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Cnidarians are among the most important diploblastic organisms, elucidating many of the early stages of Metazoan evolution. However, Cnidarian fossils from Cambrian deposits have been rarely documented, mainly due to difficulties in identifying early Cnidarian representatives. Halysites, a tabulate coral from Silurian reef systems, serves as a crucial taxon for interpreting Cambrian cnidarians. Traditionally, the biological characteristics of Halysites have been analyzed using methods limited by pretreatment requirements (destructive testing) and the chamber size capacity of relevant analytical instruments. These constraints often lead to irreversible information loss and inadequate data extraction. This means that, to date, there has been no high-resolution three-dimensional mineralization analysis of Halysites. This study aims to introduce novel, non-destructive techniques to analyze the internal structure and chemical composition of Halysites. Furthermore, it seeks to elucidate the relationship between coral organisms and biomineralization in reef settings and to compare Silurian Tabulata with putative Cambrian cnidarians. Techniques such as micro-X-ray fluorescence spectrometry (micro-XRF), micro-X-ray computed tomography (micro-CT), and scanning electron microscopy (SEM) were employed in this research. With the help of high-resolution micro-CT scanning, we identify the growth pattern of Halysites, showing both lateral and vertical development. The lateral multiple-branching growth pattern of Halysites corals is first established herein. The flaggy corallite at the initial stage of branching is also observed. The micro-XRF mapping results reveal the occurrence of septa spines for Halysites, a trait previously thought rare or absent. Additionally, the ratio of coral volume to the surrounding rock was assessed, revealing that Halysites reefs were relatively sparse (volume ratio = ~30%). The cavities between Halysites likely provided more space for other organisms (e.g., rugose corals and bryozoans) when compared to other coral reef types. Additionally, we provide a comparative analysis of post-Cambrian colonial calcareous skeletons, offering insights into the structural features and growth patterns of early skeletal metazoans across the Ediacaran–Cambrian boundary. [ABSTRACT FROM AUTHOR]

This article presents a LiDAR system that utilizes a Fizeau interferometer and photomultiplier tube array to detect the water Rayleigh–Brillouin spectrum, utilized to obtain underwater temperature and salinity synchronizing measurements based on the Brillouin spectral linewidth and shift. Temperature and salinity measurements were conducted in the laboratory to verify the efficiency of the system. The results demonstrate that the LiDAR system can accurately obtain the Rayleigh–Brillouin spectral backscattering profiles of water. Following linear fitting and reconstruction, the retrieved temperature accuracy is ±0.13 °C and salinity accuracy is ±0.16‰. By effectively leveraging the multiparameter information contained in the Rayleigh–Brillouin spectrum, the system achieved precise temperature and salinity measurements. This study provides a reference for marine remote sensing applications [ABSTRACT FROM AUTHOR]

Manipulating plasmonic chirality has shown promising applications in nanophotonics, stereochemistry, chirality sensing, and biomedicine. However, to reconfigure plasmonic chirality, the strategy of constructing chiral plasmonic systems with a tunable morphology is cumbersome and complicated to apply for integrated devices. Here, we present a simple and effective method that can also manipulate chirality and control chiral light–matter interactions only via strong coupling between chiral plasmonic nanoparticles and excitons. This paper presents a chiral plexcitonic system consisting of L-shaped nanorod dimers and achiral molecule excitons. The circular dichroism (CD) spectra in our strong-coupling system can be calculated by finite element method simulations. We found that the formation of the chiral plexcitons can significantly modulate the CD spectra, including the appearance of new hybridized peaks, double Rabi splitting, and bisignate anti-crossing behaviors. This phenomenon can be explained by our extended coupled-mode theory. Moreover, we explored the applications of this method in enantiomer ratio sensing by using the properties of the CD spectra. We found a strong linear dependence of the CD spectra on the enantiomer ratio. Our work provides a facile and efficient method to modulate the chirality of nanosystems, deepens our understanding of chiral plexcitons in nanosystems, and facilitates the development of chiral devices and chiral sensing. [ABSTRACT FROM AUTHOR]

Exploiting novel materials with high specific capacities is crucial for the progress of advanced energy storage devices. Intentionally constructing functional heterostructures based on a variety of two-dimensional (2D) substances proves to be an extremely efficient method for capitalizing on the shared benefits of these materials. By elaborately designing the structure, a greatly escalated steadiness can be achieved throughout electrochemical cycles, along with boosted electron transfer kinetics. In this study, chemical vapor deposition (CVD) was utilized to alter the surface composition of multilayer Ti3C2Tx MXene, contributing to contriving various layered heterostructure materials through a precise adjustment of the reaction temperature. The optimal composite materials at a reaction temperature of 500 °C (defined as MX500), incorporating MXene as the conductive substrate, exhibited outstanding stability and high coulombic efficiency during electrochemical cycling. Meanwhile, the reactive sites are increased by using TiS2 and TiO2 at the heterogeneous interfaces, which sustains a specific capacity of 449 mAh g−1 after 200 cycles at a current density of 0.1 A g−1 and further demonstrates their exceptional electrochemical characteristics. Additionally, the noted pseudocapacitive properties, like MXene materials, further highlight the diverse capabilities of intuitive material design. This study illuminates the complex details of surface modification in multilayer MXene and offers a crucial understanding of the strategic creation of heterostructures, significantly impacting sophisticated electrochemical applications. [ABSTRACT FROM AUTHOR]

We develop a quantum theory based on macroscopic quantum electrodynamics to research the resonance energy transfer (RET) between a chiral donor and acceptor. It differs from the previous Green function approach which needs specific boundary conditions to obtain an analytical solution for calculating the RET rate. Our theory can combine the finite-difference time-domain (FDTD) method, which gives a simple and efficient semi-analytical approach, to evaluate the chiral RET rate in an arbitrary plasmonic nanosystem. Applying our theory to the systems of chiral molecules 3-methylcyclopentanone (3MCP) near the achiral/chiral plasmonic nanostructures, the RET process, which is divided into nondiscriminatory and discriminatory parts, is investigated. We find that plasmon will enhance both nondiscriminatory and discriminatory rates compared to the absence of plasmonic nanostructure, but the plasmon supported by chiral nanostructure contributes more to the discriminatory rate. The ratio of discriminatory to nondiscriminatory rates in the system consisting of 3MCP and chiral plasmonic structure is five-fold compared to the system consisting of 3MCP and achiral plasmonic structure. The phenomena can be attributed to the chiral electric-magnetic coupling. Our findings are important in understanding the achiral and chiral electric-magnetic interaction and designing chiral light-harvesting and sensing devices. [ABSTRACT FROM AUTHOR]

