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Heisenberg's uncertainty principle is originally represented by the tradeoff relations between the error of measuring an observable A and the consequential disturbance to the value of another observable B with respect to a particular quantum state. Many different error-disturbance tradeoff relations have been proposed and experimentally tested in various scenarios. The error-disturbance uncertainty relations is incorporated into multiparameter estimation theory recently, but they are all the tradeoff relations between the errors of measuring two observables. Here, we derive the error-disturbance tradeoff relations for three observables A, B and C and demonstrate that the new relation is violated, while the relations derived from triple of two observables A and B, A and C and B and C directly are valid by some examples. [ABSTRACT FROM AUTHOR]

This paper introduces the development process of building cable structures in China over the past 70 years according to three stages: the initial, slow, and rapid development. It also summarizes the types of cable components and joints of building cable structures. The structural characteristics and representative projects of suspension, cable membrane, beam string (cable-supported), and cable dome structures are reviewed in this paper. Finally, the achievements and prospects of cable structures in China are discussed. [ABSTRACT FROM AUTHOR]

High demands for precision laser soldering technologies arise as digital devices move towards volume downsizing. Laser soldering is a very complicated thermodynamic chemical process, and controlling the temperature also becomes challenging. Based on experimental data, a thermodynamic model for the soldering process is developed in this study, taking into account variables like laser power, spot size, and heating duration, among others. A novel feedforward-PI control algorithm is proposed using the model which includes a target temperature curve-based feedforward algorithm to help the PI feedback control to achieve precise temperature control during the laser soldering process. Experiments and comparisons are used to demonstrate the efficacy of the suggested model and control approach. The outcomes show that the suggested model is capable of effectively describing the dynamics of laser soldering. The temperature standard deviation of the proposed control technique is shown to be lower than 55%-60% of the classic PID control approach, while the former has higher precision. [ABSTRACT FROM AUTHOR]

Dual-phase high-entropy alloys with excellent room temperature and high-temperature properties have been widely studied as potential high-temperature structural materials. However, interface weakening causes its high-temperature performance to decline at higher temperatures, severely limiting further development. In this study, a series of Al17Cr10Fe36Ni36Mo1Hfx (x = 0, 0.03, 0.15, 0.3, 0.5, and 0.8 at%) alloys were prepared to study the effect of Hf content on the microstructure and mechanical properties of the matrix alloy. The results indicate that with the addition of the Hf, the Hf-rich phase began to precipitate at the interface and inside the B2 phase in the matrix alloy. In contrast, the morphology of both the FCC and B2 phases had no noticeable change. With the increase in Hf content, the high-temperature strength and ductility of the alloy first increased and then decreased, while the room temperature performance remained almost unchanged. Benefiting from the hindrance of the Hf-rich phase to grain boundary sliding and dislocation movement during high-temperature deformation, the tensile strength, yield strength, and plasticity of the matrix alloy increased from 474 MPa, 535 MPa, and 8.7% to 816 MPa, 923 MPa, and 42.0% for the Al17Cr10Fe36Ni36Mo1Hf0.5 alloys, respectively. This work provides a new path for designing a high-entropy alloy with excellent high-temperature mechanical properties. [ABSTRACT FROM AUTHOR]

In recent years, the realm of deep learning has witnessed significant advancements, particularly in object detection algorithms. However, the unique challenges posed by remote sensing images, such as complex backgrounds, diverse target sizes, dense target distribution, and overlapping or obscuring targets, demand specialized solutions. Addressing these challenges, we introduce a novel lightweight object detection algorithm based on Yolov5s to enhance detection performance while ensuring rapid processing and broad applicability. Our primary contributions include: firstly, we implemented a new Lightweight Asymmetric Detection Head (LADH-Head), replacing the original detection head in the Yolov5s model. Secondly, we introduce a new C3CA module, incorporating the Coordinate Attention mechanism, strengthening the network's capability to extract precise location information. Thirdly, we proposed a new backbone network, replacing the C3 module in the Yolov5s backbone with a FasterConv module, enhancing the network's feature extraction capabilities. Additionally, we introduced a Content-aware Feature Reassembly (content-aware reassembly of features) (CARAFE) module to reassemble semantic similar feature points effectively, enhancing the network's detection capabilities and reducing the model parameters. Finally, we introduced a novel XIoU loss function, aiming to improve the model's convergence speed and robustness during training. Experimental results on widely used remote sensing image datasets such as DIOR, DOTA, and SIMD demonstrate the effectiveness of our proposed model. Compared to the original Yolov5s algorithm, we achieved a mean average precision (mAP) increase of 3.3%, 6.7%, and 3.2%, respectively. These findings underscore the superior performance of our proposed model in remote sensing image object detection, offering an efficient, lightweight solution for remote sensing applications. [ABSTRACT FROM AUTHOR]

The process of bundling and clustering hasno clear boundaries; hence, their analysis contains uncertainities. Thus, it is more suitable to deal withbundling and clusteringby usingfuzzy graphs. Since picture fuzzy sets (PFSs) are more accurate, compatible, and flexible compared to the other generalizations of fuzzy sets (FSs),hence, it would be more effective to present edge bundling and clustering usingpicture fuzzy line graphs (PFLGs). The aim of our study is to introduce the notions of picture fuzzy intersection graphs (PFIGs) and picture fuzzy line graphs (PFLGs). These concepts are the generalizations of fuzzy intersection graphs (FIGs) and fuzzy line graphs (FLGs), respectively. We begin our discussion by introducing some fresh and useful terminologies in the theory of fuzzy graphs such as fuzzy intersection number, picture fuzzy intersection number, etc., and we explore few interesting results related to them. Based on these concepts, first we introduce the notion of picture fuzzy intersection graphs (PFIGs) and discuss manyimportant characteristics of these graphs. Afterwards, we introduce the notion of picture fuzzy line graphs (PFLGs) and discuss their various properties. We also investigate some structural properties of our newly established fuzzy graphs usingweak isomorphism and isomorphism. Finally, we provide an outline of the applications of picture fuzzy line graphs (PFLGs) in terms of cluster-based picture fuzzy edge bundling (CBPFEB) and the picture fuzzy c-mean algorithm. Since asymmetrical clusters ensure that the databases remain identical across the clusters, our study is deeply related to symmety. [ABSTRACT FROM AUTHOR]

A limited feasible region restricts individuals from evolving optionally and makes it more difficult to solve constrained optimization problems. In order to overcome difficulties such as introducing initial feasible solutions, a novel algorithm called the successive approximation genetic algorithm (SAGA) is proposed; (a) the simple genetic algorithm (SGA) is the main frame; (b) a self-adaptive penalty function is considered and the penalty factor is adjusted automatically by the proportion of feasible and infeasible solutions; (c) a generation-by-generation approach and a three-stages evolution are introduced; and (d) dynamically enlarging and reducing the tolerance error of the constraint violation makes it much easier to generate initial feasible solutions. Then, ten benchmarks and an engineering problem were adopted to evaluate the SAGA in detail. It was compared with the improved dual-population genetic algorithm (IDPGA) and eight other algorithms, and the results show that SAGA finds the optimum in 5 s for an equality constraint and 1 s for an inequality constraint. The largest constraint violation can be accurate to at least three decimal fractions for most problems. SAGA obtains a better value, of 1.3398, than the eight other algorithms for the engineering problem. In conclusion, SAGA is very suitable for solving nonlinear optimization problems with a single constraint, accompanied by more accurate solutions, but it takes a longer time. In reality, SAGA searched for a better solution along the bound after several iterations and converged to an acceptable solution in early evolution. It is critical to improve the running speed of SAGA in the future. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to define multiple alternative q-harmonic numbers, H n k ; q and multi-generalized q-hyperharmonic numbers of order r, H n r k ; q by using q-multiple zeta star values (q-MZSVs). We obtain some finite sum identities and give some applications of them for certain combinations of q-multiple polylogarithms L i q ; k 1 , k 2 , ... , k d t 1 , t 2 , ... , t d with the help of generating functions. Additionally, one of the applications is the sum involving q-Stirling numbers and q-Bernoulli numbers. [ABSTRACT FROM AUTHOR]

