Abstract: Firm-level financial statement data form multivariate annual time series with strong cross-variable dependencies and temporal dynamics, yet publicly available panels are often short and incomplete, limiting the generalization of predictive models. We present Latent Financial Time-Series Diffusion (LFTD), a structure-aware augmentation framework that synthesizes realistic firm-level financial time series in a compact latent space. LFTD first learns information-preserving representations with a dual encoder: an FT-Transformer that captures within-year interactions across financial variables and a Time Series Transformer (TST) that models long-horizon evolution across years. On this latent sequence, we train a Transformer-based denoising diffusion model whose reverse process is FiLM-conditioned on the diffusion step as well as year, firm identity, and firm age, enabling controllable generation aligned with firm- and time-specific context. A TST-based cross-decoder then reconstructs continuous and binary financial variables for each year. Experiments on Korean listed-firm data from 2011–2023 show that augmenting training sets with LFTD-generated samples consistently improves firm-value prediction for market-to-book and Tobin’s Q under both static (same-year) and dynamic (τ→ τ+1) forecasting settings, and outperforms conventional generative augmentation baselines and ablated variants. These results suggest that domain-conditioned latent diffusion is a practical route to reliable augmentation for firm-level financial time series.

Abstract: This paper presents an all-digital fractional-N phase-locked loop (ADPLL) operating in the 2.86-3.2 GHz range, optimized for IoT and high-frequency RF transceiver applications demanding stringent phase noise performance, fast settling time, and high integration capability. The key innovation lies in the introduction of a bandpass delta-sigma time-to-digital converter (BPDSTDC) that achieves high-resolution phase detection, an extended detection range of ± 2π, and superior noise-shaping characteristics, completely eliminating the complex calibration procedures typically required in conventional TDC designs. The proposed architecture synergistically combines the BPDSTDC with digital down-conversion blocks to extract phase error at baseband, a divider chain integrated with phase interpolators achieving 1/4 fractional resolution to suppress in-band quantization noise, and a wide-bandwidth digital loop filter (>1 MHz) ensuring fast dynamic response and robust stability. The bandpass delta-sigma modulator is implemented with compact resonator structures and a flash quantizer, achieving an optimal balance among resolution, power consumption, and silicon area. The incorporation of highly linear phase interpolators extends fractional frequency synthesis capability without requiring complex digital-to-time converters (DTCs), significantly reducing design complexity and calibration overhead. Fabricated in a 180-nm CMOS technology, the proposed chip demonstrates robust measured performance. The band-pass delta-sigma TDC achieves a low integrated rms timing noise of 183 fs within a 1-MHz bandwidth. Leveraging this low TDC noise, the complete ADPLL exhibits a measured in-band phase noise of -120 dBc/Hz at a 1-MHz offset for a 3.2-GHz output frequency while operating with a loop bandwidth exceeding 1 MHz. This corresponds to a normalized phase noise of -216 dBc/Hz. The system operates from a 1.8-V supply and consumes 10 mW, achieving competitive performance compared with prior noise-shaping TDC-based all-digital PLLs.

Abstract: This work addresses the qualification of photovoltaic micromodules intended for energy-harvesting applications in Internet of Things systems and proposes a novel qualification method based on highresolution electronic signature masks obtained through Time-Domain Reflectometry. The method applies frequency-to-time conversion of measured S11 parameters acquired using a Vector Network Analyzer under laboratory conditions. Accelerated reliability testing is employed as a sample preparation stage to validate the proposed qualification approach and to contextualize micromodules within a framework beyond existing regulatory standards, which currently exclude PV devices below 5 Wp. The qualification method based on pass/fail TDR signature masks demonstrated in this study has the potential to become a powerful tool for quality inspection of photovoltaic micromodules by assessing deterioration over time. The research introduces TDR technology—traditionally associated with high-frequency telecommunications—into the photovoltaic contex for research and development, manufacturing inspection, and certification purposes.

Abstract: Over-the-air (OTA) updates often face unstable delay and limited bandwidth, which lower data transfer speed and reliability. This study built an adaptive OTA transmission method that combines a Bayesian delay prediction model with Brotli–LZMA compression. The model estimates short-term delay changes and adjusts compression level according to network conditions. Tests were done under simulated satellite and IoT links with bandwidth between 0.5 and 10 Mbps. The results showed that packet loss dropped by 41%, transfer rate increased by 29%, and compression time accounted for 3.8% of the total process. The prediction model reached a root mean square error (RMSE) of 18 ms, showing good accuracy in delay estimation. These results show that combining delay prediction with adaptive compression can make OTA transmission faster and more stable in low-bandwidth networks. The method can be used in satellite, IoT, and remote monitoring systems that require reliable OTA data delivery.

