Multi-layered Semantic Representation Network for Multi-label Image Classification

Multi-label image classification (MLIC) is a fundamental and practical task, which aims to assign multiple possible labels to an image. In recent years, many deep convolutional neural network (CNN) based approaches have been proposed which model label correlations to discover semantics of labels and learn semantic representations of images. This paper advances this research direction by improving both the modeling of label correlations and the learning of semantic representations. On the one hand, besides the local semantics of each label, we propose to further explore global semantics shared by multiple labels. On the other hand, existing approaches mainly learn the semantic representations at the last convolutional layer of a CNN. But it has been noted that the image representations of different layers of CNN capture different levels or scales of features and have different discriminative abilities. We thus propose to learn semantic representations at multiple convolutional layers. To this end, this paper designs a Multi-layered Semantic Representation Network (MSRN) which discovers both local and global semantics of labels through modeling label correlations and utilizes the label semantics to guide the semantic representations learning at multiple layers through an attention mechanism. Extensive experiments on four benchmark datasets including VOC 2007, COCO, NUS-WIDE, and Apparel show a competitive performance of the proposed MSRN against state-of-the-art models

HEADLAND TURNING CONTROL METHOD SIMULATION OF AUTONOMOUS AGRICULTRUAL MACHINE BASED ON IMPROVED PURE PURSUIT MODEL

Abstract: According to the features of headland turning, new path planning and headland turning control algorithms for autonomous agricultural machine were presented in this paper. The turning path planning considered both the minimum turning radius and headland space was created by applying three straight lines. A path tracking algorithm based on the improved pure pursuit model was also proposed. This study used the BP neutral network to implement the dynamical look-ahead distance control for the improved pure pursuit model. Based on simplified bicycle kinematics model parameters, MATLAB/Simulink simulation results showed that the path planning algorithm were simple, occupied small headland space while still had a high tracking accuracy. The control method is feasible and practical

Numerical simulation of thermal stratification in Lake Qiandaohu using an improved WRF-Lake model

Lake thermal stratification is important for regulating lake environments and ecosystems and is sensitive to climate change and human activity. However, numerical simulation of coupled hydrodynamics and heat transfer processes in deep lakes using one-dimensional lake models remains challenging because of the insufficient representation of key parameters. In this study, Lake Qiandaohu, a deep and warm monomictic reservoir, was used as an example to investigate thermal stratification via an improved parameterization scheme of the Weather Research and Forecast (WRF)-Lake. A comparison with in situ observations demonstrated that the default WRF-Lake model was able to simulate well the seasonal variation of the lake thermal structure. However, the simulations exhibited cold biases in lake surface water temperature (LSWT) throughout the year while generating weaker stratification in summer, thereby leading to an earlier cooling period in autumn. With an improved parameterization (i.e., via determination of initial lake water temperature profiles, light extinction coefficients, eddy diffusion coefficients and surface roughness lengths), the modified WRF-Lake model was able to better simulate LSWT and thermal stratification. Critically, employing realistic initial conditions for lake water temperature is essential for producing realistic hypolimnetic water temperatures. The use of time-dependent light extinction coefficients resulted in a deep thermocline and warm LSWT. Enlarging eddy diffusivity led to stronger mixing in summer and further influenced autumn cooling. The parameterized surface roughness lengths mitigated the excessive turbulent heat loss at the lake surface, improved the model performance in simulating LSWT, and generated a warm mixed layer. This study provides guidance on model parameterization for simulating the thermal structure of deep lakes and advances our understanding of the strength and revolution of lake thermal stratification under seasonal changes

Shape Stability of Metallic Nanoplates: A Molecular Dynamics Study

Abstract(#br)Metallic nanoplates have attracted widespread interests owing to their functional versatility, which relies heavily on their morphologies. In this study, the shape stability of several metallic nanoplates with body-centered-cubic (bcc) lattices is investigated by employing molecular dynamics simulations. It is found that the nanoplate with (110) surface planes is the most stable compared to the ones with (111) and (001) surfaces, and their shapes evolve with different patterns as the temperature increases. The formation of differently orientated facets is observed in the (001) nanoplates, which leads to the accumulation of shear stress and thus results in the subsequent formation of saddle shape. The associated shape evolution is quantitatively characterized. Further..

