Search

Efficient spin sources with large spin Hall angle (θSH) and long spin diffusion length (λSD) are highly desired in the application of spintronic devices. However, due to strong spin‐orbit coupling, the two targets can hardly be achieved simultaneously in conventional relativistic spin sources, like heavy metals. Here, it is proven that collinear antiferromagnetic RuO2 films are able to address this key issue and break the inverse relationship of θSH versus λSD. Based on spin torque‐ferromagnetic resonance and spin pumping measurements, the authors demonstrate that the θSH of RuO2(100) films is 0.183, and the λSD is over 12 nm being an order of magnitude longer than that of Pt, β‐W, and β‐Ta. Meanwhile, sizable λSD is also obtained in spin current with out‐of‐plane spin polarization generated by RuO2(101) films. By conducting a control experiment, the nonrelativistic altermagnetic spin splitting effect (ASSE) is ascertained to be the crucial mechanism accounting for the simultaneous large θSH and long λSD in RuO2. Besides the fundamental significance, these findings will advance the development of spintronics towards higher efficiency and lower power consumption. [ABSTRACT FROM AUTHOR]

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]

With clustered data, such as where students are nested within schools or employees are nested within organizations, it is often of interest to estimate and compare associations among variables separately for each level. While researchers routinely estimate between-cluster effects using the sample cluster means of a predictor, previous research has shown that such practice leads to biased estimates of coefficients at the between level, and recent research has recommended the use of latent cluster means with the multilevel structural equation modeling framework. However, the latent cluster mean approach may not always be the best choice as it (a) relies on the assumption that the population cluster sizes are close to infinite, (b) requires a relatively large number of clusters, and (c) is currently only implemented in specialized software such as Mplus. In this paper, we show how using empirical Bayes estimates of the cluster means can also lead to consistent estimates of between-level coefficients, and illustrate how the empirical Bayes estimate can incorporate finite population corrections when information on population cluster sizes is available. Through a series of Monte Carlo simulation studies, we show that the empirical Bayes cluster-mean approach performs similarly to the latent cluster mean approach for estimating the between-cluster coefficients in most conditions when the infinite-population assumption holds, and applying the finite population correction provides reasonable point and interval estimates when the population is finite. The performance of EBM can be further improved with restricted maximum likelihood estimation and likelihood-based confidence intervals. We also provide an R function that implements the empirical Bayes cluster-mean approach, and illustrate it using data from the classic High School and Beyond Study. [ABSTRACT FROM AUTHOR]

This study evaluated measurement invariance across males and females on the Neurobehavioral Symptom Inventory (NSI) in U.S. military veterans enrolled in the VA Million Veteran Program. Participants (N = 17,059; males: n = 15,450; females: n = 1,609) included Veterans who took part in the VA Traumatic Brain Injury (TBI) Screening and Evaluation Program and completed the NSI. Multiple-group confirmatory factor analyses investigated measurement invariance of the NSI 4-factor model. The configural (comparative fit index [CFI] = 0.948, root mean square error of approximation [RMSEA] = 0.060) and metric (CFI = 0.948, RMSEA = 0.058) invariance models showed acceptable fit. There was a minor violation of scalar invariance (Δχ2 = 232.50, p <.001); however, the degree of noninvariance was mild (ΔCFI = −0.002, Δ RMSEA = 0. 000). Our results demonstrate measurement invariance across sex, suggesting that the NSI 4-factor model can be used to accurately assess symptoms in males and females following TBI. Findings highlight the importance of considering validity of measurement across study groups to increase confidence that a measure is interpreted similarly by respondents from different subgroups. [ABSTRACT FROM AUTHOR]

