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Network measurement provides operators an efficient tool for many network management tasks such as performance diagnosis, traffic engineering and intrusion prevention. However, with the rapid and continuous growth of traffic speed, it needs more computing and memory resources to monitor traffic in per-flow or per-packet granularity. Sample-based measurement systems (e.g., NetFlow, sFlow) have been developed to perform coarse-grained measurement, but they may miss part of records, especially for mice flows, which are important for some network management tasks (e.g., anomaly detection, performance diagnosis). To address these issues, data streaming algorithms such as hash tables and sketches have been introduced to balance the trade-off among accuracy, speed, and memory usage. In this paper, we present a systematic survey of various data structures, algorithms and systems which have been proposed in recent years to perform fine-grained measurement for high-speed networks. We organize these methods and systems from a software-defined perspective. In particular, we abstract fine-grained network measurement into three-layer architecture. We introduce the responsibility of each layer and categorize existing state-of-the-art works into this architecture. Finally, we conclude the paper and discuss the future directions of fine-grained network measurement.

Defects on rail surfaces, which have become critical problems, need to be detected and removed as quickly as possible to ensure the fast, safe, and stable operation of trains. At present, although many solutions have been proposed to address these problems, the comprehensiveness, rapidity, and accuracy of defect detection remain unsatisfactory. This study aims to resolve these existing problems and accordingly proposes a multi-model rail surface defect detection system based on convolutional neural networks (MRSDI-CNN) from the standpoint of studying the squat on the rail surface. The convolutional neural networks utilized include the improved Single Shot MultiBox Detector (SSD) and You Only Look Once version 3(YOLOv3)--two types of one-stage networks. We expounded and analyzed the performance of the convolutional neural networks as well as their applicability to rail surface defect detection. We used a diverse range of rail defect sizes to improve the detection performance of the two deep learning networks, following which they could identify three types of squats in parallel with improved accuracy and without reduction of the detection speed. The experimental results confirm the effectiveness and superiority of the proposed method over those of previous studies.

The superiority of Convolutional Neural Networks (CNNs) largely relies on their architectures that are usually manually crafted with extensive human expertise. Unfortunately, such kind of domain knowledge is not necessarily owned by every interested user. Data mining on existing CNNs can discover useful patterns and fundamental comments from their architectures, providing researchers with strong prior knowledge to design effective CNN architectures when they have no expertise in CNNs. There are various state-of-the-art data mining algorithms at hand, while there is only rare work on mining CNN architectures. One of the main reasons is the gap between CNN architectures and data mining algorithms. Specifically, the current CNN architecture descriptions cannot be exactly vectorized to feed to an data mining algorithm. In this paper, we propose a unified approach, named ArcText, to describing CNN architectures based on text. Particularly, four different units and an ordering method have been elaborately designed in ArcText, to uniquely describe the same CNN architecture with sufficient information. Also, the resulted description can be exactly converted back to the corresponding CNN architecture. ArcText bridges the gap between CNN architectures and data mining researchers, and has the potential to be utilized to wider scenarios.

Evolutionary multitasking (EMT) is an emerging research direction in the field of evolutionary computation. EMT solves multiple optimization tasks simultaneously using evolutionary algorithms with the aim to improve the solution for each task via intertask knowledge transfer. The effectiveness of intertask knowledge transfer is the key to the success of EMT. The multifactorial evolutionary algorithm (MFEA) represents one of the most widely used implementation paradigms of EMT. However, it tends to suffer from noneffective or even negative knowledge transfer. To address this issue and improve the performance of MFEA, we incorporate a prior-knowledge-based multiobjectivization via decomposition (MVD) into MFEA to construct strongly related meme helper-tasks. In the proposed method, MVD creates a related multiobjective optimization problem for each component task based on the corresponding problem structure or decision variable grouping to enhance positive intertask knowledge transfer. MVD can reduce the number of local optima and increase population diversity. Comparative experiments on the widely used test problems demonstrate that the constructed meme helper-tasks can utilize the prior knowledge of the target problems to improve the performance of MFEA.

Background Some genetic association studies tried to investigate potential associations of phosphatase and actin regulator 1 (PHACTR1) polymorphisms with coronary artery disease (CAD). However, the results of these studies were not consistent. Thus, we performed the present meta-analysis to explore associations between PHACTR1 polymorphisms and CAD in a larger pooled population. Methods Systematic literature research of PubMed, Web of Science, Embase and CNKI was performed to identify eligible studies. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) to estimate strength of associations. Results Totally 8 studies were included for analyses (10856 cases and 18801 controls). Pooled analyses suggested that rs9349379 polymorphism was significantly associated with CAD in overall population (dominant model: p=0.004, OR=1.39, 95%CI 1.11-1.73, I2 =91%; recessive model: p=0.002, OR=0.63, 95%CI 0.48-0.84, I2 =85%; over-dominant model: p=0.03, OR=0.89, 95%CI 0.80-0.99, I2 =59%; allele model: p=0.0002, OR=1.30, 95%CI 1.13-1.49, I2 =89%), and this significant finding was further confirmed in both Asians and Caucasians. However, no any positive findings were observed for rs2026458 polymorphism in pooled analyses. Conclusions Our meta-analysis suggested that rs9349379 polymorphism might affect individual susceptibility to CAD in both Caucasians and Asians. Future investigations need to explore the underlying molecular mechanisms of our positive findings.

