Abstract: Automated quality inspection is a central component of modern industrial production processes. Over the past few decades, machine vision has evolved from rule-based, traditional image processing methods to data-driven machine learning and deep learning approaches. In particular, with the advent of powerful neural networks, significant progress has been made in the detection, classification, and localization of defects. At the same time, industrial applications place high demands on robustness, real-time capability, explainability, and the handling of rare or unknown defect patterns. This brief survey provides an overview of machine vision methods for industrial quality inspection. It systematizes classical image processing approaches, supervised, unsupervised, and semi-supervised learning methods, and discusses their strengths and limitations in real-world production environments. Furthermore, it examines multisensory and three-dimensional inspection approaches, aspects of industrial implementation, and current developments in the field of explainable artificial intelligence. Finally, this brief overview identifies outstanding challenges and research gaps and outlines future trends in automated quality inspection.

Abstract: Unconventional oil production plants are complex industrial systems characterized by harsh operating conditions, modular facility configurations, and tightly coupled electrical, instrumentation, and control subsystems. Conventional centralized control architectures, such as Distributed Control Systems (DCS) and Programmable Logic Controller (PLC)-based systems, often exhibit structural limitations in scalability, maintainability, and subsystem integration when applied to such distributed plant environments. This study proposes a Direct Digital Control (DDC)-based integrated electrical and instrumentation control system architecture for unconventional oil production plants from a systems engineering perspective. The proposed architecture adopts distributed field-level DDC controllers as autonomous system nodes, enabling direct processing of instrumentation signals and coordinated integration with electrical subsystems through a network-based structure. This transforms the control platform into a system-of-systems architecture in which process, electrical, instrumentation, safety, and supervisory layers operate as interoperable subsystems. The proposed system was implemented in a pilot-scale unconventional oil production plant to evaluate its practical applicability. The results indicate that the proposed architecture improves system scalability, modular adaptability, maintenance efficiency, and operational robustness compared with conventional centralized architectures. In particular, system expansion and module integration were achieved without structural redesign of the overall control platform. This study provides a practical architectural framework for integrated control of complex industrial plants and offers a foundation for future extensions toward smart plant operation, digital twin integration, and intelligent industrial system-of-systems engineering.

Abstract: The cislunar space, governed by the circular restricted three-body problem (CR3BP), presents significant challenges for mission design due to its complex stability structure. Traditional high-fidelity numerical integration is computationally prohibitive for a systematic stability census of millions of orbits. Here, we present a novel approach based on global volunteer computing via the BOINC platform to overcome this barrier. Using the public "Million Orbit" dataset from Lawrence Livermore National Laboratory, we distributed the computation of Jacobi constant time series across thousands of volunteer devices, producing over 16 billion individual values. The resulting dataset is freely available. Analysis reveals that 91.68% of orbits belong to the high-energy Region V, 8.07% to the stable Region I, and only 0.24% to Region III, with Region II completely absent. A single rare Region IV orbit (ID 754482) was identified and analyzed. This work demonstrates the transformative potential of volunteer computing for large-scale astrodynamics research, providing a detailed stability map and a benchmark for future machine-learning applications.

Abstract: We ask for C*-metric version of following three: (1) Bourgain-Figiel-Milman Theorem, (2) Enflo Type, (3) Mendel-Naor Cotype.

Abstract: Background: Early motor milestones play a critical role in shaping developmental trajectories across motor, cognitive, social, and functional domains. Increasing evidence indicates that motor competence facilitates environmental exploration, learning opportunities, and social engagement during infancy and early childhood. Methods: The present scoping review mapped the literature on early motor interventions, describing the respective characteristics and outcomes across pediatric populations. The review followed PRISMA‑ScR reporting guidelines and included thirty peer‑reviewed publications published between 2005 and 2025. Studies were identified through searches in major electronic databases, including PubMed, Scopus, and Web of Science. Results: Evidence across populations—including preterm infants, children at risk of cerebral palsy, developmental coordination disorder, autism spectrum disorder, congenital conditions, and typically developing children—supports early, intensive, task‑specific, and family‑centered interventions. Benefits extend beyond motor development to cognitive and social outcomes. Conclusions: Early motor intervention should be considered a multidimensional developmental strategy. Future research should prioritize standardized intervention protocols, rigorous study designs, and long‑term follow‑up.

