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Nowadays, with the rapid development of consumer Unmanned Aerial Vehicles (UAVs), utilizing UAV platforms for visual surveillance has become very attractive, and a key part of this is remote vision-based pedestrian attribute recognition. Pedestrian Attribute Recognition (PAR) is dedicated to predicting multiple attribute labels of a single pedestrian image extracted from surveillance videos and aerial imagery, which presents significant challenges in the computer vision community due to factors such as poor imaging quality and substantial pose variations. Despite recent studies demonstrating impressive advancements in utilizing complicated architectures and exploring relations, most of them may fail to fully and systematically consider the inter-region, inter-attribute, and region-attribute mapping relations simultaneously and be stuck in the dilemma of information redundancy, leading to the degradation of recognition accuracy. To address the issues, we construct a novel Mask-Relation-Guided Transformer (MRG-T) framework that consists of three relation modeling modules to fully exploit spatial and semantic relations in the model learning process. Specifically, we first propose a Masked Region Relation Module (MRRM) to focus on precise spatial attention regions to extract more robust features with masked random patch training. To explore the semantic association of attributes, we further present a Masked Attribute Relation Module (MARM) to extract intrinsic and semantic inter-attribute relations with an attribute label masking strategy. Based on the cross-attention mechanism, we finally design a Region and Attribute Mapping Module (RAMM) to learn the cross-modal alignment between spatial regions and semantic attributes. We conduct comprehensive experiments on three public benchmarks such as PETA, PA-100K, and RAPv1, and conduct inference on a large-scale airborne person dataset named PRAI-1581. The extensive experimental results demonstrate the superior performance of our method compared to state-of-the-art approaches and validate the effectiveness of mask-relation-guided modeling in the remote vision-based PAR task. [ABSTRACT FROM AUTHOR]

Deferoxamine (DFO) is a water-soluble iron chelator used pharmacologically for the management of patients with transfusional iron overload. However, DFO is not cell-permeable and has a short plasma half-life, which necessitates lengthy parenteral administration with an infusion pump. We previously reported the synthesis of chitosan (CS) nanoparticles for sustained slow release of DFO. In the present study, we developed solid dispersions and nanoparticles of a carboxymethyl water-soluble chitosan derivative (CMCS) for improved DFO encapsulation and release. CS dispersions and nanoparticles with DFO have been prepared by ironical gelation using sodium triphosphate (TPP) and were examined for comparison purposes. The successful presence of DFO in CMCS polymeric dispersions and nanoparticles was confirmed through FTIR measurements. Furthermore, the formation of CMCS nanoparticles led to inclusion of DFO in an amorphous state, while dispersion of DFO in the polymeric matrix led to a decrease in its crystallinity according to X-ray diffraction (XRD) and differential scanning calorimetry (DSC) results. An in vitro release assay indicated sustained release of DFO from CS and CMCS nanoparticles over 48 h and 24 h, respectively. Application of CMCS-DFO dispersions to murine RAW 264.7 macrophages or human HeLa cervical carcinoma cells triggered cellular responses to iron deficiency. These were exemplified in the induction of the mRNA encoding transferrin receptor 1, the major iron uptake protein, and the suppression of ferritin, the iron storage protein. Our data indicate that CMCS-DFO nanoparticles release bioactive DFO that causes effective iron chelation in cultured cells. [ABSTRACT FROM AUTHOR]

Changes of customer requirements (CRs) are inevitable disturbances for products which will lead to product obsolescence or frequent redesign. The property of product defending and recovering from the shock of ever-changing CRs is resilience. It is beneficial for designers to explore and evaluate product resilience towards changing CRs. Fortunately, various resilience assessment methods in engineering realm have offered some significant insights. Motivated by the deficiencies of the existing studies and the advantages of engineering resilience assessment methods, product resilience towards changing CRs is measured. Firstly, joint customer satisfaction is defined by integrating competition analysis and importance analysis. Secondly, the evolution trends of CRs are depicted and captured based on a modified grey model and polynomial fitting, respectively. Then, a three-stage model considering absorption, adaptation, and recovery is established to evaluate product resilience. Lastly, a case study of an electric vehicle is implemented to elucidate the utility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstarct: Customer requirements (CRs) are the essential driven forces of product development. Constrained by the rigid budget and time allocated to product development, much attentions and resources should be paid on critical customer requirements (CCRs). Product design occurs with an increasingly frenetic pace of change in today's competitive market, and the changes of external environment will lead to the changes of CRs. Thus, involving the sensitivity of CRs toward influence factors to identify CCRs is of great significance to grasp the directions of product evolution and enhance market competitiveness. To fill this gap, this study proposes a CCRs identification method integrated Kano model and structural equation model (SEM). First, the Kano model is adopted to determine the category of each CR. Second, based on CRs' categorization, an SEM model is established to measure the sensitivity of CRs toward the turbulence of influence factors. Then the importance of each CR is calculated, and by integrating the sensitivity and importance, a four-quadrant diagram is constructed to identify the CCRs. Finally, the identification of CCRs for smartphone is implemented as an example to demonstrate the feasibility and additional value of the proposed method. [ABSTRACT FROM AUTHOR]

In drilling processes, faulty downhole conditions often lead to drilling performance degradation and even serious accidents, such as the blowout, and well collapse. To improve the drilling efficiency and enhance the process safety, a new downhole condition identification method is proposed for geological drilling processes based on quantitative trends and expert rules. A knowledge base that associates the quantitative trends and downhole conditions is established based on variational trends extracted from the historical data and rules summarized from the drilling operation manual. When the new data arrive for online monitoring, the variational trends are extracted, and then, the downhole condition is identified by comparing such trends with each rule in the knowledge base. The effectiveness and practicality of the proposed method are demonstrated by industrial case studies with real drilling process data. [ABSTRACT FROM AUTHOR]

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology. [ABSTRACT FROM AUTHOR]

The early warning of drilling faults is of paramount importance to prevent or reduce environmental and property damages. In view of the complex drillstring kinematic characteristics and changeable formation environment, this paper proposes a new fault early warning method for the drillstring system based on a multi-model fusion and self-updating strategy. The major contributions are twofold: (1) A hybrid drillstring early warning method is proposed to identify faulty conditions based on the fusion of multi-dimensional prediction models of the drillstring system; (2) An event-triggered model self-updating strategy is proposed to mitigate the prediction performance degradation caused by formation uncertainties. The effectiveness and practicability of the proposed method are demonstrated by industrial case studies, and the results indicate that the proposed method outperforms other approaches. • A hybrid drillstring early warning method is proposed based on multi-model fusion. • An event triggered model updating strategy is proposed for formation uncertainties. [ABSTRACT FROM AUTHOR]