In recent years, the emergence of large-scale language models, such as ChatGPT, has presented significant challenges to research on knowledge graphs and knowledge-based reasoning. As a result, the direction of research on knowledge reasoning has shifted. Two critical issues in knowledge reasoning research are the algorithm of the model itself and the selection of paths. Most studies utilize LSTM as the path encoder and memory module. However, when processing long sequence data, LSTM models may encounter the problem of long-term dependencies, where memory units of the model may decay gradually with an increase in time steps, leading to forgetting earlier input information. This can result in a decline in the performance of the LSTM model in long sequence data. Additionally, as the data volume and network depth increase, there is a risk of gradient disappearance. This study improved and optimized the LSTM model to effectively address the problems of gradient explosion and gradient disappearance. An attention layer was employed to alleviate the issue of long-term dependencies, and ConvR embedding was used to guide path selection and action pruning in the reinforcement learning inference model. The overall model achieved excellent reasoning results. [ABSTRACT FROM AUTHOR]

A multi-constellation, multi-frequency Global Navigation Satellite System (GNSS) receiver is capable of simultaneously receiving signals from multiple satellite constellations across various frequency bands. This allows for increased observations, thereby enhancing navigation accuracy, continuity, effectiveness, and reliability. The spread spectrum code structures used in satellite navigation signals differ among systems. Compatible code generators are employed in multi-constellation, multi-frequency GNSS receivers to support tasks such as signal acquisition and tracking. There are three main types of spread spectrum code structures: Linear Feedback Shift Register (LFSR), Legendre sequences, and Memory codes. The Indian Regional Navigation Satellite System (IRNSS) released the L1-SPS (Standard Positioning Service) signal format in August 2023, which utilizes the Interleaved Z4-linear ranging code (IZ4 code) as its spread spectrum code. Currently, there is no universal code generator design compatible with the IZ4 code. In this paper, a proposed universal code generator is based on the hardware structure of the IRNSS IZ4 code generator. It achieves compatibility with all LFSR-based spread spectrum codes and enables parallel generation of multiple sets of GNSS signal spread spectrum codes, thereby improving hardware utilization efficiency. The proposed structure is implemented and validated using FPGA design, and resource consumption is provided as part of the validation results. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation (STI) is an important internal driver of social and economic development. Reasonable evaluation of regional scientific and technological innovation (RSTI) capability helps discover shortcomings in the development of urban development and guides the allocation of scientific and technological resources and the formulation of policies to promote innovation. This paper analyzes new opportunities created by big data and artificial intelligence for the evaluation of RSTI capability, and based on this analysis, the collaborative evaluation schemes of multi-entity participation are investigated. In addition, considering the important value of unstructured data in evaluating STI, the Latent Dirichlet Allocation (LDA) topic model and sentiment analysis method are employed to analyze the construction of an evaluation indicator system that integrates scientific and technological news data. To fully utilize the respective advantages of human experts and machine learning in the field of complex issue evaluation, this paper proposes an RSTI capability evaluation model based on AHP-SMO human-machine fusion. This study promotes the integration of science and technology and economy and has theoretical and practical significance. [ABSTRACT FROM AUTHOR]

Archaeocyaths are a group of extinct filter feeders that flourished in the early Cambrian period and occupied an important position in the evolution of basal fauna and the early marine ecosystem. However, the detailed morphological and anatomical information of this group are still unclear due to insufficient fossil material and limited experimental analyses. Here, we report exquisitely preserved phosphatized archaeocyathan fossil cups, ca. 515 million years old, from the top of the Shuijingtuo Formation (Series 2, Stage 3) and the Xiannüdong Formation (Series 2, Stage 3) of the Yangtze Platform, South China. Detailed observation of their external morphology via scanning electron microscopy (SEM) and micro-computed tomography (Micro-CT) analysis revealed detailed information of their internal structure. They have a typical double-walled cup, with the perforated inner and outer walls concentrically distributed, but the structure between the two walls differs. The inverted cone-shaped cups have radially distributed septa between the walls. Perforated septa connect the two walls. The low and columnar cups have canals between the two walls, forming the network. These pores and cavities constitute an important component of the water current system (pumping and filtering water with a network of canals and chambers) and influence the process of filtration in the cup. In comparison to traditional thin-section analysis, the combination of SEM and Micro-CT analysis on phosphatized archaeocyaths presented in this study further explored the detailed internal structure and finely reconstructed the microscopic overall morphology and anatomy, which provide important information to help us understand the systematic taxonomy, anatomy, and morphology of archaeocyaths during the Cambrian period. [ABSTRACT FROM AUTHOR]

Online learning platforms provide diverse course resources, but this often results in the issue of information overload. Learners always want to learn courses that are appropriate for their knowledge level and preferences quickly and accurately. Effective course recommendation plays a key role in helping learners select appropriate courses and improving the efficiency of online learning. However, when a user is enrolled in multiple courses, existing course recommendation methods face the challenge of accurately recommending the target course that is most relevant to the user because of the noise courses. In this paper, we propose a novel reinforcement learning model named Actor-Critic Hierarchical Reinforcement Learning (ACHRL). The model incorporates the actor-critic method to construct the profile reviser. This can remove noise courses and make personalized course recommendations effectively. Furthermore, we propose a policy gradient based on the temporal difference error to reduce the variance in the training process, to speed up the convergence of the model, and to improve the accuracy of the recommendation. We evaluate the proposed model using two real datasets, and the experimental results show that the proposed model significantly outperforms the existing recommendation models (improving 3.77% to 13.66% in terms of HR@5). [ABSTRACT FROM AUTHOR]

The grid terminal deploys numerous types of communication equipment for the digital construction of the smart grid. Once communication equipment failure occurs, it might jeopardize the safety of the power grid. The massive amount of communication equipment leads to a dramatic increase in fault research and judgment data, making it difficult to locate fault information in equipment maintenance. Therefore, this paper designs a knowledge-graph-driven method for intelligent decision making on power communication equipment faults. The method consists of two parts: power knowledge extraction and user intent multi-feature learning recommendation. The power knowledge extraction model utilizes a multi-layer bidirectional encoder to capture the global features of the sentence and then characterizes the deep local semantics of the sentence through a convolutional pooling layer, which achieves the joint extraction and visual display of the fault entity relations. The user intent multi-feature learning recommendation model uses a graph convolutional neural network to aggregate the higher-order neighborhood information of faulty entities and then the cross-compression matrix to solve the feature interaction degree of the user and graph, which achieves accurate prediction of fault retrieval. The experimental results show that the method is optimal in knowledge extraction compared to classical models such as BERT-CRF, in which the F1 value reaches 81.7%, which can effectively extract fault knowledge. User intent multi-feature learning recommendation works best, with an F1 value of 87%. Compared with the classical models such as CKAN and KGCN, it is improved by 5%~11%, which can effectively solve the problem of insufficient mining of user retrieval intent. This method realizes accurate retrieval and personalized recommendation of fault information of electric power communication equipment. [ABSTRACT FROM AUTHOR]