Objective. The study focused on the separation effects of ultrasound blood flow signal detection, based on empirical mode decomposition (EMD) algorithm, and the clinical efficacy of Compound Danshen injection and magnesium sulfate in the treatment of pregnancy-induced hypertension (PIH) syndrome. Methods. The empirical mode decomposition (EMD) algorithm was optimized first and compared with other algorithms for the accuracy and stability in separation of blood flow signals. 80 patients with PIH syndrome undergoing ultrasound examination were selected as the research subjects and randomly divided into control group and observation group according to the actual treatment methods. 40 cases in the observation group were treated with Compound Danshen injection + magnesium sulfate, and 40 cases in the control group were treated with magnesium sulfate. After the treatment, the clinical indicators of the two groups of patients were analyzed. Results. The accuracy and stability in separating blood flow signal of the optimized EMD algorithm were better than those of other algorithms. After treatment, the total effective rate and blood pressure control of the observation group were significantly better than those of the control group, and the incidence of adverse maternal and infant outcomes was significantly lower than that of the control group. After treatment, the endothelin-1 (ET-1), C-reactive protein (CRP), and homocysteine (Hcy) indexes of the two groups of patients decreased significantly, and the decrease level of the observation group was significantly greater than that of the control group ( P P

The signcryption protocols supporting the equality test are only for a single system rather than a flexible heterogeneous environment of wireless body area networks (WBANs). In this article, this problem is efficiently addressed through a proposed heterogeneous signcryption scheme from identity-based cryptosystem (IBC) to public key infrastructure (PKI) with an equality test (HSCIP-ET) for WBANs. Our scheme allows the sensors planted or worn by a user in the IBC system to signcrypt sensitive data using the public key of the management center in the PKI system, and then uploading it to the cloud server. Subsequently, the equality test can be executed by the cloud server on diverse ciphertexts to determine whether they contain the identical plaintext and return the corresponding result after receiving a request from an application provider. Furthermore, a rigorous analysis and an experimental comparison demonstrate the security and efficiency of the HSCIP-ET approach, respectively.

In this article, we present a multiagent framework for real-time large-scale 3-D reconstruction applications. In SLAM, researchers usually build and update a 3-D map after applying nonlinear pose graph optimization techniques. Moreover, many multiagent systems are prevalently using odometry information from additional sensors. These methods generally involve extensive computer vision algorithms and are tightly coupled with various sensors. We develop a generic method for the key challenging scenarios in multiagent 3-D mapping based on different camera systems. The proposed framework performs actively in terms of localizing each agent after the first loop closure between them. It is shown that the proposed system only uses monocular cameras to yield real-time multiagent large-scale localization and 3-D global mapping. Based on the initial matching, our system can calculate the optimal scale difference between multiple 3-D maps and then estimate an accurate relative pose transformation for large-scale global mapping.

As a promising technology, the Internet of Vehicle (IoV) enables vehicles connected to the network and sends announcements to roadside units (RSUs) or other vehicles. Nevertheless, because of the open nature of IoV, trust and privacy are confronted with challenges from cyber attacks. Motivated by addressing the above-mentioned problems, a privacy-preserve announcement protocol is constructed in this article, in which an identity-based group signature is used to achieve anonymity of vehicles. In addition, a novel blockchain-based trust management system is designed to guarantee the authenticity of the transmitted messages while realizing the message synchronization. In the meanwhile, a joint proof of work and improved practical Byzantine fault tolerance consensus mechanism is adopted in our scheme to enhance the efficiency of verification. Security analysis as well as simulation results indicate that our proposal is suitable and effective for IoV environment.

Customer loyalty programs are often used by retailers as an important marketing tool. As an essential element of loyalty programs (LPs), the reward amount invested by the retailer is often linked to retailer's profit and customer behavior. We consider a retailer who sells a type of product in two periods to strategic customers. The retailer makes inventory ordering and loyalty program investment decisions. Customers decide whether to purchase immediately (in period 1) to receive the product and reward, or to wait for a markdown discount but face the risk of stockout. We have focused on three main questions: (1) How does the loyalty reward investment decision impact strategic customers’ behavior? (2) What are the optimal decisions and profits for the retailer when investing in a loyalty program? (3) What are the factors influencing the reward investment decision? We find that investing in the loyalty program induces more customers to make an early purchase, leading to a higher inventory ordering decision and more profit for the retailer. The benefits from reward investments are significantly affected by the product's cost and customers’ valuation of the product. Our results shed light on the reward investment decision of LPs. For products with high profit margins and market-determined prices (valuation approximates price), the retailer should invest in a loyalty program to achieve better profits.

Massive trajectory data stem from the prevalence of equipment-supporting GPS and wireless communication technology. Especially, activity trajectory from LBSN endows traditional trajectory data with additional user semantic activities. Measuring the similarity between activity trajectories is to compare their proximity in multiple dimensions such as time, location, and semantics. In this way, we can mine implicit user preference and apply it to route planning, POI recommendation or any other online tasks. The key challenge of comparing activity trajectories lies in two aspects. One is the uneven sampling rate in both time and space. The other is the discrepancy of individual activities. Previous effort alleviates the issue of uneven sampling rate via trajectory complements, which is limited to spatial-temporal information. In this paper, we propose to learn a representation for one activity trajectory by jointly considering the spatio-temporal characteristics and the activity semantics. The similarity of two trajectories is computed by weighting individual trajectory points and contextual features with multi-level attention mechanisms. In specific, we propose a point-level and feature-level attention mechanism to adaptively select critical elements and contextual factors for learning trajectory representation. Our proposed approach, called At2vec, demonstrates better performance than existing baselines in extensive experimental evaluation on real databases.

Existing conditional anonymous authentication protocols to secure the group communication in VANETs (Vehicular Ad hoc Networks) render challenges such as dynamically updating membership in a domain and achieving vehicle user's privacy preservation. This paper elegantly addresses these challenges by proposing a novel conditional privacy-preserving authentication with dynamic membership for VANETs depending on chinese remainder theorem (CRT). Specifically, the CRT is utilized by a trusted authority to securely disseminate a domain key for the authorized vehicles in the same domain, where each vehicle in this domain is able to obtain the domain key by only performing one modulo division operation in case of domain key updating. Distinct from the previous works in this field, our proposed protocol not only achieves message authentication, anonymity and conditional privacy-preserving, but also provides forward security and backward security of vehicles. Theoretical analysis and experiment simulation demonstrate that the proposed protocol is provably secure and highly feasible.

Organic metal halide perovskite materials have excellent photoelectric properties, and the power conversion efficiency (PCE) of the perovskite solar cells (PSCs) has increased from 3.8% to more than 25%. In the development of PSCs, innovative architectures were being proposed constantly. However, the use of the electron transport layer (ETL) and hole transport layer (HTL) increases manufacturing costs and process complexity. Perovskite material has ambipolar charge transport characteristics, so it could functionalize as both the optical absorption layer and carrier transport layer (CTL). In this review, we analyzed the P/N-type perovskite materials, perovskite P-N homojunction solar cells, and carrier transport layers-free (CTLs-free) devices. Finally, we proposed some innovative device architectures. We hoped that this mini review could pave way for the simplification of the architectures, promote the preparation of the low-cost and high-efficiency devices, and accelerate the commercialization of the PSCs.