The superhydrophobic surfaces with three kinds of nanopillars on polypropylene (PP) substrates are fabricated by a plasma nanotexturing technique comprising oxygen‐plasma treatment (OPT) followed by fluorocarbon polymer deposition (FPD). The diameters of nanopillars and spacing distances between nanopillars are tuned under the different OPT and FPD duration times. The wettability and contact electrification on the surfaces are analyzed under the water droplet impact by changing the impacting droplet number, Weber number, and salt concentration. The dense or wide nanopillars favor high contact charge on the surfaces with nanopillars, arousing the damage of the superhydrophobicity with low adhesion. The low contact charge impacting the droplets with high salt concentration has a weakened effect on the superhydrophobicity of the surfaces with nanopillars. [ABSTRACT FROM AUTHOR]

Background: KIF6 (kinesin family member 6), a protein coded by the KIF6 gene, serves an important intracellular function to transport organelles along microtubules. In a pilot study, we found that a common KIF6 Trp719Arg variant increased the propensity of thoracic aortic aneurysms (TAA) to suffer dissection (AD). The present study aims for a definite investigation of the predictive ability of KIF6 719Arg vis à vis AD. Confirmatory findings would enhance natural history prediction in TAA. Methods: 1108 subjects (899 aneurysm and 209 dissection patients) had KIF6 719Arg variant status determined. Results: The 719Arg variant in the KIF6 gene correlated strongly with occurrence of AD. Specifically, KIF6 719Arg positivity (homozygous or heterozygous) was substantially more common in dissectors (69.8%) than non-dissectors (58.5%) (p = 0.003). Odds ratios (OR) for suffering aortic dissection ranged from 1.77 to 1.94 for Arg carriers in various dissection categories. These high OR associations were noted for both ascending and descending aneurysms and for homozygous and heterozygous Arg variant patients. The rate of aortic dissection over time was significantly higher for carriers of the Arg allele (p = 0.004). Additionally, Arg allele carriers were more likely to reach the combined endpoint of dissection or death (p = 0.03). Conclusions: We demonstrate the marked adverse impact of the 719Arg variant of the KIF6 gene on the likelihood that a TAA patient will suffer aortic dissection. Clinical assessment of the variant status of this molecularly important gene may provide a valuable "non-size" criterion to enhance surgical decision making above and beyond the currently used metric of aortic size (diameter). [ABSTRACT FROM AUTHOR]

Remote-vision-based image processing plays a vital role in the safety helmet and harness monitoring of construction sites, in which computer-vision-based automatic safety helmet and harness monitoring systems have attracted significant attention for practical applications. However, many problems have not been well solved in existing computer-vision-based systems, such as the shortage of safety helmet and harness monitoring datasets and the low accuracy of the detection algorithms. To address these issues, an attribute-knowledge-modeling-based safety helmet and harness monitoring system is constructed in this paper, which elegantly transforms safety state recognition into images' semantic attribute recognition. Specifically, a novel transformer-based end-to-end network with a self-attention mechanism is proposed to improve attribute recognition performance by making full use of the correlations between image features and semantic attributes, based on which a security recognition system is constructed by integrating detection, tracking, and attribute recognition. Experimental results for safety helmet and harness detection demonstrate that the accuracy and robustness of the proposed transformer-based attribute recognition algorithm obviously outperforms the state-of-the-art algorithms, and the presented system is robust to challenges such as pose variation, occlusion, and a cluttered background. [ABSTRACT FROM AUTHOR]

The survival, growth, and virulence of Leishmania spp., a group of protozoan parasites, depends on the proper access and regulation of iron. Macrophages, Leishmania's host cell, may divert iron traffic by reducing uptake or by increasing the efflux of iron via the exporter ferroportin. This parasite has adapted by inhibiting the synthesis and inducing the degradation of ferroportin. To study the role of iron in leishmaniasis, we employed Hjv−/− mice, a model of hemochromatosis. The disruption of hemojuvelin (Hjv) abrogates the expression of the iron hormone hepcidin. This allows unrestricted iron entry into the plasma from ferroportin-expressing intestinal epithelial cells and tissue macrophages, resulting in systemic iron overload. Mice were injected with Leishmania major in hind footpads or intraperitoneally. Compared with wild-type controls, Hjv−/− mice displayed transient delayed growth of L. major in hind footpads, with a significant difference in parasite burden 4 weeks post-infection. Following acute intraperitoneal exposure to L. major, Hjv−/− peritoneal cells manifested increased expression of inflammatory cytokines and chemokines (Il1b, Tnfa, Cxcl2, and Ccl2). In response to infection with L. infantum, the causative agent of visceral leishmaniasis, Hjv−/− and control mice developed similar liver and splenic parasite burden despite vastly different tissue iron content and ferroportin expression. Thus, genetic iron overload due to hemojuvelin deficiency appears to mitigate the early development of only cutaneous leishmaniasis. [ABSTRACT FROM AUTHOR]

White circularly polarized organic light‐emitting diodes (CP‐WOLEDs) are of great significance in potential lighting sources and full‐color 3D displays. However, High‐performance white CP‐EL sources are almost unexplored. We have constructed full‐color CP‐EL devices based on chiral co‐assemblies by using three achiral conjugated pyrene‐based dyes (BP, w‐WP and c‐WP) doped with chiral binaphthyl‐based enantiomers (S‐/R‐M) as the EMLs through an intermolecular chirality induction mechanism. (S‐/R‐M)0.2‐(c‐WP)0.8 films exhibit regular helix nanofibers under annealing treatment and emit strong white CPL. Significantly, remarkable CP‐WOLEDs based on (S‐/R‐M)0.2‐(c‐WP)0.8 were achieved with |gEL| values as high as 6.2×10−2 and an excellent CRI of 98 at the CIE coordinates of (0.33, 0.33). These are the highest gEL and CRI values of reported CP‐WOLEDs to date. This is the first achievement of CP‐WOLEDs based on chiral co‐assembled helix nanofiber emitters, and provides a valuable strategy with which to develop white CP‐EL for future practical applications. [ABSTRACT FROM AUTHOR]

White circularly polarized organic light‐emitting diodes (CP‐WOLEDs) are of great significance in potential lighting sources and full‐color 3D displays. However, High‐performance white CP‐EL sources are almost unexplored. We have constructed full‐color CP‐EL devices based on chiral co‐assemblies by using three achiral conjugated pyrene‐based dyes (BP, w‐WP and c‐WP) doped with chiral binaphthyl‐based enantiomers (S‐/R‐M) as the EMLs through an intermolecular chirality induction mechanism. (S‐/R‐M)0.2‐(c‐WP)0.8 films exhibit regular helix nanofibers under annealing treatment and emit strong white CPL. Significantly, remarkable CP‐WOLEDs based on (S‐/R‐M)0.2‐(c‐WP)0.8 were achieved with |gEL| values as high as 6.2×10−2 and an excellent CRI of 98 at the CIE coordinates of (0.33, 0.33). These are the highest gEL and CRI values of reported CP‐WOLEDs to date. This is the first achievement of CP‐WOLEDs based on chiral co‐assembled helix nanofiber emitters, and provides a valuable strategy with which to develop white CP‐EL for future practical applications. [ABSTRACT FROM AUTHOR]