Abstract: Flexible photovoltaic(PV) technology not only has high power efficiency but also is thin and lightweight, enabling seamless adaption to the surface of curved buildings. However, the distinctive spatial geometry of curved surfaces leads to inhomogeneous irradiance, causing electrical mismatch losses. This paper presents a systematic indoor experimental study on the electrical performance of Copper Indium Gallium Selenide (CIGS) cells under various bending configurations, including length-convex (lgvx), length-concave (lgcv), width-convex (wdvx), and width-concave (wdcv). Tests were conducted under standard testing conditions (1000 W/m², 25°C) with central angles ranging from 0° to 180° and placed in longitudinal and horizontal orientations， respectively. Results indicate that width-bending configurations generally outperform length-bending ones due to lower mismatch losses. For width-bending, concave forms exhibit higher power output than convex forms due to a mutual reflection mechanism. Conversely, length-concave forms manifest the highest power mismatch loss (up to 319.70 mW at 180°) due to significant self-shading. These findings provide critical design guidelines for optimizing cell layouts in curved BIPV systems.

Abstract: Crack paths are predicted using empirical mixed-mode criteria, while branching is attributed to a singular critical velocity. We show that fracture directionality and branching emerge from intrinsic thermodynamic topology. Mapping dissipation density to geometric distance defines a Finsler manifold from the interplay between the Eshelby tensor and directional fracture energy. Crack propagation becomes a Hamiltonian geodesic whose affine parameter is the physical crack advance. Classical mixed-mode criteria are linearized artifacts of this geodesic motion in isotropic (Riemannian) limits, enforced by macroscopic scale invariance. Analyzing Finsler Jacobi fields yields a geometric bifurcation condition: branching occurs when the curvature of the resistance field cancels the driving field. This framework predicts that materials with strong microstructural anisotropy undergo deterministic branching at quasi-static velocities, establishing velocity as a secondary parameter modifying the driving curvature rather than originating bifurcation.

Abstract: Debris avalanche deposits related to the edifice collapse of the summit area of Zao Volcano have been identified for the first time at the volcano’s eastern foot. These deposits extend approximately 11–15 km from the summit. Based on their spatial distribution and clast petrology, the deposits are interpreted to have originated from the Umanose caldera. Deposit thickness ranges from 20–30 m in the western and northern parts to over 50 m in the eastern part, with an estimated volume of approximately 0.3 km³, comparable to that of the summit caldera depression. Matrix facies occur at most outcrops, whereas block facies are found at only three sites. The vertical drop-to-runout distance ratio (H/L) is less than 0.09, which falls within the typical range for debris avalanches but indicates relatively high mobility. Based on its volume and stratigraphic relationships, the collapse is interpreted to have been caused either by a phreatic eruption or by a non-eruptive large-scale failure of a hydrothermally altered zone beneath the summit area. The collapse is considered to mark the onset of the latest activity stage of Zao Volcano, and the petrological characteristics of the magma differ markedly from those of the preceding stage.

Abstract: Myocardial ischemia-reperfusion (I/R) injury represents a major clinical challenge in cardiothoracic surgery, notably during cardiopulmonary bypass, coronary artery bypass grafting (CABG), and orthotopic heart transplantation. The complex pathophysiology underlying I/R injury involves severe disruptions in protein dynamics, pronounced inflammatory cascades, and the induction of cellular apoptosis. Emerging molecular evidence highlights the critical regulatory roles of non-coding RNAs (ncRNAs)—specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs)—alongside damage-associated molecular patterns (DAMPs), or alarmins, in orchestrating these processes. This review provides a comprehensive analysis of the molecular interplay between ncRNAs and alarmins during myocardial I/R injury. It delineates how the dysregulation of these molecules alters proteostasis, amplifies oxidative stress, and initiates perioperative inflammatory pathways. Furthermore, we summarize recent preclinical and clinical findings that identify specific ncRNAs (e.g., miR-1, miR-21, and MALAT1) and alarmins (e.g., HMGB1) as viable, targeted therapeutic avenues. Modulating these targets offers a promising approach to mitigating myocardial damage, enhancing cardioprotection, and improving surgical outcomes. Future investigations must prioritize translating these molecular targets into clinically feasible cardioprotective strategies.