Renewable energy has become an important choice to solve the energy crisis and environmental problems. A sustainable development needs policies and strategies policies, which can improve energy efficiency and reduce greenhouse gas emissions. By collecting the research results released by relevant statistical departments and authoritative institutions, this paper summarizes the international energy development situation, systematically combs the energy development situation of the European Union, United States, Australia, India, Brazil. The development trend of wind, solar, biomass, geothermal, ocean, and hydrogen energy have been analyzed. In addition, this paper proposes that China should draw up its own development path of renewable energy from international development experience, and actively explore renewable energy policies and strategies adapted to different stages of development.

OBJECTIVE To determine the risk for pulmonary embolism (PE) and explore the relationship between the site of thrombosis and PE in patients with acute lower extremity deep vein thrombosis (DVT). METHODS 1585 hospitalized patients first diagnosed with acute lower extremity DVT were investigated retrospectively. The patients were divided into two groups: the non-PE group (Group 1) and the PE group (Group 2). Then, Group 2 was divided into two subgroups: asymptomatic pulmonary embolism (asPE, Group 2a) and symptomatic pulmonary embolism (sPE, Group 2b). Kaplan-Meier curves and logistic regression analysis were used to explore the relevant risk factors for PE. RESULTS Among 1585 patients, 458 patients suffered from PE, accounting for 28.9%. 102 (22.3%) of them had the typical clinical manifestations of PE and were defined as sPE, and the remaining 356 (77.7%) patients were classified as asPE. Patients with proximal lower extremity DVT were significantly more predominant in the PE group than in the non-PE group (92.8% vs. 86.2%, p

Robotic compliant manipulation is a very challenging but urgent research spot in the domain of robotics. One difficulty lies in the lack of a unified representation for encoding and learning of compliant profiles. This article aims to introduce a novel learning and control framework to address this problem: 1) we provide a parametric representation that enables a compliant skill to be encoded in a parametric space and allows a robot to learn compliant manipulation skills based on motion and force information collected from human demonstrations; and 2) the updating laws of the compliant profiles, including impedance and force profiles, are derived from a biomimetic control strategy based on the human motor learning principles. Our approach enables the simultaneous adaptation of impedance and feedforward force online during robot’s reproduction of the demonstrated tasks to deal with task dynamics and external interferences. The proposed approach is verified based on both simulation and real-world task scenarios.

The rapid recombination of photoinduced charge carriers and low selectivity are still challenges for the CO2 photoreduction. Herein, we proposed that ZIF-67-derived Co3O4 hollow polyhedrons (CoHP) were embedded into NaCl-template-assisted synthesized 3D graphitic carbon nitride (NCN), subsequently, loading Ag by photo-deposition as efficient composites (CoHP@NCN@Ag) for CO2 photoreduction. This integration simultaneously constructs two heterojunctions: p-n junction between Co3O4 and g-C3N4 and metal-semiconductor junction between Ag and g-C3N4, in which Co3O4 and Ag serve as hole (h+) trapping sites and electron (e-) sinks, respectively, achieving spatial separation of charge carriers. The donor-acceptor structure design of NCN realize a good photogenerated e--h+ separation efficiency. The mesoporous structure of hollow Co3O4 facilitate gas-diffusion efficiency, light scattering and harvesting. And the introduction of plasmonic Ag further strengthens the light-harvesting and charge migration. Benefiting from the rational design, the optimized ternary heterostructures exhibit a high CO2-CO yield (562 μmol g-1), which is about 4-fold as high as that of the NCN (151 μmol g-1). Moreover, the conjectural mechanism was systematically summarized. We hope this study provides a promising strategy for designing efficient g-C3N4 systems for the CO2 photoreduction.

An interaction function was constructed based on the axial compression/tension and shear loads of orthotropic plates. The coefficients of the polynomial function were determined by uniaxial test results. Buckling interaction and failure interaction formulae under combined axial tension/compression and shear loads were established. Based on the uniaxial load test results of orthotropic plates, the buckling load and bearing capacity under any proportion of the combined loads could be predicted by using the proposed interaction formulae. The buckling interaction curves and failure envelopes predicted by the proposed interaction formulae were in excellent agreement with the test results.

The use of semiconductors to construct heterojunctions to suppress the rapid recombination of photogenerated charges and holes is considered to be an effective way to improve the efficiency of photocatalytic hydrogen evolution. Herein, cobalt sulfide (CoSx) nanoparticles are cultivated in situ in the folds of three-dimensional flower-like nickel-aluminium layered double hydroxides (NiAl-LDHs) using a facile solvothermal method. The hydrogen production rate of the binary CoSx/NiAl-LDH heterojunction reaches 3678.59 μmol/g/h, which is 83.74 and 22 times the rates of CoSx and NiAl-LDH, respectively. The unique three-dimensional structure of NiAl-LDH facilitates the growth of CoSx and shortens the transfer pathway of photogenerated electrons. More importantly, the built-in electric field formed at the interface and the S-type charge transport mechanism caused by the bending of the energy band enhance not only charge separation but also maintain the strong oxidation ability of the holes. In this study, the newly designed S-scheme heterojunction offers a new strategy for enhancing photocatalytic water splitting.

In this paper, we show the feasibility of improving the performance of a high voltage and high repetition avalanche transistor pulse generator by applying a two-phase immersion cooling technique. The forced air cooling, single-phase immersion cooling, and two-phase immersion cooling technique was applied to a 60-stage sub-nanosecond pulse generator. The experimental results indicate that the two-phase immersion cooling technique can effectively control the temperature rising and thus reduce the time base jitter and voltage amplitude jitter. Five types of dielectric fluid with different boiling temperatures were comparatively studied. The FC-72 was finally adopted for the balanced performance on voltage amplitude and repetition rate. The two-phase immersion cooling technique could reduce the thermal resistance between the case and ambient, and increase the power from 330mW to 876mW. With this cooling method, the surface temperature of the transistor can be effectively controlled below 62. The pulse generator could achieve outstanding performance with a voltage of 2350 V and a rise time of 180 ps. It can work stably at 200 kHz for more than 30 minutes, and the burst repetition rate could be 260 kHz within one minute. This work offers new perspectives in high repetitive avalanche transistorized sub-nanosecond generators.