Sensitivity analysis provides information to understand response models and helps make better decisions in many fields, including the petroleum and mining industries. A new approximate method for sensitivity analysis through extracting covariogram ranges is proposed in this paper. In this method, the covariogram range will be treated the same as the variogram range, and each factor in the response model will be looked as a separate coordinate in a pseudo-spatial space. The result indicates that the covariogram ranges calculated in this space for each variable have a strong relationship with the main effect sensitivity index in variance-based method, that is, a longer range has less sensitivity. Thus, the sensitivity of each factor is accessible through covariogram range calculation, which is a unique approach to sensitivity analysis compared to existing approaches. This approach provides a new perspective of understanding global sensitivity. Furthermore, a modified covariogram fitting algorithm is put forward to calculate the ranges through optimization. This iterative algorithm minimizes the squared error between the modified experimental covariogram and Gaussian covariogram model, which is useful in a high dimension with sparse sampling. The simulated data are also used to validate the automatic covariogram fitting, and the optimized ranges are very close to the true ranges even with a small sample size. Finally, this method is successfully applied in the parameter sensitivity analysis of reservoir simulation, and limitations or considerations for the practical application have been discussed. [ABSTRACT FROM AUTHOR]

The carbon fiber‐reinforced polyetheretherketone (CF/PEEK) composite coatings with two types of short CFs, that is, 300‐ and 600‐mesh, each in the contents of 10 and 30 wt% are deposited in comparison with the pure PEEK coatings by using a flame spraying method, respectively. The 300‐mesh CFs with intact morphology and the 600‐mesh CFs preserving fractured shape and higher graphitization degree are selected as the reinforced fillers in the CF/PEEK composite coatings. The flame‐sprayed CF/PEEK composite coatings show the increased porosity with the higher CF contents. The adding of CFs in the flame‐sprayed CF/PEEK composite coatings limits the thermal degradation of PEEK and restrains the PEEK crystallization showing low crystallinity degree and small crystallite size. The composite coatings in 10 wt% CF content exhibit the optimized nanoindentation behavior and tribological property. The 300‐mesh CFs with large length and intact morphology in flame‐sprayed CF/PEEK composite coatings lead to the increased surface hardness by 1.31 times over that of the pure PEEK coatings. The 600‐mesh CFs with higher graphitization degree contribute to better tribological property of flame‐sprayed CF/PEEK composite coatings with an order of magnitude lower specific wear rate. [ABSTRACT FROM AUTHOR]

A novel analytical model is derived based on fractal geometry theory to characterize the permeability of power-law fluids through fractured porous media with fractal asperities on surfaces. The proposed model is expressed as a function of structure parameters of fractured porous media, fractal dimensions for porous matrix and for fracture as well as the index n of power-law fluid behavior. The influences of these parameters on the permeability are analyzed in detail. It is found that the relationship between permeability and roughness exhibits nonlinear characteristics. A higher power-law fluid behavior index significantly affects the reduction rate of permeability with relative roughness. Moreover, permeability is sensitive to the perturbation due to the rate of aperture to length. The proposed fractal model can clearly reveal more physical mechanisms for power-law fluid in fractured porous media than the existing models. Compared with the experimental data available in the literature, the validity of model predictions is verified. [ABSTRACT FROM AUTHOR]

The aim of this work is to investigate the evolution of the peak temperature of thermal cycle, microstructure, and mechanical properties of the joint during underwater bobbin tool friction stir welding (underwater BT-FSW) of 6082-T6 aluminum alloy with the butt joint by comparison with atmospheric bobbin tool friction stir–welded (atmospheric BT-FSW) joints. The results show that the peak temperature of advancing side (AS) and retreating side (RS) at 3 mm from the center of the weld reduces to 440 °C and 461 °C respectively because of the cooling effect of the aqueous medium. On the cross-section of the joint, an "S" line and a distinct gray-white texture can be seen. The stir zone (SZ) has much smaller equiaxed recrystallized grains. The ranges of the heat-affected zone (HAZ) and the thermal-mechanically affected zone (TMAZ) of underwater BT-FSW joint are smaller than those of atmospheric BT-FSW joint. The microstructures of the SZ, TMAZ, and HAZ of underwater BT-FSW joint are α-Al + GP zones, α-Al + GP zones, and α-Al + β' + Q' phases respectively. The Vickers hardness of underwater BT-FSW joint distribution profiles exhibit a W-shape. The SZ of underwater BT-FSW joint has the highest Vickers hardness at 94–103 HV and the minimum hardness of underwater BT-FSW joint appears at the transition zone of HAZ and TMAZ and is 79 HV. The tensile strength of underwater BT-FSW is 308 MPa, which is 95% of the strength of the base metal (BM). [ABSTRACT FROM AUTHOR]

Waterborne polyurethane that integrates fast room-temperature self-healable ability, high mechanical properties, antibacterial activity, and photoluminescence features is highly desirable but challenging. Herein, a novel waterborne polyurethane (ZIWPU) is synthesized with the double dynamic cross-linked networks of multiple hydrogen bonds formed by asymmetric polyurea structure and Zn2+-carboxylate coordination bonds. Profiting from the synergistic effects of double dynamic cross-linked networks, the optimized ZIWPU 2 film exhibits excellent mechanical properties (tensile strength of 34.36 MPa and toughness of 107.21 MJ/m3) and rapid room-temperature self-healing ability (healing efficiency > 85 % within 10 h) with the assistant of trace alcohol, which is superior to those of the most of currently reported room-temperature self-healing waterborne polyurethane. In addition, owing to the existence of Zn2+, ZIWPU 2 is simultaneously integrated with the outstanding antibacterial ability (antibacterial rate>96 %). Especially, the carbon dots (CDs) are introduced into ZIWPU 2 to give it an excellent photoluminescence function that can be used for anti-counterfeiting and crack diagnosis. Finally, this versatile WPU material is successfully applied to leather finishing. [Display omitted] • A simple strategy for the preparation of waterborne polyurethane with dual dynamic cross-linking networks was proposed. • The crosslinked WPU possesses excellent mechanical properties and rapid room-temperature self-healing ability. • The crosslinked WPU exhibits excellent antibacterial activity. • ZIWPU/CDs composite film displays photoluminescence, anti-counterfeiting and crack diagnosis. • The multifunctional WPU emulsions can be successfully used as a leather finishing. [ABSTRACT FROM AUTHOR]

