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What is analytical jurisprudence? The mainstream understanding is that it is a descriptive project of investigating the nature of law by revealing necessary truths about law through the method of conceptual analysis. In recent years this mainstream understanding has been challenged on two fronts: some philosophers argue that jurisprudence is inherently informed by moral-political values and hence cannot be purely descriptive. From their perspective, analytical jurisprudence is political philosophy in disguise. Meanwhile, others have challenged the method of conceptual analysis, arguing that this methodology is unviable because it is either uninterestingly lexicographical or epistemically bankrupt. From their perspective, analytical jurisprudence is legal sociology poorly done from the armchair. In this dissertation I try to defend the mainstream understanding of analytical jurisprudence based on a pragmatist approach, which characterizes analytical jurisprudence as a project of revealing the actual linguistic rules governing the application of a given community’s concept of law, whose meaning is encapsulated in the concept’s inferential role. This pragmatist picture provides several benefits that advance our understanding of analytical jurisprudence as a distinctly philosophical enterprise: first, it explains why analytical jurisprudence is a semantic project but not a definitional one; secondly, it clarifies how the semantic project of conceptual analysis can be both descriptive and evaluative, and thirdly, it preserves the autonomy of analytical jurisprudence by carving out a space for conceptual inquiries that cannot be subsumed under either legal sociology or political philosophy. Moreover, when applied to the domain of internal legal statements, this pragmatist approach allows us to vindicate law’s objectivity, thereby fending off the implausible legal realist thesis that legal statements cannot be objectively true or false, and it allows us to do so without endorsing the implausible metaphysical realist thesis that legal statements can be objectively true only if they correspond to a mind-independent reality.

We formulate a new criterion of the asymptotic stability for some non-equicontinuous Markov semigroups, the so-called eventually continuous semigroups. In particular, we provide a non-equicontinuous Markov semigroup example with essential randomness, which is asymptotically stable.

Power system oscillation has caused many serious accidents in renewable energy grid connection system. The concept of observability and controllability in control theory has been widely applied to power system oscillation study. In this paper, observability metric (OM) and controllability metric (CM) are defined from the perspective of oscillation modes, acting as a novel quantification method to quantify the observability and controllability of power system with distinct or repeated eigenvalues. Furthermore, in order to compare the reflection degree and control effect of signals in different oscillation modes, the mode comprehensive observability metric (MCOM) and comprehensive controllability metric (MCCM) are proposed. The proposed method shows clearer relationship between controllability/observability and oscillation modes by combining the information of conjugate eigenvalues together. The advantages of metrics are illustrated by comparing with theoretical derivations and calculation results of three traditional methods: participation factor, residue method and geometric measures. Finally, the metrics are applied to a subsynchronous damping controller (SSDC) design for better performance in oscillation monitoring and suppression. With the small-signal model and corresponding time-domain simulation, the effectiveness of the proposed method is verified.

We investigate the relation between the e-property and the eventual continuity, or called the asymptotic equicontinuity, which is a generalization of the e-property. We prove that, for any discrete-time or strongly continuous continuous-time eventually continuous Markov-Feller semigroup with an ergodic measure, if the interior of the support of the ergodic measure is nonempty, then the e-property is satisfied on the interior of the support. In particular, it implies that, restricted on the support of each ergodic measure, the e-property and the eventual continuity are equivalent for the discrete-time and the strongly continuous continuous-time Markov-Feller semigroups.

Additional file 1: Figure S1. Examples of Q–Q plots in four tail scenarios with respect to the normal distribution’s tails. Figure S2. Examples of Q–Q plots in unimodal and bimodal scenarios. Figure S3. Flow chart of selecting the meta-analyses from the Cochrane Library.

Given a subshift of finite type and a finite set $\mathcal{W}$ of admissible words, we consider two types of points in the shift space. One are the admissible sequences in which the words in $\mathcal{W}$ appear frequently, and the other are those in which arbitrarily long consecutive repetitions of words in $\mathcal{W}$ cannot appear. We investigate the $u$-dimension of the set of such types of points at which the Birkhoff sums of some given function are bounded. The results have a natural implication on the upper and lower \holder derivatives of the cumulative distribution function of a Gibbs measure on an interval.

The high-quality development and technological upgrading of the tobacco industry put forward higher requirements for the overall quality of talents. In the context of the increasing popularity of blended teaching, in order to help teachers, major in tobacco, tomake better teaching decisions in the teaching process, guide college students majoring in tobacco to better complete their studies and provide timely warnings for students’ unhealthy conditions, this article proposes a method to assist teachers in teaching decision-making based on student portraits constructed based on online learning big data. First, collect basic student information and student learning information from the online learning platform. Secondly, preprocess of the data, delete data and normalize dense data. Then, collect and classify student information to form a portrait of basic student information, a portrait of learning achievements, a portrait of learning active level and a portrait of learning status. Analyze the portrait to guide and assist students in their learning and to give early warning of bad learning conditions. At last, analyze the student portraits according to different rules and put forward corresponding suggestions according to the characteristics of different groups of college students. According to the learning situation of learners majoring in tobacco, the article constructs the student portrait label system and portrait model. According to the constructed student portrait, it puts forward learning suggestions for individual students and student groups respectively. In the field of tobacco teaching, it has certain reference significance and application value in providing decision-making reference for differentiated and individualized teaching and assisting teaching decision-making.

