immuno-oncology–based regimens, and 50.6% received tyrosine kinase inhibitors directly before Len/Eve initiation. The median time to treatment discontinuation was 5.7 months (95% CI, 3.3-6.9). The physician-assessed objective response rate was 55.7% (1.6% complete response and 54.1% with some degree of tumor shrinkage). The median duration of response was 9.7 months (95% CI, 5.8-17.1). The median PFS was 6.1 months (95% CI, 4.4-9.0). The median PFS for patients receiving Len/Eve post–immuno-oncology was 6.4 months (95% CI, 4.1-10.8) and for post–tyrosine kinase inhibitor 5.7 months (95% CI, 4.1-10.5). Median overall survival was 14.8 months (95% CI, 10.2-23.9). Conclusion In this longitudinal retrospective study, Len/Eve showed real-world effectiveness in clinical practice in a heavily pretreated a/mRCC patient population.

Background Among stroke survivors, the risk of stroke recurrence is high, and stroke survivors' perception of the risk of recurrence is crucial to promote healthy behaviours. Objectives This study aimed to explore the perceptions of stroke survivors about their risk of recurrence and healthy behavioural modifications. Design A qualitative interview study was carried out. Results We interviewed 19 stroke survivors from 3 hospitals. Thematic analysis showed that the perceptions of recurrence risk and healthy behavioural changes differed between first‐ever and recurrent stroke survivors. Three themes were generated from the data of first‐ever stroke survivors: indifference to and unawareness of the risk of stroke recurrence, the need for professional information support and different awareness of the importance of different healthy behaviours. For first‐relapse stroke patients: worry but feel powerlessness towards recurrent event, accurate information is still warranted, regret of unhealthy behaviour patterns. For the survivors suffered two or more times recurrences: perceived severity of recurrences, increased psychological care need, incorrect perceptions of healthy behaviour. Discussion and Conclusion Stroke survivors with or without recurrence hold different perceptions towards the risk of recurrence and behavioural changes. The need for information related to warning signs, recurrence risk and risk factors remained consistently unmet. The benefits of healthy behaviours could be a double‐edged sword for the prevention of stroke recurrence if the survivors fail to understand these accurately. It is strongly recommended that a specific recurrence risk communication tool and related health education plan be explored on the basis of the number of times patients have experienced stroke recurrence to inform secondary prevention of stroke in the future. Patient/Public Contribution The patients were involved in the formulation of interview questions and conduct of this study. No public was involved in this study.

Background and objectives Despite a high burden of human papillomavirus (HPV)-attributable cancers, the southern US lags other regions in HPV vaccination coverage. This study sought to characterize and contextualize predictors of HPV vaccination in the southern US. Methods From December 2019 – January 2020, parents of adolescents (ages 9–17 years) living in thirteen southern US states were recruited from a nationally-representative online survey panel and completed a cross-sectional survey. The primary study outcome was initiation of HPV vaccination. Results Of 1105 parents who responded to the survey, most were ≥35 years of age and of female gender. HPV vaccination initiation was reported only among 37.3% of adolescents and was highest at age 12. Cumulative HPV vaccination coverage was highest at age 15 (52%) but lower than coverage for tetanus-diphtheria-acellular pertussis (Tdap, 79.3%) and Meningococcal vaccines (MenACWY, 67.3%). Provider recommendation was strongly associated with higher odds of HPV vaccination (aOR: 49.9, 95 %CI: 23.1–107.5). In alternative predictive models, home/online (vs. public) schooling and parents’ working status were associated with lower odds of vaccination; health care visits in the past 12 months and shorter travel times to adolescents’ usual health care provider were associated with greater odds of vaccination. Conclusions Our findings suggest missed opportunities for HPV vaccination in the southern US and support strengthening provider recommendation for on-time initiation of HPV vaccination among adolescents. Other strategies to increase HPV vaccinations may include encouraging co-administration with other adolescent vaccines, increasing vaccine access, and promoting vaccinations for home/online-school students.

