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Fuzzy clustering algorithms are widely applied in the field of traffic driving, aiding in the classification of driving behaviors from massive traffic data and enhancing traffic safety levels. However, classical Fuzzy C-Means (FCM) algorithms are sensitive to noise during the clustering process, leading to suboptimal performance when dealing with traffic datasets with lower accuracy. Moreover, single-kernel clustering algorithms are greatly influenced by kernel function selection. To address these issues, this paper proposes a Possibility Weighted Multi-Kernel Fuzzy Clustering Algorithm (PMWFCM). By integrating possibility-based fuzzy clustering with FCM and introducing a multi-kernel weighting mechanism, PMWFCM effectively reduces FCM’s sensitivity to outliers while resolving issues of clustering consistency in Possibilistic C-Means (PCM) algorithms, overcoming the challenges associated with kernel function selection. Validation on three different types of datasets demonstrates that the PMWFCM algorithm performs exceptionally well in terms of average accuracy, normalized information, average time, robustness, and convergence. When applied to the evaluation of driving behaviors in traffic datasets. Therefore, the improved FCM algorithm proposed in this paper can accurately and comprehensively reflect changes in traffic data, providing a solid theoretical foundation for identifying and assessing major risk types among passenger drivers.

ObjectiveIn order to improve the combined navigation accuracy of unmanned surface vehicles (USVs) by strapdown inertial navigation system (SINS) and doppler range finder (DVL), the DVL error needs to be accurately calibrated. MethodsThis paper carries out error modeling of the installation error angle, lever arm, and scale factor of the DVL, and focuses on the analysis of the impact of the lever arm error term on the combined navigation positioning in the vessels, pointing out the necessity of its calibration; proposes a DVL error calibration method based on the parameter estimation between two point sets, which treats the SINS/GNSS navigation parameters and DVL output parameters as two point sets, converting the calibration problem into an estimation problem of the difference between the two point sets, and using the Kalman filter to estimate the error parameters between the two point sets; using the SVD（singular value decomposition）-based observability analysis to quantify the observability of the filter in different motion condtions, giving the motion recommendations of the carrier during the calibration process.ResultsThe results of mathematical simulation and real ship experiments show that the global relative accuracy of the calibrated SINS/DVL algorithm can reach a voyage of 0.122%. During cornering maneuvers, the lever arm causes abrupt changes in SINS/DVL positioning. After compensating for the lever arm, the positioning errors become smoother and the overall positioning error is reduced.ConclusionThe proposed method provides a feasible way to calibrate each DVL error including the lever arm.

Abstract The recent discovery of nickelate superconductivity represents an important step toward understanding the four‐decade mastery of unconventional high‐temperature superconductivity. However, the synthesis of the infinite‐layer nickelate superconductors shows great challenges. Particularly, surface capping layers are usually unitized to facilitate the sample synthesis. This leads to an important question whether nickelate superconductors with d9 configuration and ultralow valence of Ni1+ are in metastable state and whether nickelate superconductivity can be robust? In this work, a series of redox cycling experiments are performed across the phase transition between perovskite Nd0.8Sr0.2NiO3 and infinite‐layer Nd0.8Sr0.2NiO2. The infinite‐layer Nd0.8Sr0.2NiO2 is quite robust in the redox environment and can survive the cycling experiments with unchanged crystallographic quality. However, as the cycling number goes on, the perovskite Nd0.8Sr0.2NiO3 shows structural degradation, suggesting stability of nickelate superconductivity is not restricted by the ultralow valence of Ni1+, but by the quality of its perovskite precursor. The observed robustness of infinite‐layer Nd0.8Sr0.2NiO2 up to ten redox cycles further indicates that if an ideal high‐quality perovskite precursor can be obtained, infinite‐layer nickelate superconductivity can be very stable and sustainable under environmental conditions. This work provides important implications for potential device applications for nickelate superconductors.

