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The direct and selective C(sp 3 )-H functionalization of cycloalkanes and alkanes is a highly useful process in organic synthesis owing to the low-cost starting materials, the high step and atom economy. Its application to asymmetric catalysis, however, has been scarcely explored. Herein, we disclose our effort toward this goal by incorporation of dual asymmetric photocatalysis by a chiral nickel catalyst and a commercially available organophotocatalyst with a radical relay strategy through sulfur dioxide insertion. Such design leads to the development of three-component asymmetric sulfonylation involving direct functionalization of cycloalkanes, alkanes, toluene derivatives or ethers. The photochemical reaction of a C(sp 3 )-H precursor, a SO 2 surrogate and a common α,β-unsaturated carbonyl compound proceeds smoothly under mild conditions, delivering a wide range of biologically interesting α-C chiral sulfones with high regio- and enantioselectivity (>50 examples, up to >50:1 rr and 95% ee). This method is applicable to late-stage functionalization of bioactive molecules, and provides an appealing access to enantioenriched compounds starting from the abundant hydrocarbon compounds. The direct and selective C(sp 3 )-H functionalization of cycloalkanes and alkanes is useful in organic synthesis but its application to asymmetric catalysis has been less explored. Here, the authors demonstrate the incorporation of a dual asymmetric photocatalyst which leads to the development of asymmetric sulfonylation involving direct functionalization of cycloalkanes, alkanes, toluene derivatives or ethers.

Development of practical deuteration reactions is highly valuable for organic synthesis, analytic chemistry and pharmaceutic chemistry. Deuterodehalogenation of organic chlorides tends to be an attractive strategy but remains a challenging task. We here develop a photocatalytic system consisting of an aryl-amine photocatalyst and a disulfide co-catalyst in the presence of sodium formate as an electron and hydrogen donor. Accordingly, many aryl chlorides, alkyl chlorides, and other halides are converted to deuterated products at room temperature in air (>90 examples, up to 99% D-incorporation). The mechanistic studies reveal that the aryl amine serves as reducing photoredox catalyst to initiate cleavage of the C-Cl bond, at the same time as energy transfer catalyst to induce homolysis of the disulfide for consequent deuterium transfer process. This economic and environmentally-friendly method can be used for site-selective D-labeling of a number of bioactive molecules and direct H/D exchange of some drug molecules. Deuterodehalogenation of organic chlorides is a useful strategy to install deuterium atoms at specific positions, however, it has several drawbacks. In this study, the authors report an organophotocatalytic system consisting of an aryl-amine-based photocatalyst and a common disulfide co-catalyst, for efficient deuteration of a wide range of aryl chlorides, alkyl chlorides and other halides, at room temperature in air.