The study characterizes power-law fluid through charged fibrous porous media with spatial fractional-derivative and fractal geometry. Seepage flow of power-law fluid across fractal fibrous porous media in the presence of electric double layers (EDLs) is investigated based on the capillary bundle model. The acquired velocity distribution equation in a narrow capillary is then transformed into the form of series with appropriate Taylor approximation. After that, an analytical formula for dimensionless permeability is derived based on the generalized Darcy's law. The effects of diverse parameters, including the fractal dimension of pore area, porosity, fractional order and Zeta potential on dimensionless permeability, are discussed. It can be seen from the results that lower fractional order has an amplification effect on dimensionless permeability with the change in Zeta potential. The results provide some theoretical guidance for revealing the seepage mechanism of a power-law fluid in charged porous media. [ABSTRACT FROM AUTHOR]

The tobacco-specific N-nitrosamines 4-(N-nitrosomethylamino)-1-(3-pyridyl)-1-butanone (NNK) and N′-nitrosonornicotine (NNN) always occur together and exclusively in tobacco products or in environments contaminated by tobacco smoke. They have been classified as "carcinogenic to humans" by the International Agency for Research on Cancer. In 1998, we published a review of the biochemistry, biology and carcinogenicity of tobacco-specific nitrosamines. Over the past 20 years, considerable progress has been made in our understanding of the mechanisms of metabolism and DNA adduct formation by these two important carcinogens, along with progress on their carcinogenicity and mutagenicity. In this review, we aim to provide an update on the carcinogenicity and mechanisms of the metabolism and DNA interactions of NNK and NNN. [ABSTRACT FROM AUTHOR]

Carcinogenic N-nitrosamine contamination in certain drugs has recently caused great concern and the attention of regulatory agencies. These carcinogens—widely detectable in relatively low levels in food, water, cosmetics, and drugs—are well-established and powerful animal carcinogens. The electrophiles resulting from the cytochrome P450-mediated metabolism of N-nitrosamines can readily react with DNA and form covalent addition products (DNA adducts) that play a central role in carcinogenesis if not repaired. In this review, we aim to provide a comprehensive and updated review of progress on the metabolic activation and DNA interactions of 10 carcinogenic N-nitrosamines to which humans are commonly exposed. Certain DNA adducts such as O6-methylguanine with established miscoding properties play central roles in the cancer induction process, whereas others have been linked to the high incidence of certain types of cancers. We hope the data summarized here will help researchers gain a better understanding of the bioactivation and DNA interactions of these 10 carcinogenic N-nitrosamines and facilitate further research on their toxicologic and carcinogenic properties. [ABSTRACT FROM AUTHOR]

Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by the fuzzy and rough division of moving image edges, this paper proposes a point tracking technology based on a fuzzy clustering algorithm, which is used for the point tracking of moving image sequence signs. This article analyzes the development status of sports image sequence analysis and processing technology and introduces some basic theories about fuzzy clustering algorithms. On the basis of the fuzzy clustering algorithm, the positioning and tracking of the marker points of the moving image sequence are studied. A series of experiments have proved that the fuzzy clustering algorithm can improve the recognition rate of the landmark points of the moving image. For the detection and tracking of moving targets, the fuzzy clustering algorithm can reach the limit faster under the same number of iterations, and the image noise can be reduced to 60% of the original by 5 iterations. This has excellent development value in application. [ABSTRACT FROM AUTHOR]

Aims: Peroxiredoxins (PRDX6) regulates the occurrence and progression of cancer. The aim of this study is to investigate the effect of PRDX6 knockdown on the biological behavior of human gastric cancer cell line BGC-823 cells.Settings and Design: Research article.Subjects and Methods: The differential expression of PRDX6 in gastric cancer and normal gastric tissues was tested by immunohistochemistry. Ribonucleic acid plasmid of PRDX6 gene was packaged using a lentivirus, and BGC-823 cells were transfected with the lentivirus to obtain a BGC-823 cell line in which the expression of PRDX6 was stably silenced.Statistical Analysis Used: The proliferation activity of BGC-823 cells was detected using the cell counting kit-8 method. The effect of PRDX6 on the migration and invasion of BGC-823 cells was evaluated using the scratch test and Transwell assay, and the expression of related proteins was detected by western blot.Results: The expression of PRDX6 in gastric cancer was significantly increased (P < 0.05). Compared with those in the untransfected and negative control groups. The proliferation, migration, and invasion of gastric cancer BGC-823 cells were significantly inhibited, and the apoptotic rates were significantly increased in the lentivirus-transfected (short hairpin-PRDX6) group. Western blot analysis showed that the expression of Bax protein increased, whereas that of proliferating cell nuclear antigen, Bcl-2, PI3K, phospho (p-Akt), and phosphorylated-mammalian target of rapamycin (mTOR) decreased significantly compared with that in WT and vector groups (P < 0.05).Conclusion: The knockdown of PRDX6 gene expression in BGC-823 cells can inhibit the proliferation, migration, and invasion of gastric cancer cells and promote apoptosis, thereby affecting gastric cancer cells. [ABSTRACT FROM AUTHOR]

Sports training strategies should be combined with science and technology to design the most suitable coaching strategies for athletes. In the current 5G Internet of Everything, the collection of wireless sensors and the deep learning of neural networks provide a new direction for the formulation of sports training strategies, guiding sports strategies to be more effective and scientific. This article aims to study and formulate sports training strategies, through the empowerment of science and technology, to better guide scientific training. With the help of the collection and sorting of sensors, the neural network allows deep learning of data, realizes human-computer interaction, and allows machines to better serve humans. This paper proposes an interactive control strategy for sports training, which enhances the interactive control of humans and machines and improves the level of training through the deep fusion of data. The experimental results of this article show that the human-computer interaction exercise training can better guide the exercise training and improve the training efficiency by 20%. [ABSTRACT FROM AUTHOR]

Product structural properties are fundamental in product structure optimisation and design. Due to the inevitable evolution of products, product structural properties also change accordingly. Although the evolution of the product structure has been preliminarily investigated, it is mainly analyzed from the viewpoint of commonalities for product generations, and the evolution trend of product structure across product generations has not been well explored. To provide product development direction for designers, this study aims at uncovering the evolution characteristics of product structural properties based on the time-dependent network model. Firstly, weighted time-dependent networks are constructed to represent the cross-generation product structures. Secondly, product structural properties (including complexity, importance, and robustness) are analyzed benefited from topology similarities between product structures and complex networks. Thirdly, 25 generations of iPhones are selected to analyze the evolution characteristics of product structural properties. The results show that in the evolution of product structures, the complexity of the product is decreasing while core components are becoming more complex owing to scale-free property. And the core components are always important in each product generation. Additionally, the evolving product structural networks are highly robust in random failure of components (RFC) and vulnerable in the failure of core components (FCC). [ABSTRACT FROM AUTHOR]