Summary: Background: Janus kinase (JAK) inhibition is a promising approach for treating vitiligo. We aimed to assess the efficacy and safety of upadacitinib, an oral selective JAK inhibitor, in adults with non-segmental vitiligo. Methods: This was a phase 2, multicentre, randomised, double-blind, placebo-controlled, dose-ranging study completed at 33 clinical centres in the United States, Canada, France, and Japan. Eligible patients were aged 18–65 years with non-segmental vitiligo and had a Facial Vitiligo Area Scoring Index (F-VASI) ≥0.5 and a Total Vitiligo Area Scoring Index (T-VASI) ≥5. Patients were randomly assigned (2:2:2:1:1) using an interactive response technology to receive upadacitinib 6 mg (UPA6), upadacitinib 11 mg (UPA11), upadacitinib 22 mg (UPA22), or placebo (PBO; preassigned to switch to either UPA11 or UPA22 in period 2) once daily for 24 weeks (period 1). For weeks 24–52 (period 2), patients randomly assigned to upadacitinib continued their treatment, and patients receiving PBO switched to their preassigned upadacitinib dose in a blinded fashion. The primary endpoint was the percent change from baseline in F-VASI at week 24. Efficacy was analysed in the intention-to-treat population, and safety was examined in all randomly assigned patients who received at least one dose of study drug. This study is registered with ClinicalTrials.gov, number NCT04927975. Findings: Between June 16, 2021, and June 27, 2022, 185 patients (including 115 [62%] who were female and 70 [38%] who were male) were randomly assigned to UPA6 (n = 49), UPA11 (n = 47), UPA22 (n = 43), or PBO (n = 46). At week 24, the LS mean difference versus PBO in the percent change from baseline in F-VASI was −7.60 (95% CI −22.18 to 6.97; p = 0.3037) for UPA6, −21.27 (95% CI −36.02 to −6.52; p = 0.0051) for UPA11, and −19.60 (95% CI −35.04 to −4.16; p = 0.0132) for UPA22. The LS mean difference versus PBO in the percent change from baseline in T-VASI was −7.45 (95% CI −16.86 to 1.96; p = 0.1198) for UPA6, −10.84 (95% CI −20.37 to −1.32; p = 0.0259) for UPA11 and −14.27 (95% CI −24.24 to −4.30; p = 0.0053) for UPA22. Ongoing treatment with upadacitinib induced continuous skin repigmentation over time without reaching a plateau through week 52. The rates for study drug discontinuation and serious treatment-emergent adverse events (TEAEs) were higher in the UPA22 group than in the UPA11 and UPA6 groups. Eight serious TEAEs, including one death of unknown cause and one case of infiltrating lobular breast carcinoma, were reported through 52 weeks; only two serious TEAEs (coronary artery arteriosclerosis [UPA6 (n = 1)] and non-fatal ischemic stroke [UPA11 (n = 1)]) were deemed by the investigator to have a reasonable possibility of being related to study drug. The one case of breast cancer in the UPA11 group was deemed unrelated to study drug, and the one death of unknown cause in the UPA22 group was reviewed and adjudicated and was deemed to be unrelated to study drug. The most common TEAEs were COVID-19, headache, acne, and fatigue. No new safety signals were observed. Interpretation: Upadacitinib monotherapy led to substantial repigmentation of both facial and total body vitiligo lesions and may offer an effective treatment option for adults with extensive non-segmental vitiligo. Based on these findings, upadacitinib 15 mg is being investigated in adults and adolescents with non-segmental vitiligo in an ongoing phase 3 randomised controlled trial. Funding: AbbVie Inc.

Abstract Layered two‐dimensional (2D) materials have garnered marvelous attention in diverse fields, including sensors, capacitors, nanocomposites and transistors, owing to their distinctive structural morphologies and superior physicochemical properties. Recently, layered quasi‐2D materials, especially layered bismuth oxyselenide (Bi2O2Se), are of particular interest, because of their different interlayer interactions from other layered 2D materials. On this basis, this material offers richer and more intriguing physics, including high electron mobility, sizeable bandgap, and remarkable thermal and chemical durability, rendering it an utterly prospective contender for use in advanced electronic and optoelectronic applications. Herein, this article reviews the recent advances related with Bi2O2Se. Initially, its structural characterization, band structure, and basic properties are briefly introduced. Further, the synthetic strategies for the preparation of Bi2O2Se are presented. Furthermore, the diverse applications of Bi2O2Se in the field of electronics and optoelectronics, photocatalytic, solar cells and sensing were summarized in detail. Ultimately, the challenges and future perspectives of Bi2O2Se are included.