For lightweight steel frame structures consisting of steel H-beams and cold-formed steel columns filled with concrete, seismic performance comparison tests and numerical simulation analyses were performed for bare and infilled frames. The effects of the lightweight wall panels, the axial compression ratio and the wall thickness of the steel sections of the columns on the seismic properties of the structure were investigated. The failure of the bare frame was concentrated in the weld fractures at the beam-column joints. When the wall panels were embedded in the frame, the damage was concentrated at the corners and edges of the wall panels and the connectors. The wall panels significantly improved the initial stiffness of the frame, early energy dissipation and resistance, and the wall panel energy dissipation rate was initially as great as 91%. As the axial compression ratio increased, the resistance of the structure significantly decreased. Under monotonic loading, the resistance on the structure with an axial compression ratio of 0.4 was reduced by nearly 44% compared to the structure without axial compression. Increasing the wall thickness of the steel sections of the columns increased the load-bearing capacity of the structure, but the increase diminished with increasing wall thickness. [ABSTRACT FROM AUTHOR]

A novel strategy for developing a hypochlorite fluorescent probe by exploiting the ortho-vinylhydropyridine-assisted amido-to-nitroso oxidation reaction is presented. The designed 1,8-naphthalimide-based derivative (1a) is employed to monitor and identify trace amounts of ClO− with the advantage of fast response (within 1.2 seconds, LOD = 36.0 nM), good selectivity, and high sensitivity in solution and living cells. [ABSTRACT FROM AUTHOR]

The study of corroded metal materials in building structures is the basis for analyzing and evaluating the residual bearing capacities of existing structures. In this study, the corrosion behaviors and residual properties of two types of low-alloy steel and a 6061-T6 aluminum alloy were investigated under different corrosion times in an acetic acid spray environment. Scanning electron microscopy (SEM) and three-dimensional (3D) laser scanning were performed. Uniaxial tensile tests were conducted on the three metal materials with different corrosion levels. The test results showed that the corrosion rate of the aluminum alloy increased with corrosion time, and the corrosion rates of the low-alloy steels decreased with corrosion time. The pitting of the low-alloy steels was shallow and wide; the pitting of the 6061-T6 aluminum alloy was narrow and deep. Characteristic parameters are proposed for the pitting morphologies of the low-alloy steels. The corrosion depths of the pitting were more inclined toward a generalized extreme value distribution. Simplified models and evaluation indexes were defined for the stress-strain relationships of the three materials. The two types of low-alloy steel were reduced to 60% of their original engineering strength, and the engineering strength of the aluminum alloy was reduced to 85%. Methods are proposed for evaluating the residual mechanical properties of different structural materials with different corrosion behaviors. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) robot microwave imaging systems have attracted comprehensive attention. Compared with visible light and infrared imaging systems, microwave imaging is not susceptible to weather. Active microwave imaging systems have been realized in UAV robots. However, the scattering signals of geographical objects from satellite transmitting systems received by UAV robots to process imaging is studied rarely, which reduces the need of load weight for the UAV robot. In this paper, a multi-path scattering model of vegetation on the earth surface is proposed, and then the microwave imaging algorithm is introduced to reconstruct the images from the UAV robot receiving the scattering data based on the multi-path model. In image processing, it is assumed that the orbit altitude of a transmitter loaded on the satellite remains unchanged, and the receiver loaded UAV robot obtains the reflective information from ground vegetation with different zenith angles. The imaging results show that the angle change has an impact on the imaging resolution. The combination of electromagnetic scattering model and image processing method contributes to understanding the image results and the multi-path scattering mechanisms of vegetation, which provide a reference for the research and development of microwave imaging systems of UAV robot networking using satellite transmitting signals. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) ship detection has been the focus of many previous studies. Traditional SAR ship detectors face challenges in complex environments due to the limitations of manual feature extraction. With the rise of deep learning (DL) techniques, SAR ship detection based on convolutional neural networks (CNNs) has achieved significant achievements. However, research on CNN-based SAR ship detection has mainly focused on improving detection accuracy, and relatively little research has been conducted on reducing computational complexity. Therefore, this paper proposes a lightweight detector, LssDet, for SAR ship detection. LssDet uses Shufflenet v2, YOLOX PAFPN and YOLOX Decopuled Head as the baseline networks, improving based on the cross sidelobe attention (CSAT) module, the lightweight path aggregation feature pyramid network (L-PAFPN) module and the Focus module. Specifically, the CSAT module is an attention mechanism that enhances the model's attention to the cross sidelobe region and models the long-range dependence between the channel and spatial information. The L-PAFPN module is a lightweight feature fusion network that achieves excellent performance with little computational effort and a low parametric count. The Focus module is a low-loss feature extraction structure. Experiments showed that on the Sar ship detection dataset(SSDD), LssDet's computational cost was 2.60 GFlops, the model's volume was 2.25 M and A P @ [ 0.5 : 0.95 ] was 68.1%. On the Large-scale SAR ship detection dataset-v1.0 (LS-SSDD-v1.0), LssDet's computational cost was 4.49 GFlops, the model's volume was 2.25 M and A P @ [ 0.5 : 0.95 ] was 27.8%. Compared to the baseline network, LssDet had a 3.6% improvement in A P @ [ 0.5 : 0.95 ] on the SSDD, and LssDet had a 1.5% improvement in A P @ [ 0.5 : 0.95 ] on the LS-SSDD-v1.0. At the same time, LssDet reduced Floating-point operations per second (Flops) by 7.1% and Paraments (Params) by 23.2%. Extensive experiments showed that LssDet achieves excellent detection results with minimal computational complexity. Furthermore, we investigated the effectiveness of the proposed module through ablation experiments. [ABSTRACT FROM AUTHOR]

