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Sulforaphane (SFN) is an organosulfur compound categorized as an isothiocyanate (ITC), primarily extracted from cruciferous vegetables like broccoli and cabbage. The molecular formula of sulforaphane (SFN) is C6H11NOS2. SFN is generated by the hydrolysis of glucoraphanin (GRP) through the enzyme myrosinase, showing notable properties including anti‐diabetic, anti‐inflammatory, antimicrobial, anti‐angiogenic, and anticancer attributes. Ongoing clinical trials are investigating its potential in diseases such as cancer, neurodegenerative diseases, diabetes‐related complications, chronic kidney disease, cardiovascular disease, and liver diseases. Several animal carcinogenesis models and cell culture models have shown it to be a very effective chemopreventive agent, and the protective effects of SFN in ophthalmic diseases have been linked to multiple mechanisms. In murine models of diabetic retinopathy and age‐related macular degeneration, SFN delays retinal photoreceptor cell degeneration through the Nrf2 antioxidative pathway, NF‐κB pathway, AMPK pathway, and Txnip/mTOR pathway. In rabbit models of keratoconus and cataract, SFN has been shown to protect corneal and lens epithelial cells from oxidative stress injury by activating the Keap1‐Nrf2‐ARE pathway and the Nrf‐2/HO‐1 antioxidant pathway. Oral delivery or intraperitoneal injection at varying concentrations are the primary strategies for SFN intake in current preclinical studies. Challenges remain in the application of SFN in eye disorders due to its weak solubility in water and limited bioavailability because of the presence of blood–ocular barrier systems. This review comprehensively outlines recent research on SFN, elucidates its mechanisms of action, and discusses potential therapeutic benefits for eye disorders such as age‐related macular degeneration (AMD), diabetic retinopathy (DR), cataracts, and other ophthalmic diseases, while also indicating directions for future clinical research to achieve efficient SFN treatment for ophthalmic diseases. [ABSTRACT FROM AUTHOR]

Loop closure detection is an important component of the Simultaneous Localization and Mapping (SLAM) algorithm, which is utilized in environmental sensing. It helps to reduce drift errors during long-term operation, improving the accuracy and robustness of localization. Such improvements are sorely needed, as conventional visual-based loop detection algorithms are greatly affected by significant changes in viewpoint and lighting conditions. In this paper, we present a semantic spatial structure-based loop detection algorithm. In place of feature points, robust semantic features are used to cope with the variation in the viewpoint. In consideration of the semantic features, which are region-based, we provide a corresponding matching algorithm. Constraints on semantic information and spatial structure are used to determine the existence of loop-back. A multi-stage pipeline framework is proposed to systematically leverage semantic information at different levels, enabling efficient filtering of potential loop closure candidates. To validate the effectiveness of our algorithm, we conducted experiments using the uHumans2 dataset. Our results demonstrate that, even when there are significant changes in viewpoint, the algorithm exhibits superior robustness compared to that of traditional loop detection methods. [ABSTRACT FROM AUTHOR]

Covariance estimation for matrix-valued data has received an increasing interest in applications. Unlike previous works that rely heavily on matrix normal distribution assumption and the requirement of fixed matrix size, we propose a class of distribution-free regularized covariance estimation methods for high-dimensional matrix data under a separability condition and a bandable covariance structure. Under these conditions, the original covariance matrix is decomposed into a Kronecker product of two bandable small covariance matrices representing the variability over row and column directions. We formulate a unified framework for estimating bandable covariance, and introduce an efficient algorithm based on rank one unconstrained Kronecker product approximation. The convergence rates of the proposed estimators are established, and the derived minimax lower bound shows our proposed estimator is rate-optimal under certain divergence regimes of matrix size. We further introduce a class of robust covariance estimators and provide theoretical guarantees to deal with heavy-tailed data. We demonstrate the superior finite-sample performance of our methods using simulations and real applications from a gridded temperature anomalies dataset and an S&P 500 stock data analysis. for this article are available online. [ABSTRACT FROM AUTHOR]

Meta-diamides (e.g. broflanilide) and isoxazolines (e.g. fluralaner) are novel insecticides that target the resistant to dieldrin (RDL) subunit of insect γ-aminobutyric acid receptors (GABARs). In this study, we used in silico analysis to identify residues that are critical for the interaction between RDL and these insecticides. Substitution of glycine at the third position (G3') in the third transmembrane domain (TMD3) with methionine (G3'M TMD3), which is present in vertebrate GABARs, had the strongest effect on fluralaner binding. This was confirmed by expression of RDL from the rice stem borer, Chilo suppressalis (CsRDL) in oocytes of the African clawed frog, Xenopus laevis, where the G3'MTMD3 mutation almost abolished the antagonistic action of fluralaner. Subsequently, G3'MTMD3 was introduced into the Rdl gene of the fruit fly, Drosophila melanogaster, using the CRISPR/Cas9 system. Larvae of heterozygous lines bearing G3'MTMD3 did not show significant resistance to avermectin, fipronil, broflanilide, and fluralaner. However, larvae homozygous for G3'MTMD3 were highly resistant to broflanilide and fluralaner whilst still being sensitive to fipronil and avermectin. Also, homozygous lines showed severely impaired locomotivity and did not survive to the pupal stage, indicating a significant fitness cost associated with the G3'MTMD3. Moreover, the M3'GTMD3 in the mouse Mus musculus α1β2 GABAR increased sensitivity to fluralaner. Taken together, these results provide convincing in vitro and in vivo evidence for both broflanilide and fluralaner acting on the same amino acid site, as well as insights into potential mechanisms leading to target-site resistance to these insecticides. In addition, our findings could guide further modification of isoxazolines to achieve higher selectivity for the control of insect pests with minimal effects on mammals. Author summary: Meta-diamides (e.g. broflanilide) and isoxazolines (e.g. fluralaner) are members of group 30 of compounds according to the Insecticide Resistance Action Committee, and are defined as γ-aminobutyric acid (GABA)-gated chloride channel allosteric modulators. However, their mode of action on the GABAR remains to be fully elucidated. In the current study, we provide in silico, in vitro and in vivo evidence that G3'TMD3, the glycine residue at the third position (G3') in the third transmembrane domain (TMD3) of the insect GABAR subunit, resistant to dieldrin (RDL), is critical for the action of these insecticides. Furthermore, the homozygous but not heterozygous lines of the fruit fly Drosophila melanogaster bearing G3'MTMD3 showed high resistance to broflanilide and fluralaner but were unable to survive to the pupal stage. These findings enhance our understanding of resistance-related and homozygous-lethal gene mutations, and may prove useful for the future synthesis of related insecticides to gain long-term effectiveness and higher selectivity. [ABSTRACT FROM AUTHOR]

Simple Summary: The use of computer vision technology has improved the effectiveness of individual sheep identification, but existing methods face challenges such as large parameter sizes, slow recognition speeds, and difficult deployment. To address this issue, we have made improvements and optimizations based on the Retinaface face recognition model to create a balanced speed-accuracy sheep face recognition model. The optimized model has fewer parameters, simpler computations, faster inference speeds, and higher recognition accuracy, making it well-suited for deployment on resource-constrained edge devices. This research is expected to promote the application of deep learning-based sheep face recognition methods in production. The recognition of sheep faces based on computer vision has improved the efficiency and effectiveness of individual sheep identification, providing technical support for the development of smart farming. However, current recognition models have problems such as large parameter sizes, slow recognition speed, and difficult deployment. Therefore, this paper proposes an efficient and fast basic module called Eblock and uses it to build a lightweight sheep face recognition model called SheepFaceNet, which achieves the best balance between speed and accuracy. SheepFaceNet includes two modules: SheepFaceNetDet for detection and SheepFaceNetRec for recognition. SheepFaceNetDet uses Eblock to construct the backbone network to enhance feature extraction capability and efficiency, designs a bidirectional FPN layer (BiFPN) to enhance geometric location ability, and optimizes the network structure, which affects inference speed, to achieve fast and accurate sheep face detection. SheepFaceNetRec uses Eblock to construct the feature extraction network, uses ECA channel attention to improve the effectiveness of feature extraction, and uses multi-scale feature fusion to achieve fast and accurate sheep face recognition. On our self-built sheep face dataset, SheepFaceNet recognized 387 sheep face images per second with an accuracy rate of 97.75%, achieving an advanced balance between speed and accuracy. This research is expected to further promote the application of deep-learning-based sheep face recognition methods in production. [ABSTRACT FROM AUTHOR]

