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New energy industries, such as wind and photovoltaic (PV) power generation, are key to supporting the carbon peaking and carbon neutrality goals of China. The installed capacity of wind and PV power in China is the largest worldwide; therefore, it is necessary to secure the supply of key metal materials and conduct a more accurate management of emerging solid wastes. This study sets different development scenarios based on the historical data and planning objectives of wind and PV power industries of China. It assesses the demand, waste, and supply of key metals in China’s new energy industry using a life distribution model of wind and PV power generation equipment, and focuses on identifying the supply pressure of silver, copper, gallium, silver, steel, and neodymium,thereby providing a basic support for realizing the green and low-carbon development of the energy industry by 2060. In the baseline scenario, the decommissioned volume of the wind and PV power generation industries will reach 4.6 GW and 28.3 GW in 2035,respectively; and the total decommissioned volume (by mass) of both wind and PV power generation equipment will reach 2.54 ×106 t and 1.048 ×107 t in 2035 and 2060, respectively. In terms of the supply of key metals for the new energy industry during 2030‒2060,iron and steel have a low supply risk (≤5%), neodymium has a medium-high supply risk (25%‒50%), copper and silver have a high supply risk (50%‒100%), and the supply of gallium and indium are at an extremely high risk owing to their excessive peak demand.To improve the security and diversity of the supply chain of the new energy industry, it is necessary to ensure the sustainable supply of metal mineral resources and promote material recycling and efficient use. Furthermore, we propose the following recommendations:(1) treating decommissioned equipment for wind and PV power generation as waste electrical and electronic products, (2) incorporating wind and PV power generation enterprises into the Catalogue of Classified Management of Pollutant Discharge Permits for Stationary Pollution Sources, (3) improving the distributed new-energy solid-waste recycling system, and (4) developing recycling technologies for emerging solid wastes.

Objective To explore the application value of machine learning in preliminary evaluation of the degree of co-ronary artery stenosis caused by different types of plaques. Methods Eighty patients who underwent coronary CT angiography (CCTA) and coronary angiography (CAG) in the following 14 d from January 2020 to October 2022 were selected. During CCTA, 103 coronary artery stenosis sites were randomly selected and divided into calcified plaque group (38 sites), non-calcified plaque group (34 sites), and mixed plaque group (31 sites) according to plaque properties. Subjective evaluation (SA), post-processing workstation measurement (AW), artificial intelligence (AI), and SA combined with AI (Semi-AI) were used to assess the degree of coronary artery stenosis caused by plaques in each group. CAG results were used as the gold standard for the degree of coronary artery stenosis. The coincidence, underestimation, and overestimation rates were calculated based on the gold standard and compared between the four methods. Results Among the four methods, there were no significant differences in the coincidence rate, underestimation rate, and overestimation rate between AI and SA (P>0.008 3). In the evaluation of non-calcified plaque and mixed plaque, the coincidence rate of AI was significantly higher than those of AW and Semi-AI (χ2=7.65-16.20,P0.05). In the evaluation of calcified plaque and mixed plaque, the overestimation rate of Semi-AI was significantly lower than those of the other three methods (χ2=8.77-23.62,P

Anterior cruciate ligament (ACL) injury is a common sports injury, and ACL reconstruction is an effective surgery for this trauma. Most cases gain good recovery after surgery, while some patients may experience knee stiffness, which is characterized by joint fibrosis, leading to reduced joint mobility, pain, and dysfunction. Currently, various research studies have been conducted to unveil the mechanisms underlying this condition, identifying pre-, intra-, and post-operative risk factors, and testify the efficacy of different therapeutic methods against it. In this review, we summarize the current progress regarding the advancements in knee fibrosis after ACL reconstruction. The risk factors associated with knee fibrosis are systematically delineated, accompanied by an evaluation of the efficacy of various treatment modalities for both the prevention and mitigation of fibrosis. Furthermore, recommendations for future research directions are proposed, offering a foundational basis for subsequent investigations. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) metabarcoding has been widely used in freshwater systems, contributing to the advancements in the monitoring of fish diversity and community species composition. Nevertheless, the accuracy and reliability of eDNA metabarcoding in assessing functional structures and revealing the mechanisms underlying fish community assembly remain unclear. In this study, we combined a traditional survey method (electrofishing) and eDNA metabarcoding to conduct fish stock monitoring in the upper reaches of the Huishui stream. We assessed taxonomic and functional structures, as well as community assembly mechanisms, during dry and wet seasons. The results revealed that, compared with electrofishing surveys, eDNA metabarcoding detected a greater number of species and higher functional richness in both seasons. Despite significant differences in fish taxonomic composition between the seasons, both eDNA and traditional methods indicated that environmental filtering dominated the process of fish community assembly in both dry and wet seasons. We showed that eDNA metabarcoding is comparable to the electrofishing method in monitoring the community composition of stream fish and can accurately and reliably determine fish community assembly mechanisms. Combining functional traits and eDNA is a robust approach for monitoring stream fish community compared to taxonomic uncertainty. [ABSTRACT FROM AUTHOR]

TiB2 nanoparticles with a bandgap of 0 eV were prepared, and the corresponding nonlinear optical response at 2.85 μm was investigated. Employing a TiB2 as a saturable absorber, a 2.85 μm pulsed Er:Lu2O3 crystal laser with an average output power of 1.2 W was achieved under a maximum pump power of 9.51 W. Laser pulses with durations of ~203 ns were delivered at a repetition rate of 154 kHz, which corresponds to a pulse energy of ~7.8 µJ and a peak power of 39.3 W. As far as we know, the result represents the highest average output power from all Q-switched Er:Lu2O3 crystal lasers. [ABSTRACT FROM AUTHOR]