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Objective: USP14 (Ubiquitin‐specific‐processing protease 14) is a deubiquitinating enzyme with oncogenic effects in oral squamous cell carcinoma (OSCC). This study aims to identify new substrates of USP14 and elucidate their role in modulating cancer stem‐like cells (CSCs) in OSCC. Materials and Methods: Bioinformatics prediction and docking were performed using UbiBrowser 2.0 and HDOCK, respectively. OSCC cell lines and patient‐derived cells were used for experimental validation, employing co‐immunoprecipitation, cycloheximide chase assays, and tumor sphere formation to evaluate the effects of USP14 on SOX2 stability, ubiquitination, and CSC phenotypes. Results: USP14 upregulation was associated with worse overall survival and progression‐free interval in OSCC. USP14 interacted with SOX2 with its ubiquitin carboxyl‐terminal hydrolase domain. USP14 knockdown impaired SOX2 stability by increasing its polyubiquitination. Ectopic overexpression of wild‐type USP14, but not the hydrolase‐deficient‐mutant USP14C114A, enhanced SOX2 stability by reducing polyubiquitination. USP14 knockdown suppressed OSCC cell proliferation, colony formation, and tumor sphere formation in vitro and tumor growth in vivo. However, the reduction of CSC markers following USP14 knockdown was mitigated by overexpressing SOX2. These findings were verified in OSCC patient‐derived CSC cells. Conclusion: This study revealed a USP14‐SOX2 axis regulating the CSC properties of OSCC. [ABSTRACT FROM AUTHOR]

Analyzing the changes in carbon storage in terrestrial ecosystems caused by land use changes is a crucial part of exploring the carbon cycle. In addition, enhancing carbon storage in terrestrial ecosystems is an effective and environmentally friendly measure to sequester anthropogenic carbon emissions, which is significant for achieving carbon neutrality and curbing global climate change. This paper uses land use data and carbon density tables with the InVEST model to obtain a carbon storage distribution map of China. It further applies land use response elasticity coefficients, Theil index multi-stage nested decomposition, and spatial autocorrelation analysis to examine the spatial-temporal patterns, causes of changes, and evolution characteristics of carbon storage in terrestrial ecosystems from 1980 to 2020. The results show that the temporal changes in China's carbon storage generally present an inverted S-curve, with an initial rapid decline followed by a slower decrease. Spatially, it features high levels in the northeast, low levels in the northwest, and a uniform distribution in the central and southern regions. The disturbance of land use type changes on terrestrial ecosystem carbon storage has been effectively mitigated. The significant reduction in grassland area in the Southwest region is the main source of carbon storage loss during the study period, and the encroachment of construction land on arable land in large urban agglomerations is one of the important causes of carbon storage loss. The Theil index multi-stage nested decomposition results indicate that the overall difference in carbon storage in China has decreased, while differences among cities within provinces and among counties within cities have increased. The influence of natural factors on the distribution of carbon storage is weakening, whereas the impact of human activities is becoming more profound, enhancing its influence on the spatial distribution of carbon storage in China. From 1980 to 2000, the carbon density in coastal metropolises generally showed a declining trend. From 2000 to 2020, the carbon density in the central urban areas of eastern coastal city clusters gradually showed an upward trend and continued to expand outward, revealing to some extent the "Environmental Kuznets Curve" characteristic in the development process of urban carbon storage. Therefore, in future ecological construction, the government should fully consider the impact of land management planning on carbon storage in different regions, promote the efficient use and standardized management of land, and strive to cross the "Environmental Kuznets Curve" inflection point of carbon storage as soon as possible. [ABSTRACT FROM AUTHOR]

With the continuous expansion of regional trade, interregional teleconnections have an increasingly pronounced impact on the changes in carbon storage caused by land use in China. Current research in this area remains remarkably limited, however. This study employs land-use data, carbon density data, and a multiregional input–output model to precisely quantify the embodied flow and spatial patterns of land-use carbon storage in China. We found that the carbon storage embodied in interprovincial trade in China accounts for 34.9 percent of total carbon storage, with cropland (44.9 percent) and woodland (43.6 percent) representing the highest proportions within their land-use categories. Inner Mongolia, Heilongjiang, and Tibet were found to be the most externally driven in terms of land-use-related carbon storage, with outflows exceeding 2,000 Tg C. Beijing, Tianjin, and Shanghai, on the other hand, were shown to consume up to 90 percent of land-use-related carbon storage inflows, showcasing the strongest external dependence. Additionally, Hunan (1,300.5 Tg C), Hubei (863.4 Tg C), Henan (1,534.6 Tg C), and Shanxi (2,223.6 Tg C) are the provinces where changes in land-use carbon storage are most significant, exerting the greatest influence on changes in China's total carbon storage. China's international export of land-use-related embodied carbon storage decreased by 3,964.7 Tg C during the study period, with woodland (1,516.8 Tg C) and grassland (1,505.7 Tg C) being the primary declining land types. Interestingly, as land utilization efficiency continues to rise, over half of the provinces have seen an increase in export trade value, while their corresponding embodied carbon storage has declined. The findings not only unveil the complex dynamics and spatial distribution at work in China's embodied land-use-related carbon storage but also provide practical insights and directions for achieving carbon neutrality goals. [ABSTRACT FROM AUTHOR]

The prior plays a central role in Bayesian inference but specifying a prior is often difficult and a prior considered appropriate by a modeler may be significantly biased. We propose multi-pass Bayesian estimation (MBE), a robust Bayesian method capable of adjusting the prior's influence on the inference result based on the prior's quality. MBE adjusts the relative importance of the prior and the data by iteratively performing approximate Bayesian updates on the given data, with the number of updates determined using a cross-validation method. The repeated use of the data resembles the data cloning method, but data cloning performs maximum likelihood estimation (MLE), while MBE interpolates between standard Bayesian inference and MLE; there are also algorithmic differences in how MBE and data cloning make repeated use of the data. Alternatively, MBE can be considered a method for constructing a new prior from the given initial prior and the data. We additionally provide a new non-asymptotic bound on the convergence of data cloning, and provide an MBE-like iterative heuristic approach which achieves faster convergence speed by boosting posterior variance. In numerical simulations on several simulated and real-world datasets, MBE provides robust inference results as compared to standard Bayesian inference and MLE. [ABSTRACT FROM AUTHOR]

Soil fungi are involved in the decomposition of organic matter, and they alter soil structure and physicochemical properties and drive the material cycle and energy flow in terrestrial ecosystems. Fungal community assembly processes were dissimilar in different soil layers and significantly affected soil microbial community function and plant growth. Grazing exclusion is one of the most common measures used to restore degraded grasslands worldwide. However, changes in soil fungal community characteristics during grazing exclusion in different types of grasslands are unknown. Here, we investigated the effects of a 9‐year grazing exclusion on soil properties, fungal community composition, and diversity in three grassland types (temperate desert, temperate steppe, and mountain meadow). The results showed that (1) in the 0–5 cm soil layer, grazing exclusion significantly increased the differences in SWC, SOC, KN, and N:P among the three grassland types, while the final pH, BD, TP, C:N, and C:P values were consistent with the results before exclusion. In the 5–10 cm soil layer, grazing exclusion significantly increased total phosphorus (TP) in temperate deserts by 34.1%, while significantly decreasing bulk density (BD) by 9.8% and the nitrogen: phosphorus ratio (N:P) by 47.1%. (2) The soil fungal community composition differed among the grassland types, For example, significant differences were found among the three grassland types for the Glomeromycota and Mucoromycota. (3) Under the influence of both grazing exclusion and grassland type, there was no significant change in soil fungal alpha diversity, but there were significant differences in fungal beta diversity. (4) Grassland type was the most important factor influencing changes in fungal community diversity, and vegetation cover and soil kjeldahl nitrogen were the main factors influencing fungal diversity. Our research provides a long‐term perspective for better understanding and managing different grasslands, as well as a better scientific basis for future research on grass–soil–microbe interactions. [ABSTRACT FROM AUTHOR]