In the process of emergency relief material dispatching, most of the traditional algorithms for dispatching are for single rescue point and single material dispatching, which cannot solve the problem of multirescue emergency relief dispatching. The various supply and demand points for emergency relief materials and the multiple emergency relief material dispatching are utilized to create the multiobjective planning model, which is then used as the optimization objective to create the best material dispatching plan. Genetic algorithm (GA) is used to solve the optimal material dispatching scheme and symbolic coding; special pulse crossover operator and variational operator are used to ensure the quality of the solution. The experiment proves that the simulation method of the aviation emergency rescue process considering the application scenario characteristics is efficient in the emergency rescue process and can meet the application requirements of material dispatching in the process of civil emergency disaster relief. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of the lithium-ion battery industry, the massive upstream consumption of mineral raw materials has led to great crises and challenges in balancing global supply and demand. A diversity of trading partners can effectively alleviate the pressure of supply and demand for raw materials; so, it is particularly important for trading countries to find suitable trading partners. This study takes nine important minerals contained in the main element raw materials of lithium-ion batteries as the research object, and the international trade data range from 2011 to 2020. The study combines complex networks and motifs and links prediction methods to predict the potential international trade relations of the nine minerals based on the actual network topology. We summarize three trade link rules as follows. (1) The predicted links have a timeliness requirement, and they generally turn into actual trade links within 3 years. (2) When looking for trading partners, trading countries tend to establish long-term and stable trade relations. (3) The existing trade relations will promote the establishment of predicted trade relations. In addition, we find that successfully predicted links will promote the formation of important motifs in the network. This study can provide a theoretical basis for trading countries to find suitable trading partners and can strengthen the safety of trading countries in the trade of the main element minerals for lithium-ion batteries. [ABSTRACT FROM AUTHOR]

Pyropia haitanensis, one of the most economically and ecologically important seaweed species, is often exposed to persistent or transient low irradiance (LI), resulting in limited yield and quality. However, the mechanisms mediating P. haitanensis responses to LI are largely unknown. In this study, LI-tolerant (LIT) and LI-sensitive (LIS) P. haitanensis strains were compared regarding their physiological and transcriptomic changes induced by 1 and 4 days of LI (5 μmol photons/m2·s). The results indicated that the inhibition of photomorphogenesis and decreases in photosynthesis and photosynthetic carbon fixation as the duration of LI increased are the key reasons for retarded blade growth under LI conditions. A potential self-amplifying loop involving calcium signaling, phosphatidylinositol signaling, reactive oxygen species signaling, and MAPK signaling may be triggered in blades in response to LI stress. These signaling pathways might activate various downstream responses, including improving light energy use, maintaining cell membrane stability, mitigating oxidative damage, to resist LI stress. Additionally, the LIT strain maintained transcriptional homeostasis better than the LIS strain under LI stress. Specifically, photosynthesis and energy production were relatively stable in the LIT strain, which may help to explain why the LIT strain was more tolerant to LI stress than the LIS strain. The findings of this study provide the basis for future investigations on the precise mechanisms underlying the LI stress tolerance of P. haitanensis. [ABSTRACT FROM AUTHOR]

Researchers increasingly report the therapeutic effect of exosomes derived from rat bone marrow mesenchymal stem cells (Exos-rBMMSC) on liver disease, while the optimal dose of Exos-rBMMSC in liver cirrhotic treatment has not been reported. In this study, we aimed to explore the efficacy and dose of Exos-rBMMSC in a hepatic cirrhosis rat model. The therapeutic effects of a low dose, medium dose and high dose of Exos-rBMMSC were assessed by liver function tests and histopathology. After four-weeks of Exos-rBMMSC therapy, pyroptosis-related expression levels in the medium dose and the high dose Exos-rBMMSC groups were significantly decreased compared to those in the liver cirrhosis group (p < 0.05). The hepatic function assay and histopathology results showed significant improvement in the medium dose and the high dose Exos-rBMMSCs groups. The localization of PKH67-labeled Exos-rBMMSC was verified microscopically, and these particles were coexpressed with the PCNA, NLRP3, GSDMD and Caspase-1. Our results demonstrated that Exos-rBMMSC accelerated hepatocyte proliferation and relieved liver fibrosis by restraining hepatocyte pyroptosis. More importantly, we confirmed that the high dose of Exos-rBMMSC may be the optimal dose for liver cirrhosis, which is conducive to the application of Exos-rBMMSC as a promising cell-free strategy. [ABSTRACT FROM AUTHOR]

The two-stage suspension system (TSSS) is designed for the fiber optic vector hydrophone (FOVH) to isolate the vibration from the mooring rope. The acceleration transmissibility of the TSSS is studied theoretically and experimentally. The results show that the TSSS has a major advantage over the traditional one-stage suspension system (OSSS). Typically, the vibration isolation of the TSSS is demonstrated to be over 25 dB higher than that of the OSSS at 100 Hz. Meanwhile, it is demonstrated that the TSSS has little negative influence on the in-band acceleration response of the FOVH. The TSSS has the prospect of reducing the mechanical noise of the FOVH, which is conducive to suppressing the self-noise and enhancing the ability of weak signal detection. [ABSTRACT FROM AUTHOR]

Background: Carotid plaque and triglyceride-glucose (TyG) index are associated with insulin resistance. However, a highly debated question is whether there is an association between the TyG index and carotid plaque incidence. Thus we performed an in-depth longitudinal study to investigate the relationship between carotid plaque occurrence and the TyG index among Chinese individuals. Methods: Two thousand and three hundred seventy subjects (1381 males and 989 females) were enrolled and followed up for three years. The subjects were stratified into four groups based on the quartile of the TyG index at baseline. Univariate and multivariate Cox proportional hazard models were conducted to examine the role of TyG played in the carotid plaque. The strength of association was expressed as hazard ratio (HR) and 95% confidence interval (CI). Results: After three years of follow-up, 444 subjects were detected with newly formed carotid plaque. The overall 3-year cumulative carotid plaque incidence was 18.7%, and the risk of carotid plaque increased with elevated TyG index (p < 0.001). The Cox regression analysis showed that males (HR: 1.33, 95% CI: 1.10–1.61), and people with higher systolic blood pressure (HR:1.01, 95% CI: 1.01–1.02), lower high-density lipoprotein cholesterol (HR: 0.68, 95% CI: 0.50–0.93), diabetes (HR: 2.21, 95% CI: 1.64–2.97), and hypertension (HR:1.49, 95% CI: 1.23–1.81) had a significantly increased risk for the carotid plaque formation. Similar results remained in the sensitivity analysis. Conclusions: The TyG index can be used as a dose-responsive indicator of carotid plaque in the Chinese population. Elderly males with dyslipidemia, diabetes, or hypertension should be more vigilant about their TyG index since they are susceptible to developing carotid plaque. Physicians are encouraged to monitor the TyG index to help identify and treat patients with carotid plaque at an early stage. [ABSTRACT FROM AUTHOR]