This study was to investigate whether miR-193a-5p and ZFP57 are involved in the radioresistance of pancreatic cancer and to explore its working mechanism. Pancreatic cancer tissues were harvested from patients who achieved CR (complete remission) and PR (partial remission) and those who achieved PD (progressive disease) and SD (stable disease). The mRNA and protein expressions of ZFP57 and miR-193a-5p were determined by RT-qPCR and WB (Western blot), respectively. For in vitro experiments, the parental BxPC-3 cell line was irradiated by X-ray at a total dose of 40 Gy to induce the irradiation-resistant subtype BxPC-3-RR. ZFP57 was downregulated in radioresistant pancreatic cancer cells. The results of dual-luciferase reporter gene assay, RNA pull-down assay, RT-qPCR, and WB confirmed that miR-193a-5p targeted ZFP57 and inhibited ZFP57 expression. The MTT assay and the colony formation assay showed that the radioresistant pancreatic cancer cells had higher viability and survival fraction. The results of WB indicated that in the radioresistant pancreatic cancer cells, the cyclin D1, Bax, CDk4, cleaved caspase-3, Bcl-2, and γ-H2AX proteins were upregulated to varying degrees. The results of the in vitro nude mouse experiment were consistent with those of in vivo experiments. According to the cell transfection and salvage experiments, miR-193a-5p down regulated ZFP57 after radiotherapy. As a result, the Wnt pathway was activated, which further induced radioresistance of pancreatic cancer cells. Our experiments showed that the miR-193a-5p/ZFP57/Wnt pathway mediated the radioresistance of pancreatic cancer cells, providing novel clues for the treatment of pancreatic cancer. [ABSTRACT FROM AUTHOR]

Einstein-Podolsky-Rosen steering is a kind of powerful nonlocal quantum resource in quantum information processing such as quantum cryptography and quantum communication. Many criteria have been proposed in the past few years to detect steerability, both analytically and numerically, for bipartite quantum systems. We propose effective criteria for tripartite steerability and genuine tripartite steerability of three-qubit quantum states by establishing connections between the tripartite steerability (resp. genuine tripartite steerability) and the tripartite entanglement (resp. genuine tripartite entanglement) of certain corresponding quantum states. From these connections, tripartite steerability and genuine tripartite steerability can be detected without using any steering inequalities. The "complex cost" of determining tripartite steering and genuine tripartite steering can be reduced by detecting the entanglement of the newly constructed states in the experiment. Detailed examples are given to illustrate the power of our criteria in detecting the (genuine) tripartite steerability of tripartite states. [ABSTRACT FROM AUTHOR]

Product failure resulting from sourcing supplier’s defective component has compelled a brand owner to enhance quality management, especially when the supplier has informational advantage. In this article, we examine a brand owner’s problem of screening a certain supplier’s inherent quality level with an attempt to induce supply chain partners’ quality efforts using the warranty contract based on information acquired from inspection technology. A supplier’s inherent quality level is herein determined by the private information held by the supplier and is typically characterized as an uncertain variable. The optimal warranty contracts and the expected profits of the brand owner and the supplier are derived from four different scenarios under the framework of uncertainty theory and principal–agent theory. We find that under the condition of pure double moral hazard or pure adverse selection, the first-best outcomes can be achieved without incurring agency cost under the designed contract. However, double moral hazard combined with adverse selection often leads to underinvestment in quality efforts as the supplier can shirk by misreporting her type. Consequently, we present the menu of warranty contracts to screen the supplier’s private information. Finally, we provide empirical managerial recommendations on mitigating potential adverse impacts caused by information asymmetry, supported with numerical investigations. [ABSTRACT FROM AUTHOR]

• All-in-one treatment of radiocesium under strongly acidic conditions with low energy consumption and high safety. • Simultaneous adsorption and immobilization of radiocesium by ultra-stable inorganic solid acid materials. • Excellent 137Cs removal ability in actual 137Cs liquid waste generated during industrial production. • The Cs+ removal mechanism and structure-function relationship have been elucidated. Capture and immobilization of 137Cs is urgent for radioactive contamination remediation and spent fuel treatment. Herein, an effective all-in-one treatment method to simultaneously adsorb and immobilize Cs+ without high-temperature treatment is proposed. According to the strategy of incorporating high-valency metal ions into molybdates to increase the material stability and affinity towards radionuclides, layered H M MoO 6 · n H 2 O (M = Ta (1), Nb (2)) are prepared. Both materials exhibit excellent acid resistance (even 15 mol/L HNO 3). They maintain remarkable adsorption capacity for Cs+ in 1 mol/L HNO 3 solutions and can selectively capture Cs+ under excessive competitive ions. Furthermore, they show successful cleanup for actual 137Cs-liquid-wastes generated during industrial production. In particular, adsorbed Cs+ can be firmly immobilized in interlayer spaces of materials due to the highly stable anionic framework. The removal mechanism is attributed to ion exchange between Cs+ and interlayer H+ by multiple characterizations. Study of the structure-function relationship shows that the occurrence of Cs+ ion exchange is closely related to plate-like layered structure. This work develops an efficient all-in-one treatment method for capturing and immobilizing radiocesium by ultra-stable inorganic solid acid materials with low energy consumption and high safety for radionuclide remediation. [Display omitted] [ABSTRACT FROM AUTHOR]

Environmental pH plays an irreplaceable role in both cellular processes and production, and anomalous pH changes within cells may lead to various diseases. To tackle this issue, we designed and synthesized the novel low-cytotoxicity fluorescent probe called NAP-MP. The probe incorporates 1,8-naphthalimide as the fluorescence emitter, 1-methylpiperazine as the pH-sensitive moiety, and utilizes 3-aminopropyltriethoxysilane to improve its biocompatibility. The fluorescence of NAP-MP inhibits the photoinduced electron transfer (PET) process with the protonation of 1-methylpiperazine, resulting in the enhancement of fluorescence intensity. Density functional theory calculations have also confirmed the fluorescence mechanism. The probe demonstrates high selectivity, photostability and recyclability. The hydrogel prepared by the probe can detect different concentrations of ammonia in the air. In addition, due to its low toxicity and good biocompatibility, this probe has been successfully employed to observe pH changes in living HeLa cells. Overall, the development of this probe offers significant potential in the field of pH sensing, allowing for precise monitoring of pH levels in both environmental and biological systems. [Display omitted] • NAP-MP demonstrates excellent linear pH changes within the range of 6–8. • NAP-MP has excellent selectivity, photostability, and recyclability. • NAP-MP has low toxicity and good biocompatibility, which can be used to observe pH changes in living HeLa cells. • NAP-MP hydrogel can be utilized to the detection of environmental ammonia with a smartphone scanning application. [ABSTRACT FROM AUTHOR]

Temozolomide (TMZ), an oral alkylating agent, is the widely used first-line chemotherapeutic reagent for glioma in clinical practice. However, TMZ-induced autophagy is another cellular process favoring glioma cell survival. This study aimed to explore whether hispidulin can facilitate TMZ-induced cell death of glioma. The MTT assay showed that coadministration with hispidulin and TMZ could significantly decrease the viability of glioma U87MG cells. Meanwhile, hispidulin administration was also observed to promote TMZ-induced apoptosis. Furthermore, additional hispidulin treatment further elevated TMZ-induced expression of Bax, cleaved-caspase-9, and cleaved-caspase-3 protein but decreased Bcl-2 protein expression in U87MG cells. We also observed that hispidulin suppressed TMZ-induced autophagy to promote apoptosis, as showed by decreased AVOs and LC3B-I/II protein expression. These results collectively suggested that the combination of hispidulin and TMZ could improve the antitumor efficiency of TMZ against malignant gliomas. [ABSTRACT FROM AUTHOR]