The seasonal evolution of the sea surface temperature (SST) in the joining area of Asia and Indian-Pacific Ocean (AIPO) has strong impacts on its surrounding areas. Greenhouse gas-induced global warming brings seasonally varying changes in SST in AIPO, the formation of which is not totally understood. Based on historical and SSP5-8.5 runs of 23 climate models in phase 6 of the Coupled Model Intercomparison Project, this study shows that the SST changes under global warming over AIPO have considerable seasonal variation from boreal spring to summer and their formation is related to different physical processes. The AIPO SST changes show distinct seasonal variations across two subregions: the eastern Indian Ocean (EIO) experiences more pronounced warming in April and May compared to the annual mean, while the EIO and equatorial western Pacific (EWP) exhibit weaker warming from June to August. In the EIO, the seasonal variation in the changes in evaporative damping effect dominates the seasonal variation in SST changes, due to the change in surface wind speed and climatological evaporative damping. Compared to other seasons, the stronger warming during June and July in the equatorial eastern Pacific causes a greater eastward shift of convective upward motion in the EWP. This results in reduced shortwave radiation and weaker warming over the EWP during these months. [ABSTRACT FROM AUTHOR]

Visual simultaneous localization and mapping is a widely used technology for mobile robots to carry out precise positioning in the environment of GNSS technology failure. However, as the robot moves around indoors, its position accuracy will gradually decrease over time due to common and unavoidable environmental factors. In this paper, we propose an improved method called RTABMAP-VIWO, which is based on RTABMAP. The basic idea is to use an Extended Kalman Filter (EKF) framework for fusion attitude estimates from the wheel odometry and IMU, and provide new prediction values. This helps to reduce the local cumulative error of RTABMAP and make it more accurate. We compare and evaluate three kinds of SLAM methods using both public datasets and real indoor scenes. In the dataset experiments, our proposed method reduces the Root-Mean-Square Error (RMSE) coefficient by 48.1% compared to the RTABMAP, and the coefficient is also reduced by at least 29.4% in the real environment experiments. The results demonstrate that the improved method is feasible. By incorporating the IMU into the RTABMAP method, the trajectory and posture errors of the mobile robot are significantly improved. [ABSTRACT FROM AUTHOR]

Seasonally frozen soils are exposed to freeze‒thaw cycles every year, leading to mechanical property deterioration. To reasonably describe the deterioration of soil under different conditions, machine learning (ML) technology is used to establish a prediction model for soil static strength. Six key influencing factors (moisture content, compaction degree, confining pressure, freezing temperature, number of freeze‒thaw cycles and thawing duration) are included in the modelling database. The accuracy of three typical ML algorithms (support vector machine (SVM), random forest (RF) and artificial neural network (ANN)) is compared. The results show that the ANN outperforms the SVM and RF. Principal component analysis (PCA) is combined with the ANN, and the PCA–ANN algorithm is proposed, which further improves the prediction accuracy. The deterioration of soil static strength is systematically researched using the PCA–ANN algorithm. The results show that the soil static strength decreased considerably after the first several freeze‒thaw cycles before the strength plateau occurred, and the strength reduction increased significantly with increasing moisture content and compaction degree. The PCA–ANN model can generate a reasonable prediction for the static strength or other soil properties of seasonally frozen soil, which will provide a scientific reference for practical engineering. [ABSTRACT FROM AUTHOR]

Background: Chronic musculoskeletal pain (CMP) is a complex condition that is mainly treated with analgesic drugs. However, antidepressant intervention is also an important factor in the treatment of CMP. Duloxetine is an effective treatment option for patients with CMP as its antidepressant effect. The purpose of this article is to evaluate the efficacy and safety of duloxetine in treating CMP. Databases and data treatment: We searched PubMed, Web of Science, Embase, Cochrane Library from inception to May, 2022. Randomized controlled trials (RCTs) evaluating the efficacy and safety of duloxetine versus placebo in patients with CMP were included. We identified 13 articles and studied a population of 4201 participants in 4 countries. Results: This meta-analysis showed that the duloxetine has statistically significant compared with the placebo control, benefits on 24-hour average pain, living quality, physical function, and global impressions and there was no difference in the incidence of serious adverse event. In general, duloxetine can improve mood and pain level at the same time. Conclusions: This review shows a significant contribution of duloxetine to CMP symptom relief. This meta-analysis improved that duloxetine can significantly reduce the pain level of patients, improve depressive symptoms and global impression, and has no obvious serious adverse reactions. However, additional studies are required to confirm the relationship between psychological diseases and chronic pain and explore their internal links. [ABSTRACT FROM AUTHOR]

In the field of anomaly detection (AD), Few-Shot Anomaly Detection (FSAD) has gained significant attention in recent years. The goal of anomaly detection is to identify defects at the image level and localize them at the pixel level. Including defect data in training helps to improve model performance, and FSAD methods require a large amount of data to achieve better results. However, defect data is often difficult to obtain in experiments and applications. This paper proposes a more realistic method for simulating anomaly data, incorporating the synthesized anomaly data into the training process and applying it to the FSAD domain through multi-class mixed training. The anomaly data generated using our synthesis method closely resembles real anomalies. The corresponding anomaly synthesis method synthesizes the anomaly data from normal samples for the adaptively selected polygonal mesh region. We enhance the model's ability to distinguish between positive and negative samples by incorporating synthesized anomaly data and normal data as triplets during training. This results in that more detailed features for normal samples will be noticed. During the testing phase, we obtain the feature distribution of normal images for a few unknown class normal samples to quickly adapt to the detection task of new categories. The effectiveness of the anomaly synthesis method was validated through experiments. Comparisons with advanced methods in the FSAD domain demonstrated that our method achieved competitive performance. • We designed a more realistic anomaly synthesis method that is adaptive to different categories of samples. • Using the triplet loss, we promoted a more compact representation of normal sample features while increasing the disparity between positive and negative samples, thereby enhancing the model's detection capabilities. • Experimental results show that our AdapSyn outperforms the SOTA methods in FSAD. Moreover, compared to other methods that use the entire dataset for training, our method also demonstrates competitive performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • The effect of different modification methods and modified materials on zero-valent iron (ZVI) is reviewed. • The removal mechanism of heavy metals, radionuclides and halogenated organic compounds by modified ZVI is listed. • The application of modified ZVI as an activator in advanced oxidation is elaborated. • The methods of mass production of modified ZVI and its application in practical environments are reviewed. • Some outlooks on the future applications and research directions of modified zero-valent iron are presented. Zero-valent iron (ZVI) has garnered widespread attention in the treatment of industrial wastewater due to its strong reducibility, low cost, ease of acquisition, and environmental friendliness. However, the application of ZVI is hindered by several drawbacks, particularly the agglomeration and surface passivation. In contrast to previous reviews, this paper provides a detailed overview of several methods of modifying ZVI and describes the effects of different materials or modification methods. The removal mechanisms of heavy metal ions, radionuclides, and halogenated organic pollutants by different modified ZVIs are also listed. The paper highlights the application of modified ZVI as an activator in the field of advanced oxidation as well as the application of different modified ZVI in real water bodies. The paper concludes with a prospective analysis, envisioning future research trajectories and applications of modified ZVI. This includes considerations for material selection, environmental impact assessments, enhanced adsorption capabilities, in-situ degradation, targeted generation of reactive species, and the scaling-up from laboratory to field settings. We also advocate for customized modifications catered to specific water body characteristics. It is hoped that this review can further promote the development of modified ZVI and provide references for its application in practical wastewater treatment. [ABSTRACT FROM AUTHOR]

• A pandemic-resilient residential building design index system was proposed. • A fuzzy comprehensive evaluation method was applied to assess each strategy. • The preference index was used to identify the most important and practical measures. • Property management, common areas and building morphology were top sub-categories. • Policy and application suggestions were given for a healthier living environment. The relationship between the built environment and epidemic transmission is particularly pronounced within the context of lockdown policies and high-density urban areas. Non-pharmaceutical interventions have become increasingly important during and after the COVID-19 pandemic. This study proposes an evaluation index system for pandemic-resilient residential building designs in high-density cities, covering the entire design process including site planning, architecture design, building equipment and management. The system includes 64 design strategies, categorized into 15 sub-categories and 4 categories. Then, we evaluate the preference of each strategy by synthesizing the dimensions of importance and implementation difficulty. A questionnaire survey was conducted among experts who have experience with pandemic-resilient designs in high-density cities. Fuzzy synthetic evaluation analysis was implemented along with the "preference index" concept to identify the most important and practical interventions during the pandemic outbreak. The results indicate that "service and management" is the category that requires priority, followed by "property management," "common areas" and "building morphology" in sub-categories. Among the design strategies, "waste receptacle," "publicity and education," "floor drain and water seal" and "environmental cleaning and disinfection" are the top four recommended strategies. This study provides policymakers and practitioners with effective and easily implementable prevention measures during an outbreak of respiratory tract infections. It also offers specific policy recommendations and application suggestions for new and existing buildings, contributing to creating a safer and healthier living environment. [ABSTRACT FROM AUTHOR]

