Over the past decade, China has witnessed fast-paced technological advancements in the media industry, as well as major shifts in the health agenda portrayed in the media. Therefore, a key starting point when discussing health communication lies in whether media attention and public attention towards health issues are structurally aligned, and to what extent the news media guide public attention. Based on data mined from 73,060 sets of the Baidu Search Index and Media Index on 20 terms covering different types of cancer from 2011 to 2020, the Granger test demonstrates that, in the last decade, public attention and media attention towards cancer in China has gone through two distinct phases. During the first phase, 2011-2015, Chinese news media still held the key in transferring the salience of issues on most cancer types to the public. In the second phase, from 2016-2020, public attention towards cancer has gradually diverged from media coverage, mirroring the imbalance and mismatch between the demand of active public and the supply of cancer information from news media. This study provides an overview of the dynamic transition on cancer issues in China over a ten-year span, along with descriptive results on public and media attention towards specific cancer types.

Rail transit tunnels span long distances, are large-scale structures and pass through complicated geological conditions; thus, the risk of uneven settlement cannot be ignored. To address this issue, a method for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed in this study. First, distributed optical fiber sensing technology is implemented to obtain a massive amount of strain data from densely distributed measurement points along regional railway tunnels, and a method for determining the intervals of strain measurement points with strong spatial correlations is proposed based on a support vector machine. Second, combined with the statistical analysis of the influence range of the uneven settlement of a tunnel, an algorithm for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed; this approach realizes the accurate identification of the uneven settlement area of long-distance urban railway tunnels. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual tunnel data.

Galangin(Gal) is a natural active flavonoid compound separated from the roots and rhizomes of Alpinia ofcinarum Hance. Modern pharmacological studies have shown that Gal has a variety of biological activities such as anti-tumor, anti-fungal, anti-bacterial, anti-inflammatory, anti-ischemic stroke, suppressing vitiligo and Alzheimer’s disease, etc. The purpose of this research was to prepare a galangin self-microemulsion drug delivery system (Gal-SMEDDS) and compare its anti-oxidant activity and pharmacokinetics with free Gal.The average particle size of the prepared Gal-SMEDDS was approximately 21.33 nm, the polydispersity index was 0.096, the zeta potential was -4.09 mV, and the entrapment efficiency was 96.74%. Compared with free Gal, the release of Gal-SMEDDS was improved in vitro release experiment. Cell experiments showed that Gal had obvious anti-oxidation effect, and the effect of Gal-SMEDDS was better than that of free Gal. In vivo pharmacokinetic experiments showed that the pharmacokinetic parameters of Gal-SMEDDS were better than that of free Gal, which indicated that the self-microemulsion drug delivery system(SMEDDS) effectively increases the oral bioavailability of Gal and alters its pharmacokinetic parameters, such that it may be effective in the treatment of anti-oxidant.

Soliton crystal micro-combs are powerful tools as sources of multiple wavelength channels for radio frequency (RF) signal processing. They offer a compact device footprint, large numbers of wavelengths, very high versatility, and wide Nyquist bandwidths. Here, we demonstrate integral order RF signal processing functions based on a soliton crystal micro-comb, including a Hilbert transformer and first- to third-order differentiators. We compare and contrast results achieved and the tradeoffs involved with varying comb spacing, tap design methods, as well as shaping methods.

Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for next-generation signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.

Revealing the binding properties of calcium ion (Ca2+) and magnesium ion (Mg2+) to chromophoric dissolved organic matter (CDOM) facilities understanding the effect of natural water composition on the photophysics of dissolved organic matter. Steady-state and time-resolved fluorescence spectrometry, and dynamic light scattering were applied to investigate the fluorescence quenching process of CODM by Ca2+ and Mg2+. The binding of Ca2+ and Mg2+ preferred terrestrial CDOM to aquatic CDOM. The fluorescence quenching of CDOM by cations mainly occurred in a static process, which was based on the fact that the decrease of steady-state fluorescence intensity was greater than fluorescence lifetime. The fluorescence quenching was profound under longer excitation and emission wavelength. The binding constant (K, L/mol) for Ca2+ to CDOM from terrestrial source ranged from 4.29 to 5.09 (lgK), which was approximately one order of magnitude higher than that of Mg2+ to CDOM (3.86 to 4.56). Fluorescence decay became faster in the presence of Ca2+ and Mg2+. Lifetime distribution of CDOM excited states shifted to small value side in the presence of metal ions, particularly for Ca2+, indicating fluorescence quenching of CDOM mainly through the interaction of Ca2+/Mg2+ with relatively long-lived fluorophores.

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr micro-comb source featuring a record low free spectral range of 49 GHz. By programming and shaping the comb lines according to calculated tap weights for up to 39 wavelengths across the C-band, we achieve tunable bandwidths ranging from 1.2 to 15.3 GHz as well as variable center frequencies from baseband to 9.5 GHz, for both standard integral and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shifts. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement standard and fractional order Hilbert transformers with broad and variable bandwidths and center frequencies, with high reconfigurability and greatly reduced size and complexity. Tan, and D. J. Moss are with the Optical Sciences Centre, Swinburne University of Technology, Hawthorn, VIC 3122, Australia. (Corresponding e-mail: [email protected]). Xu is with the Electro-Photonics Laboratory, Department of Electrical and Computer System Engineering, Monash University, Clayton, 3800 VIC, Australia

Plasma and serum are the most widely used blood-derived biofluids for metabolomics and lipidomics assays, but the isolation of these products from blood may introduce additional bias as indicated by the fact that many analytes that are present at high concentrations in blood cells cannot be measured and evaluated in those samples. Of particular concern, variable hemolysis during the pre-processing of blood products could compromise accurate and reproducible quantification. Compared with plasma or serum, whole blood may be a better alternative due to simplicity of processing. In this study, we provide a comprehensive method for quantification of the whole blood sphingolipidome and the concentrations were compared with those from plasma. Combining a single-phase extraction method with liquid-chromatography high resolution mass spectrometry (R=120, 000), assisted by alkaline hydrolysis, we were able to identify and simultaneously quantify more than 150 sphingolipids. Furthermore, most of sphingolipids remained stable after a freeze/thaw cycle. Whole blood contained a higher concentration of most sphingolipids than corresponding plasma. Moreover, individual variations in the levels of sphingolipids were lower for whole blood than plasma. These findings demonstrate that whole blood could be a better alternative to plasma, and potentially guide the evaluation of sphinglipidome for biomarker discovery.

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a novel approach to ONNs that uses integrated Kerr optical micro-combs. This approach is programmable and scalable and is capable of reaching ultra-high speeds. We demonstrate the basic building block ONNs — a single neuron perceptron — by mapping synapses onto 49 wavelengths to achieve an operating speed of 11.9 x 10⁹ operations per second, or Giga-OPS, at 8 bits per operation, which equates to 95.2 gigabits/s (Gbps). We test the perceptron on handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off-the-shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the C-band at 1550nm, resulting in a spectral efficiency of 10.4 bits/s/Hz. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency that, together with an extremely low spacing of 48.9 GHz enables a very high coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. This work demonstrates the ability of optical micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.

Convolutional neural networks (CNNs), inspired by biological visual cortex systems, are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network parametric complexity and enhance the predicting accuracy. They are of significant interest for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis [1-7]. Optical neural networks offer the promise of dramatically accelerating computing speed to overcome the inherent bandwidth bottleneck of electronics. Here, we demonstrate a universal optical vector convolutional accelerator operating beyond 10 Tera-OPS (TOPS - operations per second), generating convolutions of images of 250,000 pixels with 8-bit resolution for 10 kernels simultaneously — enough for facial image recognition. We then use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images with 88% accuracy. Our results are based on simultaneously interleaving temporal, wavelength and spatial dimensions enabled by an integrated microcomb source. This approach is scalable and trainable to much more complex networks for demanding applications such as unmanned vehicle and real-time video recognition.

We review recent work on broadband RF channelizers based on integrated optical frequency Kerr micro-combs combined with passive micro-ring resonator filters, with microcombs having channel spacings of 200GHz and 49GHz. This approach to realizing RF channelizers offers reduced complexity, size, and potential cost for a wide range of applications to microwave signal detection.

We review recent work on narrowband orthogonally polarized optical RF single sideband generators as well as dual-channel equalization, both based on high-Q integrated ring resonators. The devices operate in the optical telecommunications C-band and enable RF operation over a range of either fixed or thermally tuneable frequencies. They operate via TE/TM mode birefringence in the resonator. We achieve a very large dynamic tuning range of over 55 dB for both the optical carrier-to-sideband ratio and the dual-channel RF equalization for both the fixed and tunable devices.

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a new approach to ONNs based on integrated Kerr micro-combs that is programmable, highly scalable and capable of reaching ultra-high speeds, demonstrating the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths to achieve a single-unit throughput of 11.9 Giga-OPS at 8 bits per OP, or 95.2 Gbps. We test the perceptron on handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off-the-shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.

Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) has claimed nearly 180,000 lives and continues to spread. There are currently no approved medications or vaccines for this new coronavirus. Studies have shown that the positive RNA genome of SARS-CoV-2 contains unique features, including a 12-base sequence inserted between the two subunits of viral receptor protein Spike. This inserted sequence facilitates the cleavage of Spike by the cellular proteases Furin and TMPRSS2, leading to the fusion of virus and host cell membranes. Current studies are mostly focused on the SARS-CoV-2 Spike protein and its interacting cellular proteins ACE2, Furin, and TMPRSS2. RNA structural studies are limited and little is known about the potential impact of the 12-base sequence insert on the secondary structure of SARS-CoV-2 genomic RNA and/or its transcripts. Here, by using local and global RNA secondary structure predictions, we show that the novel 12-base insert of SARS-CoV-2 genome likely induces a major RNA secondary structure change.

With the development of Internet technology, teachers are constantly seeking innovative teaching methods to match the potential of enhanced technology. Although many studies have been performed before , they aren’t enough in this field. The purpose of this paper is to explore innovative teaching designs and examine the impact of Internet-assisted English teaching of reading based on constructivism. The case is carried out in NO.9 middle school of Bengbu, a underdeveloped area of China, most of students aren’t interested in learning English .We compared Internet-assisted with traditional textbook literature methods to improve the reading proficiency of students, using a questionnaire survey,pre-test and post-tests comparisons. The result showed Internet-assisted English reading teaching is better than textbook. It can arouse students' interest and motivation,reading proficiency and exam result of students have been improved significantly, created a positive learning situation.

Background: Rangeland degradation means that a reduction both in rank and status of general floral/ fauna composition, energy flow and biomass of a certain ecosystem. Objective: The review was conducted to assess rangeland degradation, cause and its impact on local livelihood in Yabello district and also suggests appropriate methods used to rehabilitate it. Methods: The data and literatures were collected from different both domestic and abroad researcher research result reviewed and internet sources. The research paper review mainly addresses concepts of rangeland degradation, major causes in tropics and Ethiopia particularly in Yabello rangelands, impacts of rangeland degradation, principles of rangeland restoration and common restoration techniques.Result: Based on those research papers and the current fact situations the major drivers leading to rangeland degradation includes climate change, overgrazing, bush encroachment, both human and livestock population pressure, drought, and government policy . Of all bush encroachment is becoming the major threat to Yabello rangelands. And this led to decline in rangeland condition, water potential, soil status, and animal performance, livestock holding at the household level and community become destitute and in the long run poverty. In spite of these impacts, the action of restoration techniques in the area is highly insufficient. Conclusion: Generally in order to address rangeland degradation problems, there is a strong need to coordination between the local community and the scientific community for sustainable land management trough post management techniques by applying reseeding technology.