CRM1 inhibitors have demonstrated antitumor effects in ovarian and other cancers; however, rational combinations are largely unexplored. We performed a high-throughput drug library screen to identify drugs that might combine well with selinexor in ovarian cancer. Next, we tested the combination of selinexor with the top hit from the drug screen in vitro and in vivo. Finally, we assessed for mechanisms underlying the identified synergy using reverse phase protein arrays (RPPA). The drug library screen assessing 688 drugs identified olaparib (a PARP inhibitor) as the most synergistic combination with selinexor. Synergy was further demonstrated by MTT assays. In the A2780luc ip1 mouse model, the combination of selinexor and olaparib yielded significantly lower tumor weight and fewer tumor nodules compared with the control group (P < 0.04 and P < 0.03). In the OVCAR5 mouse model, the combination yielded significantly fewer nodules (P = 0.006) and markedly lower tumor weight compared with the control group (P = 0.059). RPPA analysis indicated decreased expression of DNA damage repair proteins and increased expression of tumor suppressor proteins in the combination treatment group. Collectively, our preclinical findings indicate that combination with selinexor to expand the utility and efficacy of PARP inhibitors in ovarian cancer warrants further exploration.

Background: Metastases are responsible for over 70% of deaths from lung adenocarcinomas. Previous large-scale studies of LUAD mainly focused on primary diseases. We aimed to comprehensively analyze the genomic landscape of metastatic LUADs and elucidate its clinical implications in the context of precision medicine. Methods: We performed retrospective analyses on targeted sequencing data of 3,743 primary tumors and 934 metastases from 4,480 patients with lung adenocarcinomas, and PD-L1 immunohistochemical data of 1,336 primary tumors and 252 metastases from 1,588 LUAD patients. Results: Metastases generally manifested significantly higher mutational burdens and chromosomal instability than primary lung adenocarcinomas. Clinically actionable alterations, including ALK mutations, ALK and ROS1 fusions, and MET copy number gains, were enriched in metastases, particularly metastases to some specific organs/tissues, such as lymph nodes, liver, and brain. PD-L1 expression decreased as the approximate metastatic distance increased. Additional data of paired primary tumors and metastases to lymph nodes and brain validated patterns of actionable alterations and candidates for metastatic drivers. Two evolutionary modes of metastatic dissemination, common origins and distinct origins, were identified in both types of primary-metastasis pairs. Conclusions: Our study showed heterogenous patterns of clinically actionable alterations, PD-L1 expressions, metastatic driver candidates, and evolutionary patterns among multiple types of metastases of lung adenocarcinomas, which may advise the planning of treatments and the identification of novel therapeutic targets.

The fast-growing prevalence of Parkinson's disease (PD) creates a heavy burden for society and the health care system. Although different ways to mitigate the economic burden of PD have been discussed in the literature, including several effective treatments, few studies have paid attention to the effect of care rehabilitation (CR) on PD costs over a long-term care period. This study tracked medical expenses, care costs, and total costs of elderly individuals with PD for 3 years based on medical claims data merged with long-term care insurance (LTCI) claims data, and determined whether CR reduced PD costs. Using a retrospective, longitudinal cohort design, 3950 elderly individuals with PD who received LTCI services from April 2014 to March 2017 in Fukuoka Prefecture, Japan were followed. PD costs were compared between the CR group and the non-CR group, and a hierarchical linear model was used to examine whether CR was associated with medical expenses, care costs, and total costs. The mean value of total costs in fiscal years 2014, 2015, and 2016 were ¥3,124,944 (US$29,504), ¥3,328,398 (US$31,425), and ¥3,615,892 (US$34,140), respectively. In a hierarchical linear model, CR alone was not associated with medical expenses and care costs; additionally, CR had a positive association with higher total costs. However, the interaction term between CR and baseline care needs level significantly reduced care costs and total costs. That indicates that if older PD patients with higher care needs level receive CR, their care costs and total costs will be reduced. Further research is needed to clarify how CR reduces these patients' costs.