• HLFEMP is proposed for problems characterized by the coexistence of large and small deformations in solid mechanics. • HLFEMP is absent from flaws such as cell-crossing noise and numerical fracture. • HLFEMP outperforms conventional updated Lagrangian MPM-FEM method in accuracy and efficiency for numerical simulations. Coupling the Material Point Method (MPM) with the Finite Element Method (FEM) provides a powerful approach for addressing problems characterized by the coexistence of large and small deformations. The majority of existing MPM-FEM methods, which operate within the updated Lagrangian framework, introduce inherent issues, such as cell-crossing noise and numerical fracture, compromising the overall accuracy of the coupled method. This paper presents a coupled MPM-FEM method under a hybrid updated and total Lagrangian framework (HLFEMP). Within the HLFEMP, updated Lagrangian FEM is employed to handle small deformations, while total Lagrangian MPM is adopted to model large deformations. A particle-to-surface contact algorithm with auxiliary thickness layer is utilized to couple both methods. Notably, by imposing the weak form of total Lagrangian MPM in the undeformed configuration, HLFEMP is rendered free from cell-crossing noise and numerical fracture, resulting in better computational stability. The performance of HLFEMP in terms of energy behavior, accuracy, efficiency and stability under large elastic and elasto-plastic deformations are investigated through a series of numerical simulations. [ABSTRACT FROM AUTHOR]

We performed a study on standardizing the catch per unit effort (CPUE) for blue endeavour prawns (Metapenaeus endeavouri) caught in the Northern Prawn Fishery (NPF), one of Australia's largest and most valuable prawn fisheries. Blue endeavour prawns constitute a significant proportion of the total NPF catches. However, there have been very limited studies on their population dynamics. This study assessed the effectiveness of Artificial Neural Networks (ANNs) for CPUE standardization, with a focus on blue endeavour prawns as a case study. Our approach involved developing new ANN models for CPUE standardization with two key ideas: using an architecture inspired by the catch equation to mitigate overfitting; and using the Tweedie distribution to manage uncertainties and zero counts in the catch data. Specifically, we grouped variables into three distinct modules based on the catch equation, with each representing catchability, fishing effort, and fish density, respectively. Parameter estimation for our ANNs was achieved by maximizing the likelihood using a coordinate descent approach, which alternates between optimizing the Tweedie distribution parameters (power and dispersion) and the standard neural net parameters. We conducted a comprehensive comparison among ANNs, generalized linear models, and generalized additive models. The findings suggest that customizing ANN structure improves model fitting and effectively mitigates the risk of overfitting. It also reveals a promising path for the application of neural networks in CPUE standardization. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the F1-measure value and the AUROC value of some classical open-set classifier methods do not exceed 40% in high-openness scenarios, this paper proposes an algorithm combining negative-class feature enhancement learning and a Weibull distribution based on an extreme value theory representation method, which can effectively reduce the risk of open space in open-set scenarios. Firstly, the solution uses the negative-class sample feature enhancement learning algorithm to generate the negative sample point set of similar features and then compute the corresponding negative-class sample feature segmentation hypersphere. Secondly, the paired Weibull distributions from positive and negative samples are established based on the corresponding negative-class sample feature segmentation hypersphere of each class. Finally, solutions for non-linear multi-class classifications are constructed by using the Weibull and reverse Weibull distributions. Experiments on classic open datasets such as the open dataset of letter recognition, the Caltech256 open dataset, and the CIFAR100 open dataset show that when the openness is greater than 60%, the performance of the proposed method is significantly higher than other open-set support vector classifier algorithms, and the average is more than 7% higher. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a significant impact on many lives and the economies of many countries since late December 2019. Early detection with high accuracy is essential to help break the chain of transmission. Several radiological methodologies, such as CT scan and chest X-ray, have been employed in diagnosing and monitoring COVID-19 disease. Still, these methodologies are time-consuming and require trial and error. Machine learning techniques are currently being applied by several studies to deal with COVID-19. This study exploits the latent embeddings of variational autoencoders combined with ensemble techniques to propose three effective EVAE-Net models to detect COVID-19 disease. Two encoders are trained on chest X-ray images to generate two feature maps. The feature maps are concatenated and passed to either a combined or individual reparameterization phase to generate latent embeddings by sampling from a distribution. The latent embeddings are concatenated and passed to a classification head for classification. The COVID-19 Radiography Dataset from Kaggle is the source of chest X-ray images. The performances of the three models are evaluated. The proposed model shows satisfactory performance, with the best model achieving 99.19 % and 98.66 % accuracy on four classes and three classes, respectively. [ABSTRACT FROM AUTHOR]

Tropical rainfall is important for regional climate around the globe. In a warming climate forced by rising CO 2 , the tropical rainfall will increase over the equatorial Pacific where sea surface warming is locally enhanced. Here, we analyze an idealized CO 2 removal experiment from the Carbon Dioxide Removal Model Intercomparison Project (CDRMIP) and show that the tropical rainfall change features a stronger pattern during CO 2 ramp-down than ramp-up, even under the same global mean temperature increase, such as the 2 °C goal of the Paris Agreement. The tropical rainfall during CO 2 ramp-down increases over the equatorial Pacific with a southward extension, and decreases over the Pacific intertropical convergence zone and South Pacific convergence zone. The asymmetric rainfall changes between CO 2 ramp-down and ramp-up result from time-varying contributions of the fast and slow oceanic responses to CO 2 forcing, defined as the responses to abrupt CO 2 forcing in the first 10 years and thereafter, respectively, in the abrupt-4xCO2 experiment. The fast response follows the CO 2 evolution, but the slow response does not peak until 60 years after the CO 2 peak. The slow response features a stronger El Niño-like pattern, as the ocean dynamical thermostat effect is suppressed under stronger subsurface warming. The delayed and stronger slow response leads to stronger tropical rainfall changes during CO 2 ramp-down. Our results indicate that returning the global mean temperature increase to below a certain goal, such as 2 °C, by removing CO 2 , may fail to restore tropical convection distribution, with potentially devastating effects on climate worldwide. [ABSTRACT FROM AUTHOR]

Using length frequency distribution data (LFD) is cost-effective for estimating somatic growth in fish or invertebrates as length data are relatively easy to obtain. The recently developed R packages TropFishR and fishboot extend classic ELEFAN (Electronic LEngth Frequency ANalysis) programs and include more powerful optimization procedures and a bootstrap method for estimating uncertainties. Yet, the fundamental functions require users to provide search conditions (e.g. upper and lower limits for each parameter, length-class size, number of length-classes for the calculation of moving average), which can significantly affect the results. In this paper, we compare the ELEFAN approach with a Bayesian approach in analysing LFD, employing both standard and seasonal von Bertalanffy growth functions. We apply both approaches to a commercially valuable but poorly studied red endeavour prawn (Metapenaeus ensis) harvested in Australia's Northern Prawn Fishery. Sensitivity tests on ELEFAN confirm that any change in search settings would affect the results. Simulation studies on Bayesian growth models show that Linf and K can be accurately obtained even with modal progression of only one year-class and using non-informative priors. However, age information, including the theoretical age at length zero (t0), is difficult to estimate and requires LFD from multiple age classes and informative priors. The Bayesian models yield mean parameters of: Linf = 36.56 mm (carapace length), K = 2.74 yr–1, and t0 = -0.02 yr for the males, and Linf = 51.81 mm, K = 1.94 yr–1, and t0 = -0.02 yr for the females. Seasonal oscillation models fit the LFD better, but the improvement is small and the estimated season-related parameters have large variances. [ABSTRACT FROM AUTHOR]

Catch-per-unit-effort (CPUE) standardization is crucial for fishery stock assessment but often presents challenges due to spatial-temporal variations in species distribution and fishing effort. In this simulation study, we propose the use of customized artificial neural networks (ANNs) for modeling the spatial-temporal variations in CPUE standardization. This is achieved by encoding prior knowledge of the dependency structure between the variables into the architecture of the ANNs. We conducted numerical experiments on simulated data to compare our customized ANNs with Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), and fully connected ANNs used in previous studies. Our simulated data cover three spatial-temporal dynamics scenarios with different degrees of species distribution shift over time: (1) steady fish distribution; (2) gradual directional shift over time; (3) sudden directional shift. In predicting the standardized CPUE in this simulation study, the customized ANNs demonstrated greater accuracy compared to the commonly used fully connected ANNs with an error reduction of over 70 %, more than 80 % compared to GLMs, and more than 40 % compared to GAMs, in terms of an error metric called the scaled mean absolute relative error. Our findings suggest that customized ANNs can serve as an alternative modeling tool alongside GLMs and GAMs in fisheries modeling. [ABSTRACT FROM AUTHOR]