Thyroid cancer incidence increased over 200% from 1992 to 2018, whereas mortality rates had not increased proportionately. The increased incidence has been attributed primarily to the detection of subclinical disease, raising important questions related to thyroid cancer control. We developed the Papillary Thyroid Carcinoma Microsimulation model (PATCAM) to answer them, including the impact of overdiagnosis on thyroid cancer incidence. PATCAM simulates individuals from age 15 until death in birth cohorts starting from 1975 using 4 inter-related components, including natural history, detection, post-diagnosis, and other-cause mortality. PATCAM was built using high-quality data and calibrated against observed age-, sex-, and stage-specific incidence in the United States as reported by the Surveillance, Epidemiology, and End Results database. PATCAM was validated against US thyroid cancer mortality and 3 active surveillance studies, including the largest and longest running thyroid cancer active surveillance cohort in the world (from Japan) and 2 from the United States. PATCAM successfully replicated age- and stage-specific papillary thyroid cancers (PTC) incidence and mean tumor size at diagnosis and PTC mortality in the United States between 1975 and 2015. PATCAM accurately predicted the proportion of tumors that grew more than 3 mm and 5 mm in 5 years and 10 years, aligning with the 95% confidence intervals of the reported rates from active surveillance studies in most cases. PATCAM successfully reproduced observed US thyroid cancer incidence and mortality over time and was externally validated. PATCAM can be used to identify factors that influence the detection of subclinical PTCs. • This study used high-quality data sources and rigorous calibration to develop, to our knowledge, the first cross-population microsimulation model to replicate thyroid cancer epidemiology in the United States over time. • This study demonstrated the use of a stakeholder advisory board comprising patients, providers, policymakers, and researchers in building an epidemiologic microsimulation model. • This study successfully explained the drastic increase in the incidence of thyroid cancer since the 1990s through modeling of changing diagnostic pathways over time. [ABSTRACT FROM AUTHOR]

The Kuqa Mountain front area of Tarim is rich in oil and gas resources, but the development of ultra-deep rock salt formation is common, leading to a narrow safety density window and significant impacts on engineering operation safety and wellbore quality, such as overflow and leakage. Managed pressure drilling (MPD) is an effective solution to the problem of drilling in narrow density windows, and a precise wellbore pressure calculation method is essential to ensure the reasonable determination of MPD parameters. Conventional wellbore pressure models treat fluid properties as constant and do not consider the impact of ultra-deep rock salt formation on wellbore pressure calculation, leading to incomplete calculation accuracy that cannot fully meet engineering requirements. In this paper, an improved wellbore temperature field model coupled with the rock salt formation is established. Additionally, rheological experiments on drilling fluids used in the field are conducted and a prediction model for shear stress and density is established based on the varying degrees of temperature and pressure influences. Based on the temperature field of the wellbore and the rheological experimental, a wellbore pressure prediction model is established, and field application is conducted in Keshen Well X. By comparing the measured values, the overall error does not exceed 5%. Compared with neighboring blocks, the rate of penetration has been increased by 73.8%, and the drilling efficiency has been significantly improved. The use of wellbore pressure calculation method, which is studied in this paper, has facilitated efficient operations in drilling ultra-deep rock salt formation. [ABSTRACT FROM AUTHOR]

Under a linear-polarized AC electric field, a spheroid suspended in fluids typically aligns one of its axes with the field. The time-averaged torque model is widely used to predict the orientation of the spheroid with respect to the field. Different from the AC case, the dynamical behaviors including stable orientation, stable spinning, and the limit cycle of spheroids under the DC electric field are much richer. An inconsistency exists between the two cases, and a criterion for the validity of the time-average torque model is also missing. In this article, the dynamic model for the DC electric field was adapted to its AC counterpart and the full dynamics of spheroids under the AC field were studied. We bridged the DC and AC dynamics of spheroidal particles and widened the frequency range for applying the time-averaged torque model. It was found that the phase diagram at the DC limit is a very instructive guiding map for predicting the dynamical behavior at the AC field and ωτη ∼ 1 (ω: angular frequency of the electric field, τη: characteristic time of particle rotation) appears to be a universal criterion for the time-averaged model to be effective. The flipping of particle orientation was explained with bifurcations of the periodic solutions and the irregular dynamics at low frequencies were uncovered with the Poincaré map and the power spectrum analysis. Our study sheds light on even richer dynamical behaviors of the particles under the AC electric field and may help realize other unconventional dynamical behaviors of particles in the future. [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]

This article examines the emergence and development of playgrounds in the most significant treaty ports of China — Guangzhou, Shanghai, and Tianjin — during the first half of the 20th century. It contributes to understanding the unique evolution of playgrounds and children's play in modern China by exploring the interaction between imported ideas from the endogenous development of playgrounds in Europe and America and new ideas on children's development with local circumstances and social ideas. It reveals that initially, children's play was mainly adult-oriented, but after certain ideas on safety, education, and physical development were introduced, playgrounds were constructed. Later, physical constructions and management methods were added until they developed into particular landscapes that were constructed to meet the perceived physical, social, and mental needs of children. During this process, urban citizens changed their ideology on play, viewing playgrounds as a tool for training children to conform to society. [ABSTRACT FROM AUTHOR]