What are the main findings? * We construct a large-scale, high-resolution optical–SAR registration dataset, pairing 3-m SAR imagery from the HongTu-1 satellite with Google Earth optical imagery at zoom level 17, covering the major geographical regions of China, and we release the standardized pipeline—including full-scene pairing, DEM-based terrain correction, geometric refinement, standardized 512 × 512 slicing and multi-stage quality filtering—that was used to build it. * Our proposed Log-domain reformulation of the Total Variation (Log-TV) filter substantially improves SAR image preprocessing by converting the multiplicative speckle noise model into an additive one, thereby enabling effective suppression of speckle while preserving edge structures and providing a much cleaner foundation for subsequent keypoint detection. * Combining a machine learning-based edge filter (Structured Random Forest, SRF) with the hand-crafted phase congruency filter yields a strong synergistic effect for cross-modal optical–SAR edge filtering, producing more stable and consistent shared structural responses than either component alone. We construct a large-scale, high-resolution optical–SAR registration dataset, pairing 3-m SAR imagery from the HongTu-1 satellite with Google Earth optical imagery at zoom level 17, covering the major geographical regions of China, and we release the standardized pipeline—including full-scene pairing, DEM-based terrain correction, geometric refinement, standardized 512 × 512 slicing and multi-stage quality filtering—that was used to build it. Our proposed Log-domain reformulation of the Total Variation (Log-TV) filter substantially improves SAR image preprocessing by converting the multiplicative speckle noise model into an additive one, thereby enabling effective suppression of speckle while preserving edge structures and providing a much cleaner foundation for subsequent keypoint detection. Combining a machine learning-based edge filter (Structured Random Forest, SRF) with the hand-crafted phase congruency filter yields a strong synergistic effect for cross-modal optical–SAR edge filtering, producing more stable and consistent shared structural responses than either component alone. What are the implications of the main findings? * Large-scale, high-resolution optical–SAR datasets are both essential and scarce for registration and other downstream tasks. Only on larger and more complex benchmarks do the robustness and the true relative performance of competing algorithms become evident, making such datasets a necessary foundation for future research in this area. * Different imaging modalities require different filtering strategies: for heavily speckled data such as SAR imagery, regularisation in the logarithmic domain is more appropriate than directly applying denoisers designed for additive noise, highlighting the importance of modality-aware preprocessing in cross-modal registration. * Hybrid pipelines that integrate learning-based components with hand-crafted filters are a promising direction: beyond edge filtering, similar combinations of deep features and classical hand-crafted operators may also benefit cross-modal feature description and matching stages. Large-scale, high-resolution optical–SAR datasets are both essential and scarce for registration and other downstream tasks. Only on larger and more complex benchmarks do the robustness and the true relative performance of competing algorithms become evident, making such datasets a necessary foundation for future research in this area. Different imaging modalities require different filtering strategies: for heavily speckled data such as SAR imagery, regularisation in the logarithmic domain is more appropriate than directly applying denoisers designed for additive noise, highlighting the importance of modality-aware preprocessing in cross-modal registration. Hybrid pipelines that integrate learning-based components with hand-crafted filters are a promising direction: beyond edge filtering, similar combinations of deep features and classical hand-crafted operators may also benefit cross-modal feature description and matching stages. Optical and Synthetic Aperture Radar (SAR) image registration is a fundamental task in remote sensing information fusion, yet it remains challenging due to significant differences in imaging mechanisms, radiation characteristics, and noise properties between the two modalities. Existing public datasets suffer from limited resolution, small scale, and insufficient scene diversity, and these limitations have hindered algorithm development. This paper constructs a large-scale, high-resolution optical–SAR registration dataset based on the HongTu-1 satellite 3-m SAR imagery and Google Earth optical imagery at zoom level 17, covering diverse scenes across China with a standardized pipeline including terrain correction, geometric alignment, standardized slicing, and quality filtering. Building upon this dataset, a hand-crafted keypoint-based cross-modal registration method is proposed, incorporating multi-level edge filtering and hybrid feature detection. Unlike conventional hand-crafted methods such as RIFT, SRIF, and LNIFT, which mainly refine keypoint detection, description, or matching within a SIFT-style pipeline, the core novelty of this work lies in SAR-specific preprocessing and multi-level hybrid filtering. These components are designed to suppress speckle while extracting more stable and discriminative shared edge responses for cross-modal registration. An improved Log-domain Total Variation (Log-TV) denoising model is introduced for SAR preprocessing. A hybrid edge filtering framework combining phase congruency analysis and Structured Random Forest (SRF) edge detection is constructed within a Gaussian scale space. A dual-branch feature detection scheme integrating blob and corner features is designed with a robust orientation assignment strategy. Feature description uses the Gradient Location–Orientation Histogram (GLOH) descriptor with Principal Component Analysis (PCA) reduction, while geometric estimation employs the Fast Sample Consensus (FSC) algorithm. Experiments on the self-constructed HT dataset and on the public OSdataset and SAR2Opt benchmarks show that the proposed method consistently achieves low RMSE and high success rates. It also maintains competitive efficiency among hand-crafted methods while retaining strong robustness to scale and rotation variations.

