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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]

• 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]

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]

Purpose: Sequencing potentially causal and susceptible genes and genome-wide association studies in samples from Parkinson's disease (PD) patients has revealed several related loci. The genes for synaptosome-associated protein of 25 kDa (SNAP25), histamine-N-methyltransferase (HNMT), FCH and double SH3 domains 1 (FCHSD1) and dopamine β-hydroxylase (DBH) are candidate loci and have not been studied in a northern Chinese population. We explored the genetic distribution of four single-nucleotide polymorphisms (rs3746544, rs11558538, rs456998, rs129882) located on SNAP25, HNMT, FCHSD1 and DBH, respectively. Patients and Methods: A total of 330 patients with sporadic PD and 332 healthy controls (HCs) were recruited from a northern Chinese population. Polymerase chain reaction restriction fragment length polymorphism was used to genotype these four SNPs. Results: After statistical analyses and correction of the genotyping results, the mutant-allele T in rs456998 of FCHSD1 was found to be significantly related to reducing the PD risk (P = 0.029, OR = 0.754, 95% CI = 0.586– 0.971, power = 0.591). However, rs3746544, rs11558538, and rs129882 did not show an association with PD. Conclusion: FCHSD1 rs456998 may have a protective role in PD in a northern Chinese population, but more studies are needed to support this suggestion. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the disease burden of age‐related macular degeneration (AMD) and to evaluate the risk factors of disability‐adjusted life years (DALY) caused by AMD. Methods: Country‐specific DALY number, rate and age‐standardized rate of AMD were acquired from the Global Burden of Disease Study 2017 database. The Socio‐demographic Index (SDI), Human Development Index (HDI), Inequality‐adjusted Human Development Index (IA‐HDI) and other related data were obtained from published data or shared databases. Regression analysis was conducted to evaluate the correlations between the potential risk factors and the age‐standardized DALY rate of AMD. Results: The DALY number doubled from 1990 to 2017, and DALY rate increased from 4.73 (95% CI: 3.19–6.54) to 6.95 (95% CI: 4.76–9.54). However, change was small after standardizing. Females tended to have severer burden. Disability‐adjusted life years (DALY) rates were correlated to annual PM2.5 concentration, gross domestic product (GDP) per capita, population with at least some secondary education (secondary education), glaucoma prevalence and gross national income (GNI) per capita. In SDI model, glaucoma, GDP, healthcare access and quality index (HAQ) and secondary education were associated with disease burden (p < 0.001). In IA‐HDI model, cataract, glaucoma, PM2.5, GDP and secondary education were correlated to DALY rates (p < 0.001). In model included four components of HDI, glaucoma, PM2.5, GDP, secondary education, expected years of schooling and life expectancy at birth were associated (p < 0.001). Conclusion: Being female, older age, poor socioeconomic status and less educated are associated with a heavier disease burden of AMD. These findings would provide a basic understanding for policy making on AMD prevention and treatment. [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]

Prunus mume (also known as Mei) is an important ornamental plant that is popular with Asians. The weeping trait in P. mume has attracted the attention of researchers for its high ornamental value. However, the formation of the weeping trait of woody plants is a complex process and the molecular basis of weeping stem development is unclear. Here, the morphological and histochemical characteristics and transcriptome profiles of upright and weeping stems from P. mume were studied. Significant alterations in the histochemical characteristics of upright and weeping stems were observed, and the absence of phloem fibres and less xylem in weeping stems might be responsible for their inability to resist gravity and to grow downward. Transcriptome analysis showed that differentially expressed genes (DEGs) were enriched in phenylpropanoid biosynthesis and phytohormone signal transduction pathways. To investigate the differential responses to hormones, upright and weeping stems were treated with IAA (auxin) and GA3 (gibberellin A3), respectively, and the results revealed that weeping stems had a weaker IAA response ability and reduced upward bending angles than upright stems. On the contrary, weeping stems had increased upward bending angles than upright stems with GA3 treatment. Compared to upright stems, interestingly, DEGs associated with diterpenoid biosynthesis and phenylpropanoid biosynthesis were significantly enriched after being treated with IAA, and expression levels of genes associated with phenylpropanoid biosynthesis, ABC transporters, glycosylphosphatidylinositol (GPI)—anchor biosynthesis were altered after being treated with GA3 in weeping stems. Those results reveal that multiple molecular mechanisms regulate the formation of weeping trait in P. mume, which lays a theoretical foundation for the cultivation of new varieties. [ABSTRACT FROM AUTHOR]