In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. The experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples. [ABSTRACT FROM AUTHOR]

The article discusses the promise and challenges of tissue bioprinting in the field of regenerative medicine. Bioprinting is a manufacturing approach that allows for the precise deposition of biomaterials and cells in a 3D environment, enabling the creation of complex and defined structures. It has the potential to address clinical needs such as tissue repair and replacement. Bioprinting also has the potential to advance our understanding of biological processes and functions by creating biomimetic tissue models. However, there are still challenges to overcome, including engineering tissue complexity, post-print tissue maturation, standardized manufacture, and regulatory frameworks. Despite these challenges, the outlook for bioprinting remains promising, with exciting advances expected in the future. [Extracted from the article]

Relative to single Global Navigation Satellite System (GNSS) measurements, i.e., the measurements from a single GNSS system, a single GNSS code, and a single GNSS receiver, multi-GNSS measurements for time transfer could improve reliability and provide better short-term stability. Previous studies applied equal weighting to different GNSS systems or different GNSS time transfer receivers, which, to some extent, revealed the improvement in the additional short-term stability from the combination of two or more kinds of GNSS measurements. In this study, the effects of the different weight allocation for multi-measurements of GNSS time transfer were analyzed, and a federated Kalman filter was designed and applied to fuse multi-GNSS measurements combined with the standard-deviation-allocated weight. Tests with real data showed that the proposed approach can reduce the noise level to well below about 250 ps for short averaging times. [ABSTRACT FROM AUTHOR]

The performance of an active-quenching single-photon avalanche diode (SPAD) array that is based on the tri-state gates of a field programmable gate array (FPGA) is presented. The array is implemented by stacking a bare 4 × 4 N-on-P SPAD array on a bare FPGA die, and the electrodes of the SPAD pixels and the I/O ports of the FPGA are connected through wire bonding within the same package. The active quenching action on each SPAD pixel is performed by using the properties of the tri-state gates of the FPGA. Digital signal processing, such as pulse counters, data encoders, and command interactions, is also performed by using the same FPGA. The breakdown voltage of the SPAD pixels, with an active area of 60 μm × 60 μm, is 47.2–48.0 V. When the device is reverse biased at a voltage of ~50.4 V, a response delay of ~50 ns, a dead time of 157 ns, a dark count rate of 2.44 kHz, and an afterpulsing probability of 6.9% are obtained. Its peak photon detection probability (PDP) reaches 17.0% at a peak wavelength of 760 nm and remains above 10% at 900 nm. This hybrid integrated SPAD array is reconfigurable and cost effective. [ABSTRACT FROM AUTHOR]

Apetala2/ethylene response factor (AP2/ERF) is one of the largest families of transcription factors, regulating growth, development, and stress response in plants. Several studies have been conducted to clarify their roles in Arabidopsis and rice. However, less research has been carried out on maize. In this review, we systematically identified the AP2/ERFs in the maize genome and summarized the research progress related to AP2/ERF genes. The potential roles were predicted from rice homologs based on phylogenetic and collinear analysis. The putative regulatory interactions mediated by maize AP2/ERFs were discovered according to integrated data sources, implying that they involved complex networks in biological activities. This will facilitate the functional assignment of AP2/ERFs and their applications in breeding strategy. [ABSTRACT FROM AUTHOR]

The far- and near-field chirality properties are usually characterized by circular dichroism (CD) and optical chirality (OC), respectively. As a light–matter interaction for the hybrid states consisting of plasmons and excitons, the strong coupling interactions can affect the original chiral electromagnetic modes. However, there are few works on this influence process, which prevents an in-depth understanding of chirality. Here, we theoretically investigate both the far-field and near-field characteristics of the chiral plasmonic gold helicoid nanoparticle (GHNP) to explore the chirality mechanism further. We found that the electromagnetic field distribution of GHNP consists of one dark mode and two bright modes. The dark mode is observed more clearly in CD than in extinction spectra. Two bright modes can strongly couple with excitons respectively, which is confirmed by the anticrossing behavior and mode splitting exhibited in the extinction and CD spectra. We also analyzed the near-field OC distribution of the GHNP hybrid system and obtained the chiral responses as well as the spectral correspondence between OC and CD. Furthermore, although the strong coupling interaction changes the energy levels, resulting in mode splitting, the chiral hotspot distributions of both the upper polariton branch and lower polariton branch are consistent with the original bright mode in OC maps. Our findings provide guidance for the design of structures with strong chiral responses and enhance the comprehension of chiral strong coupling systems. [ABSTRACT FROM AUTHOR]

The potential effects of air pollution on the ocular surface environment have not been fully evaluated, and even fewer studies have been conducted on the lagged effects of air pollution on dry eye disease (DED). The data of 9970 DED outpatients between 1 January 2013 and 31 December 2020, and data for six air pollutants, including PM10, PM2.5, carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), were obtained from 11 standard urban background stationary air quality monitors in Urumqi, Xinjiang, China. Time series analysis design and quasi-Poisson generalized linear regression models combined with distributed lagged nonlinear models (DLNM) were used. Single- and multi-pollutant model results suggest that each additional per 10 μg/m3 of PM10, NO2, and SO2 is associated with an increased risk of outpatient DED on lag day 0 and PM2.5, NO2, and SO2 with other cumulative lag days; R software version 4.0.4 (15 February 2021) was used for the analysis. We conducted first time series analysis with a large sample size in northwest China (Xinjiang) and confirmed, for the first time, the impact of air pollution including particulate pollutants (PM10, PM2.5) and acidic gasses (SO2, NO2) on DED risk in the Urumqi region, and suggested the potential lagged effects of PM2.5, SO2, and NO2. [ABSTRACT FROM AUTHOR]