IntroductionAge is an established risk factor for neurodegenerative disorders. Aging-related cognitive decline is a common cause of memory impairment in aging individuals, in which hippocampal synaptic plasticity and hippocampus-dependent memory formation are damaged. Circular RNAs (circRNAs) have been reported in many cognitive disorders, but their role in aging-related memory impairment is unclear.Methods: In this study, we aimed to investigate the effects of circ-Vps41 on aging-related hippocampus-dependent memory impairment and explore the potential mechanisms. Here, D-galactose was used to produce a conventional aging model resulting in memory dysfunction.ResultsCirc-Vps41 was significantly downregulated in D-galactose-induced aging in vitro and in vivo. The overexpression of circ-Vps41 could upregulate synaptophysin (Syp), thereby promoting the synaptic plasticity and alleviating cognitive impairment in aging mice. Mechanistically, we found that circ-Vps41 upregulated Syp expression by physically binding to miR-24-3p. Moreover, the miR-24-3p mimics reversed the circ-Vps41 overexpression-induced increase in Syp expression.DiscussionOverexpression of circ-Vps41 alleviated the synaptic plasticity and memory dysfunction via the miR-24-3p/Syp axis. These findings revealed circ-Vps41 regulatory network and provided new insights into its potential mechanisms for improving aging-related learning and memory impairment.

In this study, an oomycete strain FQ01 of Phytophthora nicotianae, which could cause destructive postharvest disease, was isolated. At present, chemical fungicides are the main reagents used for controlling Phytophthora diseases. It is necessary to find new control techniques that are environmentally friendly. The biocontrol activity of Hanseniaspora uvarum MP1861 against P. nicotianae FQ01 was therefore investigated. Our results revealed that the volatile organic compounds (VOCs) released by the yeast strain MP1861 could inhibit the development of P. nicotianae FQ01. The major component of the VOCs produced by the yeast strain MP1861 was identified to be ethyl acetate (70.8%). Biocontrol experiments showed that Phytophthora disease in tomato fruit could be reduced by 95.8% after the yeast VOCs treatment. Furthermore, ethyl acetate inhibited the mycelial growth of the oomycete strain FQ01, and damaged the pathogen cell membrane. This paper describes the pioneering utilization of the yeast strain MP1861 for biocontrol of postharvest fruit rot in tomato caused by P. nicotianae.

Personalized federated learning considers learning models unique to each client in a heterogeneous network. The resulting client-specific models have been purported to improve metrics such as accuracy, fairness, and robustness in federated networks. However, despite a plethora of work in this area, it remains unclear: (1) which personalization techniques are most effective in various settings, and (2) how important personalization truly is for realistic federated applications. To better answer these questions, we propose Motley, a benchmark for personalized federated learning. Motley consists of a suite of cross-device and cross-silo federated datasets from varied problem domains, as well as thorough evaluation metrics for better understanding the possible impacts of personalization. We establish baselines on the benchmark by comparing a number of representative personalized federated learning methods. These initial results highlight strengths and weaknesses of existing approaches, and raise several open questions for the community. Motley aims to provide a reproducible means with which to advance developments in personalized and heterogeneity-aware federated learning, as well as the related areas of transfer learning, meta-learning, and multi-task learning., 40 pages, 10 figures, 7 tables. EMNIST and Landmarks fine-tuning results are corrected in (and after) v5. Code: https://github.com/google-research/federated/tree/master/personalization_benchmark

