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As a new type of inorganic ductile semiconductor, silver sulfide (α-Ag2S) has garnered a plethora of interests in recent years due to its promising applications in flexible electronics. However, the lack of detailed defect calculations and chemical intuition has largely hindered the optimization of material's performance. In this study, we systematically investigate the defect chemistry of extrinsic doping in α-Ag2S using first-principles calculations. We computationally examine a broad suite of 17 dopants and find that all aliovalent elements have extremely low doping limits (

Abstract The Fenshui River Bridge is a steel–concrete composite girder bridge with a main span of 90 m. Due to the topographical constraints, the steel box girder was constructed without the use of auxiliary piers, employing incremental launching techniques. This article focuses on the construction technology used for the steel box girder of the Fenshui River Bridge. Firstly, using the influence matrix method, the cable force is determined based on the maximum cantilever state of the structure, with the vertical deformation of the front end of the guide beam and the horizontal deformation of the top of the tower as the control objectives. The unstressed cable length is then calculated based on the mechanical relationship between cable deformation and cable force. A calculation method for adaptive cable force is proposed, which is based on the variation of the stress-free cable length within the adaptive structural system. Next, the finite element analysis method was employed to determine the optimal layout position for the tower. The results indicate that during the incremental launching construction of the steel box girder, the calculated cable forces using the method proposed in this paper are in close agreement with the measured cable forces. At the maximum cantilever state of the structure, the calculated and measured values of the cable force resulted in a percentage difference of 3.96%. The calculated values of deformation and stress in key sections showed a percentage difference of 6.4% for deformation and 6.6% for stress. To maximize the effectiveness of the tower and cable, the tower should be positioned above the bridge pier when the guide beam crosses the maximum span. The findings of this paper can serve as a reference for the construction of similar types of bridges.

Abstract Grain boundary plays a vital role in thermoelectric transports, leading to distinct properties between single crystals and polycrystals. Manipulating the grain boundary to realize good thermoelectric properties in polycrystals similar as those of single crystals is a long-standing task, but it is quite challenging. Herein, we develop a liquid-phase sintering strategy to successfully introduce Mg2Cu nano-sintering-aid into the grain boundaries of Mg3(Bi, Sb)2-based materials. The nano-aid helps to enlarge the average grain size to 23.7 μm and effectively scatter phonons, leading to excellent electrical transports similar as those of single crystals and ultralow lattice thermal conductivity as well as exceptional thermoelectric figure of merit (1.5 at 500 K) and conversion efficiency (7.4% under temperature difference of 207 K). This work provides a simple but effective strategy for the fabrication of high-performance polycrystals for large-scale applications.

Exploring new prototypes for a given chemical composition is of great importance and interest to several disciplines. As a famous semiconducting binary compound, InSe usually exhibits a two-dimensional layered structure with decent physical and mechanical properties. However, it is less noticed that InSe can also adopt a monoclinic structure, denoted as mcl-InSe. The synthesis of such a phase usually requires high-pressure conditions, and the knowledge is quite scarce on its chemical bonding, lattice dynamics, and thermal transport. Here in this work, by developing a facile method combining mechanical alloying and spark plasma sintering, we successfully synthesize mcl-InSe bulks with well-crystallized nanograins. The chemical bonding of mcl-InSe is understood as compared with layered InSe via charge analysis. Low cut-off frequencies of acoustic phonons and several low-lying optical modes are demonstrated. Noticeably, mcl-InSe exhibits a low room-temperature thermal conductivity of 0.6 W·m−1·K−1, which is smaller than that of other materials in the In–Se system and many other selenides. Low-temperature thermal analyses corroborate the role of nanograin boundaries and low-frequency optical phonons in scattering acoustic phonons. This work provides new insights into the non-common prototype of the InSe binary compound with potential applications in thermoelectrics or thermal insulation.