Grouting is a complex process involving interactions of slurry and water phase. The viscosity of slurry is of spatiotemporal variation and significant loss of slurry was observed in grouting processes. These phenomena are difficult to address in numerical models. Therefore, a numerical method of grouting considering the loss of slurry is developed in this work. Firstly, by solving the transport time of slurry, the spatiotemporal evolution of slurry viscosity is implemented. Secondly, by assuming that the water phase and slurry phase is miscible, a diffusion term is added to the transport equation of the slurry volume fraction and the dispersed phase interface of slurry and water is realized. In addition, the simulation result of the new method is compared with our precious experiment data. We show that better agreement is obtained in the variation of grouting pressure, flow rate and slurry loss rate. The effectiveness of the method is verified. Finally, the applicability of our method in engineering scale is verified at engineering scales. The results show that this method could address the interphase miscibility of slurry and water in grouting processes, and it can provide a certain theoretical reference for grouting practice in engineering. Highlights: A new numerical model considering interphase miscibility is developed to address the slurry-water interaction in grouting processes. The proposed algorithm is experimentally verified, showing good agreement in the computation of grouting parameters. By applying the proposed algorithm, the grouting process of karst conduits is studied. [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) track forecasting has been considerably improved in recent decades, while TC intensity forecasting remain challenging. In this study, orthogonal nonlinear forcing singular vectors (O‐NFSVs) for emulating the impact of model uncertainties are used to conduct TC ensemble forecasting experiments with the Weather Research and Forecasting (WRF) model, with a focus on improving TC intensity forecasting skill. The O‐NFSVs approach is compared with the traditional stochastic kinetic‐energy backscatter (SKEB) and stochastically perturbed parametrization tendency (SPPT) schemes. The results demonstrate that the O‐NFSVs ensembles generally provide a better representation of the model uncertainties affecting TC intensification, with much better deterministic and probabilistic skills. These results also extend to the ability to forecast TC track, although the perturbations have not been optimized for that specific purpose. The O‐NFSVs are therefore appropriate perturbation structures for describing the uncertainties of the TC intensity and track forecasting and are also favourable for recognizing the rapid intensification process. [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]

In order to investigate the slurry flow behavior, our newly proposed numerical method is applied to simulate the fracture grouting with flowing water condition. First, by numerical validation and experiment comparison, the advantages of this method in computation efficiency and accuracy are shown. Second, the initial velocity of water and slurry properties at different levels are selected as the influencing factors, the water reduction effect, grouting pressure, and slurry deposition behavior in different cases are investigated, and the variation characteristics of flow field and slurry outflow are analyzed. The simulation results show that within the range of slurry properties and flow velocity given in this paper, cement slurry cannot seal the water inflow. Instead, quick setting slurry with different material ratios can effectively seal the fracture. The sealing efficiency is more sensitive to the initial flow rate than the slurry property. When the groundwater flow rate is low, the effect of slurry proportion on sealing can be ignored. Meanwhile, slurry properties have more influence on the final grouting pressure. There is an obvious surge in grouting pressure after sealing, which can be used as a criterion for fracture sealing. [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]

The issue of water blocking by grouting in coastal areas has engendered the need for a novel numerical simulation method for grouting with a flowing water under tidal action, two-fluid tracking (TFT). This paper proposes such a method. First, based on the material derivative, the transport model of the residence time of injected slurry was derived. In addition, the residence time of injected slurry microgroups at any grouting time was obtained by solving the transport model. Further, the numerical characterization of slurry viscosity during grouting in flowing water was realized by introducing a time-varying viscosity function obtained from previous experiments. Then, based on the generalized tidal action model, the diffusion behavior and blocking mechanism of slurry under tidal effects were studied. The results show that: (1) under tidal action, the water velocity fluctuates and decreases, whereas the grouting pressure fluctuates and increases; (2) at the early stage of grouting, the diffusion pattern of slurry appears as a droplet, and the tailing phenomenon becomes more serious with an increase of tidal intensity; with the progress of grouting, the diffusion pattern gradually changes to U-shaped or elliptical; (3) the strong tidal action will reduce the retention rate of slurry, which is not conducive to the grouting blocking. The research results have been applied to the grouting treatment of a China Resources Cement (Hepu) limestone mine. This research can provide some useful guidance for grouting treatment engineering of water inflow in coastal areas. [ABSTRACT FROM AUTHOR]

