Using the extended science citation index database (SCI) and social science citation index (SSCI) databases, this paper analyzed the characteristics of publications, research foundations, research ...hotspots, and the evolutionary tracks of studies in the field of energy, environment, and climate change from 1990 to 2019 using a bibliometric method. This method is useful because it involves the quantitative analysis of large amounts of literature, using mathematical and statistical method. The results showed that the United States (US), the United Kingdom (UK), and China were the countries with the most published papers in the field. The US plays a key role in the cooperation between international institutions. An assessment conducted by the Intergovernmental Panel on Climate Change (IPCC) created the standard scientific reference for the research on climate change and its consequences. From 2006 to 2016, a large number of co-cited papers laid a solid foundation for research in the field. During this period, the research focused on the impact of climate change on the ecological environment, began to propose different countermeasures, and formed a set of mature research methods. From 2017 to 2019, there was an acceleration in the growth rate of the number of published articles. Strategies to address climate change, including renewable energy and energy transition, were the focus during this phase. Future studies are expected to focus on climate change mitigation strategies and energy policies. The findings provide a reference for researchers and can help policy makers balance economic development with environmental protection.
Photosynthesis is a process wherein the chromophores in plants and bacteria absorb light and convert it into chemical energy. To mimic this process, an emissive poly(ethylene glycol)‐decorated ...tetragonal prismatic platinum(II) cage was prepared and used as the donor molecule to construct a light‐harvesting system in water. Eosin Y was chosen as the acceptor because of its good spectral overlap with that of the metallacage, which is essential for the preparation of light‐harvesting systems. Such a combination showed enhanced catalytic activity in catalyzing the cross‐coupling hydrogen evolution reaction, as compared with eosin Y alone. This study offers a pathway for using the output energy from the light‐harvesting system to mimic the whole photosynthetic process.
Harvest lights: An aqueous light‐harvesting system, based on a platinum(II) cage and eosin Y, demonstrates efficient energy transfer. The system showed improved photocatalytic activity in a cross‐coupling hydrogen evolution reaction compared with the reaction employing just eosin Y alone.
The removal of material in the ductile regime while improving machining efficiency is currently the technical bottleneck in grinding zirconia ceramics. Prediction models of minimum chip thickness (
h
...min
) and ductile–brittle transition chip thickness (
h
d–b
) were developed according to grinding mechanism. Results showed that both
h
min
and
h
d–b
decreased with increasing friction coefficient. Grinding experiments were carried out using the maximum undeformed chip thickness as the input parameter. Experimental results showed that the
h
min
value in dry grinding is 0.24 μm. Meanwhile, the
h
min
values under minimum quantity lubrication (MQL) and nanoparticle jet MQL (0.4, 0.8, 1.2, 1.6, and 2 vol.%) are 0.27, 0.34, 0.49, 0.65, 0.76, and 0.91 μm, respectively. Furthermore, the
h
d–b
value in dry grinding is 0.8 μm, and the
h
d–b
values under lubrication condition that corresponds to
h
min
are 1.79, 1.98, 2.15, 2.27, 2.39, and 2.59 μm, respectively. The experimental results show the same trend as that of the prediction model. The theoretical calculation is basically consistent with the measured values, with model errors of 7.9% and 6.3%, thereby verifying the accuracy of the chip thickness models.
•Different concentration nanofluids jet MQL grinding with Ni-based alloy was experimented.•Friction coefficient, surface roughness and autocorrelation function was used to evaluate ...experiment.•Nanofluids MQL achieves higher machining precision and surface quality.•MoS2-CNTs nanofluids contribute better lubrication effect compared to pure nanoparticle.•8% is the optimal addition mass fraction of MoS2-CNTs nanopaticles in nanofluids.