Modulation instability (MI) is the main limitation factor of the maximum optical power in long-haul phase-sensitive optical time domain reflectometry (Φ-OTDR), and induces signal fading and serious phase noise. In this paper, a method of coherent seed injection is proposed to suppress the MI-induced phase noise in long-haul Φ-OTDR. The spontaneous MI is suppressed by stimulating induced MI in an optical fiber. The visibility of the signal in Φ-OTDR is enhanced and the phase noise is suppressed significantly. This paper offers an effective method to increase the maximum input power with the MI-induced phase noise suppressed in the long-haul Φ-OTDR system. As a result, the maximum input power and sensing distance can be potentially increased, which is greatly beneficial to the enhancement of the performance of long-haul Φ-OTDR. [ABSTRACT FROM AUTHOR]

Transition-metal dichalcogenide materials have attracted considerable attention due to their outstanding properties, and however, the carrier collection efficiency remains a major problem for achieving high-performance electronic and optoelectronic devices. In this research, we compared the carrier transport properties of graphite and Au in contact with MoS2 (WS2) materials. The use of graphite for the drain–source electrodes significantly improves carrier collection efficiency, thus enhancing the overall electronic and optoelectronic performance of MoS2 and WS2 FETs. The device’s ON/ OFF current ratio with two graphite contact electrodes increased by about two orders of magnitude (120 and 207 for MoS2 and WS2 FETs, respectively) than that with conventional Au electrodes. Furthermore, the Gr-MoS2-Gr FET shows ultrahigh responsivity (3869 A/W), detectivity ($4.6\times10$ 12 Jones), and extraordinary short photoresponse fall time ($60 ~\mu \text{s}$). Compared with the Au-MoS2-Au FET, the fall time is reduced by about six orders of magnitude. Interestingly, the Gr-MoS2-Gr and Gr-WS2-Gr FETs demonstrate different detection mechanisms. The Gr-MoS2-Gr photodetector shows a photoconduction mechanism under the gate voltage of −10 to −6 V and a photogate mechanism under −4 to 2 V, whereas the Gr-WS2-Gr photodetector is only driven by a photoconduction mechanism. The Gr-TMDs-Gr’s outstanding electronic and photoelectrical properties hold great potential for various applications in advanced optoelectronic devices. [ABSTRACT FROM AUTHOR]

As a member of the death-associated protein kinase (DAPK) family, STK17B plays an important role in the regulation of cellular apoptosis and has been considered as a promising drug target for hepatocellular carcinoma. However, the highly conserved ATP-binding site of protein kinases represents a challenge to design selective inhibitors for a specific DAPK isoform. In this study, molecular docking, multiple large-scale molecular dynamics (MD) simulations, and binding free energy calculations were performed to decipher the molecular mechanism of the binding selectivity of PKIS43 toward STK17B against its high homology STK17A. MD simulations revealed that STK17A underwent a significant conformational arrangement of the activation loop compared to STK17B. The binding free energy predictions suggested that the driving force to control the binding selectivity of PKIS43 was derived from the difference in the protein–ligand electrostatic interactions. Furthermore, the per-residue free energy decomposition unveiled that the energy contribution from Arg41 at the phosphate-binding loop of STK17B was the determinant factor responsible for the binding specificity of PKIS43. This study may provide useful information for the rational design of novel and potent selective inhibitors toward STK17B. [ABSTRACT FROM AUTHOR]

To examine methodologies that address imbalanced treatment switching and censoring, 6 different analytical approaches were evaluated under a comparative effectiveness framework: intention-to-treat, as-treated, intention-to-treat with censor-weighting, as-treated with censor-weighting, time-varying exposure, and time-varying exposure with censor-weighting. Marginal structural models were employed to address time-varying exposure, confounding, and possibly informative censoring in an administrative data set of adult patients who were hospitalized with acute coronary syndrome and treated with either clopidogrel or ticagrelor. The effectiveness endpoint included first occurrence of death, myocardial infarction, or stroke. These methodologies were then applied across simulated data sets with varying frequencies of treatment switching and censoring to compare the effect estimate of each analysis. The findings suggest that implementing different analytical approaches has an impact on the point estimate and interpretation of analyses, especially when censoring is highly unbalanced. [ABSTRACT FROM AUTHOR]

In recent years, fused deposition molding (FDM) has attracted much attention as one of the most common and promising 3D printing technologies. Forming accuracy is one of the most concerned quality characteristics in the FDM process and is influenced by many factors. Based on the fact that the temperature gradient affects the molding accuracy, this paper presents a method for optimizing the accuracy of fused deposition molded parts based on least square support vector regression (LS-SVR), which considers a functional input: the printing speed varies continuously in the printing process, thus reducing the temperature gradients. Some parameters that can affect the temperature and cooling of the part such as nozzle temperature, hotbed temperature, and filling rate are also included in the study. Integrating the characteristics of a functional input and the principle of experimental design, we propose to model the printing speed curve using a Bézier curve and use the curve control points together with the scalar inputs as the variables to be optimized. Then, the sample set is obtained experimentally using stratified Latin hypercube sampling for experimental point selection. The regression modeling of the sample data is performed using LS-SVR with an improved kernel function, where the kernel function is improved by the Fréchet distance. Finally, the entire model is optimized by means of the genetic algorithm. The results show that the dimensional accuracy of the parts is significantly optimized by the proposed method. A comparison with existing methods demonstrates the efficiency and practicality of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, we present a novel nonlinear vector network analyzer (NVNA) setup for charactering the in-band full-duplex (IBFD) performance of millimeter-wave antenna systems. To achieve millimeter-wave modulated measurements on dense spectral grids, this NVNA setup utilizes user-defined: 1) digitally-modulated test stimuli; 2) multisine phase reference; and 3) pulsed-radio frequency (RF) phase calibration standards for test bench establishment and calibration. To create the IBFD test scenario, a special design of test stimuli is developed for antenna characterization, where the spectral components of two periodical transmitting signals (digitally modulated within the same frequency band) do not overlap with each other. In this way, the desired magnitude and phase information of transmitted and received signals can be easily separated and extracted from the NVNA measurements, to support various frequency-, time-, and digital-domain analysis. The validity of the proposed NVNA setup is experimentally verified at 28 GHz, where the error vector magnitude (EVM) results of 100 MSymbol/s 64-QAM test signals are from 2.0% to 2.3%. From the application perspective, this measurement setup and test method can be widely used for fifth-generation (5G)-oriented over-the-air test of IBFD antenna systems. [ABSTRACT FROM AUTHOR]

Au nanoparticles (NPs) were drop-casted onto germanium (Ge) devices to investigate the influence of Au NPs on the electronic transport and photodetection properties of Ge metal–semiconductor–metal photodetectors. A significant hysteresis behavior was observed in the current–voltage curves of the Au NP-decorated Ge photodetector, which was ascribed to the energy band bending below the Au NPs and the electrostatic effect of image charges in the Au NPs. More interestingly, at the optical communication wavelength of $1.55~\mu \text{m}$ , the introduction of Au NPs effectively improved the responsivity of the device from 0.18 to 0.92 A/W. Rather than the localized surface plasmon resonance effect, the increase of responsivity in the Au NP-decorated Ge photodetector was caused by a type-II liked energy band alignment, which enhanced the spatial electron–hole separation effect. These results provide inspiration for the development of novel optoelectronic devices. [ABSTRACT FROM AUTHOR]