The application of solvent method in the preparation of polypropylene powders was investigated, including the influence of various technological conditions, such as the raw material melt index of polypropylene, processing temperature, dosage of the solvent and the packing pressure. The experimental data show that using solvent method can effectively produce polypropylene powder, and the optimal technological conditions are: melt index of polypropylene being about 17.8 g/10min, processing temperature being about 166.0 ℃, dosage of the solvent being about 0.067g/ml and the packing pressure being about 0.7MPa.Under this technological conditions, polypropylene powder with excellent sphericity could be prepared, the apparent density of powder can reach 0.40 g/cm3 and the prepared powder displayed a narrow size distribution with the mean size of about 42.7 µm.

It is demonstrated in this study that PhabrOmeter creates genuine wrinkle on fabrics comparable to that in AATCC specifications, and measures fabric wrinkle recovery values fast with repeatable and reliable results with high resolution, over wide range of fabric types. It thus provides an appealing alternative to the existing test methods that are known to be slow, insensitive and unreliable. In addition, with enormous varieties of fabrics, we used a new criterion termed fabric linear density λ so that fabrics can in general be divided into relatively homogeneous groups for further study. The calculation and application of this parameter are showed in this report.

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their readiness to be implemented. The damping performances of the three different modes are listed and compared. Electrical circuit and control algorithms have also been evaluated to maximize the power output and to deliver the premium ride comfort and handling performance. Different types of parameterized road excitations have been applied to vehicle suspension systems to investigate the performance of the regenerative shock absorbers including that of the nonlinear regenerative shock absorber. The research gaps for comparison of the different drive modes and the nonlinearity analysis of the regenerative shock absorbers are identified and, the corresponding research questions have been proposed for future work.

This paper studies the optimization method of pump hydraulic performance based on the response surface method. A parametric model of impeller and diffuser is established. Three-dimensional optimization is carried out on the basis of the initial model obtained by one-dimensional design method. We select the pump hydraulic efficiency and the head as objective function and constraint function. Response surface models are constructed to analyze the relationship between the objectives and the design variables, and the global optimization of hydraulic performance is realized. According to the internal flow characteristics of pump, this paper proposes the strategy of two steps optimization, which aims at meridional plane and blade shape, respectively, to solve the problem of large numbers of design parameters and computational cost. The optimization results show that the hydraulic efficiency of pump increased by 3.7%, and the head is nearly the same.

Using DCC-GARCH and EGARCH model, this paper finds that since 1990, the relationship between crude oil prices and the US dollar index is time-varying, demonstrating a process of “very weak correlation—negative correlation—enhanced negative correlation—weakening negative correlation”, but the existing research does not provide enough reasonable explanation. Therefore, this paper proposed a “key mediating factors” hypothesis which points out that whether there is a common “key mediating factor” is important source of the time-varying relationship between two assets. We argue that market trend and financial market sentiment undertook the role of “key mediating factor” during the period of “2002 to the financial crisis” and “financial crisis to 2013”, while other periods lack the “key mediating factors”.

With huge varieties of fabrics, the first challenge for any performance evaluation is to categorize the vast types of the products into fewer, more homogeneous and thus akin groups. Classification or sorting is arguably the first step of any scientific investigation, and comparison of product quality is meaningful only when conducted within a group of comparable products. A new criterion termed fabric linear density λ is first proposed in this paper so that fabrics can in general be divided into 4 groups. The derivation and validation of this parameter are provided. The importance of fabric drape is almost self-evident, but there is still no effective ways to measure this fabric attribute. The Cusick Drapemeter suffers from its low repeatability and low sensitivity, and is hence not widely or frequently used. The PhabrOmeter, along with the fabric linear density λ, is proposed and demonstrated in this study as a much more efficient alternative for fabric drape test. By actually testing 40 various fabrics, the principle, procedure and results of this method is presented in this paper.

Strata and surface movement induced by mining under open-pit final slope is a huge threat to mine safety. Physical model test is an important method to study mining-induced strata and surface movement laws. Because of rock joints predominantly control rock mass deformation and failure, thus physical model test leaving out of consideration of rock joints is difficult to reflect the influence of rock joints on rock mass deformation. Therefore, this paper presents a three-dimensional physical model test considering simplified dominant rock joints. This test process includes the design of testing equipment, the construction of physical model with dominant rock joint sets, conduction of mining and deformation monitoring. And mining under eastern final slope of Yanqianshan iron mine was selected as a case to study the behavior of mining-induced strata and surface movement.

Interface between matrix/coating or coating/coating in fact represents a very complicate thin interfacial layer. So interface model is necessary to avoid the difficulty on considering such a complicate thin layer in analysis. Classic interface model and cohesive model have been widely used in stress analysis of coating materials, though they cannot represent the effect of very thin interfacial layer accurately. A complete interface model has been deduced from the equivalent constitutive of interfacial layer in this paper. It is found that both classic interface model and cohesive model sometimes cannot give correct analysis results, while the complete interface model can always give a correct result. Moreover, the stress parallel to interface within the interfacial layer can also be analyzed by the new model. Besides, this model can also be used to describe the equivalent properties of interfacial layer, thereby, can provide a quantitative characterizing method for interfacial layer itself.

High-precision dynamic positioning of highway vehicles is the foundation and prerequisite for achieving intelligent connected transportation. For the shortcomings of GNSS/INS combination and GNSS/INS/OD combination in tunnel vehicle positioning, this paper proposes a tunnel vehi-cle positioning method of GNSS/INS/OD combination based on lateral distance measurement and lane constraint. Firstly, lateral distance measurement of vehicles inside the tunnel is conducted based on laser radar point cloud data. Secondly, map matching positioning is performed based on lateral distance measurement, odometer, and lane markings. Experimental results demonstrate that for a 4.6 km tunnel, the average absolute error of lateral positioning is 0.294 meters, and the longitudinal positioning error is no more than 0.6 meters, which can effectively meet practical operational requirements.

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions.

Digital infrastructure is the basic guarantee for digital transformation, it is of practical significance to discuss how to effectively use digital infrastructure construction to promote the digital transformation of tourism enterprises. This paper examines the impact of digital infrastructure construction on tourism enterprises based on the "Broadband China" policy as a quasi-natural experiment. A-share tourism listed enterprises from 2010 to 2021 are studied using the double difference method. Findings indicate that digital infrastructure construction positively and significantly influences the digital transformation of tourism enterprises, driven by digital leadership and innovation capabilities. State-owned, small-scale, and high-growth tourism enterprises benefit more from this transformation. The results suggested that the state should develop differentiated digital infrastructure plans based on the specific conditions of different tourism enterprises. Additionally, tourism enterprises should enhance digital leadership and innovation capabilities through strategic changes and digital applications to amplify the impact of digital infrastructure on their transformation.

Sea level rise (SLR) is a critical consequence of climate change, posing significant threats to coastal regions worldwide. Accurate and efficient assessment of potential inundation areas is crucial for effective coastal planning and adaptation strategies. This study aims to explore the utility of free and open source software for geospatial (FOSS4G) tools for mapping SLR inundation, providing cost-effective solutions that are accessible to researchers and policymakers. We employed a combination of geospatial data, including high-resolution elevation models, tidal data, and projected SLR scenarios. Utilizing widely available FOSS4G tools like QGIS, GDAL/OGR and GRASS GIS we developed an integrated workflow to map inundation extents using a passive bathtub approach for various SLR scenarios. Our findings demonstrate that FOSS4G tools offer reliable and accessible means to map SLR inundation, empowering stakeholders to assess coastal vulnerabilities and devise sustainable adaptation measures. The open-source approach facilitates collaboration and reproducibility, fostering a comprehensive understanding of the potential impacts of SLR on coastal ecosystems and communities.

Hypersonic aircraft focuses more on the integration of aircraft and engine than ordinary aircraft owing to high performance requirements, and the nozzle design is reflected in the required large area ratio of nozzle inlet and outlet and the compactness of the overall size of the aircraft. In this study, the height constraint is directly introduced into the maximum thrust nozzle design method. A new method for designing nozzles under the height constraints that consults the maximum thrust theory is proposed. Initially, the condition that the nozzle reaches the maximum thrust under the height constraint is deduced mathematically. Then, a nozzle design method satisfying the height constraint is computed using the method of characteristics (MOC). Subsequently, the influence of the design parameters on the design method is studied parametrically. Results show that Mach number scale and asymmetrical factors can affect ramp length and flap length of the nozzle, respectively. These factors great influence the axial thrust performance and lift under a specific height constraint. Compared with the traditional truncation design method, the thrust coefficient and lift increased by 11.93% and 138.45% respectively.

Objective: To evaluate the effect of care bundles on treatment compliance and intestinal barrier function in patients with refractory septic shock in the intensive care units (ICUs). Methods: In this retrospective study, the clinical data of 94 patients with refractory septic shock admitted to our hospital between June 2020 and April 2022 were collected. Patients with routine nursing were included in the routine group, and those with care bundles were assigned to the care bundles group, with 47 cases in each group. Outcome measures included nursing efficiency, treatment compliance, sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation (APACHE II) score, intestinal barrier function, inflammation factor level, treatment outcome and complications. Results: Care bundles resulted in significantly higher nursing efficiency and treatment compliance versus routine care (P<0.05). Patients receiving care bundles showed significantly higher SOFA scores and APACHE II scores than those receiving routine care (P<0.05). Intestinal fatty-acid binding protein (I-FABP), diamine oxidase (DAO), lactate, endotoxin, and intestinal dysfunction scores in the care bundles group were significantly lower than those in the conventional group after treatment (P<0.05). Care bundles were associated with significantly lower levels of procalcitonin (PCT) and hypersensitive C-reactive protein (hsCRP), shorter time to symptom relief, ICU treatment time, and duration of mechanical ventilation, and lower 28-d morbidity and mortality versus routine care (P<0.05). Patients in the care bundles group had a significantly lower incidence of complications than those in the routine group (P<0.05). Conclusion: Care bundles effectively enhance treatment compliance, improve intestinal barrier function and treatment outcomes, reduce the inflammatory response, and decrease the risk of SOFA score, APACHE II score, and complications in patients with refractory septic shock.