Sharks (class Chondrichthyes, subclass Elasmobranchii) typically have a long lifespan, slow growth rate and low fecundity, leading to low productivity and hence relatively high vulnerability to fishing. Information for managing fisheries catches of elasmobranchs is often lacking, because elasmobranchs are usually non‐target species, often with low abundance. It is more feasible to develop management reference points for elasmobranchs based on their life‐history information than through traditional stock assessments. The natural mortality rate (M) is the leading life‐history parameter (LHP) required by many methods for developing reference points and is itself often derived indirectly from other LHPs. In this paper, we evaluate nine M estimators, using 15 shark stocks in the Western and Central Pacific Ocean as examples. We then compare four methods for developing fishing mortality reference points Fmsy, including empirical modelling, the Euler‐Lotka equation, an M‐productivity‐based method and the spawning potential rate converted method. Our analyses show that popular M estimators developed mainly from teleost data resulted in large deviations from the average and were not suitable for elasmobranchs. All four methods for estimating Fmsy performed similarly. However, the empirical method is very simple and cost‐effective and tended to produce smaller deviations from the average than the other three methods. Nonetheless, it is recommended that multiple methods should be used to minimize possible bias and reflect uncertainty, if the required LHPs are available. [ABSTRACT FROM AUTHOR]

• The CV adverse effects of ALK inhibitors were not widely appreciated initially. • Bradycardia is being increasingly recognized as an adverse effect of these drugs. • Although usually mild, the rate of ALK inhibitor-induced bradycardia is up to 9%. • Crizotinib led to a higher risk of bradycardia compared to standard chemotherapy. • Newer ALK inhibitors appear to have a similar risk of bradycardia as crizotinib. Anaplastic Lymphoma Kinase (ALK) inhibitors have revolutionized the treatment of advanced ALK-positive non-small cell lung cancer (NSCLC), improving progression-free survival. Bradycardia is a potential adverse effect of these agents. We aimed to determine the risk of bradycardia associated with ALK inhibitors in patients with advanced NSCLC. We conducted a systematic search of MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, National clinical trial registry, and Web of Science Core Collection. We included all randomized controlled trials in which an ALK-inhibitor was compared with another ALK-inhibitor or standard chemotherapy. Meta-analyses were conducted to evaluate the pooled incidence rates of bradycardia and dizziness using fixed effect models. The pooled incidence of bradycardia among 1737 individuals prescribed ALK inhibitors was 8% during a mean follow-up of 1.26 years. Crizotinib led to more bradycardia than standard chemotherapy (relative risk, RR 24.68, 95% CI 7.11–85.), while no difference was seen between crizotinib and alectinib (RR 1.12, 95% CI 0.79–1.59). The next-generation ALK inhibitors alectinib, brigatinib and lorlatinib combined resulted in a similar rate of bradycardia when compared to crizotinib (RR 0.77, 95% CI 0.57–1.04). All ALK inhibitors (as an aggregate) caused more dizziness (as a potential symptom of bradycardia) than standard chemotherapy (RR 1.88, 95% CI 1.44–2.44). Conclusion: Crizotinib for the treatment of NSCLC is associated with a higher risk for bradycardia compared to standard chemotherapy. There is no evidence of a difference in bradycardia risk between crizotinib and newer ALK inhibitors. [ABSTRACT FROM AUTHOR]

The development of regional trade has fostered teleconnections in land resource across various regions, emerging as a pivotal influence on the expansion of construction land. However, the potential consequences of regional trade on carbon storage associated with construction land remain largely unquantified. Therefore, this study zeroes in on Guangdong Province as the focal point, employing China's multiregional input-output model to quantify interregional teleconnections and delineate changes in carbon storage. Through meticulous analysis, it seeks to pinpoint the catalysts driving these alterations in teleconnections. By delving into the latest teleconnections within Guangdong, the study unveils the ramifications of the province's trade scale and structure with other provinces on carbon storage, thereby identifying imperative avenues for carbon storage preservation. The findings underscore that during the study period, the expansion of construction land in Guangdong Province precipitated a notable loss of land carbon storage, amounting to 2.6 Tg C, primarily sourced from forests and arable land. Concurrently, the total carbon flow surged by 20.77 Tg C, propelled by a 4.63 Tg C influx and a 16.05 Tg C outflow, resulting in a net inflow decrease of 11.51 Tg C. This delineates the influence of external forces on carbon storage within Guangdong Province, with the surge primarily attributed to heightened external demand, notably for construction land. Nevertheless, technological advancements have partially alleviated the impact of this demand surge on carbon storage. The outcomes of this study underscore the pivotal role of external linkages in shaping carbon storage dynamics and furnish invaluable insights for steering future regional endeavors towards carbon neutrality objectives. • Teleconnection of carbon storage in construction land and its driving forces is investigated. • The latest multi-regional input-output tables and structural decomposition analysis are used. • The overall flow of carbon storage totaled 77.89 Tg C, consisting of an inflow of 53.34 Tg C and an outflow of 24.54 Tg C. • Consumption demand serves as the primary factor, followed by consumption and production structure. • The intensity of construction land carbon storage significantly reduces the flow. [ABSTRACT FROM AUTHOR]

Introduction: We recently developed two noninvasive methodologies to help guide VT ablation: population‐derived automated VT exit localization (PAVEL) and virtual‐heart arrhythmia ablation targeting (VAAT). We hypothesized that while very different in their nature, limitations, and type of ablation targets (substrate‐based vs. clinical VT), the image‐based VAAT and the ECG‐based PAVEL technologies would be spatially concordant in their predictions. Objective: The objective is to test this hypothesis in ischemic cardiomyopathy patients in a retrospective feasibility study. Methods: Four post‐infarct patients who underwent LV VT ablation and had pre‐procedural LGE‐CMRs were enrolled. Virtual hearts with patient‐specific scar and border zone identified potential VTs and ablation targets. Patient‐specific PAVEL based on a population‐derived statistical method localized VT exit sites onto a patient‐specific 238‐triangle LV endocardial surface. Results: Ten induced VTs were analyzed and 9‐exit sites were localized by PAVEL onto the patient‐specific LV endocardial surface. All nine predicted VT exit sites were in the scar border zone defined by voltage mapping and spatially correlated with successful clinical lesions. There were 2.3 ± 1.9 VTs per patient in the models. All five VAAT lesions fell within regions ablated clinically. VAAT targets correlated well with 6 PAVEL‐predicted VT exit sites. The distance between the center of the predicted VT‐exit‐site triangle and nearest corresponding VAAT ablation lesion was 10.7 ± 7.3 mm. Conclusions: VAAT targets are concordant with the patient‐specific PAVEL‐predicted VT exit sites. These findings support investigation into combining these two complementary technologies as a noninvasive, clinical tool for targeting clinically induced VTs and regions likely to harbor potential VTs. [ABSTRACT FROM AUTHOR]

In this paper, we present an adaptive scheme involving heterogeneous delay interactions to suppress synchronization in a large population of oscillators. We analytically investigate the incoherent state stability regions for several specific kinds of distributions for delays. Interestingly, we find that, among the distributions that we discuss, the exponential distribution may offer great convenience to the performance of our adaptive scheme because this distribution renders an unbounded stability region. Moreover, we demonstrate our scheme in the realization of synchronization elimination in some representative, realistic neuronal networks, which makes it possible to deepen the understanding and even refine the existing techniques of deep brain stimulation in the treatment of some synchronization-induced mental disorders. [ABSTRACT FROM AUTHOR]