Background: Ulcerative colitis (UC) is a chronic and recurrent disease without satisfactory treatment strategies. Dental pulp stem cell (DPSC) transplantation has been proposed as a potential therapy for UC. This study aimed to investigate the therapeutic effects of the rat hepatocyte growth factor (HGF) gene transduced into DPSCs for UC. Methods: The therapeutic effects of HGF-DPSCs transplanted intravenously into a rat model of UC induced by 5% dextran sulphate sodium (DSS) were compared with the other treatment groups (LV-HGF group, DPSCs group and GFP-DPSCs group). Immunofluorescence and immunohistochemistry were used to observe the localization and proliferation of HGF-DPSCs at the site of colon injury. The expression levels of inflammatory factors were detected by real-time quantitative PCR (RT-PCR) and western blotting. The oxidative stress markers were detected by ELISA. DAI scores and body weight changes were used to macroscopically evaluate the treatment of rats in each group. Results: Immunofluorescence and immunohistochemistry assays showed that HGF-DPSCs homed to colon injury sites and colocalized with intestinal stem cell (ISC) markers (Bmi1, Musashi1 and Sox9) and significantly promoted protein expression (Bmi1, Musashi1, Sox9 and PCNA). Anti-inflammatory cytokine (TGF-β and IL-10) expression was the highest in the HGF-DPSCs group compared with the other treatment groups, while the expression of pro-inflammatory cytokines (TNF-α and INF-γ) was the lowest. Additionally, the oxidative stress response results showed that malondialdehyde (MDA) and myeloperoxidase (MPO) expression decreased while superoxide dismutase (SOD) expression increased, especially in the HGF-DPSCs group. The DAI scores showed a downward trend with time in the five treatment groups, whereas body weight increased, and the changes were most prominent in the HGF-DPSCs group. Conclusions: The study indicated that HGF-DPSCs can alleviate injuries to the intestinal mucosa by transdifferentiating into ISC-like cells, promoting ISC-like cell proliferation, suppressing inflammatory responses and reducing oxidative stress damage, which provides new ideas for the clinical treatment of UC. [ABSTRACT FROM AUTHOR]

In this article, we present a novel nonlinear vector network analyzer (NVNA) setup for generating and measuring digitally modulated signals at millimeter-wave test bands. The first difference between this setup and commercial NVNAs is the use of a user-defined multisine signal as the phase reference, in order to enable more precise synchronization and denser spectral grid. To achieve this, a single 12.5-GHz microwave source is used for generating both the digitally modulated test signal and the phase reference, which not only offers the clock to the arbitrary waveform generator for user-defined intermediate frequency (IF) waveform generation but also provides the local oscillator drive after frequency multiplication. The second novelty of this work is the use of pulsed-radio frequency (RF) signals for NVNA phase calibration. By replacing the digitally modulated IF waveform with pulsed-RF signals, tone-by-tone phase calibration on dense spectral grids can be easily achieved under the same synchronization scheme. The validity of the proposed NVNA setup (as well as its simplified modification) and the phase calibration method is verified at the fifth-generation (5G)-oriented millimeter-wave bands of 28, 39, 43, and 70 GHz in this work, where the EVM measurements of 64-QAM test signals with a wide range of symbol rates from 0.1 to 1.5625 GSymbol/s are demonstrated reachable in practice. [ABSTRACT FROM AUTHOR]