Introduction Gut microbiota has been implicated in the pharmacological activities of many natural products. As an effective hypolipidemic agent, berberine (BBR)’s clinical application is greatly impeded by the obvious inter-individual response variation. To date, little evidence exists on the causality between gut microbes and its therapeutic effects, and the linkage of bacteria alterations to the inter-individual response variation. Objectives This study aims to confirm the causal role of the gut microbiota in BBR’s anti-hyperlipidemic effect and identify key bacteria that can predict its effectiveness. Methods The correlation between gut microbiota and BBR’s inter-individual response variation was studied in hyperlipidemic patients. The causal role of gut microbes in BBR’s anti-hyperlipidemic effects was subsequently assessed by altered administration routes, co-treatment with antibiotics, fecal microbiota transplantation, and metagenomic analysis. Results Three-month clinical study showed that BBR was effectively to decrease serum lipids but displayed an obvious response variation. The cholesterol-lowering but not triglyceride-decreasing effect of BBR was closely related to its modulation on gut microbiota. Interestingly, the baseline levels of Alistipes and Blautia could accurately predict its anti-hypercholesterolemic efficiency in the following treatment. Causality experiments in mice further confirmed that the gut microbiome is both necessary and sufficient to mediate the lipid-lowering effect of BBR. The absence of Blautia substantially abolished BBR's cholesterol-decreasing efficacy. Conclusion The gut microbiota is necessary and sufficient for BBR’s hyperlipidemia-ameliorating effect. The baseline composition of gut microbes can be an effective predictor for its pharmacotherapeutic efficacy, providing a novel way to achieve personalized therapy.

MET-targeted therapies are clinically effective in MET-amplified and MET exon 14 deletion mutant (METex14) non–small cell lung cancers (NSCLCs), but their efficacy is limited by the development of drug resistance. Structurally distinct MET tyrosine kinase inhibitors (TKIs) (type I/II) have been developed or are under clinical evaluation, which may overcome MET-mediated drug resistance mechanisms. In this study, we assess secondary MET mutations likely to emerge in response to treatment with single-agent or combinations of type I/type II MET TKIs using TPR-MET transformed Ba/F3 cell mutagenesis assays. We found that these inhibitors gave rise to distinct secondary MET mutant profiles. However, a combination of type I/II TKI inhibitors (capmatinib and merestinib) yielded no resistant clones in vitro. The combination of capmatinib/merestinib was evaluated in vivo and led to a significant reduction in tumor outgrowth compared with either MET inhibitor alone. Our findings demonstrate in vitro and in vivo that a simultaneous treatment with a type I and type II MET TKI may be a clinically viable approach to delay and/or diminish the emergence of on target MET-mediated drug-resistance mutations.

Optical tunneling is an effect extremely sensitive to wavelength changes. In this article, we use this effect to design a new type of biosensor. The tunneling effect is excited by long range surface plasmon resonance, the energy is concentrated in the sensing medium in the form of standing waves, which lead a very high wavelength sensitivity and quality factor. By using COMSOL for finite element analysis, for the sensor structure of BK7/Cytop /Al2O3/Ag/Al2O3/sensing media/air, a quality factor of 10296 RIU-1 is achieved under angle modulation, a sensitivity of 170,000 nm/ RIU and a quality factor of 11333 RIU-1 are obtained under wavelength modulation. At the same time, the advantage of this structure is that there is no excessive requirement on the refractive index of the material, and a good sensing effect can be achieved even if the material is cheap and easy to prepare. After optimization, this structure is suitable for sensing media with a refractive index of 1.335-1.375, which can be applied to most liquid solutions.

In this work, we fabricated and characterized 4 × 4 parallel flip-chip AlGaN-based micro-LED arrays with varied mesa diameters of 120 µm, 100 µm, 80 µm, and 60 µm. The reported micro-LED arrays have a maximum bandwidth of 380 MHz and a peak wavelength of ∼275 nm. It is found that the electrical and optical characteristics of AlGaN-based micro-LED arrays show strong size dependence for ultraviolet communication (UVC). The differential resistance increases from 28.8 Ω to 112 Ω, the external quantum efficiency (EQE) is increased by ∼30%, and the bandwidth doubles as the diameter of individual micro-LED decreases from 120 µm to 60 µm. Our research proves that tailoring the mesa size of parallel flip-chip AlGaN-based micro-LED arrays can further enhance its bandwidth and promote its application in UVC.

Flexible narrowband near infrared (NIR) photodetectors (PDs) are urgently in demand in the fast-developing era of flexible electronics, due to their crucial roles in various innovative applications. Hence, we designed and synthesized the core–shell structured NaYF4:Yb3+,Er3+@NaYF4:Nd3+ upconversion nanoparticles (UCNPs), which can be pumped by the 808 and 980 nm lights. The upconversion luminescence (UCL) are significantly enhanced after being assembled with the opal photonic crystals (OPCs) due to the photonic crystal effect, with 55 and 48 folds of enhancement factors under illuminations of 808 and 980 nm lights, respectively. Based on this hybrid, the flexible narrowband PDs were successfully fabricated on the PET substrate with the structure of OPCs/NaYF4:Yb3+,Er3+@Nd3+/MAPbI3, which displays excellent detection performance to double narrowband NIR light (808 and 980 nm) benefiting from the amplified UCL, with responsivity of 8.79 and 7.39 A/W, detectivity of 3.01 × 1011 and 2.68 × 1011 cm⋅Hz1/2/ W for 808 and 980 nm lights detection respectively, along with short response time in the range of 120–160 ms. Furthermore, the OPCs/NaYF4:Yb3+,Er3+@NaYF4:Nd3+/MAPbI3 double narrowband PDs display low photodetection power threshold (0.05 W/cm2), outstanding flexibility, prominent moisture resistance, and good long-time stability. This work displays a new concept of narrowband NIR PDs, which open a new field for specific NIR light detections.

