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Antimony sulfide (Sb2S3) is an appealing semiconductor as light absorber for solar cells due to its high absorption coefficient, appropriate band gap (~1.7 eV) and abundance of constituent elements. However, power conversion efficiency (PCE) of Sb2S3-based solar cells still lags much behind the theoretically predicted due to the imperfect energy level alignment at the charge transporting layer/Sb2S3 interfaces and hence severe charge recombination. Herein, we insert a high-temperature sintered magnesium (Mg)-doped tin oxide (SnO2) layer between cadmium sulfide (CdS) and fluorine doped tin oxide to form a cascaded energy level alignment and thus mitigate interfacial charge recombination. Simultaneously, the inserted Mg-doped SnO2 buffer layer facilitates the growth of the neibouring CdS film with orientation followed by Sb2S3 film with larger grains and fewer pinholes. Consequently, the resultant Sb2S3 solar cells with Mg-doped SnO2 deliver a champion PCE of 6.31%, 22.8% higher than those without a buffer layer. Our work demonstrates that deliberate absorber growth as well as efficient hole blocking upon an appropriate buffer layer is viable in obtaining solution-processed Sb2S3 solar cells with high performance.

A miniaturized radio frequency (RF) excited grid-free field emission cathode made by single-wall carbon nanotubes (SWCNTs) is suggested and studied. The $\lambda $ /4 coaxial resonant cavity is used as field-emitted electron source with length of 26.5 mm and diameter of 12.8 mm. Electrons can be pulled out by a small electrostatic field and an RF electric field without interception. The RF electric field of inner conductor surface at the open end, which pasted SWCNTs, can reach 3 MV/m when the input power is 30 W, and the field is larger than the turn-on field of SWCNTs. The results of simulation and experiment both show that the maximum emission current under input RF power of 30 W is 30 times larger than without RF excitation, which can reach 24 mA at the anode voltage of 950 V. This miniaturized RF excited grid-free field emission cathode electron source can be used as electron source, in a high repetition frequency vacuum electronic devices, e.g., terahertz (THz) devices, and X-ray tubes.

The anisotropic magnetoresistance film is an important core material for developing the magnetic sensors. Here, Ta(5)/MgO(3)/NiFe(10)/MgO(3)/Ta(3) multilayers (in nanometer) were prepared by magnetron sputtering and further applied to construct a sensor element by combining with the Wheatstone bridge. The 1/f noise of the sensor element was greatly reduced by three orders of magnitude after annealing at 400 °C for 7200 s, which was mainly due to the significant microstructural changes during the annealing. However, when the sensor element was applied to detect the magnetic signal of a magnetic code disk with 512 N–S magnetic poles, the output voltage signal of the sensor displayed a large fluctuation of ± 0.05 V. In order to reduce the voltage fluctuation, a magnetic sensor chip by using a parallelly arranged multi-path Wheatstone bridges and auto-gain compensation structure was designed, and magnetic sensor elements and the high-performance computing drive module were prepared. The output voltage fluctuation of the magnetic sensor was reduced by about 90% and approached to ± 0.005 V. These findings provide an important basis for the practical application of NiFe-based magnetic sensing film materials.

Visual odometry (VO) is one of the essential techniques in mobile robots field; an accurate VO system is of great significance for mobile robot simultaneous localization and mapping. As for traditional monocular VO systems, they work by presuming the monocular scale is 1 (scale = 1), or relying on ground truth (GT) to estimate scale. As a result, the traditional monocular VO systems estimate the pose state with big drift or cannot work on the image sequence without GT. Although some classical monocular VO systems have been proposed, they still have imperfect performance or even unable to work in some extreme scene conditions, such as scene is monotony without obvious texture information or camera large-scale displacement motion. As for learning-based VO system, it is realized by training deep neural networks in supervised or self-supervised manner to end-to-end estimate the pose state; however, the accuracy of pose estimation entirely depends on the ability of networks. Although the ability of networks can be improved by increasing the number of training data sets and optimizing the network structure, it is inevitable to encounter problems such as insufficient generalization ability and insufficient accuracy on rotational pose estimation. In this article, a monocular VO system named DL_Hybrid is proposed, which takes full advantage of DL networks used in image processing and geometric localization theory based on hybrid pose estimation methods. The DL_Hybrid VO system can estimate a six-DoF pose one-frame-by-one-frame and recover camera trajectory, and it can extract accurate key points from per-frame even in extreme scene condition, and it has good performance even in the extreme moving condition, such as camera rotation-only action or static action, also it can work well in the condition of camera large-scale displacement motion. The real scale is also accurately estimated without depending on GT, and the pose estimation method is designed based on hybrid 2d–2d and 3d–2d localization theory to make the DL_Hyrid VO system to estimate translational and rotational information with accuracy and robustness. Experimental results show that the proposed DL_Hybrid VO system has a better performance than traditional and learning-based VO systems.

