New Interpretations of Normalization Methods in Deep Learning

In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalization (WN), group normalization (GN), etc. However, mathematical tools to analyze all these normalization methods are lacking. In this paper, we first propose a lemma to define some necessary tools. Then, we use these tools to make a deep analysis on popular normalization methods and obtain the following conclusions: 1) Most of the normalization methods can be interpreted in a unified framework, namely normalizing pre-activations or weights onto a sphere; 2) Since most of the existing normalization methods are scaling invariant, we can conduct optimization on a sphere with scaling symmetry removed, which can help stabilize the training of network; 3) We prove that training with these normalization methods can make the norm of weights increase, which could cause adversarial vulnerability as it amplifies the attack. Finally, a series of experiments are conducted to verify these claims.Comment: Accepted by AAAI 202

Opening up the participation laboratory: the co-creation of publics and futures in upstream participation.

How to embed reflexivity in public participation in techno-science and to open it up to the agency of publics are key concerns in current debates. There is a risk that engagements become limited to “laboratory experiments,” highly controlled and foreclosed by participation experts, particularly in upstream techno-sciences. In this paper, we propose a way to open up the “participation laboratory” by engaging localized, self-assembling publics in ways that respect and mobilize their ecologies of participation. Our innovative reflexive methodology introduced participatory methods to public engagement with upstream techno-science, with the public contributing to both the content and format of the project. Reflecting on the project, we draw attention to the largely overlooked issue of temporalities of participation, and the co-production of futures and publics in participation methodologies. We argue that many public participation methodologies are underpinned by the open futures model, which imagines the future as a space of unrestrained creativity. We contrast that model with the lived futures model typical of localized publics, which respects latency of materials and processes but imposes limits on creativity. We argue that to continue being societally relevant and scientifically important, public participation methods should reconcile the open future of research with the lived futures of localized publics

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Linjär modellering av dubbelmatade asynkrongeneratorer och spänningsstyva HVDC-system

Recently, with growing application of wind power, the system based on the doubly fedinduction generator (DFIG) has become the one of the most popular concepts. Theproblem of connecting to the grid is also gradually revealed. As an effective solution toconnect offshore wind farm, VSC-HVDC line is the most suitable choice for stabilityreasons. However, there are possibilities that the converter of a VSC-HVDC link canadversely interact with the wind turbine and generate poorly damped sub-synchronousoscillations. Therefore, this master thesis will derive the linear model of a single DFIG aswell as the linear model of several DFIGs connecting to a VSC-HVDC link. For thelinearization method, the Jacobian transfer matrix modeling method will be explainedand adopted. The frequency response and time-domain response comparison betweenthe linear model and the identical system in PSCAD will be presented for validation.Nyligen, med ökande tillämpning av vindkraft, det system som bygger på den dubbeltmatad induktion generator (DFIG) har blivit en av de mest populära begrepp. Problemetmed att ansluta till nätet är också gradvis avslöjas. Som en effektiv lösning för att anslutavindkraftpark är VSC -HVDC linje det lämpligaste valet av stabilitetsskäl. Det finns dockmöjligheter att omvandlaren en VSC-HVDC länk negativt kan interagera medvindturbinen och genererar dåligt dämpade under synkron svängningar. Därför kommerdetta examensarbete härleda den linjära modellen av en enda DFIG liksom den linjäramodellen av flera DFIGs ansluter till en VSC-HVDC -länk. För arise metoden kommerJacobian transfer matrix modelleringsmetodförklaras och antas. Jämförelse mellan denlinjära modellen och identiskt system i PSCAD frekvensgången och tidsdomänensvarkommer att presenteras för godkännande

Linjär modellering av dubbelmatade asynkrongeneratorer och spänningsstyva HVDC-system

Recently, with growing application of wind power, the system based on the doubly fedinduction generator (DFIG) has become the one of the most popular concepts. Theproblem of connecting to the grid is also gradually revealed. As an effective solution toconnect offshore wind farm, VSC-HVDC line is the most suitable choice for stabilityreasons. However, there are possibilities that the converter of a VSC-HVDC link canadversely interact with the wind turbine and generate poorly damped sub-synchronousoscillations. Therefore, this master thesis will derive the linear model of a single DFIG aswell as the linear model of several DFIGs connecting to a VSC-HVDC link. For thelinearization method, the Jacobian transfer matrix modeling method will be explainedand adopted. The frequency response and time-domain response comparison betweenthe linear model and the identical system in PSCAD will be presented for validation.Nyligen, med ökande tillämpning av vindkraft, det system som bygger på den dubbeltmatad induktion generator (DFIG) har blivit en av de mest populära begrepp. Problemetmed att ansluta till nätet är också gradvis avslöjas. Som en effektiv lösning för att anslutavindkraftpark är VSC -HVDC linje det lämpligaste valet av stabilitetsskäl. Det finns dockmöjligheter att omvandlaren en VSC-HVDC länk negativt kan interagera medvindturbinen och genererar dåligt dämpade under synkron svängningar. Därför kommerdetta examensarbete härleda den linjära modellen av en enda DFIG liksom den linjäramodellen av flera DFIGs ansluter till en VSC-HVDC -länk. För arise metoden kommerJacobian transfer matrix modelleringsmetodförklaras och antas. Jämförelse mellan denlinjära modellen och identiskt system i PSCAD frekvensgången och tidsdomänensvarkommer att presenteras för godkännande

Low body temperature and mortality in critically ill patients with coronary heart disease: a retrospective analysis from MIMIC-IV database

