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Thermal insulation composites are widely used in civil and military applications; however, it is difficult to achieve the synergy of multiple technical objectives such as lightweight, thermal insulation, high pressure resistance and high-temperature resistance by adopting traditional preparation techniques. In this study, a novel carbon-graphite thermal insulation material was rapidly prepared by exploiting the micro-thermal press additive manufacturing forming technology, and these multiple objectives were simultaneously achieved by introducing a large number of closed pores. It was found that the percentage of closed pores in the carbon-graphite insulation was increased by increasing the forming density or the amount of thermosetting phenolic resin added, but the thermal conductivity increased in parallel with the compressive strength, while the addition of pre-covered expandable graphite was able to achieve the synergy of high compressive strength and low thermal conductivity. When the content of thermosetting phenolic resin was 25 wt%, forming density was 1.2 g·cm−3, and expandable graphite was clad twice, the prepared carbon-graphite insulation exhibited a closed porosity/porosity ratio, compressive strength, and thermal conductivity of 48.92%, 16.432 MPa, and 0.743 W·m −1 K−1, which has the advantages of lightweight, high compressive strength, heat insulation and high-temperature resistance and has good prospects for industrial applications.

Molybdenite and chalcopyrite closely coexist and have good natural floatability. During the Cu-Mo separation process, it is necessary to enhance the inhibition of chalcopyrite to reduce its influence on molybdenite. In this paper, a combined inhibitor, sodium thioglycollate (HSCH2COONa) and sodium sulfide (Na2S), with a molar ratio of 2:1, was obtained through pure mineral flotation experiments. It could reduce the impact on molybdenite while maintaining a good inhibitory effect on chalcopyrite. In the artificial mixed minerals test, the use of the combined inhibitor (80 mg/L) can achieve good indicators with Mo grade and recovery rate of 54.34% and 88.12%, respectively, and Cu grade of 2.15%. The contact angle test shows that the combined inhibitor can significantly reduce the wettability of the chalcopyrite surface while having a relatively small effect on molybdenite. The infrared spectroscopy and SEM-EDS energy spectrum indicated that the combined inhibitor C = O and S-H groups underwent chemical reactions on the surface of chalcopyrite and squeezed out kerosene on the surface of chalcopyrite. Molecular dynamics simulations indicate that the HS−, S2−, and HSCH2COO− components in the combined inhibitor are more likely to act on the surface of chalcopyrite, exerting an enhanced inhibitory effect on chalcopyrite.

Fault fracture zones, characterized by high weathering, low strength, and a high degree of fragmentation, are common adverse geological phenomena encountered in tunneling projects. This paper performed a series of large-scale triaxial compression tests on the cohesive soil–rock mixture (SRM) samples with dimensions of 500 mm × 1000 mm to investigate the influence of rock content PBV (20, 40, and 60% by volume), rock orientation angle α, and confining pressure on their macro-mechanical properties. Furthermore, a triaxial numerical model, which takes into account PBV and α, was constructed by means of PFC3D to investigate the evolution of the mechanical properties of the cohesive SRM. The results indicated that (1) the influence of the α is significant at high confining pressures. For the sample with an α of 0°, shear failure was inhibited, and the rock blocks tended to break more easily, while the samples with an α of 30° and 60° exhibited fewer fragmentations. (2) PBV significantly affected the shear behaviors of the cohesive SRM. The peak deviatoric stress of the sample with an α of 0° was minimized at lower PBV (<20%), while both the deformation modulus and peak deviatoric stress were larger at high PBV (>60%). Based on these findings, an equation correlating shear strength and PBV was proposed under consistent α and matrix strength conditions. This equation effectively predicts the shear strength of the cohesive SRM with different PBV values.

Under the combined influence of climate change and urban development, the risk of urban flooding caused by extreme weather events has increased significantly, making assessing flood vulnerability and resilience increasingly crucial for urban flood management. With the 45 counties in Qinghai Province as the research objects, the hazard risk of flood and exposure are combined to study their vulnerability. At the same time, resilience is evaluated by the indicators selected from four dimensions (society, economy, environment, and infrastructure). Through Z-scoring, the vulnerability and resilience of each county are clustered into four groups to explore their associations from a spatial balance perspective. Obstacle factor analysis is introduced to summarize the key factors affecting the improvement of urban resilience in Qinghai Provence. The results show that the eastern areas of Qinghai experience high vulnerability to flooding because of high levels of hazard and exposure. What is more, Xining, Haidong, and Haixi experience a high level of resilience. A strong spatial mismatch between vulnerability and resilience exists in Qinghai, with 24 counties (58%) being self-adapted, 8 counties (18%) over-abundant, and 11 counties deficient in terms of nature–nurture. The length of levee and number of beds in medical institutions are the main obstacles to resilience in Qinghai. The research results can provide a theoretical and scientific basis for future urban flood management and resilience development in the Qinghai–Tibetan Plateau.