With the development of prefabricated buildings in China, the demand for prefabricated components is also increasing. The construction schedule of prefabricated components has heterogeneity and timeliness, which makes the traditional scheduling models not applicable. In order to control the construction process and reduce costs, research is conducted on controlling the construction process of prefabricated components in prefabricated buildings. This study divides the construction process into three stages according to the construction characteristics of prefabricated buildings. The scheduling models of these three stages are established, namely assembly, production, and transportation stages scheduling models. The scheduling model of the three stages is related to each other through the duration constraints. In addition, an improved genetic algorithm is developed to solve the scheduling model of the assembly stage. Then an improved particle swarm optimization is designed to solve the scheduling model in the production and transportation stages. The results show that the minimum duration of the assembly phase was 8 days. The duration and cost of the production phase cannot be minimized at the same time. The minimum carbon emission duration and transportation cost in the transportation phase are 93.8 hours and 22516 yuan, respectively. The improved genetic algorithm tended to flatten out after nearly 180 iterations. The maximum running time of the improved particle swarm algorithm on the training set is 4.23s, the maximum hyper volume is 0.736, and the maximum anti generation distance is $2.35\times 10 ^{-3}$ . The scheduling models of different stages and corresponding solving algorithms are effective and provide technical support for the construction process control of assembly parts. The technical contribution of this study is to optimize the genetic algorithm based on weed invasion algorithm and improve the local search ability of genetic algorithm. Then, the differential evolution algorithm is used to improve the particle swarm optimization algorithm and continuously generate new particles to replace the optimal position.

Abstract Realization of highly tunable second-order nonlinear optical responses, e.g., second-harmonic generation and bulk photovoltaic effect, is critical for developing modern optical and optoelectronic devices. Recently, the van der Waals niobium oxide dihalides are discovered to exhibit unusually large second-harmonic generation. However, the physical origin and possible tunability of nonlinear optical responses in these materials remain to be unclear. In this article, we reveal that the large second-harmonic generation in NbOX 2 (X = Cl, Br, and I) may be partially contributed by the large band nesting effect in different Brillouin zone. Interestingly, the NbOCl2 can exhibit dramatically different strain-dependent bulk photovoltaic effect under different polarized light, originating from the light-polarization-dependent orbital transitions. Importantly, we achieve a reversible ferroelectric-to-antiferroelectric phase transition in NbOCl2 and a reversible ferroelectric-to-paraelectric phase transition in NbOI2 under a certain region of external pressure, accompanied by the greatly tunable nonlinear optical responses but with different microscopic mechanisms. Our study establishes the interesting external-field tunability of NbOX 2 for nonlinear optical device applications.

Ductile iron is a heterogeneous material. The presence of spherical graphite and a hard and brittle structure makes the surface of the workpiece easily form pits and crack defects under harsh grinding conditions, which seriously affects the service life and service performance of the workpiece. The new assisted grinding process based on the electroplastic effect is expected to avoid the surface defects of ductile iron. By comparing the surface roughness and microstructure of conventional grinding and electroplastic-assisted grinding, the superiority of electroplastic-assisted grinding surface quality is confirmed. Further discussion is presented on the impact of grinding parameters on the workpiece’s surface quality under the same electrical parameters. The results show that the sensitivity of surface roughness to grinding parameters from strong to weak is grinding wheel speed, feed speed and grinding depth. The optimal combination of grinding parameters is determined as a grinding wheel speed of 30 m/s, a feed speed of 0.5 m/min and a grinding depth of 10 μm.

Abstract. Background:. Transplant renal artery stenosis (TRAS) is a vascular complication after kidney transplantation associated with poor outcomes. This study aimed to analyze the efficacy and safety of low-dose aspirin for preventing TRAS. Methods:. After kidney transplantation, patients were enrolled from January 2018 to December 2020 in Henan Provincial People's Hospital. A total of 351 enrolled recipients were randomized to an aspirin group with low-dose intake of aspirin in addition to standard treatment (n = 178), or a control group with only standard treatment (n = 173). The patients was initially diagnosed as TRAS (id-TRAS) by Doppler ultrasound, and confirmed cases were diagnosed by DSA (c-TRAS). Results:. In the aspirin and control groups, 15.7% (28/178) and 22.0% (38/173) of the recipients developed id-TRAS, respectively, with no statistical difference. However, for c-TRAS, the difference of incidence and cumulative incidence was statistically significant. The incidence of c-TRAS was lower in the aspirin group compared with the control group (2.8% [5/178] vs. 11.6% [20/173], P = 0.001). Kaplan–Meier estimates and Cox regression model identified the cumulative incidence and hazard ratio (HR) of TRAS over time in two groups, showing that recipients treated with aspirin had a significantly lower risk of c-TRAS than those who were not treated (log-rank P = 0.001, HR = 0.23, 95% confidence interval [CI]: 0.09–0.62). The levels of platelet aggregation rate (P