Abstract: Mental stress is a common issue in demanding occupational setups, such as smart industrial settings, particularly from working with robots, being one of the primary reasons for decreased performance and productivity. Quantifying and evaluating stress are critical for worker safety, performance, and overall well-being. A novel integrated framework is proposed in this research for digitising and assessing cognitive stress that combines neuroimaging (EEG and fNIRS), gaze tracking and machine learning. A factory workers’ stress assessment experiment is designed and implemented, which employs physiological, behavioural and subjective measures to assess mental stress from different perspectives. Physiological features extracted from multimodal data are used for training supervised classification and regression models. To further optimise the pipeline, multiple feature selection algorithms are tested, followed by ensemble learning approaches, and the best one is chosen for stress prediction. After implementing the novel stress quantification framework for the factory workers' stress assessment experiment, the ensemble learning approach produced the best results for both regression (RMSE: 10.86) and classification (accuracy: 84.1%) techniques using the STAI score as the target. The behavioural and subjective measures demonstrate the effect of varying process variables (light, noise, task speed, and complexity) during the experiment. Multimodal data, machine learning, and other computational approaches are integrated in this study to objectively quantify cognitive stress, utilising the novel stress quantification framework presented in this research, thereby bridging the gap between research and practical application. This study proposes a multi-domain framework for measuring stress, providing a promising solution for worker well-being in occupational setups.

Abstract: Background: Microplastics (MPs) are a pervasive environmental contaminant, with growing evidence implicating them in human health risks. While toxicological studies have explored their effects, the specific role of particle morphology (shape) in driving biological outcomes remains poorly characterized. This is particularly relevant for liver pathology, where particle shape may influence cellular uptake, inflammation, and toxicity. Objective: This study aimed to conduct a secondary analysis of a national public dataset to quantify the morphological distribution of MPs in aquatic environments and evaluate the potential implications of these prevalent shapes for liver disease pathogenesis. Methods: We performed an integrated analysis of microplastic data collected via manta trawl and publicly available on Data.gov. The dataset comprised [mention number of samples or particles here, if available] samples from surface waters. Data on particle count, morphology, color, and size were extracted and cleaned. Frequency distributions for morphological categories were calculated using R software (v4.3.1) and the tidyverse package suite. Results: Analysis of 20,000 individual microparticles revealed a clear morphological distribution: fragments were the most abundant category (49.8%), closely followed by fibers (40.3%). Foam, film, spheres, and fiber bundles constituted smaller proportions (5.7%, 2.2%, 1.7%, and 0.4%, respectively). The prevalence of fibers and fragments represents the dominant morphological profile in surface waters. Conclusion: The high abundance of microfibers is of significant toxicological concern. Their linear, biopersistent nature enhances their potential for cellular interaction and pro-inflammatory effects, which may directly contribute to key mechanisms of liver disease pathogenesis, including oxidative stress, chronic inflammation, and immune dysregulation. This morphological analysis underscores the need to consider physical particle characteristics in environmental risk assessments for hepatic health.

Abstract: This study develops and validates a climate-based, user-centred and data-informed framework to improve lighting performance in educational buildings through the integrated use of daylight and smart LED control systems. The research was conducted in a university facility in Madrid, Spain, using a mixed-methods approach combining on-site illuminance measurements, climate-based lighting simulations (CBMS) with Dialux Evo 12.1, and structured surveys on user perception. The objective was to quantify the dynamic interaction between daylight availability, artificial lighting demand, and perceived visual comfort, while assessing the energy-saving potential of daylight-responsive control strategies. Results show that existing LED systems meet current illuminance standards while maintaining low lighting power density (LPD). Daylight and electric lighting act complementarily, with daylight reducing artificial lighting demand by up to 50% in optimally oriented classrooms, particularly during spring and summer. Smart dimming and adaptive control systems provide additional energy savings ranging from 27% to 46%, with estimated payback periods of approximately four years. Overall, the findings demonstrate that integrating daylight and adaptive LED systems is an effective and scalable strategy for reducing energy use while maintaining visual comfort in educational buildings under Mediterranean climatic conditions.