Idiopathic interstitial pneumonia (IIP) is a group of progressive lower respiratory tract diseases of unknown origin characterized by diffuse alveolitis and alveolar structural disorders leading to pulmonary fibrillation and hypertension, pulmonary heart disease, and right heart failure due to pulmonary fibrosis, and more than half of them die from respiratory failure. To address these problems of overly complex prediction methods and large data sets involved in the prediction process of interstitial pneumonia, this paper proposes a prediction model for interstitial pneumonia which is based on the Gaussian Parsimonious Bayes algorithm. Three usual tests of pneumonia, specifically from various patients, were collected as the sample set. These samples are divided into training and testing sets. Additionally, a cross-validation strategy was used to avoid the overfitting problem. The results showed that the prediction model based on the Gaussian Parsimonious Bayes algorithm predicted 92% accuracy on the test set, and the Parsimonious Bayes method could directly predict the final detection of interstitial pneumonia based on the usual pneumonia test pneumonia. In addition, it was found that the closer the data distribution of the sample set was to a normal distribution, the higher the prediction accuracy was, and then, after excluding pneumonia from the test below 60 points, the prediction accuracy reached 96%. [ABSTRACT FROM AUTHOR]

In this study, ferric-loaded magnetic burley tobacco stem biochar (MBTS) was synthesized via pyrolysis to improve the removal of Cr(VI). The results showed that MBTS had an adsorption capacity of 54.92 mg Cr(VI)/g, which was about 14 times higher than raw burley tobacco stem biochar (i.e., 3.84 mg/g). According to the findings obtained, a three-step mechanism of Cr(VI) removal by MBTS was further put forward, i.e., (1) Cr(VI) exchanged with hydroxyl groups on MBTS, (2) the reduction in Cr(VI) to Cr(III) mediated by oxygen-containing groups, and (3) the chelation of produced Cr(III) with the amino groups on MBTS. FTIR spectra further revealed that C-N, C-H, and C=C groups played an important role in Cr(VI) removal. Furthermore, the adsorption equilibrium and kinetics of Cr(VI) on MBTS could better be described by the Langmuir equation and pseudo-second-order rate equation. This study clearly demonstrated that ferric-loaded biochar derived from burley tobacco stems could serve as a cost-effective magnetic adsorbent for the high-efficiency removal of soluble Cr(VI) from wastewater. Tobacco stem-adsorbed Cr(VI) realized a green path for treating waste by waste. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) carsharing operation is facing major challenge to balance the increasing user demand with insufficient vehicle availability and station capacity. Previous researchers mainly focus on reallocating EVs in limited stations and discrete periods through operator-oriented strategies, while containing scant study of dynamic pricing scheme that can benefit supply-demand balance and service profitability in continuous operation periods. Therefore, this paper proposes a multistage simulation-optimization-integrated methodology framework for adaptively incentivizing users based on dynamic price subsidy (DPS). In stage I, Simulation of Urban Mobility (SUMO) is used to determine the real-time supply-demand distributions from user historical data. In stage II, a novel user-oriented reallocation optimization model is established to maximize the operation profit based on the obtained SUMO results. To obtian feasibile solutions, an improved immune genetic algorithm is developed to effectively solve the model. The real-world case study in Shanghai shows that, compared with other benchmark methods, the proposed methodology can significantly increase the daily profit from 78981 RMB to 89506 RMB and improve the system balance from 78.1 % to 94.5 %. Sensitivity analysis and cost-benefit analysis show that the user-oriented DPS can reduce operation cost and order waiting time, while promoting EV utilization within different user populations. • A novel user-oriented EV carsharing reallocation strategy based on dynamic price subsidy (DPS) is proposed. • A multistage simulation-optimization-integrated methodology framework is established to effectively perform user-oriented reallocation and obtain real-time supply-demand distributions. • Real-world case study shows that daily maximum profit has improved to 89506 RMB and system balance has increased up to 94.5 % under DPS. • Cost-benefit analysis shows that the proposed DPS can reduce cost and order waiting time, while promoting EV utilization. • Feasible implications are given to relevant carsharing stakeholders. [ABSTRACT FROM AUTHOR]

Roll-to-roll (R2R) printing systems provide a continuous process of thin, flexible material (called web) through printing cylinders, where the required patterns are printed on the web. Tension fluctuation caused by the upstream register control quantity may lead to the downstream register errors. Thus, it is a challenge to develop a register control algorithm to remove the couplings among the angular velocity, tension fluctuation, and register error. In this article, the register error is defined as the marks position misalignment between the first and the current printing unit. Based on the definition, a mathematical model of registration is derived. Based on the model, a fully decoupled proportional-derivative (FDPD) control algorithm is proposed to completely remove the coupling between the upstream register control quantity and the downstream register error. Simulations and experiments are carried out to demonstrate the effectiveness of the proposed control algorithm. Compared with the other compensation control methods, FDPD is a complete decoupling control method, which can control the register errors of all downstream printing units (more than seven printing units) within $\pm 0.05$ mm, even if the upstream printing unit has a 3 mm register error. Decoupling formula included in the FDPD control is a first-order compensation formula, which is easy to implement in the actual industry. Furthermore, the proposed FDPD can deal with the situation where two adjacent gravure cylinders have different web lengths, which is not taken into account by other control methods. [ABSTRACT FROM AUTHOR]

Due to various complex environmental factors and parking scenes, there are more stringent requirements for automatic parking than the manual one. The existing auto-parking technology is based on space or plane dimension, where the former usually ignores the ground parking spot lines which may cause parking at a wrong position, while the latter often costs a lot of time in object classification which may decreases the algorithm applicability. In this paper, we propose a Generative Parking Spot Detection algorithm which uses a multi-clue recovery model to reconstruct parking spots. In the proposed method, we firstly dismantle the parking spot geometrically for marking the location of its corresponding corners and then use a micro-target recognition network to find corners from the ground image taken by car cameras. After these, we use the multi-clue model to correct the fully pairing map so that the reliable true parking spot can be recovered correctly. The proposed algorithm is compared with several existing algorithms, and the experimental result shows that it has a higher accuracy than others which can reach more than 80% in most test cases. [ABSTRACT FROM AUTHOR]

The purpose of this research is to introduce a Jungck–S iterative method with m , h 1 , h 2 –convexity and hence unify different comparable iterative schemes existing in the literature. A Jungck–S orbit is constructed, and escape radius is derived with our scheme. A new escape radius is also obtained for generating the fractals. Julia and Mandelbrot set are visualized with the help of proposed algorithms based on our iterative scheme. Moreover, we present some complex graphs of Julia and Mandelbrot sets using the derived orbit and discuss their nature in detail. [ABSTRACT FROM AUTHOR]

Collision accidents of construction vehicles frequently occur during the construction of building projects. It is difficult to warn of collision risk efficiently by using the safety control methods of on-site inspection and viewing surveillance video. Therefore, a novel collision risk warning model for construction vehicles is proposed in this paper. The model comprises a state awareness module and a collision risk assessment module. In the state awareness module, the YOLOv7 algorithm is used to identify and locate construction vehicles. The DeepSORT algorithm is used for the real-time tracking of construction vehicles. Finally, the state awareness module obtains a wealth of sensing information and provides it to the collision risk assessment module. In the collision risk assessment module, the speed assessment method and the minimum safety distance assessment method of construction vehicles are innovatively proposed and compiled. In the speed assessment method, the speed of construction vehicles is calculated and speeding warnings are performed using the transformation matrix between latitude and longitude coordinates and image pixel coordinates. In the minimum safety distance assessment method, the original surveillance picture is converted into a bird's eye view (BEV) of the world coordinate system through inverse perspective mapping (IPM). Then the distance of all construction vehicles is traversed, and the visual warning of the minimum safe distance is provided. The effectiveness and robustness of this collision risk warning model were verified by taking three practical projects in different construction stages as examples. The research results show that the mean average precision (mAP@0.5:0.95) of the construction vehicles collision risk warning model can reach 89.10%, and it has a good tracking effect and an efficient collision risk warning strategy. [ABSTRACT FROM AUTHOR]