Redesign is a widespread strategy for product improvement whose essence is the optimization of design parameters (DPs) considering the trade-off between customer satisfaction and cost concerns. Similar to the relation between customer requirements (CRs) and customer satisfaction, the sensitivity of customer satisfaction is diverse to different DPs. In this study, a sensitivity-enhanced customer satisfaction function is defined for redesign model construction. This fills the research gap in product redesign that lacking of consideration and quantification of customer satisfaction sensitivity. First, a sensitivity index is defined based on Kano indices for analyzing sensitivity of customer satisfaction in different DP categories. Second, traditional customer satisfaction function has been improved by injecting the sensitivity of customer satisfaction to the variations of DPs. Subsequently, a DP optimization model is established to maximize shared surplus between customers and enterprise. Finally, a case study involving the redesign of a braking system of automobile is implemented to demonstrate the effectiveness and rationality of the proposed approach. The results show that the improved customer satisfaction function can reflect a more nuanced relationship between customer satisfaction and fulfilment level of DPs. Additionally, the proposed redesign model helps designers determine the target values of DPs under a better trade-off and enhances enterprise competitiveness. [ABSTRACT FROM AUTHOR]

Molten salt phase change materials (MSPCMs) provide strong support for the long-term and stable operation of new energy systems. This study focuses on LiNO 3 (high latent heat, low melting temperature), NaNO 3 (an important component in solar salts), and binary eutectic nitrate (LiNaNO 3). The aim is to explore eutectic nitrate that matches lower working temperature requirements by eutectic reaction. The other aim is to enhance the specific heat and thermal conductivity of nitrates by adding nanoparticles (NPs) with different microstructures. The NPs include multi-walled carbon nanotubes (MWCNT), graphene nanoplatelets (GNP), AlN, BN, and SiC. The distribution patterns of nitrate molecules near NPs were investigated under the influence of interaction strength through molecular dynamics. The enhancement of thermal transport is decided by phonon vibrations, interface thermal resistance, and heat pathway. NPs can significantly weaken the melting enthalpy and limit the enhancement of thermal conductivity by disrupting the eutectic microstructure of LiNaNO 3 , which is different from the mechanism of NPs' action on unitary nitrates. MWCNTs exhibit the most significant enhancement in thermal conductivity and specific heat of nitrates, which is due to the diffusion of nitrate molecules in the MWCNT. The in-plane phonon vibrations of GNP contribute slightly to the thermal transport in the vertical plane direction, resulting in limited enhancement of thermal transport. Therefore, we propose principles for selecting NPs doped into eutectic salts, which should ensure that the interaction strength between NPs and both unitary nitrates is similar or that their microscopic structure can maintain the integrity of the eutectic structure. [Display omitted] • The thermal conductivity and specific heat of nitrates were experimentally enhanced with maximum rate of 237.72 %, 95.67 %. • NPs weaken the melting enthalpy of LiNO 3 and NaNO 3 by binding them on the surfaces of NPs. • For LiNaNO 3 , the disruption of eutectic structure by NP will weaken enthalpy and limit enhancement on thermal conductivity. • The diffusion of nitrate molecules inside the structure of MWCNT leads to diverse impact on thermal properties of nitrates. • A principle for selecting NPs doped into eutectic salts is proposed to more effectively enhance heat storage efficiency. [ABSTRACT FROM AUTHOR]

Enterprises are challenged with fulfilling continuously changing customer requirements (CRs) that are influenced by many uncertain factors. Existing research only modelled the dynamics of CRs (DoCRs) by focusing on the potential resultant effects of CR changes, while lacking insightful exploration of the change characteristics of CRs themselves. To fill this gap, an online review-based DoCRs modelling method is proposed considering the lability and sensitivity of CRs by analyzing the changes in customers' perceptions of product features over time. First, CRs in online reviews are extracted through Latent Dirichlet Allocation. Second, Bidirectional Long Short-Term Memory is applied to measure customer sentiments in different periods towards specific product features. The probabilistic linguistic term sets are employed to characterize customer sentiment distributions which are then incorporated into the modelling of DoCRs. Third, a novel CRs classification cube is established by integrating the lability, sensitivity, and importance of CRs from an evolution-adapted perspective. Finally, the DoCRs of a smartphone is investigated as a case study to demonstrate and effectiveness of the proposed methodology. Several managerial implications for the selection and adjustment of product development strategy are provided. [ABSTRACT FROM AUTHOR]

Driven by the evolving customer requirements and the advancement of key technologies, design changes broadly exist in the lifecycle of the complex product. And as a popular engineering management strategy, the modularization strategy has been widely applied in the research and development process of complex products. However, most of the existing modularization methods do not consider the issue of design change management. Under this circumstance, the "avalanche effect" of the design change propagation might be magnified due to the inappropriate modular structure. Thus, to decrease the effect of the design change propagation, a novel modularization method of the complex product is proposed incorporating the modularity and the scope of design change propagation (SDCP). Firstly, considering the functional and physical relationship between components, the correlation matrix that is the adjacency matrix of the related weighted and directed network model is constructed. Secondly, the indexes of modularity and SDCP are defined based on the predetermined network model and correlation matrix, respectively. Thirdly, taking the modularity and the SDCP as the optimization objectives, a bi-objective optimization model is built for the modularization of the complex product, and then the model is solved by the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Finally, the modularization of the cab for a specific electronic sanitation vehicle is implemented as the case study to expound the utility and effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

More and more customers place emphasis on the product obsolescence instead of the product quality, which is driven by changing customer requirements, developing technology and evolving market environments. The product redesign is the prior design strategy to respond to the factors that cause product obsolescence. In this study, the necessary assessment of a product redesign is modelled as the product obsolescence assessment problem based on the Information Axiom. First, the customer-expected functional requirement (FR) and the existing FR of a product are characterised as the design range and the system range, respectively. The information content, which is defined to assess the degree of product obsolescence, is then calculated. In the process of calculating information content, the integral characterised by fuzzy bounds is a challenging problem. To solve this issue, this study proposes a defuzzification method to convert fuzzy bounds into crisp numbers. Finally, the assessment of product obsolescence for a crawler crane is performed as an example to elaborate on the effectiveness of the developed approach. [ABSTRACT FROM AUTHOR]