Maize is widely cultivated and planted all over the world, which is one of the main food resources. Accurately identifying the defect of maize seeds is of great significance in both food safety and agricultural production. In recent years, methods based on deep learning have performed well in image processing, but their potential in the identification of maize seed defects has not been fully realized. Therefore, in this paper, a lightweight and effective network for maize seed defect identification is proposed. In the proposed network, the Convolutional Block Attention Module (CBAM) was integrated into the pretrained MobileNetv3 network for extracting important features in the channel and spatial domain. In this way, the network can be focused on useful feature information, and making it easier to converge. To verify the effectiveness of the proposed network, a total of 12784 images was collected, and 7 defect types were defined. Compared with other popular pretrained models, the proposed network converges with the least number of iterations and achieves the true positive rate is 93.14% and the false positive rate is 1.14%.

Abstract Proton exchange membrane fuel cells (PEMFCs) have become a major component of current clean energy technologies. Accounting for nearly half the cost of a commercial fuel cell stack, Pt‐based catalysts are the main choices for both anode and cathode in PEMFCs. However, catalytical activity and operating life of Pt‐based catalysts are still unsatisfactory. High cost and scarcity of Pt further hinder the development of PEMFCs. Constructing core‐shell structure for Pt‐based catalysts is a promising strategy to enhance the catalytic activity and reduce the cost. In this review, we overview recent advances in Pt‐based core‐shell catalysts according to catalytic reaction types involved in PEMFCs. Furthermore, we discuss the working principle of core‐shell catalysts from the perspective of coupling between core and shell. In the end, we conclude the recent progress and discuss the future developments and facing challenges.

In modern clinical medicine, the important information of red blood cells, such as shape and number, is applied to detect blood diseases. However, the automatic recognition problem of single cells and adherent cells always exists in a densely distributed medical scene, which is difficult to solve for both the traditional detection algorithms with lower recognition rates and the conventional networks with weaker feature extraction capabilities. In this paper, an automatic recognition method of adherent blood cells with dense distribution is proposed. Based on the Faster R-CNN, the balanced feature pyramid structure, deformable convolution network, and efficient pyramid split attention mechanism are adopted to automatically recognize the blood cells under the conditions of dense distribution, extrusion deformation, adhesion and overlap. In addition, the Align algorithm for region of interest also contributes to improving the accuracy of recognition results. The experimental results show that the mean average precision of cell detection is 0.895, which is 24.5% higher than that of the original network model. Compared with the one-stage mainstream networks, the presented network has a stronger feature extraction capability. The proposed method is suitable for identifying single cells and adherent cells with dense distribution in the actual medical scene.

The interface characterization is one of the important properties of molten slag, which has a significant influence on the interface phenomenon of molten slag and the reaction between slag and metal. The wettability of molten CaO–Al2O3–MgO–FeO slag on BN substrate was investigated in a wide range of temperatures from 1673 to 1773K. The FeO content was varied from 0 to 15 wt%. The contact angle was measured by the sessile drop method, the surface tension and interfacial tension were calculated by Dorsey method and Young's equation, respectively. The effects of the FeO content and temperature on the contact angle, surface tension and interfacial tension were discussed. The results indicated that the initial contact angle decreases with the increase of temperature and FeO content. And the wetting reaction between BN substrate and the selected molten slag is non-reactive wetting. The surface tension of the selected molten slag is in the range of 586–616 mN/m, and the surface tension decrease with the increase of FeO content and temperature. The value of interfacial tension between the selected molten slag and BN substrate is close to that of the surface tension, and the interfacial tension is 211–375 mN/m. The trend that the interfacial tension changes with the FeO content and temperature was the same as the trend that surface tension changes with the FeO content and temperature. Changes in the interfacial tension were correlated with modifications in the slag structure when FeO is added. The interfacial tension linearly decreases with increasing the optical basicity, which can provide a global measure of the concentrations of free oxygen ion in molten slag.