Purpose: Mechanical chest compression has been shown to be equivalent to manual chest compression in providing survival benefits to patients experiencing cardiac arrest. There has been a growing need for a contemporary review of iatrogenic injuries caused by mechanical in comparison with manual chest compression. Our study aims to analyze the studies that document significant life-threatening iatrogenic injuries caused by mechanical and manual chest compression. Methods: A systematic review of PubMed and Embase was performed according to Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. All studies published after January 1st, 2000 were reviewed using inclusion/exclusion criteria and completed by May 2020. A total of 7202 patients enrolled in 15 studies were included in our meta-analysis. Results: Significant life-threatening iatrogenic injuries had higher odds of occurring when mechanical chest compression was used compared to manual chest compression, especially for hemothorax and liver lacerations. Mechanical chest compression involves consistently deeper compression depths compared to manual chest compression, potentially resulting in more injuries. In the mechanical chest compression cohort, chest wall fractures had the highest incidence rate (55.7%), followed by sternal fracture (28.3%), lung injuries (3.7%), liver (1.0%), and diaphragm (.2%) lacerations. Conclusions: Mechanical chest compression was associated with more iatrogenic injuries as compared to manual chest compression. Further research is needed to define the appropriate application of mechanical in comparison with manual chest compression in different scenarios. Levels of provider training, different mechanical chest compression device types, patient demographics, and compression duration/depth may all play roles in influencing outcomes. [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]

We present three studies to demonstrate the important role of institutional trust in promoting prosocial behavior in China. In study 1, we used a Chinese national survey and found that institutional trust significantly predicted people's donation and volunteer activities. In study 2, we experimentally examined the effects of institutional trust in public goods games. Participants allocated more money to public accounts when a positive impression of institutions was implicitly activated than when a negative impression or no concepts were activated. In study 3, we tested the effects of institutional trust in a field experiment with a "pay what you want" strategy. In a charity bazaar, participants who received leaflets that implicitly activated institutional concepts paid more money. [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]

With the growth of green awareness and the national support, the consumer groups of green agricultural products will popularize the vast majority of the people in the future, and green agricultural products will usher in a considerable potential market. The rapid development of agricultural product e-commerce is the inevitable modern Internet information technology. Big data has collected and converted into valuable information. This article combines GIS business intelligence analysis to help planters make the best planting decisions. This article designs an overall plan of data mining and analysis technology through the demand analysis of the precision marketing of agricultural products, and conduct effective data collection. Precise marketing strategies are formulated for different times, locations, quantities, varieties, etc., not only to meet customer needs, to comply with the market, but also to effectively prevent slow sales and other phenomena, so as to maximize the benefits of growers. This article uses big data analysis and processing technology to identify consumers across the country without making mistakes, grasp their characteristics, preferences and potential consumer demands, and quickly calculate and process to obtain precise segmentation, precise positioning and target markets for consumers. [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]

There has been tremendous growth in research on measurement invariance over the past two decades. However, given that psychological tests are commonly used for making classification decisions such as personnel selections or diagnoses, surprisingly, there has been little research on how noninvariance impacts classification accuracy. Millsap and Kwok previously proposed a selection accuracy framework for that purpose, which has been recently extended to categorical data. Their framework, however, only deals with classification using a unidimensional test. In contrast, classification in practice usually involves multidimensional tests (e.g., personality) or multiple tests, with different weights assigned to each dimension. In the current paper, we extend Millsap and Kwok's framework for examining the impact of noninvariance to a multidimensional test on classification. We also provide an R script for the proposed method and illustrate it with a personnel selection example using data from a published report featuring a five-factor personality inventory. [ABSTRACT FROM AUTHOR]

Topological relationship identification of geological boundaries greatly affects 3D geological modeling efficiency. However, due to the complex spatial distribution and unstructured data architecture of geological boundaries, the current topological identification still mainly depends on the manual operation and interpretation, which is time-consuming and labor-intensive. And geologists' judgments are based on knowledge and experience that are challenging to replicate through conventional algorithmic approaches. To address these challenges, a graph neural network-based geological boundary topological relationships automatic identification method is proposed. Based on graph theory, we conceptualize geological boundaries and their topological relationships as a graph transforming the identification task into an edge prediction problem within this topological graph. We employ the variational graph auto-encoder (VGAE) model to predict unknown edges in the topological graph, enabling automatic identification of geological boundary topological relationships. A geological information transformation method is proposed to extract and encode the geological boundaries' features as inputs for VGAE. The proposed method is verified in an engineering case study. The results reveal that this method can efficiently and accurately analyze the geological boundary topological relationships. Moreover, it can greatly reduce the manual workload, requiring only 30% of the manual effort to obtain the geological boundary topological relationships, while achieving an average prediction accuracy of approximately 95%. • Construct geological boundary topological relationship graphs based on graph theory. • Convert topological analysis into edge prediction in graphs for automation. • Use variational graph auto-encoder to predict unknown edges in topological graphs. • Suggest a method for geological boundary feature extraction and encoding. [ABSTRACT FROM AUTHOR]