Dynamic surface control (DSC) is a recognized nonlinear control approach for high-order systems. However, as the complexity of the system increases and the first-order filter (FOF) is introduced, there exists a singularity problem, i.e., the control input will reach infinity. This limits the application of the DSC algorithm to a class of real-world systems with complex dynamics. To address the problem of singularity, we present a novel DSC approach called nonsingular dynamic surface control (NDSC), which completely avoids the singularity problem and significantly improves the overall control performance. NDSC includes a nonsingular hypersurface, which is constructed by the error between system states and virtual control inputs. Then the nonsingular hypersurface will be applied to derive the corresponding control law with the aid of the DSC approach to ensure the output of the system can track arbitrary desired trajectories. NDSC has the following novel features: (1) finite time asymptotic stabilization can be guaranteed; (2) the performance of NDSC is insensitive to the FOF's parameter variation once the maximum tracking error of FOF is bounded, which significantly reduces reliance on the control sampling frequency. We thoroughly evaluate the proposed NDSC algorithm in an unmanned aerial vehicle (UAV) system with an underactuated nature. Finally, the simulation results illustrate and highlight the effectiveness and superiority of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This study is aiming to propose a framework integrating new criteria system, rough-fuzzy best-worst method (BWM) and rough-fuzzy data envelopment analysis (DEA) for evaluation and selection of sustainable hydrogen production technologies (HPTs) with hybrid types of sustainability indicators (i.e. quantitative and qualitative) and hybrid decision uncertainties (i.e. intrapersonal linguistic vagueness and interpersonal preference randomness). The rough-fuzzy BWM is presented to determine the relative weights of sustainability criteria and the rough-fuzzy DEA is proposed for prioritizing the alternative HPTs with hybrid types of performance data (including crisp number, interval number and group linguistic terms). Such integration combines the collaborative capability of rough-fuzzy number in fully manipulating hybrid uncertainties, the merits of BWM in quickly searching optimal weights and the advantages of DEA in effectively obtaining efficiency with multiscale input and output data. The application of the proposed approach to five typical HPTs with 14 hybrid uncertain sustainability indicators show that the wind-based electrolysis has the most sustainability priority (0.480) for hydrogen production compared with coal gasification (0.035), steam methane reforming (0.056), biomass gasification (0.246) and photovoltaic-based electrolysis (0.182). Moreover, the comparisons with other methods demonstrate the validity and effectiveness of the proposed approach. Image 1 • New sustainability criteria are applied to assess hydrogen production technologies. • A rough-fuzzy best-worst method is introduced to determine criteria's weights. • A rough-fuzzy data envelopment analysis method is developed for alternative ranking. • Hybrid information and uncertainties are fully manipulated by rough-fuzzy approaches. • Wind-based electrolysis technology is prioritized as the most sustainable one. [ABSTRACT FROM AUTHOR]

The purpose of this research is to introduce a Jungck–S iterative method with m , h 1 , h 2 –convexity and hence unify different comparable iterative schemes existing in the literature. A Jungck–S orbit is constructed, and escape radius is derived with our scheme. A new escape radius is also obtained for generating the fractals. Julia and Mandelbrot set are visualized with the help of proposed algorithms based on our iterative scheme. Moreover, we present some complex graphs of Julia and Mandelbrot sets using the derived orbit and discuss their nature in detail. [ABSTRACT FROM AUTHOR]

• Three compression tests were conducted on corner-supported modular steel sway frames (CMSFs) with rotary inter-modular connections (IMCs). • An experimentally validated finite element model (FEM) was developed, and 77 frames were analyzed to determine the effect of various parameters on the compressive resistance, initial stiffness, and ductility of CMSFs. • Using semi-rigid and pinned theoretical models, conservative estimates of the buckling load for sub-assembled CMSFs have been computed considering the member stiffness and the rotary IMCs. Corner-supported modular steel sway frames (CMSFs) with rotary inter-modular connections (IMCs) differed from traditional frames regarding their column discontinuities, beam groupings, and unique intra- and inter-modular connections, necessitating the investigation into their compressive performance to guarantee their safe and reliable application. This study investigated the compressive behavior of CMSFs with rotary IMCs using experimental tests, numerical modeling, and theoretical analysis. Three compression tests were conducted on sub-assembled CMSFs, considering varying floor and ceiling beam stiffnesses. The results showed that all frames experienced lateral sway, with upper columns at lower regions undergoing inward or outward elastic and plastic local buckling. RS1 (RS2) demonstrated 12 % (3 %) higher strength than RS3, and stiffness increased by 2 % for RS1 compared to RS3. Pre-and post-ultimate ductility of RS3 was 3 % (13 %) and 20 % (37 %) greater than RS1 (RS2), indicating that increased rigidity with thicker beams enhanced strength and stiffness but resulted in reduced CMSFs' ductility. A finite element model (FEM) was generated, and its accuracy was verified using experimental load-shortening and failure outcomes, revealing an average prediction error of 0.3 %, 9.1 %, and 8.5 % for compressive resistance, stiffness, and ductility index, respectively. Based on validated FEMs, a parametric study was conducted on 77 CMSFs to investigate the effects of varying beam and column sizes, lengths, beam gaps, and connecting plate thicknesses on compressive resistance, stiffness, and pre-and post-ultimate ductilities. Increasing column and beam sizes from 150 to 200 mm and thicknesses from 6 to 8 mm enhanced strength and stiffness by up to 123 % (55 %) and 46 % (10 %), with pre-and post-ultimate ductility growing by 16 % (113 %) and 15 % (19 %). However, lengthening them from 0.6 to 1.2 and 3 m decreased CMSFs' strength (stiffness) by up to 37 % (5 %) and 65 % (71 %), with no IMC failure. The sub-assembled CMSFs' buckling load was evaluated using theoretical models, considering members' stiffnesses and rotary IMC as pinned and semi-rigid. The average theory-to-FEM buckling load for pinned and semi-rigid IMC was 0.70 and 0.96, indicating that both models were conservative. However, considering IMC's rotational stiffness provided less scattering and a more realistic depiction of the CMSFs' buckling behavior than the pinned model. The study's findings and the accuracy of theoretical buckling models ensured they could conservatively design CMSFs under compressive loadings while considering their uniquenesses. [ABSTRACT FROM AUTHOR]