Wide-band gap (WBG) mixed-halide perovskites have drawn much attention because of their excellent optoelectronic properties and the potential to be deployed in tandem solar cells. Nevertheless, the bromine incorporation inevitably leads to photoinduced phase segregation in WBG mixed-halide perovskites. Herein, potassium is used to effectively suppress photoinduced phase segregation, which is visualized with confocal photoluminescence microscopy imaging. Strikingly, the potassium passivation not only inhibits the formation of the narrow-band gap subphase but also enhances the crystallinity of the WBG mixed-halide perovskite. In addition, the potassium-passivated WBG perovskite exhibits lower defect density, longer charge carrier lifetime, and better photostability. As a result, the optimized KI (2 mol %)-passivated WBG perovskite solar cells (PSCs) deliver a champion power conversion efficiency of 18.3% with negligible hysteresis. They maintain 98% of their initial efficiency after 400 h under 100 mW·cm

To evaluate and compare the surgical outcomes and complications of the modified circumcision using disposable circumcision suture device (device group) and the conventional dorsal slit circumcision (conventional group) in children.A total of 284 patients were randomized to either device group or conventional group. All patients were preoperatively assessed and evaluated at 4 weeks after surgery. The perioperative data and postoperative outcomes were compared between the 2 groups.No statistical differences were observed in the average age and indications between the 2 groups preoperatively (P.05). Compared with the conventional group, patients in the device group were shorter mean operative time, less blood loss, lower intraoperative and postoperative pain score, faster incision healing time and a higher satisfaction rate of penile cosmetic appearance (P.01). Similarly, the incidences of complication were significantly lower in the device group than in the conventional group (4.3% vs 12.3%, P.05).The modified circumcision using disposable circumcision suture device is a simple, safe, faster, and effective procedure and may become the attractive alternative to the conventional technique for the children, with a relatively lower complication rate and better cosmetic results. With the improvement of disposable circumcision suture device, the modified circumcision using disposable circumcision suture device has the potential to be widely used in the world.

For oil fields, shooting target range, military forbidden zones and other special complex scenarios, it is not only difficult to deploy communication infrastructure because of its remote location and difficult environment, but also difficult to transmit surveillance video images to command stations in real time through centralized communication networks. Furthermore, there is a waste of bandwidth resources and the use of wireless ad hoc networks to transmit surveillance video. Therefore, we aim at designing and implementing a real-time intelligent surveillance system based on wireless ad-hoc networks in special scenes in this project. The system is supposed to capture the video frames of the monitored area and perform automatic intrusion detection. Only when an intrusion is detected, the video frame is encoded and transmitted together with the alarm message to the command center. An improved Yolov2 algorithm to achieve real time object detection on a computationally limited platform was proposed first. A wireless ad-hoc communication system was designed and implemented on the basic of the Tactical Targeting Network Technology (TTNT) Data Link to transmit surveillance video stream, control signaling and alarm message. Then the extensive experiments were conducted to evaluate the system in terms of detection accuracy and communication performance. The experiments results demonstrate the effectiveness and accuracy of the proposed system, the size of the model is only 7.6% of Yolov2 and the detection speed is increased 4 times. This design transforms long-time data transmission into burst data transmission, thus saving bandwidth resources and improving bit error rate of 96.9%. It is of great significance for the future application of artificial intelligence and machine learning in the field of communication

Introduction Data on the associations between esophageal histological lesions and risk of esophageal squamous cell carcinoma (ESCC) in general populations are limited. We aimed to investigate these associations in a large Chinese general population to inform future Chinese ESCC screening guidelines. Methods We performed endoscopic screening of 21,111 participants aged 40-69 years from 3 high-risk areas of China in 2005-2009, and followed the cohort through 2016. Cumulative incidence and mortality rates of ESCC were calculated by baseline histological diagnosis, and hazard ratios of ESCC, overall and by age and sex, were assessed using the Cox proportional hazards models. Results We identified 143 new ESCC cases (0.68%) and 62 ESCC deaths (0.29%) during a median follow-up of 8.5 years. Increasing grades of squamous dysplasia were associated with the increasing risk of ESCC incidence and mortality. The cumulative ESCC incidence rates for severe dysplasia/carcinoma in situ, moderate dysplasia (MD), and mild dysplasia were 15.5%, 4.5%, and 1.4%, respectively. Older individuals (50-69 years) had 3.1 times higher ESCC incidence than younger individuals (40-49 years), and men had 2.4 times higher ESCC incidence than women. Conclusions This study confirmed that increasing grades of squamous dysplasia are associated with increasing risk of ESCC and that severe dysplasia and carcinoma in situ require clinical treatment. This study suggests that in high-risk areas of China, patients with endoscopically worrisome MD should also receive therapy, the first screening can be postponed to 50 years, and endoscopic surveillance intervals for unremarkable MD and mild dysplasia can be lengthened to 3 and 5 years, respectively.

Organic heterostructures (OHSs) consist of organic micro/nanocrystals are of essential importance for the construction of integrated optoelectronics in the future. However, the scarcity of materials and the problem of phase separation still hinder the fine synthesis of OHSs. Herein, based on the α phase one-dimensional (1D) microrods and the β phase 2D microplates of one organic compound 3,3′-((1 E ,1′ E )-anthracene-9,10-diylbis(ethane-2,1-diyl))dibenzonitril ( m -B2BCB), we facilely synthesized the OHSs composed of these two polymorph phases, whose growth mechanism is attributed to the low lattice mismatch rate of 5.8% between (001) plane of α phase (trunk) and (010) crystal plane of β phase (branch). Significantly, the multiport in/output channels can be achieved in the OHSs, which demonstrates the structure-dependent optical signals with the different output channels in the OHSs. Therefore, our experiment exhibits the great prospect of polymorphism in OHSs, which could provide further applications on multifunctional organic integrated photonics circuits.