Ship collision accidents occur frequently and developing rapid prediction methods for structural crashworthiness analysis is of crucial importance in the design phase. This paper proposed a new analytical method to rapidly evaluate side structural responses impacted by a rigid raked bow in right-angle ship collisions with large indentation. Numerical simulations were carried out to help identify and understand the mechanisms of structural deformation of primary structural members. The side structure is divided into different key components and a new analytical model for evaluating the hull shell plating and stiffeners under large indentation subjected to lateral impact was developed. The model considered the shell plating deformation in three different phases, denting, ruptured and tearing phase. Different formulas were derived to cover the analysis from minor deflection to large indentation. Combined with other existing formulas for stiffened decks under in-plane loads, an integrated method was proposed to predict the total resistance and energy dissipation of the side structure. The newly developed method innovatively considered the coupling effects and interactions between various structural members in the collision analysis by dynamically correcting some parameters theoretically. The newly developed method was verified against numerical simulations of full-scale ship collisions through five typical scenarios and good accuracy was achieved. The newly developed method is valuable for use in the preliminary design phase, especially for severe collision scenarios. • New analytical solution is proposed for plate tearing under lateral impact by a raked bow. • New analytical solution for stiffeners during plate tearing was proposed. • The method considers interaction effects from structural components during collision. • The method was suitable for sever right-angle collision with large indentation. [ABSTRACT FROM AUTHOR]

Better control of the channel is crucial to improve the performance of existing electron devices. A phototransistor with a specifically designed dual‐gate structure based on a vertical van der Waals heterojunction of WS2 and MoS2 is proposed. The top gate modulates the carrier transport in WS2 at the top of the heterojunction, whereas the back gate can simultaneously control the carrier transport in both MoS2 and WS2 regions located on either side of the heterojunction. Therefore, the rectification ratio of the WS2/MoS2 heterojunction can be modified from approximately 1 to above 104. A very low subthreshold swing of 47 mV dec−1 is obtained. Optoelectronic characterization shows that the responsivity and detectivity are as high as 167.8 A W−1 and 5.8 × 1012 Jones at 532 nm, respectively, which are attributed to the combined modulation effect of the WS2/MoS2 heterojunction and additional homojunction in WS2. Moreover, a logic operation between electronic and optical signals can be performed by utilizing only one multiposition controllable gate phototransistor. In addition, the capability of this dual‐gate phototransistor to emulate information transmission in neuromorphic architectures is presented. These results demonstrate the potential of this approach for the development of next‐generation optoelectronic devices. [ABSTRACT FROM AUTHOR]

Objective: Studies showed that a lack of insurance is associated with worse trauma outcomes. We examine insurance status and trauma mortality in a diverse metropolitan city and hypothesize that the higher risk of mortality in uninsured patients is due to insurance status and other factors.Methods: A retrospective analysis of patients admitted to a Level 1 Trauma center for emergent surgery in a diverse metropolitan city from Jan 2016-May 2020 was conducted. Patients of different insurance statuses were analyzed for their injury mechanism and surgical intervention outcomes. Multivariate logistic regression was performed and the results were presented as odds ratio with 95% confidence intervals and P values. Statistical significance was set at P < .05.Results: 738 patients met study criteria. Medicaid patients made up the largest proportions of injury mechanisms: 65.1% of gunshot wound cases, sharp object (41.7%), and falls (32.5%). Private insurance (OR = .13, 95% CI: .05-.35, P = .000), Medicaid (OR = .19, 95% CI: .10-.35, P = .000), Medicare (OR = .65, 95% CI: 0.28-1.51, P = .31), and other insurance (OR = .44, 95% CI 0.22-.87, P = .01) were associated with survival. Uninsured patients had the highest mortality rate resulting from trauma at 32.6% (P < .001), and the lowest mortality rate belonged to the private insurance cohort (6.3%, P < .001). Uninsured patients accounted for 10.5% of gunshot wound cases, 8.5% of motor vehicle accident cases, 25% of sharp object cases, and 6.6% of falls.Conclusion: Being uninsured was independently associated with mortality, while having insurance improved outcomes. Underlying mechanisms should be further elucidated to improve health equity and trauma outcomes in diverse patient populations. [ABSTRACT FROM AUTHOR]