Photos taken under nighttime or backlit conditions often suffer from complex and unpredictable degradation, such as low visibility, messy noise, and distorted color. Previous methods mainly focused on global brightness and contrast while ignoring structural and textural details, or they handled the fusion of features without adequately considering their intrinsic association, resulting in incomplete feature representations. To address this issue, we propose a global-and-local aware network (GLAN) by projecting the features into the frequency domain and incorporating them in a knowledge-sharing manner. This method effectively integrates the global modeling capability of the transformer and the local sensitivity of the convolutional neural network to represent structure and texture. First, the global branch, which is comprised of transformer blocks, performs feature extraction under the global receptive field, while the local branch constructs multi-scale features to provide local fine-grained details. Then, we design a novel adaptive multi-scale feature block (AMSFB) that deploys channel split operation to decrease the calculation amount. To better learn the channel and spatial correlations of intermediate features, we introduce a multi-scale channel attention module (MSCAM) and a pixel attention module (PAM) into the AMSFB. Finally, a frequency-aware interaction module (FAIM) is developed for bidirectional information supplementation, which builds feature descriptors simultaneously covering low-frequency and high-frequency information based on the discrete cosine transform (DCT). Through extensive quantitative and qualitative experiments, our method can achieve competitive results compared with over ten state-of-the-art image enhancement methods on eight benchmark datasets. • The AMSFB preserves ample image details based on attention modules. • The FAIM filters low-frequency and high-frequency information of images, simultaneously. • The GLAN extracts global context information and local fine-grained details. [ABSTRACT FROM AUTHOR]

Understanding the demand flexibility of city-scale buildings under different demand response (DR) strategies is crucial to balance the power supply and demand in the grid. This paper presented a case study to evaluate the electricity consumption reduction potential for buildings in Changsha under different DR strategies. First, sixty-six prototype energy models for twenty-two building types of three vintages were selected to represent 59,332 buildings in Changsha. The total electricity consumption of the building stock was obtained by aggregating the prototype electricity use intensity with their representative building area. Three DR strategies were formulated, including temperature reset, lighting control, and plug load control. Second, a toolkit, AutoBPS-DR, was developed to automatically integrate individual DR strategy as well as their combination into the baseline energy models. Five scenarios were analyzed, including the baseline case, three cases with a single DR strategy, and a case with three DR strategies combined. The results showed that compared to the baseline scenario, the electricity consumption reductions of the case buildings for a 3-h DR event under temperature reset, lighting control, plug load control, and combined control scenarios were 603.97 MWh (7.94%), 441.08 MWh (5.80%), 663.26 MWh (8.72%) and 1673.32 MWh (22.00%), respectively. In the plug load control scenarios, high-rise apartments made the largest contribution with a reduction of 134.15 MWh. Medium office buildings had the most reduction under the other three scenarios, with a reduction of 122.16 MWh for temperature reset, 107.90 MWh for lighting control, and 357.16 MWh for combination control. This study demonstrated a significant DR potential for buildings in Changsha to overcome the electricity shortage period. [ABSTRACT FROM AUTHOR]

Spiral strands, galvanized steel wires, galvanized semiparallel wire strands, and steel tie rods in large-span building structures are inevitably corroded due to long-term exposure to corrosive atmospheres. However, research on different structural cables is rare, and lifetime safety evaluation of large-span building structures is urgently required. Therefore, three corrosion tests and static tensile tests after corrosion of four types of structural cables were conducted to determine the effects on corrosion behavior caused by plating, coating, twisting, and the environment. The corrosion behavior of a cable had different characteristics. A calculation method for the uniform corrosion depth of semiparallel wire strands and a three-parameter power function that effectively expresses the relationship between corrosion depth and exposure time were proposed and verified. The equivalent conversion relationship between the atmospheric exposure test and the standard laboratory accelerated corrosion test was established. The recommended 50-year corrosion depth for different structural cables was calculated, based on two corrosive environments in which long-span building structures often exist. [ABSTRACT FROM AUTHOR]

Single-image dehazing is an ill-posed problem. Most previous methods focused on estimating intermediate parameters for input hazy images. In this paper, we propose a novel end-to-end Simplified Non-locally Dense Network (SNDN) which does not rely on intermediate parameters. To capture long-range dependencies, we propose a Simplified Non-local Dense Block (SNDB) which is lightweight and outperforms traditional non-local method. Our SNDB will be embedded into a densely connected encoder–decoder network. To avoid gradients vanishing problem, we propose a simple branch network which only have five convolution layers. The effectiveness of our proposed network is proved through ablation experiment. In addition, we enhanced our training set by synthesizing colored hazy images, which helps restore the original color of the hazy image. The experimental results demonstrate that our network have better performance than most of the pervious state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper studies fractional integral inequalities for fractional integral operators containing extended Mittag-Leffler (ML) functions. These inequalities provide upper bounds of left- and right-sided fractional integrals for (α , h − m) convex functions. A generalized fractional Hadamard inequality is established. All the results hold for h-convex, (h , m) -convex, (α , m) -convex, (s , m) -convex, and associated functions. [ABSTRACT FROM AUTHOR]

A multi-scale numerical model was used to study the mechanism of steel tube restraint effect on the concrete of concrete-filled steel tube (CFST) columns under compression. In the developed model, aggregates, mortar, and interfacial transition zones (ITZ) of concrete core were fabricated in meso-scale; however, steel tube was considered to be in macro-scale to investigate the interactions of all phases. Parametric analyses with different diameters and steel ratios were conducted to evaluate multi-scale model. The developed multi-scale numerical simulation could be employed to provide a better understanding on cracking processes of concrete and stress paths of steel tubes in CFST. [ABSTRACT FROM AUTHOR]

Previous research studies indicate that the proportion of Magnus force at the spinning projectile tail position is very high. Meanwhile, the large mutations of aerodynamic characteristics are found after adding boattail structures. In order to study the influences of boattail structures on aerodynamics of a spinning projectile, a 6.37-diameter long tangential-ogive-cylinder projectile is selected as the original model. Moreover, several boattail configurations are adopted to investigate the effects of boattail structures on the aerodynamics. Numerical simulations with the use of detached eddy simulation method have been performed to study the modification of boattail structure on the surface pressure of the projectile to expose the effects on the aerodynamic characteristics. The reliability of the numerical method has been validated through comparison with experimental data. The numerical results show that the variations of the wake vortex field due to the boattail structures have important influences on the surface pressure and the aerodynamic characteristics. The results provide important observations which can be valuable for design optimization of supersonic spinning projectile. [ABSTRACT FROM AUTHOR]

This paper presents an effective video cut-out approach, which can be utilized to segment the moving object in video shots. We first introduce the Octagon-Sensitive-Filtering (OSF) and its illumination invariant feature (IIF), which is computed on each pixel of the image via adding contributions from neighboring pixels. We integrate our IIF into the variational model and obtain the seeds during preprocessing to help address large displacement and illumination changes. An effective seed update method based on tracking-then-refinement based on IIF is presented to compensate for location ambiguities, and the strategy is effective to deal with illumination variances and objects deformation. Furthermore, we apply the IIF-based graph-cut to deal with fuzzy boundaries. Multiple experiments on quantitative challenging datasets have shown the robustness, high-quality video cut-out and efficiency of our approach to acute variances of illumination and complex motion. [ABSTRACT FROM AUTHOR]

This research investigates the bounds of fractional integral operators containing an extended generalized Mittag-Leffler function as a kernel via several kinds of convexity. In particular, the established bounds are studied for convex functions and further connected with known results. Furthermore, these results applied to the parabolic function and consequently recurrence relations for Mittag-Leffler functions are obtained. Moreover, some fractional differential equations containing Mittag-Leffler functions are constructed and their solutions are provided by Laplace transform technique. [ABSTRACT FROM AUTHOR]