The immunosuppressive microenvironment is associated with poor prognosis in papillary thyroid cancer (PTC); however, the molecular mechanisms involved are unknown. Among the triggering receptors expressed on myeloid cell (TREM) family, we found that TREM1 expression in PTC was significantly higher than that in normal tissues. TREM1 overexpression was associated with BRAFV600E profiles and advanced tumor stages. Furthermore, TREM1 mRNA expression was negatively correlated with promoter methylation status. Specifically, hypomethylation of CpG site cg06196379 in the TREM1 promoter was related with poor patient disease-free survival (DFS) and a high PTC recurrence rate. Mechanistically, TREM1 was mainly expressed in malignant epithelial cells but not in macrophages in PTC by single-cell analysis. PTC tissues with high TREM1 levels had enhanced infiltration of regulatory T cells (Tregs) and decreased infiltration of CD8+ T cells. Our study confirms that hypomethylation-mediated overexpression of TREM1 in PTC cells promotes an immunosuppressive microenvironment by enhancing Treg infiltration. We recommend the future use of therapeutic strategy targeting TREM1 for the treatment of PTC.

Objective Older adults with subjective memory complaints (SMC) have a higher risk of dementia and commonly demonstrate symptoms of depression and anxiety. The study aimed to examine the effect of a memory training program for individuals with SMC, and whether additional group counseling aimed at alleviating depression and anxiety would boost memory training gains. Design A three-armed, double-blind, randomized controlled trial. Setting and Participants Community-dwelling older adults with SMC, age ≥60. Methods Participants (n = 124) were randomly assigned to memory training (MT), group counseling (GC), or GC + MT intervention. The GT + MT group received 3 sessions of group counseling followed by a 4-week memory training, while the MT group attended reading and memory training, and the GC group received group counseling and health lectures. Cognitive function and symptoms of depression and anxiety were assessed at baseline, mid-, and post-intervention. Results After group counseling, the GC + MT and GC groups showed reduced symptoms of anxiety compared to the MT group. Memory training enhanced associative learning in both MT and GC + MT groups compare with the GC group, but the GC + MT group demonstrated a larger memory improvement (Cohen's d = 0.57) than the MT group (Cohen's d = 0.44). Conclusion and Implications Group counseling decreased symptoms of anxiety, memory training increased associative learning, and the combination of two intervention induced larger memory gain than memory training alone. The results suggest that it may need to integrate treatment for anxiety into memory training for older adults with SMC to achieve better intervention effect. Trial Registration ChiCTR-IOR-15006165 in the Chinese Clinical Trial Registry.

Background: Lobar cerebral microbleeds (CMBs), which can impair white matter (WM), are often concomitant with definite Alzheimer’s disease (AD). Objective: To explore the features of cognitive impairments and WM disruptions due to lobar CMBs in patients with AD. Methods: There were 310 participants who underwent Florbetapir F18 (AV45) amyloid PET and susceptibility-weighted imaging. Participants with cognitive impairment and amyloid-β positive (ADCI) were included into three groups: ADCI without CMBs, with strictly lobar CMBs (SL-CMBs), and with mixed CMBs (M-CMBs). Tract-based spatial statistics were performed to detect the group differences in WM integrity. Results: There were 82 patients and 29 healthy controls finally included. A decreasing tendency in memory and executive performance can be found among HCs > no CMBs (n = 16) >SL-CMBs (n = 41) >M-CMBs (n = 25) group. Compared to no CMBs, M-CMBs group had significantly decreased fractional anisotropy in left anterior thalamic radiation (ATR), forceps major, forceps minor and inferior longitudinal fasciculus, bilateral inferior fronto-occipital fasciculus (IFOF), and superior longitudinal fasciculus. M-CMBs group also had lower fractional anisotropy in left ATR, IFOF, uncinate fasciculus, and forceps minor compared with SL-CMBs. Furthermore, analysis of Pearson correlation indicated damages in discrepant WMs were positively associated with impairment of memory, executive function, and attention. Conclusion: This study showed lobar CMBs had intensively aggravated cognitive impairments associated with extensive WM damages in definite AD. These findings highlight that lobar CMBs play an important role in AD progression and need to be taken into consideration for the early detection of AD.

Laser-induced graphene (LIG) technology featuring low-cost, high-efficiency and scalability has presented great advantages in micro-supercapacitors (MSCs) fabrication. However, the limited capacitance of LIG based MSCs is still hindering their further development. Herein, we introduce joule heating as a critical in-situ treatment merged with the assembly of laser-induced graphene paper based MSCs (LIGP-MSCs) toward capacitive enhancement. By increasing heating-treatment temperature from ∼20 to 500 °C, the number of nanopores in LIGP continuously increases, attributed to the gradual decomposition of amorphous carbon components. The resulting joule-heated LIGP (J-LIGP) with improved specific surface area (160.97–533.49 m2/g) and pore volume (0.179–0.553 cm3/g) as well as superhydrophilic surface is highly suitable to be employed as J-LIGP-MSCs microelectrodes. By investigating process dependent performance, the J-LIGP-MSCs heated at 500 °C for 60 min delivers a significantly improved specific areal capacitance (CA) of 13.71 mF/cm2 at 10 mV/s, which is approximately six-fold higher than that of unheated LIGP-MSCs. By further exploring and optimizing the process efficiency, J-LIGP-MSCs with a CA of 12.61 mF/cm2 has been achieved by 550 °C heating for only 5 min. Along with superior mechanical flexibility, cyclability and structural modularity, the proposed in-situ joule heating treatment is finally proved to be a universal approach for consistently enhancing the CA of LIG based MSCs processed under various chemical modifications.