Medium-frequency (mid-frequency) vibration analysis of complex structures plays an important role in automotive, aerospace, mechanical, and civil engineering. Flexible beam structures modeled by the classical Euler–Bernoulli beam theory have been widely used in various engineering problems. A kinematic hypothesis made in the Euler–Bernoulli beam theory is that the plane sections of a beam normal to its neutral axis remain planes after the beam experiences bending deformation, which neglects shear deformation. However, previous investigations found out that the shear deformation of a beam (even with a large slenderness ratio) becomes noticeable in high-frequency vibrations. The Timoshenko beam theory, which describes both bending deformation and shear deformation, would naturally be more suitable for medium-frequency vibration analysis. Nevertheless, vibrations of Timoshenko beam structures in a medium frequency region have not been well studied in the literature. This paper presents a new method for mid-frequency vibration analysis of two-dimensional Timoshenko beam structures. The proposed method, which is called the augmented Distributed Transfer Function Method (DTFM), models a Timoshenko beam structure by a spatial state-space formulation in the s -domain. The augmented DTFM determines the frequency response of a beam structure in an exact and analytical form, in any frequency region covering low, middle, or high frequencies. Meanwhile, the proposed method provides the local information of a beam structure, such as displacement, shear deformation, bending moment and shear force at any location, which otherwise would be very difficult with energy-based methods. The medium-frequency analysis by the augmented DTFM is validated in numerical examples, where the efficiency and accuracy of the proposed method is demonstrated. Also, the effects of shear deformation on the dynamic behaviors of a beam structure at medium frequencies are examined through comparison of the Timoshenko beam and Euler–Bernoulli beam theories. [ABSTRACT FROM AUTHOR]

Ge1-x Snx alloy films with Sn contents of 3% and 10% were grown on Si wafers by low-temperature nonequilibrium molecular beam epitaxy. The thermostabilities of the GeSn films and photodetectors containing them were studied. No Sn segregation was observed in Ge0.97Sn0.03 films annealed below 750 °C. Conversely, Sn segregation occurred and Sn nanoparticles formed within the Ge0.90Sn0.10 films annealed above 400 °C. Upon increasing the annealing temperature to 750 °C, Sn particles were thermally driven and segregated on the surface of both Ge0.97Sn0.03 and Ge0.90Sn0.10 films. Photodetectors were fabricated based on the as-grown and annealed Ge0.90Sn0.10 films. Because of the decreased defect content of the Ge0.90Sn0.10 film after annealing, the dark current of the GeSn photodetectors decreased obviously and the responsivity of the devices increased. These results are fundamentally important for the applications of high-performance photodetectors and lasers based on GeSn alloys. [ABSTRACT FROM AUTHOR]

This article presents the evaluation of using pulsed-radio frequency (RF) signals as multitone phase standards for modulated measurements at millimeter-wave (mm-Wave) bands, offering an alternative phase calibration choice for nonlinear vector network analyzers (NVNAs). Based on the NVNA measurements of two pulsed-RF signals generated by square-wave-driven mixers, a high correlation between magnitude and phase errors of unideal pulsed-RF signals is discovered, and an empirical method is developed to accurately estimate the phase errors according to magnitude-only measurements. To confirm its robustness and key preconditions for wide-range applications, theoretical support and explanation to the empirical method is revealed, in which the dominant waveform distortion of an applicable pulsed-RF signal can be decomposed into modulated perturbations with Sinc-like envelopes. The validity of the proposed empirical method, as well as its application for mm-Wave NVNA phase calibration, is verified by both experimental measurements and simulation results, where an estimation error (or phase calibration error) less than ±2° is demonstrated that is reachable in practice. [ABSTRACT FROM AUTHOR]

Although Bayesian Optimization (BO) has been employed for accelerating materials design in computational materials engineering, existing works are restricted to problems with quantitative variables. However, real designs of materials systems involve both qualitative and quantitative design variables representing material compositions, microstructure morphology, and processing conditions. For mixed-variable problems, existing Bayesian Optimization (BO) approaches represent qualitative factors by dummy variables first and then fit a standard Gaussian process (GP) model with numerical variables as the surrogate model. This approach is restrictive theoretically and fails to capture complex correlations between qualitative levels. We present in this paper the integration of a novel latent-variable (LV) approach for mixed-variable GP modeling with the BO framework for materials design. LVGP is a fundamentally different approach that maps qualitative design variables to underlying numerical LV in GP, which has strong physical justification. It provides flexible parameterization and representation of qualitative factors and shows superior modeling accuracy compared to the existing methods. We demonstrate our approach through testing with numerical examples and materials design examples. The chosen materials design examples represent two different scenarios, one on concurrent materials selection and microstructure optimization for optimizing the light absorption of a quasi-random solar cell, and another on combinatorial search of material constitutes for optimal Hybrid Organic-Inorganic Perovskite (HOIP) design. It is found that in all test examples the mapped LVs provide intuitive visualization and substantial insight into the nature and effects of the qualitative factors. Though materials designs are used as examples, the method presented is generic and can be utilized for other mixed variable design optimization problems that involve expensive physics-based simulations. [ABSTRACT FROM AUTHOR]