Yan Lin,1,* Xing Gao,1,* Ziyu Liu,1 Zhihui Liu,1 Yongqiang Li,1 Rong Liang,1 Zhiling Liao,2 Jiazhou Ye3 1Department of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China; 2Department of Pathology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China; 3Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Rong Liang, Department of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, 530021, People’s Republic of China, Tel +86 771 5335155, Fax +86 771 5335155, Email liangrong@gxmu.edu.cn Jiazhou Ye, Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, 530021, People’s Republic of China, Tel +86 771 5331211, Fax +86 771 5331211, Email yejiazhou@gxmu.edu.cnAbstract: Low-grade myofibroblastic sarcoma (LGMS) is a rare, poorly differentiated, malignant tumor. The disease mainly occurs in the head and neck and rarely metastasizes at any age. Currently, there is no consensus regarding the treatment of metastatic LGMS. Here, we report the case of a 45-year-old man who was admitted to our hospital with cough for two weeks and abdominal pain for one week. Preoperative computed tomography revealed a large mass (116× 35 mm) in both the lungs and jejunal mass (maximum diameter, 32 mm). The tumor was excised, and immunohistochemical staining was positive for SMA and CD117 and negative for desmin and CD34, indicating a case of LGMS. The patient was effectively treated with apatinib (250 mg/day) after failure of imatinib, liposomal doxorubicin, and ifosfamide. The progression-free survival time was 8.5 months, and the overall survival time was 17 months after treatment with apatinib. No grade 3 or 4 side effects were observed, except hand-foot syndrome. Whole-exome sequencing (WES) and RNA sequencing (RNA-seq) were performed on the patient’s jejunal tumor and para-cancerous tissue samples, and bioinformatics analysis was performed on the results. WES identified five mutations in MKI67, OR2J2, EPPK1, FCGBP, and OR10G4. RNA-seq revealed that 1422 genes were upregulated and 1890 genes were downregulated. The differentially expressed genes were mainly enriched in the phosphatidylinositol 3-kinase (PI3K) signaling pathway, neuroactive ligand-receptor interaction signaling pathway, and cAMP signaling pathway. Our study indicated that apatinib may be a potential novel and effective treatment for LGMS.Keywords: low-grade myofibroblastic sarcoma, apatinib, VEGFR-PI3K/Akt signaling pathway, whole-exome sequencing, RNA sequencing

As e-commerce continues to develop, online shopping is becoming more and more popular, and community e-commerce platform emerges as the times require. To make the participants in the supply chain of community e-commerce platform play a greater role in value creation, the supply chain of community e-commerce platform can get more benefits. This paper studies the psychology of all participants in the supply chain of community e-commerce platform, so as to establish the value creation mechanism of community e-commerce platform. Through the research, it is found that by studying the psychology of the two main participants in the supply chain of community-based online store, community e-commerce platform and community leader, and considering whether they will do their best to participate in value co-creation, a two-party evolutionary game model is constructed. By calculating the dynamic replication equation, the influence of the psychology of the participants in the supply chain of the community-based online store on the supply chain revenue of the community-based online store is obtained, and the evolutionary trend of both parties in the game is simulated by Matlab. It is concluded that the key factors that affect the co-creation of the value of a community-based online store supply chain are the proportion of increased income, the cost of participating in co-creation of value, and the purchasing power of consumers brought by participating with both parties. Finally, some suggestions and countermeasures are put forward through the analysis of simulation results.

With the aging of China’s population and the expansion of household debt, the health of the elderly has become an important social issue. Based on the 2018 China Family Panel Studies (CFPS) database, we explored the impact of household debt on the health of older adults and the mechanism of transmission. The Oprobit and IV-Oprobit models were employed for our analysis. Results: (1) Household debt had a significant negative impact on both the physical and mental health of older adults. (2) Female older adults were more sensitive to the impact of household debt. Additionally, a higher education level led to an increasing impact of debt on mental health, but physical health was only affected in the low-education group. (3) The impact of household debt had an inverted U-shape relationship with household income, indicating that, as household income increases, the impact on health level first rises and then reduces after peaking at a middling level of income. (4) According to the mechanism analysis, household debt affects the health of the elderly by causing them to return to work and reducing their medical expenditures. Considering the above conclusions, we put forward some policy implications to alleviate the health problems of the elderly.

The purpose of this paper is to discover the impacts of contradictory factors in the application of agricultural residue with sustainable biofuel benefits. Based on the Life cycle assessment (LCA) approach, the quantitative LCA assessment model and approach have been established, coupling upstream cultivation and downstream jet biofuel product, which would benefit agriculture residue choice. The LCA model investigated the effects of interaction factors on energy consumption, including land release and agriculture residue use change. The computational framework of the LCA model is classified into three sub-models, including the cultivation and harvesting model, the refining process and distribution model, and the flight model. According to uncertainty analysis by the LCA model, the positive energy gains have been conducted at a wide range of hydrogen production and methanol production. The application model is represented by six types of typical aircraft widely used in China, including the LTO cycle module, actual cruising distance and maximum cruising distance module, actual payload, and maximum payload module. In the whole life cycle assessment, GHGs of agriculture residue is 17.9 gCO2e/MJ while petroleum-based jet fuel is 90.2 gCO2e/MJ. The order of GHGs in WTW (well to wheel) is agriculture residue < corn stover < beanstalk < wheat straw < rice straw. The land release conducted obviously to the total GHGs emission for rice straw, which indicated that land release should involve in the LCA.