Metformin Treatment is Associated with Mortality in Patients with Type 2 Diabetes and Chronic Heart Failure in the Intensive Care Unit: A Retrospective Cohort Study

Objective: Patients receiving intensive care often have diabetes mellitus (DM) together with chronic heart failure (CHF). In these patients, the use of metformin in intensive care is controversial. This study was aimed at assessing the mortality rates of patients with DM and CHF treated with metformin. Methods: The Medical Information Mart for Intensive Care database was used to identify patients with type 2 diabetes mellitus (T2DM) and CHF. A 90-day mortality comparison was conducted between patients who were and were not administered metformin. Propensity score matching analysis and multivariable Cox proportional hazard regression were used to ensure the robustness of our results. Results: A total of 2153 patients (180 receiving metformin and 1973 not receiving metformin) with T2DM and CHF were included in the study. The 90-day mortality rates were 30.5% (601/1971) and 5.5% (10/182) in the non-metformin and metformin groups, respectively. In the propensity score matching analyses, metformin use was associated with a 71% lower 90-day mortality (hazard ratio, 0.29; 95% confidence interval, 0.14–0.59; P < 0.001). The results were insensitive to change when sensitivity analyses were performed. Conclusion: Metformin treatment may decrease the mortality risk in critically ill patients with T2DM and CHF in the intensive care unit

Pancreatic cancer mortality trends attributable to high fasting blood sugar over the period 1990–2019 and projections up to 2040

BackgroundPancreatic cancer (PC) is a prevalent malignancy within the digestive system, with diabetes recognized as one of its well-established risk factors.MethodsData on PC mortality attributed to high fasting blood sugar were retrieved from the Global Burden of Disease (GBD) study 2019 online database. To assess the temporal trends of PC burden attributable to high fasting plasma glucose (HFPG), estimated annual percentage changes (EAPCs) for age-standardized death rates (ASDRs) between 1990 and 2019 were determined using a generalized linear model. Furthermore, a Bayesian age-period-cohort (BAPC) model using the integrated nested Laplacian approximation algorithm was employed to project the disease burden over the next 20 years.ResultsGlobally, the crude death number of PC attributable to HFPG almost tripled (from 13,065.7 in 1990 to 48,358.5 in 2019) from 1990 to 2019, and the ASDR increased from 0.36/100,000 to 0.61/100,000 with an EAPC of 2.04 (95% CI 1.91–2.16). The population aged ≥70 years accounted for nearly 60% of total deaths in 2019 and experienced a more significant increase, with the death number increasing approximately fourfold and the ASDR increasing annually by 2.65%. In regions with different sociodemographic indexes (SDIs), the highest disease burden was observed in the high-SDI region, whereas more pronounced increasing trends in ASDR were observed in the low to middle-SDI, low-SDI, and middle-SDI regions. Additionally, a significantly negative association was found between EAPCs and ASDRs of PC attributable to HFPG from 1990 to 2019. Moreover, the BAPC model predicts that ASDR and age-standardized disability-adjusted life-years (DALYs) rate for PC attributed to HFPG was projected to increase obviously for men and women from 2019 to 2040.ConclusionsThe burden of PC attributed to HFPG has increased globally over the past three decades, with the elderly population and high-SDI regions carrying a relatively greater disease burden, but more adverse trends observed in low-SDI areas. Furthermore, the burden is projected to continue increasing over the next 20 years. Hence, more tailored prevention methodologies should be established to mitigate this increasing trend

ceRNA crosstalk mediated by ncRNAs is a novel regulatory mechanism in fish sex determination and differentiation

Competing endogenous RNAs (ceRNAs) are vital regulators of gene networks in mammals. The involvement of noncoding RNAs (ncRNAs) as ceRNA in genotypic sex determination (GSD) and environmental sex determination (ESD) in fish is unknown. The Chinese tongue sole, which has both GSD and ESD mechanisms, was used to map the dynamic expression pattern of ncRNAs and mRNA in gonads during sex determination and differentiation. Transcript expression patterns shift during the sex differentiation phase, and ceRNA modulation occurs through crosstalk of differentially expressed long ncRNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and sex-related genes in fish. Of note was the significant up-regulation of a circRNA from the sex-determining gene dmrt1 (circular RNA dmrt1) and a lncRNA, called AMSDT (which stands for associated with male sex differentiation of tongue sole) in Chinese tongue sole testis. These two ncRNAs both share the same miRNA response elements with gsdf, which has an up-regulated expression when they bind to miRNA cse-miR-196 and concurrent down-regulated female sex-related genes to facilitate testis differentiation. This is the first demonstration in fish that ceRNA crosstalk mediated by ncRNAs modulates sexual development and unveils a novel regulatory mechanism for sex determination and differentiation.info:eu-repo/semantics/publishedVersio