Due to growing concern for the environment and human health, searching for high-performance lead-free piezoceramics has been a hot topic of scientific and industrial research. Despite the significant progress achieved toward enhancing piezoelectricity, further efforts should be devoted to the synergistic improvement of piezoelectricity and its thermal stability. This study provides new insight into these topics. A new KNN-based lead-free ceramic material is presented, which features a large piezoelectric coefficient (d 33) exceeding 500 pC/N and a high Curie temperature (T c) of  ∼200°C. The superior piezoelectric response strongly relies on the increased composition-induced structural flexibility due to lattice softening and decreased unit cell distortion. In contrast to piezoelectricity anomalies induced via polymorphic transition, this piezoelectricity enhancement is effective within a broad temperature range rather than a specific small range. In particular, a hierarchical domain architecture composed of nano-sized domains along the submicron domains was detected in this material system, which further contributes to the high piezoelectricity. [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]

Precision medicine is currently a topic of great interest in clinical and intervention science.  A key component of precision medicine is that it is evidence-based, that is, data-driven, and consequently there has been tremendous interest in estimation of precision medicine strategies using observational or randomized study data. One way to formalize precision medicine is through a treatment regime, which is a sequence of decision rules, one per stage of clinical intervention, that map up-to-date patient information to a recommended treatment. An optimal treatment regime is defined as maximizing the mean of some cumulative clinical outcome if applied to a population of interest. It is well-known that even under simple generative models an optimal treatment regime can be a highly nonlinear function of patient information. Consequently, a focal point of recent methodological research has been the development of flexible models for estimating optimal treatment regimes. However, in many settings, estimation of an optimal treatment regime is an exploratory analysis intended to generate new hypotheses for subsequent research and not to directly dictate treatment to new patients. In such settings, an estimated treatment regime that is interpretable in a domain context may be of greater value than an unintelligible treatment regime built using "black-box" estimation methods. We propose an estimator of an optimal treatment regime composed of a sequence of decision rules, each expressible as a list of "if-then" statements that can be presented as either a paragraph or as a simple flowchart that is immediately interpretable to domain experts. The discreteness of these lists precludes smooth, that is, gradient-based, methods of estimation and leads to nonstandard asymptotics. Nevertheless, we provide a computationally efficient estimation algorithm, prove consistency of the proposed estimator, and derive rates of convergence. We illustrate the proposed methods using a series of simulation examples and application to data from a sequential clinical trial on bipolar disorder. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

This paper proposes a measurement strategy to remove the random phase contributions of the sweeping local oscillator (LO) from modulated radio frequency phase measurements based on downconversion. To obtain a stable phase spectrum for each run of tone-by-tone sweeping measurement, the LO used for downconversion is coupled out to an extra path and modulated to be a wideband multisine signal. By monitoring the phase change of multisine signal at a specific and fixed frequency point, random LO phase offsets during the frequency sweep can be measured and compensated. In this paper, two experimental test benches with the same core measurement strategy but different architectures are established for method validation. According to the experimental results using test bench one, the phase stability is ±(0.2°–0.4°) at 1.8 GHz for fundamental mixing-based downconversion and ±(0.6°–1°) for harmonic mixing at 6 GHz. Based on test bench two, relative phase deviations of ±(0.8°–1.2°) at 22 GHz for fundamental mixing and ±(2°–3°) at 66 GHz for harmonic mixing are reachable. [ABSTRACT FROM AUTHOR]

To predict the properties of nanocomposites, computational models have demonstrated that the interphase behavior can be expressed using the matrix properties with a modified (shifted) frequency. The amount of the shift necessary for a given sample data set can be determined by achieving the best fit between the predicted curve from a computation model and the experimental data through trial-and-error. However, with the complexity of experimental data and expensive computational costs, a manual process to solve this inverse problem is impractical to handle many experimental data sets. This difficulty hinders investigation of the underlying principles behind nanocomposite interphase. In this work, we present an adaptive optimization approach that accelerates the search for interphase properties in polymer nanocomposite data sets by solving the inverse problem using global optimization. The objective is to minimize the difference between the predicted bulk property of a nanocomposite with that from the experiment data. A Gaussian Process (GP) model is built as a surrogate of the objective function with quantification of prediction uncertainty. An adaptive sampling strategy is applied to effectively navigate the complex search space by iteratively selecting the next sampling point based on an expected improvement function. The surrogate model and the optimal solution evolve until the desired objective is achieved. The approach is tested on both the simulations of dielectric and viscoelastic properties in nanocomposites. Our work provides insight into identifying the interphase properties for polymer nanocomposites using adaptive optimization and demonstrates the potential of data-driven approach for achieving a deeper understanding of the interphase properties and its origins. [ABSTRACT FROM AUTHOR]

Abstract: We propose a novel geological modeling method based on T‐splines for computer‐aided design (CAD) and building information modeling (BIM) systems of geotechnical engineering and perform original research on special T‐splines modeling strategies and the algorithm aiming at depicting structural complexity to develop and introduce the T‐splines technology into engineering geological modeling. A methodology of parametric geological modeling with T‐splines is established, where a topology‐geometry modeling strategy is adopted, the inhomogeneity, arbitrary connectivity and discontinuity of geological structures are quantified and associated with T‐spline surface elements in the topology phase. A representative parametric algorithm called IBALR is presented in the context of dam foundation geological modeling to generate an inhomogeneous local refined T‐mesh with high genus topology which can fit a complex geological layer. The proposed method is flexible and effective in improving geological representation within geotechnical engineering. [ABSTRACT FROM AUTHOR]

The tensile response, the low cycle fatigue (LCF) resistance, and the creep behavior of an aluminum (Al) cast alloy are studied at ambient and elevated temperatures. A non-contact real-time optical extensometer based on the digital image correlation (DIC) is developed to achieve strain measurements without damage to the specimen. The optical extensometer is validated and used to monitor dynamic strains during the mechanical experiments. Results show that Young’s modulus of the cast alloy decreases with the increasing temperature, and the percentage elongation to fracture at 100 °C is the lowest over the temperature range evaluated from 25 °C to 300 °C. In the LCF test, the fatigue strength coefficient decreases, whereas the fatigue strength exponent increases with the rising temperature. The fatigue ductility coefficient and exponent reach maximum values at 100 °C. As expected, the resistance to creep decreases with the increasing temperature and changes from 200 °C to 300 °C. [ABSTRACT FROM AUTHOR]

We investigated the measurement techniques of the nonlinear vector network analyzer (NVNA) test bench, to fully characterize the nonlinear behavior of radio frequency (RF) power amplifiers (PAs) driven by complex modulated signals. In order to extend the baseband measurements, two kinds of NVNA phase reference approaches are developed as alternative solutions, so that the baseband phase measurements can be achieved with those of modulated components at multiharmonic RF bands. In the first approach, a modulated baseband signal is combined with another modulated RF one to become the desired NVNA phase reference. While as an alternative solution, the second phase reference design is based on a “stepped” multisine, which is stepped through the baseband and each harmonic following the NVNA swept measurements, to achieve stable phase measurements. To validate these proposed NVNA test bench designs, an RF PA, driven by a large-signal long-term evolution-like multisine, was tested and compared with digital real-time oscilloscope measurements. [ABSTRACT FROM PUBLISHER]

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]

This paper presents novel nonlinear vector network analyzer (NVNA)-based techniques for characterizing the harmonic and intermodulation nonlinearity of dual-band radio frequency (RF) power amplifiers (PAs). On the one hand, a wideband Schroeder-phase multisine is used to drive a step recovery diode comb generator, so that a novel multiharmonic-band NVNA phase reference on a dense spectral grid is obtained. On the other hand, a novel phase calibration approach is developed to synchronize the NVNA multiband measurements. To validate the NVNA testbed with novel techniques, an RF PA under two typical kinds of dual-band multisine stimulus is tested, where the NVNA measurement is compared with that of an oscilloscope. This paper can be easily adapted for various multiband conditions. [ABSTRACT FROM PUBLISHER]

This paper presents a novel realization of nonlinear vector network analyzer (NVNA) test-bed with a new phase calibration technique, in order to characterize the multiharmonic intermodulation nonlinearity of a radio frequency (RF) power amplifier (PA) under a large-signal modulated input. The NVNA test-bed uses a step recovery diode comb generator as the phase reference, which is driven by a pulsed-RF signal with a high duty cycle of over 99%. Hence all the multiharmonic intermodulation tones of interest can be measured at once. A multisine phase standard provided by a vector signal analyzer is used to calibrate the intermodulation tones at each harmonic on a dense spectral grid. Two harmonic phase standards with different fundamental frequencies are used to synchronize the phase calibration results at different harmonics. The validity of this paper is verified by comparing NVNA measurements with oscilloscope measurements of the same PA under test. This paper can be used to inspect the nonlinearity of RF amplifiers under large-signal modulated excitations in both the frequency and time domains. [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]

( Ba, Ca)( Ti, Zr) O3 lead-free piezoelectric ceramics have been considered to be one of the most potential lead-free alternatives for PZT in the room-temperature range. The stability of the piezoelectric performance during unipolar cycling is investigated in this study. It is found that the unipolar fatigue behavior is similar to soft PZT. Developments of bias field, offset polarization, asymmetry in strain, and dielectric hysteresis loops are observed during bipolar measurements. The changes are mainly contributed to the migration of charge carriers to the grain boundaries driven by the unscreened depolarization field. Redistribution of the accumulated charge carriers by bipolar electric cycling or thermal annealing can significantly recover the unipolar fatigued state. The unipolar strain response stabilized after 1000 cycles at 0.053% for an electric field of 0.6 kV/mm ( d33*= 883 pm/V), which is a good characteristic for actuator applications. [ABSTRACT FROM AUTHOR]

Purpose. To evaluate and compare the accuracy of different intraocular lens (IOL) power calculation formulas for eyes with an axial length (AL) greater than 26.00 mm. Methods. This study reviewed 407 eyes of 219 patients with AL longer than 26.0 mm. The refractive prediction errors of IOL power calculation formulas (SRK/T, Haigis, Holladay, Hoffer Q, and Barrett Universal II) using User Group for Laser Interference Biometry (ULIB) constants were evaluated and compared. Results. One hundred seventy-one eyes were enrolled. The Barrett Universal II formula had the lowest mean absolute error (MAE) and SRK/T and Haigis had similar MAE, and the statistical highest MAE were seen with the Holladay and Hoffer Q formulas. The interquartile range of the Barrett Universal II formula was also the lowest among all the formulas. The Barrett Universal II formulas yielded the highest percentage of eyes within ±1.0 D and ±0.5 D of the target refraction in this study (97.24% and 79.56%, resp.). Conclusions. Barrett Universal II formula produced the lowest predictive error and the least variable predictive error compared with the SRK/T, Haigis, Holladay, and Hoffer Q formulas. For high myopic eyes, the Barrett Universal II formula may be a more suitable choice. [ABSTRACT FROM AUTHOR]

(Ba, Ca)(Ti, Zr)O3 ceramics have been considered as a potential lead-free alternative to commonly used lead-based piezoelectric ceramics due to their high piezoelectric performance at room temperature. In this study, the bipolar fatigue behavior of this material is investigated at room temperature. Two compositions were cycled with a bipolar electric field signal at 10 Hz with a maximum of three times the coercive field for up to approximately 107 cycles. Both investigated compositions exhibited high bipolar fatigue resistance compared to other ceramics reported in the literatures. The high fatigue resistance originates from the lack of mechanical damage and a weak domain wall pinning effect due to their location in the phase transition region. It was also found that pore morphology affected bipolar fatigue behavior. [ABSTRACT FROM AUTHOR]