The purpose of this study was to assess the association of blood pressure (BP) measurements with the risk of cardiovascular disease (CVD) and examine whether central systolic BP (CSBP) predicts CVD better than brachial BP measurements (SBP and pulse pressure [PP]). Based on a cross-sectional study conducted in 2009-2010 with follow-up in 2016-2017 among 35- to 64-year-old subjects in China, we evaluated the performance of non-invasively predicted CSBP over brachial BP measurements on the first CVD events. Each BP measurement, individually and jointly with another BP measurement, was entered into the multivariate Cox proportional-hazards models, to examine the predictability of central and brachial BP measurements. Mean age of participants (n = 8710) was 50.1 years at baseline. After a median follow-up of 6.36 years, 187 CVD events occurred. CSBP was a stronger predictor for CVD than brachial BP measurements (CSBP, 1-standard deviation increment HR = 1.49, 95%CI: 1.31-1.70). With CSBP and SBP entering into models jointly, the HR for CSBP and SBP was 1.28 (1.04-1.58) and 1.22 (0.98-1.50), respectively. With CSBP and PP entering into models jointly, the HR for CSBP and PP was 1.51 (1.28-1.78) and 0.98 (0.83-1.15), respectively. For subgroup analysis, the association of CSBP with CVD was stronger than brachial BP measurements in women, those with hypertension and obesity. In the middle-aged Chinese population, noninvasively estimated CSBP may offer advantages over brachial BP measurements to predict CVD events, especially for participants with higher risk. These findings suggest prospective assessment of CSBP as a prevention and treatment target in further trials.

Nickel oxide (NiOx) as a hole-transporting layer (HTL) in perovskite solar cells (PSCs) has been studied extensively in recent years. However, unlike the solution-processed NiOx films, magnetron sputtered NiOx exhibits relatively low conductivity and imperfect band alignment with perovskites, severely limiting the device performance of PSCs. In this study, a synergistically combined strategy consisting of triple interface treatments – including post-annealing, O2-plasma, and potassium chloride treatments – is employed to modulate the optoelectronic properties of the sputtered NiOx films. Through this approach, we successfully obtained NiOx films with increased carrier density and conductivity, better energy level alignment with the perovskite absorber layer, reduced interface trap density, and improved interfacial charge extraction. PSCs using this modified sputtered NiOx as the HTL deliver a highest stabilized efficiency of 18.7%. Our result offers an alternative method to manipulate sputtered NiOx thin film properties and thereby sheds light on a manufacturing pathway to perovskite solar cells featuring sputtered NiOx HTL.

BackgroundCDC20(cell division cycle 20 homologue) plays a vital role in the cell cycle progression through targeting key substrates for destruction. Current studies have shown that CDC20 functions as an oncogene in various cancers. However, the potential correlations of CDC20 with prognosis and immune infiltrates in different cancers remain unclear.ResultCDC20 expression was higher in most cancers, compared with normal tissues, and the high expression of CDC20 was correlated with poor prognosis and a higher pathological stage. Furthermore, there were significant correlations between CDC20 dysregulation with tumor mutation burden(TMB), microsatellite instability(MSI), tumor microenvironment and tumor- and immune-related genes.ConclusionCDC20 may be used as a potential prognostic and immunotherapeuticbiomarker which affects tumor progression.

Depression is one of the strongest predictors of quality of life in patients with Parkinson’s disease (PD). Despite the high prevalence of depression, there is no clear guidance for its treatment in PD because the evidence for the efficacy of most antidepressants remains insufficient. Pramipexole, a dopamine agonist, is one of the few drugs that has proven to be clinically useful. However, the underlying mechanisms of antidepressive effects of pramipexole are still unknown. A 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model, dopamine D2 receptor (DRD2) and D3 receptor (DRD3) knockout mice were used in our study. Compared with other dopamine D2-like receptor agonists and madopar, pramipexole improved depression-like behavior and alleviate bradykinesia in an MPTP-induced mouse model of PD. Pramipexole significantly improved depression-like behavior in DRD2−/− mice but not in DRD3−/− mice. These results demonstrate that the antidepressive effect of pramipexole is mediated by DRD3 but not DRD2. Our findings highlight the need to develop novel dopamine agonists specifically targeting DRD3 for the treatment of depression in PD in the future.