An extremely ultra-wideband (UWB) antipodal Vivaldi antenna with a high gain and excellent impedance matching is proposed. An elliptical-shaped director embedded in an exponentially tapered slot is employed to enhance the gain at the high frequency band, while a metamaterial inspired structure is employed to enhance the gain around center frequency band and the symmetry of radiation pattern at the low frequency band. Furthermore, two sets of rectangular slits are symmetrically embedded around the tapered slot to improve the impedance matching at the low frequency band. Based on this novel structure, an antipodal Vivaldi antenna with good impedance matching and a high gain over an extremely UWB band is successfully designed. The reflection coefficient is lower than -12 dB at 1-4.16 GHz and lower than -16 dB at 4.16-28 GHz. The gain is 4.9-11.6 dBi at 1-8 GHz and higher than 11.6 dBi at 8-28 GHz.

In order to achieve the purpose of efficient, safe and reliable operation, it has become the development trend and direction to build an intelligent oilfield transportation pipeline network with big data analysis, comprehensive situation awareness and automatic control and management capabilities in the future. In this paper, Supervisory Control and Data Acquisition (SCADA) system was used to collect the production and operation data of an oilfield in Western China. The thermal and hydraulic models have been corrected based on these collected data. Then, the influence factors of thermal characteristics of several categories of pipelines were analyzed, and the critical temperature gradient of various categories of pipelines was obtained by interpolating fitting method. Furthermore, the optimal operation conditions of the transportation pipelines were obtained, and the universal relationship of pipeline operation parameters was established as well. The results indicated that the corrected models can predict the temperature drop and pressure drop of multiphase mixture transportation pipeline well, liquid flow rate, water cut and initial temperature do have obvious influences on pipeline operation parameters, and the universal relationship of pipeline operation parameters can effectively guide the production practice of oilfield. However, the operation parameters optimization universal relationship cannot meet the requirements of personalized control of all pipelines. Therefore, this paper proposed an intelligent control strategy for multiphase mixture transportation pipeline in oilfield. This case study is of great significance to guide the optimization of operation parameters and ensure high efficiency and safe operation of multiphase mixture transportation pipelines in oilfield.

Do external uncertainties hold back or accelerate firms’ strategic change? To examine this issue, we develop a theoretical framework on the relationship between policy uncertainty caused by political turnover and the level of a firm’s strategic change and also theorize how political connections and financial resources affect firms’ response in the form of strategic change to environmental uncertainty. We test our framework with 16,451 firm-year observations of listed firms in China from 2008 to 2015 and find that political turnover has a negative influence on the level of a firm’s strategic change. Moreover, this influence is mitigated by political connections and/or financial resources.

Optoelectronic synaptic elements are emerging functional devices for the vigorous development of advanced neuromorphic computing technology in the post-Moore era. However, optoelectronic devices based on transition metal dichalcogenides (TMDs) are limited to their poor mobilities and weak light-matter interactions, which still hardly exhibit superior device performances in the application of artificial synapses. Here, we demonstrate the successful fabrication of Au nanoparticle-coupled MoS2 heterostructures via chemical vapor deposition (CVD), where the light absorption of MoS2 is greatly enhanced and engineered by plasmonic effects. Hot electrons are excited from Au nanoparticles, and then injected into MoS2 semiconductors under the light illumination. The plasmonically-engineered photo-gating effect at the metal-semiconductor junction is demonstrated to create optoelectronic devices with excellent synaptic behaviors, especially in ultra-sensitive excitatory postsynaptic current (EPSC, 9.6 × 10−3 nA@3.4 nW·cm−2), ultralow energy consumption (34.7 pJ), long-state retention time (> 1,000 s), and tunable synaptic plasticity transitions. The material system of Au-nanoparticles coupled TMDs presents unique advantages for building artificial synapses, which may lead the future development of neuromorphic electronics in optical information sensing and learning.