Objective: To evaluate the effect of care bundles on treatment compliance and intestinal barrier function in patients with refractory septic shock in the intensive care units (ICUs). Methods: In this retrospective study, the clinical data of 94 patients with refractory septic shock admitted to our hospital between June 2020 and April 2022 were collected. Patients with routine nursing were included in the routine group, and those with care bundles were assigned to the care bundles group, with 47 cases in each group. Outcome measures included nursing efficiency, treatment compliance, sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation (APACHE II) score, intestinal barrier function, inflammation factor level, treatment outcome and complications. Results: Care bundles resulted in significantly higher nursing efficiency and treatment compliance versus routine care (P<0.05). Patients receiving care bundles showed significantly higher SOFA scores and APACHE II scores than those receiving routine care (P<0.05). Intestinal fatty-acid binding protein (I-FABP), diamine oxidase (DAO), lactate, endotoxin, and intestinal dysfunction scores in the care bundles group were significantly lower than those in the conventional group after treatment (P<0.05). Care bundles were associated with significantly lower levels of procalcitonin (PCT) and hypersensitive C-reactive protein (hsCRP), shorter time to symptom relief, ICU treatment time, and duration of mechanical ventilation, and lower 28-d morbidity and mortality versus routine care (P<0.05). Patients in the care bundles group had a significantly lower incidence of complications than those in the routine group (P<0.05). Conclusion: Care bundles effectively enhance treatment compliance, improve intestinal barrier function and treatment outcomes, reduce the inflammatory response, and decrease the risk of SOFA score, APACHE II score, and complications in patients with refractory septic shock.

Because of hyper complexity, difficulty to define, multiple stakeholders with conflicting perspectives, and lack of clear-cut solutions, wicked problems necessitate innovative and adaptive strategies. Operations Research has been a valuable tool for managers to make informed decisions for years. However, as we face increasingly complex and messy problems, it has become apparent that relying solely on either hard or soft OR approaches is no longer sufficient. We need to explore more innovative methodologies to address these wicked problems effectively. This study has bridged the research gap by proposing a structured process encompassing a subdivision-based problem structuring method for defining the wicked problem, a multi-attribute decision-making (MADM) for prioritizing sub-problems, and a hard OR technique, data envelopment analysis (DEA) for tackling one of the most critical sub-divisions. The proposed methodology, implemented in a case study, focuses on a higher education institution experiencing a decline in student admissions and involves five steps. First, a diverse group of stakeholders is formed to ensure comprehensive consideration of perspectives. Second, the wicked problem is defined, considering long-term consequences, multiple stakeholders, and qualitative stakeholder opinions. Third, a hierarchical structure is created to break down the wicked problem into manageable sub-problems. Fourth, a multi-criteria decision-making (MCDM) method prioritizes sub-problems. Finally, the sub-problems are addressed one by one using a combination of soft and hard OR tools. The findings highlight the benefits of integrating hard and soft OR approaches. The article concludes with reflections on the implications of using a combined OR approach to tackle wicked problems in higher education and beyond.

Studying concurrent systems is to sort the read/write and control events in the concurrent system according to the order, or in partial order, or in strict order. Because of the concurrency of events and the timeliness of writing events, there will be overlap between events, which requires interval order analysis. A single start and end sequence to represent the entire hierarchical order structure as well as all equivalent spaced order observations.a single sequence of beginnings and endings to represent the entire stratified order structures as well as all equivalent interval order observations. Mazurkiewicz traces and Comtracks are hierarchical traces, but they cannot describe interval traces. In a few sentences of this summary, we can tell the problems (petri interval traces with data), the previous work (Mazurkiewicz traces, Comtracks), the reasons that cannot be solved, and our own solutions (DPN: Petri nets with data, interval traces). This paper focuses on a BE (Beginnings and Endings) sequence representing an equivalent class of runs, or targets. Our goal is to have a BE sequence to represent the entire hierarchical order structure, that is, all equivalent observable interval orders.

This study numerically evaluated the long-term and stable trends of meandering channel planform at different mean annual subcritical flows based on a depth-averaged linearized meander evolution model. The calculation cases included an idealized sine-generated meander with moderate max-deflection angle and a typical natural meander - Jiyun River (in China). Within the increase of the selection of the mean annual width-depth ratio in a certain scope, the results showed some specific phase characteristics of channel centerline evolution: (1) the meander straightening trend became weaker in phase 1 (B/H ≤ 16.5) and gradually turned into the meander developing trend in phase 2 (B/H ≤ 27) with the overall immunity to flow magnitude; (2) the symmetric development form along the transverse direction perpendicular to the flow average direction was broken starting from the downstream tail in phase 3 (B/H ≤ 28.9), meantime accompanied by the highlight of flow effects when the mean annual B/H exceeded 28; (3) in phase 4 (B/H ≤ 29.5), there occurred obvious incipience and jump process of the channel sensitivity responding to flow when the selected B/H crossed 29.3, which were very similar to the transition process from the laminar flow to turbulent flow. Besides, the initial sinuosity and curvature-ratio indicator could contribute much to the channel evolutionary state, as demonstrated in the comparison between natural Jiyun River case and the correspondingly idealized sine-generated meander case with the same level of mean annual B/H. This research provides innovation spaces for deeper meander mechanism exploration and effective riparian management.

We conducted the meander evolution experiments incorporating the effects of riparian vegetation and the series of upper vortex flow disturbances induced by a scour pit simultaneously. Two employed nonlegume plants with salinity and alkalinity resistance, had uniform degrees of seedling normal growth and different lengths of root networks. Our results show that riparian vegetation in general can consolidate the single-thread channel planform without branching outward under the flooding flow conditions. Transverse point bars on inner banks were instead by downstream scroll bars in overall channel for long, unless the coupling of riparian vegetation and flood scour. Shallow-rooted plant was inadequate to resist the inner-bank cutting effect brought by the upper vortex flow. Deep-rooted plant can stabilize the bank-lines and thalweg significantly, but that was susceptible to locally low vegetation coverage. Using evolutionary spectral analysis based on thalweg, we found streamwise high-frequency distribution of bed topography mainly concentrated downstream the bifurcation interface in unvegetated scenario when faced with a flood, shrank to the upper isolated turning interface in shallow-rooted scenario, and conversely stood out along the bare roots disturbed region in deep-rooted scenario. This experimental study expands a much wider understanding of vegetation effects in hydro-bio-geomorphological systems engineering.

Objective: To visualize and analyze the published literature on diabetes and pyroptosis based on a bibliometric approach, so as to provide a comprehensive picture of the hot research directions and dynamic progress in this field. Methods: This study was based on the web of science core collection database to conduct a comprehensive search of the published literature in the field of diabetes and Pyroptosis from January 1985 to August 2022, including the published research literature in this field, as well as a visual analysis of the number of citations, year of publication, journal, author, research institution, country, and research topic. Results: A total of 139 literature on research related to diabetes and cellular scorch from 2011 to 2022 were retrieved, with a total of 3009 citations and a maximum of 255 citations for a single article, which had a first authorSchmid-Burgk, JL The first author of this article is from Germany; among 20 publishing countries, China leads with 100 articles; among 222 publishing institutions, Harbin Medical University leads with 18 articles and 184 citations; among 980 authors, Chen, X from China tops the list of high-impact authors with 5 articles and 29 citations; Among the 98 journals, "CELL DEATH DISEASE" ranked first in both volume and high impact journals with 4 articles and 29 citations; among 349 keywords, "pyroptosis" ranked first with a cumulative frequency of 65 times. The cluster analysis was divided into three categories, chronic complications of diabetes and pyroptosis (67 articles), diabetes and pyroptosis (60 articles), and diabetes combined with other diseases and pyroptosis (12 articles), and the number of articles related to diabetes and its chronic complications increased rapidly from 2019, among which, diabetic cardiomyopathy (27 articles) had the highest number of articles. Conclusions: Based on a comprehensive analysis of published literature in the field of diabetes and pyroptosis from 2011-2022, this study achieved a visual analysis of studies with significant and outstanding contributions to the field, thus framing a picture showing the development and changes in the field. At the same time, this study provides research information and direction for clinicians and investigators to conduct diabetes and pyroptosis related research in the future.

In this study a method for predicting the preferred pleasantness induced by different forest environments, represented by virtual photographs, was proposed and evaluated using a novel Anti-Environmental Forest Experience Scale psychometric test. The evaluation questionnaire contained twenty-one items divided into four different subscales. The factor structure was assessed in two separate samples collected online (sample 1: N = 254, sample 2: N = 280). The internal validity of the four subscales was confirmed using an exploratory factor analysis. Discriminant validity was tested and confirmed using the Amoebic Self Scale (Spatial-Symbolic domain). Concurrent validity was confirmed using the Connectedness to Nature Scale. Predictive validity was based on assessment of pleasantness induced by nine different photographs (control – urban landscapes, forest landscapes, dense forest landscapes), with subscales differently correlated with the level of pleasantness assessed for each photograph. This evaluation instrument is appropriate for predicting preferred pleasantness induced by different forest environments.

Using machine learning or deep learning to solve the problem of garbage recognition and classification is an important application in computer vision, but due to the incomplete establishment of garbage datasets and the poor performance of complex network models on smart terminal devices, the existing garbage classification models The effect is not good.This paper presents a waste classification and identification method base on transfer learning and lightweight neural network. By migrating the lightweight neural network MobileNetV2 and rebuild it, The reconstructed network is used for feature extraction, and the extracted features are introduced into the SVM to realize the identification of 6 types of garbage. The model was trained and verified by using 2527 pieces of garbage labeled data in the TrashNet dataset, which ultimately resulted in a classification accuracy of 98.4% of the method, which proves that the method can effectively improve the classification accuracy and time and overcome the problem of weak data and less labeling. The over-fitting phenomenon encountered by small data sets in deep learning makes the model robust.

The development of biosensors with high sensitivity and low-detection limits provides a new direction for medical and personal care. Graphene and graphene derivatives have been used to prepare various types of biosensors due to their excellent sensing performance (e.g. high specific surface area, extraordinary electronic properties, electron transport capabilities and ultrahigh flexibility). This perspective review focuses on graphene-based biosensors for quantitative detection of cancer related biomarkers such as DNA, miRNA, small molecules and proteins by integrating with different signal outputting approaches including fluorescent, electrochemistry, surface plasmon resonance, surface enhanced Raman scattering etc. The article also discussed their challenges and potential solutions along with future prospects.

In the world city theory, most researchers focus on the service sector in the urban economy and less discuss the role of manufacturing. However, the path of only emphasizing financial and corporate service could not fit the sustainability concept. Compared to Anglo-American world city, Global South’s world cities have distinct pathway to be industrialization, tertiarization and globalization. This paper adopted dynamic historic perspective with first-hand materials including in-depth interviews with managers and government officers and second-hand data including yearbook statics and economic census to closely examine the emerging world city-- ‘World Factory’ in Global South, Guangzhou in China, from 1949 to 2015, to emphasize how manufacturing affects the urban globalization through three dimensions, economic, social and spatial dimensions. To make the confirmation of the role of manufacturing in Guangzhou as sustainable world city, we find manufacturing in Guangzhou builds up the basic foundation of export-oriented economy and makes positive effects on urban economic transformation. In addition, manufacturing remains important source of employment and foreign immigration. Along with urbanization and industrialization, urban spatial expansion and aggregation changes with different urban development concept. We provide new insights on multiple globalization on manufacturing for sustainable world city.