Inhalable environmental pollutants induce pulmonary malfunction, which alters thoracoabdominal respiratory conditions. Traditional methods of recording pressure differences or existing machine vision analyses for detecting respiratory abnormalities are not suitable for synchronous thoracic and abdominal respiratory detections. The present study provides a new method that combines a model of thoracoabdominal localization and distribution based on respiratory physiological characteristics and a machine vision analysis on respiratory conditions in mice exposed to aqueous aerosol containing cadmium with classical symptoms. Thoracoabdominal respirations of mice were similar to male humans based on thoracic and abdominal composite respiration and the primarily presented abdominal respiration. Under environmental inhalable cadmium doses (1, 3, 5 mM CdCl2 in solution respectively atomized to be 112.41, 337.23, 562.05 μg/g Cd/Aerosol), the pathological thoracoabdominal respirations of mice showed that abdominal respiration contributed more to respiratory compensation and presented greater adaptive adjustments and more obvious fluctuations during lung injury than thoracic respiration, which suggests that toxic aerosol from a high-risk work environment quickly induces discernible respiratory clinical manifestations in occupational groups, as a warning for health, and abdominal obesity is unfavorable for male respiratory compensation. The respiratory abnormality shown in machine vision analysis was verified in pulmonary structural changes and hypoxia stress. Conclusively, the present method may be used to test the effects of aerosols on respiratory state and provides new prospects for toxicity determinations and risk evaluations of aerosols in the respiratory system in vivo.

Organic semiconductor molecules that ideally suitable for being used to achieve solid-state lasers (OSSLs) in aggregate-state cannot actually act as the efficient laser gain materials due to variet...

Inhalable environmental toxicants can induce pulmonary malfunction resulting abnormal respiratory conditions. The traditional methods currently available to detect the respiratory condition of animals rely on differential pressure transducers and signal amplifiers. In comparison, current machine vision application requires little hardware. But it is unsuitable for respiratory condition tests of experimental animals reflecting respiratory toxicities of inhalable pollutants. In this study, we establish a new automatic method of machine vision analysis using a model that has mice inhaling aqueous aerosol with different concentrations of CdCl2 (0, 1, 3, 5 mM 2 h/day) for 7 days as simulant occupational exposure of inhalable Cd and analyze respiratory conditions such as respiratory rate, rhythm index, drive index and exchange index. Additionally, the models with different degrees of lung damage in mice are further tested and verified by the concentrations of cadmium accumulated in the lungs and the analyses on pulmonary porosity, fibrosis and inflammation. Machine vision analysis can identify the abnormal respiratory conditions of mice. Respiratory rate and rhythm index increase after exposure to cadmium. In the individuals with mild lung damage, respiratory drive index and exchange index in treatment group are higher than that in the control group, and in individuals with severe lung damage, these indices are similar to that of the control group. These abnormal respiratory conditions related to variable lung damage in mice demonstrate that the respiration is synchronously influenced by inhalable Cd and respiratory compensation according to normal physiological regulation, suggesting the present method is effective.

Two low cost hexa-substituted benzene derivatives, namely HFB-OMeDPA and HPB-OMeDPA, have been successfully utilized as hole transporting materials (HTMs) for efficient perovskite solar cells (PSCs). The relationships between molecular structure, electronic properties of the semiconductor and eventually the photovoltaic performance are investigated. The planar PSCs employing HPB-OMeDPA as HTM exhibit excellent power conversion efficiencies exceeding 16% under AM 1.5G illumination conditions, which are comparable to the reference cells based on spiro-OMeTAD.

Unsupervised feature selection is an important machine learning task since the manual annotated data are dramatically expensive to obtain and therefore very limited. However, due to the existence of noise and outliers in different data samples, feature selection without the help of discriminant information embedded in the annotated data is quite challenging. To relieve these limitations, we investigate the embedding of spectral learning into a general sparse regression framework for unsupervised feature selection. Generally, the proposed general spectral sparse regression (GSSR) method handles the outlier features by learning the joint sparsity and the noisy features by preserving the local structures of data, jointly. Specifically, GSSR is conducted in two stages. First, the classic sparse dictionary learning method is used to build the bases of original data. After that, the original data are project to the basis space by learning a new representation via GSSR. In GSSR, robust loss function $$\ell _{2,r}{-}{norm}(0

Purpose The purpose of this paper is to advance a digital technology that is intended to bring about innovations on the existing textile patterns. Design/methodology/approach The pattern is deemed as a relation function between colors and positions which can be learnt by the artificial neural network (ANN). The outputs of the ANN are used for the reconstruction of the pattern and the innovation is performed by interceptors in the input/output layer. The ANN is carried out with one input layer, one output layer and several hidden layers, and the capacity of the architecture is adjusted by the scale of hidden layers to accommodate different function relations of the patterns. The training is conducted repeatedly on a sample set extracted from the pixels of the pattern image to minimize the error, and the chromatic outputs of the architecture are replaced to their origins so as to rebuild the pattern. Then, the interceptors are installed into the input and output layers to modulate the positions and the colors, and consequently the innovations are achieved on the geometric formation and color distribution of the pattern. Findings It has turned out that the precision of reconstruction is concerned with network scale, training epochs and color mode of the sample set. Four primary innovative effects including stripes, twisters, sandification and overprints have been qualified in terms of interceptors. Originality/value This study introduces ANN into textile pattern generation and provides a novel way to perform digital innovation of textile patterns.