With the increasing wide applications of wearable wireless networks, body-to-body networks (BBNs) have become significantly important to provide timely and reliable data delivery services. For a specific BBN, assessing its theoretically achievable Quality of Service (QoS) is necessary, especially on the key performance metrics of end-to-end delay distribution and packet loss ratio. The existing analysis models in the literature mainly focused on 1-D space scenarios. In this article, BBN in a 2-D area is considered, where mobile nodes freely and stochastically move along lanes. By introducing two new definitions: 1) node entrance probability and 2) network entrance probability, a systematically analytical framework for end-to-end delay distribution and packet loss ratio is presented. The proposed analytical framework is built on three critical techniques: 1) the Markov chain to model node behaviors; 2) the first passage theory to calculate node entrance probability and network entrance probability; and 3) the central limit theory to decrease the computation time for summing up per-hop delay. Simulation results demonstrate the effectiveness and accuracy of our proposed analysis model.

In the recommender system, the user’s historical behavior data is one of the most important sources of the system’s input data. According to the user’s feedback mechanism, behavior data can be divided into explicit feedback data and implicit feedback data. However, most recommendation algorithms focus separately on explicit feedback or implicit feedback. How to combine explicit and implicit feedback for recommendation tasks has always been a research problem. In recent years, deep learning technology has dominated the research on recommendation algorithms. But even the latest neural network-based recommendation algorithm cannot exceed classic methods (such as matrix factorization) in most cases. In this work, we propose a new collaborative filtering framework with neural network architecture. On the one hand, we use both explicit feedback data and implicit feedback data as input to learn multiple representations of users and items. On the other hand, we use multi-task learning to optimize our framework and use two relatively simple auxiliary tasks to enhance the generalization ability of our framework. Extensive experiments on five real-world datasets show significant improvements in our proposed framework over the state-of-the-art methods and vanilla matrix factorization.

The utility of circulating tumor DNA (ctDNA) in classifying the cell origin of diffuse large B-cell lymphoma (DLBCL) has not been explored in the Chinese population. In this study, we aimed to investigate the genetic characteristics of DLBCL based on both tumor and ctDNA sequencing and to assess the predictive value of ctDNA in DLBCL. A targeted sequencing panel of 413 genes was applied to tumor biopsies and paired plasma samples obtained from 30 patients with DLBCL before therapeutic intervention (pretreatment). The concordance between plasma genotyping classification and traditional cell-of-origin classification using tumor tissue was 80.0% (20/25). Patients with higher baseline plasma ctDNA levels had poorer survival compared to those with lower ctDNA levels (2-year progression survival rate: 40.0% vs. 80.0%, p = 0.011; 5-year overall survival rate: 30.5% vs. 70.0%, p = 0.004). Collectively, our results demonstrated that pretreatment ctDNA analysis could assist origin determination and prognosis prediction clinically.

Patient-reported outcomes are critical for obtaining valuable patient insight into different surgical treatment options with comparable clinical outcomes. This study aimed to compare early postoperative patient-reported symptoms and functioning between thoracoscopic segmentectomy and lobectomy for small-sized (≤ 2 cm) peripheral non-small-cell lung cancer (NSCLC). This study included 110 patients who underwent thoracoscopic segmentectomy or lobectomy for peripheral NSCLC ≤ 2 cm in a multicenter prospective longitudinal study (CN-PRO-Lung 1). Symptom severity, functional status, and short-term clinical outcomes were compared between the groups. Symptom severity and functional status were measured using the MD Anderson Symptom Inventory−Lung Cancer at baseline, daily post-surgery, and weekly post-discharge for up to 4 weeks. Both the proportion of moderate-to-severe scores and mean scores on a 0–10 scale were compared between the groups. Overall, 48 and 62 patients underwent thoracoscopic segmentectomy and lobectomy, respectively. No significant between-group differences were found in the severity of the top five symptoms (coughing, shortness of breath, pain, fatigue, and disturbed sleep) or in the impairment of all six function items (work, walking, general activity, enjoyment of life, mood, and relations with others) during both the 6-day postoperative hospitalization and the 4-week post-discharge (all p > 0.05). Short-term clinical outcomes of postoperative hospital stay, operative time, drainage time, postoperative in-hospital oral morphine equivalent dose, and complication rate were also comparable (all p > 0.05). In patients with peripheral NSCLC ≤ 2 cm, thoracoscopic segmentectomy and lobectomy might produce comparable symptom burden and functional impairment during the early postoperative period.