Fast and accurate plant counting tools affect revolution in modern agriculture. Agricultural practitioners, however, expect the output of the tools to be not only accurate but also explainable. Such explainability often refers to the ability to infer which instance is counted. One intuitive way is to generate a bounding box for each instance. Nevertheless, compared with counting by detection, plant counts can be inferred more directly in the local count framework, while one thing reproaching this paradigm is its poor explainability of output visualization. In particular, we find that the poor explainability becomes a bottleneck limiting the counting performance. To address this, we explore the idea of guided upsampling and background suppression where a novel upsampling operator is proposed to allow count redistribution, and segmentation decoders with different fusion strategies are investigated to suppress background, respectively. By integrating them into our previous counting model TasselNetV2, we introduce TasselNetV3 series: TasselNetV3-Lite and TasselNetV3-Seg. We validate the TasselNetV3 series on three public plant counting data sets and a new unmanned aircraft vehicle (UAV)-based data set, covering maize tassels counting, wheat ears counting, and rice plants counting. Extensive results show that guided upsampling and background suppression not only improve counting performance but also enable explainable visualization. Aside from state-of-the-art performance, we have several interesting observations: 1) a limited-receptive-field counter in most cases outperforms a large-receptive-field one; 2) it is sufficient to generate empirical segmentation masks from dotted annotations; 3) middle fusion is a good choice to integrate foreground-background a priori knowledge; and 4) decoupling the learning of counting and segmentation matters.

Noise reduction is an essential step in seismic exploration. Formally, the random broadband noise in the desert seismic is characterized as nonlinear, nonstationary, and non-Gaussian, and the energy is concentrated mainly in the low-frequency range. Moreover, the reflected signals generally cover the same spectral region as a strong random broadband noise. In this letter, a method combining unsupervised feature learning and the time-frequency transform (TFT) technique is proposed to reduce random broadband noise in desert seismic data. First, as a TFT technique, the variational mode decomposition (VMD) is carried out to decompose the multicomponent desert seismic signal into an ensemble of band-limited modes. Then, we apply an unsupervised feature learning method on each decomposed mode for detecting desert seismic events. Finally, the inverse VMD transform is conducted to obtain the final denoised result. This method is tested on both synthetic and field desert seismic data, demonstrating its preferable performance in reducing random broadband noise and preserving reflected signals.

Background & aims Regulatory T cell (Treg) depletion increases antitumor immunity. However, severe autoimmunity can occur following systemic loss of Tregs, which could be avoided by selectively depleting intratumoral Tregs. Herein, we aimed to investigate the role of tumor-infiltrating CCR4+ Tregs in hepatocellular carcinoma (HCC) and to provide a potential target strategy for immunotherapy. Methods CCR4+ Tregs were analyzed by flow cytometry in murine models and clinical samples. The function of tumor-infiltrating and induced CCR4+ Tregs was interrogated by genetic and epigenetic approaches. To block CCR4+ Treg chemotaxis, we developed an N-terminus recombinant protein of CCR4 (N-CCR4-Fc) as a neutralizing pseudo-receptor that effectively bound to its ligand CCL22. The efficacy of CCR4 antagonism as an immunotherapeutic agent was evaluated by tumor weights, growth kinetics and survival curves. Results CCR4+ Tregs were the predominant type of Tregs recruited to hepatitis B-associated HCC (HBV+ HCC), correlating with sorafenib resistance and HBV load titers. Compared with CCR4- Tregs, CCR4+ Tregs exhibited increased IL-10 and IL-35 expression, and enhanced functionality in suppressing CD8+ T cells. CCR4+ Tregs also displayed PD-1+TCF1+ stem-like properties. ATAC-seq data revealed substantial chromatin remodeling between tumor-infiltrating Tregs (TIL-Tregs) and induced Tregs, suggesting that long-term chromatin reprogramming accounted for the acquisition of enhanced immunosuppressive stem-like specificity by CCR4+ TIL-Tregs. Treatment with a CCR4 antagonist or N-CCR4-Fc blocked intratumoral Treg accumulation, overcame sorafenib resistance, and sensitized tumors to PD-1 checkpoint blockade. Conclusions Intratumoral stem-like CCR4+ Tregs orchestrated immunosuppressive resource cells in the tumor microenvironment. CCR4 could be targeted to enhance antitumor immunity by specifically blocking infiltration of Tregs into the tumor microenvironment and inhibiting maintenance of the TIL-Treg pool. Lay summary Targeting regulatory T cells is a promising approach in cancer immunotherapy; however, severe autoimmunity can occur following systemic regulatory T cell loss. This could be avoided by selectively depleting intratumoral regulatory T cells. Herein, targeting intratumoral stem-like CCR4+ regulatory T cells helped to overcome sorafenib resistance and sensitize tumors to immune checkpoint blockade in mouse models of liver cancer. This approach could have wide clinical applicability.

Cuprous oxide (Cu2O) is a p-type semiconductor with excellent catalytic activity and stability that has gained much attention because it is non-toxic, abundant, and inexpensive. Porous carbon materials have large specific surface areas, which offer abundant electroactive sites, enhance the electrical conductivity of materials, and prevent the aggregation of Cu2O nanocubes. In this study, a composite with high electrocatalytic activity was prepared based on Cu2O nanocubes anchored onto three-dimensional macroporous carbon (MPC) by a simple, eco-friendly, and cheap method for hydrazine detection. Due to the synergistic effect of MPC and Cu2O, the sensor exhibited high electrocatalytic activity, sensitivity, better selectivity, and low limit of detection. The resulting sensor could be a sensitive and effective platform for detecting hydrazine and promising practical applications.

A variety of deep learning approaches have been applied to region of interest (ROI) extraction, which is a fundamental task in the field of remote sensing image (RSI) processing. However, the unbalanced distribution of positive and negative samples in most RSIs greatly restricts the performance of these deep learning-based methods. In this study, a data augmentation method based on variational autoencoder-multiscale generative adversarial network (VAE-MSGAN) with spatial and channelwise attention (SCA) is proposed to balance the sample distribution and improve the subsequent ROI extraction results. First, we combine the original multispectral information with handcrafted texture features to make full use of the low-level visual features of RSIs. We then design a VAE-MSGAN to generate realistic RSIs with high quality and diversity. Specifically, in the generator construct, SCA blocks are introduced to adaptively recalibrate the varying importance of different channels and spatial regions. We also build a multiscale discriminator architecture to improve the visual quality of the generated samples. Finally, we compare the ROI extraction results before and after the augmentation. Our experimental results demonstrate that the proposed method can not only improve the performance of ROI extraction but also be superior to other classical generative methods.