ObjectivesThere are significant differences in the composition of intestinal flora in renal transplant recipients before and after an operation, which has a great impact on the prognosis of renal transplantation. The purpose of this project is to study the effect of intestinal flora imbalance on renal transplantation.MethodsThe animal model of renal transplantation was established after intestinal flora imbalance (mice pretreated with compound antibiotics), or the animal model of renal transplantation was established after being pretreated with single antibiotics. HE, PAS, and Masson staining was used to detecting the histopathological changes of transplanted renal. The expression of inflammatory factors and infiltration of inflammatory cells of renal tissue were respectively been detected by ELISA kit and flow cytometry.ResultsAntibiotic pretreatment restored weight loss, and decreased serum creatinine level in mice after renal transplantation. The tissue staining, ELISA assay, and flow cytometry data showed that antibiotic pretreatment alleviated injury of the renal allograft, inhibited the inflammatory factors levels, and reduced inflammatory cell infiltration in mice after renal transplantation. Furthermore, single antibiotic, especially ampicillin pretreatment can also play the same role as compound antibiotics, such as restoring weight loss, decreasing serum creatinine level, alleviating renal allograft injury, inhibiting inflammatory factors levels, and reducing inflammatory cell infiltration in mice after renal transplantation.ConclusionsAntibiotic ampicillin may inhibit inflammatory cell infiltration after renal transplantation by regulating the proportion of intestinal flora in mice, to reduce renal injury and play a role in renal protection.

BackgroundTo study the clinical application of metagenomic next-generation sequencing (mNGS) in the detection of viral infections in kidney transplant recipients (KTRs) during the COVID-19 pandemic.MethodsUsing mNGS technology, 50 human fluid samples of KTRs were detected, including 20 bronchoalveolar lavage fluid (BALF) samples, 21 urine samples and 9 blood samples. The detected nucleic acid sequences were compared and analyzed with the existing viral nucleic acid sequences in the database, and the virus infection spectrum of KTRs was drawn.ResultsThe viral nucleic acids of 15 types of viruses were detected in 96.00% (48/50) of the samples, of which 11 types of viruses were in BALF (95.00%, 19/20), and the dominant viruses were torque teno virus (TTV) (65.00%; 13/20), cytomegalovirus (CMV) (45.00%; 9/20) and human alphaherpesvirus 1 (25.00%; 5/20). 12 viruses (95.24%, 20/21) were detected in the urine, and the dominant viruses were TTV (52.38%; 11/21), JC polyomavirus (52.38%; 11/21), BK polyomavirus (42.86%; 9/21), CMV (33.33%; 7/21) and human betaherpesvirus 6B (28.57%; 6/21). 7 viruses were detected in the blood (100.00%, 9/9), and the dominant virus was TTV (100.00%; 9/9). Four rare viruses were detected in BALF and urine, including WU polyomavirus, primate bocaparvovirus 1, simian virus 12, and volepox virus. Further analysis showed that TTV infection with high reads indicated a higher risk of acute rejection (P < 0.05).ConclusionsmNGS detection reveals the rich virus spectrum of infected KTRs, and improves the detection rate of rare viruses. TTV may be a new biomarker for predicting rejection.

To prevent soil pollution caused by polyethylene (PE) films in the central region of Gansu, China, liquid mulching made from cow dung (CDLM) was trailed in silage maize fields. The degradation of CDLM and PE films, soil temperature, soil organic matter content, silage maize yield and water use efficiency (WUE) were evaluated for three years (2018-2020). The degradability of CDLM has been found to be much stronger than the one of PE films, with CDLM degrading 40-60 days after sowing and finishing around 100 days. CDLM had a lower insulating impact than PE films but a higher insulating effect than non-mulching films as the control (CK); CDLM could successfully increase soil organic matter, with a total increase of 1.01% over three years. CDLM increased silage maize yield by 6.2% compared to PE films and 17.2% compared to CK. Consequently, CDLM may be an interesting alternative to PE films for enhancing silage maize yield while decreasing soil contamination.