Meshfree particle method, which is always regarded as a pure Lagrangian approach, is easily represented complicated domain topologies, moving boundaries, and multiphase media. Solving acoustic problems with the mesfree particle method forms a branch of the acoustic wave modeling field, namely, particle-based computational acoustics (PCA). The aim of this paper is to improve the accuracy of using the PCA method to solve two-dimensional acoustic problems, and realize the particle representation with a hybrid meshfree and finite-difference time-domain (FDTD) method for acoustic boundary conditions at both the plane and curved surface. As a widely used Lagrangian meshfree method, the smoothed particle hydrodynamics (SPH) based on the support domain and the kernel function has developed rapidly in recent years. The traditional SPH method is easily implements parallel processing and has been applied in sound wave simulation. As a corrective method with higher accuracy than SPH, the acoustic propagation and scattering in the time domain is simulated with the corrective smoothed particle method (CSPM). Moreover, a hybrid meshfree-FDTD boundary treatment technique is utilized to represent different acoustic boundaries in the Lagrangian approach. In this boundary treatment technique, the parameter value of virtual particles is obtained with the FDTD method, which concerns truncation errors based on the Tayler series expansion. Soft, rigid, and Mur’s absorbing boundary conditions are developed to simulate sound waves in finite and infinite domain. Results of modeling acoustic propagation and scattering show that CSPM is accurate and convergence with exact solutions, and different acoustic boundaries are validated to be effective in the computation.

(-)-Zeylenone is a promising cytotoxic agent，which is a natural product isolated from Uvaria grandiflora Roxb. Though substantial antitumor mechanism has been researched , little has focused on its enantiomer (+)-Zeylenone.This article will try to find a gram scale synthesis method of (+)-Zeylenone and explain the structure-activity relationship of this kind of compound. Total synthesis of (+)-zeylenone was completed in 13 steps with quinic acid as starting material in 8.8% overall yield. The highlight of the route was the control of the three carbon’s chirality by clever use of single step dihydroxylation under the direction of the key C-3 chirality. In addition, zeylenone derivatives were designed and synthesized and their antitumor activity were evaluated against three human cancer cell lines using the CCK8 assay. Structure-activity relationship suggested compounds with both two absolute configurations exhibited good activity. Besides, hydroxyls at C-1/2 position were crucial for the activity and esterification of C-1 hydroxyl with large groups made the activity disappeared. Hydroxyl at C-3 position was also important as proper ester substituent could increase the potency.

In breast cancer, epithelial-mesenchymal transition (EMT) is positively associated with programmed death ligand 1 (PD-L1) expression and immune escape, and TWIST1 induces EMT and cancer metastasis. However, how TWIST1 regulates PD-L1 and immune evasion is unknown. This study analyzed TWIST1 and PD-L1 expression in breast cancers, investigated the mechanism for TWIST1 to regulate PD-L1 transcription, and assessed the effects of TWIST1 and PD-L1 in cancer cells on the cytotoxicity of CD8+ effector T cells. Interestingly, TWIST1 expression is associated with high-level PD-L1 in triple negative breast cancers (TNBCs). Overexpression and knockdown of TWIST1 robustly upregulates and downregulate PD-L1 expression, respectively. TWIST1 binds to the PD-L1 promoter and recruits the TIP60 acetyltransferase complex in a BRD8-dependent manner to promote PD-L1 expression, which drives immune escape of breast cancer cells by accelerating the exhaustion of CD8+ T cells. Accordingly, knockdown of TWIST1 or BRD8 or blockade of PD-L1 with a PD-L1 antibody significantly enhances CD8+ T cells to inhibit breast cancer cell growth. These results demonstrate that TWIST1 directly induces PD-L1 expression in breast cancer cells to drive immune evasion. Targeting TWIST1, BRD8 or PD-L1 in TNBC should facilitate CD8+ T cell-mediated immune therapy. TWIST1 may also serve as a biomarker for anti-PD-L1 immunotherapy.

In this paper, a distributed algorithm is proposed to solve a consensus convex optimization problem. It is a Jacobi-proximal alternating direction method of multipliers with a damping parameter $\gamma$ in the iteration of multiplier. Compared with existing algorithms, it has the following nice properties: (1) The restriction on proximal matrix is relaxed substantively, thus alleviating the weight of the proximal term. Therefore, the algorithm has a faster convergence speed. (2) The convergence analysis of the algorithm is established for any damping parameter $\gamma\in(0,2]$, which is larger ones in the literature. In addition, some numerical experiments and an application to a logistic regression problem are provided to validate the effectiveness and the characteristics of the proposed algorithm.

The valve controlled cylinder drive system is the most common type among hydraulic applications. The nonlinear behaviour in such system is inevitable when the valve spool around its null position [1] , Leaney [2] utilised component linking method to investigate the nonlinearities in a Moog valve controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An factor is proposed in the generalised concepts to describe the asymmetric cylinder state, which is a constant when the cylinder in extending or retracting, but numerically calculated when the valve spool in the underlap region [2]. This paper utilises the component linking method to simulate the Moog valve controlled asymmetric cylinder drive system in Matlab Simulink, and proposed an analytical solution for factor when the valve spool in the underlap region.

When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to the imbalance in samples dataset, as well as the complexity and laboriousness of annotating and acquiring target image masks. In order to solve these problems, a method based on sample and mask auto-generation for deep generative network models is proposed. We first generate an augmented dataset of negative samples using a generative adversarial network(GAN), and then highlight the defect regions in these samples using the training method constructed by the GAN to generate masks for the defect images automatically. Experimental results shows the effectiveness of our proposed method, as it allows for the simultaneous generation of LCD image samples and their corresponding image masks. Through a comparative experiment on the deep learning method Mask R-CNN, we demonstrate that the automatically obtained image masks have high detection accuracy.

In order to further investigate the study of the effect of grouped stud effect on the force properties of stud connector, based on the premise that the correctness of the finite element simulation method in this paper, finite element modeling of grouped stud connectors was developed, the grouped stud effect and its sensitivity factors were analyzed, to validate the recommended formula for calculating the shear capacity of grouped stud connectors. Results show that the number of grouped stud rows and row spacing have a significant effect on the grouped stud effect, and the unevenness coefficient of grouped stud force Ⅰ is negatively correlated with the number of grouped stud rows as well as the grouped stud row spacing. For grouped stud connectors with commonly used concrete grades greater than C50 and height-to-diameter ratios greater than 4 in steel-concrete composite structural bridges, which is insensitive to changes in the concrete strength grades and the length of the studs. The direction of force transmission for the grouped stud changes with the change of loading angle, and the unevenness coefficient of force for the grouped stud will therefore be reduced. By comparing the results of the 62 existing groups of grouped stud connectors push-out tests, the mean value of the ratio of tested to calculated values is found to be 1.12, the variance is 0.023, the dispersion is small, it is shown that the recommended formula has a high degree of accuracy. The results of this paper can be used as a theoretical basis for the study of the shear stress performance of grouped stud connectors.

This work investigates the sliding mode control (SMC) problem for a class of uncertain switched systems subject to asynchronous switching and an assigned finite time constraint. Two important issues are how to ensure the reachability of state trajectories within the assigned time and the input-to-output finite-time stability (IO-FTS) of the closed-loop switched systems during the whole phase under asynchronous switching. To achieve these objectives, an asynchronous sliding mode controller with adjustable parameters is constructed to drive the state trajectories onto the sliding surface during the assigned finite-time interval. By means of the partitioning strategy, sufficient conditions for the IO-FTS of the closed-loop switched are derived during the whole phase [0,T] using the multiple Lyapunov function (MLF) approach. Additionally, the asynchronous characteristics are detailedly investigated while analyzing the reachability of a specified sliding surface. Finally, an illustrative example is given to illustrate the effectiveness of the proposed method.

In order to clarify the individual role of freezing and frozen storage on the quality of fish, fillets of large-mouth bass (Micropterus salmoides) were subjected to different freezing rates (freezing with -18 °C (A), -60 °C (B), -60 °C with forced air circulation at 2 m/s (C), respectively) followed by frozen storage at -18 °C for 30 and 90 days. Another 2 groups were frozen with -60 °C, followed by storage at -40 °C (D) and -60 °C (E), respectively. Results showed that water-holding and TVBN were mainly affected by storage time. No significant changes were found in free thiol content among treatments. A greater freezing rate and lower storage temperature generally led to lower TBARS. GC×GC-TOFMS revealed a total of 66 volatile compounds which were related to lipid oxidation. PLS-DA showed that fresh samples were separated from the frozen-thawed ones, and fillets in group D &amp; E were relatively close to fresh fillets in the composition of oxidation-related volatiles. In conclusion, freezing rate and storage temperature had significant impact on lipid oxidation and protein denaturation in the fillets of large-mouth bass, while protein oxidation was more affected by freezing rate.

The adsorption of supramolecular composites for Cs(I) in high level liquid waste (HLLW) are different due to different carriers. We chose 25,27-bis(ethyl)-calix[4]arene-26,28-crown-6 (EC[4]C6) as adsorbent, SiO2-P, XAD-7 and UiO-66 as carriers. The synthesis and characterization of supramolecular EC[4]C6 loaded with three different carriers were presented. SEM, N2 adsorption/desorption isotherms, TG-DSC spectra, FT-IR spectra results shown that EC[4]C6 was successfully introduced into the pores of carriers via physical intermolecular interactions. EC[4]C6/SiO2-P, EC[4]C6/XAD-7 and EC[4]C6/UiO-66 shown high efficiency, high selectivity towards Cs(I) over 18 typical fission or corrosion products in HNO3 solution. The adsorption properties of the three materials were investigated after electron irradiation. These results demonstrate that EC[4]C6/SiO2-P possess greater potential for highly efficient removal of Cs(I) from HLLW.

The purpose of this article is to disclose the strenuous efforts of Laszlo Hudec in China and Antonin Raymond in Japan and India to create a modern architectural stance by heralding an incipient space syntax. In the turn of the 19th Century, for dynastic, politic and economic reasons, Eastern Asia had very little modern Architecture. It is a surprising fact that, out of happenstance, two European architects Antonin Raymond and Laszlo Hudec, had to intervene to remedy this situation, to the point of becoming 20th Century icons in Japan and China. Their fruitful careers spanned over thirty years and included locations, like Tamil Nadu or the Philippines. The Oriental territories were not an easy ground for the bold architectural achievements that they produced. Despite of faraway strangeness and uncountable personal losses, in revolutions and wars, which eventually forced them both to leave for the United States of America and never to return, they were successful in the manner of establishing a broad avenue for Modern Asian Architecture which is still recognisable today thanks to their systematic approach. However, theirs is an endangered heritage and the intention of this article is to be a just remembrance of in which way such actions could be performed, how they predated by many years a syntactic approach to architectural composition and why their legacy should be preserved.