Background: Mediator is a multiprotein complex that acts as an essential transcriptional coactivator in eukaryotic cells for successful transcription. In this study, we aimed to explore the expression profile of 33 mediator subunit genes in oral cavity squamous cell carcinoma (OCSCC) and the functional role of MED28 in cellular behaviors of OCSCC cells.Methods: Single-cell (sc)RNA-seq data from OCSCC cells (Puram 2017's dataset) and bulk-seq data of the OCSCC subgroup of TCGA-head and neck squamous cell carcinoma (HNSC) were used for bioinformatic analysis. SCC9 cells were used in in-vitro and in-vivo analysis.Results: Among the 33 genes subjected to screening, MED28 showed the best prognostic value and its upregulation might independently predict shorter OS (HR: 3.699, 95% CI: 1.383-9.892, P = .009) and PFS (HR: 2.769, 95% CI: 1.462-5.244, P = .002). MED28 expression was positively correlated with cancer stem cell (CSC)-like properties of SCC9 cells, including colony/sphere formation, and the expression of CSC markers (CD44, KLF4, NANOG, and OCT4). RCOR1 could suppress the CSC-like properties of SCC9 cells and had direct interaction with MED28. Its overexpression partly abrogated MED28-induced expression of CSC markers. RCOR1 expression was associated with promoter hypermethylation, while MED28 expression was positively correlated with its MED28 copy number (Pearson's r = .44) in OCSCC tissues.Conclusion: Among the mediator complex subunits, MED28 might serve as a potential biomarker of unfavorable survival. Its overexpression increased CSC-like activity of OCSCC cells, the effect of which could be abrogated by RCOR1 via direct interaction. [ABSTRACT FROM AUTHOR]

Maintaining the original advantages of symmetrical solid oxide fuel cells (SSOFCs), the electrochemical performance can be further enhanced by new quasi-symmetrical solid oxide fuel cells. Herein, highly active Ruddlesden-Popper oxides Co-doped LaSr 3 Fe 3 O 10-δ are investigated as possible symmetric electrodes for SSOFCs, and in situ exsolution of Co–Fe nanoparticles can be homogenously observed on the backbone of this catalyst after high temperature hydrogenation. Spin coated gadolinium doped ceria (GDC) buffer layer onto both sides of the YSZ electrolyte is used to avoid the side reaction of YSZ electrolyte and the symmetric electrodes. LaSr 3 Fe 2 CoO 10-δ showed more excellent electrochemical performance with the high maximum power density of 351.4 mW cm−2 and the electrode polarization resistance of 0.2894 Ω cm2 at 800 °C. Moreover, no sign of degradation with this SSOFCs during 100 h long-time testing is observed at 700 °C, indicating that the LaSr 3 Fe 2 CoO 10-δ symmetrical electrode exhibits good redox reversibility. The high stability and catalytic activity of Ruddlesden-Popper oxides can provide more promise related applications for SSOFCs. [ABSTRACT FROM AUTHOR]

Matrix Factorization (MF) based on Stochastic Gradient Descent (SGD) is a powerful machine learning technique to derive hidden features of objects from observations. In this article, we design a highly parallel architecture based on Field-Programmable Gate Array (FPGA) to accelerate the training process of the SGD-based MF algorithm. We identify the challenges for the acceleration and propose novel algorithmic optimizations to overcome them. By transforming the SGD-based MF algorithm into a bipartite graph processing problem, we propose a 3-level hierarchical partitioning scheme that enables conflict-minimizing scheduling and processing of edges to achieve significant speedup. First, we develop a fast heuristic graph partitioning approach to partition the bipartite graph into induced subgraphs; this enables to efficiently use the on-chip memory resources of FPGA for data reuse and completely hide the data communication between FPGA and external memory. Second, we partition all the edges of each subgraph into non-overlapping matchings to extract the maximum parallelism. Third, we propose a batching algorithm to schedule the execution of the edges inside each matching to reduce the memory access conflicts to the on-chip RAMs of FPGA. Compared with non-optimized FPGA-based baseline designs, the proposed optimizations result in up to 60× data dependency reduction, 4.2× bank conflict reduction, and 15.4× speedup. We evaluate the performance of our design using a state-of-the-art FPGA device. Experimental results show that our FPGA accelerator sustains a high computing throughput of up to 217 billion floating-point operations per second (GFLOPS) for training very large real-life sparse matrices. Compared with highly-optimized GPU-based accelerators, our FPGA accelerator achieves up to 12.7× speedup. Based on our optimization methodology, we also implement a software-based design on a multi-core platform, which demonstrates 1.3× speedup compared with the state-of-the-art multi-core implementation. [ABSTRACT FROM AUTHOR]

Empirical studies are popular in estimating fish natural mortality rate (⁠ M ⁠). However, these empirical methods derive M from other life-history parameters and are often perceived as being less reliable than direct methods. To improve the predictive performance and reliability of empirical methods, we develop ensemble learning models, including bagging trees, random forests, and boosting trees, to predict M based on a dataset of 256 records of both Chondrichthyes and Osteichthyes. Three common life-history parameters are used as predictors: the maximum age and two growth parameters (growth coefficient and asymptotic length). In addition, taxonomic variable class is included to distinguish Chondrichthyes and Osteichthyes. Results indicate that tree-based ensemble learning models significantly improve the accuracy of M estimate, compared to the traditional statistical regression models and the basic regression tree model. Among ensemble learning models, boosting trees and random forests perform best on the training dataset, but the former performs a slightly better on the test dataset. We develop four boosting trees models for estimating M based on varying life-history parameters, and an R package is provided for interested readers to estimate M of their new species. [ABSTRACT FROM AUTHOR]

Analysis of spawning biomass per‐recruit has been widely adopted in fisheries management. Fishing mortality expressed as spawning potential ratio (SPR) often requires a reference point as an appropriate proxy for the fishing mortality that supports a maximum sustainable yield—FMSY. To date, a single generic level between F30% and F40% is routinely used. Using records from stock assessments in the RAM Legacy Database (RAMLD), we confirm that SPR at MSY (SPRMSY) is a declining function of stock productivity quantified by FMSY. We then use general linear models (GLM) and Bayesian errors‐in‐variables models (BEIVM) to show that SPRMSY can be predicted from life‐history parameters (LHPs, including maximum lifespan, age‐ and length‐at‐maturation, growth parameters, natural mortality, and taxonomic Class) as well as gear selectivity. The calculated SPRMSY ranges from about 13% to 95% with a mean of 47%. About 64% of the stocks in the RAMLD require SPRMSY > 40%. Modelling SPRMSY reveals that LHPs plus Class explain 61% of the deviance in SPRMSY. Faster‐growing, low‐survival, and short‐lived species generally require a high SPR. With equal LHPs, elasmobranchs require about 20% higher SPRMSY than teleosts. When FMSY is estimated from fisheries that harvest older fish, increasing the vulnerable age by one year leads to about an 8% increase in SPRMSY. The BEIVM yields smaller variance and bias than the GLM. The models developed in this study could be used to predict SPRMSY reference points for new stocks using the same LHPs for calculating Fx%, but without knowledge of the stock‐recruitment parameters. [ABSTRACT FROM AUTHOR]

In phases 5 and 6 of the state-of-the-art Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) models, there is an apparent excessive rainfall bias with a negative SST bias in the tropical Pacific intertropical convergence zone (ITCZ). The regime of the excessive ITCZ but negative SST bias is inconsistent with the common positive rainfall–SST correlation of climate anomalies over the tropics. Using a two-mode model, we decomposed the rainfall bias into two components and found that the surface convergence (SC) bias is the key factor forming the excessive ITCZ bias in the historical runs of 25 CMIP5 models and 23 CMIP6 models. A mixed layer model was further applied to connect the formation of the SC bias with the SST pattern bias. The results suggest that the meridional pattern of the SST bias plays a key role in forming the SC bias. In the CMIP5 and CMIP6 models, the overall negative SST bias has two apparent meridional troughs at around 10°S and 10°N, respectively. The two meridional troughs in the SST bias drive two convergence centers in the SC bias favoring the excessive ITCZ, even though the local SST bias is negative. [ABSTRACT FROM AUTHOR]

Estimating fish growth from length frequency data is challenging. There is often a lack of clearly separated modes and modal progression in the length samples due to a combination of factors, including gear selectivity, slowing growth with increasing age, and spatial segregation of different year classes. In this study, we present an innovative Bayesian hierarchical model (BHM) that enables growth to be estimated where there are few distinguishable length modes in the samples. We analyse and identify the modes in multiple length frequency strata using a multinormal mixture model and then integrate the modes and associated variances into the BHM to estimate von Bertalanffy growth parameters. The hierarchical approach allows the parameters to be estimated at regional levels, where they are assumed to represent subpopulations, as well as at species level for the whole stock. We carry out simulations to validate the method and then demonstrate its application to Indian Ocean longtail tuna (Thunnus tonggol). The results show that the estimates are generally consistent with the range of estimates reported in the literature, but with less uncertainty. The BHM can be useful for deriving growth parameters for other species even if the length data contain few age classes and do not exhibit modal progression. [ABSTRACT FROM AUTHOR]