Abstract: The C-C motif chemokine receptor 1 (CCR1) plays key roles in guiding leukocyte movement during immune surveillance and inflammatory responses. Targeting CCR1 is a promising approach for treating autoimmune diseases and cancers. We previously developed anti-mouse CCR1 (mCCR1) monoclonal antibodies (clones C1Mab-2 and C1Mab-6) for use in flow cytometry and western blotting. However, the specific binding sites have not yet been identified. This study examined the binding epitope of C1Mab-2 and C1Mab-6. Analysis of mCCR1 mutants with altered extracellular domains showed that C1Mab-2 and C1Mab-6 bind to the N-terminal region of mCCR1. Additionally, PA-tag substitution experiments identified the epitope as comprising amino acids 1–13 of mCCR1. Further, alanine (or glycine) scanning within the N-terminal region (amino acids 2–13) was performed using flow cytometry and western blotting. The results demonstrated that Met1, Glu2, Asp5, and Phe6 are critical for recognition by C1Mab-2, while Met1, Glu2, Ile3, and Asp5 are essential for recognition by C1Mab-6. These findings enhance our under-standing of how mCCR1 interacts with C1Mabs.

Abstract: We conducted this single-center, retrospective study to assess a concordance rate between the microsatellite instability (MSI) analysis and the immunohistochemistry (IHC) in a cohort of Korean patients with hereditary non-polyposis colorectal carcinoma (HNPCRC). A total of 251 patients (n = 251) were included in the current study, who comprise 149 men (59.4%) and 102 women (40.6%) and whose mean age was 64.6 ± 11.5 years old. In our series, MSI-high (MSI-H) and microsatellite-stable (MSS) were identified in 17 (6.7%) and 234 patients (93.3%), respectively. Concordance analysis showed a strong agreement between MSI status and IHC expression of mismatch repair (MMR) proteins. Of the 17 patients with MSI-H, 16 (94.11%) had a loss of expression of ³ one MMR protein in the IHC findings, while one patient (5.9%) with MSI-H retained an intact expression of all four MMR proteins. Moreover, of the 234 patients with MSS, four (1.71%) had a loss of expression of ³ one MMR protein in the IHC findings. Of the 20 patients with a loss of expression of ³ one MMR protein in the IHC findings, 16 (80%) and four (20%) were found to have MSI-H and MSS, respectively. By contrast, 231 patients retained an intact expression of all four MMR proteins, with only one case (0.4%) being MSI-H and the remaining 98.3% (n = 230) MSS. There were distinct associations between the pattern of IHC expression of MMR proteins and microsatellite status. The most frequent abnormal expression patterns include mutL homolog 1 (MLH1) (-) postmeiotic segregation increased 2 (PMS2) (-) (n = 7), all of which were MSI-H, and mutS homologs 2 (MSH2) (-) mutS homologs 6 (MSH6) (-) (n = 7), with six patients with MSI-H and one with MSS. PMS2 (-) alone was observed in three patients, one and two of whom were MSI-H and MSS, respectively. MSH6 (-) alone was observed in one patient with MSS. Finally, there were two patients with PMS2 (-) and MSH6 (-), both classified as MSI-H. The current study indicates the high concordance between IHC and MSI testing in HNPCRC. But this deserves further large-scale, prospective studies.