Keywords: underground engineering; numerical simulation; excavation length effect, major principal stress; displacement; damage initiation; CPU time

Aims: To assess the occurrence of Chemotherapy-induced nausea and vomiting (CINV) after standard antiemetic therapy in the acute (24 h post-chemotherapy) and delayed (2–5 days post-chemotherapy) phases, as well as to identify risk factors for CINV in the acute and delayed phases. Methods: This prospective longitudinal and observational study analyzed the data of 400 breast cancer patients scheduled for chemotherapy over two cycles in two hospitals. The self-report survey was developed to assess the occurrence of CINV and their associated factors. CINV was evaluated with a Multinational Association of Supportive Care in Cancer Antiemetic Tool (MAT) on days 2 and 6 of chemotherapy. The incidence of acute and delayed CINV were presented by frequency and percentage. Generalized equation estimates (GEE) was used to identify risk factors of acute and delayed CINV. Results: There were 400 evaluable patients with complete Round 1 data, 334 for Round 2 data. Among 400 patients, 29.8% and 23.5% experienced acute and delayed CINV, respectively. Risk factors associated with for acute CINV were pain/insomnia, history of CINV, history of motion sickness (MS), and highly emetogenic chemotherapy regimen, while history of MS, CINV history, number of completed chemotherapy cycle number < 3, and the incidence of acute CINV were risk factors of delayed CINV (all p < 0.05). Conclusions: The findings may help nurses working for Chinese population in identifying patients at risk for CINV and in planning effective program to reduce the occurrence of CINV.

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) proteins are a diverse and evolutionarily conserved family of cytidine deaminases that provide a variety of functions from tissue-specific gene expression and immunoglobulin diversity to control of viruses and retrotransposons. APOBEC family expansion has been documented among mammalian species, suggesting a powerful selection for their activity. Enzymes with a duplicated zinc-binding domain often have catalytically active and inactive domains, yet both have antiviral function. Although APOBEC antiviral function was discovered through hypermutation of HIV-1 genomes lacking an active Vif protein, much evidence indicates that APOBECs also inhibit virus replication through mechanisms other than mutagenesis. Multiple steps of the viral replication cycle may be affected, although nucleic acid replication is a primary target. Packaging of APOBECs into virions was first noted with HIV-1, yet is not a prerequisite for viral inhibition. APOBEC antagonism may occur in viral producer and recipient cells. Signatures of APOBEC activity include G-to-A and C-to-T mutations in a particular sequence context. The importance of APOBEC activity for viral inhibition is reflected in the identification of numerous viral factors, including Vif, which are dedicated to antagonism of these deaminases. Such viral antagonists often are only partially successful, leading to selection for viral variants.

Permanent magnet synchronous motor (PMSM) AC servo system shows the characteristics of uncertainty, time-varying and non-linearity, which makes it difficult for traditional PID control to achieve ideal control effect. Fuzzy control has strong adaptability to the problems of parameter variation, non-linearity and model inaccuracy of the controlled object. Vector control strategy is used to study its control principle and the realization of SVPWM. Because the motor object has certain fractional order characteristics, the fuzzy parameter self-tuning PIλ control is chosen as the position regulator of servo motor. It combines the accuracy of fractional order PI control and the adaptability of fuzzy control. A simulation model of PMSM three-closed-loop system is built in MATLAB/Simulink environment. The results show that the control method is effective and can satisfy the trajectory tracking of servo control.

In the process of sustainable development in the future, human society faces problems such as severe population load, economic transition, and lack of educational measures. One of the root causes of these problems is the shortage of innovative talents. Therefore, how to cultivate learners with multi-disciplinary integration and innovation ability is the key point that should be paid attention to in promoting the concept of quality education and coping with the future sustainable development process. This paper uses questionnaire survey method and literature analysis method to analyze the development of many educational institutions with STEAM concept as the core in China since 2017. It is found that the existing STEAM educational institutions generally have the following problems: the lack of team composition、difficulty in independent research and development、single course content and insufficient validation of course effectiveness. In order to more effectively promote the sustainable development of China's future course, STEAM education institutions should focus on strengthening the following development strategy: gradient team building, continuous independent research and development, cutting-edge projects curriculum transformation mechanism and multi-angle course effectiveness verification.

Recently, there have been revolutions in the development of both gene therapy and genome surgical treatments for inherited diseases. Much of this progress has been centered around hereditary retinal dystrophies, because the eye is an immune-privileged and anatomically ideal target. Gene therapy treatments, already demonstrated to be safe and efficacious in numerous clinical trials, are benefitting from the development of new viral vectors, such as dual and triple AAVs. CRISPR/Ca9, which revolutionized the field of gene editing, is being adapted into more precise “high fidelity” and catalytically dead variants. New CRISPR endonucleases, such as CjCas9 and Cas12a, are generating excitement in the field as well. Stem cell therapy has emerged as a promising alternative, allowing human embryo derived stem cells and induced pluripotent stem cells to be edited precisely in vitro and then reintroduced into the body. This article highlights recent progress made in gene therapy and genome surgery for retinal disorders, and it provides an update on precision medicine FDA treatment trials.

The 2015 Dietary Guidelines for Americans recommends that individuals should eat as little dietary cholesterol as possible. However, current dietary cholesterol intake and its food sources have not been well-characterized. We examined dietary cholesterol intake by age, sex, race, and food sources using 24-hour dietary recall data from a nationally representative sample of 5047 adults aged 20 years or older who participated in NHANES (2013–2014 survey cycle). We also reported trends in cholesterol intake across the past 7 NHANES surveys. Mean dietary cholesterol intake was 293 mg/day (348 mg/day for males and 242 mg/day for females) in the 2013–2014 survey cycle; 39% of adults had dietary cholesterol intake above 300 mg/day (46% for males and 28% for females). Meat, eggs, grain products, and milk were the highest four food sources of cholesterol, contributing to 96% of the total consumption. Both average cholesterol intake and food source varied by age, sex, and race (each p < 0.05). Mean cholesterol intake of the overall population had been relatively constant at ~290 mg/day from 2001–2002 to 2013–2014 (p-trend = 0.98). These results should inform public health efforts in implementing dietary guidelines and tailoring dietary recommendations.

Aiming at the defects of low precision and time cumulative error, an external wireless signal weighted centroid localization algorithm aided inertial positioning method is designed in this paper. According to the signal strength of each anchor node received at the test point, the distance between the anchor node and the anchor node is obtained by using the attenuation model of the wireless signal. Three anchor nodes are used to measure the distance between the anchor node and the measured point. We can obtain the area to be measured according to the actual situation, the position of the measured point is obtained by the weighted centroid localization algorithm and a combined model of wireless signal aided inertial navigation system is established. The simulation results show that the method can greatly improve the positioning accuracy and restrain the divergence of the longitude error and latitude error.

As the increase threat of flood risk and environmental safety due to the urbanization, Sponge city research has been attracting extensive attention both in practical and theoretical research field. To date, there are only scattered studies about Sponge city. Moreover, vary names of Sponge city prevalent in different countries, which leads to disconnection of literature in the same field of Sponge city. In this paper, a thorough systematic literature mining of Sponge city is presented. A literature analysis system is created, which includes literature export from Web of Sciences and systematic analysis via NoteExpress and CiteSpace. Some literature statistical results are derived. Challenges and opportunities for future research are anticipated. Our goals are to promote this promising thought, summarize past research, and identify issues for future research to create impacts on the practice of Sponge city.

Controlling the concentration of free radicals in polymerization systems is advantageous for preparing cationic polyacrylamide (CPAM) with high molecular weight and acceptable dissolvability. In this study, a novel ultraviolet (UV)-initiated system characterized with adjustable light intensity and redox-azo complex initiator was used to synthesize a CPAM flocculant named NP. Comparatively, another CPAM flocculant named SP with stable UV light intensity and single initiator was prepared. The chemical structure, morphology, and thermal stability were analyzed through instrumental analysis. Proton nuclear magnetic resonance indicated that NP was successfully prepared, and a small fraction of cationic homopolymer was mixed in the product. Polymerization conditions were optimized, and polymerization mechanism was determined by investigating the effects of various parameters on intrinsic viscosity, conversion, and dissolvability. Results showed that the best performance was obtained at indexes of 0.45 wt‰ redox initiator concentration, 0.2 wt‰ azo initiator concentration, 40.0 wt% of cationic monomer, first- and second-stage light intensities of 8.5 and 13 mW/cm², respectively, and 3 wt% urea. Sludge conditioning performances of NP and SP were comparatively evaluated, and the mechanism was determined by investigating the sedimentation behavior and floc size distribution. High intrinsic viscosity, porous morphology structure, and the mixed cationic homopolymer of NP resulted in better sludge conditioning performance.

As a chronic disease, osteoarthritis (OA) leads to degradation of both cartilage and subchondral bone, of which the development is related to proinflammatory cytokines like interleukin-1β. In the present study, the anti-inflammatory effect of Specnvezhenide in osteoarthritis and mechanism of it was studied in vitro and in vivo. The results showed that Specnvezhenide decreases interleukin-1β-induced expression of matix-degrading enzymes and reduces the activation of NF-κB and wnt/β-catenin pathways in vitro. Furthermore, Specnvezhenide treatment prevents the degeneration of both cartilage and subchondral bone in rats OA model. As conclusion, to the best of our knowledge, we report firstly that Specnvezhenide decreases interleukin-1β-induced inflammation on rat chondrocytes by inhibiting activation of NF-κB and wnt/β-catenin pathways, and has therapeutic potential in OA treatment.

s: The lack of historical employment data for college graduates, the need to solve the system cold-start problem and the consideration of reciprocity of job recommendation in job recommendation, lead to low recommendation satisfaction and immature application of the existing job recommendation methods. The article presents a new approach to job recommendation using college graduates as the object of study. In the screening stage, a semantic keyword iterative algorithm is applied to compute the similarity between the resume and recruitment texts. This algorithm enhances the intersectionality of keywords in the calculation process, maximizing the utilization of resume information to enhance the accuracy of text similarity calculations. The ranking phase utilizes in-school data to build a social network between college graduates and graduated students, and solves the system's cold-start problem by using the social network to recommend jobs for college graduates where graduated students are employed. Building upon the amalgamation of the semantic keyword iterative algorithm and the social network job recommendation method outlined above, we introduce a dual-dimensional matching approach involving specialty and salary. This enhancement is designed to elevate the reciprocity of job recommendations. The analysis of the results indicates that the average satisfaction rate (AR) and normalized discounted cumulative gain (NDCG) values for the newly proposed job recommendation method surpass those of other methods, demonstrating its superior effectiveness. The method caters to the preferences of graduate job seekers, aligns with job recruitment requirements, and offers extensive job search assistance to a broad spectrum of graduates.

In this study, the preparation of the composite 3% Au/graphite-C3N4 (3% Au/g-C3N4) sensing material was prepared by doping 3% Au onto the surface of graphitic carbonitride (C3N4) for detection pimobendan. By the way of sensing materials characterization, the X-ray diffraction analysis (XRD) and transmission electron Microscope (TEM) were performed. The cyclic voltammetry (CV) was used to measure the concentration and redox properties of pimobendan. It can be seen that when the voltage value is 0.05 V, and a reduction peak was appeared and the pimobendan concentration (0 to 55 μM) has a relationship with the reduction current value. At low concentrations of pimobendan concentration from 0.0 to 0.8 μM, the linearity R2 = 0.9642 with a detection limit of 0.28 μM. A possible pimobendan sensing mechanism on 3% Au/g-C3N4 was proposed.