Abstract Artificial Z‐scheme, a tandem structure with two‐step excitation process, has gained significant attention in energy production and environmental remediation. By effectively connecting and matching the band‐gaps of two different photosystems, it is significant to utilize more photons for excellent photoactivity. Herein, a novel one‐photon (same energy‐two‐photon) Z‐scheme system is constructed between rGO modified boron‐nitrogen co‐doped‐WO3, and coupled CdSe quantum dots‐(QDs). The coctalyst‐0.5%RhxCr2O3(0.5RCr) modified amount‐optimized sample 6%CdSe/1%rGO3%BN‐WO3 revealed an unprecedented visible‐light driven overall‐water‐splitting to produce ≈51 µmol h−1 g−1 H2 and 25.5 µmol h−1 g−1 O2, and it remained unchanged for 5 runs in 30 h. This superior performance is ascribed to the one‐photon Z‐scheme, which simultaneously stimulates a two photocatalysts system, and enhanced charge separation as revealed by various spectroscopy techniques. The density‐functional theory is further utilized to understand the origin of this performance enhancement. This work provides a feasible strategy for constructing an efficient one‐photon Z‐scheme for practical applications.

Graphitic carbon nitride (g-C3N4) fabricated from different precursors exhibits unique microstructures and photocatalytic performance under visible light. Herein, we synthesized five different microstructures of g-C3N4 by the thermal poly condensation method using guanidine hydrochloride, melamine, urea, dicyandiamide and thiourea as the precursors. The results indicated that g-C3N4 prepared from urea precursor (UCN) has a nanostructure, porous layered structure, large specific surface area, and high separation efficiency of photo generated hole-electron pairs, which showed the best photocatalytic activity among all of the as-prepared samples. As for the lowest cost among the above five precursors, urea is an ideal candidate material for preparing g-C3N4 photocatalyst for a huge potential of wide industrial applications. In addition, Pt or Ni were used as the co-catalyst and loaded onto the g-C3N4 surface for photocatalytic hydrogen production. In comparison with noble metal Pt co-catalyst, Ni co-catalyst is inexpensive and has a significant effect o enhancing the photocatalytic activity under visible light. Therefore, Ni exhibits a considerable prospect to replace noble metal co-catalysts in the photocatalytic reactions.

Electronic fitness function (EFF, achieved by the electrical transport properties) as a new quantity to estimate thermoelectric (TE) performance of semiconductor crystals is usually used for screening novel TE materials. In recent years, because of the high EFF values, an increasing number of two-dimensional materials have been predicted to have the potential for TE applications via high-throughput calculations. Among them, the GeS2 monolayer has many interesting physical properties and is being used for industrial applications. Hence, in this work, we systematically investigated the TE performance, including both electronic and thermal transport properties, of the GeS2 monolayer with first-principles calculations. The results show that the structure of the GeS2 monolayer at 700 K is thermally unstable, so we study its TE performance only at 300 and 500 K. As compared with other typical TE monolayers, the GeS2 monolayer exhibits excellent electronic transport properties but a relatively high lattice thermal conductivity of 5.71 W m−1 K−1 at 500 K, and thus an unsatisfactory ZT value of 0.23. Such a low ZT value indicates that it is necessary to consider not only the electron transport properties but also the thermal transport properties to screen the thermoelectric materials with excellent performance through high-throughput calculations.

Background: Several novel immune checkpoint inhibitor (ICI)-based treatments exhibited promising survival benefits for metastatic renal cell carcinoma (mRCC), yet there is no current guidance regarding the optimum first-line regimen. We performed this network analysis to compare the efficacy and safety of all available treatments for mRCC. Methods: A systematic search of literature was conducted up to April 30, 2019, and the analysis was done on a Bayesian fixed-effect model. Findings: Twenty-five randomized clinical trials (RCTs) involving 13,010 patients were included in this study. The results showed that for overall survival, pembrolizumab plus axitinib (hazard ratio [HR]: 0.53; 95% credible interval [CrI]: 0.38–0.73) and nivolumab plus ipilimumab (HR: 0.63; 95% CrI: 0.50–0.79) were significantly more effective than sunitinib, and pembrolizumab plus axitinib was probably (68%) to be the best choice. For progression-free survival, cabozantinib (HR: 0.66; 95% CrI: 0.46–0.94), pembrolizumab plus axitinib (HR: 0.69; 95% CrI: 0.57–0.84), avelumab plus axitinib (HR: 0.69; 95% CrI: 0.56–0.85), nivolumab plus ipilimumab (HR: 0.82; 95% CrI: 0.68–0.99), and atezolizumab plus bevacizumab (HR: 0.86; 95% CrI: 0.74–0.99) were statistically superior to sunitinib, and cabozantinib was likely (43%) to be the preferred options. Nivolumab plus ipilimumab (OR: 0.50; 95% CrI: 0.28–0.84), and atezolizumab plus bevacizumab (OR: 0.56; 95% CrI: 0.36–0.83) were associated with significantly lower rate of high-grade adverse events than sunitinib. Interpretation: Our findings demonstrate that pembrolizumab plus axitinib might be the best treatment for mRCC, while nivolumab plus ipilimumab has the most favorable balance between efficacy and acceptability, and may provide new guidance to make treatment decisions. Fund: This research was supported by the Henan Provincial Scientific and Technological Research Project (Grant No. 192102310036). Keywords: Renal cell carcinoma, First-line systemic therapies, Immune checkpoint inhibitor, Efficacy, Safety