The weaker van der Waals force between layers inhibits the interlayer electron migration, which greatly limiting the enhancement of the photocatalytic activity over graphitic carbon nitride (g-C 3 N 4). Herein, the metal-free sulfur-doped 2D/3D van der Waals (vdW) homojunction (2D/3D CNSCN) that containing 2D sulfur-doped g-C 3 N 4 nanosheets (CNS) and 3D g-C 3 N 4 flower-like hierarchical structure (CN) was fabricated. Thanks to the cooperative effect of 2D-3D structural and good compatibility between CNS and CN, an in situ formed 2D/3D vdW homojunction served as the driving force for promoting charge carrier separation and transfer. The optimal photocatalytic H 2 evolution of 2D/3D CNSCN reached up to 2196 μmol h−1g−1, which was 4.1 and 3.2 times higher than that of CN and CNS, respectively. 10 mg of the 2D/3D CNSCN photocatalyst was able to totally remove of rhodamine B (RhB) solution in less than 80 min under the visible light. This study provides new opportunities to construct novel 2D/3D mixed-dimensional vdW homojunction, and broad interest in vdW homojunction research for the applications in energy conversion and environmental protection field. [Display omitted] • 2D/3D mixed-dimensional vdW homojunction of CN is prepared for the first time. • CNSCN has high activity and stability in photocatalytic H 2 evolution and removing RhB. • The optimal photocatalytic H 2 evolution of 2D/3D CNSCN reaches up to 2196 μmol h−1g−1. • CNSCN exhibits ultrahigh charge-carrier separation and transfer efficiency. • A possible photocatalytic mechanism is proposed. [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]

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]

• The influence from stiffener dimensions and directions on the plate tearing resistance cut by a wedge is numerically studied. • A novel analytical method is proposed to predict the cutting resistance of stiffened plate. • Coupling effects from stiffeners and plates are considered by dynamically modifying the plate curling radius in the novel method. • The new method is validated and verified against experimental and numerical results, and a better accuracy is achieved compared with previous formulas. Stiffened panels are widely used in ship and offshore structures and the evaluation of cutting resistance is important for structural safety assessment in ship collision and grounding accidents. This paper presented numerical and analytical analyses for cutting analysis stiffened plates. The numerical simulations were firstly validated against experimental data and the stiffener effects on the cutting resistance were then studied through numerical simulations by changing the stiffener direction and thickness. The longitudinal stiffener was found to influence the resistance from an earlier stage while a much larger peak value of cutting resistance was reached for transversely stiffened plate. Based on the numerical study and review of previous formulas, a new analytical model was proposed to predict the cutting resistance of stiffened plates. The new method established analytical model for longitudinal and transverse stiffeners respectively to capture their dynamic responses, and the coupling effects from them were considered by dynamically updating the curling radius of plate during cutting process. The newly developed method was validated and verified against existing experimental data and the presented numerical results, and very good agreement was achieved. The newly proposed method was also compared with existing formulas to investigate the adaptivity and it is found that the accuracy is better than previous formulas, which combines with equivalent thickness method, especially when predicting the cutting resistance of transversely stiffened plate. The present study can benefit the structural damage assessment of stiffened decks or bottom plates of ships in real collision and grounding accidents. [ABSTRACT FROM AUTHOR]

Subsea production system occupies an important position in the development of deep-sea resources. As a key part of the subsea production system, the safety and reliability of the pipeline system of the subsea production system is crucially important. In recent years, with the development of artificial intelligence technology, the use of machine learning algorithms for large-scale complex pipeline system to provide a possibility of safety assessment. This paper collects the burst pressure of the pipeline in the experiments and uses various machine learning methods to evaluate and predict. The XGBoost model with the best performance after preliminary selection, and the accuracy of this method is improved through hyperparameter optimization with Bayesian principle. The improved XGBoost model are explained based on the Forward Feature Selection method and SHAP analysis, compared with commonly pipeline industry standards. The results show that the improved XGBoost model can significantly improve the prediction of the burst pressure and can effectively assess the structural integrity and reliability of pipelines. Moreover, the influencing factors of the burst pressure of the pipeline are analysed, and it is concluded that t (thickness of the pipeline), L (length of corrosion) are the two most important factors influencing the pipeline burst pressure. • Different machine learning methods are compared and it is found that the XGboost model has the best predictive performance. • The improved XGboost model is explained based on the Forward Feature Selection method and SHAP analysis. • The improved XGboost model is compared with existing industry standards. [ABSTRACT FROM AUTHOR]