In Henan province of China, the power demand is vigorous, and the existing provincial generators are mostly high-carbon. Henan faces greater challenges in electricity revolution than other provinces. Currently, there are two development modes for generating low-carbon electricity in Henan: the “large-scale and long-distance transmission” (LSLDT) mode and the “local development and consumption” (LDC) mode. To make a better choice on development mode, following works have been done. Firstly, as there is still no macro evaluation on the self-sufficiency ratio by photovoltaic (PV) power in each region of Henan, a rooftop PV installation potential evaluation method based on the roof covering rate is proposed. And two development scenes for wind and PV power generation are set to fit the development trend of Henan in the near future. Secondly, as the load can only be stably supplied by the cooperation of wind turbine, PV equipment and other controllable generation, the real cost of wind turbine and PV power generation is never only the equipment investment. Different from the commonly used levelized cost of electricity method, a bi-level generation planning model based on the total social cost is established. Finally, generation planning schemes are made and the power supply cost per kWh electricity is evaluated under the two development scenes mentioned above. It is found that there is a significant cost advantage when wind and PV electricity are generated with the LDC mode in both scenes. What is more, the existence of reliability cost, wheeling cost and grid-loss cost makes the LSLDT mode difficult to cut down the wind and PV power supply cost. Wind and PV power generation of the LDC mode should be focused on in Henan.

BACKGROUND: The choice of treatment methods for children with deep partial-thickness burn wounds (DPBWs) is an issue that requires careful consideration from surgeons. The purpose of this study was to evaluate the efficacy of precise partial scab removal (PPSR) in the treatment of DPBWs in children. METHODS: We retrospectively analyzed the clinical data of 78 children with DPBWs. The children were divided into a PPSR group (n=37) and a routine dressing change (RDC) group (n=41). In the PPSR group, an electric dermatome was used to cut the scab in the early post-injury period. The thickness scale of the electric dermatome was set to 0.1 mm. The scab was removed to the base with scattered bleeding points. There was still a small amount of necrotic tissue in the base of the wound. For the acellular dermal matrix, the first dressing change was about 1 week after surgery. The RDC group was given conventional wound-dressing treatment. The wound dressing was changed with epidermal growth factor, silver-zinc antibacterial cream, and dressing change. The frequency of dressing change was adjusted once a day or once every other day depending on the condition of wound secretions. The hospitalization time, wound-healing time, fever duration, antibiotic use time, number of subsequent operations, and overall hospitalization expenses were compared between the two groups. RESULTS: The wound-healing time of the PPSR group was 19.86±6.4 days, and the wound-healing time of the RDC group was 24.15±7.12 days (P=0.0068). The duration of fever in the PPSR group and RDC group was 2.62±1.99 and 4.44±3.10 days, respectively (P=0.0032). The antibiotic use time in the PPSR group and RDC group was 4.0±1.33 and 4.83±1.88 days, respectively (P=0.0292). The overall hospitalization cost of the PPSR group and RDC group was yuan renminbi ¥37,852.84±10,894.64 and ¥38,047.46±19,450.37, respectively (P=0.9573). CONCLUSIONS: PPSR can shorten wound-healing time, reduce the frequency of dressing changes, shorten the time of fever in children, lower the frequency of antibiotic use, and decrease number of dressing changes on the wound.

