Optimizing environmental regulation policies for digital transformation in energy enterprises in China: An evolutionary game theory approach.

In response to the global consensus on achieving carbon reduction, China has introduced a series of policies aimed at accelerating the digital transformation of energy enterprises. However, these policies have revealed shortcomings such as deficiency in regulation methods and insufficient integration of regulation with technologies. This study applies evolutionary game theory (EGT) to evaluate the impacts of different environmental regulatory policies on the digital transformation and verifies the effectiveness of the theory in policy optimization.

Multi-region calcium imaging in freely behaving mice with ultra-compact head-mounted fluorescence microscopes.

To investigate the circuit-level neural mechanisms of behavior, simultaneous imaging of neuronal activity in multiple cortical and subcortical regions is highly desired. Miniature head-mounted microscopes offer the capability of calcium imaging in freely behaving animals. However, implanting multiple microscopes on a mouse brain remains challenging due to space constraints and the cumbersome weight of the equipment.

Castleman disease of plasma cell type accompanied with bronchiolitis obliterans: a case report and review of the literature.

Background: Castleman disease, also known as giant lymph node hyperplasia or angiofollicular lymph node hyperplasia, is a highly heterogeneous clinicopathological entity that belongs to the family lymphoproliferative disorders. Castleman disease accompanied by bronchiolitis obliterans is uncommon and often poses a great diagnostic challenge, which is easily confused with respiratory diseases and impeding the correct diagnosis and treatment. The main aim in presenting such rare case studies is to raise awareness and expand the diagnostic horizon of clinicians for appropriate management.

Cynomolgus monkey embryo model captures gastrulation and early pregnancy.

Human stem cell-derived blastoids display similar morphology and cell lineages to normal blastocysts. However, the ability to investigate their developmental potential is limited. Here, we construct cynomolgus monkey blastoids resembling blastocysts in morphology and transcriptomics using naive ESCs.

Decoding anterior-posterior axis emergence among mouse, monkey, and human embryos.

Anterior-posterior axis formation regulated by the distal visceral endoderm (DVE) and anterior visceral endoderm (AVE) is essential for peri-implantation embryogenesis. However, the principles of the origin and specialization of DVE and AVE remain elusive. Here, with single-cell transcriptome analysis and pseudotime prediction, we show that DVE and AVE independently originate from the specialized primary endoderm in mouse blastocysts.

Applications of machine learning in tumor-associated macrophages.

Evaluation of tumor-host interaction and intratumoral heterogeneity in the tumor microenvironment (TME) is gaining increasing attention in modern cancer therapies because it can reveal unique information about the tumor status. As tumor-associated macrophages (TAMs) are the major immune cells infiltrating in TME, a better understanding of TAMs could help us further elucidate the cellular and molecular mechanisms responsible for cancer development. However, the high-dimensional and heterogeneous data in biology limit the extensive integrative analysis of cancer research.

A personalized DVH prediction model for HDR brachytherapy in cervical cancer treatment.

Purpose: Although the knowledge-based dose-volume histogram (DVH) prediction has been largely researched and applied in External Beam Radiation Therapy, it is still less investigated in the domain of brachytherapy. The purpose of this study is to develop a reliable DVH prediction method for high-dose-rate brachytherapy plans.

Method: A DVH prediction workflow combining kernel density estimation (KDE), k-nearest neighbor (kNN), and principal component analysis (PCA) was proposed.

A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy.

Purpose: Fast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rate brachytherapy due to the highly time-intensive online treatment planning process and the high dose gradient around the HRCTV. This study aims to apply a self-configured ensemble method for fast and reproducible auto-segmentation of OARs and HRCTVs in gynecological cancer.

Materials And Methods: We applied nnU-Net (no new U-Net), an automatically adapted deep convolutional neural network based on U-Net, to segment the bladder, rectum and HRCTV on CT images in gynecological cancer.

Evaluating China's regional energy and environmental efficiency by considering three internal parallel industries.

With the rapid development of China's economy, high energy consumption and high pollution emission have become serious problems. To solve these problems, many studies have been done to evaluate energy and environmental efficiency, as the results can provide valuable information to improve performance. However, the previous research mainly evaluates China's regional energy and environmental efficiency by considering each region's industry as a whole system, ignoring the internal structure.

as a key gene drives the early primate telencephalon development.

Evolutionary mutations in primate-specific genes drove primate cortex expansion. However, whether conserved genes with previously unidentified functions also play a key role in primate brain expansion remains unknown. Here, we focus on (), a gene encoding a neural transcription factor commonly expressed in both primates and mice.

Impacts of renewable electricity standard and Renewable Energy Certificates on renewable energy investments and carbon emissions.

