Universal Domain Adaptation via Compressive Attention Matching

Universal domain adaptation (UniDA) aims to transfer knowledge from the source domain to the target domain without any prior knowledge about the label set. The challenge lies in how to determine whether the target samples belong to common categories. The mainstream methods make judgments based on the sample features, which overemphasizes global information while ignoring the most crucial local objects in the image, resulting in limited accuracy. To address this issue, we propose a Universal Attention Matching (UniAM) framework by exploiting the self-attention mechanism in vision transformer to capture the crucial object information. The proposed framework introduces a novel Compressive Attention Matching (CAM) approach to explore the core information by compressively representing attentions. Furthermore, CAM incorporates a residual-based measurement to determine the sample commonness. By utilizing the measurement, UniAM achieves domain-wise and category-wise Common Feature Alignment (CFA) and Target Class Separation (TCS). Notably, UniAM is the first method utilizing the attention in vision transformer directly to perform classification tasks. Extensive experiments show that UniAM outperforms the current state-of-the-art methods on various benchmark datasets

Investigation on Actuating Pressure Gradient of Low Permeability Reservoir

Due to the presence of actuating pressure of low permeability reservoir, researching on actuating pressure gradient of low permeability reservoir is necessary. While actuating pressure gradient is relevant to permeability and porosity, it can be obtained through laboratory experiments, well testing interpretation method and theory derivation combined with practical application method. The results of a large number of laboratory experiments show that actuating pressure is related to permeability. The greater the permeability is, the smaller the actuating pressure is. They both present the similar hyperbolic relationship; the greater the viscosity of the oil is, the greater the actuating pressure is. Here, we get the actuating pressure gradient formula through the method of theory derivation combined with practical application, meanwhile we put forward the relationship between actuating pressure gradient and permeability, porosity and viscosity.Key words: Low permeability reservoir; Actuating pressure gradient; Porosity; Fluid viscosit

Water Drive Characteristic Curve Theory of Low Permeability Reservoir

The so-called water flooding characteristic curve refers to the oilfield water injection (or natural water drive) development process, a relationship between curve cumulative oil production, cumulative water production and accumulation of fluid production. These curves have been widely used for water injection development of dynamic and recoverable reserves forecast. After many years of practical application, summed up the four kinds of water drive characteristic curve, they have a good practical significance. Recoverable reserves are important indicators of field development and also the main basis for planning and design, while the application of water flooding characteristic curve can be predicted oil recoverable reserves. Four kinds of water flooding characteristics discussed above curve are mainly applied in high-permeability oil field, which did not consider starting pressure. In fact we should consider the impact of low permeability oilfield actuating pressure gradient on the water content. Here, we deduce the formulation considering the actuating pressure.Key words: Low permeability; Water flooding; Actuating pressur

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization

Domain generalization (DG) is a prevalent problem in real-world applications, which aims to train well-generalized models for unseen target domains by utilizing several source domains. Since domain labels, i.e., which domain each data point is sampled from, naturally exist, most DG algorithms treat them as a kind of supervision information to improve the generalization performance. However, the original domain labels may not be the optimal supervision signal due to the lack of domain heterogeneity, i.e., the diversity among domains. For example, a sample in one domain may be closer to another domain, its original label thus can be the noise to disturb the generalization learning. Although some methods try to solve it by re-dividing domains and applying the newly generated dividing pattern, the pattern they choose may not be the most heterogeneous due to the lack of the metric for heterogeneity. In this paper, we point out that domain heterogeneity mainly lies in variant features under the invariant learning framework. With contrastive learning, we propose a learning potential-guided metric for domain heterogeneity by promoting learning variant features. Then we notice the differences between seeking variance-based heterogeneity and training invariance-based generalizable model. We thus propose a novel method called Heterogeneity-based Two-stage Contrastive Learning (HTCL) for the DG task. In the first stage, we generate the most heterogeneous dividing pattern with our contrastive metric. In the second stage, we employ an invariance-aimed contrastive learning by re-building pairs with the stable relation hinted by domains and classes, which better utilizes generated domain labels for generalization learning. Extensive experiments show HTCL better digs heterogeneity and yields great generalization performance.Comment: This paper has been accepted by KDD 202