With the frequent occurrence of natural disasters, the problem of dam failure with low probability and high risk has gradually attracted people's attention. This paper uses flume model tests to systematically analyze the overtopping failure mechanisms of concrete face rockfill dam (CFRD) and identify its failure modes. The tests reveal that the longitudinal erosion of the CFRD breach progress through stages of soil erosion, panel failures, and water flow stabilization. Meanwhile, the cross-section breach process involves the evolution of breach size in rockfill materials, including traceable erosion, lateral broadening, and breach morphology stabilization. The fracture characteristics of the water-blocking panel are primarily evident in the flow-time curve. By analyzing the breach morphology evolution processes in longitudinal and cross sections, the flow-time curve can be subdivided into stages of burst flow formation, breach expansion with flow increase, rapid increase of breach flow discharge due to panel failures, and stabilization of breach flow and size. The primary damage process of the CFRD occurs in a cyclical stage of breach expansion, flow increase, panel failure, and rapid discharge. The rigid face plate and granular body structure contribute to partial dam failure, showing a tendency for gradual expansion of the breach. The longitudinal section illustrates dam failure resulting from panel fracture and rockfill erosion interaction, while downstream slopes exhibit failure due to lateral intrusion of rockfill and cyclic instability. These research results can serve as a reference for constructing a concrete CFRD failure prediction model and conducting disaster risk assessments.

Accurately estimating the dolomite content in carbonate rocks is crucial for optimizing oil and gas exploration and production strategies. Hyperspectral techniques for estimating dolomite content have advantages in terms of efficiency, cost-effectiveness, and non-destructiveness compared with traditional laboratory methods. Despite the abundance of hyperspectral data, feature selection and extraction remain challenging. In this study, hyperspectral data collected from surface outcrop in the field using the analytical spectral device (ASD) were applied to construct model for estimating dolomite content. Firstly, the data were preprocessed via outlier analysis and continuum transformation. Next, a hybrid approach integrating spectral knowledge with machine learning was proposed and applied to facilitate efficient and precise feature selection of the hyperspectral data; in this approach, preliminary screening based on spectral knowledge is followed by further hyperspectral data feature selection using a random forest algorithm. The selected features were then combined using a support vector regression algorithm to obtain the estimation model. Finally, the accuracy of the model was evaluated using the hyperspectral data from field outcrop samples. To further verify the effectiveness of this method, various combinations of eight input variables and four machine learning algorithms were compared. Among all combinations, our model achieved the highest accuracy with a test R2 value of 0.91 and a root-mean-square error of only 0.122. The proposed method is practical and efficient and provides precise quantitative data for field geologists to identify the mineral distribution in outcrops. Thus, our method provides robust support for understanding reservoir characteristics and has significant practical value in geological surveys and mineral exploration.

Abstract Critical phenomena are one of the most captivating areas of modern physics, whereas the relevant experimental and theoretical studies are still very challenging. Particularly, the underlying mechanism behind the anomalous thermoelectric properties during critical phase transitions remains elusive, i.e., the current theoretical models for critical electrical transports are either qualitative or solely focused on a specific transport parameter. Herein, we develop a quantitative theory to model the electrical transports during critical phase transitions by incorporating both the band broadening effect and carrier-soft TO phonon interactions. It is found that the band-broadening effect contributes an additional term to Seebeck coefficient, while the carrier—soft TO phonon interactions greatly affects both electrical resistivity and Seebeck coefficient. The universality and validity of our model are well confirmed by experimental data. Furthermore, the features of critical phase transitions are effectively tuned. For example, alloying S in Cu2Se can reduce the phase transition temperature but increase the phase transition parameter b. The maximum thermoelectric figure of merit zT is pushed to a high value of 1.3 at the critical point (377 K), which is at least twice as large as those of normal static phases. This work not only provides a clear picture of the critical electrical transports but also presents new guidelines for future studies in this exciting area.

Abstract The flexible thermoelectric technique, which can convert heat from the human body to electricity via the Seebeck effect, is expected to provide a peerless solution for the power supply of wearables. The recent discovery of ductile semiconductors has opened a new avenue for flexible thermoelectric technology, but their power factor and figure-of-merit values are still much lower than those of classic thermoelectric materials. Herein, we demonstrate the presence of morphotropic phase boundary in Ag2Se-Ag2S pseudobinary compounds. The morphotropic phase boundary can be freely tuned by adjusting the material thermal treatment processes. High-performance ductile thermoelectric materials with excellent power factor (22 μWcm−1 K−2) and figure-of-merit (0.61) values are realized near the morphotropic phase boundary at 300 K. These materials perform better than all existing ductile inorganic semiconductors and organic materials. Furthermore, the in-plane flexible thermoelectric device based on these high-performance thermoelectric materials demonstrates a normalized maximum power density reaching 0.26 Wm−1 under a temperature gradient of 20 K, which is at least two orders of magnitude higher than those of flexible organic thermoelectric devices. This work can greatly accelerate the development of flexible thermoelectric technology.