The on-board power supply system provides power for the launch vehicle. The power transmission and transformation system plays an irreplaceable role to ensure that the on-board power supply system receives the normal working voltage of the launch vehicle. There are many types of faults in power transmission and transformation systems. The traditional faulty diagnosis method of power transmission and transformation equipment has the disadvantages of being susceptible to experts' subjectivity and model's ossification. In this paper, a new method of equipment fault diagnosis based on big data is proposed. On the basis of big data, this paper introduces the failure mode clustering algorithm, the state parameter correlation analysis algorithm, the fault diagnosis method based on the correlation matrix, and other key fault diagnosis technologies. The fault record data of the 400 kV voltage grade oil-immersed transformer bushing in the past ten years by a Chinese combat unit is used as a case for demonstration. The results show that the accuracy rate of SC-LSTM-K-means clustering model exceeds 95%. And the fault classification mode can be accurately obtained. A priori correlation algorithm with TA coefficient can be used to evaluate the strong and weak relationship between the state parameters; the fault diagnosis matrix based on Pearson's correlation coefficient can accurately determine the fault mode consistent with the actual operation and maintenance test results. Therefore, the fault diagnosis method of power transmission and transformation system based on big data can both effectively obtain the inherent laws of historical data and realize more accurate fault diagnosis with data adaptability. [ABSTRACT FROM AUTHOR]

In this article, we present a vector network analyzer (VNA)-based measurement scheme and setup to obtain repeatable phase spectrum measurements of 75–110-GHz modulated radio frequency (RF) signals. In order to remove the random phase contribution of sweeping local oscillator (LO) in harmonic downconversion, the LO signal is coupled out into an auxiliary measurement channel where its random phase at the fundamental can be derived after additional modulation and downconversion treatments. Afterward, a user-defined math equation is used inside the VNA for LO phase cancellation, based on the traces of RF- and auxiliary-channel raw measurements. The key point of the proposed LO phase cancellation technique is measuring the 75–110-GHz test signal and the auxiliary-channel signal at the same GHz intermediate frequency so that the receivers of VNA can measure both of them simultaneously when working on the peculiar continuous-wave or zero-span mode. According to the method validation at 78, 93, and 108 GHz, a phase fluctuation of ±2° for single-run measurements is found reachable in practice. [ABSTRACT FROM AUTHOR]

Microstructure reconstruction is an important and emerging field of research and an essential foundation to improving inverse computational materials engineering (ICME). Much of the recent progress in the field is made based on generative adversarial networks (GANs). Although excellent results have been achieved throughout a variety of materials, challenges remain regarding the interpretability of the model's latent space as well as the applicability to extremely small data sets. The present work addresses these issues by introducing DA-VEGAN, a model with two central innovations. First, a β -variational autoencoder is incorporated into a hybrid GAN architecture that allows to penalize strong nonlinearities in the latent space by an additional parameter, β. Secondly, a custom differentiable data augmentation scheme is developed specifically for this architecture. The differentiability allows the model to learn from extremely small data sets without mode collapse or deteriorated sample quality. An extensive validation on a variety of structures demonstrates the potential of the method and future directions of investigation are discussed. [Display omitted] [ABSTRACT FROM AUTHOR]

• NDVI differentiation in endorheic basins was described nonlinearly by the TWSA. • Approximately 98% of NDVI in the study area responded nonlinearly to the TWSA. • The nonlinear causal test was improved by considering the optimal moving window. The terrestrial water storage anomaly (TWSA) is an important parameter for assessing the land water budget, and it interacts well with terrestrial ecosystems via complex hydrological processes. Recently, the decline in central Asian terrestrial water storage (TWS) has threatened the health of local ecosystems. Therefore, it is of great significance to adopt an efficient approach to explore and identify the nonlinear relationship between two important indicators, i.e., the TWSA and normalized difference vegetation index (NDVI) in the arid central Asian endorheic basins. In this study, we analysed the long-term trends of the TWSA and NDVI, and identified the lag month (1 month) as the optimal moving window of the nonlinear Granger causality test embedded in random forest to detect the nonlinear NDVI change response of NDVI changes in vegetation to the TWSA from 2003 to 2015. There are decreasing trends in TWSAs over approximately 81.7% of the study area and the NDVI generally decreased resulting in approximately 36% vegetation browning in the study area. The nonlinear Granger unidirectional causes of the TWSA were responsible for 97.9% of the NDVI variation in the study area considering the optimal response time for moving windows. The causes of vegetation browning in the central Asian Aral Sea basin and vegetation greening in the basins of Northwest China could be mostly explained by the changes in TWS. Our findings contribute to understanding the nonlinear causal linkages between vegetation and the TWSA in endorheic basins, and these findings provide insights for obtaining terrestrial water consumption patterns and water resource management under the joint influence of climate change and human activities. [ABSTRACT FROM AUTHOR]

To enhance high-temperature wear resistance and cutting performances of cermet tools, nano-Al 2 O 3 particles were added into four kinds of Ti(C,N)-based cermets. The microstructure, mechanical properties, wear resistance, and cutting performances were studied. The nano-Al 2 O 3 was supposed to distribute in the binder phase, leading to the change of lattice constants and dispersion strengthening. Due to the distribution of nanoparticles at the grain boundaries, the movement of the grain boundaries was hindered, and the mean grain size decreased from 1.03 μm to 0.89 μm. The hardness and fracture toughness showed the change tendency of rising the peak and then falling with nano-Al 2 O 3 addition. The cermet with 2 wt% nano-Al 2 O 3 displayed the topmost hardness of 1654.4 HV 30 and fracture toughness of 9.1 MPa·m1/2, due to the dispersion strengthening and pinning effect of nano particles. During the sliding wear tests at 700 °C, the wear rates of cermet containing 2 wt% nano-Al 2 O 3 decreased by 63% compared to cermet without nano-Al 2 O 3. The superior high-temperature wear resistance was ascribed to the thermal softening resistance of nano-Al 2 O 3 , the strengthening and toughening effect of nano-Al 2 O 3 on matrix and the dense tribo-chemical layers. The abrasive wear of cermet with no nano-Al 2 O 3 addition was more significant, while the wear behavior changed to the removal of tribo-chemical layers when nano-Al 2 O 3 was 2 wt%. The tool life of cermet with 2 wt% nano-Al 2 O 3 was increased by 50% in comparison with cermet without nano-Al 2 O 3 during machining 45 steel. • Ti(C,N)-based cermets are prepared with different nano-Al 2 O 3 additions. • Dispersion strengthening theory shows the mechanism of the enhancement of hardness. • High temperature friction properties and wear morphologies of cermets are analyzed. • A certain amount of nano-Al 2 O 3 improves high temperature wear resistance and cutting performance of cermet tools. [ABSTRACT FROM AUTHOR]

• Overlapping heating and cooling demand in the entire European building stock is assessed. • Evaluation is based on hectare-sized units and GIS method. • 8 scenarios representing future climate, renovations, and cooling area are considered. • Less than 0.1% of the current building stock has enough overlapping demand for 5GDHC. • The future potential of 5GDHC considering overlapping demand and density is limited. With warmer climate conditions, the growing need to cool down building environment in Europe calls for efficient solutions to solve the heating and cooling demand altogether. To meet such requirement, the bi-directional fifth generation district heating and cooling (5GDHC) system has been proposed in recent years, while having the capability of integrating the renewable and waste energy sources. The overlapping heating and cooling demand, or referred to as the simultaneous demand, is proved as the key pre-requisite to guide the application of 5GDHC through several case studies. However, how large is this overlapping part in the practical building stock and where are the feasible areas for 5GDHC remain unclear. To close the gap, this study assesses the quantities and geographical distributions of overlapping heating and cooling demand across Europe in EU 27, UK, and EFTA countries. Using GIS-based methods and data sources, the study region is split into 28 million hectare-sized units where the overlapping demand is specifically calculated. Moreover, the possible future changes to the heating and cooling demand alone brought by warmer climate, building renovations, and increased cooling area were investigated. The results from reference condition at year 2016 reveal that less than 0.1% of the building stock has DOC larger than 0.3, which is the threshold for 5GDHC being energy efficient. These potential areas are primarily found in city centres involving cooling demands from commercial and industrial processes. In the future scenarios of year 2050, while a better energy performance of buildings and warmer climate may decrease the heating and increase the cooling demand, the overlapping part is only slightly increased by around 5%. Accordingly, around 2500 ha-sized units from the entire study region are found to meet the DOC limit required by the 5GDHC while having large enough demand density to support district energy systems. The presented works geographically identified the potential areas for 5GDHC and can be extended with regional details to serve as the connection between top-level planning and bottom-level case studies. [ABSTRACT FROM AUTHOR]