Abstract: Ultrafast physical random bit generators (PRBGs) are essential components for modern applications in secure communication, quantum cryptography, and artificial intelligence. While optical chaos-based PRBGs offer high-speed capabilities, conventional systems often rely on discrete components that suffer from system complexity and environmental instability. This paper proposes and experimentally demonstrates a robust, integrated solution using a two-section mutual injection DFB laser. The device was fabricated using the reconstruction equivalent chirp (REC) technique, which provides precise control over grating phase variation while utilizing low-cost, high-volume fabrication methods.The laser sections, each measuring 450 m in length, were designed with a free-running wavelength difference of 0.3 nm to ensure a flat optical spectrum and enhanced chaotic dynamics. By optimizing the bias currents, we achieved a chaos RF bandwidth of 20.1 GHz. Notably, the resulting chaotic signal lacks time-delayed signatures, which simplifies the randomness extraction process. To generate random bits, the chaotic waveform was sampled by an 8-bit analog-to-digital converter at 100 Gb/s. Following post-processing through delay-subtracting and the extraction of the four least significant bits (4-LSBs), we realized a total physical random bit rate of 400 Gb/s. The randomness of the generated sequence was successfully verified using the NIST SP 800-22 statistical test suite. This approach offers a compact, energy-efficient, and high-performance integrated chaotic source suitable for secure communication and high-performance computation.

Abstract: Soil salinization is increasingly threatening global agricultural productivity and food security, currently affecting over 6% of the world’s land and one-third of irrigated areas. Tomato (Solanum lycopersicum L.), a major vegetable crop worldwide, exhibits moderate sensitivity to salinity, which limits both its yield and fruit quality. In recent years, epigenetic regulation has gained attention as a key mechanism enabling flexible and reversible control of gene expression without altering DNA sequences. This review synthesizes current knowledge on the epigenetic control of salt stress responses in tomato, focusing on three interconnected levels: DNA methylation dynamics, RNA-directed DNA methylation (RdDM), and histone modifications. We explore how DNA methyltransferases reshape the methylome under salinity, using examples such as PKE1 and SlGI to illustrate functional gene-body methylation. The RdDM pathway is discussed with emphasis on the unexpected role of SlAGO4A as a negative modulator of stress tolerance and the growing evidence for RdDM-mediated regulation of transcription factors. We also examine the balanced regulation of histone acetylation and deacetylation, highlighting the conserved role of GCN5 in maintaining cell wall integrity and the diverse functions of HDACs (SlHDA1, SlHDA3, SlHDA5) in stress adaptation. Additionally, insights from wild tomato species and grafting-induced epigenetic changes are presented, revealing new dimensions of stress memory. Collectively, these epigenetic mechanisms constitute a complex regulatory framework that integrates stress responses with growth and development, providing potential targets for epigenetic breeding of salt-tolerant tomatoes.

Abstract: Ochratoxin A (OTA) is a mycotoxin commonly associated with coffee production and represents a potential concern for occupational health due to fungal exposure in agricultural environments. This study aimed to assess occupational risk related to fungal exposure and OTA in small-scale coffee production systems in Quindío, Co-lombia. A cross-sectional descriptive study was conducted in ten farms. OTA concen-trations in green coffee were analysed using High-Performance Liquid Chromatog-raphy with Fluorescence Detection (HPLC-FLD), while environmental variables, in-cluding temperature and relative humidity, were measured, and structured surveys were applied to evaluate agricultural practices and hygienic conditions. All samples showed OTA concentrations below the detection limit (< 0.8 µg/kg). However, compli-ance with hygienic practices averaged 48.9%, indicating deficiencies in preventive measures. Although OTA contamination was not detected under the evaluated condi-tions, the results indicate potential occupational exposure to fungal bioaerosols during coffee production activities. These findings highlight the importance of integrating en-vironmental monitoring, Good Agricultural Practices (GAP), and occupational risk management strategies to reduce biological hazards and protect agricultural workers.