GeSb2Te4 (GST124), one of the well‐known phase‐change materials for nonvolatile memory and rewritable optical storage, has been recently found to be promising thermoelectric materials with low lattice thermal conductivity and high electrical conductivity. However, its thermoelectric performance is greatly restricted by the excessively high hole concentration. Herein, the impact of a series of group IIIA (Al, Ga, In) and group VIA (S, Se) dopants on the electrical transport properties of polycrystalline GST124 has been studied. It is found that element sulfur (S) has the best doping efficiency because the GeS bonds are very strong and ionic that are beneficial for suppressing Ge vacancies to reduce the carrier concentration. Meanwhile, element indium (In) also shows decent doping efficiency because its ionic radius is close to the Ge ion and the InTe bonds have moderate bonding strength. Moreover, In doping introduces a resonant level in the valence band, leading to enhanced Seebeck coefficient and power factor. A high figure of merit (zT)of 0.73 at 700 K and an average zT of 0.48 over 300–750 K are obtained in Ge0.92In0.08Sb2Te4, which are 26% and 66% higher than pristine GST124. This study will advance the understanding and development of high‐performance GeSbTe‐based thermoelectric materials.

Changes in soybean flower and pod numbers are important factors affecting soybean yields. Obtaining the number of flowers and pods, as well as fallen flowers and pods, quickly and accurately is crucial for soybean variety breeding and high-quality and high-yielding production. This is especially challenging in the natural field environment. Therefore, this study proposed a field soybean flower- and pod-detection method based on an improved network model (YOLOv8-VEW). VanillaNet is used as the backbone feature-extraction network for YOLOv8, and the EMA attention mechanism module is added to C2f, replacing the CioU function with the WIoU position loss function. The results showed that the F1, mAP, and FPS (frames per second) of the YOLOv8-VEW model were 0.95, 96.9%, and 90 FPS, respectively, which were 0.05, 2.4%, and 24 FPS better than those of the YOLOv8 model. The model was used to compare soybean flower and pod counts with manual counts, and its R2 for flowers and pods was 0.98311 and 0.98926, respectively, achieving rapid detection of soybean flower pods in the field. This study can provide reliable technical support for detecting soybean flowers and pod numbers in the field and selecting high-yielding varieties.

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6.

Indium selenide (InSe) crystals are reported to show exceptional plasticity, a new property to two-dimensional van der Waals (2D vdW) semiconductors. However, the correlation between plasticity and specific prototypes is unclear, and the understanding of detailed plastic deformation mechanisms is inadequate. Here three prototypes of InSe are predicted to be plastically deformable by calculation, and the plasticity of polymorphic crystals is verified by experiment. Moreover, distinct nanoindentation behaviors are seen on the cleavage and cross-section surfaces. The modulus and hardness of InSe are the lowest ones among a large variety of materials. The plastic deformation is further perceived from chemical interactions during the slip process. Particularly for the cross-layer slip, the initial In-Se bonds break while new In-In and Se-Se bonds are newly formed, maintaining a decent interaction strength. The remarkable plasticity and softness alongside the novel physical properties, endow InSe great promise for application in deformable and flexible electronics.

To explore the effect of pore precipitation freezing in different saturated states on mechanical performance for drainage asphalt pavement, the study revealed the freezing behavior characteristics of pore precipitation in different saturated states by combining CT scanning, FEM simulation and mechanical tests. Firstly, the real spatial structure of drainage asphalt mixture was obtained through the CT scanning, and the corresponding FEM simulation model was established. Secondly, the process of pore precipitation freezing in different saturated states was simulated and analyzed, and its influence on the spatial structure of drainage asphalt mixture was obtained. Finally, the effect of pore precipitation freezing in different saturated states on drainage asphalt mixture was proved through mechanical tests. It is found that the effect of pore precipitation freezing on mechanical performance of drainage asphalt mixture is different under different saturated states. With the increase of saturation state, the influence of pore precipitation freezing becomes more obvious, and the difference of stress-strain distribution in spatial structure for drainage asphalt mixture is more prominent. The study explains how pore precipitation freezing in different saturated states affects the mechanical performance for drainage asphalt pavement, providing a theoretical basis for enhancing its durability.