• A novel thermal management technology has been proposed using a surface-modified silicon chip and TSV for packaging 3D ICs. • Transient thermal property measurement system is originally designed using Raman spectroscopy to assess cooling performance. • Cooling performance for each specific surface-modified silicon chip is extracted by characterized time constant value τ. A novel surface-modified silicon-based thermal management technology has been proposed for 3D IC architecture in this study. 2 × 2 cm2 double sides polished silicon chips' surface with micro-fin (MF) and micro-pin fin (MPF) structures have been achieved by applying silicon microfabrication technology of deep reactive ion etching, which is applicable to the interlayer of 3D IC packaging technology. By integrating a mini wind tunnel with Raman spectrometer, the transient thermal property measurement system is originally designed to evaluate the cooling capability of the surface-modified silicon interlayer. Finite Element Analysis was involved to confirm this view by taking fluid dynamics and heat transfer into account. The sample with 100 × 100 µm2 MPF structure expresses the appropriate exponential decay time constant τ (with unit of 1), which is 4.71 and 8.53 under cooling and heating measurement conditions, respectively. This also proved that the combination of Raman thermometry with forced gas flow could be a relevant measurement tool for transient thermal property. [ABSTRACT FROM AUTHOR]

Multilevel modeling (MLM) is commonly used in psychological research to model clustered data. However, data in applied research usually violate one of the essential assumptions of MLM—homogeneity of variance. While the fixed-effect estimates produced by the maximum likelihood method remain unbiased, the standard errors for the fixed effects are misestimated, resulting in inaccurate inferences and inflated or deflated type I error rates. To correct the bias in fixed effects standard errors and provide valid inferences, small-sample corrections such as the Kenward-Roger (KR) adjustment and the adjusted cluster-robust standard errors (CR-SEs) with the Satterthwaite approximation for t tests have been used. The current study compares KR with random slope (RS) models and the adjusted CR-SEs with ordinary least squares (OLS), random intercept (RI) and RS models to analyze small, heteroscedastic, clustered data using a Monte Carlo simulation. Results show the KR procedure with RS models has large biases and inflated type I error rates for between-cluster effects in the presence of level 2 heteroscedasticity. In contrast, the adjusted CR-SEs generally yield results with acceptable biases and maintain type I error rates close to the nominal level for all examined models. Thus, when the interest is only in within-cluster effect, any model with the adjusted CR-SEs could be used. However, when the interest is to make accurate inferences of the between-cluster effect, researchers should use the adjusted CR-SEs with RS to have higher power and guard against unmodeled heterogeneity. We reanalyzed an example in Snijders & Bosker (2012) to demonstrate the use of the adjusted CR-SEs with different models. [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]

Carbon nitride with tailored atomic structure has recently attracted considerable attention, however, the fast carrier recombination and incomplete visible light absorption great limited the practical application. Here, novel intramolecular synergetic effects of in-plane and interlayer dual regulation on sandworm-like graphitic carbon nitride (CN-NiC) was constructed for promoting the photocatalytic performance. Benefiting from the visible light band tail resulted from the extended π-conjugated system from carbon bridged doping, CN-NiC possesses expanded visible absorption range, and reduces the bandgap. More importantly, the Ni intercalation acts as an electron transport channel between the interlayer to reinforce the transfer of charge carriers. With this unique molecular structure, the optimized CN-NiC2 photocatalyst exhibits a high photocatalytic performance with 23.9 and 11.1-fold improvement as much as that of CN for H 2 evolution and RhB degradation, respectively. In addition, the photocatalytic performance remains stable after several times cycles. This research provides an idea to obtain atomic structure tailored CN-based photocatalyst for high efficiency photocatalytic application. [Display omitted] • In-plane C doping and interlayer Ni modified sandworm-like carbon nitride were synthesized. • The synergetic effects improve the light absorption and accelerate carrier separation. • CN-NiC2 shows impressive photocatalytic activity for H 2 evolution and removing dye. [ABSTRACT FROM AUTHOR]

A CP based CoFe electrocatalyst with a simple and quick technique has been invested in our study. This amorphous CoFe/CP hybrid exhibits commendable electrocatalytic performance in the OER process, requiring only overpotential of 278 mV to achieve 10 mAm−2 in 1.0 M KOH solution and a lower Tafel slope of 54.58 mV dec-1. Because it enjoys peculiar multistage graded nano structure and Fe, Co co-incorporation, which can modify the surface structure, creating fertile ground for the specific surface area of CP and efficiency of electronic transmission. [Display omitted] • CoFe/CP has successfully grown on 3D nanoarray carbon paper (CP) containing non-precious metals. • The multistage graded nano structure can create fertile ground for the specific surface area of CP and efficiency of electronic transmission. • CoFe/CP with a nanosheet-like structure exhibits amorphous phase. • CoFe/CP-9 shows the corresponding overpotential at 10 mA•cm−2 is 278 mV and remarkable stability. Tremendous attention has been paid on high efficiency, readily available and stability of electrocatalysts. Herein, we ingenious report a one-step reaction strategy synthesis of CoFe/CP grown on three-dimensional (3D) nanoarray carbon paper (CP) containing non-precious metals for oxygen evolution reaction (OER) with low-cost and unique hierarchical porous structure. This amorphous CoFe/CP hybrid exhibits commendable electrocatalytic performance in the OER process, requiring only overpotential of 278 mV to achieve 10 mAcm−2 in 1.0 M KOH solution and a lower Tafel slope of 49.12 mVdec-1. In addition, this sample shows a long-term durability even at 200 mAcm−2 without obvious decay, which attributes to peculiar multistage graded nano structure and the change of composition at the interface of CP. Therefore, the remarkable OER activity can provide a new strategy to construct potential candidates, which will replace the state-of-the-art precious metals for OER in the future. [ABSTRACT FROM AUTHOR]