Increasing sensor sensitivity and maintaining a large FOM (figure of merit) are challenging to achieve at the same time. Adding grooves and asymmetrical structures to the annular cavity increases sensitivity; however, it usually makes the FOM of the structure decrease. Herein, we propose a MIM (metal-insulator-metal) sensor of a novel structure with nano-cylinders loaded in a ring resonator (NCRR), whose sensitivity can reach as high as 3636.4 nm/RIU (refractive index unit). The FOM is maintained around 2000 in the mid-infrared (MIR) region. We find that grating effects only occur in the ring cavity when the cylinder's distance is below three times its radius, and it can improve the sensitivity of the proposed structure up to 42.3% without decreasing its FOM. In addition, results suggest that our sensor has excellent resistance to eccentricity, which brings in manufacturing. Furthermore, we investigate the capability of the proposed device as a temperature sensor with ethanol, which exhibits a maximum temperature sensitivity of 1.48 nm/°C. We believe that our research has essential application prospects in miniature integrated sensors, optical switches, splitters, filters, and broadband passers. [ABSTRACT FROM AUTHOR]

Brillouin spectroscopy is a powerful tool to measure the water temperature and salinity profiles of seawater. Considering the insufficiency of the current spectral measurement methods in real-time, spectral integrity, continuity, and stability, we developed a new lidar system for spectrum measurement on an airborne platform that is based on a Fizeau interferometer and multichannel photomultiplier tube. In this approach, the lidar system uses time-of-flight information to measure the depth and relies on Brillouin spectroscopy as the temperature and salinity indicator. In this study, the system parameters were first optimized and analyzed. Based on the analysis results, the performance of the system in terms of detection depth and accuracy was evaluated. The results showed that this method has strong anti-interference ability, and under a temperature measurement accuracy of 0.5 °C and a salinity measurement accuracy of 1‰, the effective detection depth exceeds 40.51 m. Therefore, the proposed method performs well and will be a good choice for achieving Brillouin lidar application in seawater remote sensing. [ABSTRACT FROM AUTHOR]

Purpose: High-involvement experience products (HIEP) are generally characterized by a high value and difficult purchasing decision for customers, and a wrong decision will bring large losses to consumers, severely affecting their trust in enterprises. The purpose of this paper is to solve the problem of trust evaluation of HIEP e-commerce enterprises. Tasks and research methods: First, given the heterogeneity of trust information in the big data context, this paper collects the reputation data of HIEP enterprises and the trust big data of enterprises in industry, commerce and justice by a crawler program. Next, we use the dictionary and pattern matching methods to extract the trust features in text big data and construct the trust evaluation feature set integrating judicial information. Then, based on machine learning methods, we propose a LAS-RS model, which aims to solve the problem of trust evaluation in an imbalanced and high-dimensional data context. Finally, by introducing signal theory, this paper reveals the differential influence mechanism of big data feature variables on the trust of HIEP e-commerce enterprises. Originality: This study further enriches the relevant theories and methods of e-commerce trust evaluation research and is conducive to a better understanding and control of potential trust risks. [ABSTRACT FROM AUTHOR]

With the rapid development of smart grids, the number of various types of power IoT terminal devices has grown by leaps and bounds. An attack on either of the difficult-to-protect end devices or any node in a large and complex network can put the grid at risk. The traffic generated by Distributed Denial of Service (DDoS) attacks is characterised by short bursts of time, making it difficult to apply existing centralised detection methods that rely on manual setting of attack characteristics to changing attack scenarios. In this paper, a DDoS attack detection model based on Bidirectional Long Short-Term Memory (BiLSTM) is proposed by constructing an edge detection framework, which achieves bi-directional contextual information extraction of the network environment using the BiLSTM network and automatically learns the temporal characteristics of the attack traffic in the original data traffic. This paper takes the DDoS attack in the power Internet of Things as the research object. Simulation results show that the model outperforms traditional advanced models such as Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) in terms of accuracy, false detection rate, and time delay. It plays an auxiliary role in the security protection of the power Internet of Things and effectively improves the reliability of the power grid. [ABSTRACT FROM AUTHOR]

The supply chain is an important part for firms to maintain competitive advantages. With the development of the Internet industry, the complexity of the business environment faced by E-commerce firms has greatly increased. Additionally, unexpected events have occurred from time to time, which have seriously affected the stability of the E-commerce supply chain. Supply chain social capital comprises the resources obtained by firms in the supply chain network through reputation, status, trust, commitment, etc., which allows the firms in the supply chain to form an interdependent relationship. Supply chain social capital can generate sustainable competitive advantages for supply chain firms. Based on the theory of social capital, this paper analyzes the impact on supply chain collaboration and stability from the three dimensions of supply chain capital: structural capital, cognitive capital, and relational capital. The results show that supply chain social capital positively affects supply chain collaboration and affects the stability of the supply chain in indirect ways. At the same time, this paper also found that under different supply chain governance modes, there are differences in the relationship between supply chain social capital and supply chain collaboration, that the moderation effects of contractual governance are not significant, while relational governance has positive moderation effects on the relationship between supply chain structural capital, relational capital, and supply chain collaboration. The conclusion of this study provides a theoretical basis for E-commerce firms to improve the level of supply chain social capital, adopt informal relational governance to face market uncertainty, and then promote the stability of the supply chain. At the same time, it also provides practical reference for the management department to issue policies so as to promote mutual understanding between supply chain cooperative firms, and to form a harmonious supply chain relationship. [ABSTRACT FROM AUTHOR]

The highly localized and uneven spatial distribution of the subwavelength light field in metal metasurfaces provides a promising means for the generation of optical vortices (OVs) with arbitrary topological charges. In this paper, a simple and reliable way for generating multichannel OVs on gold nanoporous metasurfaces is reported. The instantaneous field of arbitrary-order OVs can be regulated and concentrated on the same focal surface by adapting photonic spin–orbit interaction (SOI) and geometric phase. The focal ring energy distribution of OVs along the conical propagation path is accurately calculated, and the double phase of units induced by spin rotation is confirmed. Based on the parameter optimization of the nanohole arrangement, the simultaneous amplitude and phase modulation of multichannel OVs has been realized. Furthermore, the average multichannel signal-to-noise ratio exceeds 15 dB, which meets the requirements of high resolution and low crosstalk. Our study obtains broadband and efficient OVs, which can contribute to improving the capacity storage and security of optical information and possess great application prospects in beam shaping, optical tweezers, and communication coding. [ABSTRACT FROM AUTHOR]

The seismic response characteristics of a cable-stayed bridge are closely related to the structural system. At the same time, the influence of the height of the gravity center cannot be ignored in the structural system selection of cable-stayed bridges. For convenience, to make the scheme comparison and structural system selection in the preliminary design stage of a cable-stayed bridge, the judgment criterion of a low gravity center cable-stayed bridge was proposed, based on the simplified calculation of the fundamental frequency of cable-stayed bridges with two kinds of the structural system and combined with the response spectrum analysis method. The comparison of the results of the finite element model and the calculating results of the criterion showed that the judgment criterion has high accuracy and reliability, and can be applied to the preliminary design, the scheme comparison of cable-stayed bridges, and help select structural systems in the preliminary design stage of cable-stayed bridges. [ABSTRACT FROM AUTHOR]

