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We prove that every smooth Fano threefold from the family N o ̲ 2.8 is K-stable. Such a Fano threefold is a double cover of the blow-up of P 3 at one point branched along an anti-canonical divisor.

With the rapid development of information technology and the uniquity of audiovisual materials, applying audiovisual translation (AVT) in language education (LE) has emerged as a growing interdisciplinary research field (Torralba et al., 2022; Talaván & Lertola, 2022). This scoping review attempts to map out the current research landscape of the pedagogical use of AVT in LE, identify knowledge gaps and propose future research directions. Following the PRISMA Extension for Scoping Reviews—PRISMA-ScR—(Tricco et al., 2018), a quantitative analysis of predefined categories was conducted based on 162 studies, focusing on three key areas: publication characteristics, contextual factors and research design. Additionally, this review contrasts using AVT in LE across European and non-European contexts, summarising general research trends and discussing future implications. Findings indicate a significant rise in research in this area since 2021, of which experimental designs in higher education, primarily targeting English language learning outcomes, are the most common. Increasing attention is being paid to AVT’s role in enhancing integrated and transferable skills; however, there are significant geographical disparities: Europe leads the field in terms of research diversity and innovation, while studies in non-European countries tend to focus predominantly on the passive use of subtitling for English learning, aimed at improving specific linguistic skills. Recommendations for future research include promoting greater international and interdisciplinary collaboration, as well as a broader inclusion of diverse target languages and educational settings.

As autonomous driving technology continues to advance and gradually become a reality, ensuring the safety of autonomous driving in complex traffic scenarios has become a key focus and challenge in current research. Model-free deep reinforcement learning (Deep Reinforcement Learning) methods have been widely used for addressing motion planning problems in complex traffic scenarios, as they can implicitly learn interactions between vehicles. However, current planning methods based on deep reinforcement learning exhibit limited robustness and generalization performance. They struggle to adapt to traffic conditions beyond the training scenarios and face difficulties in handling uncertainties arising from unexpected situations. Therefore, this paper addresses the challenges presented by complex traffic scenarios, such as signal-free intersections. It does so by first utilizing the historical trajectories of adjacent vehicles observed in these scenarios. Through a Variational Auto-Encoder (VAE) based on the Gated Recurrent Unit (GRU) recurrent neural network, it extracts driver style features. These driver style features are then integrated with other state parameters and used to train a motion planning strategy within an extended reinforcement learning framework. This approach ultimately yields a more robust and interpretable mid-to-mid motion planning method. Experimental results confirm that the proposed method achieves low collision rates, high efficiency, and successful task completion in complex traffic scenarios.

The conventional strategy for cancer gene therapy offers limited control of specificity and efficacy. A possible way to overcome these limitations is to construct logic circuits. Here we present modular AND gate circuits based on CRISPR-Cas9 system. The circuits integrate cellular information from two promoters as inputs and activate the output gene only when both inputs are active in the tested cell lines. Using the luciferase reporter as the output gene, we show that the circuit specifically detects bladder cancer cells and significantly enhances luciferase expression in comparison to the human telomerase reverse transcriptase-renilla luciferase construct. We also test the modularity of the design by replacing the output with other cellular functional genes including hBAX , p21 and E-cadherin . The circuits effectively inhibit bladder cancer cell growth, induce apoptosis and decrease cell motility by regulating the corresponding gene. This approach provides a synthetic biology platform for targeting and controlling bladder cancer cells in vitro . Tools derived from synthetic biology offer powerful means to refine drug delivery and disease detection. Liu et al . engineer a logical AND gate using CRISPR-Cas9 to drive gene expression only cells in which two promoters are active, and use it to selectively inhibit the growth of bladder cancer cells in vitro .

Pressure-driven, superfast organic solvent filtration membranes have significant practical applications. An excellent filtration membrane should exhibit high selectivity and permeation in aqueous and organic solvents to meet increasing industrial demand. Here, we report an amino functionalized boron nitride (FBN) based filtration membrane with a nanochannel network for molecular separation and permeation. This membrane is highly stable in water and in several organic solvents and shows high transport performance for solvents depending on the membranes’ thickness. In addition, the FBN membrane is applicable for solute screening in water as well as in organic solvents. More importantly, the FBN membranes are very stable in acidic, alkaline and oxidative media for up to one month. The fast-flow rate and good separation performance of the FBN membranes can be attributed to their stable networks of nanochannels and thin laminar structure, which provide the membranes with beneficial properties for practical separation and purification processes. 2D materials show promise for membrane filtration technologies, but their permeance to organic solvents is typically poor. Here, the authors prepare functionalized boron nitride membranes with high flux and high molecular separation performances in both aqueous solutions and organic solvents.