Background and purpose: There is an ongoing debate about whether a direct aspiration first-pass technique (ADAPT) or stent retriever should be used as the first-pass mechanical thrombectomy device for patients with acute ischemic stroke (AIS). This meta-analysis aimed to compare the safety and efficacy of ADAPT versus stent retriever in patients with AIS. Methods: Structured searches on the PubMed, Embase, and Cochrane Library databases were conducted through July 2020. The primary outcomes of this study were: successful and complete recanalization; excellent and favorable outcomes; all-cause mortality at 90 days; and symptomatic intracerebral hemorrhage (sICH). The secondary outcomes of this study were: successful recanalization by primary chosen device; additional therapy; occurrence of emboli in a new territory; hemorrhagic complication; hemorrhagic infarction; parenchymatous hematoma; and subarachnoid hemorrhage. The odds ratios (ORs) with 95% confidence intervals (CIs) of the primary and secondary outcomes were calculated using a random-effects model. I2 statistics were used to assess the heterogeneity for each outcome among the included studies. Results: Finally, 20 studies with a total of 6311 patients were included in our meta-analysis. There were no significant differences between the ADAPT group and the stent retriever group of the primary and secondary outcomes except additional therapy. Our pooled results indicated that patients in the ADAPT group needed more additional therapy than those in the stent retriever group (OR 2.24, 95% CI 1.41–3.57). Conclusion: In conclusion, our meta-analysis showed similar clinical outcomes of ADAPT and stent retriever. However, patients in the ADAPT group had higher additional therapy rates than those in the stent retriever group. Due to several inevitable limitations of this meta-analysis, more large-scale randomized controlled trials are required to further investigate this topic. [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]

A transnational flow of capital exchange during the 19th and early 20th centuries brought planning ideas and modernity into China. Since European countries and America used violence to place China into a colonial world and its forms of power-knowledge, the existing works too often focus on the impact of the 'west', treating the Chinese as passive recipients who responded to 'western' transnational planning ideas, while neglecting the transnational flow of Intra-Asia. By exploring the formation of urbanism in Hebei New Area in Tianjin, this article reveals that the Chinese did not allow themselves to be dictated to by the planning ideas emanating from the west. Instead, they both sought the most suitable ideas based on their local situations and actively imported planning ideas from the east – Japan. The authorities in Tianjin sent officials to Japan to draw upon Japanese industrial and commercial planning models to set up their own organizational framework, urban built environments, and operational management. Consequently, they incorporated planning ideas from the 'east' to re-organize the daily life of the masses and modernize their city. These ideas were juxtaposed with ideas from the 'west' to shape the urbanism of Tianjin. [ABSTRACT FROM AUTHOR]

Special flask-shaped Au grating-Ge nanowire arrays are used to improve the performance of a Ge photodetector in the infrared optical communication band. The responsivity of the device with alternate Au grating-Ge nanowire arrays reaches as high as 0.75 and 0.62 A/W at 1310 and 1550 nm, respectively, indicating a nearly 100% increment compared to a device without a grating structure. This enhancement is attributed to the excitation of the surface plasmon polaritons, which simultaneously enhance the inter-band transition absorption and the internal photoemission of carriers. Moreover, the photoresponsivity of the dual-band plasmon-enhanced device is remarkably asymmetrical with regard to the voltage polarity, and the asymmetric ratios are about 4:1 and 3:1 at 1310 and 1550 nm, respectively. Band energy theory indicates that this bias-dependent responsivity originates from the asymmetrical distribution of hot electrons between the two electrodes and the mobility difference between electrons and holes in Ge. These results provide a valuable guideline for achieving a high performance dual-band near infrared photodetector, and the results demonstrate the potential of this approach for developing next-generation 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]