As a pleiotropic cytokine, interleukin-6 (IL-6) not only regulates the cellular immune response, but it also promotes tumor development by activating multiple carcinogenic pathways. IL-6 expression is significantly elevated in colorectal cancer (CRC) and is closely related to CRC development and patient prognosis. In CRC, IL-6 activates signal transducers and activators of transduction-3 (STAT3) to promote tumor initiation and tumor growth. IL-6/STAT3 signalling has a profound effect on tumor-infiltrating immune cells in the tumor immune microenvironment in CRC. Additionally, IL-6/STAT3 pathway activates downstream target genes to protect tumor cells from apoptosis; drive tumor cell proliferation, cell cycle progression, invasion and metastasis; promote tumor angiogenesis; and stimulate drug resistance. Therefore, a thorough understanding of the many effects of the IL-6/STAT3 pathway in CRC is needed, which the present review examines.

With the development of network and the popularity of e-commerce, the network service industry has shown strong development potential, and many community e-commerce platforms have emerged as the times require. In order to ensure the profit of the supply chain of community e-commerce platform and supervise whether the suppliers of enterprises and grid station service providers try their best to participate in value co-creation, this paper introduces the delay parameter a of community e-commerce platform, constructs a three-party evolutionary game model of "community e-commerce platform-grid station service provider-supplier", simulates the strategies of each agent with matlab, studies the behaviours of community e-commerce platform under different delay parameters, and concludes that the delay parameter a of community e-commerce platform has a great influence on the timing of community e-commerce platform supervision. Finally, three suggestions are put forward for the supervision of the supply chain of community e-commerce platform: (1) encourage consumers to report; (2) formulate the reward and punishment system for the settled enterprises; (3) formulating a reasonable supervision system.

Additional file 3 This pdf file contains two tables which include results on two related tasks (table 1, 2).

While the application of differential privacy (DP) has been well-studied in cross-device federated learning (FL), there is a lack of work considering DP and its implications for cross-silo FL, a setting characterized by a limited number of clients each containing many data subjects. In cross-silo FL, usual notions of client-level DP are less suitable as real-world privacy regulations typically concern the in-silo data subjects rather than the silos themselves. In this work, we instead consider an alternative notion of silo-specific sample-level DP, where silos set their own privacy targets for their local examples. Under this setting, we reconsider the roles of personalization in federated learning. In particular, we show that mean-regularized multi-task learning (MR-MTL), a simple personalization framework, is a strong baseline for cross-silo FL: under stronger privacy requirements, silos are incentivized to federate more with each other to mitigate DP noise, resulting in consistent improvements relative to standard baseline methods. We provide an empirical study of competing methods as well as a theoretical characterization of MR-MTL for mean estimation, highlighting the interplay between privacy and cross-silo data heterogeneity. Our work serves to establish baselines for private cross-silo FL as well as identify key directions of future work in this area., Comment: NeurIPS 2022, 37 pages

Influence of folate metabolism has long been studied in cancer and copies evidences have suggested that the key genes involved were correlated with GC risk and prognosis. However, their genetically association and contribution for GC prognosis are still elusive. To evaluate the effect of folate metabolism related genes polymorphisms on the prognosis of gastric cancer (GC), the genotype of seven single nucleotide polymorphisms (SNPs) of three genes were selected and genotyped in a cohort of 664 GC patients, including genes of Methylenetetrahydrofolate reductase (MTHFR), Methionine synthase reductase (MTRR), and Methionine synthase (MTR). Kaplan-Meier Curve, long-rank tests and multivariate Cox proportional hazard model were used for prognosis analysis. The results demonstrated that TT or CT/TT genotypes of SNP rs1532268 in MTRR gene coding region are significantly associated with a poorer overall survival (OS) when compared with CC genotype (HR=2.340, 95% CI: 1.240-4.414, p=0.009; or HR=1.502, 95% CI: 1.083-2.085, p=0.015, respectively). Furthermore, comparing to that of the CC genotype, the detrimental effect of rs1532268 TT genotype was also evident in the special subgroups of GC patients, especially in patients with BMI

Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness.

We introduce the multi-dimensional Skellam mechanism, a discrete differential privacy mechanism based on the difference of two independent Poisson random variables. To quantify its privacy guarantees, we analyze the privacy loss distribution via a numerical evaluation and provide a sharp bound on the R\'enyi divergence between two shifted Skellam distributions. While useful in both centralized and distributed privacy applications, we investigate how it can be applied in the context of federated learning with secure aggregation under communication constraints. Our theoretical findings and extensive experimental evaluations demonstrate that the Skellam mechanism provides the same privacy-accuracy trade-offs as the continuous Gaussian mechanism, even when the precision is low. More importantly, Skellam is closed under summation and sampling from it only requires sampling from a Poisson distribution -- an efficient routine that ships with all machine learning and data analysis software packages. These features, along with its discrete nature and competitive privacy-accuracy trade-offs, make it an attractive practical alternative to the newly introduced discrete Gaussian mechanism., Comment: Paper published in NeurIPS 2021