Abstract: Peptides are short chains of amino acids with a unique pharmacological niche between small-molecule drugs and large proteins. Their use in sports medicine is rapidly expanding, driven by patient demand for accelerated injury recovery and performance enhancement. While numerous peptide drugs have undergone a rigorous approval process that evaluates both safety and efficacy, a parallel "gray market" of unapproved compounds has emerged, operating largely outside regulatory oversight. Our objective is to present the pharmacological mechanisms, safety profiles, and regulatory status of prominent approved and unapproved peptides marketed direct to patients, including AOD-9604 (Anti-Obesity Drug 9604), BPC-157 (Body Protection Compound 157), CJC-1295, FS-344 (Follistatin-344), GHK-Cu (Glycyl-L-histidyl-L-lysine copper), ipamorelin, MOTS-C (Mitochondrial ORF of the 12S rRNA type-c), sermorelin, SS-31 (Elamipretide), tesamorelin (Egrifta), Tβ4 (thymosin beta-4), and TB-500 (thymosin beta-4 fragment). Many unapproved peptides demonstrate favorable tissue repair and metabolic outcomes in animal models, but rigorous human safety data is scarce, and there is potential for serious harm to patients. This narrative review focuses on the utilization of peptides in sports medicine, and alternative treatments that may be considered. We provide a framework to navigate patient discussions about peptides to better facilitate evidence-based practices for musculoskeletal healing and athletic performance. We also discuss the placebo effect as a mediator of peptide efficacy, and how social media amplifies this effect.

Abstract: This study evaluates the environmental performance of feed‑grade soy protein concentrate (SPC‑Feed) produced by Porta Hnos. S.A. in Córdoba, Argentina, through a cradle‑to‑gate plus end‑of‑life Life Cycle Assessment (LCA), with a specific focus on carbon footprint (CF). The assessment follows ISO 14040, 14044, and 14067 standards, using SimaPro^® with Ecoinvent 3.10 and Agri‑footprint 6.0 databases. Primary agricultural data were collected from soybean‑producing farms in Córdoba for the 2023/2024 season, while industrial process data correspond to the 2024 production year. System boundaries include soybean cultivation, soybean pressing, SPC extraction and drying, packaging, transportation to local and international markets, and packaging end‑of‑life. Results show CF values ranging from 0.608 to 0.851 kg CO₂‑eq per kg of SPC‑Feed, depending on market destination and packaging type. Agricultural production contributes ≈25% of total emissions, driven mainly by crop residues (54.7%), herbicide use, and fuel consumption. Industrial emissions are dominated by natural gas use in cogeneration and thermal processes, representing ≈43% of total CF. Downstream emissions are highly dependent on transport distances, especially for international markets. Comparative assessments indicate that SPC‑Feed produced in Argentina exhibits lower carbon intensity than similar products modeled for Brazil, USA, and Europe, primarily due to favorable agricultural conditions and the absence of land‑use‑change emissions. These findings support the environmental competitiveness of Argentine SPC‑Feed and highlight opportunities for further emission reductions through energy efficiency and logistics optimization.

Abstract:

Alice stays outside a black hole; Bob falls in. Alice never sees the interior. Bob crosses the horizon but can never signal back. Physics holds subjectively for both, yet their realities objectively contradict. This illustrating a conflict between quantum and classical mechanics. AMPS is a thought experiment about this. It asks one observer to distil a purifier of a late Hawking mode \( B \) from early radiation $R$, then compare it with the interior partner \( A \) inside a single causal patch. The hidden cost is not just computation but control. If the correct decoder depends on the black hole microstate, the observer must carry a physical selector for the decoder family. I model that selector as a finite control register bounded by the covariant entropy bound on the patch. A covering argument shows that any fixed, state-independent decoder works on at most \( 2^{\alpha_* S_{\mathrm{BH}}+c_\varepsilon} \) microstates, so the observer needs at least \( (1-\alpha_*)S_{\mathrm{BH}}-c_\varepsilon \) control bits---requiring a patch with area fraction \( \rho^2 \ge 1-\alpha_* - c_\varepsilon/S_{\mathrm{BH}} \). A time-sharing objection fails because single-observer verification requires co-instantiation, not mere sequential occurrence; serialisation creates no free room. The conclusion: a subhorizon observer generally cannot certify the AMPS contradiction. In quantum gravity, control information is physical, and single-observer certification is a capacity problem. If the contradiction can never be measured, is it real?