Objective: To explore the dynamic accumulation characteristics of 10 inorganic elements including Mg, Ca, V, Mn, Fe, Co, Ni, Cu, Zn and Ba in Astragalus membranaceus at different growth stages, and determine the optimal harvesting period. Methods: Collected Astragalus membranaceus form different growth stages and determined its element contents by inductively coupled plasma mass spectrometry(ICP-MS), then analyzed its changes and accumulation rule by one-way ANOVA, principal component analysis(PCA), orthogonal projections to latent structures discriminant analysis(OPLS-DA) and correlation analysis. Results: The contents of 10 elements of Astragalus membranaceus at different growth stages were significantly different. The contents of Mg, Ca, V, Mn, Fe, Ni, Cu and Co reached the peak in October, and Ba reached the peak in June. The contents of above element were the lowest in August. The content of Zn in September was significantly higher and in July was significantly lower than that in other growing seasons (P

Background: Collagen-related cell adhesion molecules (CAMs) are a major component of the extracellular matrix (ECM) and often accumulate in the liver during chronic liver disease or hepatocellular carcinoma (HCC). In this study we identified several promising collagens related to CAMs that may be of clinical use for the diagnosis and prognosis of HCC. Methods: We obtained multi-omics data including RNA sequencing (RNA-Seq) data, microarray data, proteomic data from the TCGA, GEO databases, GTEx, and NODE. Bioinformatics analyses were then performed to investigate correlations between the expression patterns of significant genes and HCC. Tumor tissue and para-cancerous tissue samples from HCC patients were also used to validate the results using RT-PCR. Results: A literature research and LASSO-COX analysis identified three significant collagen-related CAM genes: SERPINH1, DCN, and ITGB1. Immunohistochemistry images in the Human Protein Atlas Project database showed that SERPINH1 and ITGB1 proteins were moderately or highly expressed in HCC tumor tissues compared to para-cancerous tissue, whereas DCN expression was lower in HCC tumor tissue. These results were validated by RT-PCR. Low- and high-risk groups of HCC patients were distinguished by the logistic panel in the TCGA database. These showed significantly different prognosis, clinicopathological features, and immune cell infiltration. Logistic regression was used to construct predictive models based on the individual expression levels of DCN, SERPINH1, and ITGB1. These showed highly accurate diagnostic ability (AUC = 0.987). Conclusions: The current findings suggest that the collagen-related CAMs DCN, SERPINH1, and ITGB1 may be potential therapeutic targets in HCC. Logistic panels of DCN, SERPINH1 and ITGB1 could serve as non-invasive and effective diagnostic biomarkers for HCC. Clinical Trial registration: Identifier: NCT03189992. Registered on June 4, 2017. Retrospectively registered (https://clinicaltrials.gov/).

Compared to traditional actuators (such as piezoelectric ceramics), metal actuators possess the advantages of a low energy consumption, large strain amplitude, and high strain energy density. However, most of the existing metal actuators with an excellent comprehensive performance are composed of precious metals, which are limited by high costs and have almost no possibility for large-scale production in the future. This study focuses on non-precious metal materials and exploits a one-step chemical dealloying method to prepare bulk nanoporous (NP) CoCuAl actuators (NP-CCA) from Al70Co20Cu10 alloy. The microstructure and actuation properties of the NP-CCA were analyzed in detail. The dense continuous nanoscale pores provide an excellent network connectivity for a large strain response, enabling the NP-CCA to achieve a strain amplitude of up to 1.19% (more than eight and two times that of NP-Pt and NP-Ag, respectively), comparable to precious metal actuators. In addition, the NP-CCA possesses a high strain energy density, which is prominent in many precious metal actuation materials (such as NP-Au, NP-Ag, and NP-Pt).