Electrocardiography (ECG) signal is a highly applied measurement for individual heart condition, and much effort have been endeavored towards automatic heart arrhythmia diagnosis based on machine learning. However, traditional machine learning models require large investment of time and effort for raw data preprocessing and feature extraction, as well as challenged by poor classification performance. Here, we propose a novel deep learning model, named Attention-Based Convolutional Neural Networks (ABCNN) that taking advantage of CNN and multi-head attention, to directly work on the raw ECG signals and automatically extract the informative dependencies for accurate arrhythmia detection. To evaluate the proposed approach, we conduct extensive experiments over a benchmark ECG dataset. Our main task is to find the arrhythmia from normal heartbeats and, at the meantime, accurately recognize the heart diseases from five arrhythmia types. We also provide convergence analysis of ABCNN and intuitively show the meaningfulness of extracted representation through visualization. The experimental results show that the proposed ABCNN outperforms the widely used baselines, which puts one step closer to intelligent heart disease diagnosis system., 7 pages, accepted by The 2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS 2021)

Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness.

Database systems analyze queries to determine upfront which data is needed for answering them and use indexes and other physical design techniques to speed-up access to that data. However, for important classes of queries, e.g., HAVING and top-k queries, it is impossible to determine up-front what data is relevant. To overcome this limitation, we develop provenance-based data skipping (PBDS), a novel approach that generates provenance sketches to concisely encode what data is relevant for a query. Once a provenance sketch has been captured it is used to speed up subsequent queries. PBDS can exploit physical design artifacts such as indexes and zone maps. Our approach significantly improves performance for both disk-based and main-memory database systems., 20 pages, 14 figures

Hypoxia-inducible factor (HIF)-1α is a crucial transcription factor that regulates the expression of target genes involved in angiogenesis. Prolyl hydroxylase 2 (PHD2) dominantly hydroxylates two highly conserved proline residues of HIF-1α to promote its degradation. This study was designed to construct an intrabody against PHD2 that can inhibit PHD2 activity and promote angiogenesis. Single-chain variable fragment (scFv) against PHD2, INP, was isolated by phage display technique and was modified with an endoplasmic reticulum (ER) sequence to obtain ER-retained intrabody against PHD2 (ER-INP). ER-INP was efficiently expressed and bound to PHD2 in cells, significantly increased the levels of HIF-1α, and decreased hydroxylated HIF-1α in human embryonic kidney cell line (HEK293) cells and mouse mononuclear macrophage leukaemia cell line (RAW264.7) cells. ER-INP has shown distinct angiogenic activity both in vitro and in vivo, as ER-INP expression significantly promoted the migration and tube formation of human umbilical vein endothelial cells (HUVECs) and enhanced angiogenesis of chick chorioallantoic membranes (CAMs). Furthermore, ER-INP promoted distinct expression and secretion of a range of angiogenic factors. To the best of our knowledge, this is the first study to report an ER-INP intrabody enhancing angiogenesis by blocking PHD2 activity to increase HIF-1α abundance and activity. These results indicate that ER-INP may play a role in the clinical treatment of tissue injury and ischemic diseases in the future.

Reviews the evolution of China's corporate rescue strategies. Examines the role of Chinese local government in corporate rescue and how the attempted restructuring of Taizinai Dairy Group Co Ltd showed the link between bankruptcy enforcement and political accountability. Discusses key features of the current approach, and whether the coronavirus pandemic has led to more supportive and economically-orientated interventions.

We consider training models on private data that are distributed across user devices. To ensure privacy, we add on-device noise and use secure aggregation so that only the noisy sum is revealed to the server. We present a comprehensive end-to-end system, which appropriately discretizes the data and adds discrete Gaussian noise before performing secure aggregation. We provide a novel privacy analysis for sums of discrete Gaussians and carefully analyze the effects of data quantization and modular summation arithmetic. Our theoretical guarantees highlight the complex tension between communication, privacy, and accuracy. Our extensive experimental results demonstrate that our solution is essentially able to match the accuracy to central differential privacy with less than 16 bits of precision per value., Comment: International Conference on Machine Learning (ICML), 2021