Shop floor scheduling requires consideration of the dynamic, time-varying, and unpredictable natures of the manufacturing environment. A shop floor scheduling/rescheduling method based on Petri net and ant colony optimization (PN-ACO) is proposed given an abnormal event represented by machine breakdown. Because of the difficulty to schedule in the complex and changeable internal and external environment of the shop floor, an Internet-of-Things (IoT)-enabled process control method is proposed, using sensors, RFID, industrial wireless communication, automatic identification, and other technologies to perceive the shop floor field. The value of the mean relative error is 1.77, which illustrates the feasibility and efficiency of the proposed PN-ACO algorithm to solve flexible job shop scheduling problems. To represent operation sequencing information, a schedule timed transition Petri net (TTPN) is proposed which is evolved from the TTPN. On the basis of the mapping mechanism between the Petri net model and the XML, manufacturing resources become autonomous and interactive distributed intelligent manufacturing resources. The experimental results confirm that the proposed method is effective for scheduling and process control of the IoT-enabled shop floor.

This paper addresses the energy-efficient scheduling and real-time control of flexible job shop that requires rescheduling affected operations and updating the scheduling. For energy-efficient scheduling shop floor efficiently, we propose a metaheuristic algorithm called PN-ACO algorithm, which combines a timed transition Petri nets (TTPN) based representation tool and an ant colony optimization (ACO) heuristic search method. To address the real-time control problem in energy-efficient scheduling of the shop floor, we apply the Internet of Things (IoT) technology to product production to form an Internet of Manufacturing Things environment (IoMT). In the IoMT environment, there are usually many abnormal event disturbances, including machine breakdown and urgent order arrival. To quickly handle the disturbance problem of abnormal events, the distributed control system architecture is proposed, the core of which is the negotiation and cooperation between manufacturing resources based on the wireless communication network. The proposed approach is further illustrated by a case energy-efficient of scheduling for a flexible job shop through which the optimal scheduling and correct supervisory control instructions can be obtained easily and quickly. In sum, the proposed optimization algorithm obtains a good effect in engineering applications while the validity of optimization is proved.

Iris segmentation is an essential process of iris recognition. Iris segmentation plays an important role in maintaining the accuracy of iris based on recognition system by limiting the errors in the current stage. However, its performance is affected by non-ideal conditions caused by ambient light noise and user non-cooperation. The existing segmentation methods based on local features cannot find the real iris boundary under these non-ideal conditions, and the errors generated in the segmentation stage will traverse to all subsequent stages, resulting in decreased accuracy and reliability. In addition, real iris boundaries need to be divided without additional denoising costs. Aiming at the problems of existing algorithms in complex scenes and cross-device applications, an Iris segmentation algorithm based on Dense U-Net is presented in this paper. Combining Dense network with U-Net network, Iris is segmented by taking advantage of dense U-Net network, which is narrower and has fewer parameters, and taking advantage of U-Net in semantic segmentation. Dense connected path is derived from dense connected network (Dense U-Net), in which improved information and parameters are helpful to reduce the training difficulty of deep network. The final segmentation accuracy was 98. 36%. F1 is 97.07%. The experimental results prove the presented model can improve the accuracy, reduce the error rate, and assist doctors in the diagnosis of Iris Diseases effectively.