Cohesive particulate flows play an important role in environmental fluid dynamics, as well as in a wide variety of civil and process engineering applications. However, the scaling laws, constitutive equations and continuum field descriptions governing such flows are currently less well understood than for their non-cohesive counterparts. Grain-resolved simulations represent an essential tool for addressing this shortcoming, along with theoretical investigations, laboratory experiments and field studies. Here we provide a tutorial introduction to simulations of fine-grained sediments in viscous fluids, along with an overview of some representative insights that this approach has yielded to date. After a brief review of the key physical concepts governing van der Waals forces as the main cohesive effect for subaqueous sediment suspensions, we discuss their incorporation into particle-resolved simulations based on the immersed boundary method. We subsequently describe simulations of cohesive particles in several model turbulent flows, which demonstrate the emergence of a statistical equilibrium between the growth and break-up of aggregates. As a next step, we review the influence of cohesive forces on the settling behaviour of dense suspensions, before moving on to submerged granular collapses. Throughout the article, we highlight open research questions in the field of cohesive particulate flows whose investigation may benefit from grain-resolved simulations.

Variations in soil aggregates and soil organic carbon (SOC) in response to land-use change are important to understanding the carbon cycle in forest ecosystems. However, few studies investigated the effect of forest type on aggregate stability, SOC content, and particulate organic carbon (POC) content. Therefore, we collected soil and fine root samples in two natural forests (Pinus massoniana and Quercus variabilis) and a planted forest (Cunninghamia lanceolata) in a warm temperate–subtropical climate transition zone to analyze the effect of forest type on aggregate stability, SOC content, and POC content. The results showed that the mean weight diameter (MWD) of the soil aggregates was significantly higher in Quercus variabilis and Pinus massoniana forests (62% and 21%, respectively) than in the Cunninghamia lanceolata forest due to higher mycelial length density, mycelial infection rate, and glomalin content. Similarly, the SOC and POC contents were significantly higher in Quercus variabilis and Pinus massoniana forests than in the Cunninghamia lanceolata forest (p < 0.05). The dominant size fraction of aggregate was highly correlated with the carbon fraction content. The SOC and POC contents and fungal traits (mycelial length density, mycelial infection rate, and glomalin content) were significantly positively correlated with the MWD. These results indicated that natural forests had higher aggregate stability than planted forests due to higher SOC content and more favorable fungal traits in the warm temperate–subtropical climate transition zone.

On the basis of the analysis on the circular-arc-tooth-trace cylindrical gear， the geometrical parameters of involute elliptic-arc-tooth-trace cylindrical gear are expounded. It can be concluded that the tooth profiles remain the same involute on any vertical axis section， its tooth thickness is equal to the slot width on the different vertical axis section of the gear teeth， and pressure angle at the reference circle is equal， the expanded tooth trace on reference cylinder is a symmetrical elliptical arc. The equations of tooth surface， transverse tooth profile and contact curve are derived. Meantime， the tilting rotary cutter processing method is proposed. The models of the gear special cutters are established in VERICUT. The elliptic-arc-tooth-trace cylindrical gear machined by the tilting rotary cutter processing method is carried out by VERICUT machining simulation. The contact curve characteristics of the gear pair are analyzed by using the gear models obtained from the simulation. The results show that the elliptic-arc-tooth-trace cylindrical gear pair can achieve full tooth width curve contact， which verifies the feasibility of the machining method. It provides the basis for the machining and application of the involute elliptic-arc-tooth-trace cylindrical gear.

A continuous attractor neural network (CANN) configured with various synaptic dynamics can implement many brain cognitive functions. Corresponding neuromorphic implementation can be beneficial to carry out these cognitive computations in real-time. Herein, we present a neuromorphic implementation of the CANN of spiking neurons on the field-programmable gate array (FPGA), in which the synaptic strength of local excitation and global inhibition can be configured to achieve winner-take-all (WTA) competition. In contrast to previously reported neuromorphic CANN, in addition to fast-linear synapses, recurrent connections can also be implemented with slow-nonlinear synapses. This endows the proposed CANN on the FPGA with the capability of performing neural computations that require slow and nonlinear temporal dynamics, such as decision making and working memory. Circuit simulations on the hardware reproduced gradually ramping neural activities observed in decision-making experiments and multiple sustained activities observed during the delay in working memory experiments, especially the fade-out and merging of activity bumps in the latter task. Theoretical analysis illuminated the underlying mechanisms of decision making and working memory on the FPGA. The unstable two-bump steady state of the CANN is responsible for the two-alternative decision making, similar to the saddle-node structure in the reduced two-variable decision model. Meanwhile, the stable uniformly distributed N-bump steady states account for the multiple-item working memory, similar to the multistability in previous mean-field models. Furthermore, the asymmetrical N-bump unstable steady states exhibit attractor dynamics underlying the fade-out and merging of activity bumps. The consistency between simulations on the hardware and the theoretical analysis demonstrated that the neuromorphic CANN is endowed with attractor dynamics relating to slow and nonlinear neural computations and has the potential to implement sophisticated cognitive functions by configuring various synaptic dynamics. This implementation shows promise for integrating the cognitive platform due to its characteristics of various dynamics and flexible configurations.

The coupling in integrated electricity and gas community energy system (IEGS) provides alternative operation modes when unpredictable outages occur at energy-supply sides. Reasonable operation strategies and system configuration can effectively improve the system's resilience, making reliable and continuous operation feasible. Based on the complementary characteristics and reserve capabilities of IEGS, this paper proposes a multi-stage scheduling strategy for resilience enhancement in which thermal storage serves as emergency response resources. The resilient scheduling framework consists of rolling reserve optimization stage, day-ahead economic dispatch stage and fault restoration stage. With the reserve capacity of energy storage generated by rolling optimization and day-ahead dispatch, multiple forms' critical loads will be satisfied in priority when outage occurs on energy-supply sides. Furthermore, a two-level planning model integrating the resilient operation strategy is formulated to better adapt to the source emergency. The proposed planning method is applied to an IEGS with practical demands as a case study. The results show that the configuration generated by the two-level planning model can satisfy the daily reserve requirements for emergency failures, and the resilient scheduling strategy with storage reserve can improve the system resilience effectively.

A new type of Continuously Variable Transmission （CVT） with surface-contact friction transmission structure is presented， which is a discrete adjustable radius CVT. The relationship between the size parameters of the discrete adjustable radius pulley transmission structure and the transmission ratio is analyzed. The calculation formula of the critical friction force of the discrete adjustable radius pulley transmission is derived. It is verified that the discrete adjustable radius pulley has large torque transmission capability in theory. In addition， the rotational speed fluctuation analysis based on ADAMS is carried out， and the experimental device of the discrete adjustable radius CVT is built and tested. The results show that the speed fluctuation meets the transmission requirements of most equipments. The new discrete adjustable radius CVT has great development value， which has the characteristics of compact structure and reasonable design.

Person re-identification can be seen as a process of open set recognition. Usually, the deep learning models consider the person re-identification model as a classification model with a softmax layer. However, the softmax layer cannot be extended to unknown classes because of its closed nature, so the classification model is just regarded as the feature extractor. To overcome the problem mentioned above and make the person re-identification process end-to-end, this paper cast the person re-identification into a regression process and calculates the probability that persons in the images belong to the same identity. First, this paper proposes a deep regression model, named deep regression neural network integrating adaptive multi-attribute fusion method (DRNN-AMAF), which can make the person re-identification as regression analysis. Second, attributes are taken as the basis of this model for calculating the probability of persons belonging to the same identity, and each attribute corresponds to each branch of the deep regression neural network. Finally, hard labels of multiple attributes are adaptively fused into a soft label by the proposed multi-label fusion method based on the idea of Bayesian inference, which makes the attribute labels suitable for regression tasks. The comprehensive experiments on available public databases are conducted, and the experimental results show that our model produces competitive performance compared with the state-of-the-art approaches.

Glulam bamboo has been preliminarily explored for use as a structural building material, and its stress–strain model under axial loading has a fundamental role in the analysis of bamboo components. To study the tension and compression behaviour of glulam bamboo, the bamboo scrimber and laminated bamboo as two kinds of typical glulam bamboo materials were tested under axial loading. Their mechanical behaviour and failure modes were investigated. The results showed that the bamboo scrimber and laminated bamboo have similar failure modes. For tensile failure, bamboo fibres were ruptured with sawtooth failure surfaces shown as brittle failure; for compression failure, the two modes of compression are buckling and compression shear failure. The stress–strain relationship curves of the bamboo scrimber and laminated bamboo are also similar. The tensile stress–strain curves showed a linear relationship, and the compressive stress–strain curves can be divided into three stages: elastic, elastoplastic and post-yield. Based on the test results, the stress–strain model was proposed for glulam bamboo, in which a linear equation was used to describe the tensile stress–strain relationship and the Richard–Abbott model was employed to model the compressive stress–strain relationship. A comparison with the experimental results shows that the predicted results are in good agreement with the experimental curves.

