Advancing Open Science

Soil sensors have a vital role in precision agriculture. In smart agriculture, soil moisture sensors, soil temperature–humidity sensors, soil pH sensors, soil nutrient sensors, soil pollutant and pest sensors, and wearable sensors detect data to improve crop yields and advance agricultural development. This paper summarizes the types and applications of the above sensors. Soil sensors serve as the core technological engine of smart agriculture, and this review also illustrates that the integration of the Internet of Things and sensors—including plant wearable sensors, which indirectly reflect soil conditions through plant physiological signals—can simultaneously measure or infer parameters, e.g., moisture, temperature, pH, and nutrients, that play a crucial role in precision agriculture. This paper concludes with the future prospects and challenges of soil sensors in smart agriculture, emphasizing the need to address bottlenecks in data fusion, model optimization, and cost control, as well as to advance the implementation of smart agriculture through the development of standards and ecological construction.

Informal food trading is a cornerstone of urban livelihoods and food security in Namibia, yet traders operate under fragile conditions marked by limited capital, policy exclusion, and exposure to shocks such as COVID-19. Despite this vulnerability, traders exhibit resilience through everyday forms of social innovation. This study investigates how adaptive pricing, customer credit, and digital communication and e-payment practices function as pathways of resilience among 470 informal food traders in Windhoek, using Structural Equation Modelling to assess gender-differentiated determinants and outcomes. The analysis reveals that women’s adoption of adaptive pricing and digital tools is driven primarily by education and startup capital, while men’s innovation practices are shaped by vendor type and access to financing. Social innovations mediate the effects of these structural factors on enterprise growth, demonstrating that innovation acts as a critical mechanism linking resources and resilience. The study concludes that enhancing informal traders’ resilience requires policies that strengthen human and financial capital, improve digital inclusion, and recognize gendered differences in access to opportunity. It recommends targeted support for women’s entrepreneurial training, affordable credit, and digital infrastructure to transform the informal food sector into a more equitable and sustainable component of Namibia’s urban economy.

Ultrasound imaging is widely used for early breast cancer screening to enhance patient survival. However, interpreting these images is inherently challenging due to speckle noise, low lesion-to-tissue contrast, and highly variable tumor morphology within complex anatomical structures. Additionally, variations in image characteristics across institutions and devices further impede the development of robust and generalizable computer-aided diagnostic systems. To alleviate these issues, this paper presents a cross-domain segmentation prior guided classification strategy for robust breast tumor diagnosis in ultrasound imaging, implemented through a novel Dual-Stream Diagnosis Network (DSDNet). DSDNet adopts a decoupled dual-stream architecture, where a frozen segmentation branch supplies spatial priors to guide the classification backbone. This design enables stable and accurate performance across diverse imaging conditions and clinical settings. To realize the proposed DSDNet framework, three novel modules are created. The Dual-Stream Mask Attention (DSMA) module enhances lesion priors by jointly modeling foreground and background cues. The Segmentation Prior Guidance Fusion (SPGF) module integrates multi-scale priors into the classification backbone using cross-domain spatial cues, improving tumor morphology representation. The Mamba-Inspired Linear Transformer (MILT) block, built upon the Mamba-Inspired Linear Attention (MILA) mechanism, serves as an efficient attention-based feature extractor. On the BUSI, BUS, and GDPH_SYSUCC datasets, DSDNet achieves ACC values of 0.878, 0.836, and 0.882, and Recall scores of 0.866, 0.789, and 0.878, respectively. These results highlight the effectiveness and strong classification performance of our method in ultrasound breast cancer diagnosis.

This study introduces a novel enhanced voxel-by-voxel fused filament fabrication approach utilizing a custom 3D printer. The key innovation is the simultaneous, real-time manipulation of both filament flow and printing speed per voxel. By adjusting the printing speed proportionally to the extrusion rate, the method ensures sufficient time for precise material deposition, effectively countering under-extrusion effects and significantly improving the process’s responsiveness and accuracy. The method was validated through a calibration process and in the fabrication of a breast phantom derived from a patient’s MRI data. Calibration demonstrated a strong linear correlation between HUs, extrusion rate, and speed, with a coefficient of R = 0.99. CT scans of the phantom confirmed consistent replication of the expected HU distribution and anatomical features, visually demonstrating high correlation with the original patient images. The dual-parameter control strategy successfully enhances the fidelity of soft tissue phantoms fabrication. Future work will focus on adapting the method for high-speed printing and multi-material applications.

