Advancing Open Science

Accurate air temperature and precipitation data are fundamental for environmental and socioeconomic applications in Brazil. However, the observational network managed by the National Institute of Meteorology, suffers from spatial gaps, necessitating the use of gridded datasets. This study provides a rigorous comparative assessment of three prominent gridded products—the station-interpolated dataset of Brazilian Daily Weather Gridded Data (BR-DWGD), the satellite-gauge blended product MERGE, and the ERA5-Land Reanalysis dataset—against station data. We evaluate the performance of the institutionally supported MERGE and ERA5-Land products as viable alternatives to the interpolated dataset. Daily data for maximum temperature (Tmax), minimum temperature (Tmin), and total precipitation were selected from 1994 to 2024 and analyzed using statistical metrics. The interpolated product showed the highest fidelity to observations, especially for temperature. For precipitation, the MERGE product demonstrated the best performance, achieving higher correlation and lower error than both the interpolated dataset and the poorly performing ERA5-Land. For temperature, ERA5-Land proved to be an excellent alternative for minimum temperature, but exhibited significant regional biases for maximum temperature and a tendency to underestimate heat extremes. We conclude that MERGE is the most robust alternative for precipitation studies in Brazil. ERA5-Land is a highly reliable source for minimum temperature, but its direct use for maximum temperature requires caution.

As a neighborhood-scale derivative of the Business Improvement District (BID) model, the Neighborhood Business Improvement District (NBID) represents a collaborative governance framework aimed at fostering spontaneous urban regeneration. Its successful establishment critically depends on building consensus among diverse stakeholders during the preparatory phase. This study addresses a significant gap by investigating the psychological mechanisms that shape stakeholders’ willingness to engage in NBIDs prior to their formation. Employing an exploratory sequential mixed-methods approach, we conducted semi-structured interviews in the Tiyuan North Community (Tianjin) and the Yulin East Road Community (Chengdu). Insights from the qualitative phase informed a subsequent quantitative survey administered to 215 stakeholders in Tianjin. Data were analyzed using regression analysis and Structural Equation Modeling (SEM). The results reveal that stakeholders’ performance expectations and collaborative willingness are significantly influenced by three core confidence factors: “Confidence in Authority Support (AS)” (particularly “Confidence in Council Representation”), “Confidence in Organization Capability (OC)” (especially “Confidence in Coordination Ability”), and “Confidence in Multi-party Collaboration.” Crucially, “Confidence in Enabling collaboration (MC_3)” itself acts as a key mediator, translating institutional trust into performance expectations. This study contributes a novel “Confidence–Expectation” framework to the literature on collective action and offers practical, context-sensitive insights for designing collaborative community governance structures aimed at sustainable urban regeneration in China and beyond.

In flight tests, to meet the requirements of consistent acquisition and storage of multiple targets, multiple systems, and multiple data types, various data types are processed into Pulse Code Modulation (PCM) data streams using PCM encoding for storage. Aiming at the requirement of real-time storage of high-bit-rate PCM data streams, a large-capacity storage system based on Serial Advanced Technology Attachment 3.0 (SATA3.0) is designed. The system uses the Kintex 7 series Field-Programmable Gate Array (FPGA) as the control core, receives PCM data streams through the Low-Voltage Differential Signaling (LVDS) low-voltage differential interface, stores the received PCM data streams into the mSATA disk via the SATA3.0 transmission bus, and transmits the stored data back to the host computer through the USB3.0 interface for analysis. Meanwhile, to solve the problem of complex data export, the storage system constructs a FAT32 file system through the MicroBlaze soft core to optimize the management and operation of the large-capacity storage system. Test results show that the storage system can perform stable high-rate storage at −40 °C~80 °C.

Marine ecotourism and Small–Medium Enterprise (SME) digitalization are increasingly seen as key drivers for coastal community welfare, yet their combined impact, particularly through local economic empowerment, remains underexplored. This study aims to examine whether marine ecotourism (ME) and SME digitalization (SD) influence local community welfare (LCW), mediated by SME empowerment (SE), and moderated by government support (GS). A quantitative, cross-sectional survey was conducted with 312 marine tourism entrepreneurs in North Minahasa, Indonesia, and data were analyzed using Partial Least Squares Structural Equation Modeling. The results show that ME and SD have a significant positive effect on SE and LCW. However, ME and SD were found to be insignificant on LCW. Crucially, SE fully mediates the relationship between both ME and SD on LCW, indicating that empowerment is the primary mechanism for welfare improvement. Furthermore, GS was found to significantly strengthen the positive relationship between SE and LCW. This study concludes that empowering local SMEs is the critical bridge for transforming ecotourism and digitalization into tangible community welfare, and this process is significantly amplified by a supportive institutional environment provided by the government.