Ganoderma lucidum has salutary effects on tumor treatment, including pancreatic cancer and hepatocellular carcinoma. However, the molecular mechanisms underlying Ganoderma lucidum therapy is obscure. In this study, the Hepa1-6-bearing C57 BL/6 mouse model was utilized to explore the therapeutic efficacy of Ganoderma lucidum extract (GLE), documenting that it could effectively inhibit tumor growth. The microRNA (miRNA) profiles of GLE-treated and untreated mice were detected, and 25 differentially expressed (DE) miRNAs were determined, including 24 up-expressed and one down-expressed miRNAs. Using the ClusterOne algorithm, 8 hub miRNAs were isolated from the established miRNA-target network. The qRT-PCR assay demonstrated that these 8 miRNAs were up-expressed in the GLE treated tumor mice. Furthermore, the mRNA profiles showed that there are 76 DE mRNAs between GLE treated and model groups. The protein-protein interaction (PPI) network shows that Cntn1, Irs1, Nfkbia, Rybp and Ywhaz playing important roles, and qRT-PCR further revealed they were down-expressed in GLE treated Hepa1-6-bearing C57 BL/6 mice. The rebuilt miRNA-target network was shown that these 5 mRNAs were regulated by mmu-mir-23a-5p, -3102-3p, -337-3p, and -467a-3p, respectively. This study suggested that these 4 interesting miRNAs were potential biomarkers for evaluation of GLE efficacy, which may down-regulate the expression of Cntn1, Irs1, Nfkbia, Rybp and Ywhaz, and mediate many signaling pathways occurring in tumor treatment.

Abstract Liquid‐like materials are one family of promising thermoelectric materials discovered in the past years due to their advantanges of ultrahigh thermoelectric figure of merit (zT), low cost, and environmental friendliness. However, their practial applications are greatly limited by the low service stability from the Cu/Ag metal deposition under large current and/or temperature gradient. Both high zT for high efficiency and large critical voltage for good stability are required for liquid‐like materials, but they are usually strongly correlated and hard to be tuned individually. Herein, based on the thermodynamic analysis, it is shown that such a correlation can be decoupled through doping immobile ions into the liquid‐like sublattice. Taking Cu2−δS as an example, doping immobile Fe ions in Cu1.90S scarcely degrades the initial large critical voltage, but significantly enhances the zT to 1.5 at 1000 K by tuning the carrier concentration to the optimal range. Combining the low‐cost and environmentally friendly features, these Fe‐doped Cu2−δS‐based compounds show great potential in civil applications. This study sheds light on the realization of both good stability and high performance for many other liquid‐like thermoelectric materials that have not been considered for real applications before.

In order to investigate the relationship between tribo-magnetization and wear phenomena, a series of sliding-friction tests were carried out using a pin-on-block reciprocator type device, which was specially designed to generate sliding friction and to detect magnetic fields. The tribological behavior was observed by a charge-coupled device (CCD) camera in real time, and the magnetic signal was detected by using a two-axis magnetic sensor. It was found that as the friction continues, both the tangential and the normal components of magnetic field on the material surface increase gradually, and that both the average value of the tangential magnetic field ΔH(x)mean and the peak-to-peak value of the normal magnetic field Vpp at the wear scar clearly reflect changes of the wear state. Furthermore, in order to better understand the tribo-magnetization phenomenon, the changes of surface morphology and wear debris in different wear stages were analyzed. Moreover, an improved magnetic dipole model that considered the distribution of magnetic charges on the worn surface was established. This model can successfully describe the tribo-magnetization phenomenon during the stable wear stage, and should be useful for characterizing frictional wear phenomena in the future.