Asphalt binder is a temperature sensitive material, whose performance is greatly affected by the climate change of the environment. Improper selection of asphalt will cause a lot of damage and affect the durability of the road. The establishment of asphalt pavement performance zoning in Xinjiang, a vast area with great temperature difference, will provide reference for the selection of asphalt suitability, the refinement of pavement design and the sustainable development of road engineering. In this study, 11 years of temperature data in Xinjiang region were collected and analyzed, and 98% reliability of pavement design temperature was used to draw a performance grading map of asphalt pavement in Xinjiang region based on ArcGIS platform. Finally, Xinjiang region was divided into 9 performance zones. At the same time, the performance grade (PG) of five kinds of asphalt binders in Karamay were explored. The result shows that there is little difference in continuous PG span between different matrix asphalt binders, the lower penetration grade, the better high temperature performance, the worse low temperature performance. After adding SBS modifier, the continuous PG span can be higher than the matrix asphalt in 20 ℃. All these provide the basis for reasonable selection of asphalt binders in different areas of Xinjiang.

Suitable soil structure and nutrient security are important for plant growth and development, characteristics of soil fractal dimension and distribution of physical and chemical properties and their interactions play an important role in studying the stability of soil structure and water and fertilizer cycles. As a sustainable management model, intercropping has positive benefits for erosion control, spatial optimization of resources, as well as improving system productivity. The effects of four intercropping methods on soil fractal dimension and physicochemical properties were investigated by intercropping Salvia miltiorrhiza with forage and S. miltiorrhiza with forest under typical karst rock desertification habitats in Guizhou. The results showed that soil nutrient content of intercropping was significantly higher than that of monoculture, the organic carbon content of soil grown under forest is higher than other treatments, and there was a non-significant change in soil water content of intercropping compared with monoculture. The soil fine-grained matter of intercropping was significantly higher than that of monoculture, while the soil fractal dimension showed a tendency to become larger with the increase of fine-grained matter. The intercropping planting, due to its component types and spatial and temporal configurations, leads to differences in soil water and fertilizer interactions, which can be combined with other ecological restoration measures to optimize the composite model and jointly promote the restoration and development of ecologically fragile areas.

To verify the concept of the metasurfaced reverberation chamber (MRC) which was proposed. This paper reports on measurements in the reverberation chamber (RC) performance by using a 1-bit random coding metasurfaced stirrer. The measurement results are validated and compared with that from two mechanical stirrers (horizontal stirrer and vertical stirrer). Figures of merit such as quality factor (Q factor), number of samples, standard deviation, angle autocorrelation, average K-factor, total scattering cross section (TSCS) and the enhanced back scattering coefficient (eb) are presented. Results indicate the feasibility of the MRC technique in the operation frequency of the RC. And it is possible to enlarge the test volume of the RC by using the 1-bit random coding metasurface stirrer.

Human epidemiologic studies and laboratory investigations in animal models suggest that exposure to general anesthetic agents (GAs) have harmful effects on brain development. The mechanism underlying this putative iatrogenic condition is not clear and there are currently no accepted strategies for prophylaxis or treatment. Recent evidence suggests that anesthetics might cause persistent deficits in synaptogenesis by disrupting key events in neurodevelopment. Using an in vitro model consisting of dissociated primary cultured mouse neurons we demonstrate abnormal pre- and post-synaptic marker expression after a clinically relevant isoflurane anesthesia exposure conducted during neuron development. We find that pharmacologic inhibition of the mechanistic target of rapamycin (mTOR) pathway can reverse the observed changes. Isoflurane exposure increases expression of phospho-S6, a marker of mTOR pathway activity, in a concentration-dependent fashion and this effect occurs throughout neuronal development. The mTOR 1 complex (mTORC1) and the mTOR 2 complex (mTORC2) branches of the pathway are both activated by isoflurane exposure and this is reversible with branch-specific inhibitors. Upregulation of mTOR is also seen with sevoflurane and propofol exposure, suggesting that this mechanism of developmental anesthetic neurotoxicity may occur with all the commonly used GAs in pediatric practice. We conclude that GAs disrupt the development of neurons during development by activating a well-defined neurodevelopmental disease pathway and that this phenotype can be reversed by pharmacologic inhibition.

The accurate of model attitude angel plays an important role on the aerodynamic test results in the wind tunnel test. The original method applies the spherical coordinate system transformation to obtain attitude angel calculation. The model attitude angel is obtained by coordinate transformation and spherical surface mapping applying the nominal attitude angel (the balance attitude angel in the wind tunnel coordinate system) indicated by the mechanism. First, the coordinate transformation of this method is not only complex but also difficult to establish the transformed relationship between the space coordinate systems especially after many steps of coordinate transformation, moreover it cannot realize the iterative calculation of the interference relationship between attitude angels; Second, during the calculate process to solve the problem the arc is approximately used to replace the straight line, the angel for the tangent value, and the inverse trigonometric function is applied. Therefore, in the calculation of attitude angel, the process is complex and inaccurate, which can be solved approximately when calculating small attack angel. However, with the advancing development of modern aerodynamic unsteady research, the aircraft tends to develop high or super large attack angel and unsteady research field. According to engineering practice and vector theory, the concept of vector angel coordinate system is proposed for the first time, and the vector angel coordinate system of attitude angel is established. With the iterative correction calculation and avoiding the problem of approximate and inverse trigonometric function solution, the model attitude calculation process is carried out in detail, which validates that the calculation accuracy and accuracy of model attitude angels are improved. Based on engineering and theoretical methods, a vector angel coordinate system is established for the first time, which gives the transformation and angel definition relations between different flight attitude coordinate systems, that can accurately calculate the attitude angel of the corresponding coordinate system and determine its direction, especially in the channel coupling calculation, the calculation of the attitude angel between the coordinate systems is only related to the angel, and has nothing to do with the change order s of the coordinate system, which simplifies the calculation process.

Verticillium wilt (VW) is a soil borne fungal diseases caused by Verticillium dahliae Kleb, and lead to serious damage to cotton production annually in the world. In our previous study, a transmembrane protein 214 protein (TMEM214) gene associated with VW resistance was map-based cloned from Gossypium barbadense (G. barbadense). TMEM214 proteins are a kind of transmembrane protein, but their function in plants is rarely studied. To reveal the function of TMEM214s in VW resistance, all six TMEM214s were cloned from G. barbadense in this study. These genes were named as GbTMEM214-1, GbTMEM214-4 and GbTMEM214-7 according to their location on the chromosomes, and the encoded proteins are all located on cell membrane. TMEM214 genes were all induced by Verticillium dahliae inoculation and showed significant differences between resistant and susceptible varieties, but the expression patterns of GbTMEM214s under different hormone treatments were significantly different. Virus-induced gene silencing analysis showed the resistance to VW of GbTMEM214s-silenced lines decreased significantly, which further proves the important role of GbTMEM214s in the resistance to Verticillium dahliae. Our study provides an insight into the involvement of GbTMEM214s in VW resistance, which was helpful to better understand the disease resistance mechanism of plants.

Numerous studies have shown that quinolones residues in the foods exceeding the MRL is harmful to the human health. There are some limitations in the existing methods for the residues, so we developed a new limit test method (TLC-SERS) to rapidly determine following residues: enrofloxacin(A), ciprofloxacin (B), ofloxacin(C), fleroxacin(D), sparfloxacin(E), enoxacin(F), gatifloxacin(G) and nadifloxacin(H). The residues can be preliminarily separated by TLC. Labeling the tested compounds’ position on the thin layer plate by their relative Rf under 254nm ultraviolet, and an appropriate amount of nanometer silver solution should be added to the position. The silver on the plate should be irradiated with 532nm laser to obtain SERS of the compounds. The results showed a significant differences of the 8 quinolones’ SERS; the LOD of the H, A, D, E, C, G, F and B were orderly 9.0, 12.6, 8.0, 19.0, 8.0, 8.4, 9.0 and 12.6 ng/mL, and the RSD≤4.9% for SERS of each quinolones.The limit test results of the 20 samples was consistent with that determined by the UPLC–MS/MS. The above results indicate that the TLC-SERS is specific, sensitive, stable, and accurate, providing a new reference for the rapid limit test of harmful residues in foods.

A series of novel indole Schiff base derivatives (2a–2t) containing a 1,3,4-thiadiazole scaffold modified with a thioether group were synthesized, and their structures were confirmed using FT-IR, ¹H NMR, ¹³C NMR, andHR-MS. In addition, the antifungal activity of synthesized indole derivatives was investigated against Fusarium graminearum (F. graminearum), Fusarium oxysporum (F. oxysporum), Fusarium moniliforme (F. moniliforme), Curvularia lunata (C. lunata), and Phytophthora parasitica var. nicotiana (P. p. var. nicotianae) using the mycelium growth rate method. Among the synthesized indole derivatives, compound 2j showed the highest inhibition rates of 100%, 95.7%, 89%, and 76.5% at a concentration of 500 μg/mL against F. graminearum, F. oxysporum, F. moniliforme, and P. p. var. nicotianae, respectively. Similarly, compounds 2j and 2q exhibited higher inhibition rates of 81.9% and 83.7% at a concentration of 500 μg/mL against C. lunata. In addition, compound 2j has been recognized as a potential compound for further investigation in the field of fungicides.

With the widespread application of artificial intelligence technology in various industries, users' attention to privacy and data security has increased significantly. Federated learning, as a new technology paradigm combining privacy-enhanced computing and artificial intelligence, resolves the contradiction between data security and open sharing. This paper presents the benefits of federated learning in terms of privacy, real-time processing, model robustness, compliance and cross-industry applications. At the same time, when combined with Edge AI technology, federated learning promotes the decentralisation of intelligent systems, improving data privacy protection and model accuracy. This paper also discusses the application cases of federated learning in the medical field, through local data processing and model training, effectively protecting user privacy, realizing medical data sharing and model optimization, and promoting the development of artificial intelligence.

This study is based on the BP neural network regression model optimised by genetic algorithm and dedicated to predicting the amount of car purchase, this study is important for all parties in the automotive industry. By plotting the violins of six indicators, including gender, age, annual salary, credit card debt, net worth, and car purchase amount, we found that, except for gender, the other data showed a trend of dense in the middle gradually decreasing to the upper and lower sides, with an overall normal distribution. The correlation analysis shows that the amount of car purchase has a high positive correlation with age (0.63), followed by annual income (0.62), the correlation between net worth and the amount of car purchase is 0.49, while the correlation between credit card debt and the amount of car purchase is low (0.03). In the experimental part, we analyse the predicted-actual values of the training and test sets in comparison and find that the model predicted values are very close to the actual values. The RMSE of the training set is 11.559 and the RMSE of the test set is 11.4835, which is not much different from each other, indicating that the model has good generalisation ability. In addition, the R2 of both the training and test sets is 1, indicating that the model fits well. The MAE of the training set is 8.2512 and the MAE of the test set is 9.578; the MBE of the training set is -4.3035 and the MBE of the test set is -2.4547.These metrics indicate that the model performs well in predicting the amount of car purchase. In conclusion, this study provides an effective and reliable method to predict the amount of car purchase, creating a useful bridge between car manufacturers, dealers and consumers.