Medical image segmentation is a fundamental and critical step in many clinical approaches. Semi-supervised learning has been widely applied to medical image segmentation tasks since it alleviates the heavy burden of acquiring expert-examined annotations and takes the advantage of unlabeled data which is much easier to acquire. Although consistency learning has been proven to be an effective approach by enforcing an invariance of predictions under different distributions, existing approaches cannot make full use of region-level shape constraint and boundary-level distance information from unlabeled data. In this paper, we propose a novel uncertainty-guided mutual consistency learning framework to effectively exploit unlabeled data by integrating intra-task consistency learning from up-to-date predictions for self-ensembling and cross-task consistency learning from task-level regularization to exploit geometric shape information. The framework is guided by the estimated segmentation uncertainty of models to select out relatively certain predictions for consistency learning, so as to effectively exploit more reliable information from unlabeled data. Experiments on two publicly available benchmark datasets showed that: (1) Our proposed method can achieve significant performance improvement by leveraging unlabeled data, with up to 4.13% and 9.82% in Dice coefficient compared to supervised baseline on left atrium segmentation and brain tumor segmentation, respectively. (2) Compared with other semi-supervised segmentation methods, our proposed method achieve better segmentation performance under the same backbone network and task settings on both datasets, demonstrating the effectiveness and robustness of our method and potential transferability for other medical image segmentation tasks. • A novel uncertainty-guided mutual consistency learning framework is proposed for semi-supervised medical image segmentation to alleviate the heavy burden of acquiring expert-examined annotations. • Incorporating both intra-task and cross-task consistency learning with the guidance of estimated segmentation uncertainty to efficiently utilize unlabeled data. • Extensive experiments on two benchmark datasets show that our proposed method outperforms existing semi-supervised segmentation methods with promising performance. [ABSTRACT FROM AUTHOR]

This paper presents a spatial–spectral low-light enhancement approach based on the neural network. Considering that the Image Signal Processor (ISP) which non-linearly maps RAW data to RGB images may introduce additional noise and artifacts, we propose to conduct the enhancement task directly on RAW data. To this end, we propose a cross-scale framework to map the input low-light RAW data to visually pleasing RGB images. The cross-scale framework consists of three branches for low-level, mid-level, and high-level representations of input images. We embed paired Fast Fourier Convolution (FFC) and Transformer in each level for global and local feature analysis and aggregation. Specifically, the FFC enlarges the receptive field of our neural network, exploring the pixel correlations in the spectral space; the following Transformer uses self-attention for feature selection and aggregation in the spatial space. As a result, spatial–spectral information within an image is jointly utilized for the final fusion. Experimental results demonstrate that the proposed approach significantly outperforms state-of-the-art low-light enhancement methods in both full reference assessment metrics, including PSNR, MPSNR, and SSIM, and no-reference metrics, such as NIMA. Moreover, the proposed method produces more aesthetically pleasing RGB images than other methods. [Display omitted] • We propose a cross-scale framework to map the RAW data to RGB images. • We utilize FFC and Transformer to extract latent features in each scale of our framework. • Results show that the proposed method remarkably outperforms sota works. [ABSTRACT FROM AUTHOR]

• Spatiotemporal variation in vegetation on the Loess Plateau was investigated. • Precipitation was the greatest driving factor. • There was a bivariate or nonlinear enhancement between all factors. • Key factors' adaptation range or type suitable for vegetation cover was identified. Vegetation, being a core component of ecosystems, is known to be influenced by natural and anthropogenic factors. Studying vegetation cover dynamics variation and its drivers is critical to understanding the interactions between vegetation and ecosystems. The Loess Plateau (LP) is located in a semi-arid and semi-humid region with severe soil erosion and fragile ecology. This paper used the annual maximum Normalized Difference Vegetation Index (NDVI ymax) and growing season mean NDVI (NDVI gsmean) as the vegetation cover indicator. The vegetation cover variation of LP from 2000 to 2020 was analyzed using Sen's slope and Mann-Kendall test. Then the influence of natural and anthropogenic factors on the driving mechanisms of spatial vegetation differentiation was explored by the Geodetector model. The results revealed that the growth trends of NDVI ymax and NDVI gsmean were 0.075/10 years and 0.038/10 years, respectively, and the areas with improved vegetation cover accounted for 92.67 % and 88.58 % of the total area. The vegetation cover of the southeastern and northern parts of the LP decreased significantly; however, the central, southwestern, and northeastern parts exhibited a remarkable improvement. Precipitation, vegetation type, soil type, temperature, and land use type were the key driving forces, ranked differently on NDVI ymax and NDVI gsmean. However, precipitation was the most critical factor both on NDVI ymax and NDVI gsmean. The interaction detection showed non-linear and mutual enhancement, with no independent factor. The findings of our study can assist in identifying the vegetation cover status of the LP, as well as the driving forces, which can provide theoretical support for the formulation of environmental conservation policies. [ABSTRACT FROM AUTHOR]

Uveal melanoma (UVM) is the most common primary ocular malignancy in adults and involves several types of regulated cell death. Cuproptosis is a novel method of regulating cell death by binding lipoylated TCA cycle proteins. There is still no research on the relationship between cuproptosis-related genes (CRGs) and UVM. Here, we aimed to develop a prognostic CRG signature for UVM. After a prognostic CRG signature was constructed, we determined the relationship between the signature and immune infiltration, bioinformatics analysis and experimental validation. Finally, a prognostic cuproptosis-related three-gene (CRTG) signature was constructed, which comprised ORAI2, ACADSB and SLC47A1. The risk score of the CRTG signature was negatively correlated with the overall survival (OS) and progression-free survival (PFS) of patients, which revealed strong predictive ability and its independent prognostic value. In addition, we found that the risk score was negative for chromosomes 3 and 6p, and positive for 8q, and high-risk UVM patients showed an increase in protumor immune infiltrates and a high expression of immune checkpoints. Finally, experimental validation verified that the migratory ability of MUM-2B cells was suppressed by the knockdown of the identified genes in vitro. We constructed a CRTG signature that is helpful in predicting prognosis and guiding treatment for patients with UVM. [ABSTRACT FROM AUTHOR]