In this paper, we propose a point-cloudbased algorithm for human-following robots to detect and follow the target person in a complex outdoor environment. Specifically, we exploit AdaBoost to train a binary classifier in a designed feature space based on sparse point-cloud to distinguish the target person from other objects. Then a particle filter is applied to continuously track the target's position. Motivated by the interference of obstacles in long-distance human-following scenarios, a motion plan algorithm based on vector field histogram is adopted. Experiments are carried out both on the dataset we collected and in real application scenarios. The results show that our algorithm has the ability of real-time target detection and tracking, and is robust to deal with complex situations in outdoor environments.

Perovskite solar cells (PSCs) have become a promising alternative to sustainable energy due to their high power conversion efficiency (PCE) and low-cost processing. However, the practical applications of PSCs are still limited by the trade-off between high performance and poor stability under operation. Here, a 2D@3D perovskite with quasi core-shell architecture linking the superiorities of both two-dimensional (2D) and three-dimensional (3D) perovskite is prepared through a novel upgraded antisolvent approach. The basic properties as well as the phase distribution and the charge transport behavior of the 2D@3D perovskite were systematically elucidated. A high PCE of 21.60% for 2D@3D PSCs is achieved due to the enhanced surface and grain boundaries passivation, improved energy level alignment and efficient holes transport. The 2D@3D perovskite device without encapsulation shows significantly improved stability at the room temperature (90% of initial PCE for 45 d with a relative humidity of 50%±5%) and relative thermal conditions (83% of initial PCE for 200 h under 85 °C). Compared with traditional 3D PSCs, it proved that such 2D@3D perovskite configuration is an effective architecture for enhancing efficiency and improving stability and therefore will facilitate the further industrialization of PSCs.

A supervisory control for neutron scattering superconducting magnet is proposed in this paper, which adopts hierarchical control strategy. In the field layer, programmable logic controller (PLC) based on monitoring control and data acquisition system is used for automatic control of various working conditions. PLC and upper monitoring computer are independent of each other in the equipment control layer, and independent operation is not dependent on the upper computer, which ensures the independence and safety of the process. The running parameters of superconducting magnet can be detected in real-time with the coverage of local area network (LAN), and the significant equipment of neutron scattering superconducting magnet can be controlled by using real-time control method in the mobile environment. In case of abnormal situation, the backfeed control will be used to realize remote alarm and other functions, which ensures the normal running of neutron scattering superconducting magnet safely and reliably.

Yunpeng Cui, Xuedong Shi, Chuan Mi, Bing Wang, Yuanxing Pan, Yunfei Lin Department of Orthopaedics, Peking University First Hospital, Beijing, People’s Republic of ChinaCorrespondence: Xuedong ShiDepartment of Orthopedic, Peking University First Hospital, No. 7 Xishiku Street, Xicheng District, Beijing, 100032, People’s Republic of ChinaTel +86 10-83575660Email pku_ortho@163.comBackground: This study aimed to evaluate the perioperative safety and efficacy of minimally invasive tubular surgery for patients with spinal metastasis.Methods: A total of 161 consecutive patients with spinal metastasis between June 2017 and June 2020 were retrospectively reviewed. A total of 36 patients were included in this study, 14 patients underwent minimally invasive tubular surgery (M), and 22 patients underwent conventional surgery (C). T-test and chi-square tests were used to evaluate demographic and perioperative data differences between the two groups.Results: Baseline characteristics did not differ significantly between M and C groups except for the SINS (p=0.002) and preoperative Alb (p=0.026). There was no significant difference in operative time and complications between M and C groups (p< 0.05). The M group had less mean blood loss than the C group (1275 vs 718mL, p=0.045). Blood transfusion was comparable between the two groups (p< 0.05). The mean amount and drainage time were lower than the C group (141 vs 873mL, p< 0.001; 3.1 vs 7.0 days, P< 0.001). The mean postoperative hospitalization of the M group was 8.8 days, which was lower than the C group (11.3 days, p=0.045). Sub-analysis showed that for patients with hyper-vascular tumor, the M group had less mean amount and time of drainage compared with the C group (p< 0.05); for patients with hypo-vascular tumor, the mean blood loss and amount of blood transfusion were also reduced in M group (p< 0.05). The mean blood loss and drainage time of patients with hypo-vascular tumors were less than patients with hyper-vascular tumors in the M group (p< 0.05).Conclusion: In selected cases, minimally invasive tubular surgery is safe and effective for patients with spinal metastasis. Patients with hypo-vascular tumors were more suitable for this technique with less blood loss, fewer blood transfusions, minor drainage, and shorter postoperative hospitalization.Keywords: spinal metastasis, minimally invasive tubular surgery, minimally invasive spine surgery, conventional surgery, tubular retractor, hypo-vascular tumor