Designing Functional Carriage of High-Speed Medical Train – Systematic Analysis and Evaluation of Tasks, Functions and Flow Routes

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains

Di’ao Xinxuekang Capsule, a Chinese Medicinal Product, Decreases Serum Lipids Levels in High-Fat Diet-Fed ApoE–/– Mice by Downregulating PCSK9

Numerous risk factors are responsible for the development of atherosclerosis, for which an increased serum level of low-density lipoprotein cholesterol (LDL-C) is a driving force. By binding to the low-density lipoprotein cholesterol receptor (LDLR) and inducing LDLR degradation, proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a key role in cholesterol homeostasis regulation. The inducement of PCSK9 expression is also an important reason for statin intolerance. The Di’ao Xinxuekang (DXXK) capsule extracted from Dioscorea nipponica Makino is a well-known traditional Chinese herbal medicinal product used in atherosclerotic cardiovascular disease. Although DXXK has been widely used in atherosclerotic cardiovascular treatment for nearly 30 years, studies on the potential mechanisms of the lipid-lowering effect are very limited. The purpose of the present study was to demonstrate the possible involvement of the PCSK9/LDLR signaling pathway in the lipid-lowering and antiatherosclerotic effect of DXXK in high-fat diet-fed ApoE–/– mice. The results showed that DXXK treatment alleviated hyperlipidemia, fat accumulation, and atherosclerosis formation in ApoE–/– mice. Furthermore, changes in the expression of PCSK9 mRNA in liver tissue and the circulating PCSK9 level in ApoE–/– mice were both reversed after DXXK treatment, and upregulation of LDLR in the liver was also detected in the protein level in DXXK-treated mice. Our study is the first to show that DXXK could alleviate lipid disorder and ameliorate atherosclerosis with downregulation of the PCSK9 in high-fat diet-fed ApoE–/– mice, suggesting that DXXK may be a potential novel therapeutic treatment and may support statin action in the treatment of atherosclerosis

Designing Functional Carriage of High-Speed Medical Train – Systematic Analysis and Evaluation of Tasks, Functions and Flow Routes

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains

Reducing vulnerability and precarity of low-skilled women in short-term migration from the global south: Key policy recommendations for the G-20

Women migrant workers make significant contributions to the global economy, but face risks of being subject to forced labour and trafficking, heightened by COVID-19. As women migrate from low-income to G20 countries to undertake key service functions, the G20 should uphold women’s human rights and fair work conditions. G20 countries can support migrant women workers through technical and information exchange, giving voice, and partnership with source countries to certify migration agents, provide social assistance and establish reintegration programmes. G20 can also support migrants in their own countries by providing standard employment contracts, securing access to health services and ensuring accessible redress mechanisms

Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans

It is well established that somatic genomic changes can influence phenotypes in cancer, but the role of adaptive changes in developmental disorders is less well understood. Here we have used next-generation sequencing approaches to identify de novo heterozygous mutations in sterile α motif domain–containing protein 9 (SAMD9, located on chromosome 7q21.2) in 8 children with a multisystem disorder termed MIRAGE syndrome that is characterized by intrauterine growth restriction (IUGR) with gonadal, adrenal, and bone marrow failure, predisposition to infections, and high mortality. These mutations result in gain of function of the growth repressor product SAMD9. Progressive loss of mutated SAMD9 through the development of monosomy 7 (–7), deletions of 7q (7q–), and secondary somatic loss-of-function (nonsense and frameshift) mutations in SAMD9 rescued the growth-restricting effects of mutant SAMD9 proteins in bone marrow and was associated with increased length of survival. However, 2 patients with –7 and 7q– developed myelodysplastic syndrome, most likely due to haploinsufficiency of related 7q21.2 genes. Taken together, these findings provide strong evidence that progressive somatic changes can occur in specific tissues and can subsequently modify disease phenotype and influence survival. Such tissue-specific adaptability may be a more common mechanism modifying the expression of human genetic conditions than is currently recognized