With the rise and expansion of responsible and sustainable investing in recent years, ESG investing is one of the categories that has gained momentum. This literature review aims to bring ESG investing and its current state of development to a broader audience. The article first introduces the concepts related to ESG and the ESG ecosystem, demonstrating the current manifestation of the framework in prestigious corporations among different industries with in-depth case studies. In addition to understanding the content and structure of ESG, it is essential to recognize the controversial topics that have been argued in recent years. This article also highlights the current inconsistencies in ESG disclosure and the examination of its financial performance by authoritative bodies to bring a deeper and more contemporary understanding of ESG investing. Lastly, it draws out the improvement solutions that are currently available to refine ESG investing by demonstrating the most up-to-date policy announcements.

In this paper, we propose a multimodal flexible sensory interface for interactively teaching soft robots to perform skilled locomotion using bare human hands. First, we develop a flexible bimodal smart skin (FBSS) based on triboelectric nanogenerator and liquid metal sensing that can perform simultaneous tactile and touchless sensing and distinguish these two modes in real time. With the FBSS, soft robots can react on their own to tactile and touchless stimuli. We then propose a distance control method that enabled humans to teach soft robots movements via bare hand-eye coordination. The results showed that participants can effectively teach a self-reacting soft continuum manipulator complex motions in three-dimensional space through a “shifting sensors and teaching” method within just a few minutes. The soft manipulator can repeat the human-taught motions and replay them at different speeds. Finally, we demonstrate that humans can easily teach the soft manipulator to complete specific tasks such as completing a pen-and-paper maze, taking a throat swab, and crossing a barrier to grasp an object. We envision that this user-friendly, non-programmable teaching method based on flexible multimodal sensory interfaces could broadly expand the domains in which humans interact with and utilize soft robots. Soft robots are challenging to model and program. Non-specialists face non-negligible obstacles when working with soft robots to perform tasks. Here, the authors propose a method to interactively teach soft robots complex motions through flexible touchless and tactile multimodal sensors.

Flexible organic−inorganic hybrids are promising thermoelectric materials to recycle waste heat in versatile formats. However, current organic/inorganic hybrids suffer from inferior thermoelectric properties due to aggregate nanostructures. Here we demonstrate flexible organic−inorganic hybrids where size-tunable Bi 2 Te 3 nanoparticles are discontinuously monodispersed in the continuous conductive polymer phase, completely distinct from traditional bi-continuous hybrids. Periodic nanofillers significantly scatter phonons while continuous conducting polymer phase provides favored electronic transport, resulting in ultrahigh power factor of ~1350 μW m −1  K −2 and ultralow in-plane thermal conductivity of ~0.7 W m −1  K −1 . Consequently, figure-of-merit (ZT) of 0.58 is obtained at room temperature, outperforming all reported organic materials and organic−inorganic hybrids. Thermoelectric properties of as-fabricated hybrids show negligible change for bending 100 cycles, indicating superior mechanical flexibility. These findings provide significant scientific foundation for shaping flexible thermoelectric functionality via synergistic integration of organic and inorganic components. The potential of flexible organic/inorganic hybrids for thermoelectrics is limited by the inability to control their microstructure. Here, the authors demonstrate polymer-nanoparticle hybrids with a monodispersed, periodic nanophase that shows high thermoelectric performance at room temperature.

The logical AND gate gene circuit based on the CRISPR-Cas9 system can distinguish bladder cancer cells from normal bladder epithelial cells. However, the layered artificial gene circuits have the problems of high complexity, difficulty in accurately predicting the behavior, and excessive redundancy, which cannot be applied to clinical translation. Here, we construct minigene circuits based on the CRISPReader, a technology used to control promoter-less gene expression in a robust manner. The minigene circuits significantly induce robust gene expression output in bladder cancer cells, but have nearly undetectable gene expression in normal bladder epithelial cells. The minigene circuits show a higher capability for cancer identification and intervention when compared with traditional gene circuits, and could be used for in vivo cancer gene therapy using the all-in-one AAV vector. This approach expands the design ideas and concepts of gene circuits in medical synthetic biology. Synthetic biology logic gates can be used to distinguish healthy cells from cancer cells. Here the authors design minigene circuits that show more robust identification of cancer cells compared to traditional genetic circuits.

How does strong state capacity in an authoritarian regime translate into police power? Do states with strong capacity enforce totalitarian-level policies in all areas equally? This article uses an examination of frontline police work in three provinces in China to show that policing is enforced unequally by issue area, and that high degrees of variation exist even within the same policing agenda. Two factors are vital to explain the mode of daily frontline policing: political pressure (either oral or via written directive) and individual incentives (including promotion, pay, and sense of pride). The results indicate a typology of four policing modes: zealous, deceptive, selective, and lazy policing.