• Single-Opponent feature map is calculated for microvessel image feature extraction. • Locality constraint is embedded in the feature-biased dictionary learning. • Group lasso coding is solved by constrained smooth convex optimization. Image-based classification of histology sections plays an important role in predicting clinical outcomes. In this paper, we propose a Locality-Constrained Group Lasso Coding (LCGLC) method for microvessel image classification, which realizes the automatic "hot spot" detection of angiogenesis for human liver carcinoma. First, we extract Scale-Invariant Feature Transform (SIFT) descriptors on the Single-Opponent (SO) feature map, which simulates the biological functionality of human visual systems. Then, we present the feature-biased dictionary learning to effectively generate the dictionary of SIFT descriptors. With the learned dictionary, our LCGLC method introduces the locality constraint in classical group lasso problem to encode SIFT descriptors. Furthermore, we apply the Spatial Pyramid Matching (SPM) for the code pooling of microvessel images. Finally, we use Support Vector Machine (SVM) to classify a tissue image as having angiogenesis or not. Comprehensive experiments on the microvessel dataset show that the proposed LCGLC method achieves better performance compared with other representative approaches. [ABSTRACT FROM AUTHOR]

Energy sharing between multiple zero-emission buildings is an important energy management strategy that can reduce the negative effects of energy mismatch. This study proposed a cross-harbour nearshore and offshore ocean renewable energy system connected by submarine cables to support two large-scale zero-emission harbour-to-harbour buildings in the Greater Bay Area. Two scenarios named were proposed based on the absence or presence of intermediate submarine cables and the energy sharing between the two regions. Eight representative renewable energy combinations consisting of wind turbines, tidal stream generators, and floating photovoltaic systems were designed to demonstrate the impact of different renewable energy systems on the overall performance. Two integration policies were designed based on the different renewable energy policies of the two regions, and their characteristics were tested. The impact of the submarine cable capacity on the system performance, the possible installation of batteries at offshore sites to replace some of the submarine cable capacity, and the impact of realistic land prices in Hong Kong and Macau on different renewable energy combinations were also investigated. The results showed that the combination with only the nearshore wind turbine system achieved the best economic performance, with relative net present values of 25.63 × 108 and 30.78 × 108 HKD in the two scenarios when the nearshore and offshore sites had equally cheap land prices. When the true land price was introduced, only the combinations with the all-offshore system had positive relative net present values, while the combinations with nearshore systems all had negative relative net present values. Meanwhile, batteries could not replace the role of submarine cables in this system. Installing intermediate submarine cables and sharing energy between the two regions could significantly improve the energy matching by 8 to 21% and economic performance by 4.44 × 108 to 5.30 × 108 HKD of the system. When all submarine cables were maintained at 40% of their maximum capacity, the energy usage ratio could be guaranteed to be 100% without dumped energy. • Nearshore and offshore ocean-energy-supported zero-emission public buildings. • Co-ordinations of energy sharing between cross-harbour zero emission system. • Energy exchange and sharing supported by submarine cables. • Integrated feed-in tariff policy in HK and MO to support energy exchange. • Impact of the realistic land prices on the performance of zero-emission system. [ABSTRACT FROM AUTHOR]

Controlling complex dynamical systems has garnered significant attention within academic circles in recent decades. While most existing works have focused on closed-loop control schemes with infinite-time durations, this paper introduces a novel finite-time, closed-loop stochastic controller that considers control time, energy consumption, and their dependence on system parameters. This stochastic control technique not only enables finite-time control in chaotic dynamical systems but also facilitates finite-time synchronization in unidirectionally coupled systems. Importantly, our proposed scheme offers several advantages over existing deterministic finite-time controllers, particularly in terms of time and energy consumption. Through numerical experiments utilizing random ecosystems, neural networks, and Lorenz systems, we provide evidence of the effectiveness of our analytical results. We anticipate that this stochastic scheme will find wide-ranging applications in the control of complex dynamical systems and in achieving network synchronization. [ABSTRACT FROM AUTHOR]

Projecting regional rainfall changes in a warmer climate attracts ongoing attention. However, large uncertainty still exists in multi-model projection. In this study, we introduce a bias-corrected method to correct the multi-model projection of changes in East Asian summer monsoon (EASM) rainfall based on the historical and RCP8.5 runs of 25 models from phase 5 of Coupled Model Intercomparison Project. Firstly, the total rainfall changes are separated into the thermodynamic component due to increased specific humidity and the dynamic component due to circulation changes. The thermodynamic component is corrected using the observed present-day rainfall and the increase rate of specific humidity based on the wet-get-wetter mechanism. On the other hand, the dynamic component with the circulation changes is corrected based on a "spatial emergent constraint" method, which is further validated by the perfect model approach. Together, these corrections give an integrated projection for EASM rainfall changes under global warming. Such an approach can improve the signal-to-noise ratio of projection effectively, from the original 0.73 of the multimodel mean to around 1.9. The corrected projection of EASM rainfall changes shows a pronounced increase in southern China, the northwest Pacific and a belt from northern China to northeastern China, and a weak increase in other EASM regions. [ABSTRACT FROM AUTHOR]

The majority of catch per unit effort (cpue) standardizations use generalized linear models (GLMs) or generalized additive models (GAMs). We develop geostatistical models that model catch locations as continuous Gaussian random fields (GRFs) and apply them to standardizing cpue in Australia's Eastern Tuna and Billfish Fishery (ETBF). The results are compared with the traditional GLMs currently used in ETBF assessments as well as GAMs. Specifically, we compare seven models in three groups: two GLMs, two GAMs, and three GRF models. Within each group, one model treats spatial and temporal variables independently, while the other model(s) treats them together as an interaction term. The two spatio-temporal GRF models differ in treating the spatial–temporal interaction: either as a random process or as an autoregressive process. We simulate catch rate data for five pelagic species based on real fishery catch rates so that the simulated data reflect real fishery patterns while the "true" annual abundance levels are known. The results show that within each group, the model with a spatial–temporal interaction term significantly outperforms the other model treating spatial and temporal variables independently. For spatial–temporal models between the three groups, prediction accuracy tends to improve from GLM to GAM and to the GRF models. Overall, the spatio-temporal GRF autoregressive model reduces mean relative predictive error by 43.4% from the GLM, 33.9% from the GAM, and reduces mean absolute predictive error by 23.5% from the GLM and 3.3% from the GAM, respectively. The comparison suggests a promising direction for further developing the geostatistical models for the ETBF. [ABSTRACT FROM AUTHOR]

Graphene is considered to be the core material for the next Industrial Revolution. In this work, graphene oxide (GO) was prepared using a modified Hummers method and, then, reduced to obtain graphene. NH–RGO and VC–RGO were obtained by reducing GO under the same conditions by using hydrazine hydrate and vitamin C, respectively. X-ray diffraction (XRD) spectra were employed to characterize its crystal structure. A scanning electron microscope (SEM) was used to observe the microstructure. The defect degree was determined using Raman spectra. The resistivity of the nitrogen-doped graphene was determined using a four-probe method. The results showed that the preparation time was shorter when vitamin C was used for the GO reduction; further, both the required temperature and the environmental pollution were low in this case. The characteristic peaks of XRD were more obvious than those of NH–RGO and had fewer defects. Raman spectroscopy showed that the G-peak of the prepared VC–RGO was narrower and the D-peak was weaker. Further, the Raman spectroscopy ID/IG was smaller and the structural performance was better. The sheet resistivity of VC–RGO of approximately 0.0163 Ωm was slightly smaller than that of NH–RGO (0.0171 Ωm). Therefore, the proposed method is an ideal method for replacing hydrazine hydrate to produce graphene. [ABSTRACT FROM AUTHOR]

This paper presents, HitGraph, an FPGA framework to accelerate graph processing based on the edge-centric paradigm. HitGraph takes in an edge-centric graph algorithm and hardware resource constraints, determines design parameters and then generates a Register Transfer Level (RTL) FPGA design. This makes accelerator design for various graph analytics transparent and user-friendly by masking internal details of the accelerator design process. HitGraph enables increased data reuse and parallelism through novel algorithmic optimizations, including (1) an optimized data layout that reduces non-sequential external memory accesses, (2) an efficient update merging and filtering scheme to reduce the data communication between the FPGA and external memory, and (3) a partition skipping scheme to reduce redundant edge traversals for non-stationary graph algorithms. Based on our design methodology, we accelerate Sparse Matrix Vector Multiplication (SpMV), PageRank (PR), Single Source Shortest Path (SSSP), and Weakly Connected Component (WCC). Experimental results show that HitGraph sustains a high throughput of 2076 Million Traversed Edges Per Second (MTEPS) for SpMV, 2225 MTEPS for PR, 2916 MTEPS for SSSP, and 3493 MTEPS for WCC, respectively. Compared with highly-optimized multi-core implementations, HitGraph achieves up to 37.9× speedup. Compared with state-of-the-art FPGA frameworks, HitGraph achieves up to 50.7× throughput improvement. [ABSTRACT FROM AUTHOR]