This paper attempts to better understand contract type and risk attitude in R&D alliance under information asymmetry, that is, how the marketer designs and chooses optimal contract between royalty contract and milestone contract and how the innovator's risk attitude and asymmetric information affect the marketer's optimal contract strategies and profits. We use principal–agent models to formulate the marketer's contracting problem under asymmetric information about the innovator's innovation expertise and unobservable efforts. We find that, compared to the case under full information in both contracting structures, the marketer should distort the commission rate upwards under dual asymmetric information when the innovator is risk averse or downwards to lower innovation–expertise and risk-loving innovator; nevertheless, the marketer should offer the first-best contract. Furthermore, investigating the impacts of information asymmetry on the marketer's profits under two information structures, we find that dual asymmetric information harms the marketer's profit, especially when the innovator's effort marginal efficiency is higher. Finally, by comparing the marketer's profits in two types of contracts, we give the specific regions that milestone contract or royalty contract benefits the marketer better under different information structures. [ABSTRACT FROM AUTHOR]

Dendrimers are rising polymeric structures known for their flexibility in medication conveyance and high usefulness, whose properties are same biomolecules. These nanostructured macromolecules have shown potential capacities in capturing as well as conjugating the high subatomic weight hydrophilic/hydrophobic substances by host-visitor collaborations and covalent holding (prodrug approach) individually. In quantitative structure-property relationships (QSPR), topological indices are utilized to gather properties of dendrimers. Topological indices catch symmetry of dendrimer structures and give it a logical reasoning to predict properties, for instance, viscosity, boiling points, the radius of gyrations, etc. In this report, we intend to examine dendrimers through irregularity indices that are valuable in QSPR studies. We studied sixteen irregularity indices if diverse dendrimer structures. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the most common cancers of the digestive tract. Although numerous studies have been conducted to elucidate the cause of CRC, the exact mechanism of CRC development remains to be determined. To identify candidate genes that may be involved in CRC development and progression, the microarray datasets GSE41657, GSE77953 and GSE113513 were downloaded from the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for functional enrichment analysis of differentially expressed genes (DEGs). A protein-protein interaction network was constructed, and the hub genes were subjected to module analysis and identification using Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. A total of 142 DEGs were identified, with enriched functions and pathways in the 'cell cycle', 'cell proliferation', 'the mitotic cell cycle' and 'one-carbon metabolic process'. In addition, 10 hub genes were identified, and functional analysis indicated that these genes are mainly enriched in 'cell division', 'cell cycle' and functions associated with nucleotide binding processes. Survival analysis demonstrated that DNA topoisomerase II α, cyclin-dependent kinase 1 and CDC28 protein kinase regulatory subunit 2 may be involved in cancer invasion or recurrence. The DEGs identified in the present study may help explain the molecular mechanisms of CRC development and progression. [ABSTRACT FROM AUTHOR]

Minghuai 1 (MH1) is a yam (Dioscorea alata) cultivar with high tolerance to flooding but sensitivity to chilling. MH1 responded differently to chilling and flooding according to various physiological parameters and antioxidant enzymes. Flooding led to an increase in ascorbate peroxidase (APX) activity in both roots and leaves, while chilling did not affect APX activity. The full length DaAPX ORF sequence from MH1 (750 bp) was then cloned. Phylogenetic analysis showed that plant cytosolic APXs into four major clusters and DaAPX was closely related to Oncidium. The DaAPX gene driven by a 35S promoter was transferred into Arabidopsis. The gene expression and enzyme activity of APX in the DaAPX transgenic lines 1–3 were significantly higher than in wild type (WT) plants. Compared to WT plants, seedling growth characteristics were significantly better in all transgenic lines under chilling, flooding, and oxidative stresses, indicating that the overexpression of DaAPX in Arabidopsis enhanced tolerance to several abiotic stresses. MH1 plants supplied with H2O2 presented an increase in the activity of APX leading to enhanced tolerance to chilling. Functional characterization of the APX gene should improve our understanding of the chilling- and flood-response mechanism in the yam. [ABSTRACT FROM AUTHOR]

This article quantitatively evaluated the influence of three-dimensional multi-layer welding on the welding residual stress of super-big diameter welded hollow sphere joint in the large-span spatial steel structure considering the influence of material state change using finite element method. First, this article proposed a conception of equivalent state change time—the virtual time of state change in the analysis of welding and cooling—which represents the heat absorbed or released during the change of solid and fluid states in welding material. The equivalent state change time increases the accuracy of the thermal analysis considering the latent heat of fusion in welding and cooling process. Second, this article simulated the numerical experiments of three welding methods including multi-layer symmetric welding, multi-layer sequential welding, and single-layer symmetric welding, which show that multi-layer symmetric welding not only increases the balance of supporting ability of structure but also decreases the value of maximum tensile residual stress, and it is better than the other two welding methods. [ABSTRACT FROM AUTHOR]

Groundwater recharge source and flowpaths, along with aquifer medium characteristics, are identified based on nitrate distribution and dynamics. These are significant factors in long-term water-resources management of the Sichuan-Yunnan-Guizhou lead-zinc mining deposits, southwestern China. The results show that high nitrate concentration correlates with lower temperature and heavy isotope enrichment, indicating groundwater recharge from the eastern karst depression area (situated at higher elevation), which has intensive agriculture. Higher NO3- concentration corresponds to higher Ca/Mg ratio in the Carboniferous karst aquifer, both indicating the preferential groundwater flowpath, while the lateral nitrate distribution signifies hydraulic connection with the northern Devonian aquifer passing through the aquitard via NE–SW and N–S trending faults. Nitrate pollution has reached deep sections of the karst aquifers and generated a wide vertical distribution, with the lowest elevation of significant nitrate concentration at –28 m relative to sea level, far lower than the recharge area by over 1,500 m. The variations in groundwater temperature, electrical conductivity and partial pressure of CO2 in the early rainy season are associated with enhanced dissolution capacity of the carbonate minerals, controlled by the soil CO2 effect, hence characterizing the mining area as a fissure-dominant karst groundwater system. Under such conditions, nitrate concentration rises and recedes subsequent to recharge events, and these processes characterize nitrate leaching. Overall, the current nitrate distribution is the result of increased agricultural productivity, intensive mine dewatering works and intrinsic media heterogeneity. Nitrate functions as an artificial, stable and cost-effective tracer for groundwater-system characterization in this mining area. [ABSTRACT FROM AUTHOR]