Accelerating the development of renewable energy is seen as an effective way for achieving the goals of carbon peak and carbon neutrality. The polices of Renewable Electricity Standard (RES) and Renewable Energy Certificates (REC) play increasing and important roles in developing renewable energy. In this paper, we develop an analytical model to analyze the impacts of the interaction of RES and REC polices on the renewable energy investment levels of an electricity generation firm and the carbon emissions.

Effects of different oxygen conditions on pollutants removal and the abundances of tetracycline resistance genes in activated sludge systems.

The individual and combined effects of tetracycline (TC) and divalent copper (Cu) on the performance of activated sludge systems and the abundances of tetracycline resistance genes (TRGs) in activated sludge, under both aerobic and anaerobic conditions, were studied. Activated sludge systems received TC (0.2 mg L) and Cu (5 mg L) separately or jointly under either aerobic or anaerobic conditions.

The efficacy of moxibustion and acupuncture therapy for ankylosing spondylitis: A protocol for an overview of systematic reviews and meta-analysis.

Background: Ankylosing spondylitis is a complex and progressive autoimmune inflammatory disease with a worldwide prevalence ranging up to 0.9%. Several systematic reviews and meta-analyses of traditional Chinese medicine alternative therapies, such as acupuncture or moxibustion, have demonstrated the effectiveness of moxibustion and acupuncture in the treatment of ankylosing spondylitis.

Little needle-scalpel for piriformis syndrome: A protocol for systematic review and meta-analysis.

Background: Piriformis syndrome (PS) is a condition in which the sciatic nerve is compressed when passing through the inferior mouth of the piriformis muscle, mainly caused by pain in one hip and leg. In severe cases, patients may experience severe buttock and lower limb pain, discomfort, difficulty walking, and claudication. It is estimated that the annual incidence of low back pain and sciatica is about 40 million cases, and the annual incidence of piriformis syndrome is about 2.

Inhibition of coronavirus infection by a synthetic STING agonist in primary human airway system.

The newly emerged severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) coronavirus initiated a pneumonia outbreak (COVID-19) that rapidly spread worldwide and quickly became a public health emergency of international concern; However to date, except Remdesivir, there are no clinically approved specific or effective medicines to prevent or treat COVID-19. Therefore, the development of novel treatments against coronavirus infections caused by the current SARS-CoV-2 virus, as well as other highly pathogenic human coronaviruses, represents an urgent unmet need. Stimulator of interferon genes (STING) plays a central role in host defense mechanisms against microbial infections.

Impacts of the carbon emission trading system on China's carbon emission peak: a new data-driven approach.

Over the past four decades, China's extensive economic growth mode has led to substantial greenhouse gas emissions, and China has become the world's largest emitter since 2009. In order to alleviate the dual pressures from international climate negotiations and domestic environmental degradation, the Chinese government has pronounced it will reach its emission peak before 2030. However, through analyzing 12 scenarios, we found that it will be very difficult to meet this ambitious goal under the current widely used policies.

A synthetic STING agonist inhibits the replication of human parainfluenza virus 3 and rhinovirus 16 through distinct mechanisms.

Stimulator of interferon genes (STING), as a signaling hub in innate immunity, plays a central role for the effective initiation of host defense mechanisms against microbial infections. Upon binding of its ligand cyclic dinucleotides (CDNs) produced by the cyclic GMP-AMP synthase (cGAS) or invading bacteria, STING is activated, leading to the induction of both type I interferon responses and autophagy, which are critical for the control of certain microbial infections. RNA viruses, such as Parainfluenza virus (PIV) and Rhinovirus (HRV), are among the leading causes of respiratory infections that affect human health without effective treatments.

Novel Laser-Based Obstacle Detection for Autonomous Robots on Unstructured Terrain.

Obstacle detection is one of the essential capabilities for autonomous robots operated on unstructured terrain. In this paper, a novel laser-based approach is proposed for obstacle detection by autonomous robots, in which the Sobel operator is deployed in the edge-detection process of 3D laser point clouds. The point clouds of unstructured terrain are filtered by VoxelGrid, and then processed by the Gaussian kernel function to obtain the edge features of obstacles.

Dynamic wetting of solid-liquid-liquid system by molecular kinetic theory.

Hypothesis: The mechanisms of dynamic wetting of solid-liquid-liquid (SLL) system, especially the viscosity effects of two liquids, can be investigated by the molecular kinetic theory (MKT).

Methods: The molecular kinetic theory combined with published data was used to study the roles of a fluid viscosity and a solid surface in dynamic wetting.

Findings: First, the MKT on dynamic wetting was introduced and its limitation was analyzed.

Analysis of resource allocation and environmental performance in China's three major urban agglomerations.

This study focuses on the analysis of optimal energy allocation and environmental performance of China's three major urban agglomerations. Specifically, this paper first uses a fixed-input DEA model to obtain the optimal allocation of energy input. Then, an evaluation model based on the optimal allocation of energy input is proposed to evaluate environmental performance.