The rapid development of new retail and the impact of COVID-19 have catalyzed the blowout growth of community group purchasing. The emergence of community group purchasing collection and delivery points (CGPCDPs) has become a new way to solve the "last mile" problem of new retail delivery. Based on the point of interest (POI) data of CGPCDPs of Nansha District, Guangzhou City, this study uses text analysis, spatial analysis, model analysis, and other methods to analyze the operation mode, spatial distribution, and influencing factors of CGPCDPs. The conclusions are as follows: CGPCDPs initiators are mainly shopkeepers. They depend mainly on wholesale and retail shops. Service targets are mainly urban and rural communities, followed by industrial areas. The distribution of CGPCDPs has apparent spatial differentiation. At the macro scale, it shows the characteristics of "central agglomeration and peripheral dispersion". It is distributed along the "northwest-southeast" direction and presents a "dual-core multi-center" pattern. At meso-micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun) and rural areas show distinct distribution patterns. The MGWR regression model has a better fitting effect than OLS and GWR. The main influencing factors are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.

In recent years, researches on combining wavelet decomposition and convolutional neural network (CNN) together to classify hyperspectral images (HSI) have emerged, and some effective classification models have been proposed and achieved good classification results. However, there are two problems for most of the proposed models. One is the heavy training parameters and the other is that there is no distinction between the classification effectiveness of low frequency and high frequency features after wavelet decomposition. In this paper, a new light-weighted HSI classification model (LLFWCNN) is proposed, which performs multi-layer wavelet decomposition for HSI after dimensionality reduction, and only arranges the low frequency features in a specific stack mode, then classifies them through a well-designed convolutional neural network. Compared with other classification models, the number of parameters is only 2.5% of that of other models. And only the low frequency features after wavelet decomposition are used, while the high frequency features are abandoned. The results showed that compared with the state-of-the-art classification models, LLFWCNN could obtain the same or even better classification results with fewer network parameters and proved that the low frequency features after wavelet decomposition provide LLFWCNN with more favorable information for HSI classification as well.

Pool boiling heat transfer is recognized as one of the most effective heat transfer methods and has extensive applications in industry. The application of non-azeotropic binary mixtures can not only meet the environmental requirements of modern industrial development, but also improve the coefficient of performance (COP) of many systems. Therefore, studying the boiling heat transfer characteristics of non-azeotropic mixtures is important on improving their potential industrial application. This article selected ethylene glycol/deionized water (EG/DW) at varies concentration as the research working fluids, and conducted experimental research on the pool boiling performance. At the same time, the thermophysical parameters of the mixtures were studied and analyzed. The results showed that the concentration of EG in the mixture had a significant impact on the thermal properties and temperature glide of the mixture, where both affected the heat transfer deterioration. Based on experimental data, six widely used heat transfer coefficient prediction correlations were used for calculation, and two of them were modified. The deviation between the modified correlations and the experimental results remained within 20%.

In order to reveal the frost heaving mechanism of void water behind the lining of high-speed railway tunnels in cold regions，the voids were first classified according to the positional relationship between voids and waterproof panels，and then the water supply and discharge conditions of different types of voids were investigated，then the influence of the excretion conditions on the frost heave force was experimentally studied. Based on these conditions，circular wedge-shaped and flying saucer-shaped void freezing models were established to analyze the evolution process of accumulated water frost heave. Then，according to the relative position of the excretion channel and the void，the excretion coefficient was introduced，and the calculation method of the frost heaving force of the voided water was proposed，and the influencing factors and laws of the frost-heave force were revealed. The results are shown as follows: 1) The blockage of the excretion channel will lead to the generation of frost heaving force; 2) The freezing and thawing process of the water within the cavity develops from the thinnest part of the void edge to the thicker part，and the process of frost heave-thaw，water replenishment-re-freeze heave of the water within the cavity leads to greater and greater frost heave force; 3) The frost-heaving force of the water within cavity is controlled by the void height and the position of the excretion channel. The larger the cavity height is or the closer the excretion channel is to the bottom surface of the void，the greater the frost-heave force is.

For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions at the expense of the main lobe resolutions. Therefore, the improved spatially variant apodization imaging method for forward-looking sonar is proposed to reduce the sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear post-processing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent beam sidelobe heightening from occurring prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately -40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

In this paper, a special recurrent neural network (RNN) called \emph{Long Short-Term Memory (LSTM)} is used to design a virtual load sensor that estimates the mass of heavy vehicles. The estimation algorithm consists of a two-layer LSTM network, with the two layers based on sequence-to-sequence and sequence-to-one logic, respectively. The network estimates the vehicle mass based on the vehicle speed, longitudinal acceleration, engine speed, engine torque, and the accelerator pedal position. The network is trained and tested with a data set collected in a high-fidelity simulation environment called Truckmaker. Training data is generated in acceleration maneuvers in a range of speeds whereas test data is obtained by simulating the vehicle in a Worldwide harmonized light vehicles test cycle (WLTC). Preliminary results show that, with the proposed approach, the heavy-vehicle mass can be estimated as accurately as commercial load sensors in a range of load mass as wide as four tons.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

The heat generated during the startup process of dry gas seals, such as the friction heat of the asperities, viscous shear heat, and the expansion heat of the gas film, easily leads to seal failure and endangers the stable operation of turbomachinery. This study combines the statistically modified contact model and the average Reynolds equation by considering the adiabatic index and the microscale effects of dry gas seals to explore the heat generation characteristics of dry gas seals formed in series at multiple times. In particular, the change laws and influencing factors among the components, including the friction heat of asperities and the shear heat and expansion heat of the gas film and total heat, are investigated. A comparative analysis indicates that the slip flow effect increases the total heat during the startup process. The friction heat is much greater than expansion heat and shear heat. Despite constant acceleration, exponential acceleration, or Harrision acceleration, the heat changes are uneven during the startup process. In particular, the heat changes sharply in the early stage and gently in the later stage. The Harrision acceleration mode is the most conducive to sealing stability.

Intrauterine adhesions (IUA) has become one of the main causes of female infertility, how to effectively prevent postoperative re-adhesion has been a clinical challenge. In this study, a mussel-inspired dual-network hydrogel was proposed for postoperative anti-adhesion of IUA. First, calcium alginate/polyacrylamide (CA-PAM) hydrogel was prepared by covalent and Ca2+ cross-linking. Benefiting from abundant phenolic hydroxyl groups, polydopamine (PDA) was introduced to further enhance the adhesion ability and biocompatibility. This CA-PAM hydrogel immersed in 10 mg/mL dopamine solution possessed remarkable mechanical strength (elastic modulus > 5 kPa) and super stretchability (with a breaking elongation of 720%). At the same time, it shown excellent adhesion more than 6 kPa. Surprisingly, the coagulation index of the hydrogel was 27.27 ± 4.91, demonstrating attractive coagulation performance in vitro and the potential for rapid hemostasis after surgery.

For a fiber optic gyroscope, thermal deformation of the fiber coil can introduce additional ther-mal-induced phase errors, commonly referred to as thermal errors. Thermal error compensation techniques are effective means of addressing this issue. The principle behind these techniques involves real-time sensing of thermal errors and correcting them within the output signal. Since it is challenging to directly separate thermal errors from the output signal of the fiber optic gyro-scope, it is necessary to predict thermal errors based on temperature. To establish a mathematical model between temperature and thermal errors, this paper measured synchronized data of phase errors and angular velocity for the fiber coil under different temperature conditions and aimed to model it using data-driven methods. Due to the difficulty of conducting tests and the limited number of data samples, an algorithm called TD-model modeling is proposed to address the issue of overfitting, which can reduce the model's generalization ability. First, a theoretical analysis of the phase errors caused by thermal deformation of the fiber coil is performed. Subsequently, the critical parameters, such as the thermal expansion coefficient, are determined, and a theoretical model is established. Finally, the theoretical analysis model is incorporated as a regularization term and combined with the test data to jointly participate in the regression of model coefficients. Through experimental comparative analysis, it is shown that, relative to ordinary regression models, the TD-model effectively mitigates overfitting caused by the limited number of samples, leading to a 58% improvement in predictive accuracy.

Drought poses a significant environmental risk and can deeply affect the growth of grasslands. However, there is still uncertainty regarding the precise impact of varying levels of drought on grassland growth. To address this gap, we utilized several key indicators, including the Nor-malized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), the Global Or-biting Carbon Observatory-2 based Solar-induced Chlorophyll Fluorescence (GOSIF), and the Gross Primary Productivity (GPP), in conjunction with drought indices (the Standardized Precip-itation Evapotranspiration Index (SPEI) and the soil moisture (SM). Our study aimed to compre-hensively assess the consistency of spatio-temporal patterns in grassland vegetation and its re-sponsiveness to different drought levels in the Inner Mongolia region from 2002 to 2020. Results indicated that NDVI, EVI, GOSIF, and GPP in grassland vegetation across Inner Mongolia exhibited significant increasing trends from 2002 to 2020. Specifically, NDVI, EVI, GOSIF, and GPP all dis-played consistent spatial patterns, with 25.83%, 21.18%, 22.65% and 48.13% of the grassland area showing significant increases, respectively. Drought events, as described by SPEI and SM, in June 2007 to September 2007 and June 2017 to July 2017, were selected to evaluated the response of grassland vegetation to drought. The drought events of 2007 and 2017 resulted in reductions in NDVI, EVI, GOSIF, and GPP relative to multi-year average (2002-2020). GOSIF exhibited a more intense response to drought, suggesting that GOSIF may reflect the inhibition of water stress on grassland photosynthesis better than NDVI and EVI during drought in 2007 and 2017. The reduc-tions in NDVI, EVI, GOSIF and GPP in grassland increased significantly across different drought-levels, with the sharpest reductions observed during extreme drought. Under the severe and extreme drought events, the most substantial reductions in NDVI, EVI, GOSIF, and GPP were observed in the temperate steppe (TS). Moreover, the effects of different drought severity levels within the same grassland type varied, with the most significant reductions in NDVI, EVI, GOSIF and GPP observed during extreme drought. Our results provide new perspectives for developing and implementing effective strategies to address grassland carbon cycling management and climate change in Inner Mongolia.

For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time-consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks. To address these challenges, this paper introduces the OptionEM-based reinforcement learning framework to achieve end-to-end SAR image registration. This framework outputs registered images directly without requiring feature matching and calculation of the transformation matrix, leading to significant processing time savings. The Transformer architecture is employed to learn image features, while a correlation network is introduced to learn the correlation and transformation matrix between image pairs. Reinforcement learning, as a decision process, can dynamically correct errors, making it more efficient and robust compared to supervised learning mechanisms like deep learning. We present a hierarchical reinforcement learning framework combined with episodic memory to mitigate the inherent problem of invalid exploration in generalized reinforcement learning algorithms. This approach effectively combines coarse and fine registration, further enhancing training efficiency. Experiments conducted on three sets of SAR images, acquired by TerraSAR-X and Sentinel-1A, demonstrate that the proposed method’s average runtime is sub-second, achieving subpixel registration accuracy.