Xiaomin She, Yan Lin, Rong Liang, Ziyu Liu, Xing Gao, Jiazhou Ye Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of ChinaCorrespondence: Jiazhou Ye Tel +86 7715301253Email nnsz20013@163.comAbstract: RNA-binding proteins (RBPs) act as a key factor in gene regulation by governing RNA metabolism. They contribute to the expression and functions of most RNAs by binding to them and forming complexes. RNA-binding motif protein 38 (RBM38), a member of the RBP family, alters the stability and translation of targeted mRNAs to affect various biological processes, such as cell proliferation, cell cycle arrest, and myogenic differentiation. RBM38 contains a highly conserved RNA recognition motif (RRM) consisting of two subunits, RNP1 and RNP2, which specifically bind to RNAs. Recent studies have revealed that RBM38 regulates the mRNA stability of several tumor-related genes, such as p53, mdm2, p63, p73, p21, and c-Myc, by binding to their 3′ untranslated regions (3′ UTRs); thus, RBM38 modulates targeted gene expression and affects the biological processes of tumors. In addition, abnormal RBM38 expression in some malignant tumors and its correlation with prognosis have been documented in many studies, indicating its value for potential clinical applications. In this review, we present an overview of RBM38, specifically highlighting its relationship with tumor manifestation and development. A brief overview of the potential use of RBM38 in cancer therapy is also included to provide ideas for further research on RBM38.Keywords: RBM38, malignant tumors, p53 family, posttranscriptional regulation

Yan Lin,1 Ziqin He,1 Jiazhou Ye,2 Ziyu Liu,1 Xiaomin She,1 Xing Gao,1 Rong Liang1 1Department of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, People’s Republic of China; 2Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, People’s Republic of ChinaCorrespondence: Rong LiangDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, People’s Republic of ChinaTel +86 771 5333058Email ronglianggx@126.comAbstract: As a pleiotropic cytokine, interleukin-6 (IL-6) not only regulates the cellular immune response, but it also promotes tumor development by activating multiple carcinogenic pathways. IL-6 expression is significantly elevated in colorectal cancer (CRC) and is closely related to CRC development and patient prognosis. In CRC, IL-6 activates signal transducers and activators of transduction-3 (STAT3) to promote tumor initiation and tumor growth. IL-6/STAT3 signalling has a profound effect on tumor-infiltrating immune cells in the tumor immune microenvironment in CRC. Additionally, IL-6/STAT3 pathway activates downstream target genes to protect tumor cells from apoptosis; drive tumor cell proliferation, cell cycle progression, invasion and metastasis; promote tumor angiogenesis; and stimulate drug resistance. Therefore, a thorough understanding of the many effects of the IL-6/STAT3 pathway in CRC is needed, which the present review examines.Keywords: IL-6/STAT3 pathway, colorectal cancer, tumor development

In order to realize the coordination of the pre-stage circuit and the post-stage circuit of the isolated bidirectional AC/DC matrix converter, a novel partition-phase-shift control strategy is proposed. In this control strategy, dual-line-voltage modulation and partition-phase-shift control are employed for the pre-stage circuit, and complementary control is adopted for the post-stage circuit. Simulation results show that the balanced sinusoidal grid currents, nearly unity input power factor and low output voltage/current ripple have been realized, which demonstrates the feasibility and validity of the proposed control strategy.

We aimed to identify a hepatocellular carcinoma (HCC)-specific gene set during progression. Using the HCC data set from The Cancer Genome Atlas, we found that 10 genes were gradually upregulated with the progression of HCC and associated with survival, classified as HCC-unfavorable genes; 29 genes were gradually downregulated and associated with survival, classified as HCC-favorable genes. Gene set variation analysis (GSVA) was used to score individual samples against the two gene sets. Receiver operating characteristic (ROC) curve analysis showed that both the HCC-unfavorable GSVA score and HCC-favorable GSVA score were reliable biomarkers for diagnosing HCC. Moreover, tROC curve analysis and univariate/multivariate Cox proportional hazards analyses indicated that the HCC-unfavorable GSVA score was an independent prognostic biomarker. The results were validated in an external independent data set. Our results support a ten-gene set variation score as a diagnostic and predictive strategy tool in HCC.

We present a multi-agent actor-critic method that aims to implicitly address the credit assignment problem under fully cooperative settings. Our key motivation is that credit assignment among agents may not require an explicit formulation as long as (1) the policy gradients derived from a centralized critic carry sufficient information for the decentralized agents to maximize their joint action value through optimal cooperation and (2) a sustained level of exploration is enforced throughout training. Under the centralized training with decentralized execution (CTDE) paradigm, we achieve the former by formulating the centralized critic as a hypernetwork such that a latent state representation is integrated into the policy gradients through its multiplicative association with the stochastic policies; to achieve the latter, we derive a simple technique called adaptive entropy regularization where magnitudes of the entropy gradients are dynamically rescaled based on the current policy stochasticity to encourage consistent levels of exploration. Our algorithm, referred to as LICA, is evaluated on several benchmarks including the multi-agent particle environments and a set of challenging StarCraft II micromanagement tasks, and we show that LICA significantly outperforms previous methods., NeurIPS 2020 Camera Ready; first two authors contributed equally

Target localization and proposal generation are two essential subtasks in generic visual tracking, and it is a challenge to address both the two efficiently. In this paper, we propose an efficient two-stage architecture which makes full use of the complementarity of two subtasks to achieve robust localization and high-quality proposals generation of the target jointly. Specifically, our model performs a novel deformable central correlation operation by an online learning model in both two stages to locate new target centers while generating target proposals in the vicinity of these centers. The proposals are refined in the refinement stage to further improve accuracy and robustness. Moreover, the model benefits from multi-level features aggregation in a neck module and a feature enhancement module. We conduct extensive ablation studies to demonstrate the effectiveness of our proposed methods. Our tracker runs at over 30 FPS and sets a new state-of-the-art on five tracking benchmarks, including LaSOT, VOT2018, TrackingNet, GOT10k, OTB2015.