Efficient human-machine interface (HMI) for exoskeletons remains an active research topic, where sample methods have been proposed including using computer vision, EEG (electroencephalogram), and voice recognition. However, some of these methods lack sufficient accuracy, security, and portability. This paper proposes a HMI referred as integrated trigger-word configurable voice activation and speaker verification system (CVASV). The CVASV system is designed for embedded systems with limited computing power that can be applied to any exoskeleton platform. The CVASV system consists of two main sections, including an API based voice activation section and a deep learning based text-independent voice verification section. These two sections are combined into a system that allows the user to configure the activation trigger-word and verify the user’s command in real-time.

This paper presents the design of an exoskeleton glove system for people who suffer from the brachial plexus injuries in an effort to restore their lost grasping functionality. The robotic system consists of an embedded controller and a portable glove system. The glove system consists of Linear Series Elastic Actuators (SEA), Rotary SEA and optimized finger linkages to provide motion to each finger and a coupled motion of the hand and the wrist. The design is based on various functionality requirements such as being lightweight and portable for activities of daily living, especially for grasping. The contact force at each fingertip and bending angle of each finger are measured for future implementation of intelligent control algorithms for autonomous grasping. To provide better flexibility and comfort for the users, abduction and adduction of each finger as well as flexion of the thumb were taken into consideration in the design. The glove system is adjustable for different hand sizes. The micro-controllers and batteries are integrated on the forearm in order to provide a completely portable design solution.

Injection of total saponins from Panax notoginseng (ISPN) is a modern preparation derived from traditional Chinese medicine (TCM) and is widely applied in the treatment of cardiovascular, cerebrovascular, ophthalmology, and endocrine system diseases. With the increase in the clinical application of ISPN, its adverse drug reactions (ADRs) and related safety issues have attracted much attention. In the present study, a data-independent acquisition (DIA) strategy was proposed to comprehensively characterize the saponins contained in ISPN based on the ultra-high-performance liquid chromatography/quadrupole-Orbitrap MS (UHPLC/Q-Orbitrap MS) platform. As many as 276 saponins were detected, and 250 compounds were identified or tentatively identified based on the retention times and MS/MS data. Furthermore, a metabolomic strategy was utilized to discover the discriminative saponins between normal and ADR batches. The results showed that six saponins, including ginsenoside Rh4, ginsenoside Rk3, ginsenoside Rg5, ginsenoside Rk1, ginsenoside Rg6, and 20(S)-ginsenoside Rh2, were significantly different between the two groups. According to cytotoxicity analysis and degranulation detection of RBL-2H3 cells, ginsenoside Rg5, ginsenoside Rk1, and 20(S)-ginsenoside Rh2 were considered the potential compounds responsible for clinical ADRs, ultimately. In addition, the quantitative analysis showed that the content of these three compounds in ISPN samples with ADRs was generally higher than that in samples without ADRs. This study demonstrated that it is advisable to screen out potential markers related to ADRs for developing the quality standard of ISPN by the integration of untargeted metabolomic analysis and cell biology study, and thus reduce its ADRs in the clinic.