To address the limitations of traditional timber mortise-and-tenon joints, particularly their low pull-out resistance and rapid stiffness degradation under cyclic loading, this study proposes a novel integrated sleeve mortise-and-tenon steel–timber composite beam–column joint. Building upon prior experimental validation and numerical model verification, a comprehensive parametric study was conducted to systematically investigate the influence of key geometric parameters on the seismic performance of the joint. The investigated parameters included beam sleeve thickness (1–10 mm), sleeve length (150–350 mm), bolt diameter (4–16 mm), and the dimensions and thickness of stiffeners. The results indicate that a sleeve thickness of 2–3 mm yields the optimal overall performance: sleeves thinner than 2 mm are prone to yielding, while those thicker than 3 mm induce stress concentration in the timber beam. A sleeve length of approximately 250 mm provides the highest initial stiffness and a ductility coefficient exceeding 4.0, representing the best seismic behavior. Bolt diameters within the range of 8–10 mm produce full and stable hysteresis loops, effectively balancing load-carrying capacity and energy dissipation; smaller diameters lead to pinching failure, whereas larger diameters trigger premature plastic deformation in the timber. Furthermore, stiffeners with a width of 40 mm and a thickness of 2 mm effectively enhance joint stiffness, promote a uniform stress distribution, and mitigate local damage. The optimized joint configuration demonstrates excellent ductility, stable hysteretic behavior, and a high load capacity, providing a robust technical foundation for the design and practical application of advanced steel–timber composite connections.

Titanium (Ti) and its alloys are widely used in biomedical applications due to their biocompatibility and corrosion resistance; however, surface modifications are required to enhance biological functionality. Surface functionalization using natural biomolecules has emerged as a promising strategy to improve early cell–surface interactions and biocompatibility of implant materials. In this study, Ti6Al4V alloy surfaces were biofunctionalized using Spirulina platensis (S. platensis) biomass and protein extract to evaluate morphological, chemical, and biological effects. The functionalization process involved activation with piranha solution, silanization with 3-aminopropyltriethoxysilane (APTES), and subsequent biomolecule immobilization. Surface characterization by scanning electron microscopy (SEM), inductively coupled plasma mass spectrometry (ICP-MS), energy-dispersive X-ray spectroscopy (EDS), and Fourier transform infrared spectroscopy (FTIR) confirmed the successful incorporation of microalgal components, including nitrogen-, phosphorus-, and oxygen-rich organic groups. Biomass-functionalized surfaces exhibited higher phosphorus and oxygen content, while protein-coated surfaces showed nitrogen-enrich chemical signatures, reflecting the distinct molecular compositions of the immobilized biomolecules. Cell adhesion assays demonstrated enhanced early cell attachment on biofunctionalized surfaces, particularly in samples functionalized with 5 g/L biomass for three hours, which showed significantly greater cell attachment than both the control and protein-treated samples. These findings highlight the complementary yet distinct roles of S. platensis biomass and protein extract in modulating surface chemistry and cell–material interactions, emphasizing the importance of tailoring biofunctionalization strategies to optimize early biological responses on titanium-based implants.

In order to solve the problems of small-target detection in UAV aerial photography, such as small scale, blurred features and complex background interference, this article proposes the ACS-YOLOv8s method to optimize the YOLOv8s network: notably, most small man-made targets in UAV aerial scenes (e.g., small vehicles, micro-drones) inherently possess symmetry, a key geometric attribute that can significantly enhance the discriminability of blurred or incomplete target features, and thus symmetry-aware mechanisms are integrated into the aforementioned improved modules to further boost detection performance. The backbone network introduces an adaptive feature enhancement module, the edge and detail representation of small targets is enhanced by dynamically modulating the receptive field with deformable attention while also capturing symmetric contour features to strengthen the perception of target geometric structures; a cascaded multi-receptive field module is embedded at the end of the trunk to integrate multi-scale features in a hierarchical manner to take into account both expressive ability and computational efficiency with a focus on fusing symmetric multi-scale features to optimize feature representation; the neck is integrated with a spatially adaptive feature modulation network to achieve dynamic weighting of cross-layer features and detail fidelity and, meanwhile, models symmetric feature dependencies across channels to reduce the loss of discriminative information. Experimental results based on the VisDrone2019 data set show that ACS-YOLOv8s is superior to the baseline model in precision, recall, and mAP indicators, with mAP50 increased by 2.8% to 41.6% and mAP50:90 increased by 1.9% to 25.0%, verifying its effectiveness and robustness in small-target detection in complex drone aerial-photography scenarios.

This review explores the innovative approaches in the development of next-generation biopesticides, focusing on molecular and microbial strategies for effective control of fungal plant pathogens. As agricultural practices increasingly seek sustainable solutions to combat plant diseases, biopesticides have emerged as a promising alternative to chemical pesticides, offering reduced environmental impact and enhanced safety for non-target organisms. The review begins by outlining the critical role of fungal pathogens in global agriculture, emphasizing the need for novel control methods that can mitigate their detrimental effects on crop yields. Key molecular strategies discussed include the use of genetic engineering to enhance the efficacy of biopesticides, the application of RNA interference (RNAi) techniques to target specific fungal genes, and the development of bioactive compounds derived from natural sources. Additionally, this review highlights the potential of microbial agents, such as beneficial bacteria and fungi, in establishing biocontrol mechanisms that promote plant health and resilience. Through a comprehensive review of recent studies and advancements in the field, this manuscript illustrates how integrating molecular and microbial strategies can lead to the development of effective biopesticides tailored to combat specific fungal threats. The implications of these strategies for sustainable agriculture are discussed, alongside the challenges and future directions for research and implementation. Ultimately, this review aims to provide a thorough understanding of the transformative potential of next-generation biopesticides in the fight against fungal plant pathogens, contributing to the broader goal of sustainable food production.