Balanced harvest has been proposed to reduce fishing impact on ecosystems while simultaneously maintaining or even increasing fishery yield. The concept has attracted broad interest, but also received criticisms. In this paper, we examine the theory, modelling studies, empirical evidence, the legal and policy frameworks, and management implications of balanced harvest. The examination reveals unresolved issues and challenges from both scientific and management perspectives. We summarize current knowledge and address common questions relevant to the idea. Major conclusions include: balanced harvest can be expressed in several ways and implemented on multiple levels, and with different approaches e.g. métier based management; it explicitly bridges fisheries and conservation goals in accordance with international legal and policy frameworks; modelling studies and limited empirical evidence reveal that balanced harvest can reduce fishing impact on ecosystem structure and increase the aggregate yield; the extent of balanced harvest is not purely a scientific question, but also a legal and social choice; a transition to balanced harvest may incur short-term economic costs, while in the long-term, economic results will vary across individual fisheries and for society overall; for its application, balanced harvest can be adopted at both strategic and tactical levels and need not be a full implementation, but could aim for a "partially-balanced" harvest. Further objective discussions and research on this subject are needed to move balanced harvest toward supporting a practical ecosystem approach to fisheries. [ABSTRACT FROM AUTHOR]

Objective: Ablation treatment of ventricular arrhythmias can be facilitated by pre-procedure planning aided by electrocardiographic inverse solution, which can help to localize the origin of arrhythmia. Our aim was to improve localization accuracy of the inverse solution for activation originating on the left-ventricular endocardial surface, by using a sparse Bayesian learning (SBL). Methods: The inverse problem of electrocardiography was solved by reconstructing endocardial potentials from time integrals of body-surface electrocardiograms and from patient-specific geometry of the heart and torso for three patients with structurally normal ventricular myocardium, who underwent endocardial catheter mapping that included pace mapping. Complementary simulations using dipole sources in patient-specific geometry were also performed. The proposed method is using sparse property of the equivalent-double-layer (EDL) model of cardiac sources; it employs the SBL and makes use of the spatio-temporal features of the cardiac action potentials. Results: The mean localization error of the proposed method for pooled pacing sites ($n=52$) was significantly smaller ($p=0.0039$) than that achieved for the same patients in the study of Erem et al. Simulation experiments localized the source dipoles ($n=48$) from forward-simulated potentials with the error of 9.4 $\pm$ 4.5 mm (mean $\pm$ SD). Conclusion: The results of our clinical and simulation experiments demonstrate that localization of left-ventricular endocardial activation by means of the Bayesian approach, based on sparse representation of sources by EDL, is feasible and accurate. Significance: The proposed approach to localizing endocardial sources may have important applications in pre-procedure assessment of arrhythmias and in guiding their ablation treatment. [ABSTRACT FROM AUTHOR]

To assess fishing effects on data-poor species, impact can be derived from spatial overlap between species distribution and fishing effort and gear catchability. Here, we enhance the existing sustainability assessment for fishing effect method by estimating gear efficiency and heterogeneous density from sporadic catch data. We apply the method to two chondrichthyan bycatch species, Bight Skate and Draughtboard Shark in Australia, to assess cumulative fishing mortality (F cum) from multiple fisheries. Gear efficiency is estimated from a Bayesian mixture distribution model and fish density is predicted by a generalized additive model. These results, combined with actual fishing effort, allow estimation of fishing mortality in each sector and subsequently, the F cum. Risk is quantified by comparing F cum with reference points based on life history parameters. When only the point estimates were considered, our result indicates that for the period 2009 and 2010 Bight Skate caught in 14 fisheries was at high cumulative risk (F cum ≥ F lim) while Draughtboard Shark caught by 19 fisheries was at low cumulative risk (F cum ≤ F msy). Because of the high cost of conducting cumulative risk assessments, we recommend examining the distribution of fishing effort across fisheries before carrying out the assessments. [ABSTRACT FROM AUTHOR]

Objective: Ablation treatment of ventricular arrhythmias can be facilitated by pre-procedure planning aided by electrocardiographic inverse solution, which can help to localize the origin of arrhythmia. Our aim was to improve localization accuracy of the inverse solution by using a novel Bayesian approach. Methods: The inverse problem of electrocardiography was solved by reconstructing epicardial potentials from 120 body-surface electrocardiograms and from patient-specific geometry of the heart and torso for four patients suffering from scar-related ventricular tachycardia who underwent epicardial catheter mapping, which included pace-mapping. Simulations using dipole sources in patient-specific geometry were also performed. The proposed method, using dynamic spatio-temporal a priori constraints of the solution, was compared with classical Tikhonov methods based on fixed constraints. Results: The mean localization error of the proposed method for all available pacing sites $(n=78)$ was significantly smaller than that achieved by Tikhonov methods; specifically, the localization accuracy for pacing in the normal tissue $(n=17)$ was $\text{8} \pm \text{6}$  mm (mean $\pm$ SD) versus $\text{13} \pm \text{9}$  mm $(P < 0.00001)$ reported in the previous study using the same clinical data and Tikhonov regularization. Simulation experiments further supported these clinical findings. Conclusion: The promising results of in vivo and in silico experiments presented in this study provide a strong incentive to pursuing further investigation of data-driven Bayesian methods in solving the electrocardiographic inverse problem. Significance: The proposed approach to localizing origin of ventricular activation sequence may have important applications in pre-procedure assessment of arrhythmias and in guiding their ablation treatment. [ABSTRACT FROM AUTHOR]

The interaction between the tropical Pacific and Atlantic at the decadal timescale has received widespread attention. This study evaluates the simulation of the interdecadal interaction of the tropical Pacific and Atlantic in 39 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Most of CMIP6 models have a positive correlation with the observations. The high-skill models reproduce well the temporal evolution of the lead–lag correlation. However, the low-skill models cannot reproduce the observed relationship between tropical Pacific decadal variability (TPDV) and tropical Atlantic multidecadal variability (TAMV) relationship, always incorrectly simulating the observed negative correlation when TAMV leads greater than 3 years as a positive correlation. We additionally demonstrate that the intermodel spread in the TPDV–TAMV relationship when TAMV leads is primarily linked to the persistence of TPDV and the background sea surface temperature (SST) in the northern tropical Atlantic. A relatively lower background SST in the north tropical Atlantic suppresses local convection and the remote response to TAMV-related SST anomalies. Consequently, the low-level circulation anomalies in the tropical Pacific connected to TAMV in the low-skill models are not primarily dominated by the observed easterly anomalies. Our research highlights the importance of background SST in the simulation of interbasin interaction and the necessity for model selection before applying CMIP models in relevant studies. [ABSTRACT FROM AUTHOR]

Silicon (Si), as one of the most promising anode candidates, is expected to improve the energy density of Li−ion batteries due to its high specific capacity (≈4200 mAh g−1). However, the cyclic performance of Si anode is unsatisfactory for practical usage due to its inadequate toughness when exceeding the mass loading beyond 2 mg cm−2, which triggers unceasing electrode breakage. Here, a biomimetic Si electrode is created by interconnecting vertically aligned graphene oxide sheets with conductive carbon nanotubes (AGO−Si/C). Unlike reported structures, the AGO−Si/C electrode exhibits superior interlaminar toughness owing to its unique crumpling architecture of reversible interlayer slipping. The elastic structure releases the accumulative lithiation stress of Si nanoparticles to address the degraded inactivation. Thus, the AGO−Si/C electrode shows long−lived cycles by toughening the structure, allowing the fabrication of very thick loading (4.1 mg cm−2) with an impressive areal capacity of 10.0 mAh cm−2. This discovery offers an easily scalable method for graphite/Si anode with high areal capacity that exceeds the commercial−level of 5 mAh cm−2. [ABSTRACT FROM AUTHOR]