Abstract: This study developed a patient-facing digital health app for precision screening of oral anti-obesity medications (AOMs), integrating questionnaires, lifestyle factors, wearable signals, and prior metabolic indicators to enable personalized drug recommendations. Based on real-world testing data from 520 users, a weighted ensemble model was employed for multidimensional risk assessment, achieving 82% consistency between recommended outcomes and clinical prescriptions. UX testing validated the system's patient-friendliness, significantly enhancing appointment readiness and long-term adherence. This study provides a scalable tool for AOM clinical screening and follow-up.

Abstract: Modern avionics increasingly depend on frequent software updates, making it necessary to understand how fleet-wide OTA rollouts affect operational risk. This study builds a digital-twin model that links onboard software states, air–ground communication, and maintenance timing, and uses three years of operational data containing 7.2×108 logs to test 32 OTA strategies. The simulations show that single-shot updates create the highest exposure, while batch updates with fixed thresholds reduce exposure but remain sensitive to short link disturbances. A combined strategy that uses batch updates, dynamic thresholds, and delayed rollback produces the best performance, lowering potential exposure by 48.3% without affecting mission completion. Module-level analysis based on importance sampling identifies the communication link and the update agent as the main contributors to the remaining risk and supports the construction of safety limit curves. These results demonstrate that software-centered digital twins can give practical guidance for OTA planning and fleet management. The study also notes limits related to human actions, fleet diversity and simplified security events, which should be addressed in future work.

Abstract: Background: Surgical removal of jaw cysts frequently results in bone defects that may compromise healing and delay functional rehabilitation. Laser photobiomodulation (PBM) has been proposed as a minimally invasive adjuvant capable of enhancing osteogenic activity; however, translational evidence based on freshly harvested human jaw bone tissue remains limited. Objective: To investigate the effects of intraoperative laser photobiomodulation on osteogenic differentiation and cellular viability in human bone explants obtained during cystectomy, using a paired experimental design. Materials and Methods: This translational experimental study included 20 patients undergoing surgical treatment for medium to large maxillary or mandibular cysts. From each patient, paired bone explants were harvested intraoperatively, with one explant exposed to diode laser photobiomodulation and the contralateral explant serving as an untreated control. Explants were cultured under standardized conditions and assessed for osteogenic differentiation using morphometric analysis, immunofluorescence staining for alkaline phosphatase (ALPL) and osteocalcin (OCN), and confocal microscopy. Cell viability was evaluated using a live/dead fluorescence assay. Results: Biologically viable osteogenic cultures were obtained from 8 patients and included in the final paired analysis. In the majority of responsive cases, laser-treated explants demonstrated an increased number of osteoblast-like cellular structures, greater osteoblastic surface area occupancy, and enhanced expression of ALPL and OCN compared with paired controls. No evidence of laser-induced cytotoxicity was observed. Conclusions: Intraoperative laser photobiomodulation enhanced osteogenic activity in human jaw bone explants in a subset of cases, supporting its potential role as a biologically active adjuvant in maxillofacial cyst surgery. Inter-individual variability highlights the need for further optimization of irradiation protocols and larger controlled studies to identify predictive factors for clinical responsiveness.

Abstract: In high-density urban environments, residential design often faces a conflict between maximizing landscape access and maintaining energy-oriented compactness. This study proposes a target-based visibility analysis framework to optimize high-rise forms under strict performance constraints. Utilizing a Quad-mesh reconstruction strategy and Inverse Targeted Ray-Casting, the method accurately quantifies visibility via the cumulative Landscape Visible Surface (LVS) on the target building and Viewpoint-Specific Surface Visibility Rate (Rv) for precise verification against specific landscape targets. The frame-work is applied to evaluate three morphological prototypes: Compact Tower, Dispersed Tower, and Slab–Tower Hybrid. Quantitative simulations identify the Slab–Tower Hybrid as the optimal solution, demonstrating superior "Visual Morphological Efficiency." While maintaining a moderate Shape Coefficient (SC=0.326) to satisfy energy standards, the Hy-brid achieves a cumulative Park-View LVS approximately 1.8 times that of the Compact Tower. Furthermore, environmental simulations indicate the Hybrid fosters stable wind environments (0.4–0.7 m/s) and equitable sunlight distribution. The research concludes that through differentiated massing, high-rise architecture can achieve a synergistic bal-ance between visual openness and physical compactness, transforming view analysis from a passive check into an active design driver.