The impacts of land use/cover change (LUCC) on hydrological processes and water resources are mainly reflected in changes in runoff and pollutant variations. Low impact development (LID) technology is utilized as an effective strategy to control urban stormwater runoff and pollution in the urban catchment. In this study, the impact of LUCC on runoff and pollutants in an urbanizing catchment of Guang-Ming New District in Shenzhen, China, were quantified using a dynamic rainfall-runoff model with the EPA Storm Water Management Model (SWMM). Based on the simulations and observations, the main objectives of this study were: (1) to evaluate the catchment runoff and pollutant variations with LUCC, (2) to select and optimize the appropriate layout of LID in a planning scenario for reducing the growth of runoff and pollutants under LUCC, (3) to assess the optimal planning schemes for land use/cover. The results showed that compared to 2013, the runoff volume, peak flow and pollution load of suspended solids (SS), and chemical oxygen demand increased by 35.1%, 33.6% and 248.5%, and 54.5% respectively in a traditional planning scenario. The assessment result of optimal planning of land use showed that annual rainfall control of land use for an optimal planning scenario with LID technology was 65%, and SS pollutant load reduction efficiency 65.6%.

Bamboo is one of the most important forest resources with a strong carbon fixation capability. To utilize genetic resource of Phyllostachys violascens, ISSR (inter-simple sequence repeat), SRAP (sequence-related amplified polymorphism), and AFLP (amplified fragment length polymorphism) techniques were used for the first time for the assessment of genetic diversity within its different cultivars. A total of 209 (136 polymorphic), 222 (152 polymorphic), and 434 (253 polymorphic) bands were detected using 15 ISSR primers, 15 primer combinations of SRAP, and 15 primer combinations of AFLP, respectively. The mean genetic similarity of Ph. violascens was 0.872, 0.867 or 0.871 for the ISSR, SRAP and AFLP analyses, respectively. Based on genetic diversity, all the cultivars of Ph. violascens could be divided into four groups, which are reflected by their morphologies. Our data demonstrated that all three methods are useful in the identification of genetic diversity in Ph. violascens, but AFLP is the most efficient.

We report a voltage generator based on a graphene network （GN）. In response to the movement of a droplet of ionic solution over a GN strip, a voltage of several hundred millivolts is observed under ambient conditions. In the voltage-generation process, the unique structure of GN plays an important role in improving the rate of electron transfer. Given their excellent mechanical properties, GNs may find applications for harvesting vibrational energy in various places such as raincoats, umbrellas, windows, and other surfaces that are exposed to rain.

Developing vision-language models (VLMs) capable of understanding 3D scenes has been a longstanding goal in the 3D-VL community. Despite recent progress, 3D VLMs still fall short of their 2D counterparts in capability and robustness. A key bottleneck is that current scene representations struggle to balance performance and efficiency: competitive performance comes at the cost of heavy token overhead, which in turn hampers the scalability of 3D-VL learning. To address this, we propose the condensed feature grid (CFG), an efficient scene representation featuring significantly reduced token overhead and strong perception capability. Building on CFG, we introduce LEO-VL, a 3D VLM trained on 700k 3D-VL data spanning four real-world indoor domains and five tasks such as captioning and dialogue. To enhance the robustness of 3D VLM, we further propose SceneDPO for post-training, which involves contrasts across answers and scenes. LEO-VL achieves state-of-the-art performance on various 3D QA benchmarks, including SQA3D, MSQA, and Beacon3D. Our extensive experiments highlight the efficiency of our representation, the benefit of task and scene diversity, consistent scaling effects, and the advantages of SceneDPO compared to SFT and GRPO. We hope our findings advance the efficiency, scalability, and robustness of future 3D VLMs.

The world of small noncoding RNAs (sncRNAs) is ever-expanding, from small interfering RNA, microRNA and Piwi-interacting RNA to the recently emerging non-canonical sncRNAs derived from longer structured RNAs (for example, transfer, ribosomal, Y, small nucleolar, small nuclear and vault RNAs), showing distinct biogenesis and functional principles. Here we discuss recent tools for sncRNA identification, caveats in sncRNA expression analysis and emerging methods for direct sequencing of sncRNAs and systematic mapping of RNA modifications that are integral to their function. Shi et al. discuss recent approaches for the discovery of small noncoding RNAs (sncRNAs), limitations associated with sncRNA expression analyses, and emerging methods for direct and simultaneous detection of multiple RNA modifications.

To overcome the limitations of classical MPCC for brushless DC motors, which allows only one voltage vector per cycle causing tracking issues, we propose a dual-vector MPCC strategy. This divides the voltage vector plane into six sectors and 14 sub-sectors. By identifying the sub-sector, the optimal voltage vector combination is selected, and action times are calculated to minimize the cost function. This uses two voltage vectors per cycle. Effectiveness is confirmed through simulations.