Advancing Open Science

Considering the rapid iteration of you-only-look-once (YOLO)-series algorithms, this paper aims to provide a data-driven performance spectrum and selection guide for the latest YOLO series algorithm (YOLOv8 to YOLOv13) in printed circuit board (PCB) automatic optical inspection (AOI) through systematic benchmarking. A comprehensive evaluation of the six state-of-the-art YOLO series algorithms is conducted on a standardized dataset containing six typical PCB defects: missing hole, mouse bite, open circuit, short circuit, spur, and spurious copper. An innovative dual-cycle comparative experiment (100 rounds and 500 rounds) is designed, and a systematic assessment is performed across multiple dimensions, including accuracy, efficiency, and inference speed. The experimental results have revealed significant variations in algorithm performance with training cycles: under short-term training (100 rounds), YOLOv13 achieves leading detection performance (mAP50 = 0.924, mAP50-95 = 0.484) with the fewest parameters (2.45 million); after full training (500 rounds), YOLOv10 achieves the highest overall accuracy (mAP50 = 0.946, mAP50-95 = 0.526); additionally, YOLOv11 shows the optimal speed-accuracy balance after long-term training, while YOLOv12 excels in short-term training; moreover, “open circuit” and “spur” are evaluated as the most challenging defect categories to detect. The findings given in this paper indicate the absence of a universally applicable “all-in-one” algorithm and propose a clear algorithm selection roadmap: YOLOv10 is recommended for offline analysis scenarios prioritizing extreme accuracy; YOLOv13 is the top choice for applications requiring rapid iteration with tight training time constraints; and YOLOv11 is the best option for high-throughput online inspection PCB production lines.

This study develops a field-based techno-economic model and decision framework for a CO₂-enhanced oil recovery and storage project under joint market uncertainty. Historical drilling and completion expenditures calibrate investment cost functions, and three years of production data are fitted with segmented hyperbolic Arps curves to forecast 20-year oil output. Markov-chain models jointly generate internally consistent pathways for crude oil, ETA, and purchased CO₂ prices, which are embedded in a Monte Carlo valuation. The framework outputs probability distributions of NPV and deferral option value; under the mid scenario, their mean values are USD 18.1M and USD 2.0M, respectively. PRCC-based global sensitivity analysis identifies the dominant value drivers as oil price, CO₂ price, utilization factor, oil density, pipeline length, and injection volume. Techno-economic boundary maps in the joint oil and CO₂ price space then delineate feasible regions and break-even thresholds for key design parameters. Results indicate that CCUS-EOR viability cannot be inferred from oil price or any single cost factor alone, but requires coordinated consideration of subsurface constraints, engineering configuration, and multi-market dynamics, including the value of waiting in unfavorable regimes, contributing to low-carbon development and sustainable energy transition objectives.

Horse flies (Tabanidae) negatively affect livestock by reducing productivity, compromising animal welfare, and serving as mechanical vectors of pathogens. However, the spatial processes shaping their community organization in southern Brazil’s Coastal Plain of Rio Grande do Sul (CPRS) remain poorly understood. To address this, we conducted standardized Malaise-trap surveys and combined them with historical–contemporary comparisons to examine distance–decay patterns in community composition. We evaluated both abundance-based (Bray–Curtis) and presence–absence (Jaccard) dissimilarities using candidate models. Across sites, Tabanus triangulum emerged as the dominant species. Dissimilarity in community structure increased monotonically with geographic distance, with no evidence of abrupt thresholds. The square-root model provided the best fit for abundance-based data, whereas a linear model best described presence–absence patterns, reflecting dispersal limitation and environmental filtering across a heterogeneous coastal landscape. Sites within riparian forests and conservation units displayed higher diversity, emphasizing the ecological role of protected habitats and the importance of maintaining connected corridors. Collectively, these findings establish a process-based framework for surveillance and landscape management strategies to mitigate vector, host contact. Future directions include integrating remote sensing and host distribution, applying predictive validation across temporal scales.

Cooperative control of multi-agent systems (MASs) is essential in engineering applications. However, malicious attacks and uncertainties can drive MASs to failure. Regrettably, prior work on resilient control of MASs rarely addresses uncertainties and malicious attacks concurrently. In this article, the resilient leader–follower consensus control problem is studied for non-linear MASs with cyber-physical attacks and uncertainties, and a novel resilient model reference adaptive sliding mode control (MRASMC) strategy is proposed. The stability of the MASs is proven via the Lyapunov theory, and the effectiveness of the proposed control framework is validated by numerical simulations.