Geological drilling process is operating under complex geological conditions, which may lead to a high risk of downhole incidents and thus compromise the drilling efficiency. To achieve prompt detection of downhole incidents and prevent them from developing to serious drilling accidents, this paper proposes a new data-driven detection method for downhole incidents based on the amplitude change detection and dynamic time warping. Two major phases are involved: the change monitoring phase detects whether there is any significant change in the drilling signals and extracts variational trend features by linear fitting and amplitude change detection; the incident detection phase determines if the cause of a change is a normal switching or a downhole incident by similarity analysis based on the dynamic time warping and the density-based spatial clustering. Industrial case studies show that the proposed method achieves good performance in downhole incidents detection for geological drilling processes. • This work proposes a new data-driven method to detect downhole incidents. • A change monitoring approach is presented to detect signal amplitude changes. • A similarity analysis technique is developed based on DTW and DBSCAN. [ABSTRACT FROM AUTHOR]

OBJECTIVES Ascending aortic aneurysms pose a different risk to each patient. We aim to provide personalized risk stratification for such patients based on sex, age, body surface area and aneurysm location (root versus ascending). METHODS Root and ascending diameters, and adverse aortic events (dissection, rupture, death) of ascending thoracic aortic aneurysm patients were analysed. Aortic diameter was placed in context vis-a-vis the normal distribution in the general population with similar sex, age and body surface area, by conversion to z scores. These were correlated of major adverse aortic events, producing risk curves with 'hinge points' of steep risk, constructed separately for the aortic root and mid-ascending aorta. RESULTS A total of 1162 patients were included. Risk curves unveiled generalized thresholds of z  = 4 for the aortic root and z  = 5 for the mid-ascending aorta. These correspond to individualized thresholds of less than the standard criterion of 5.5 cm in the vast majority of patients. Indicative results include a 75-year-old typical male with 2.1 m2 body surface area, who was found to be at increased risk of adverse events if root diameter exceeds 5.15 cm, or mid ascending exceeds 5.27 cm. An automated calculator is presented, which identifies patients at high risk of adverse events based on sex, age, height, weight, and root and ascending size. CONCLUSIONS This analysis exploits a large sample of aneurysmal patients, demographic features of the general population, pre-dissection diameter, discrimination of root and supracoronary segments, and statistical tools to extract thresholds of increased risk tailor-made for each patient. [ABSTRACT FROM AUTHOR]

Identifying defective design elements is a prerequisite for design improvements. Previous identification methods were implemented in the context of static customer requirements (CRs). However, CRs always evolve continuously, which easily leads to a failure of existing product functions in fulfilling customer expectations; this, in turn, can lead to a decline in customer satisfaction. In this study, the phenomenon is termed as 'function obsolescence', and a data-driven identification approach for obsolete functions is proposed for design improvements. Firstly, product operating data are employed to construct the observing parameters of functional performance (OPs), and based on the distribution of OPs, the desired level of functional performance (DL) is defined to quantitatively characterise CRs. Secondly, the time series of DL is constructed to embody the evolution of CRs, in which a Sigmoid-like function is employed to establish a dissatisfaction function. With the time series, an obsolescence index measuring the severity of obsolescence for each function is defined to identify obsolete functions. A case study was implemented on a smart phone to identify its obsolete functions to demonstrate the effectiveness of the proposed methodology. The results show that some potentially obsolete functions can be identified by the proposed method considering the evolution of CRs. [ABSTRACT FROM AUTHOR]

Topological materials and topological phases have recently become a hot topic in condensed matter physics. In this work, we report an In-intercalated transition-metal dichalcogenide In x TaSe 2 (named 112 system), a topological nodal-line semimetal in the presence of both charge density wave (CDW) and superconductivity. In the x = 0.58 sample, the 2 × 3 commensurate CDW (CCDW) and the 2 × 2 CCDW are observed below 116 and 77 K, respectively. Consistent with theoretical calculations, the spin–orbital coupling gives rise to two twofold-degenerate nodal rings (Weyl rings) connected by drumhead surface states, confirmed by angle-resolved photoemission spectroscopy. Our results suggest that the 2 × 2 CCDW ordering gaps out one Weyl ring in accordance with the CDW band folding, while the other Weyl ring remains gapless with intact surface states. In addition, superconductivity emerges at 0.91 K, with the upper critical field deviating from the s-wave behavior at low temperature, implying possibly unconventional superconductivity. Therefore, we think this type of the 112 system may possess abundant physical states and offer a platform to investigate the interplay between CDW, nontrivial band topology and superconductivity. [ABSTRACT FROM AUTHOR]

• PI-based and PDMS-based membrane units are integrated to reclaim LNG vent stream. • Dual-membrane synergism is verified during concurrent helium and methane recovery. • Helium recovery can be economically enhanced to 99.8% by the integrated system. • LNG harvest can be enhanced by 9.7% with the dual-membrane integrated system. • Benefit can be doubled by retrofitting LNG plants with the dual-membrane system. The residual gases emitted after natural gas liquefaction are the major sources for industrial helium generation. Besides, methane remaining in these streams is valuable for reclamation. In order to make sufficient and efficient utilization, multi-membrane integrated processes, in which both the glassy and the rubbery polymeric membranes are invested for significant tasks, meanwhile they are synergistic with each other under specific process frameworks, are established in this research. Furthermore, the multi-membrane separation unit is meticulously integrated with the flash-vaporization units to reduce nitrogen accumulation during cryogenic operation. Based on the classical LNG plant using two-stage flash-vaporization units, in which the feedstock is about 4780 Nm3/h in flow rate and 0.174 mol% in helium content, the customized multi-membrane process behaved excellent with helium recovered by 99.8% and concurrently LNG harvest increased by 9.7%. The economical assessment revealed that the annual gross benefit can be strikingly increased by 25.16 million CNY, while the annual operation cost is increased by only about 3.96 million CNY, and the additional investment for membrane unit is about 5.48 million CNY, respectively. On the whole, the multi-membrane integrated system using the glassy and the rubbery polymeric membranes synergistically should be a highly promising approach to reclaim valuable components in the residual gases after natural gas liquefaction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Seven unprecedented spirooxindole alkaloids were obtained from the stem barks of Voacanga Africana. • 1 and 2 possess a unique indoleone system in conjugation with a 3,4ʹ-decahydroquinoline spiral ring originating from the seco-quinolhiddin core of the precursor. • Compounds 1 and 7 showed potent activity against MBLs producing E. coli 298 and 140, respectively. • Possible interaction sites of compounds 1 and 7 with membrane protein Bap were preliminarily explored by means of molecular docking. Seven rarely spirooxindole alkaloids, voagafricines A-G (1 – 7) were isolated from the stem barks of Voacanga africana. Their structures were unambiguously elucidated by comprehensive spectroscopic data and electronic circular dichroism (ECD) analyses. 1 and 2 possess a unique indoleone system in conjugation with a 3,4ʹ-decahydroquinoline spiral ring originating from seco-quinolhiddin core of the precursor, furthermore 1 undergo decarburization formed a novel C-3-nor monoterpenoid indole. All isolates were evaluated for their antibacterial activities against MBLs producing Escherichia coli strains. Compounds 1 and 7 were found to be potent inhibitors against E. coli 298 and 140 by targeting biofilm. Possible interaction sites of 1 and 7 with biofilm were preliminarily explored by means of molecular docking. [ABSTRACT FROM AUTHOR]