Abstract Background This study was aimed to investigate the correlation between low body temperature and outcomes in critically ill patients with coronary heart disease (CHD). Methods Participants from the Medical Information Mart for Intensive Care (MIMIC)-IV were divided into three groups (≤ 36.5 ℃, 36.6–37.4 ℃, ≥ 37.5 ℃) in accordance with body temperature measured orally in ICU. In-hospital, 28-day and 90-day mortality were the major outcomes. Multivariable Cox regression, decision curve analysis (DCA), restricted cubic splines (RCS), Kaplan–Meier curves (with or without propensity score matching), and subgroup analyses were used to investigate the association between body temperature and outcomes. Results A total of 8577 patients (65% men) were included. The in-hospital, 28-day, 90-day, and 1-year overall mortality rate were 10.9%, 16.7%, 21.5%, and 30.4%, respectively. Multivariable Cox proportional hazards regression analyses indicated that patients with hypothermia compared to the patients with normothermia were at higher risk of in-hospital [adjusted hazard ratios (HR) 1.23, 95% confidence interval (CI) 1.01–1.49], 28-day (1.38, 1.19–1.61), and 90-day (1.36, 1.19–1.56) overall mortality. For every 1 ℃ decrease in body temperature, adjusted survival rates were likely to eliminate 14.6% during the 1-year follow-up. The DCA suggested the applicability of the model 3 in clinical practice and the RCS revealed a consistent higher mortality in hypothermia group. Conclusions Low body temperature was associated with increased mortality in critically ill patients with coronary heart disease

Digital Transformation to Help Carbon Neutrality and Green Sustainable Development Based on the Metaverse

With the development of sustainable theory, environmental and resource issues have become one of the major challenges facing human society. As an important part of social economy, enterprises are also an important source of carbon emissions and environmental pollution. With the growth of the digital economy, digital technology has played an important role in improving economic efficiency. Digital transformation can not only enable enterprises to obtain and allocate resources more efficiently and reasonably, but can also provide a powerful driving force for the healthy development of the environment. This can improve the positive role and impact of enterprises on environmental development. Based on the overview of social carbon neutrality and green sustainable development goals, this paper made an in-depth study of digital transformation to help carbon neutrality and green sustainable development. In order to verify its effect, this paper took a medium-sized enterprise as the object, analyzed the growth of its economic and environmental benefits in the process of digital transformation, and compared it with the traditional development strategy. The empirical results showed that in the perspective of the Metaverse, the highest growth rate of environmental benefits of the enterprise would reach 19.6% every month in 2021. From this data, digital transformation based on the perspective of the Metaverse was more able to help carbon neutrality and green sustainable development

Three-Dimensional Animation Generation and Image Enhancement Technology Based on Multi-Column Convolutional Neural Network Model

This paper aims to improve the quality and fidelity of three-dimensional (3D) animation. Firstly, the application model of Multi-Column Convolutional Neural Network (MCNN) in 3D animation generation and image enhancement is proposed. Aiming at the generation of 3D animation, the MCNN algorithm suitable for this field is selected, and its working principle is explained in detail. Meanwhile, the theoretical basis of 3D animation generation is introduced, which provides a theoretical basis for subsequent experiments. Secondly, for image enhancement, the MCNN is also selected as the key technology, and its application model in image enhancement is explained. Finally, a simulation experiment is carried out to evaluate the effect of the proposed MCNN model in 3D animation generation and image enhancement. By collecting appropriate data sets and setting parameters in the corresponding experimental environment, the performance of the proposed model is evaluated. The results show that, compared with the traditional methods, the MCNN model shows better performance and effect in animation generation and image enhancement tasks. Specifically, this method can still maintain good performance under the conditions of shorter training time, faster reasoning time and lower memory occupation, and this method has advantages in computational efficiency. 3D animation generation and image enhancement technology with MCNN model can significantly improve the animation quality and image fidelity, and satisfactory experimental results have been obtained. The experimental results in this paper verify the application potential of MCNN in 3D animation generation and image enhancement, and provide new ideas and directions for further research and application

Expression of SLP-2 was associated with invasion of esophageal squamous cell carcinoma.

Stomatin-like protein 2 (SLP-2), a member of the Stomatin superfamily, has been identified as an oncogenic-related protein and found to be up-regulated in multi-cancers. Nonetheless, the expression pattern and regulation of SLP-2 in human esophageal squamous cell carcinoma (ESCC) remain unexplored.Immunohistochemistry and immunofluorescence staining analysis were performed to show SLP-2 expression and location. RNAi method was used to inhibit specific protein expression. Transwell assay was done to investigate cells invasive capability. RT-PCR and Western blot analysis were used to detect mRNA and protein expression levels.Immunohistochemical analysis showed that up-regulation of SLP-2 was found in invasive front compared with cancer central tissue in ESCC. Inhibition of SLP-2 by SLP-2 siRNA can decrease ESCC cells invasive capability through MMP-2 dependent manner. Up-regulation of SLP-2 was effectively abrogated by the ERK1/2 inhibitors either PD98059 or U0126, but no effect was showed by the treatment of AKT inhibitors either LY294002 or MK-2206. So the regulation of SLP-2 was involved in activation of the MAPK/ERK pathway.We found that PMA/EGF could induce the up-regulated expression of SLP-2 probably through activating ERK signalling. The current study suggests that SLP-2 may represent an important molecular hallmark that is clinically relevant to the invasion of ESCC

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Abstract As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD