As technological progress and environmental regulation are not only important drivers of but also the double-edged swords in mitigation of CO2 emissions, it is important to figure out their optimal ...threshold values for CO2 emissions' reduction. This paper employs the panel smooth transition regression technique to explore these optimal values in the case of OECD countries and emerging economies. The results show that: (1) OECD countries are at a level of excessive technological progress, which will have a rebound effect and increase CO2 emissions. (2) Emerging economies are under a strict level of environmental regulation, which will lead to serious ‘green paradox’ effects and harm the economic development. Moreover, they have great potential to achieve CO2 emissions reduction targets through technological progress. (3) Due to the rebound effect, the concentration of environment-related technologies should be shifted from improving energy efficiency to reducing carbon emissions directly such as capture, storage, sequestration or disposal of greenhouse gases. (4) OECD countries should provide low-carbon technical support to emerging economies. In addition, because of the existence of heterogeneity, OECD countries ought to determine their levels of technological progress and environmental regulation according to their own actual conditions.
•A PSTR model is employed to explore the optimal values of technological progress and environment regulation for OECD countries and emerging economies.•Results indicate that technological progress may lead to rebound effect.•The strict level of environmental regulation in emerging economies will cause ‘green paradox’ effects and hinder economic development.•Concentration of CO2 mitigation should be shifted from improving energy efficiency to reducing carbon emissions directly.•OECD countries should provide low-carbon emission reduction technical support to emerging economies.
Carbon market, which is capable of scientific quantifying and marked-based pricing of carbon emission, is an important way for countries to achieve the target of carbon emission reduction. The global ...carbon market, after more than ten years of development, has developed a mature mechanism. China started the trial of carbon market in 2011. After ten years of exploration, the national carbon trading market was officially launched in mid-July 2021. Against the backdrop of carbon neutrality, the national carbon market will shoulder a greater mission of carbon emission reduction and speed up its financialization and internationalization. However, it should take a dialectical attitude toward the opportunities and risks of carbon market financialization. In the future, China can promote the development of carbon market through efforts to develop market participants, clarify the attributes of carbon finance, prevent potential risks of carbon finance, improve the connection mechanism with the international carbon market, and innovate carbon finance services.
In recent years, the classification and identification of surface materials on earth have emerged as fundamental yet challenging research topics in the fields of geoscience and remote sensing (RS). ...The classification of multi-modality RS data still poses certain challenges, despite the notable advancements achieved by deep learning technology in RS image classification. In this work, a deep learning architecture based on convolutional neural network (CNN) is proposed for the classification of multimodal RS image data. The network structure introduces a cross modality reconstruction (CMR) module in the multi-modality feature fusion stage, called CMR-Net. In other words, CMR-Net is based on CNN network structure. In the feature fusion stage, a plug-and-play module for cross-modal fusion reconstruction is designed to compactly integrate features extracted from multiple modalities of remote sensing data, enabling effective information exchange and feature integration. In addition, to validate the proposed scheme, extensive experiments were conducted on two multi-modality RS datasets, namely the Houston2013 dataset consisting of hyperspectral (HS) and light detection and ranging (LiDAR) data, as well as the Berlin dataset comprising HS and synthetic aperture radar (SAR) data. The results demonstrate the effectiveness and superiority of our proposed CMR-Net compared to several state-of-the-art methods for multi-modality RS data classification.
Anticancer peptides are defence substances with innate immune functions that can selectively act on cancer cells without harming normal cells and many studies have been conducted to identify ...anticancer peptides. In this paper, we introduce the anticancer peptide secondary structures as additional features and propose an effective computational model, CL-ACP, that uses a combined network and attention mechanism to predict anticancer peptides. The CL-ACP model uses secondary structures and original sequences of anticancer peptides to construct the feature space. The long short-term memory and convolutional neural network are used to extract the contextual dependence and local correlations of the feature space. Furthermore, a multi-head self-attention mechanism is used to strengthen the anticancer peptide sequences. Finally, three categories of feature information are classified by cascading. CL-ACP was validated using two types of datasets, anticancer peptide datasets and antimicrobial peptide datasets, on which it achieved good results compared to previous methods. CL-ACP achieved the highest AUC values of 0.935 and 0.972 on the anticancer peptide and antimicrobial peptide datasets, respectively. CL-ACP can effectively recognize antimicrobial peptides, especially anticancer peptides, and the parallel combined neural network structure of CL-ACP does not require complex feature design and high time cost. It is suitable for application as a useful tool in antimicrobial peptide design.
Due to the well-recognized biocompatibility, silk fibroin hydrogels have been developed for biomedical applications including bone regeneration, drug delivery and cancer therapy. For the treatment of ...cancer, silk-based photothermal agents exhibit the high photothermal conversion efficiency, but the limited light penetration depth of photothermal therapy restricts the treatment of some tumors in deep positions, such as liver tumor and glioma. To provide an alternative strategy, here we developed an injectable magnetic hydrogel based on silk fibroin and iron oxide nanocubes (IONCs). The as-prepared ferrimagnetic silk fibroin hydrogel could be easily injected through a syringe into tumor, especially rabbit hepatocellular carcinoma in deeper positions using ultrasound-guided interventional treatment. Compared with photothermal agents, the embedded IONCs endowed the ferrimagnetic silk fibroin hydrogel with remote hyperthermia performance under an alternating magnetic field, resulting in the effective magnetic hyperthermia of deep tumors including subcutaneously implanted tumor model in Balb/c mouse after the coverage of a fresh pork tissue and orthotopic transplantation liver tumor in rabbit. Furthermore, due to the confinement of IONCs in silk fibroin hydrogel, the undesired thermal damage toward normal tissue could be avoided compared with directly administrating monodispersed magnetic nanoparticles.