Interactions between proteins and ions are essential for various biological functions like structural stability, metabolism, and signal transport. Given that more than half of all proteins bind to ions, it becomes crucial to identify ion-binding sites. Accurate identification of protein-ion binding sites helps us to understand proteins’ biological functions and plays a significant role in drug discovery. While several computational approaches have been proposed, this remains a challenging problem due to the small size and high versatility of metals and acid radicals. In this study, we propose IonPred, a sequence-based approach that employs ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) to predict ion binding sites using only raw protein sequences. We successfully fine-tuned our pretrained model to predict the binding sites for nine metal ions (Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, and K+) and four acid radical ion ligands (CO32−, SO42−, PO43−, NO2−). IonPred surpassed six current state-of-the-art tools by over 44.65% and 28.46% respectively in F1 score and MCC when compared on an independent test dataset. Our method is more computationally efficient than existing tools producing prediction results for a hundred sequences for a specific ion in under ten minutes.

Fractures are the most common large organ trauma in humans. The initial inflammatory re-sponse promotes bone healing during the initial post-fracture phase, but chronic and persistent inflammation due to infection or other factors does not contribute to the healing process. The precise mechanisms by which immune cells and their cytokines are regulated in bone healing remain unclear. The use of mesenchymal stem cells (MSCs) for cellular therapy of bones injury is a novel clinical treatment approach. Bone progenitor MSCs not only differentiate into bone, but also interact with the immune system to promote the healing process. We review in vitro and in vivo studies on the role of the immune system and bone marrow MSCs in bone healing and their interactions. A deeper understanding of this paradigm may provide clues to potential therapeu-tic targets in the healing process, thereby improving the reliability and safety of clinical applica-tions of MSCs to promote bone healing.

In order to solve the problem of environmental pollution caused by a large number of discarded hickory husks in Lin'an, and to make them a clean energy source that can be recycled, in this paper,using crushed hickory husks as raw material, single factor test was carried out on a hydraulic plunger forming machine with different moisture content and length-diameter ratio of forming sleeve.The change of axial pressure and radial force in the forming sleeve is measured by the sensor, and the microstructure of the biomass moulding fuel briquette was observed by stereomicroscope. The results showed that the hickory husks could be compressed and formed at room temperature. When the moisture content of the hickory husks is 14% and the length-diameter ratio of the forming sleeve is 4.5, the forming quality is the best, and the relaxation density of the formed briquette is up to 0.98g /cm3. When the moisture` content is the same, the forming pressure increases with the increase of the length-diameter ratio of the forming sleeve. When the length-diameter ratio of molding sleeve is the same, the molding pressure increases first and then decreases with the increase of water content.

Urea, a prevalent component found in wastewater, shows great promise as an alternative substrate to water for energy-efficient hydrogen production by electrolysis. However, the sluggish kinetics of the anodic urea oxidation reaction (UOR) significantly hampers the overall reaction rate. To address this challenge, this article presents a comprehensive study focusing on the controlled fabrication of hierarchically structured nanomaterials as potential catalysts for UOR. The prepared MnO2@NiCo-LDH hybrid catalyst demonstrates remarkable improvements in reaction kinetics, benefiting from synergistic enhancements in charge transfer and efficient mass transport facilitated by its unique three-dimensional architecture. Notably, the catalyst exhibits an exceptionally low onset potential of 1.228 V and requires only 1.326 V to achieve an impressive current density of 100 mA cm-2, representing a state-of-the-art performance in UOR. These findings highlight the tremendous potential of this innovative material-designing strategy to drive advancements in electrocatalytic processes.

A self-protective metal/ liquid microcapsule composite plating coating has been prepared in our previous research. The release speed of liquid core material from microcapsules is crucial for the coating surface properties. The aim of this paper is to study the permeability rule of liquid microcapsules within composite coatings. According to permeability experimental data’s linear characteristics, multiple linear regression is firstly used to set up permeability model of liquid microcapsules. The results show that a reliable mathematical model about membrane porosity, viscosity of core material and membrane thickness is established under ambient temperature and moisture. Meanwhile, the predictive capacity and reliability of this model are analyzed carefully.

Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenarios require varying levels of granularity in address components, further complicating the parsing process. To address these challenges and adapt to low-resource environments, we propose CapICL, a novel Chinese address parsing model based on the In-Context Learning (ICL) framework. CapICL leverages a sequence generator, regular expression matching, BERT semantic similarity computation, and GPT modeling to enhance parsing accuracy by incorporating contextual information. We construct the sequence generator using a small annotated dataset, capturing distribution patterns and boundary features of address types to model address structure and semantics, mitigating interference from unnecessary variations. We introduce the REB-KNN algorithm, which selects similar samples for ICL-based parsing using regular expression matching and BERT semantic similarity computation. The selected samples, raw text, and explanatory text are combined to form prompts, and inputted into the GPT model for prediction and address parsing. Experimental results demonstrate significant achievements of CapICL in low-resource environments, reducing dependency on annotated data and computational resources. Our model's effectiveness, adaptability, and broad application potential are validated, showcasing its positive impact in natural language processing and geographical information systems.

Understanding of the correlation between the magnetomechancial coupling factors (k) and damping factors (Q^-1) is a key pathway to enhance the magnetomechanical power conversion ef-ficiency in laminated magnetoelectric (ME) composites by engineeringly manipulating the magnetic and mechanical properties of Fe-based amorphous metals. The k and Q^-1 factors of FeSiB amorphous ribbons annealed in air at different temperatures are investigated. It is found that k and Q^-1 factors are affected by both magnetic and elastic properties. The magnetic and elastic properties are equalized in terms of the magnetomechanical power efficiency for the low temperature annealing. The k and Q^-1 of FeSiB-based epoxied laminates with different stacking numbers show that the -3 dB bandwidth and Young’s modulus are equalized in terms of the magnetomechanical power efficiency for the high lamination stacking.

The nature abundant sodium metal is proposed as ideal anode materials for advanced batteries due to its high specific capacity of 1166mAh g-1 and low redox potential of -2.71V. However, the uncontrollable dendritic Na formation and low coulombic efficiency are still major obstacles for applications. Notably, the unstable and inhomogeneous solid electrolyte interphase (SEI) is recognized to be the root cause. As SEI layer plays a critical role in regulating uniform Na deposition and improving cycling stability, researches on SEI modification, especially the artificial SEI modifications has been extensively investigated recently. In this regard, we discussed the advances on artificial interface engineering from the aspects of inorganic, organic and hybrid inorganic/organic protective layers. Finally, we also highlighted the conclusions and key prospects for further investigations. We hope this review can provide a new insight for sodium metal protection.

Nonnegative matrix factorization (NMF) has been shown to be a strong data representation technique, with applications in text mining, pattern recognition, image processing, clustering and other fields. In this paper, we propose a hypergraph regularized Lp smooth nonnegative matrix factorization (HGSNMF), by incorporating hypergraph regularization and Lp smoothing constraint terms into the standard NMF. The hypergraph regularization term can capture the intrinsic geometry structure of the high dimension space data more comprehensively than simple graph, the Lp smoothing constraint may yield a smooth and more accurate solution to the optimization problem. The updating rules are given using multiplicative update techniques, and the convergence of HGSNMF is theoretically investigated. The experimental results on four different data sets show that the proposed method has better clustering effect than the related state-of-the-art methods in the vast majority of cases.

The log data generated during the operation of a software system contains information about the system, and using logs for anomaly detection can detect system failures in a timely manner. Most of the existing log anomaly detection methods are specific to a particular system, have cold start problems, and are sensitive to updates in log format. In this paper, we propose a log anomaly detection method LogBD based on pre-training model and domain adaptation, which uses the pre-training model BERT to learn the semantic information of logs, and can solve the problems caused by multiple meaning words and log statement updates. An anomaly detection method LogBD based on distance to determine anomalies is constructed based on domain adaptation, using TCN networks to extract common features of different system logs and map them to the same hypersphere space. Finally, experiments are conducted on two publicly available datasets to evaluate the method, and the experimental results show that the method can better solve the log instability problem and has some improvement in the cross-system log anomaly detection effect.

Purpose: This study aims to analyze the factors that affect the behavior of user-defined avatars in different virtual environments, and compare the differences in public self-awareness, self-expression, and emotional expression among customized avatars in multiple virtual contexts. Methods: Using a between-subjects experimental design, two random groups of participants were asked to customize avatars for themselves in two contexts, a multiplayer online social game (MOSG) and a virtual meeting (VM). i.e. a relaxed and a serious social environment. Results: When subjects perceived a more relaxed environment, the customized avatars had less self-similarity, and the subjects exhibited a stronger self-disclosure willingness and enhanced avatar wishful identification; nevertheless, public self-consciousness was not increased. When subjects perceived a more serious environment, the customized avatars exhibited a higher degree of self-similarity, and the subjects exhibited a greater self-presentation willingness, along with enhanced identification of avatar similarity, and increased public self-consciousness. Conclusions: Participants expressed positive emotions, suggesting that avatars play a positive role in various virtual contexts. The virtual context affects the self-similarity of user-customized avatars, and avatar self-similarity affects self-presentation and self-disclosure willingness, and these factors will affect the behavior of the user-customized avatar. This study contributes suggestions to the Metaverse avatar customization platform design.

The combined heat and power system is based on the principle of "cascade utilization of thermal energy" for system integration and optimization. The rational utilization of energy, as well as the rational arrangement of energy flow and the process optimization combination of the overall system are taken into account in order to achieve multifunctional goals in the field of thermal engineering. The present paper presents a detailed assessment of combined heat and power systems from above standpoints. This article is divided into two parts “CHP based on thermo-dynamic cycles” and “CHP based on non-thermodynamic cycles”. Each part is then classified based on power subsystem energy consumption efficiency (high or low), including Rankine cycle, ORC, Stirling cycle, gas turbine, reciprocating engine, PVT and fuel cell. The present paper also helps identify the research gaps in this area and provides direction on future studies on combined heat and power systems.

Urban scene point cloud pose significant challenges for registration due to its large data volume, similar scenarios and dynamic objects. In this paper, we propose PCRMLP, a model for urban scene point cloud registration that achieves comparable registration performance to prior learning-based methods. Compared to previous works which focus on extracting features and estimating correspondence, the model estimates the transformation implicitly from concrete instances. An instance-level urban scene representation method is introduced to extract instance descriptors via semantic segmentation and DBSCAN, which enable the model to obtain robust instance features, filter dynamic objects and estimate transformation in a more logical manner. Then a lightweight network consisting of MLPs is employed to obtain transformation in an encoder-decoder manner. We validate the approach on KITTI dataset. Experimental results demonstrate that PCRMLP can obtain a satisfactory coarse transformation from instance descriptors just in 0.0028s. With a subsequent ICP refinement module, the proposed method achieves higher registration accuracy and computational efficiency than prior learning-based works.