Removal of sulfide from a micro-aerobic bio-reactor was studied at 10 000 mg L−1 chemical oxygen demand (COD) of inlet water, with the sulfate volumetric loading 0.75, 1.0, 1.5 and 2.0 kg (m−3 d−1), respectively. Tentatively, activated carbon (AC) as an adsorbent was modified in positively charged iron to adsorb bio-sulfur through electrostatic interaction. At an O2/S molar ratio of 8–10, the reactor was sufficient to decrease the sulfide in the effluent and biogas to low levels at the sulfate volumetric loading of 2 kg (m−3 d−1). After iron-modified, the specific surface area of AC was form 32.4 m2 g−1 to 65.0 m2 g−1, and the zeta potential was 25.3 mV at pH 7.0. The XRD pattern of the iron-modified activated carbon (FeAC) explained that the metal species of iron was Fe3O4. It could be clearly seen that there was Fe3O4 on the surface of the FeAC, and sulfur particles with a large particle size were adsorbed by the FeAC on the SEM figures. And the XRD pattern of the bio-sulfur explained that the bio-sulfur was made up of S8 (91.444%), C3H4N2OS (1.491%) and CH5N3S (7.075%). The zeta potential of bio-sulfur was −25 mV and the particle size was mainly distributed at the average diameter of 1935 nm at pH 7.0.

This paper presents an analytical approach to investigate the free vibration analysis of cracked non-uniform beam carrying spring-mass systems by finite element method and illustrates a valid and reliable damage identification method which using hybrid neural genetic technique. Firstly, based on the finite element method, the dynamic characteristics of non-uniform cracked beam carrying spring-mass systems are obtained. Then, the first five frequencies are used as input parameters by combining genetic algorithm with neural network to identify the damage. Finally, Numerical simulations of direct and inverse problems of non-uniform cracked beams carrying a spring-mass system are carried out.

In this paper, the flow field of the approximate T-shaped tundish and the removal rate of fine inclusions are improved by changing the parameters of the flow control device of the SCB (stabilizer coupling baffle) structure. Studies have shown that the synergistic effect of the DPRW (double porous retaining wall) structure and the IRS (internal rotation stabilizer) structure has excellent performance in mixing the temperature composition of the molten steel, increasing the average residence time of the molten steel, reducing the volume fraction of the dead zone, and improving the removal rate of fine inclusions. The opening method and diameter of the double-layer retaining wall have a greater impact on the flow field parameters. The larger the diameter, the more conducive to increasing the average residence time, and the smaller the diameter, the more conducive to increasing the removal rate of fine inclusions.

Owing to the need of the 'digging container' operation function of the dual 40 feet container spreader, a novel multi-mode switchable container spreader controlled by parallel branches is designed. The container spreader is controlled to adjust the folding posture of the spreader mechanism and auxiliary supported by the contacted profile surface by two parallel branches, and realize the digging operation. Through the analysis of the functional requirements and working conditions of the existing container spreader, the requirements of six independent displacement outputs of the spreader structure are obtained. Then the structure of the mechanism is synthesized based on the topological theory of POC set, and the design of the 6R mechanism with parallel adjusting branches is studied. The completed dual 40 feet container spreader can switch between the single-row operation mode and double-row operation modes, and adjust relative position and posture of the dual spreaders, so as to satisfy the adaptability of the spreader to various working conditions. The design can greatly improve the loading and unloading efficiency of containers.

Cage aquaculture is an important strategic direction for marine aquaculture, which plays an important role in expanding aquaculture space and protecting the offshore ecological environment. First, based on the concept of embedded deployable mechanisms, a novel embedded deployable offshore cage driven by cables is proposed. Over-constrained spatial mechanisms and planar compliant mechanisms are respectively adopted as the primary and secondary cages while the secondary cages are embedded in the primary cage. A closed-loop cable-driven module is designed to deploy the cage through the pull and release of the cable. Then, due to the kinematic characteristics of threefold-symmetric Bricard mechanism with three symmetric planes intersecting at a determined line, the determined line is regarded as the central line of the driven mechanism. Finally, the relationship between the input angle and the output angle is obtained from the kinematic equations of the primary cage frame, then the relationship between the driven angle and corresponding open state of the cage frame can be derived by geometric projection.