Metal halide-based perovskite nanocrystals, as promising materials in light-emitting diodes (LEDs), have recently attracted considerable attention for their efficient charge transport properties, high color purity, and tunable bandgap over the entire visible spectral range. However, the poor stability and high surface roughness of halide-based perovskites are preventing them from wide applications in lighting and displays. Here, we report a facile method to obtain efficient and stable green-emitting perovskite light-emitting diodes (PeLEDs) by treating the surface of a perovskite film with octylamine solution. The luminescence efficiency, color purity, and light-emitting device stability were confirmed to be improved by the analysis of the morphology of the perovskite thin film and the photoelectric properties of the ligand-managed PeLEDs. The EQE of green CsPbBr3 PeLEDs increased from 7.0% to 11.1% via the surface ligand management. Therefore, the studies of this work will be promising in improving the efficiency and stability of PeLEDs. Thus, we expect these results to facilitate the research of perovskite-based light-emitting diodes for the new generation of lighting and display technologies.

The self-assembled organic microspheres of (E)-3-(4-(dip-tolylamino)phenyl)-1-(4-fluoro-2-hydroxyphenyl)prop-2-en-1-one (DTPHP) are fabricated, which serve as active WGM resonators. In addition, a dispersion relationship between the group refractive index (ng) and wavelength (λ) is revealed to demonstrate the strong light–matter interaction inside the WGM microcavity with a maximum ng to be 7.7.

Solar steam generation by direct harvesting of light irradiation has emerged as one of most efficient technologies for utilization of solar energy and production of fresh water. Herein, we report the fabrication of a novel solar steam generation system based on a blank hollow spacer fabric (BHSF) prepared by filling spaces with chitosan and coating with reduced graphene oxide on the surface. Based on its porous textile fabric structure, with excellent thermal insulation, the modified BHSF shows better performance for water transport and mechanical properties, with a compression strength of up to 733 kPa at 70% strain and low thermal conductivity (0.08 W m−1 K−1). Under solar light power of 1 kW m−2, this solar generator gives an evaporation efficiency of 86%, which is comparable to the best performance for multilayer systems that have been reported so far. More significantly, the unique hollow structure of BHSF, with an aligned big channel array (2 mm in size), which provided additional low-tortuosity pathways, endows the modified BHSF with excellent salt-resistant properties, such as evaporation in high saline solution. Such a textile-based BHSF may hold great potential for scalable manufacture of a cost-efficient solar still with excellent mechanical flexibility, physicochemical robustness and high solar energy conversion efficiency for a variety of applications, including power generation, desalination, and steam sterilization.

A physics-based 2-D analytical model is developed for AlGaN/GaN heterojunction field-effect transistor (HFET) to optimize the field-plate (FP) design for electric-field (E-field) engineering. The model reveals the impact of critical device parameters such as FP length, passivation dielectric, and dielectric thickness on the electric potential and E-field distribution in AlGaN/GaN HFET. With this model, a minimum FP length as well as the optimal dielectric thickness for different passivation dielectrics can be obtained to achieve a uniform E-field distribution and simultaneously at the minimized cost of parasitic capacitance. By taking the edge effect of both the gate and FP into account, the calculated results exhibit good agreement with numerical simulation. The developed model is of the great potential of high-voltage AlGaN/GaN HFET design for power switching applications.

White-light-emissive organic micro/nanostructures hold exotic potential applications in full-color displays, on-chip wavelength-division multiplexing, and backlights of portable display devices, but are rarely realized in organic core/shell heterostructures. Herein, through regulating the noncovalent interactions between organic semiconductor molecules, a hierarchical self-assembly approach of horizontal epitaxial-growth is demonstrated for the fine synthesis of organic core/mono-shell microwires with multicolor emission (red-green, red-blue, and green-blue) and especially organic core/double-shell microwires with radial red-green-blue (RGB) emission, whose components are dibenzo[g,p]chrysene (DgpC)-based charge-transfer (CT) complexes. In fact, the desired lattice mismatching (≈2%) and the excellent structure compatibility of these CT complexes facilitate the epitaxial-growth process for the facile synthesis of organic core/shell microwires. With the RGB-emissive substructures, these core/double-shell organic microwires are microscale white-light sources (CIE [0.34, 0.36]). Besides, the white-emissive core/double-shell microwires demonstrate the fascinating full-spectrum light transportation from 400 to 700 nm. This work indeed opens up a novel avenue for the accurate construction of organic core/shell heterostructures, which provides an attractive platform for the organic integrated optoelectronics.

Interleukin-17A (IL-17A) produced by Th17 cells, contributes to the pathogenesis of various autoimmune diseases by stimulating the release of cytokines and chemokines and its regulation. Anti-IL-17A antibody which blocks the function of IL-17A has been proved to be an effective treatment of autoimmune disease. The aim of our study was to generate a potential humanized anti-IL-17A therapeutic monoclonal antibody (mAb) through a comprehensive panel of in vitro and in vivo biological activity studies, as well as physicochemical characterization. HZD37-5, a humanized monoclonal antibody specifically recognizing N78 loci of IL-17A, binds to human and rhesus monkeys, blocks IL-17 induced signal transduction and the release of IL-6, IL-8, CXCL-1 and G-GSF. In an in vivo efficacy mouse model, HZD37-5 significantly inhibited human IL-17A induced-keratinocyte chemoattractant (KC) secretion in a dose-dependent manner. The pharmacokinetics (PK) study result of HZD37-5 in rhesus monkeys indicated that HZD37-5 had favorable PK characteristics with limited distribution (78.0–78.8 ml/kg), slow elimination (5.00–6.45 ml/day/kg), long half-life (9.1–10.7 days) and high bioavailability (103%) following a single IV or SC dose at 1.5 mg/kg. These findings provided a comprehensive preclinical characterization of HZD37-5 and supported that it may be developed as a potential therapeutic for the treatment of autoimmune diseases, including psoriasis, psoriatic arthritis, axial spondyloarthritis, etc.