Purpose The optimum systemic therapies for advanced/metastatic renal cell carcinoma (RCC) of favourable, intermediate and poor risk have not been established. We aimed to compare and rank the effects associated with systemic therapies in the first-line setting.Methods We searched PubMed, Cochrane databases, Web of Science and ClinicalTrials.gov for randomised controlled trials (RCT) published up to February 2020 of all available treatments for advanced/metastatic RCC. Analysis was done on a Bayesian framework.Results 15 unique RCTs including 8995 patients were identified. For advanced/metastatic RCC of favourable risk, avelumab plus axitinib was associated with a significantly higher improvement in progression-free survival (PFS) than sunitinib (HR 0.57, 95% CI 0.34 to 0.96). For intermediate-risk patients, cabozantinib, nivolumab plus ipilimumab, pembrolizumab plus axitinib and avelumab plus axitinib were associated with significantly higher improvement in PFS than sunitinib (HR 0.63, 95% CI 0.44 to 0.97; HR 0.66, 95% CI 0.53 to 0.81; HR 0.58, 95% CI 0.44 to 0.80; HR 0.62, 95% CI 0.47 to 0.83, respectively); pembrolizumab plus axitinib and nivolumab plus ipilimumab were associated with significantly higher improvement in overall survival (OS) than sunitinib (HR 0.53, 95% CI 0.34 to 0.81; HR 0.66, 95% CI 0.50 to 0.87, respectively). For poor-risk patients, nivolumab plus ipilimumab and pembrolizumab plus axitinib were associated with significantly higher improvement in PFS than sunitinib (HR 0.57, 95% CI 0.43 to 0.76; HR 0.48, 95% CI 0.30 to 0.82, respectively); nivolumab plus ipilimumab and pembrolizumab plus axitinib were significantly more efficacious for OS than sunitinib (HR 0.57, 95% CI 0.39 to 0.883; HR 0.43, 95% CI 0.23 to 0.80, respectively). For OS, there were 81% and 78% probabilities that pembrolizumab plus axitinib was the best option for intermediate-risk and poor-risk patients, respectively.Conclusion Avelumab plus axitinib might be the optimum treatment for advanced/metastatic RCC of favourable risk. Pembrolizumab plus axitinib might be the optimum treatment for intermediate-risk and poor-risk patients.

Vision-assisted surface defect detection technology is shallowly applied in crack identification of assembly building components, for this reason, the study proposes a crack identification and defect detection method for assembly building components oriented to intelligent construction. An image preprocessing algorithm is designed by improving bilateral filtering, on the basis of which an image classification model is constructed using the GhostNet algorithm, and the cracks are localized and measured using the 2D pixel positioning technique. Algorithm validation showed that the processed image denoising is better, and the peak signal-tonoise ratio of the image of the proposed algorithm is improved by 15.701 % and 2.395 %, respectively, compared to other algorithms. The F1 value of the proposed model after 50 training rounds increased by 20.970 % on average compared to other models, and the detection accuracy was as high as 0.990. The actual measurements of cracks in concrete wall panels revealed that the research-proposed method has better results compared to the traditional manual measurements, and is not subject to the limitations and interferences of factors such as manual experience, and it is more effective in the recognition of crack images. Overall, the detection method proposed by the study has high accuracy and small error, can meet the needs and standards of crack detection in assembly building components, and can intelligently locate the maximum length and width coordinates of the cracks, which is of high value in the application of crack detection in assembly building components. [ABSTRACT FROM AUTHOR]

The electrocatalyst for methanol oxidation is the key to determining the performance and lifetime of direct methanol fuel cells (DMFCs). At present, the most effective and promising electrocatalysts for the methanol oxidation reaction (MOR) are Pt and platinum-based catalysts. Unfortunately, the toxicity of CO intermediates leads to rapid inactivation of the MOR catalyst, further lowering the durability of the MOR. In response to this issue, it has been found that effective screening of good oxygen evolution reaction (OER) active materials and synergistic application with Pt in the MOR can reduce the loss of activity and improve its durability. Based on this strategy, a series of Pt-based MOR catalysts (Pt/Ni, Pt/Co and Pt/NiCo) are synthesized by electrodeposition. The results indicate that the OER activity of Pt/Ni, Pt/Co, and Pt/NiCo is positively correlated with MOR activity and durability. Among the Pt-based MOR catalysts, the ultimate optimized Pt/NiCo exhibits excellent MOR performance, with a good mass activity of 495 A gPt-1, strong CV cycle durability (63.6% activity retained after 5000 cycles), and a long-term operating durability of 15 000 s in alkaline solution. [ABSTRACT FROM AUTHOR]