We investigated the changes in the East Asian summer monsoon (EASM) rainfall under global warming based on the historical and representative concentration pathway (RCP) 4.5 runs of 18 models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Because the mechanism of rainfall changes under global warming studied in previous studies is widely based on the moisture budget decompositions (MBDs), we first evaluated the applicability of three MBDs for the changes in the EASM rainfall, which are two complete MBDs in Chou et al. (J Clim 22(8):1982-2005; Chou et al., J Clim 22(8):1982-2005, 2009) and Seager et al. (J Clim 23(17):4651-4668; Seager et al., J Clim 23(17):4651-4668, 2010), and the simplified MBD in Huang et al. (Nat Geosci 6(5):357-361; Huang et al., Nat Geosci 6(5):357-361, 2013). The results show that the simplified MBD in Huang et al. (Nat Geosci 6(5):357-361, 2013) is applicable for the EASM rainfall changes, providing an efficient way to study the EASM rainfall changes, which is used in this study. The EASM rainfall changes can be well explained by two components: the thermodynamic component due to the increase in specific humidity and the dynamic component due to the changes in EASM circulation changes. The thermodynamic component is quite robust among the models, whereas the dynamic component with the circulation changes contributes the major uncertainties of the EASM rainfall changes. Moreover, the apparent intermodel difference in the background circulation is another important source of the EASM rainfall changes. The results imply that the background and changes of the EASM circulation are the key factors for further narrowing the uncertainties of the projected EASM rainfall changes. [ABSTRACT FROM AUTHOR]

Abstract: Background and objectives: Catheter ablation of ventricular tachycardia (VT) may include induction of VT and localization of VT‐exit site. Our aim was to assess localization performance of a novel statistical pace‐mapping method and compare it with performance of an electrocardiographic inverse solution. Methods: Seven patients undergoing ablation of VT (4 with epicardial, 3 with endocardial exit) aided by electroanatomic mapping underwent intraprocedural 120‐lead body‐surface potential mapping (BSPM). Two approaches to localization of activation origin were tested: (1) A statistical method, based on multiple linear regression (MLR), which required only the conventional 12‐lead ECG for a sufficient number of pacing sites with known origin together with patient‐specific geometry of the endocardial/epicardial surface obtained by electroanatomic mapping; and (2) a classical deterministic inverse solution for recovering heart‐surface potentials, which required BSPM and patient‐specific geometry of the heart and torso obtained via computed tomography (CT). Results: For the MLR method, at least 10–15 pacing sites with known coordinates, together with their corresponding 12‐lead ECGs, were required to derive reliable patient‐specific regression equations, which then enabled accurate localization of ventricular activation with unknown origin. For 4 patients who underwent epicardial mapping, the median of localization error for the MLR was significantly lower than that for the inverse solution (10.6 vs. 27.3 mm, P  =  0.034); a similar result held for 3 patients who underwent endocardial mapping (7.7 vs. 17.1 mm, P  =  0.017). The pooled localization error for all epicardial and endocardial sites was also significantly smaller for the MLR compared with the inverse solution (P  =  0.005). Conclusions: The novel pace‐mapping approach to localizing the origin of ventricular activation offers an easily implementable supplement and/or alternative to the preprocedure inverse solution; its simplicity makes it suitable for real‐time applications during clinical catheter‐ablation procedures. [ABSTRACT FROM AUTHOR]

Accurate evaluation of cumulative plastic strains in subgrade soil is crucial for road designs and maintenance. Roads in seasonally frozen regions undergo several freeze–thaw (F–T) cycles annually, resulting in considerable deterioration of soil properties. Under the repeated cyclic loading of moving vehicles, distinct residual deformation occurs in the thawed subgrade. To study the influence of F–T cycles on the cumulative strain characteristics, cyclic triaxial tests were conducted on subgrade clay under the most unfavourable conditions and in situ measured dynamic stress amplitudes. The test results revealed that the cumulative strain (ε ap) increased with the dynamic stress amplitude. When the dynamic stress amplitude increased from 46 kPa to 70 kPa, ε ap of unfrozen and F-T specimens increased by more than 14 and five times, respectively. The axial deformation of clay is sensitive to the number of F–T cycles. The freeze-thaw effect was greatest in the first cycle, with ε ap increasing from 1.42% to 5.63% at the end of the test (dynamic stress amplitude of 46 kPa). In subsequent cycles, relatively small deformations accumulated. A particle swarm optimisation–back-propagation-based (PSO-BP) model for predicting the accumulative plastic strain of clay was developed based on experimental results. In this model, the influences of the F–T process and loading cycles were considered. The prediction performance of the proposed model was validated and compared with that of traditional regression models. The predictions were in good agreement with the experimental data and satisfied the deterioration law for clays subjected to F–T cycles. The maximum error of the PSO–BP model was 2.75%. • Cyclic triaxial tests using the in situ measured subgrade pressure. • Accumulative strain of freezing–thawing clay under the most unfavourable conditions. • Particle swarm optimisation–back-propagation-based accumulative plastic strain model. [ABSTRACT FROM AUTHOR]

Different subtypes of non-small cell lung cancer (NSCLC) have distinct sites of origin, histologies, genetic and epigenetic changes. In this study, we explored the mechanisms of ECT2 dysregulation and compared its prognostic value in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In addition, we also investigated the enrichment of ECT2 co-expressed genes in KEGG pathways in LUAD and LUSC. Bioinformatic analysis was performed based on data from the Cancer Genome Atlas (TCGA)-LUAD and TCGA-LUSC. Results showed that ECT2 expression was significantly upregulated in both LUAD and LUSC compared with normal lung tissues. ECT2 expression was considerably higher in LUSC than in LUAD. The level of ECT2 DNA methylation was significantly lower in LUSC than in LUAD. ECT2 mutation was observed in 5% of LUAD and in 51% of LUSC cases. Amplification was the predominant alteration. LUAD patients with ECT2 amplification had significantly worse disease-free survival (p = 0.022). High ECT2 expression was associated with unfavorable overall survival (OS) (p<0.0001) and recurrence-free survival (RFS) (p = 0.001) in LUAD patients. Nevertheless, these associations were not observed in patients with LUSC. The following univariate and multivariate analysis showed that the high ECT2 expression was an independent prognostic factor for poor OS (HR: 2.039, 95%CI: 1.457–2.852, p<0.001) and RFS (HR: 1.715, 95%CI: 1.210–2.432, p = 0.002) in LUAD patients, but not in LUSC patients. Among 518 genes co-expressed with ECT2 in LUAD and 386 genes co-expressed with ECT2 in LUSC, there were only 98 genes in the overlapping cluster. Some of the genes related KEGG pathways in LUAD were not observed in LUSC. These differences might help to explain the different prognostic value of ECT2 in LUAD and LUSC, which are also worthy of further studies. [ABSTRACT FROM AUTHOR]

The degree to which a stock is depleted is one of the most important quantities in fisheries management because it is used to quantify the success of management and to inform management responses. However, stock depletion is extremely difficult to estimate, particularly with limited data. Using the RAM Legacy database, we developed a boosted regression tree ( BRT) model to correlate depletion with a range of predictors calculated from catch data, making the model usable for many fisheries worldwide. The most important predictors were found to be catch trends obtained from linear regressions of scaled catch on time, including regression coefficients for the whole catch time series, the subseries before and after the maximum catch, and in recent years. Eight predictors explain about 80% of variation in depletion. There is a correlation of .5 between measured levels of depletion and the predictions of the BRT model. Predictions are less biased when the stock is fished down below half of the carrying capacity. The BRT model outperforms comparable existing catch-based depletion estimators and could be used to provide priors for depletion for data-poor stock assessment methods, or used more directly to provide estimates of the probability that depletion is below a given threshold value. [ABSTRACT FROM AUTHOR]

The matching ability between stent and balloon is an important property to the trackability and crossibility of delivering system; it's also influence the flexibility of operation in clinic. In this work, the low-temperature plasma sputtering method was employed to prepare nano-structure on balloon surface, the matching properties were investigated via the removing force, compliance and aging test; the micro-morphous was also characterized by scanning electron microscope. The result indicates that the removing force of the sputtered balloon is obviously increased comparing to un-treated that, and the compliance of both balloon catheters is similar, but the lower-temperature plasma treated balloon is more preferable than that of untreated that through aging test results. The distribution of stent struts on balloon surface is more uniform than untreated surface, and the deformation and fold of treated surface wasn't found, which indicates that the matching ability between stent and balloon would be enhance via low-temperature plasma sputtering. [ABSTRACT FROM PUBLISHER]