Gas diffusion layer (GDL), as an important transmission component of gas, electricity and liquid, is usually composed of carbon paper, which needs hydrophobic treatment before it is applied in fuel cell. In the paper, ultrasonic dispersion technique is added to the traditional method of preparing hydrophobic carbon paper, and the effect of ultrasonic dispersion on the PTFE load in hydrophobic carbon paper is studied. The theoretical study shows that the ultrasonic dispersion increases the movement of the liquid, thus improving the diffusion performance of the liquid molecules. The experimental results show that compared with the hydrophobic performance of the original carbon paper, the hydrophobic carbon paper prepared by ultrasonic method improves the hydrophobic performance by 13.24%. However, there is no obvious relationship between the PTFE content of the carbon paper treated by ultrasonic dispersion and the hydrophobicity of the carbon paper surface. In addition, ultrasonic dispersion also has a great influence on the gas permeability of hydrophobic treated carbon paper, but the effect on the surface conductivity of carbon paper is not obvious. The results can provide a guidance for the preparation of hydrophobic carbon paper for fuel cells.

With the ongoing progress in exploring novel fabrication methods, topics towards high-performance, simply fabricated organic light-emitting diodes (OLEDs) have received a great deal of attention. Brush-coating is a superior liquid phase thin film deposition technology with nearly 100% material utilization, which has remarkable potential application in depositing large-area uniform films. Here, a uniform and smooth polymer hole-injection layer and a small molecule light-emitting layer are successfully fabricated through brush-coating by controlling the wetting and dewetting processes. White phosphorescent OLEDs with blue and orange complementary colours are constructed by continuously brush-coating the hole-injection layer and small molecule light-emitting layer. The brush-coated white device possesses a peak luminance of 29 190 cd m−2 and a current efficiency of 29.3 cd A−1, which are comparable to those of the spin-coated device with the same structure. In addition, the brush-coated red, green and blue phosphorescent OLEDs exhibit excellent performance in our research with peak current efficiencies of 16.7, 30.4 and 20.9 cd A−1, respectively. These results demonstrate that the brush-coating technology is a simple and effective strategy for depositing uniform organic films and, consequently, fabricating a high-performance device. What's more, brush-coating is expected to be applied to the best-to-date, large-area, flexible or patterned OLEDs in the future.

BACKGROUND: The aim was to retrospectively analyze the ultrasonographic and clinical characteristics of focal inflammatory masses and malignant masses of salivary gland by using B-mode ultrasound (US) and contrast-enhanced ultrasound (CEUS) for differential analysis. METHODS: The features of US and CEUS were retrospectively analyzed for 19 cases of focal salivary inflammatory masses and 45 cases of malignant salivary masses. All cases were confirmed by pathohistological examination. RESULTS: On B-mode US, the incidence of expansive growth patterns of malignant salivary masses (44.4%, 20/45) was significantly higher than that of focal salivary inflammatory masses (15.8%, 3/19) (p = 0.029). The rate of lymphadenopathy surrounding salivary glands of malignant salivary masses (42.2%, 19/45) was significantly higher than that of focal salivary inflammatory masses (15.8%, 3/19) (p = 0.042). On CEUS, clear enhancement margins were more common in malignant salivary masses (44.4%, 20/45) compared to focal salivary inflammatory masses (15.8%, 3/19) (p = 0.029); Rapid washout was more common in malignant salivary masses (82.2%, 37/45) than focal salivary inflammatory masses (31.6%, 6/19) (p

BACKGROUND: Long-term survivals of patients with HBV-related hepatocellular carcinoma are limited by the high incidence of tumor recurrence after radiofrequency ablation (RFA), identification of the risk factors and understanding the patterns of recurrence can help to improve the comprehensive management of patients after RFA. Therefore, the purpose of the study is to explore the prognostic value of the age-male-albumin-bilirubin-platelets (aMAP) score in patients with early-stage HBV-related hepatocellular carcinoma (HCC) receiving RFA; investigate the risk factors and patterns of late recurrence (LR); and develop a nomogram to predict recurrence-free survival (RFS). METHODS: A retrospective review of HBV-related HCC patients who underwent primary RFA from March 2012 to December 2020 was conducted. The prognostic value of the aMAP score was evaluated in a primary cohort (n=302) and then further validated in an independent validation cohort (n=143). The optimal threshold of aMAP scores was calculated by X-tile 3.6.1 software. A prognostic nomogram was constructed from multivariate analysis and validated in an external validation cohort. RESULTS: Patients with aMAP scores ≤63.8, 63.8–67.8, and >67.8 were classified into low-, medium-, and high-recurrence risk groups, respectively. The C-index to predict LR was 0.76 (95% CI: 0.700–0.810). The high-risk group was associated with the worst RFS (HR: 5.298; 95% CI, 2.697–10.408; P

Background: Cardiovascular disease is the leading cause of death in both developed and developing countries. Di'ao Xinxuekang (DAXXK) is a pure Chinese medicine herbal preparation refined from dioscin extracted from the roots of Dioscorea panthaica Prain et Burk and Diosorea nipponica Makino. Objective: To evaluate the application of DAXXK in Cardiovascular disease. Methods: : We searched and summarized all the studies on DAXXK and Cardiovascular disease in pumend, Google, and CNKI. Results: Modern pharmacological studies have shown that DAXXK has pharmacological effects such as dilating blood vessels, lowering blood pressure and cardiac load, improving hemodynamics, lowering blood lipids and anti-platelet aggregation, and is widely used for the therapy of various kinds of cardiovascular diseases, including hypertension, atherosclerosis, coronary heart disease (CHD), angina pectoris (AP) and myocardial infarction. We provide an overview of the clinical efficacy, molecular mechanisms, safety and therapeutic potential of DAXXK in the treatment of cardiovascular disease, aiming to provide clues and evidence for clinical decision-making. Conclusion: DAXXK exerts cardiovascular protection by regulating a variety of cardiovascular disease-related signaling pathways.