The effect of nanoparticle concentration on the lubricating property of nanofluids for minimum quantity lubrication (MQL) grinding was experimentally investigated based on the status of nanofluid MQL. Different concentrations of nanofluids with molybdenum disulfide (MoS2), carbon nanotubes (CNTs), and their mixtures (MoS2-CNTs) were prepared. Difficult-to-cut Ni-based alloy was used as the workpiece material to explore the effect of mass fraction of nanofluids on grinding force ratio (G) and workpiece surface quality. The statistical analysis of grinding force ratio and surface roughness (Ra) were performed using one-way analysis of variance followed by Tukey’s post-hoc test with confidence intervals (CI) of 95%.
Results showed that given the same mass fraction, MoS2-CNTs achieved lower G GMix (8%)=0.274 and surface roughness (Ra=0.328μm) than MoS2 and CNTs. These characteristics were attributed to the physical collaboration of the mixed nanoparticles. For the same nanoparticle, G decreased initially, reaching the lowest value at 8% GMix (8%)=0.274, and then increased with the increase in mass fraction of nanofluids because of the influence of agglomeration. Ra, increased gradually with the increase in viscosity of nanofluids. Autocorrelation analysis shows that MoS2-CNT nanofluid MQL achieved the lowest autocorrelation initial value (RMix=0.64) when τ=0. This result confirms that MoS2-CNT nanofluid MQL could improve machining precision and surface quality. Among different concentrations of nanofluids, the high-frequency continuous oscillation of the autocorrelation curve of the 8% MoS2-CNTs indicated improved workpiece surface quality. Combined friction coefficient, Ra, and autocorrelation analytical results show that 8% MoS2-CNTs was the optimum concentration for nanofluid MQL in the experiment. Autocorrelation analysis of the profile curves reveals the microstructural information of the workpiece surface and, combined with Ra analysis, provides a better method of analyzing the surface quality of a workpiece.
Seahorses have a circum-global distribution in tropical to temperate coastal waters. Yet, seahorses show many adaptations for a sedentary, cryptic lifestyle: they require specific habitats, such as ...seagrass, kelp or coral reefs, lack pelvic and caudal fins, and give birth to directly developed offspring without pronounced pelagic larval stage, rendering long-range dispersal by conventional means inefficient. Here we investigate seahorses' worldwide dispersal and biogeographic patterns based on a de novo genome assembly of Hippocampus erectus as well as 358 re-sequenced genomes from 21 species. Seahorses evolved in the late Oligocene and subsequent circum-global colonization routes are identified and linked to changing dynamics in ocean currents and paleo-temporal seaway openings. Furthermore, the genetic basis of the recurring "bony spines" adaptive phenotype is linked to independent substitutions in a key developmental gene. Analyses thus suggest that rafting via ocean currents compensates for poor dispersal and rapid adaptation facilitates colonizing new habitats.
VEGFR2 (KDR/Flk1) signaling in endothelial cells (ECs) plays a central role in angiogenesis. The P-type ATPase transporter ATP7A regulates copper homeostasis, and its role in VEGFR2 signaling and ...angiogenesis is entirely unknown. Here, we describe the unexpected crosstalk between the Copper transporter ATP7A, autophagy, and VEGFR2 degradation. The functional significance of this Copper transporter was demonstrated by the finding that inducible EC-specific ATP7A deficient mice or ATP7A-dysfunctional ATP7Amut mice showed impaired post-ischemic neovascularization. In ECs, loss of ATP7A inhibited VEGF-induced VEGFR2 signaling and angiogenic responses, in part by promoting ligand-induced VEGFR2 protein degradation. Mechanistically, VEGF stimulated ATP7A translocation from the trans-Golgi network to the plasma membrane where it bound to VEGFR2, which prevented autophagy-mediated lysosomal VEGFR2 degradation by inhibiting autophagic cargo/adapter p62/SQSTM1 binding to ubiquitinated VEGFR2. Enhanced autophagy flux due to ATP7A dysfunction in vivo was confirmed by autophagy reporter CAG-ATP7Amut -RFP-EGFP-LC3 transgenic mice. In summary, our study uncovers a novel function of ATP7A to limit autophagy-mediated degradation of VEGFR2, thereby promoting VEGFR2 signaling and angiogenesis, which restores perfusion recovery and neovascularization. Thus, endothelial ATP7A is identified as a potential therapeutic target for treatment of ischemic cardiovascular diseases.