Ultraviolet (UV) wireless is very suitable for local area Non-line of sight(NLOS) dedicated covert communication. Overcoming the path loss and delay spread from NLOS channel is a critical mission for the UV NLOS transmitter. In the first part of this paper, the main recent short distance line of sight (LOS) and long distance NLOS UV communication transmitters are reviewed. Next, “UV NLOS acquisition tracking pointing (ATP)” is introduced. Then, “UV high speed modulation technology”, “high-power UV source” and etc. are analyzed and summarized. The prospect of “High repetition rate high power UV pulse modulation” and “High power sub-millisecond UV pulse OFDM modulation” is put forward in the end.

Objectives Down syndrome critical region 1 (DSCR1) is associated with carcinogenesis and tumor growth in several types of malignancy. However, little is known about the role of DSCR1 in CRC progression. The present study aimed to elucidate the clinicopathological significance, prognostic, and function roles of DSCR1 in CRC. Methods Firstly, we analyzed DSCR1 expression in 58 paired CRC samples and Oncomine database. Then, we analyzed DSCR1 expression in two independent CRC cohorts (test cohort: n = 70; validation cohort: n = 58) and tested its overall survival (OS) by Kaplan-Meier survival analyses. Finally, we overexpressed DSCR1 in two CRC cell lines DLD1 and LoVo and analyzed its effect on cell cycle and senescence. Results DSCR1 expression was significantly decreased in CRC samples and associated with clinicopathologic features of CRC patients, such as tumor size, lymph node metastasis, and TNM stage. CRC patients with low expression of DSCR1 had shorter overall survival (OS). Kaplan-Meier survival analyses showed that the expression of DSCR1 was significant factor for OS in both cohorts. Multiple Cox regression analysis showed that DSCR1 expression was an independent prognostic marker for OS in test cohort. Overexpression of DSCR1 isoform 4 (DSCR1-4) increased p21, p16, p-NFAT1, and p-NFAT2, while decreased CDK2, CDK4, and Cyclin D1 in CRC cells. In addition, overexpression of DSCR1-4 prevented proliferation and colony formation, and induced senescence in vitro. Moreover, overexpression of DSCR1-4 inhibited tumor growth and tumor angiogenesis in vivo. Conclusions Our study found high expression of DSCR1 contributes to favorable prognosis of CRC patients and prevents cell cycle and proliferation of CRC cells, indicating a critical tumor suppressive role in CRC progression.

The participation of demand side resources in the distributed trading market has become an important means for countries in the world to alleviate the pressure of supply and demand during peak hours. How to make full use of the time-varying price signals in the spot market and effectively tap the demand side response potential of customers has become the key issue of the key marketing strategy research for power sales companies. Firstly, this paper constructs distributed transaction models to clarify the transaction characteristics of both parties; Then, the cost model of adjustable load participating in distributed trading market is constructed with the objective of minimizing the cost of power consumption and the cost of satisfaction reduction caused by participating in demand response regulation, and the corresponding constraints are set; Finally, based on blockchain technology and smart contract system, the optimal strategy of adjustable load participating in distributed trading market is solved. Case simulation results show that the proposed strategy can effectively achieve the goal of load reduction on the grid side, and stimulate the willingness of users to participate in demand response, which has a certain practical significance.

There are many potential information of user behavior hidden in client big data, which is necessary to accurately position the users' electricity consumption behavior. The power consumption behavior of the users in different industries has certain patterns. If the different intrinsic characteristics of the users in different industries are ignored, the energy consumption prediction will produce errors. By deeply mining the accurate information in client big data, it can effectively analyze the users' electricity consumption behavior, make the user characteristics more representative, greatly improve the utilization efficiency of equipment, and reduce energy consumption. Therefore, in order to reduce the impact of the uncertainty of users' behavior on energy consumption prediction of various industries, this paper models the energy consumption of three industries based on the analysis of users' behavior in the construction industry, transportation industry and communication industry, and verifies the accuracy and effectiveness of the model through case simulation, aiming to provide basis and reference for the next planning of various industries suggestions.

Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular solutions usually suffer two key issues: 1) only focusing on feature interactions and failing to capture the sequence influence; 2) only focusing on sequence information, but ignoring internal feature relations of each event, thus failing to extract a better event representation. In this paper, we consider a two-level structure for capturing the hierarchical information over user's event sequence: 1) learning effective feature interactions based event representation; 2) modeling the sequence representation of user's historical events. Experimental results on both industrial and public datasets clearly demonstrate that our model achieves significantly better performance compared with state-of-the-art baselines., Comment: Accepted by SIGIR2020

Nowadays, automatic optical inspection (AOI) has been widely used in advanced manufactory. In AOI area, crisscross background may influence extraction of defect features. A package, semi-finished product of textile industry, usually has cricross background. This study aims to classify four types of package defects, which are wound-in waste, spillover, cobwebs, and dirt. We use a well-known supervised attention-neural-network architecture to classify the four types of package defects effectively. In this study, we use three steps to decide the best strategies. First, we find the best location of channel attention blocks for the deep attention network. After that, we compare two image preprocessing methods to enhance the features of defect. To understand if regularize the background trend will improve the performance or not, we create two kinds of dataset, rotated and non-rotated. Our study improves traditional AOI methods. The experimental results show that the proposed procedures can extract the package defects with interlacing background efficiently.

Summary Promoting solar fuels as a viable alternative to hydrocarbons calls for technologies that couple efficiency, durability, and low cost. In this work we elucidate how hybrid organic-inorganic systems employing hybrid photocathodes (HPC) and perovskite solar cells (PSC) could eventually match these needs, enabling sustainable and clean hydrogen production. First, we demonstrate a system comprising an HPC, a PSC, and a Ru-based oxygen evolution catalyst reaching a solar-to-hydrogen (STH) efficiency above 2%. Moving from this experimental result, we elaborate a perspective for this technology by adapting the existing models to the specific case of an HPC-PSC tandem. We found two very promising scenarios: one with a 10% STH efficiency, achievable using the currently available semiconducting polymers and the widely used methylammonium lead iodide (MAPI) PSC, and the other one with a 20% STH efficiency, requiring dedicated development for water-splitting applications of recently reported high-performing organic semiconductors and narrow band-gap perovskites., Graphical abstract, Highlights • 2% STH efficiency with a hybrid photocathode/perovskite solar cell tandem system • Multi-variable optimization tool used to find the optimal parameters to maximize STH • Optimized photocathode parameters are found in order to reach the 10% STH goal • Long-term scenario with 20% STH is predicted for hybrid organic tandem systems, Chemistry; Chemical engineering; Catalysis; Electrochemistry

As a general interface for chip system testing and on-chip debugging, JTAG is facing serious security threats. By analyzing the typical JTAG attack model and security protection measures, this paper designs a secure JTAG debugging model based on Schnorr identity authentication protocol, and takes RISCV as an example to build a set of SoC prototype system to complete functional verification. Experiments show that this secure JTAG debugging model has high security, flexible implementation, and good portability. It can meet the JTAG security protection requirements in various application scenarios. The maximum clock frequency can reach 833MHZ, while the hardware overhead is only 47.93KGate.

Novelty and outlier detection are both used for anomaly detection. This paper works through the method of One-Class support vector machine (SVM) which could estimate the contour of initial observations and can be applied in the problems of anomaly detection. In this paper, the experiments on both artificial and real-world data sets are performed to demonstrate the importance of kernel and kernel parameter choice and the corresponding sensitivity of the algorithm. Due to the desire for general regulations of kernel parameter selection, some general methods of selecting the kernel bandwidth parameter of RBF kernel are therefore investigated, including median heuristic method and Bayesian kernel learning method. Then, the experiments based on these methods are conducted to observe their effect. Consequently, some new discoveries together with current issues on these methods, as well as some applicable situations of these methods, are found in this paper. Furthermore, this paper also confirms the effectiveness of RBF kernel and that the initial value of its bandwidth parameter can be set by those two methods.

At present, the cleaning robot presents an intelligent situation, which can realize map building, path planning, self-charging and so on. Taking the coverage rate of intelligent cleaning robot as the research object, real-time image is used to test and analyze the target.In this method, the collected real-time image is transformed into segmented gray scale. The target is identified by template matching, and the motion path is measured by sub-pixel edge location. Thus the coverage of the cleaning robot can be calculated. Experiments show the effectiveness of the proposed method.

A new integrated power chip carrier based on high silicon aluminum alloy for high power microwave module is proposed. The film capacitance, RDL and eutectic layer are formed on the surface of high silicon aluminum alloy substrate by the fabrication process which includes flatten, magnetron sputtering, anodizing, lithography, electroplating, and etching. The whole substrate is divided into a single integrated power chip carrier by dicing technology after metallization process on the back of substrate. The capacitances value of the film capacitance is about 7 μf/mm2, and the resistance of RDL is less than 0.15 Ω/mm. The GaAs power chip is eutectic bonded to the integrated power chip carrier, and the chip carrier is assembled into a double channel microwave module by solder welding. Then the GaAs chip, film capacitance and RDL are electrical interlinked by using Au wire bonding to complete the preparation of the microwave module. The peak power and output harmonic of channel 1# of microwave module are 9.7 W and -47.97 dBc, and the peak power and output harmonic of channel 2# of microwave module are 10.6 W and -48.51 dBc.

Improving enterprise innovation performance is key for enterprises to obtain sustainable competitiveness. With the increasingly fierce market competition of technological and product innovation, acquiring external heterogeneous knowledge of alliance enterprises becomes core to improving innovation performance. In this paper, we constructed a theoretical model to present the effect of inter-enterprise knowledge heterogeneity and alliance network governance mechanisms on enterprise innovation performance. We selected high-tech enterprises as the research object for empirical research and reached the following conclusions: (1) Inter-enterprise knowledge heterogeneity has a positive effect on exploratory and exploitative innovation performance, and (2) trust and contract have a moderating effect on the relationship between inter-enterprise knowledge heterogeneity and enterprise innovation performance.

Wireline formation testing has evolved from discrete pressure measurements, introduced in the 1950s to measuring pressure gradients and fluid contacts since the 1970s. Technology introduced in the late 1980s and onwards added interval pressure transient testing, focused sampling, and downhole fluid analysis. Thirty years later, this paper shows data examples of a recently developed formation testing platform in a wide range of environments, and applications, that change how we plan, acquire, and use formation testing. The dual-flow-line architecture of the formation testing platform is designed to systematically address shortcomings of legacy technology, enabling focused sampling in the tightest conventional formations, as well as transient testing in high mobility environments. Specialized pre-job planning software evaluates conveyance options to minimize friction and borehole contact, estimates the available flow rate, compares cleanup performance of the different inlets, and simulates transient testing responses. During the operation, the platform uses hardware embedded automation algorithms that execute routine tasks in a consistent and highly efficient manner, leaving more time for the user to focus on data quality and value of the measurements. Case studies from Mexico, Norway, and the US demonstrate specific improvements in capability and performance. Field data from Mexico shows focused sampling of gas condensate from a heterogeneous submillidarcy carbonate formation in an HP/HT well drilled with oil-based mud. Controlled downhole decompression of crude oil in the flowline at a sampling station in Norway enabled real-time measurement of its bubblepoint pressure to within 6 psi of that measured in the laboratory. Another case study integrates accurate relative asphaltene gradients into an existing reservoir fluid study to prove reservoir connectivity across a large lateral distance in a producing field. Application of the dual packer subsystem demonstrates inflation within four minutes and pure oil samples within 90 minutes on station in a 1.5-md/cp fractured basement formation. The fine pump control at a low rate enabled sampling just below reservoir pressure in Alaska and a case from the Gulf of Mexico demonstrates the real-time impact of fluid properties on the understanding of reservoir architecture and completion design. The presented examples highlight the impact of downhole automation, define the new operating envelope for formation testing in the most challenging environments, and highlight how the technology development leads to decision making on a broad reservoir scale by providing contextual answers rather than an accumulation of facts and figures.

Antireflection (AR) film is a widely used technology to enhance the performance of photovoltaic devices that require transparent electrodes in the photovoltaic industry. At present, several AR films including monolayer MgF2 or multilayered composite films, textured polydimethylsiloxane (PDMS) and porous SiO2 have been successfully applied due to their excellent properties. Nevertheless, all of the above-mentioned AR films have some minor drawbacks to overcome, for instance, the cost or thermal durability. Herein, we report a cost-effective and low-temperature method to fabricate a mesoporous aluminum oxide (meso-Al2O3) layer as the AR coating with high thermal durability, which will meet the fabrication condition of various photovoltaic devices. Briefly, the process begins at magnetron sputtering a compact Al2O3 film, which shows no AR effect, followed by a hot water treatment at 80 °C to turn the compact film into a mesoporous film with graded-index and AR effect. The application of meso-Al2O3 AR film enhances the maximum transmittance of our laboratory-used fluorine-doped tin oxide (FTO) from 84% to 89%, which is in good agreement with our theoretical simulation named graded-index approximation. Taking perovskite solar cells (PSCs) as an example, planar PSCs with meso-Al2O3 AR film deliver excellent photon conversion efficiency of 21.5%, which is higher than that of cells without meso-Al2O3 AR film (20.9%).

Background: Helicobacter pylori (H. pylori) is widely accepted to be the most important cause of gastric non-cardia adenocarcinoma (GNCA), while its role in the development of cardia gastric adenocarcinoma (CGA) is not well defined. We aimed to investigate current H. pylori infection in relation to the severity of both precancerous and cancerous lesions of the gastric cardia in an Asian population at high risk of CGA. Methods: A population-based cross-sectional study was conducted in Linzhou County, Henan Province, China. Two thousand and three (2,003) randomly selected participants with data on current H. pylori infection, assayed by 13C-UBT, and a sequence of histological diagnoses of the gastric cardia mucosa were analyzed. Results: Of 2,003 subjects, 828 (41.33%) were currently infected with H. pylori. The prevalence of current H. pylori infection increased with increasing severity of histological lesions, from 34.12% in subjects with normal gastric cardia mucosa to 52.17% in subjects with cardia high-grade intraepithelial neoplasia (CHIN)/cardia gastric adenocarcinoma (CGA) (P for trend

The multi-model image registration is widely used in medical clinical diagnosis. However, the feature descriptor pairs are hard to detect between different modalities, which is a common dilemma faced in multi-modal image registration. In this paper, we detect feature descriptor pairs in the structure representation by convolutional neural network (CNN). On the one hand, structure representation can transform different modalities into a third-type modality, and it shows the potential information which do not appear at multi-modal medical image commonly. On the other hand, the matched feature points pairs which are computed by CNN can move back from structure representation to original image. Finally, the effective feature points are matched by 2NN algorithm. Extensive experiments on group-wise registration prove that this algorithm overcome the dilemma in extracting feature descriptor pairs among the multi-modal medical images.