To ensure the safety of bridges during horizontal rotation, we propose a method through which it is possible to evaluate the stability of structures in real time by measuring the vibration acceleration of the rotating structure. First, the vibration characteristics collected during the horizontal rotation of a typical high-speed railway bridge were compared with the results of a finite element analysis. Second, the analytic formula to calculate the ratio of vibration acceleration and the pier-bottom-section bending moment for the rotating structure was deduced by considering the beam and pier as an infinite-degree-of-freedom rod. Then, the results of the analytical formula were compared with those of the finite element calculation. Overall, the results showed that the bending moment of the pier bottom (which was related to the stability of the rotating bridge) was affected only by the two asymmetrical vibration modes. The analytic formula built by considering the beam and pier as an infinite degree-of-freedom rod with equal cross-section effectively described the relationship between the vibration acceleration and pier-bottom-bending moment. Finally, the vibration of the rotating bridge was simplified to the superposition of the first two asymmetric vibration modes in the facade. Based on our findings, we were able to provide a formula and some check tables to calculate the permissible value of vibration acceleration for typical high-speed railway bridges. [ABSTRACT FROM AUTHOR]

Ball shear testing is an efficient approach to investigate the mechanical reliability of solder joints at the structural level. In the present study, a series of low-speed ball shear tests were conducted to study the deformation and fracture characteristics of Sn96.5Ag3Cu0.5 solder joints at continuous speeds from 10 μm/s to 200 μm/s. In order to account for randomness, the quantity of tests was repeated for each shear rate. The relationship between mechanical properties and shear speeds was calculated in detail via effective statistical analysis. In addition, by utilizing SEM imaging and ingredient analysis the interfacial effect and fracture mechanism of solder balls were obtained and their fracture mode classified into two types, viz., bulk fracture and interface fracture. Furthermore, by means of statistical analysis and approximate calculation it was proven that bulk fracture balls have greater adhesive powers and reliability compared with interface fracture balls. [ABSTRACT FROM AUTHOR]

The Industrial Internet of Things (IIoT) deploys massive communication devices for information collection and process control. Once it reaches failure, it will seriously affect the operation of the industrial system. This paper proposes a new method for multi-entity knowledge joint extraction (MEKJE) of IIoT communication equipment faults. This method constructs a multi-task tightly coupled model of fault entity and relationship extraction. We use it to implement word embedding and bidirectional semantic capture to generate computable text vectors. At the same time, a multi-entity segmentation method is proposed, which uses noise filtering to distinguish the multi-fault relationship of single corpus. We constructed a dataset of communication failures in power IIoT and conducted experiments. The experimental results show that the method performs best in tests with the Faulty Text dataset and the CLUENER dataset. In particular, the model achieves an F1 value of 78.6% in the evaluation of relationship extraction for multiple entities, and a significant improvement of 5–8% in its accuracy and recall. It enables effective mapping and accurate extraction of fault knowledge data. [ABSTRACT FROM AUTHOR]

Production system flexibility has become an important factor to meet the needs of diversified markets in an ever-changing and turbulent market environment. Thus, this paper addresses the problems of flexibility evaluation for decision making by evaluation method driven by digital twin, which models, predicts, and evaluates the flexibility of a given production system design scheme (PSDS). Based on the definition and characteristic analysis of flexibility in the production system design phase, and combined with data modelling (static function model (SFM) and dynamic prediction model (DPM)) and data analysis (AHP-based and simulation-based analysis), the proposed framework evaluates system flexibility from the static and dynamic levels, helps enterprises quickly obtain the system's comprehensive flexibility evaluation index, realizing the rapid screening of the production system design scheme (PSDS). The successful application of the evaluation framework in case enterprise has fully proved the feasibility and effectiveness of the method. [ABSTRACT FROM AUTHOR]

Antimonene (Sb) is a novel kind of two-dimensional (2D) material that is predicted to be promising for various applications, such as water splitting and semiconductor devices. Several methods have been reported to prepare Sb nanoflakes/nanofilms; however, it is still relatively difficult to prepare Sb nanofilms. In this work, a method of low-power magnetron sputtering deposition was used for the preparation of Sb nanofilms with lateral dimensions on the centimeter scale and controllable film thickness. It was found that the control of the deposition temperature is important for the final crystalline structure of the nanofilms. Furthermore, the application of the nanofilms as a catalyst for water splitting (hydrogen evolution reaction (HER) and oxygen evolution reaction (OER)) was demonstrated. [ABSTRACT FROM AUTHOR]

For non-seismically designed columns with insufficient strength and flexural stiffness, intense inter-story drift can be incurred during a strong earthquake event, potentially leading to the collapse of the entire building. Existing strengthening methods mainly focus on enhancing axial or flexural strength but not the flexural stiffness of columns. In response, a novel direct fastening steel jackets that can increase both flexural strength and stiffness is introduced. This novel strengthening method features straightforward installation and swift strengthening as direct fastening is used to connect steel plates together to form a steel jacketed column. This new connection method can quickly and stably connect two steel components together by driving high strength fasteners into them. In this paper, the design procedure of RC columns strengthened with this novel strengthening method is originally proposed, which includes five steps: (1) estimating lateral load capacity of damaged RC columns; (2) determining connection spacing of steel jacket; (3) estimating the lateral load capacity of strengthened RC column; (4) evaluating the axial load ratio (ALR) of strengthened RC columns; and (5) estimating effective stiffness of strengthened RC columns. Lastly, an example is presented to illustrate the application of the proposed design procedure. [ABSTRACT FROM AUTHOR]