Recently, deep convolutional neural networks have achieved great success for medical image segmentation. However, unlike segmentation of natural images, most medical images such as MRI and CT are volumetric data. In order to make full use of volumetric information, 3D CNNs are widely used. However, 3D CNNs suffer from higher inference time and computation cost, which hinders their further clinical applications. Additionally, with the increased number of parameters, the risk of overfitting is higher, especially for medical images where data and annotations are expensive to acquire. To issue this problem, many 2.5D segmentation methods have been proposed to make use of volumetric spatial information with less computation cost. Despite these works lead to improvements on a variety of segmentation tasks, to the best of our knowledge, there has not previously been a large-scale empirical comparison of these methods. In this paper, we aim to present a review of the latest developments of 2.5D methods for volumetric medical image segmentation. Additionally, to compare the performance and effectiveness of these methods, we provide an empirical study of these methods on three representative segmentation tasks involving different modalities and targets. Our experimental results highlight that 3D CNNs may not always be the best choice. Despite all these 2.5D methods can bring performance gains to 2D baseline, not all the methods hold the benefits on different datasets. We hope the results and conclusions of our study will prove useful for the community on exploring and developing efficient volumetric medical image segmentation methods. • We summarize the latest developments about 2.5D segmentation methods for volumetric medical image segmentation tasks. • We make a large-scale empirical comparison of 2.5D segmentation methods with 2D and 3D methods on three representative public datasets involving different modalities (CT and MRI) and targets (cardiac, prostate and abdomen) to systematically evaluate the performance of these methods on different segmentation tasks. • We make conclusions base on the experimental results which we hope will prove useful for the community on exploring and developing efficient volumetric medical image segmentation methods. [ABSTRACT FROM AUTHOR]

• High-speed impact dynamics and temperature changes are measured experimentally. • Theoretical models of drop and surface temperature changes (Δ T d and Δ T s ) are given. • Impact outcomes significantly affect the temperature variations. • Δ T d scaling laws are found for non-Leidenfrost drops: Δ T d ∼ t 3 / 2 first and then ∼ t. • Negligible temperature changes for Leidenfrost droplets due to a vapor layer. [Display omitted] Drop impact on heated surfaces plays a vital role in numerous applications, such as spraying, cooling, and combustion. In addition to impact dynamics, we investigate both droplet and surface temperature changes using a high-speed infrared (IR) camera and thermocouples when a Milli-Q water droplet impacts on a heated surface under various Weber numbers (1.6 ≤ W e ≤ 129 , which compares the drop kinetic to surface energy) and initial surface temperature (100 ∘ C ≤ T s i ≤ 445 ∘ C). Theoretical models of droplet and surface temperature changes are deduced using the energy conservation principle. Both theoretical and experimental results show that temperature variations are dramatically influenced by impact dynamics, which shows spreading, spreading/splashing atomization, or complete rebound depending on W e and T s i. For non-Leidenfrost droplets, the experimental results show that the mean droplet temperature change (Δ T d) is increased with increasing W e and T s i and scales with Δ T d ∼ t 3 / 2 and Δ T d ∼ t in the initial spreading and later-time sticking stages, respectively. The experimental results of solid surface temperature change, Δ T s c ≡ Δ T s (z = 0) , show that Δ T s c alters sharply with W e for W e < 30 , whereas insignificantly for W e > 30 with an identical T s i. Under the same W e , Δ T s c increases first for 100 ∘ C ≲ T s i ≲ 300 ∘ C and then reduces when 300 ∘ C ≲ T s i ≲ 445 ∘ C because of enhanced atomization at elevated temperatures. Finally, a negligible Δ T d and a nearly constant Δ T s c (≲ 4 ∘ C) are observed for Leidenfrost droplets due to the formation of an insulating vapor layer formed underneath the bouncing droplet. [ABSTRACT FROM AUTHOR]

With rapid urbanization, the building stock and related winter heating demands are developing fast in the urban regions of Northern China. In addition to the national strategy to alleviate the air pollution, China has also pledged to achieve carbon neutrality in the future. Although the planning of heating system has been studied from national level, bottom-level regional plans are still lacking, which is especially crucial for a huge country as China that has significantly different characteristics across regions. Therefore, this study examined the transitions of the heating sectors towards 2035 and 2050 for 1047 third-level urban units in Northern China. Future changes in heating resources under the low-carbon transitions and future heating demands with the urbanization trend were investigated. Through geographic mapping of resources and demands for county-level units, the regional differences in future scenarios owing to the uneven socioeconomic development of Northern China were presented, which fill in the knowledge gap. By combining supply-side investigations and demand-side forecasts, various roadmaps were evaluated in terms of primary energy consumption, pollution emissions, and economic benefits. Although significant pollution reductions can be achieved in all proposed roadmaps, the clean heating roadmap with the optimal utilization of available resources presents a lower annualized cost than the business-as-usual roadmap, which simply relies on biomass and supplementary sources such as natural gas. In 2050, the primary energy consumption can be reduced to approximately 3 kgce/m2, with an annualized cost of 6 CNY/m2. Balancing the carbon emissions and economic performance, the optimal renovation pattern, together with supply side technologies, were identified in this study. • Regional investigations in 1047 urban units in Northern China. • Forecast of heating resources and demands in future conditions. • Heat roadmaps were evaluated for environmental and economic implications. • The CHR has lower annualized costs and carbon emissions than the BAU roadmap. • Optimal renovation pattern is identified based on climate and economic implication. [ABSTRACT FROM AUTHOR]

We report ultrafast charge migration in ionized iodo-alkyne chain I(CC)nH+ for n = 1, 2, ..., 5. The dynamics of electron density become more complicated with the increasing length of the molecular chain. However, the essential properties of charge migration in I(CC)nH+ can be clearly interpreted in terms of the electron flux. By systematic investigations of the dynamics of electron density, hole density, and the electron flux for different molecules, the size dependence of charge migration in I(CC)nH+ is discussed. [ABSTRACT FROM AUTHOR]

This study aimed to explore whether the defect of visual function is a risk factor of knee anterior cruciate ligament (ACL) sports injury and to provide a theoretical basis for the primary prevention of ACL sports injury. This cross-sectional study included 392 participants divided into two groups: the sports injury group (287 with sports injury of knee) and the control group (105 healthy volunteers). Participants in the sports injury group were further divided into the ACL-Intact group (133) and the ACL-Deficient group (154). Participants in the sports injury group received a questionnaire about the conditions of their injury (including injury action, site condition, weather, contact) and a visual examination by synoptophore (including binocular vision, subjective and objective oblique angle, visual fusion range, stereoacuity). Participants in the control group only received the visual examination. In the end, we found that low visual fusion range (p = 0.003) and injury action, especially quick turn (p = 0.001), sudden stop (p < 0.001) and jump (p = 0.001), are the major risk factors for ACL injury in the analysis of the integrated data. In addition, athletes with low vision fusion range have increased risk of ACL sports injury when they make a sudden stop on wooden floor, plastic floor or cement floor on cloudy days (OR = 13.208). Visual factors, especially low fusion range, significantly increase the risk of ACL sports injury. [ABSTRACT FROM AUTHOR]

Minuscule pressure/stress detection with high sensitivity can recognize and deal with potential hazards timely, which is crucial for guaranteeing the security of human and stability of social functioning. Lithium niobate (LiNbO 3) single crystal possessing excellent piezoelectric and ferroelectric properties is suitable for fabricating piezoelectric pressure sensors. Therefore, in this paper, the pressure sensors based on LiNbO 3 single crystals with parallel connected structure were researched. Sensors with parallel connected structure can improve the sensitivity from 4.86 V/N of single sheet structure to 8.71 V/N under the stress between 0.01 N and 0.2 N at 30 °C. Both types of the sensors can detect the minuscule stress low to 0.01 N and minuscule pressure generated by balloon pump, blowing largely or slowly. The influence of temperature on sensors was also researched, and the results exhibited that sensors performed well from 30 °C to 60 °C and still sustained high sensitivity of 5.26 V/N of parallel connected structure and 3.71 V/N of single sheet structure at 60 °C. Besides, the response time of sensors to the pressure of balloon pump is 60 ms under different temperature. These excellent properties indicate the great potential applications of fabricated sensors in practical minuscule pressure/stress detection. [ABSTRACT FROM AUTHOR]