Considering the poor lubricating effect of cryogenic air (CA) and inadequate cooling ability of nanofluid minimum quantity lubrication (NMQL), this work proposes a new manufacturing technique ...cryogenic air nanofluid minimum quantity lubrication (CNMQL). A heat transfer coefficient and a finite difference model under different grinding conditions were established based on the theory of boiling heat transfer and conduction. The temperature field in the grinding zone under different cooling conditions was simulated. Results showed that CNMQL exerts the optimal cooling effect, followed by CA and NMQL. On the basis of model simulation, experimental verification of the surface grinding temperature field under cooling conditions of CA, MQL, and CNMQL was conducted with Ti–6Al–4V as the workpiece material. Simultaneously, CNMQL exhibits the smallest specific tangential and normal grinding forces (2.17 and 2.66 N/mm, respectively). Further, the lowest grinding temperature (155.9 °C) was also obtained, which verified the excellent cooling and heat transfer capabilities of CNMQL grinding. Furthermore, the experimental results were in agreement with theoretical analysis, thereby validating the accuracy of the theoretical model.
Vascular endothelial growth factor receptor type 2 (VEGFR2, also known as KDR and FLK1) signalling in endothelial cells (ECs) is essential for developmental and reparative angiogenesis. Reactive ...oxygen species and copper (Cu) are also involved in these processes. However, their inter-relationship is poorly understood. Evidence of the role of the endothelial Cu importer CTR1 (also known as SLC31A1) in VEGFR2 signalling and angiogenesis in vivo is lacking. Here, we show that CTR1 functions as a redox sensor to promote angiogenesis in ECs. CTR1-depleted ECs showed reduced VEGF-induced VEGFR2 signalling and angiogenic responses. Mechanistically, CTR1 was rapidly sulfenylated at Cys189 at its cytosolic C terminus after stimulation with VEGF, which induced CTR1-VEGFR2 disulfide bond formation and their co-internalization to early endosomes, driving sustained VEGFR2 signalling. In vivo, EC-specific Ctr1-deficient mice or CRISPR-Cas9-generated redox-dead Ctr1(C187A)-knockin mutant mice had impaired developmental and reparative angiogenesis. Thus, oxidation of CTR1 at Cys189 promotes VEGFR2 internalization and signalling to enhance angiogenesis. Our study uncovers an important mechanism for sensing reactive oxygen species through CTR1 to drive neovascularization.
Accurately measuring carbon dioxide (CO2) emissions is critical for effectively implementing carbon reduction policies, and China’s increased investment in reducing CO2 emissions is expected to ...significantly impact the world. In this study, the potential of shallow learning for predicting CO2 emissions was explored. Data included CO2 emissions, renewable energy consumption, and the share of primary, secondary, and tertiary industries in China from 1965 to 2021. These time-series data were converted into labeled sample data using the sliding window method to facilitate a supervised learning model for CO2 emission prediction. Then, different shallow learning models with k-fold cross-validation were used to predict China’s short-term CO2 emissions. Finally, optimal models were presented, and the important features were identified. The key findings were as follows. (1) The combined model of RF and LASSO performed best at predicting China’s short-term CO2 emissions, followed by LASSO and SVR. The prediction performance of RF was very fragile to the window width. (2) The sliding window method is used to convert time series predictions into supervision learning problems, and historical data can be used to predict future carbon dioxide emissions. To ensure that the feature data are real, the model can predict CO2 emissions for up to six years ahead. (3) Cross-validation and grid search were critical for optimizing China’s CO2 emissions prediction with small datasets. (4) By 2027, carbon dioxide emissions will continue to grow and reach 10.3 billion tons. It can be seen that the task of China to achieve its carbon peak on schedule is very heavy. The results indicate that an increase in renewable energy consumption and adjustments in industrial structure will continue to play an important role in curbing China’s CO2 emissions.
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