In the study, in order to completely utilize the advantages of graphene monolayer, nano-fibrillated cellulose with cations from polyethyleneimine (PEI) was used as the intercalator to efficiently ...exfoliate the reduced graphene oxide into a single layer with a thickness about 0.47 nm by means of ionic attraction. After the high-temperature treatment (800 °C), the carbon aerogel (NC-GO@NFC) with an architectural structure was manufactured by combining 2D monolayer graphene with 1D nano-fibrillated cellulose. The pore volume (0.55 cm3/g) and specific surface area (441 m2/g) of NC-GO@NFC were about two times higher than those of GO carbon aerogel. Particularly, the buoyant porous aerogel showed superhydrophobicity with a large water contact angle (155.5°) due to the increase of -NH- and CC as well as the pyrolysis of hydrophilic groups. The superhydrophobicity endows the aerogel with an exceptional oil/water separation performance. The carbon aerogels exhibited the adsorption capability towards many organic phases (including lubricating oil and some organic solvents). In addition, the efficient continuous removal and collection of organic solvents (methylbenzene) from water surface was achieved by a designed water/oil pump device. Therefore, the recyclable 3D porous composite aerogel had the application potential as organic solvent adsorbents and oil/water separation agents.
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•rGO is efficiently exfoliated into monolayer by NFC on the basis of ion attraction.•The BET surface area and pore volume of the as-prepared aerogel increased by a factor of two, compared to the GO aerogel.•The aerogel exhibits continuous selective and collection of oil/water separation.
A recent study published in mBio by Cao et al. demonstrated that the helminth Trichinella sprialis (Ts) alleviates COVID-19-related cytokine storms in an IL-9-dependent way (Z. Cao, J. Wang, X. Liu, ...Y. Liu, et al., mBio 15:e00905-24, 2024, https://doi.org/10.1128/mbio.00905-24). A cytokine storm is a severe immune response characterized by the overproduction of proinflammatory cytokines, such as TNF-α and IFN-γ, leading to tissue damage and mortality in COVID-19 patients. This study indicated that IL-9 is crucial in protecting against cytokine storm syndromes associated with SARS-CoV-2 infection and proposed that anti-inflammatory molecules from Ts excretory/secretory (TsES) products could be a novel source for treating such illnesses.
Parkinson's disease (PD) is a progressive neurological disorder that affects millions of people throughout the world. Cuproptosis is a newly discovered form of programmed cell death linked to several ...neurological disorders. Nevertheless, the precise mechanisms of Cuproptosis-related genes (CRGs) in PD remain unknown. This study investigated immune infiltration and CRG expression profiling in patients with Parkinson's disease and healthy controls. Subsequently, we construct a predictive model based on 5 significant CRGs. The performance of the predictive model was validated by nomograms and external datasets. Additionally, we classified PD patients into two clusters based on CRGs and three gene clusters based on differentially expressed genes (DEG) of CRGs clusters. We further evaluated immunological characterization between the different clusters and created the CRGs scores to quantify CRGs patterns. Finally, we investigate the prediction of CRGs drugs and the ceRNA network, providing new insights into the pathogenesis and management of PD.
Vegetation effectively prevents soil erosion. However the relationship between plant diversity and soil erosion remains ambiguous under various environmental conditions. To explore the role that ...plant diversity plays in soil erosion, this study was conducted in the Three-River-Source region, located in the hinterlands of the Qinghai–Tibet Plateau, China. After examining 99 plots within the study area, and analyzing the soil 137Cs inventory within the plots, we found that with a greater number of plants distributed within an aggregation pattern, there was greater interception of the soil particles by the vegetation patch. This phenomenon results in a more developed vegetation patch that can support greater vegetation coverage and higher plant diversity than it previously could. Although a positive correlation exists between plant diversity and vegetation coverage, the relationship between the extent of soil erosion and plant diversity is modulated by the vegetation pattern. When plants are distributed in a relatively homogeneous pattern, vegetation coverage decreases with increasing plant diversity, which leads to increased soil erosion. When plants are distributed between a homogenous and a heterogeneous pattern, no relationship is found between plant diversity and soil erosion. With a heterogeneous plant distribution, vegetation coverage increases with plant diversity, and soil erosion is inhibited under such conditions.
•The relationship between plant diversity and soil erosion is ambiguous.•This relationship is negative within a homogenous vegetation pattern.•This relationship is positive within a heterogeneous vegetation pattern.•Vegetation and soil erosion processes are unified with each other.•No vegetation factor has an isolated effect on soil erosion.
With the increasing concern regarding the undesirable environmental and socioeconomic consequences of petrochemicals and limited fossil resources, biomass, bio-based polymers, and other renewable ...natural resources have increasingly become alternatives for the production of functional materials ...
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