Aging contributes significantly to cognitive decline. Aerobic exercise (AE) has been shown to induce substantial neuroplasticity changes, enhancing cognitive and brain health. Likewise, recent research underscores the cognitive benefits of foreign language learning (FLL), indicating improvements in brain structure and function across age groups. However, the lack of a comprehensive paradigm integrating language learning with exercise limits research on combined effects in older adults. In order to address this gap, we devised a novel approach using a virtual world tourism scenario for auditory-based language learning combined with aerobic cycling. Our study examines the impact of simultaneous AE and FLL integration on cognitive and language learning outcomes compared to FLL alone. A total of 20 older adults were randomly assigned to AE + FLL and FLL-only groups. The results revealed significantly improved Spanish language learning outcomes in both combined and language learning-only groups. Additionally, significant cognitive function improvement was observed in the FLL group following short-term language learning. [ABSTRACT FROM AUTHOR]

Semantic communication is a promising technology used to overcome the challenges of large bandwidth and power requirements caused by the data explosion. Semantic representation is an important issue in semantic communication. The knowledge graph, powered by deep learning, can improve the accuracy of semantic representation while removing semantic ambiguity. Therefore, we propose a semantic communication system based on the knowledge graph. Specifically, in our system, the transmitted sentences are converted into triplets by using the knowledge graph. Triplets can be viewed as basic semantic symbols for semantic extraction and restoration and can be sorted based on semantic importance. Moreover, the proposed communication system adaptively adjusts the transmitted contents according to channel quality and allocates more transmission resources to important triplets to enhance communication reliability. Simulation results show that the proposed system significantly enhances the reliability of the communication in the low signal-to-noise regime compared to the traditional schemes. [ABSTRACT FROM AUTHOR]

When extracting flight data from airport terminal area, there are matters such as large volume, unclear features, and similar trend in time series. In order to deal with the related issues and to optimize the description, by combining with the TBO (Trajectory-Based Operation), an application proposed by the ICAO (International Civil Aviation Organization) in ASBU (Aviation System Block Upgrade), using multisource dynamic model to establish 4DDW (4D dynamic warping) algorithm, the multisource modeling integrated with evaluation system is proposed to realize the flight path optimization with time series characteristics and accord with the interval concept. The calculation results show that 4DDW can obtain the optimal solution for multiprofile calculation of TBO by comparing the composite trajectory deviation values and time dimension planning using the buffer and threshold values recommended by ICAO in airspace planning and flight procedure design. The results meet the requirements of high accuracy and convergence features of spatial waypoints and can improve the airport operation standards and terminal area capacity. [ABSTRACT FROM AUTHOR]

Zinc (Zn)–dysprosium (Dy) binary alloys are promising biodegradable bone fracture fixation implants owing to their attractive biodegradability and mechanical properties. However, their clinical application is a challenge for bone fracture healing, due to the lack of Zn–Dy alloys with tailored proper bio‐mechanical and osteointegration properties for bone regeneration. A Zn‐5Dy alloy with high strength and ductility and a degradation rate aligned with the bone remodeling cycle is developed. Here, mechanical stability is further confirmed, proving that Zn‐5Dy alloy can resist aging in the degradation process, thus meeting the mechanical requirements of fracture fixation. In vitro cellular experiments reveal that the Zn‐5Dy alloy enhances osteogenesis and angiogenesis by elevating SIRT4‐mediated mitochondrial function. In vivo Micro‐CT, SEM‐EDS, and immunohistochemistry analyses further indicate good biosafety, suitable biodegradation rate, and great osteointegration of Zn‐5Dy alloy during bone healing, which also depends on the upregulation of SIRT4‐mediated mitochondrial events. Overall, the study is the first to report a Zn‐5Dy alloy that exerts remarkable osteointegration properties and has a strong potential to promote bone healing. Furthermore, the results highlight the importance of mitochondrial modulation and shall guide the future development of mitochondria‐targeting materials in enhancing bone fracture healing. [ABSTRACT FROM AUTHOR]

As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang. [ABSTRACT FROM AUTHOR]

Photovoltaic power generation can directly convert solar energy into electricity, but most of the solar energy absorbed by the photovoltaic panel is converted into heat, which significantly increases the operating temperature leading to a reduction in the power generation efficiency of the panels. To reduce the working temperature of photovoltaic panels and improve the photoelectric conversion efficiency, this paper installs aluminum fins and air channels at the traditional photovoltaic cell back sheets and cools them with forced-circulation cooling through fans. The relationships between fin spacing, fin height, air channel inlet wind speed and panel temperature, power generation, and electrical efficiency were investigated. The results show that the temperature of the photovoltaic panel decreases and then increases with the decrease of the fin spacing during natural convection and gradually decreases with the increase of the fin height. The use of forced-circulation cooling technology can effectively reduce the PV panel temperature and increase the net power generation. When the solar radiation intensity is 1000 W/m2, the ambient temperature is 35°C, the fin spacing is 6 mm, the height is 80 mm, the inlet wind speed is 1 m/s, the net generating power reaches the maximum value, and the net generating power and the electrical efficiency are increased by 14.6% and 2.25%, respectively. [ABSTRACT FROM AUTHOR]

The aggregation of the remaining battery capacity of electric vehicles (EVs) can be used as distributed energy storage to participate in the microgrid optimisation through vehicle‐to‐grid (V2G) technology. However, the reliability of this service to be delivered is affected by the uncertainty of EVs' behaviour. The un‐reliable service will bring risks in the operation of microgrid when EVs' V2G electricity is regarded as an important flexibility resource. This paper, first proposes an analytical method to quantify the reliability of EV aggregation's (EVA's) V2G electricity based on the analysis of historical charging data and compound Poisson process. Based on this model, electric vehicles aggregators can evaluate the V2G bid quantity for any time slot on day t+1 according to the reliability requirements. Secondly, an optimal operation model of microgrid with consideration of V2G's reliability is considered. Finally, a test system with photovoltaics (PVs) and EVA on top of the original IEEE 33‐node system is used to verify the effectiveness of the proposed model. The results show that with the proposed reliability evaluation method of V2G electricity, the optimal operation of the microgrid can be reached with appropriate evaluation of the capability of the EVA. [ABSTRACT FROM AUTHOR]

The application of standing surface acoustic wave (SSAW) tweezers based on backpropagation superposition to achieve precise behavior manipulation of microscale cells and even nanoscale bacteria has been widely studied and industrialized. However, the structure requires multiple transducer components or full channel resonance. It is very challenging to design a simple structure for nano-control by complex acoustic field. In this study, a reflector-interdigital transducer (R-IDT) acoustofluidic device based on unilateral coherence enhancement is proposed to achieve SSAW definition features of periodic particle capture positions. The SAW device based on a unilateral transducer can not only generate leaky-SAW in water-filled microchannel, but also have a contribution of spherical waves in the vibration area of the substrate-liquid interface due to the Huygens-Fresnel diffractive principle. Both of them form a robust time-averaged spatial periodicity in the pressure potential gradient, accurately predicting the lateral spacing of these positions through acoustic patterning methods. Furthermore, a reflector based on Bragg-reflection is used to suppress backward transmitted SAW and enhance forward conducted SAW beams. By using a finite element model, R-IDT structure's amplitude enhances 60.78% compared to single IDT structure. The particle manipulation range of the diffractive acoustic field greatly improves, verified by experimental polystyrene microspheres. Besides, biocompatibility is conformed through red blood cells and Bacillus subtilis. We investigate the overall shift of periodic pressure field that can still occur when the phase changes. This work provides a simpler and low-cost solution for the application of acoustic tweezer in biological cell culture and filtering. [ABSTRACT FROM AUTHOR]