Background: Liposomes are attractive topical carriers, yet translating laboratory fabrication to scalable, well-controlled processes remains challenging. Objectives: We compared three manufacturing methods for diclofenac-loaded liposomes: probe sonication, microfluidic mixing, and a high-turbulence microreactor, under a Quality-by-Design framework. Methods: Differential scanning calorimetry (DSC) was used to define a processing-relevant liquid-crystalline temperature window for the lipid excipients. For sonication scale-up, a Plackett-Burman screening design identified key process factors and supported an energy-density (W·s·L⁻¹) control approach. For microfluidics, the effects of flow-rate ratio (FRR) and total flow rate (TFR) were mapped and optimized using a desirability function. Microreactor trials were performed at elevated throughput. Residual ethanol during post-processing was monitored at-line by Raman spectroscopy calibrated against gas chromatography (GC). Particle size and dispersity were measured by DLS and morphology assessed by cryo-TEM. Results: DSC supported a 70–85 °C processing window. Sonication scale-up using an energy-density target (~11,000 W·s·L⁻¹) reproduced lab-scale quality at 8 L (Z-average ~87–92 nm; PDI 0.16–0.23; %EE 86–94%). Microfluidics optimization selected FRR 3:1/TFR 4 mL·min⁻¹, yielding ~64 nm liposomes with PDI ~0.13 and %EE ~93%. The microreactor achieved ~50 nm liposomes with %EE ~95% at 50 mL·min⁻¹. Cryo-TEM corroborated size trends and showed no evident aggregates. Conclusions: All three routes met topical CQAs (~50–100 nm; PDI ≤ 0.30; high %EE). Method selection should be guided by target size/dispersity and operational constraints: sonication enables energy-based scale-up, microfluidics offers precise size control, and microreactors provide higher throughput.

A compact quad-band multiple-input multiple-output (MIMO) antenna for terahertz communications is presented in this work. The proposed antenna consists of a truncated square patch with inverted-U-shaped and C-shaped slots. The operating frequencies of the proposed antenna are 0.38 THz, 0.43 THz, 0.61 THz, and 0.7 THz, with reflection coefficients of −13.8 dB, −22.1 dB, −27.3 dB, and −14.8 dB, respectively, and a −10 dB impedance bandwidth of 9 GHz, 18 GHz, 18 GHz, and 21 GHz, respectively. The peak gain values of a single element antenna at 0.38 THz, 0.43 THz, 0.61 THz, and 0.7 THz are 3.3 dB, 4.8 dB, 4.7 dB, and 5.5 dB, respectively. The dual-triangular MIMO configuration was investigated. The peak gains of the MIMO configurations at 0.38 THz, 0.43 THz, 0.61 THz, and 0.7 THz are 10.6 dB, 12.2 dB, 15.6 dB, and 15.2 dB, respectively. The envelope correlation coefficient (ECC) and the diversity gain (DG) of the proposed antenna were investigated and are presented herein. The proposed MIMO antenna demonstrates lower coupling and higher isolation at the operating frequency bands. Therefore, it is a suitable candidate for beyond 5G and 6G wireless communications applications, such as for nanodevices used in the internet of things and in wearables.

Wild seeds constitute a taxonomically diverse and underexplored reservoir of C18-series bioactive fatty acids (BFAs) with significant nutritional, biomedical, and industrial relevance. This review integrates current knowledge on their lipid composition, metabolic architecture, and potential applications. Numerous wild taxa accumulate high levels of oleic, linoleic, α-linolenic, γ-linolenic, and stearidonic acids, while others synthesise structurally specialised compounds such as punicic, petroselinic, and sciadonic acids. These FAs, together with tocopherols, phytosterols, and phenolics, underpin antioxidant, anti-inflammatory, immunomodulatory, and cardiometabolic effects supported by in vitro and in vivo evidence. The occurrence of these unusual lipids reflects lineage-specific modulation of plastidial and endoplasmic-reticulum pathways, including differential activities of SAD, FAD2/3, Δ6- and Δ5-desaturases, elongases, and acyl-editing enzymes that determine the final acyl-CoA and TAG pools. Wild seed oils show strong potential for translation into functional foods, targeted nutraceuticals, pharmacologically relevant lipid formulations, cosmetic ingredients, and bio-based materials. However, their exploitation is constrained by ecological sustainability, oxidative instability of PUFA-rich matrices, antinutritional constituents, and regulatory requirements for novel lipid sources. This review positions wild seeds as high-value, underused lipid resources with direct relevance to health and sustainability. It underscores their potential to enhance nutritional security and offer alternatives to conventional oil crops.

Background: Agri-food by-products are increasingly recognized as valuable sources of tannins, whose antioxidant properties represent the primary driver of their biological activity across human and animal health. The strong redox-modulating capacity of condensed and hydrolysable tannins provides a unifying mechanistic explanation for their effects on inflammation, metabolism, gut integrity and neuroprotection. Methods: This narrative review synthesizes evidence obtained through a structured literature search across major databases, selecting studies that investigated antioxidant mechanisms of tannin-rich matrices from plant- and processing-derived residues. Results: Condensed tannins, particularly proanthocyanidins, consistently display potent antioxidant activity through radical scavenging, metal chelation and activation of endogenous defenses, thereby underpinning their anti-inflammatory, anti-ischemic, neuroprotective and metabolic actions. Hydrolysable tannins similarly exert strong antioxidative effects that support antimicrobial activity, enzyme modulation and protection against neuroinflammation. In animals, the antioxidant capacity of tannins translates into improved oxidative balance, enhanced immune status, reduced tissue damage, better feed efficiency and mitigation of oxidative stress-linked methane emission pathways. Conclusions: Antioxidant activity emerges as the central, cross-species mechanism through which tannins mediate diverse health benefits. Tannin-rich agri-food by-products therefore represent promising sustainable antioxidant resources, although their efficacy remains influenced by tannin class, degree of polymerization and dosage, warranting further mechanistic and translational research.