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) δD, CO₂, and CH₄ records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve understanding of the intensity, amplitude, and asymmetry features of 73 marine isotope stages/substages (MISs) and seven glacial terminations. The Antarctic stack record can be described by a variance-weighted superposition of ten thermal waves of different origins (mid-term oscillation, orbitals, and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, amplitude, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low-intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low-interference regions, where dominant destructive patterns minimize the thermal envelope. The positive skewness of the EPICA stack resulted from constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect has led to the saw-tooth shape of glacial cycles, which was strongly induced by interference.

Stimuli-responsive hydrogels are an emerging class of smart materials with immense potential across biomedical engineering, soft robotics, environmental systems, and advanced manufacturing. In this review, we present an in-depth exploration of their material design, classification, fabrication strategies, and real-world applications. We examine how a wide range of external stimuli—such as temperature, pH, moisture, ions, electricity, magnetism, redox conditions, and light—interact with polymer composition and crosslinking chemistry to shape the responsive behavior of hydrogels. Special attention is given to the growing field of 4D printing, where time-dependent shape and property changes enable dynamic, programmable systems. Unlike existing reviews that often treat materials, stimuli, or applications in isolation, this work introduces a multidimensional comparative framework that connects stimulus-response behavior with fabrication techniques and end-use domains. We also highlight key challenges that limit practical deployment—including mechanical fragility, slow actuation, and scale-up difficulties—and outline engineering solutions such as hybrid material design, anisotropic structuring, and multi-stimuli integration. Our aim is to offer a forward-looking perspective that bridges material innovation with functional design, serving as a resource for researchers and engineers working to develop next-generation adaptive systems.

Working memory capacity (WMC) has long served as a central indicator of individual differences in complex cognition. However, growing evidence suggests that a substantial portion of its predictive power may reflect attention control (AC)—including goal maintenance, interference management, and inhibition—rather than storage capacity alone. This review synthesizes findings across six domains: (1) perception and sensory discrimination, (2) learning and problem solving, (3) cognitive control and decision making, (4) retrieval and memory performance, (5) multitasking and real-world performance, and (6) clinical applications. Across these areas, WMC-related effects frequently align with demands on AC, though the strength and nature of this alignment vary by domain. We highlight the importance of incorporating reliable AC measures and recommend latent-variable approaches to more clearly separate storage, control, and representational processes underlying complex performance.

Growth differentiation factor-15 (GDF-15) is an established marker of oxidative stress and a general stress-response mitokines. In this study, we aim to investigate the association of GDF-15 with the metabolic signature of gut and mitochondrial activity in HF and ageing population. A total of 25 HF (67.9 ± 10.0 years) and 29 age-matched healthy participants (HPs) (67.8 ± 11.1 years) were recruited and underwent detailed body composition assessment via dual X-ray absorptiometry; total fat mass and appendicular lean soft tissue index (ALSTI/body mass index (BMI)) were calculated. Utilizing semi-targeted Gas Chromatography–Mass Spectrometry on fasting plasma, a panel of gut microbial-derived (e.g., hippuric acid, indole derivatives, and sarcosine) and tricarboxylic acid cycle metabolites was identified. Results showed higher GDF-15 tertiles were associated with greater HF prevalence, fat mass, NT-proBNP, and TNF-α (p < 0.05). Gut-derived metabolites exhibited phenotype-specific patterns; 3-hydroxyindole predicted higher fat mass in HP; hippuric acid was inversely related in HF; and sarcosine correlated with GDF-15 only in HP. In HF, GDF-15 was strongly driven by pyruvic and fumaric acid, indicating disease-specific mitochondrial stress. In conclusion, these observed associations could be evaluated in future mechanistic studies as sensitive biomarkers of systemic oxidative stress markers, informing potential microbiome-targeted therapeutic avenues.