Cortical gray to white matter signal intensity ratio (GWR) measured from T1‐weighted magnetic resonance (MR) images was associated with neurodegeneration and dementia. We characterized topological patterns of GWR during AD pathogenesis and investigated its association with cognitive decline. The study included a cross‐sectional dataset and a longitudinal dataset. The cross‐sectional dataset included 60 cognitively healthy controls, 61 mild cognitive impairment (MCI), and 63 patients with dementia. The longitudinal dataset included 26 participants who progressed from cognitively normal to dementia and 26 controls that remained cognitively normal. GWR was compared across the cross‐sectional groups, adjusted for amyloid PET. The correlation between GWR and cognition performance was also evaluated. The longitudinal dataset was used to investigate GWR alteration during the AD pathogenesis. Dementia with β‐amyloid deposition group exhibited the largest area of increased GWR, followed by MCI with β‐amyloid deposition, MCI without β‐amyloid deposition, and controls. The spatial pattern of GWR‐increased regions was not influenced by β‐amyloid deposits. Correlation between regional GWR alteration and cognitive decline was only detected among individuals with β‐amyloid deposition. GWR showed positive correlation with tau PET in the left supramarginal, lateral occipital gyrus, and right middle frontal cortex. The longitudinal study showed that GWR increased around the fusiform, inferior/superior temporal lobe, and entorhinal cortex in MCI and progressed to larger cortical regions after progression to AD. The spatial pattern of GWR‐increased regions was independent of β‐amyloid deposits but overlapped with tauopathy. The GWR can serve as a promising biomarker of neurodegeneration in AD. [ABSTRACT FROM AUTHOR]

The finned-tube heat exchanger is the core part of an air conditioning system. Its heat exchange performance directly affects the energy consumption and efficiency of the air conditioner. The shortage and rising price of copper have led to increasing replacement of copper tubes with aluminum tubes in finned-tube heat exchangers. This paper studies two kinds of such heat exchangers, one consisting of copper tubes and aluminum fins and the other consisting of aluminum tubes and aluminum fins. The influences of the different base tube materials on heat transfer are compared and analyzed in terms of heat transfer strength and cost per unit heat transfer. The results show that the heat transfer and heat transfer coefficient increase with increasing inlet wind speed. Under different inlet wind speeds, the heat transfer and heat transfer coefficient of the finned-tube heat exchanger with aluminum tubes are 4%–12% and 7%%–9% lower than those of an identically structured heat exchanger with copper tubes, respectively. The aluminum-aluminum exchanger achieves 67% higher heat transfer than that of the copper-aluminum exchanger at only 8% of the cost. These results are significant for guiding the development and application of finned-tube heat exchangers. [ABSTRACT FROM AUTHOR]

Background: Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. Methods: We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. Results: NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). Conclusions: By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace [ABSTRACT FROM AUTHOR]

Background: Domains of unknown function (DUF) proteins are a number of uncharacterized and highly conserved protein families in eukaryotes. In plants, some DUFs have been predicted to play important roles in development and response to abiotic stress. Among them, DUF568-containing protein family is plant-specific and has not been described previously. A basic analysis and expression profiling was performed, and the co-expression and interaction networks were constructed to explore the functions of DUF568 family in rice. Results: The phylogenetic tree showed that the 8, 9 and 11 DUF568 family members from rice, Arabidopsis and maize were divided into three groups. The evolutionary relationship between DUF568 members in rice and maize was close, while the genes in Arabidopsis were more distantly related. The cis-elements prediction showed that over 82% of the elements upstream of OsDUF568 genes were responsive to light and phytohormones. Gene expression profile prediction and RT-qPCR experiments revealed that OsDUF568 genes were highly expressed in leaves, stems and roots of rice seedling. The expression of some OsDUF568 genes varied in response to plant hormones (abscisic acid, 6-benzylaminopurine) and abiotic stress (drought and chilling). Further analysis of the co-expression and protein–protein interaction networks using gene ontology showed that OsDUF568 − related genes were enriched in cellular transports, metabolism and processes. Conclusions: In summary, our findings suggest that the OsDUF568 family may be a vital gene family for the development of rice roots, leaves and stems. In addition, the OsDUF568 family may participate in abscisic acid and cytokinin signaling pathways, and may be related to abiotic stress resistance in these vegetative tissues of rice. [ABSTRACT FROM AUTHOR]

Based on the characteristics of underdeveloped areas, this paper selects the panel data of 15 underdeveloped counties in Anhui Province from 2013 to 2019 and uses the panel threshold model to empirically analyze the sustainability of rural tourism development. The results show that: (1) Rural tourism development has a non-linear positive impact on poverty alleviation in underdeveloped areas and has a double threshold effect. (2) When the poverty rate is used to express the poverty level, it can be found that the development of rural tourism at a high level can significantly promote poverty alleviation. (3) When the number of poor people is used to express the poverty level, it can be found that the poverty reduction effect shows a marginal decreasing trend with the phased improvement of the development level of rural tourism. (4) The degree of government intervention, industrial structure, economic development, and fixed asset investment play a more significant role in poverty alleviation. Therefore, we believe that we need to actively promote rural tourism in underdeveloped areas, establish a mechanism for the distribution and sharing of rural tourism benefits, and form a long-term mechanism for rural tourism poverty reduction. [ABSTRACT FROM AUTHOR]

Background: The benefit-risk profile of direct oral anticoagulants (DOACs) compared with warfarin, and between DOACs in patients with atrial fibrillation (AF) and chronic liver disease is unclear. Methods: We conducted a new-user, retrospective cohort study of patients with AF and chronic liver disease who were enrolled in a large, US-based administrative database between January 1, 2011, and December 31, 2017. We assessed the effectiveness and safety of DOACs (as a class and individually) compared with warfarin, and between DOACs in patients with AF and chronic liver disease. The primary outcomes were hospitalization for ischemic stroke/systemic embolism and hospitalization for major bleeding. Inverse probability treatment weights were used to balance the treatment groups on measured confounders. Results: Overall, 10 209 participants were included, with 4421 (43.2%) on warfarin, 2721 (26.7%) apixaban, 2211 (21.7%) rivaroxaban, and 851 (8.3%) dabigatran. The incidence rates per 100 person-years for ischemic stroke/systemic embolism were 2.2, 1.4, 2.6, and 4.4 for DOACs as a class, apixaban, rivaroxaban, and warfarin, respectively. The incidence rates per 100 person-years for major bleeding were 7.9, 6.5, 9.1, and 15.0 for DOACs as a class, apixaban, rivaroxaban, and warfarin, respectively. After inverse probability treatment weights, the risk of hospitalization for ischemic stroke/systemic embolism was significantly lower between DOACs as a class (hazard ratio [HR], 0.64 [95% CI, 0.46–0.90]) or apixaban (HR, 0.40 [95% CI, 0.19–0.82]) compared with warfarin, but not significantly different between rivaroxaban versus warfarin (HR, 0.76 [95% CI, 0.47–1.21]) or rivaroxaban versus apixaban (HR, 1.73 [95% CI, 0.91–3.29]). Compared with warfarin, the risk of hospitalization for major bleeding was lower with DOACs as a class (HR, 0.69 [95% CI, 0.58–0.82]), apixaban (HR, 0.60 [95% CI, 0.46–0.78]), and rivaroxaban (HR, 0.79 [95% CI, 0.62–1.0]). However, the risk of hospitalization for major bleeding was higher for rivaroxaban versus apixaban (HR, 1.59 [95% CI, 1.18–2.14]). Conclusions: Among patients with AF and chronic liver disease, DOACs as a class were associated with lower risks of hospitalization for ischemic stroke/systemic embolism and major bleeding versus warfarin. However, the incidence of clinical outcomes among patients with AF and chronic liver disease varied between individual DOACs and warfarin, and in head-to-head DOAC comparisons. [ABSTRACT FROM AUTHOR]