Background: Myxomas are the most common primary cardiac tumors. Angiographically detectable neovascularity (ADN) of myxoma is increasingly being reported as a result of the use of coronary angiography (CAG) to detect coronary artery disease. However, the clinical significance of these findings is not fully understood. Methods: We enrolled 59 patients with cardiac myxoma who also underwent CAG between January 2013 and October 2018. Patients were followed up for a mean of 28.9 months (range 1–69 months). The clinical features, echocardiography measurements, pathological examination findings, CAG results, and outcomes during follow-up were compared between patients with ADN and patients without ADN. Results: ADN was found in 25 patients (42.4%). The arteries feeding the ADN included the right coronary artery (n=15), the left circumflex coronary artery (n=7), and both arteries (n=3). The patients with ADN had a higher proportion of eosinophils (3.2% vs. 2.2%, P=0.03) and higher low-density lipoprotein cholesterol level (2.7 mmol/L vs. 2.2 mmol/L, P=0.02). Myxoma pedicles were more likely to be located in the interatrial septum in patients with ADN (96% vs. 73.5%, P=0.02). No significant correlation was observed between the groups in clinical manifestations, atrial arrhythmia, myxoma size, cardiac chamber size, left ventricular ejection fraction, and the prevalence of complication with coronary artery disease [16% in the ADN group (n=4) vs. 20.6% in the non-ADN group (n=7), P=0.66]. However, patients with ADN tended to have a lower incidence of major adverse cardiac and cerebrovascular events on long-term follow-up (0% vs. 14.7%, P=0.07). Conclusion: CAG-detected ADN in patients with cardiac myxoma is associated with a borderline lower rate of major adverse cardiac and cerebrovascular events.

It is widely acknowledged that drivers should remain in the control loop before automated vehicles completely meet real-world operational conditions. This paper presents an ``indirect shared control'' framework for steer-by-wire vehicles, which allows the control authority to be continuously shared between the driver and automation through an weighted-input-summation method. A ``best-response'' driver steering model based on model predictive control (MPC) for indirect shared control is proposed. Unlike any conventional driver model for manual driving, this model assumes that drivers can learn and incorporate the controller strategy into their internal model for predictive path following. The analytic solution to the driver model is provided to enable off-line simulations. A driving-simulator experiment was conducted to demonstrate the advantages of the indirect shared control system in a highway lane-keeping task. The result showed that the proposed indirect shared control method was effective to improve the subjects' lane-keeping performance and reduce steering control effort. The proposed driver steering model was also validated by the experiment data, which produced a smaller prediction error than the conventional MPC driver model.

Triple-negative breast cancer (TNBC) is an aggressive and highly lethal disease. The lack of targeted therapies and poor patient outcome have fostered efforts to discover new molecular targets to treat patients with TNBC. Here, we showed that baculoviral IAP repeat containing 6 (BIRC6) is overexpressed and positively correlated with epidermal growth factor (EGF) receptor (EGFR) in TNBC cells and tissues and that BIRC6 overexpression is associated with poor patient survival. Mechanistic studies revealed that BIRC6 stability is increased by EGF-JNK signaling, which prevents ubiquitination and degradation of BIRC6 mediated by the E3 ubiquitin ligase HECTD1. BIRC6 in turn decreases SMAC expression by inducing the ubiquitin-proteasome pathway, thereby antagonizing apoptosis and promoting the proliferation, colony formation, tumorsphere formation, and tumor growth capacity of TNBC cells. Therapeutically, the PEGylated cationic lipid nanoparticle (pCLN)-assisted delivery of BIRC6 small interfering RNA (siRNA) efficiently silences BIRC6 expression in TNBC cells, thus suppressing TNBC cell growth in vitro and in vivo, and its antitumor activity is significantly superior to that of the EGFR inhibitor gefitinib. Our findings identify an important regulatory mechanism of BIRC6 overexpression and provide a potential therapeutic option for treating TNBC., Graphical abstract, TNBC is the most aggressive subtype of breast cancer, and discovery of new targeted therapies is required. Our findings show that EGF-JNK-HECTD1 signaling can drive the overexpression of BIRC6 in TNBC. Targeting BIRC6 with lipid nanoparticle-coated siRNA represents a very promising approach for treating TNBC.

Three-dimensional (3D) video contains plentiful multi-domain correlations, including spatial, temporal, and inter-view correlations. In this paper, a deep multi-domain prediction method is proposed for 3D video coding. Different from previous methods, our proposed method utilizes not only spatial and temporal correlations but also inter-view correlation to obtain a more accurate prediction, and adopts deep convolutional neural networks to effectively fuse multi-domain references. More specifically, a hierarchical prediction mechanism, which includes a spatial-temporal prediction network and a multi-domain prediction network, is designed to overcome the fusion difficulty of multi-domain reference information. Furthermore, a progressive spatial-temporal prediction network and a multi-scale multi-domain prediction network are designed to obtain the spatial-temporal prediction result and multi-domain prediction result respectively. Experimental results show that the proposed method achieves considerable bitrate saving compared with 3D-HEVC.

Background. Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes, and the levels of chemerin were associated with the severity of DR. However, there is no research on chemerin in the development of proliferative diabetic retinopathy (PDR). Therefore, our study aimed to explore the relationship between chemerin and PDR. Methods. The levels of chemerin/chemokine-like receptor (CMKLR1), proinflammatory cytokines, and vascular endothelial growth factor (VEGF) in 90 cases of PDR and nonproliferative diabetic retinopathy (NPDR) patients and in high glucose (HG) stimulated human retinal pigment epithelium cells (ARPE-19) were evaluated by ELISA. Moreover, chemerin was added into HG-induced ARPE-19 cells to assess its effect on proinflammatory cytokines and VEGF. Results. The levels of chemerin/CMKLR1 were higher in PDR patients than NPDR ones, and chemerin was positively correlated with CMKLR1 in PDR patients. Compared to NPDR, the secretions of proinflammatory cytokines and VEGF were increased in PDR patients and positively correlated with chemerin/CMKLR1. Additionally, chemerin activated CMKLR1 and aggravated HG-induced cell injury, inflammatory responses, and VEGF expressions in ARPE-19 cells. Conclusion. Our study demonstrated that chemerin/CMKLR1 axis aggravated the progression of PDR, which suggested that inhibition of chemerin might serve as a new therapeutic approach to treat PDR.