Inspired by the antireflection and antiwetting functionalities of dragonfly wings decorated with random nanopillars and a wax layer, a facile technique to endow the same functionalities has been devised. In this two‐step plasma nanotexturing technique, first oxygen plasma treatment is implemented to grow the random nanopillars on the polymethyl methacrylate (PMMA) surfaces, and then C4F8 plasma polymer deposition is carried out so that the thin fluorocarbon film with a low surface free energy and refraction index covers the random nanopillars. The biomimetic PMMA surfaces exhibit excellent broadband and omnidirectional antireflection properties and robust antiwetting properties under the water droplet impact. The superhydrophobicity at the slippery Cassie state was maintained under the natural oscillation of residual droplets. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) has become a global emerging infectious disease. Objectives: To analyze the initial clinical characteristics of COVID-19 suspected and confirmed patients on admission in order to find out which kinds may be more likely to get positive nucleic acid testing results, and to explore the risk factors associated with all-cause death. Methods: Medical records from 309 highly suspected cases with pneumonia were collected from February 13, 2020, to March 14, 2020, in a COVID-19-designated hospital of Wuhan. The majority of the clinical data were collected on the first day of hospital admission. Results: Of 309 patients with median age 64 years (interquartile ranges [IQR], 53–72 years), 111 patients (35.9%) were confirmed by nucleic acid testing (median age 64 years, IQR: 56–71 years; 48 males). Of those 111 patients, 13 (11.7%) patients died. In multivariate analysis, factors associated with positive testing included fatigue (odds ratios [OR] = 3.14; 95% confidence interval [CI]: 1.88–5.24, p < 0.001), cough (OR = 0.55; 95% CI: 0.32–0.95, p = 0.032), no less than 1 comorbidity (OR = 1.77; 95% CI: 1.06–2.98, p = 0.030), and severe pneumonia (OR = 2.67; 95% CI: 1.20–5.97, p = 0.016). Furthermore, age, dyspnea, noneffective antibiotic treatment, white blood cell, lymphocyte, platelets, and organ dysfunction (e.g., higher lactate dehydrogenase) were significantly associated with all-cause in-hospital death in patients with COVID-19. Conclusion: Patients with severe forms of this disease were more likely to get positive results. Age and organ dysfunction were associated with a greater risk of death. [ABSTRACT FROM AUTHOR]

In deep geological drilling processes, the geological environment becomes more complex with the increasing of the drilling depth; consequently, the risks of downhole incidents get higher. If not discovered in time, these downhole incidents may develop to serious drilling accidents, causing significant financial and environmental losses. In this paper, a new method is proposed to diagnose downhole incidents by extracting trend features in multi-time scales and establishing a probabilistic neural network based diagnosis model. There are two major contributions: First, a feature extraction method is proposed to produce trend features from original process signals in different time scales; Second, an incident diagnosis method based on a broad probabilistic neural network is proposed to achieve better diagnosis performance in an expanded input space. Industrial case studies are presented to demonstrate the effectiveness and practicability of the proposed method. Results show that the proposed method has superior performance in diagnosing downhole incidents for geological drilling processes. [ABSTRACT FROM AUTHOR]

In the year 2015-2018, there are many sub- and super-synchronous interaction (S $^2$ SI) events, happened in China. However, traditional transient stability models, electro-magnetic transient (EMT) models and hybrid TS and EMT simulation methods fail to capture the desired wide frequency band interactions between large-scale AC grids and wind farms. To accurately and efficiently capture wide frequency band interactions between AC grids and wind farms, a simulation method which can extend the time-step to 500  $\mu$ s and further adopt the multi-rate structure is highly required. For this objective, we propose a multi-rate co-simulation method, in which the target system is partitioned into electro-magnetic transient (EMT) and shifted frequency phasor (SFP) subsystems, represented by our proposed transformation based SFP models and the traditional EMT models, respectively. The simulation efficiency of simulating large-scale AC grids is significantly improved by adopting a much larger time-step. Further, the multi-rate multi-domain transmission-line model (MD-TLM) and the multi-rate frequency dependent MD-TLM are respectively proposed to reflect wide-band interactions between AC grids and wind farms. Eventually, the multi-rate co-simulation is implemented based on the efficient SFP models, network partitioning, and so-called the multi-rate (FD)-MD-TLM. The performance (efficiency and accuracy) of the proposed method has been fully validated on a practical system integrating large AC grids and wind farms. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a chronic, remitting, and relapsing, inflammatory disease involving multiple organs, which exhibits abnormalities of both the innate and adaptive immune responses. A limited number of transcriptomic studies have characterized the gene pathways involved in SLE in an attempt to identify the key pathogenic drivers of the disease. In order to further advance our understanding of the pathogenesis of SLE, we used a novel Bayesian network algorithm to hybridize knowledge- and data-driven methods, and then applied the algorithm to build an SLE gene network using transcriptomic data from 1,760 SLE patients' RNA from the two tabalumab Phase III trials (ILLUMINATE-I & -II), the largest SLE RNA dataset to date. Further, based on the gene network, we carried out hub- and key driver-gene analyses for gene prioritization. Our analyses identified that the JAK-STAT pathway genes, including JAK2, STAT1, and STAT2, played essential roles in SLE pathogenesis, and reaffirmed the recent discovery of pathogenic relevance of JAK-STAT signaling in SLE. Additionally, we showed that other genes, such as IRF1, IRF7, PDIA4, FAM72C, TNFSF10, DHX58, SIGLEC1, and PML, may be also important in SLE and serve as potential therapeutic targets for SLE. In summary, using a hybridized network construction approach, we systematically investigated gene-gene interactions based on their transcriptomic profiles, prioritized genes based on their importance in the network structure, and revealed new insights into SLE activity. [ABSTRACT FROM AUTHOR]