To obtain accurate position information, herein, a one-assistant method involving the fusion of extreme learning machine (ELM)/finite impulse response (FIR) filters and vision data is proposed for inertial navigation system (INS)-based human motion capture. In the proposed method, when vision is available, the vision-based human position is considered as input to an FIR filter that accurately outputs the human position. Meanwhile, another FIR filter outputs the human position using INS data. ELM is used to build mapping between the output of the FIR filter and the corresponding error. When vision data are unavailable, FIR is used to provide the human posture and ELM is used to provide its estimation error built in the abovementioned stage. In the right-arm elbow, the proposed method can improve the cumulative distribution functions (CDFs) of the position errors by about 12.71%, which shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Featured Application: This approach focused on the direct conversion of andradite-rich red mud to magnetite-containing magnetic adsorbent, which had great potential for recycling Fe-rich solid waste. The produced low-cost magnetic adsorbent demonstrated superior Zn(II) adsorption in smelting wastewater treatment and could also be used as the low-cost core for coating functional groups in the synthesis of functional magnetic materials. Red mud, a Fe-rich waste generated from the aluminum industry, was recovered as an adsorbent for wastewater treatment. The separation process of red mud from water after adsorption, including centrifugation and filtration, was complicated. This study demonstrated an alternative option to recycle red mud for preparing magnetic adsorbent via a facile hydrothermal route using ascorbic acid as reductant. Red mud is weakly magnetized and consists of andradite, muscovite, hematite, and cancrinite. After hydrothermal treatment, andradite in red mud was reductively dissolved by ascorbic acid, and transformed into magnetite and morimotoite. With increasing hydrothermal temperature, the dissolution of andradite accelerated, and the crystallite size of magnetite increased. When the hydrothermal temperature reached 200 °C, the prepared adsorbent P-200 showed a desirable saturation magnetization of 4.1 Am2/kg, and could be easily magnetically separated from water after adsorption. The maximum adsorption capacity of P-200 for Zn2+ was 89.6 mg/g, which is eight-fold higher than that of the raw red mud. The adsorption of Zn2+ by P-200 fitted the Langmuir model, where cation exchange was the main adsorption mechanism. The average distribution coefficient of Zn2+ at low ppm level was 16.81 L/g for P-200, higher than those of the red mud (0.3 L/g) and the prepared P-120 (1.48 L/g) and P-270 (5.48 L/g), demonstrating that P-200 had the best adsorption capacity for Zn2+ and can be served as a practical adsorbent for real-world applications. To our knowledge, this is the first study to report the conversion of red mud into a magnetic adsorbent under mild conditions. [ABSTRACT FROM AUTHOR]

Energy saving and emission reduction have become common concerns in countries around the world. In China, with the implementation of the new strategy of "carbon peak and neutrality" and the rapid development of the new smart grid infrastructure, the amount of data of actual power grid dispatching and fault analysis show exponential growth, which has led to phenomena such as poor supervision effectiveness and difficulty in handling faults in the process of grid operation and maintenance. Existing research on retrieval recommendation methods has had a lower accuracy rate at cold-start due to a small sample of user interactions. In addition, the cumulative learning of user personalization during general retrieval results in a poor perception of potential interest. By constructing a power knowledge graph, this paper presents a power fault retrieval and recommendation model (PF2RM) based on user-polymorphic perception. This model includes two methods: the power fault retrieval method (PFR) and the user-polymorphic retrieval recommendation method (UPRR). First, we take the power grid fault dispatching business as the core and reconstruct the ontology layer of the power knowledge graph. The PFR method is used to design the graph-neighbor fault entity cluster to enhance the polymerization degree of a fault implementation scenario. This method can solve the search cold-start recommendation problem. At the same time, the UPRR method aims to form user retrieval subgraphs of the past-state and current-state and make a feature matching for the graph-neighbor fault entity cluster, and then realize the accurate prediction of the user's general search intention. The model is compared with other current classical models through the evaluation of multiple recommendation evaluation metrics, and the experimental results show that the model has a 3–8% improvement in the cold-start recommendation effect and 2–10% improvement in regular retrieval. The model has the best average recommendation performance in multiple metrics and has good results in fault analysis and retrieval recommendation. It plays a helpful role in intelligent operation and maintenance of the power grid and auxiliary decision-making, and effectively improves the reliability of the power grid. [ABSTRACT FROM AUTHOR]

Graphitisation of structural characteristics and improvement in electrical conductivity was reported onto waste carbon powder through femtosecond laser annealing. Raman spectroscopy on the carbon powder pre- and post-annealing showed a shift from amorphous-like carbon to graphitic-like carbon, which can be explained by the three-stage model. Electrical I-V probing of the samples revealed an increase in conductivity by up to 90%. An increase in incident laser power was found to be correlated to an increase in conductivity. An average incident laser power of 0.104 W or less showed little to no change in electrical characteristics, while an average incident laser power of greater than 1.626 W had a destructive effect on the carbon powder, shown through the reduction in powder. The most significant improvement in electrical conductivity has been observed at laser powers ranging from 0.526 to 1.286 W. To conclude, the graphitisation of waste carbon powder is possible using post-process femtosecond laser annealing to alter its electrical conductivity for future applications. [ABSTRACT FROM AUTHOR]

Abietic acid and its derivatives have broadly been used in fine chemicals and are renewable resources. Its inherent chiral rigid tricyclic phenanthrene skeleton is unique. Its utilities in asymmetric catalysis remain to be explored. A series new amide-type chiral quaternary ammoniums bearing dehydroabietylamine were designed, and prepared by two convenient steps. Acylation of dehydroabietylamine with bromoacetyl chloride afforded amide holding bromoacetyl group in higher yields using triethyl amine as base. Subsequent quaternization reaction gave the desired amide-type chiral quaternary ammoniums. The new chiral quaternary ammoniums can be used as phase-transfer catalyst (PTC) for the transition metal-catalysed alkynylation of isatin derivatives. [ABSTRACT FROM AUTHOR]

RNA polymerase III (RNAPIII) contains 17 subunits forming 4 functional domains that control the different stages of RNAPIII transcription and are dedicated to the synthesis of small RNAs such as 5S rRNA and tRNAs. Here, we identified 23 genes encoding these subunits in Arabidopsis (Arabidopsis thaliana) and further analyzed 5 subunits (NRPC2, NRPC3, NRPC8, NRPABC1, and NRPABC2) encoded by 6 genes with different expression patterns and belonging to different sub-complexes. The knockdown of these genes repressed the expression of 5S rRNA and tRNAs, causing seed developmental arrest at different stages. Among these knockdown mutants, RNA-seq analysis revealed 821 common differentially expressed genes (DEGs), significantly enriched in response to stress, abscisic acid, cytokinins, and the jasmonic acid signaling pathway. Weighted gene co-expression network analysis (WGCNA) revealed several hub genes involved in embryo development, carbohydrate metabolic and lipid metabolic processes. We identified numerous unique DEGs between the mutants belonging to pathways, including cell proliferation, ribosome biogenesis, cell death, and tRNA metabolic processes. Thus, NRPC2, NRPC3, NRPC8, NRPABC1, and NRPABC2 control seed development in Arabidopsis by influencing RNAPIII activity and, thus, hormone signaling. Reduced expression of these subunit genes causes an insufficient accumulation of the total RNAPIII, leading to the phenotypes observed following the genetic knockdown of these subunits. [ABSTRACT FROM AUTHOR]

Network behavior analysis is an effective method to outline user requirements, and can extract user characteristics by constructing machine learning models. To protect the privacy of data, the shared information in the model is limited to non-directional network behavior information, such as online duration, traffic, etc., which also hides users' unconscious needs and habits. However, the value density of this type of information is low, and it is still unclear how much student performance is affected by online behavior; in addition there is a lack of methods for analyzing the correlation between non-directed online behavior and academic performance. In this article, we propose a model for analyzing the correlation between non-directed surfing behavior and academic performance based on user portraits. Different from the existing research, we mainly focus on the public student behavior information in the campus network system and conduct in-depth research on it. The experimental results show that online time and online traffic are negatively correlated with academic performance, respectively, and student's academic performance can be predicted through the study of non-directional online behavior. [ABSTRACT FROM AUTHOR]

Methanol is hygroscopic in a gaseous state and is a promising alternative fuel for internal combustion engines. It is understood that adding water can improve the antiknock performance for spark ignition engines, but this will also affect the flame speed and stability. In this work, laminar flame characteristics of methanol/water/air mixtures were experimentally investigated at a temperature range of 380–450 K, a pressure range of 1–4 bar, and water fractions (vaporous water molar fraction in the water–methanol fuel gas) of 0–40%. The results show that laminar burning velocity increases with temperature but decreases with pressure. The burning velocity decreases linearly with water fraction at a stoichiometric ratio. For rich mixtures and high pressures, the laminar flames tend to be more sensitive to stretch and, thus, more prone to being unstable. Increasing the water fraction can slightly increase the Markstein length. Increasing the initial pressure enhances the general flame instability, while increasing the initial temperature suppresses the general flame instability. Increasing the water fraction can lead to a decreasing thermal expansion ratio and an elevated flame thickness, both of which can lead to a suppression of hydrodynamic instability. An increase in the water fraction decreases the Lewis number, resulting in preferential diffusion instability. There is no direct relationship between the onset of cellularity and general flame instability. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is a chronic metabolic disease with increasing prevalence worldwide. Diabetic foot ulcers (DFUs) are a serious complication of DM. It is estimated that 15–25% of DM patients develop DFU at least once in their lifetime. The lack of effective wound dressings and targeted therapy for DFUs often results in prolonged hospitalization and amputations. As the incidence of DM is projected to rise, the demand for specialized DFU wound management will continue to increase. Hence, it is of great interest to improve and develop effective DFU-specific wound dressings and therapies. In the last decade, 3D bioprinting technology has made a great contribution to the healthcare sector, with the development of personalized prosthetics, implants, and bioengineered tissues. In this review, we discuss the challenges faced in DFU wound management and how 3D bioprinting technology can be applied to advance current treatment methods, such as biomanufacturing of composite 3D human skin substitutes for skin grafting and the development of DFU-appropriate wound dressings. Future co-development of 3D bioprinting technologies with novel treatment approaches to mitigate DFU-specific pathophysiological challenges will be key to limiting the healthcare burden associated with the increasing prevalence of DM. [ABSTRACT FROM AUTHOR]

For the purpose of efficiency improvement, a linear motor that performs a linear reciprocating motion can be employed to directly drive the piston in a reciprocating refrigeration compressor without crankshaft mechanism. This also facilitates the modulation of cooling capacity as the stroke and frequency can be readily varied in response to heat load. A novel design of moving magnet linear motor for linear compressor was analyzed in the paper. A finite element analysis (FEA) model was built to simulate the characteristics of the linear motor. Current and displacement signals were measured from a test rig and were defined in the transient FEA model. Transient motor force was simulated with the FEA model and good agreements are shown between the results from the FEA model and interpolated shaft force from static force measurements. Major Losses, such as copper loss and core loss were also computed. Motor efficiency decreased from 0.88 to 0.83 as stroke increased from 9 mm to 12 mm, while the pressure ratio remained unchanged. Comparisons were made between the present moving magnet linear motor and moving coil linear motors. Generally, the moving magnet linear motor demonstrates higher efficiency than moving coil motors, which have significantly higher copper loss. The present moving magnet design with simple structure could be further optimized to improve motor efficiency. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are the development direction of new energy vehicles in the future. As an important part of the Internet of things (IOT) communication network, the charging pile is also facing severe challenges in information security. At present, most detection methods need a lot of prophetic data and too much human intervention, so they cannot do anything about unknown attacks. In this paper, a self-learning-based attack detection method is proposed, which makes training and prediction a closed-loop system according to a large number of false information packets broadcast to the communication network. Using long short-term memory (LSTM) neural network training to obtain the characteristics of traffic data changes in the time dimension, the unknown malicious behavior characteristics are self-extracted and self-learning, improving the detection efficiency and quality. In this paper, we take the Sybil attack in the car network as an example. The simulation results show that the proposed method can detect the Sybil early attack quickly and accurately. [ABSTRACT FROM AUTHOR]

Waterlogging stress (WS) in a dynamic environment seriously limits plant growth, development, and yield. The regulatory mechanism underlying WS conditions at an early stage in maize seedlings is largely unknown. In the present study, the primary root tips of B73 seedlings were sampled before (0 h) and after (2 h, 4 h, 6 h, 8 h, 10 h, and 12 h) WS and then subjected to transcriptome sequencing, resulting in the identification of differentially expressed protein-coding genes (DEpcGs) and long non-coding RNAs (DElncRs) in response to WS. These DEpcGs were classified into nine clusters, which were significantly enriched in several metabolic pathways, such as glycolysis and methionine metabolism. Several transcription factor families, including AP2-EREBP, bZIP, NAC, bHLH, and MYB, were also significantly enriched. In total, 6099 lncRNAs were identified, of which 3190 were DElncRs. A co-expression analysis revealed lncRNAs to be involved in 11 transcription modules, 10 of which were significantly associated with WS. The DEpcGs in the four modules were enriched in the hypoxia response pathways, including phenylpropanoid biosynthesis, MAPK signaling, and carotenoid biosynthesis, in which 137 DElncRs were also co-expressed. Most of the co-expressed DElncRs were co-localized with previously identified quantitative trait loci associated with waterlogging tolerance. A quantitative reverse transcription-polymerase chain reaction analysis of DEpcG and DElncR expression among the 32 maize genotypes after 4 h of WS verified significant expression correlations between them as well as significant correlation with the phenotype of waterlogging tolerance. Moreover, the high proportion of hypoxia response elements in the promoter region increased the reliability of the DElncRs identified in this study. These results provide a comprehensive transcriptome in response to WS at an early stage of maize seedlings and expand our understanding of the regulatory network involved in hypoxia in plants. [ABSTRACT FROM AUTHOR]