Objective We aimed to evaluate the effects of a clinical pharmacist-led-guidance-team (CPGT) on improving rational prophylactic injectable proton pump inhibitor use (PIPU) and to explore the application of the Plan–Do–Check–Act (PDCA) method in promoting rational PIPU. Methods We conducted a retrospective study among 814 patients at a Chinese tertiary teaching hospital from January 2017 to December 2018. We enrolled 98 patients before the PDCA; 297 and 419 patients were included in first- and second-round PDCA cycles, respectively. The CPGT established the criteria for PIPU and conducted interventions, including medical record reviews, provision of feedback, clinician education, and outcome analysis. We analyzed the appropriateness and costs of PIPU before and after establishment of the PDCA cycle. Results Implementation of continuous CPGT-led intervention and a PDCA cycle significantly decreased the rate of irrational PIPU (53.06% vs. 8.57%), including duration, administration route, indication, and dosing frequency. Costs of total (USD 211.28 ± 162.33 vs. 53.17 ± 22.32) and inappropriate (USD 76.70 ± 59.78 vs. 2.25 ± 3.86) PIPU per patient were significantly reduced. The target compliance rate was 107.56%. Conclusion A CPGT can have an effective role in improving rational PIPU and optimizing administration through a PDCA cycle, to attain improved clinical and economic outcomes.

We address issues in existing house layout generation methods, including chaotic room layouts, limited iterative refinement, and restricted style diversity. We propose Graph-RWGAN, a generative adversarial network based on a multi-relational graph attention mechanism, to automatically generate reasonable and globally consistent house layouts under weak constraints. In our framework, rooms are represented as graph nodes with semantic attributes. Their spatial relationships are modeled as edges. Optional room-level objects can be added by augmenting node attributes. This allows for object-aware layout generation when needed. The multi-relational graph attention mechanism captures complex inter-room relationships. Iterative generation enables stepwise layout optimization. Fusion of node features with building boundaries ensures spatial accuracy and structural coherence. A conditional graph discriminator with Wasserstein loss constrains global consistency. Experiments on the RPLAN dataset show strong performance. FID is 92.73, SSIM is 0.828, and layout accuracy is 85.96%. Room topology accuracy reaches 95%, layout quality 90%, and structural coherence 95%, outperforming House-GAN, LayoutGAN, and MR-GAT. Ablation studies confirm the effectiveness of each key component. Graph-RWGAN shows strong adaptability, flexible generation under weak constraints, and multi-style layouts. It provides an efficient and controllable scheme for intelligent building design and automated planning.

Aims Root aerenchyma, a key adaptive trait to anoxic soils has rarely been integrated into trait-based plant ecology. This study aims to evaluate the relationship between root porosity and root economics-related traits among wetland plants, focusing on the effect of aerenchyma on root tissue density, a central trait in plant economics spectrum. Methods Root porosity, root tissue density with air-space included (RTD) or excluded (RTDA), and other root traits such as root dry matter content (root dry mass to fresh mass ratio) were measured separately for adventitious and lateral roots of 16 garden-grown Ontario wetland monocots with contrasting root longevities. Results Principal component analysis showed that in the root adaptive trait space of wetland plants, the first dimension is defined by economics-related traits, the second dimension by lateral root porosity and the ratio of lateral to adventitious root length, and the third dimension by adventitious root porosity. Interspecific variation in root porosity was unrelated to root economics traits. Consequently, root tissue density excluding air space (RTDA) better differentiated between species with contrasting root longevities than RTD did, consistently both for adventitious and lateral roots. Root dry matter content accurately predicted RTDA. Conclusions Interspecific variation in root porosity is independent of root economics: Wetland plants can construct economically conservative or acquisitive roots of any porosity. Consequently, to consistently express root functional relationships among wetland plant species, root tissue density should be expressed with excluding the air space (i.e., RTDA), or with the more easily measured root dry matter content.

This article focuses on the prescribed performance sliding mode fault-tolerant control problem for an unmanned morphing flight vehicle (MFV) with actuator faults and composite disturbances during wing deformation. Firstly, the longitudinal nonlinear dynamic model of the unmanned MFV is introduced. Then, a control framework is proposed by decomposing the integrated dynamic model into attitude and velocity subsystems, effectively simplifying controller architecture and improving fault tolerance. Further, the constrained tracking errors are systematically transformed into unconstrained counterparts via projection operators to facilitate controller design. For each subsystem, a prescribed performance sliding mode fault-tolerant controller is developed, ensuring both transient performance and steady-state tracking accuracy. Finally, the simulation results verify the feasibility and effectiveness of the proposed fault-tolerant control strategy.

This paper presents a systematic design of a predefined-time sliding mode controller with integrated prescribed performance strategies, tailored to the longitudinal dynamics of hypersonic vehicles (HSVs) operating under strict real-time and high-precision requirements. A prescribed error transformation function is introduced to simultaneously constrain both transient and steady-state behaviors. This transformation converts the original constrained tracking problem into an equivalent unconstrained stabilization problem, thereby simplifying the controller synthesis. Based on the decomposed control-oriented state-space equations, separate sliding mode controllers are designed for the velocity and attitude subsystems. The proposed strategy guarantees that the tracking errors converge to zero within a user-predefined time, while strictly satisfying the prescribed performance bounds at every stage of the closed-loop response. The efficacy of the method is validated through numerical simulations.

The direct and selective coupling of benzenes with aliphatic hydrocarbons is a promising strategy for C(sp 2 )-C(sp 3 ) bond formation using readily available starting materials, yet it remains a significant challenge. In this study, we have developed a simplified photochemical system that incorporates catalytic amounts of iron(III) halides as multifunctional reagents and air as a green oxidant to address this synthetic problem. Under mild conditions, the reaction between a strong C(sp 2 )-H bond and a robust C(sp 3 )-H bond has been achieved, affording a broad range of cross-coupling products with high yields and commendable chemo-, site-selectivity. The iron halide acts as a multifunctional reagent that responds to visible light, initiates C -centered radicals, induces single-electron oxidation to carbocations, and participates in a subsequent Friedel-Crafts-type process. The gradual release of radical species and carbocation intermediates appears to be critical for achieving desirable reactivity and selectivity. This eco-friendly, cost-efficient approach offers access to various building blocks from abundant hydrocarbon feedstocks, and demonstrates the potential of iron halides in sustainable synthesis. The direct and selective coupling between unactivated C(sp2)-H and C(sp3)-H bonds is widely recognized as one of the most challenging tasks in organic synthesis. Here, the authors present an iron halidepromoted photochemical aerobic oxidation strategy for achieving such transformations.

Current clinical guidelines recommend either muscarinic receptor antagonists or β3-adrenoceptor agonists for overactive bladder (OAB) treatment. These recommendations, however, are primarily based on short-term (12-week) clinical trials, leaving a critical gap in evidence regarding their long-term (≥1 year) efficacy and safety. Moreover, the long-term evidence synthesized here is limited to solifenacin and mirabegron, and its generalizability to other agents remains uncertain. To systematically compare the long-term efficacy and safety of solifenacin monotherapy, mirabegron monotherapy, and their combination in patients with OAB. We systematically searched PubMed, Embase, Cochrane Library, Scopus, and ClinicalTrials.gov for clinical studies published from inception to 2 April 2026. Two reviewers independently screened, selected, and extracted data. Methodological quality was assessed using the Jadad scale and the Cochrane Risk of Bias 2 (ROB 2) tool. The primary outcomes were changes from baseline in mean volume voided incontinence episodes per 24 h, and micturition frequency per 24 h. The secondary outcome was the incidence of treatment-related adverse drug reactions Quantitative meta-analysis was performed only for safety outcomes using a random-effects model. For the primary efficacy outcomes, substantial heterogeneity (I >58%) across the included studies precluded meaningful pooling, therefore, a narrative synthesis of efficacy data was presented. Initial screening identified 7,451 articles, of which five randomized controlled trials met the inclusion criteria. For long-term OAB management, combination therapy (solifenacin 5 mg + mirabegron 50 mg) may be more effective than each monotherapy in improving MVV and reducing mean incontinence episodes and micturition frequency. Compared to mirabegron 50mg, solifenacin 5 mg was associated with a potentially higher risk of ADRs such as dry mouth (RR 1.73, 95%CI 0.91-3.30, P = 0.10) and constipation (RR 2.46, 95%CI 1.16-5.19, P = 0.02), but a lower incidence of dizziness (RR 0.08, 95%CI 0.01-0.62, P = 0.02). Solifenacin 5 mg was associated with a lower risk of constipation and dry mouth compared to solifenacin 10 mg. For long-term OAB pharmacotherapy with the specific regimens evaluated, mirabegron 50 mg appears to offer a favorable profile due to its comparable efficacy and lower incidence of certain treatment-limiting ADRs. However, these findings cannot be generalized to other muscarinic receptor antagonists or β3-adrenoceptor agonists. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251056532, identifier CRD420251056532.