The char-O 2 /H 2 O combustion under high-temperature entrained flow conditions was investigated experimentally and numerically to study the effect of H 2 O on the char-nitrogen (char-N) conversion. A numerical model was established based on the unsteady convection–diffusion equations for mass and heat transfer. Local Random Pore Model (RPM) was adopted to consider the change of specific surface area during char combustion. The Langmuir-Hinshelwood mechanism was used in the rate equations of main heterogeneous reactions to consider the competitions on surface active sites. The numerical results of char conversion and fractional conversion of char-N to NO reproduce the experimental results well. Both of the numerical and experimental results shows that the added H 2 O promotes the fractional conversion of char-N to NO and the promotion effect becomes weaker with the increase of O 2 concentration. Based on numerical results, four crucial factors that affect char-N conversion were decoupled and discussed quantitatively with addition of H 2 O. The added H 2 O promotes nitrogen release rate at lower oxygen concentration but inhibits nitrogen release rate at higher oxygen concentration. The added H 2 O lowers the heterogeneous char-NO reduction rate constant greatly but enlarges the pore surface area slightly, resulting in a lower overall heterogeneous char-NO reduction rate. Char-NO reaction is the main NO reduction pathway, and most of HCN formed in char-N–H 2 O reaction is more likely to release out of char particle and converts to NO through HCN→NH 3 →NO pathway in the ambient flow. [ABSTRACT FROM AUTHOR]

As reported in previous studies, global warming has caused a clear uptick in dryland areas since the 1950s. Meanwhile, the accelerated expansion of drylands has become particularly evident over the past 40 years, with dry/wet patterns showing significant differences prior to and after 1980. This paper uses the Precipitation/Potential evaporation (P/PET) index to analyze changes occurring in the dry/wet structure of various spatial and temporal scales during 1948–2008. The results show the emergence of complex aridity changes on a regional scale. While aridity generally decreased in the drylands of Asia during 1948–2008, the change in aridity was opposite in the drylands of the American and African continents between 1948 and 1979 and 1980–2008. Specifically, drylands in the American continent showed a wetting tendency during 1948–1979 and a drying tendency during 1980–2008, whereas drylands in the African continent underwent significant drying during 1948–1979 followed by subtle wetting in 1980–2008. Even though rapid warming since the 1980s has become an increasingly important cause of the recent global drying trend, especially in East and Central Asia, the changes in aridity in the American and African drylands is attributable to natural variabilities in precipitation associated with multi-decadal surface sea temperature changes, along with large-scale circulation patterns. • Dry/wet patterns in dryland areas show significant differences in the decades prior to and after 1980. • The change in aridity was opposite in American and African drylands between 1948–1979 and 1980–2008. • Aridity changes in American and African drylands are closely related to multi-decadal changes in surface sea temperature. [ABSTRACT FROM AUTHOR]

Accurate and timely fault diagnosis is a vital task to ensure process safety of modern industrial facilities. Motivated by the complex variations of process signals and mutual coupling of faults, this paper presents a multi-feature-based fault diagnosis method based on the weighted timeliness Broad Learning System (BLS). The proposed method fuses multiple features extracted from the original process data to improve the fault diagnosis performance, and makes the diagnosis model suitable for dynamic fault diagnosis problems by incorporating the BLS. The major contributions of this study are twofolds: 1) A systematic multi-feature extraction method is proposed to extract long-term trend features, short-term trend features, and binary alarm signals, which reflect the direction and amplitude changes of process signals under faulty conditions; 2) a weighted timeliness BLS structure with multiple fault-sensitive features as the input is proposed to ensure the dynamic characteristics of the fault diagnosis model. The designed fault diagnosis model can be updated in an incremental manner, and thus can improve the model updating efficiency while ensuring accuracy. The effectiveness and superiority of the proposed method is demonstrated by a case study based on the Tennessee Eastman benchmark process. [ABSTRACT FROM AUTHOR]

In online shopping, competitive product identification and evaluation (CPIE) are becoming indispensable for customers before making purchase decisions. Online user-generated content (UGC), as a common way of expressing customers' opinions or preferences toward products, is a key proxy for CPIE. Some studies have performed CPIE by the descriptive information in online reviews, while still lacking the exploration of comparative information, which is essential for potential customers to compare alternatives and usually embedded in online Questions & Answers (Q&As). In this study, a framework for CPIE based on multi-type information in online UGC is proposed. First, the competitive products toward a target product are identified from the comparative Q&As according to the co-occurrence of product names. Second, the descriptive information and comparative information which derived from online reviews and comparative Q&As, respectively, are integrated by constructing a comparative network. The nodes and edges in the comparative network represent the products and competitive relationships, respectively. The holistic evaluation of competitive products is accomplished through the PageRank algorithm. Finally, the empirical analysis is illustrated to verify the feasibility and effectiveness of the proposed method, and a system prototype of the CPIE is designed and developed to facilitate the purchase decisions for customers. [ABSTRACT FROM AUTHOR]

Ridge-furrow film mulching (RFFM) and nitrogen (N) fertilization have been widely used in semi-arid regions, it is particularly important to clarify the mechanism of crop physiological indicators in response to RFFM. A two-year (2018 and 2019) field experiment was conducted on summer maize under RFFM (including biodegradable film mulching (B) and plastic film mulching (P)) at N fertilizer application rate of 0 (N0), 90 (N1), 180 (N2) and 270 (N3) kg N ha–1. The aims of this research were to 1) explore the effects of different film mulching and N application rates under RFFM on photosynthesis, water utilization, and yield; 2) identify key factors and their contribution to yield. The results showed that RFFM and nitrogen application significantly improved net photosynthesis rate (P n), stomatal conductance (G s), transpiration rate (T r), intrinsic water use efficiency (WUE i) (grain-filling stage), the maximum quantum yield of PSII photochemistry (F v / F m), energy transformation potential activities of PSII (F v / F o), the effective quantum yield of PSII photochemistry (Φ PSII), photochemical quenching of variable chlorophyll fluorescence (qP), non-photochemical chlorophyll fluorescence quenching (NPQ), chlorophyll ab (Chl ab), evapotranspiration (ET) and yield, but decreased chlorophyll a/b (Chl a/b) and soil water storage (SWS). The maximum P n , T r , G s , WUE i , F v / F m. F v / F o , Φ PSII , qP , and Chl ab (anthesis stage) all appeared in N2. At the same N application rate, the positive effects on photosynthetic and chlorophyll fluorescence (ChlF) of the plastic film were better than biodegradable film, especially in water use efficiency (WUE). Nitrogen deficiency had significantly negative effects on various parameters (Photosynthetic parameters, ChlF, Chl ab, grain yield), while nitrogen application (N > N1) had strong positive effects. Photosynthetic parameters, F v / F m , F v / F o , NPQ , Chl ab, ET, and WUE had strong positive effects on yield. The grain yield of the plastic film were slightly better (5.03% on average) than biodegradable film, but from the perspective of sustainable development, we recommend that biodegradable film and N2 should be used in the semi-arid regions of China. • Four N rates were applied to summer maize under ridge-furrow with polyethylene film and biodegradable film mulching. • RFFM and N application significantly improved Photosynthetic parameters, ChlF, and yield, but decreased Chl a/b and SWS. • Photosynthetic parameters, F v / F m , F v / F o , NPQ , Chl ab, ET and WUE had strong positive effects on yield. [ABSTRACT FROM AUTHOR]