Space deployable structures that are constructed by the single loop over-constrained linkages have been extensively applied in the fields of aerospace and construction. The pressure angle regarded as an important index to measure the performance of the basic units has attracted more and more attention. The kinematic model of the Bennett linkage is studied by the D-H matrix and the analytic formula of the pressure angle has been deducted through kinematic equations. The rule of the Bennett linkage has been discovered that the minimum pressure angle occurs while the input angle equals nπ + π / 2(n ∈ N). According to the linkage configuration at the input angle of π / 2, the geometric meaning is revealed that the minimum pressure angle of the linkage is the same as the twist angle of the joint axes of the output link. Finally, conclusions can also be drawn that the smaller the twist angle of the output link is, the smaller the minimum pressure angle will be. The research enriches the kinematics of Bennett linkage and provides a reference for its engineering applications.

The game of Chinese Checkers is a challenging traditional board game of perfect information that differs from other traditional games in two main aspects: first, unlike Chess, all checkers remain indefinitely in the game and hence the branching factor of the search tree does not decrease as the game progresses; second, unlike Go, there are also no upper bounds on the depth of the search tree since repetitions and backward movements are allowed. Therefore, even in a restricted game instance, the state-space of the game can still be unbounded, making it challenging for a computer program to excel. In this work, we present an approach that effectively combines the use of heuristics, Monte Carlo tree search, and deep reinforcement learning for building a Chinese Checkers agent without the use of any human game-play data. Experiment results show that our agent is competent under different scenarios and reaches the level of experienced human players.

The particle filter is a popular Bayesian filtering algorithm for use in cases where the state-space model is nonlinear and/or the random terms (initial state or noises) are non-Gaussian distributed. We study the behavior of the error in the particle filter algorithm as the number of particles gets large. After a decomposition of the error into two terms, we show that the difference between the estimator and the conditional mean is asymptotically normal when the resampling is done at every step in the filtering process. Two nonlinear/non-Gaussian examples are tested to verify this conclusion.

Rong Liang, Ziyu Liu, Xuemin Piao, Mingtang Zuo, Jinyan Zhang, Zhihui Liu, Yongqiang Li, Yan Lin Department of Medical Oncology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi 530021, People’s Republic of China Abstract: Malignant cancer is one of the most serious diseases that currently endanger human health. As most tumors are diagnosed at an advanced stage, the current treatments show poor therapeutic efficacy, and the patients have poor prognosis. However, a 5-year survival rate higher than 80% could be achieved if tumors are diagnosed at an early stage. Therefore, early diagnosis and treatment play important roles in the prevention and treatment of malignant tumors, and serum tumor markers are important for the early diagnosis of malignant cancers. Recent studies have shown that GP73, a transmembrane protein, has greater diagnostic value in primary liver cancer than in other types of cancers, and research on the regulation of GP73 expression has unveiled broad prospects in anticancer targeted therapy. Thus, GP73, as a new tumor marker, deserves further study. Keywords: GP73, malignant tumors, tumor marker, diagnosis, prognosis

Experimental investigation and numerical simulation are performed to obtain the combustion characteristics of premixed hydrogen/air mixtures in a closed container, such as flame propagation velocity, peak pressure and maximum temperature. This paper mainly focused on the influence of initial temperature, hydrogen concentration and steam concentration on hydrogen/air flame propagation. An updated kinetics of hydrogen combustion based on one-step global reaction mechanism was validated by the present experimental data. The numerical results with updated kinetics show a satisfactory agreement with experimental results in term of average flame propagation velocity with the deviation less than 20%. The experimental and simulation results show that the average flame propagation velocity increases with the increase of initial hydrogen concentration and initial temperature, and reduces with the increase of initial steam concentration. The effect of hydrogen concentration on average flame propagation velocity is more significant than that of initial temperature and steam concentration.

Cobalt ferrite/reduced graphene oxide (CoFe2O4/RGO) nanocomposites were initially prepared by the interaction of alkyne-functionalized CoFe2O4 NPs and azide-functionalized graphene oxide (GO–N3) via the Cu (I)-catalyzed click reaction. The morphology and structure of CoFe2O4/RGO were investigated by means of XRD, FTIR, TGA, TEM, SEM and the electromagnetic parameters were measured by vector network analyzer. For CoFe2O4/RGO composites with click reaction, the minimum reflection loss could reach −40 dB at 6.8 GHz with a matching thickness of 4.0 mm, and also it had a bandwidth below −10 dB ranging from 5.8 to 8.5 GHz. The CoFe2O4/RGO composites with click reaction exhibited better microwave absorbing performance than the physical mixture. Furthermore, the covalent ligation between CoFe2O4 NPs and graphene oxide could make the composites have a promising future in electromagnetic wave absorption materials.