Increasing number of refrigeration units has led to an increase of CO2 emissions and the destruction of the ozone layer. Using low global warming potential (GWP) refrigerants, improving the efficiency of vapour compression refrigeration (VCR) units, and minimising refrigerant leakages can reduce the global warming effect. Investigating the refrigerant distribution under varied operating conditions can provide a deeper understanding of refrigerant charge optimization. This study proposed a model of refrigerant mass distribution in a prototype oil-free VCR system using a linear compressor with variable strokes and R134a. The absence of the oil lubricant allows the adoption of compact heat exchangers, such as micro-channels, so that the total refrigerant charge can be reduced significantly. The predicted total refrigerant charge has a Mean Absolute Percentage Error (MAPE) of 3.7%. The simulation results indicate that refrigerant distributed in the condenser is most sensitive to operating conditions and total refrigerant charges. The refrigerant accumulated in the condenser is 6.8% higher at a total refrigerant charge of 0.33 kg than that of 0.22 kg. For a total refrigerant charge of 0.33 kg, 72.1% of the total refrigerant can accumulate in the condenser. At a fixed pressure ratio, the refrigerant as a two-phase form in the condenser decreases slightly with the increase of compressor strokes, resulting in a larger mass flow rate, thus cooling capacity. The present model can be adapted for optimization of a refrigeration unit and its components. [ABSTRACT FROM AUTHOR]

The initial conditions such as temperature, pressure and dilution rate can have an effect on the laminar burning velocity of natural gas. It is acknowledged that there is an equivalent effect on the laminar burning velocity between any two initial conditions. The effects of initial temperatures (323 K–423 K), initial pressures (0.1 MPa–0.3 MPa) and dilution rate (0–16%, CO2 as diluent gas) on the laminar burning velocity and the flame instability were investigated at a series of equivalence ratios (0.7–1.2) in a constant volume chamber. A chemical kinetic simulation was also conducted to calculate the laminar burning velocity and essential radicals' concentrations under the same initial conditions. The results show that the laminar burning velocity of natural gas increases with initial temperature but decreases with initial pressure and dilution rate. The maximum concentrations of H, O and OH increase with initial temperature but decrease with initial pressure and dilution rate. Laminar burning velocity is highly correlated with the sum of the maximum concentration of H and OH. [ABSTRACT FROM AUTHOR]

The Megalobrama amblycephala (M. amblycephala) is one of the most important economic freshwater fish in China. The molecular mechanism under the glucose intolerance responses which affects the growth performance and feed utilization is still confused. miR-34a was reported as a key regulator in the glucose metabolism, but how did the miR-34a exert its function in the metabolism of glucose/insulin in M. amblycephala was still unclear. In this study, we intraperitoneally injected the miR-34a inhibitor (80 nmol/100 g body weight) into M. amblycephala (fed with high starch diet, 45% starch) for 12 h, and then analyzed the gene expression profiling in livers by RNA-seq. The results showed that miR-34a expression in M. amblycephala livers was inhibited by injection of miR-34a inhibitor, and a total of 2212 differentially expressed genes (DEGs) were dysregulated (including 1183 up- and 1029 downregulated DEGs). Function enrichment analysis of DEGs showed that most of them were enriched in the peroxisome proliferator-activated receptor (PPAR), insulin, AMP-activated protein kinase (AMPK) and janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathways, which were all associated with the glucose/lipid metabolic and biosynthetic processes. In addition, we examined and verified the differential expression levels of some genes involved in AMPK signaling pathway by qRT-PCR. These results demonstrated that the inhibition of miR-34a might regulate glucose metabolism in M. amblycephala through downstream target genes. [ABSTRACT FROM AUTHOR]

Brillouin spectroscopy is a powerful tool to measure the water temperature and salinity profiles of seawater. Considering the insufficiency of the current spectral measurement methods in real-time, spectral integrity, continuity, and stability, we developed a new lidar system for spectrum measurement on an airborne platform that is based on a Fizeau interferometer and multichannel photomultiplier tube. In this approach, the lidar system uses time-of-flight information to measure the depth and relies on Brillouin spectroscopy as the temperature and salinity indicator. In this study, the system parameters were first optimized and analyzed. Based on the analysis results, the performance of the system in terms of detection depth and accuracy was evaluated. The results showed that this method has strong anti-interference ability, and under a temperature measurement accuracy of 0.5 °C and a salinity measurement accuracy of 1‱, the effective detection depth exceeds 40.51 m. Therefore, the proposed method performs well and will be a good choice for achieving Brillouin lidar application in seawater remote sensing.

The relation between spontaneous Rayleigh Brillouin (SRB) spectrum linewidth, gas temperature, and pressure are analyzed at the temperature range from 220 to 340 K and the pressure range from 0.1 to 1 bar, covering the stratosphere and troposphere relevant for the Earth's atmosphere and for atmospheric Lidar missions. Based on the analysis, a model retrieving gas temperature from directly measured linewidth is established and the accuracy limitations are estimated. Furthermore, some experimental data of air and nitrogen are used to verify the accuracy of the model. As the results show, the retrieved temperature shows good agreement with the reference temperature, and the absolute difference is less than 3 K, which indicates that this method provides a fruitful tool in satellite retrieval to extract the gaseous properties of atmospheres on-line by directly measuring the SRB spectrum linewidth., Competing Interests: The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Apoptosis induction by short hairpin RNA (shRNA) expression vectors could be an efficient and promising strategy for cancer gene therapy. Ultrasound-targeted microbubble destruction (UTMD) is an appealing technique. In this study, we investigated the apoptosis induction and suppression of cell proliferation in vivo transfected by the UTMD-based shRNA delivery system. Nude mice with transplanted tumors of cervical cancer were randomly arranged into three groups: control group, plasmid injection and ultrasound (P + US), P + UTMD group. Expressions of Survivin and proliferating cell nuclear antigen (PCNA), Bcl-2, Bax, Caspase-3, Ki-67, nucleostemin (NS) were investigated by immunohistochemistry. Furthermore, microvessel density (MVD) was detected by CD34 protein expressions and apoptotic index (AI) was measured by TUNEL. As compared with those in the control and P + US groups, protein expressions of PCNA, Ki-67, Bcl-2, Survivin and NS in P + UTMD groups were down-regulated markedly, while those of Bax, Caspase-3 were up-regulated significantly (p < 0.05). MVD decreased significantly, whereas AI increased remarkably (p < 0.05). We suggested that UTMD-based shRNA delivery system could induce apoptosis and inhibit proliferation significantly, without causing any apparently adverse effect, representing a new, promising technology that would be used in the future gene therapy and research.