Manufacturers are today striving to offer value-added Product Service System (PSS) with the purpose of achieving higher competiveness and more environmental benefits. Requirement elicitation and evaluation with sustainability concerns play a key role in a successful development of sustainable PSS. However, the previous literature rarely address the PSS requirement from the view of sustainability, while mainly focusing on the customer satisfaction. To accurately identify the requirement with respect to sustainable value from a long term perspective, it is necessary to develop effective methods for requirement elicitation for sustainable PSS. In addition, the prioritization of sustainable value requirement provides critical guidance for the later PSS design. The prioritization involves much judgement ambiguousness and diversity which may lead to inaccurate requirement analysis result. However, there are few researches on combinatory manipulation of the vagueness and diversity. Therefore, to solve these problems, an innovative methodology incorporating requirement elicitation and evaluation is developed for sustainable PSS. This study introduces the concept of value uncaptured into the identification of product value state, and offers the Product Value State Model (PVSM) method to elicit value requirements which help PSS deliver more sustainability. Moreover, a hybrid model for evaluating the sustainable value requirement is proposed by combining the fuzzy set, rough set, Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) methods. An application in an excavator PSS and the comparisons with some different methods demonstrate the feasibility and potential of the methodology. Theoretically, the proposed evaluation model provides more accurate and realistic analysis results of PSS requirements compared to traditional methods, since it supports to simultaneously manipulate judgement vagueness, group decision diversity, and complex interrelationship. In practical PSS design, the method helps PSS designers successfully recognize the most key value requirements with both respect of sustainability and customer satisfaction. Image 1 • A new topic on sustainable value requirement of PSS is put forward. • Sustainability is embed into elicitation of PSS sustainable value requirement. • A new rough-fuzzy DEMATEL-ANP is proposed to evaluate sustainable value requirement. • Integrated rough-fuzzy number is applied to manipulate vagueness and diversity. • Showed the method's feasibility, accuracy and potentials with excavator PSS. [ABSTRACT FROM AUTHOR]

High precision register controls are indispensable in roll-to-roll (R2R) printing systems for mass manufacturing. In R2R printing systems, each gravure cylinder is driven by an individual motor and guiding rolls distributed between two adjacent gravure cylinders are driven by the tension of their wrapped web. In the speed-up phase, tension fluctuations caused by torque balance of guiding rolls generate register errors in each printing unit. Therefore, it is a challenging issue to design a control method to reduce the register errors. In this paper, a mechanical model of R2R printing systems in the speed-up phase is developed based on the principle of mass conservation and torque balance. A model-based feed-forward proportion-derivative controller is designed to reduce the register errors caused by the tension fluctuations. The validity of the proposed method is demonstrated by simulation and experiments carried out on an industrial rotogravure printing press. A comparison with other control methods especially a well-tuned proportion differential control which is widely adopted by printing presses shows that the absolute maximum register error is drastically reduced and the average register error is greatly decreased by the proposed method. The results verify the effectiveness and feasibility of the proposed control method. Note to Practitioners—This paper presents control strategy for the speed-up phase in R2R printing system, particularly for printing systems with electronic line shafts. Few existing systematic research is relevant with the speed-up phase in the R2R printing system. This paper analyses the relationship of the register error and the web tension fluctuations between two adjacent gravure cylinders which are driven by the guiding rolls, then proposes the control strategy based on the identification of the acceleration of guiding rolls. The proposed method can be extended to other similar R2R systems. Simulation and industrial experiments suggest that the control method is feasible and has superior performance compared with the existing methods. In the future research, we will study the adaptive model representing the acceleration of guiding rolls in different R2R web systems. [ABSTRACT FROM AUTHOR]

Fast-growing forests are widespread distribution, but the relevant timber products are limited by insufficient strength and low reliability in the architectural structure. In recent years, the combination of rapidly growing timber and thin-walled steel to enhance structural performance has attracted attention, and connection performance is critical in ensuring a compelling combination. In addition, adhesive technology has potential applications due to its high efficiency and lightweight. Nevertheless, in light construction, the adhesion behavior between thin-walled steel and largethickness timber with relatively low mechanical properties has yet to be effectively studied and revealed. This study investigates the bonding properties of thin-walled steel and fast-growing timber single-strap joints by numerical and experimental methods. The SS joints' shear strength and failure modes were obtained by tensile tests, considering different adhesive and overlap lengths. In addition, stress analysis was performed using the finite element method (FEM) combined with the cohesive zone model (CZM) to explore critical issues such as damage variables, peak stresses, etc. Furthermore, the parameters such as overlap, the thickness of adherends, and edge distance were investigated. As a result, it is concluded that the bond of thin-walled steel-fast-growing timber is a special non-balanced connection. The study indicates that shear stress distribution is steeper than other strap joints. The other difference is that the right end in overlapping areas may experience higher peel stress than the left ends, which might delaminate the timber. Yielding phenomena may also occur at such weak timber ends along the normal direction. The bearing capacity of these joints is susceptible to the difference in stiffness between timber and steel. Joint performance can be enhanced by increasing the timber thickness and overlap length appropriately. The summary obtained from this paper can be a reference for applying adhesive in thin-walled steel-fast-growing timber composite structure systems. • Bond failure between thin-steel and fast-growing natural timber. • Unbalanced performance of steel-timber single strap joints under tensile. • Influence of the plastic behavior and material defect of natural timber on the tensile properties of joints. • Failure mechanism of steel-timber bonded joints by detailed finite element modeling. [ABSTRACT FROM AUTHOR]

• The behavior of glulam spliced joints with self-tapping screws was studied. • Numerical models considering crack propagation were created. • The theoretical equation was established based on fracture mechanics. Tests were conducted to determine the flexural bearing capacities of glulam spliced joints connected by self-tapping screws (STSs) in five different configurations. The flexural performances and failure modes of these joints were analyzed and an extended finite element method was utilized to establish numerical models of the STS-connected glulam spliced joints while considering crack propagation. The simulation results were in excellent agreement with the test. Moreover, theoretical formulas for the flexural bearing capacity and a flexural stiffness model of STS-connected glulam spliced joints were developed. The research findings indicated that the vertical STSs were more effective in enhancing the bending capacity of the joints than the angled STSs in the vertical plane. Specifically, when using full 90° STSs, the bending capacity increased by 35.57% compared to when using full 60° STSs. The elastic rotational stiffness values of the joints were also improved by using a mixed-angle arrangement of STSs. Specifically, when utilizing a mixed arrangement of 90° and 60°, the elastic stiffness values increased by 33.44% and 63.20% compared to when using full 90° and full 60°, respectively. However, while using STSs in the horizontal plane at the vertical gap significantly enhanced the flexural bearing capacities of the spliced joints, it also led to a significant reduction in the ductility of the joints. [ABSTRACT FROM AUTHOR]

At present, both active and passive solar heating system designs rely on the sequential design method. However, this method fails to account for the correlation between passive components and active systems, leading to poor synergy between passive solar technology and active heating systems. Therefore, a collaborative simulation model of active and passive solar heating systems was constructed in this study. In addition, an optimization model with the objective of minimization carbon emissions of buildings and the active system was developed, and the sunspace depth, building envelope parameters, and the equipment capacity were optimized and simulated. The results indicate that the optimized total carbon emissions of solar active and passive heating systems can be reduced by up to 26.5%–50.3% compared to passive building and boiler combined systems. The optimized solar fraction of solar active and passive heating systems exceeds 85%. Furthermore, higher energy efficiency of heat source equipment in the active system has been related to a lower thermal insulation performance of the enclosure structure and a greater building load undertaken by the active system. In the active solar heating system, the higher the efficiency of the auxiliary heat source, the more the heating load is borne. • A co-optimization model based on the minimum carbon emission target is proposed. • The passive building and active solar heating combination systems are optimized. • Lhasa, Nyingchi, Qamdo and Pagri in Tibet were selected as typical regions. • The carbon emissions of buildings are further reduced after co-optimization. [ABSTRACT FROM AUTHOR]