The crystal structure uniquely imparts the specific properties of a material, and thus provides the starting point for any quantitative understanding of thermoelectric properties. Cu2−xSe is an intensely studied high performing, non-toxic and cheap thermoelectric material, and here for the first time, the average structure of β-Cu2−xSe is reported based on analysis of multi-temperature single-crystal X-ray diffraction data. It consists of Se–Cu layers with additional copper between every alternate layer. The structural changes during the peculiar zT enhancing phase transition mainly consist of changes in the inter-layer distance coupled with subtle Cu migration. Just prior to the transition the structure exhibits strong negative thermal expansion due to the reordering of Cu atoms, when approached from low temperatures. The phase transition is fully reversible and group–subgroup symmetry relations are derived that relate the low-temperature β-phase to the high-temperature α-phase. Weak superstructure reflections are observed and a possible Cu ordering is proposed. The structural rearrangement may have a significant impact on the band structure and the Cu rearrangement may also be linked to an entropy increase. Both factors potentially contribute to the extraordinary zT enhancement across the phase transition.

The biomass thermoplastic composites were prepared by extrusion molding method with poplar flour, rice husk, cotton stalk and corn stalk. The thermo gravimetric analyzer (TGA) has also been used for evaluating the pyrolysis process of the composites. The results showed that the pyrolysis process mainly consists of two stages: biomass pyrolysis and the plastic pyrolysis. The increase of biomass content in the composite raised the first stage pyrolysis peak temperature. However, the carbon residue was reduced and the pyrolysis efficiency was better because of synergistic effect of biomass and plastic. The composite with different kinds of biomass have similar pyrolysis process, and the pyrolysis efficiency of the composite with corn stalk was best. The calcium carbonate could inhibit pyrolysis process and increase the first stage pyrolysis peak temperature and carbon residue as a filling material of the composite. Keywords: Biomass thermoplastic composite, Calcium carbonate, Pyrolysis characteristic

The biomass polyethylene composites filled with poplar wood flour, rice husk, cotton stalk or corn stalk were prepared by extrusion molding. The static viscoelasticity of composites was investigated by the dynamic thermal mechanical analyzer (DMA). Through the stress-strain scanning, it is found that the linear viscoelasticity interval of composites gradually decreases as the temperature rises, and the critical stress and strain values are 0.8 MPa and 0.03% respectively. The experiment shows that as the temperature rises, the creep compliance of biomass polyethylene composites is increased; under the constant temperature, the creep compliance decreases with the increase of content of biomass and calcium carbonate. The biomass and calcium carbonate used to prepare composites as filler can improve damping vibration attenuation and reduce stress deformation of composites. The stress relaxation modulus of composites is reduced and the relaxation rate increases at the higher temperature. The biomass and calcium carbonate used to prepare composites as filler not only can reduce costs, but also can increase stress relaxation modulus and improve the size thermostability of composites. The corn stalk is a good kind of biomass raw material for composites since it can improve the creep resistance property and the stress relaxation resistance property of composites more effectively than other three kinds of biomass (poplar wood flour, rice husk and cotton stalk). Keywords: Biomass, Composites, Calcium carbonate, Static viscoelasticity, Creep, Stress relaxation

To meet the various requirements of full range management of vast device in buildings of smart park，an indoor localization algorithm about information fusion of multi readers was proposed.Based on device management in RFID system，using the wireless sensing characteristics between the reader and the tag，and combining with the reference tag concept，an indoor localization algorithm based on RFID was proposed.The algorithm had the characteristic of high position accuracy，low complexity and low cost.This algorithm could realize the localization of device tag in smart buildings，and realize management to a large number of device in buildings of smart park more efficiently and intelligently.

A new cement-based mortar with high early strength and toughness was developed by adding micro steel fibers (MSF) in magnesium phosphate cement (MPC) mortar. The compressive and flexural tests were carried out to investigate the effect of curing time, MSF volume fraction, sand-cement mass ratio, and water-cement mass ratio on the strength and flexural toughness of MSF-reinforced MPC mortar (MSFRMM). Also, the flexural toughness and ductility of MSFRMM were evaluated according to ASTM C1609. The results of this study showed that the addition of MSF from 0% to 1.6% by volume significantly improved the compressive strength of MSFRMM. The MSFRMM showed high early strength, especially during the first 3 days. The addition of MSFs changed the flexural failure mode of MPC-based mortar from brittleness to ductility, and the flexural toughness of MSFRMM remarkably increased with the increase of MSF volume fraction from 0% to 1.6%. The toughness and ductility of MSFRMM slightly increased with the increase of the dosage of cement. The toughness and ductility of MSFRMM increased with the decrease of the water-cement mass ratio due to the improved density of the mortar caused by the reduction of water.