Abstract: Early detection of cancer biomarkers in blood is critical for improving patient outcomes; however, conventional immunoassays often rely on complex instrumentation and are not well suited for point-of-care testing or multiplexed analysis. Herein, we present a dual-mode colorimetric–surface-enhanced Raman scattering (SERS) lateral flow immunoassay (LFIA) platform for multiplexed detection of cancer biomarkers, employing elongated rod-shaped silver nanoshells (ERNSs) as SERS nanotags. The ERNS features a rough Ag shell with internally incorporated Raman labeling compounds (RLCs), enabling plasmonic extinction for visual readout and strong SERS signals for quantitative analysis while preserving the external metal surfaces for efficient antibody conjugation. Leveraging these advantages, a multiplex LFIA capable of simultaneously detecting prostate-specific antigen (PSA) and carbohydrate antigen 19-9 (CA19-9) on a single strip was successfully demonstrated. Visual inspection enabled rapid discrimination of samples at or near clinically relevant cut-off levels, while Raman analysis achieved limits of detection of 8.0 × 10-3 ng/mL for PSA and 5.4 × 10-2 U/mL for CA19-9, corresponding to approximately 500-fold and 685-fold lower concentrations than their respective clinical thresholds. This ERNS-based colorimetric–SERS LFIA integrates rapid screening and highly sensitive quantification within a single platform and offers a versatile nanoprobe design strategy for multiplex biomarker detection and liquid biopsy–based point-of-care diagnostics.

Abstract: We present a geometric framework unifying the Riemann sphere $\hat{\mathbb{C}}$, the Moebius strip $M$, and Enneper's surface $E$ into a canonical triad that naturally encodes all fundamental physical scales. Through precise holomorphic embeddings and conformal mappings, we demonstrate: (1) The primal energy $E_0 = \SI{1820.469}{\electronvolt}$ emerges as the natural quantum of energy; (2) The primal length $\ell_0 = \ell_P = \SI{1.616255e-35}{\meter}$ is identified with the Planck length; (3) The fine-structure constant $\alpha^{-1} = 137.035999084$ is exactly derived from combinatorial relations among the first four Riemann zeta zeros $\gamma_1, \gamma_2, \gamma_3, \gamma_4$. We propose that this geometric framework could explain the Riemann Hypothesis topologically, lead to testable predictions in quantum and gravitational physics, and provide a foundation for holographic emergence of physical reality.

Abstract: For nearly a century screened Coulomb potentials have been of recognized importance in diverse areas of physics and chemistry. A key feature of interest in these potentials is the phenomenon of critical screening. This paper has three main purposes: To present an extensive, open-access, high accuracy (60 digit) benchmark reference data set of critical screening parameters, with validation; to confirm excellent past work in the field (to 30 digits), and to correct an historical oversight in its literature; and to present the essentials of our new approach, the “Phase Method” (PM), for computing them. Using the PM we calculate critical screening parameters, accurate to 60 decimal digits, for the Yukawa/Debye, Hulthén, Pseudo-Hulthén, and Exponential Cosine Screened Coulomb (ECSC)) potentials. The practical feasibility of such calculations on inexpensive hardware opens up new possibilities in research and education. We highlight an apparently overlooked 1989 paper of Demiralp on critical screening parameters of the Yukawa potential, which accurately calculated them to 30 decimal digits. Our main results are computations of the critical screening parameters µ_c= 1/D_c for screening lengths D ≤ 1000 au and angular momenta l = 0 . . . 20. The claimed accuracy of our results is supported by several independent lines of evidence: comparison with the most accurate (30 digit) values available in the print literature for the Yukawa, Hulthén, and ECSC potentials; comparison to 60 decimal digits accuracy with exactly known eigenvalues and critical binding parameters of the Pseudo-Hulthén potential; consistency tests between computed critical parameters, for various l-values for the Pseudo-Hulthén Potential, and known exact relations between eigenvalues; and application of a novel consistency test between results with different potential parameters, that exploits an exact scaling symmetry of this entire class of potentials. Similar calculations were done for ECSC and Yukawa potentials for screening lengths up to D ≤ 10⁵ and l ≤ 12, to 30 digit accuracy, which show interesting (and to our knowledge not previously reported) periodic structure in D_c(n, l) for the ECSC potential that is not observed for the Yukawa potential. The asymptotic scaling behavior for the Yukawa and Hulthén potentials is explained quantitatively by simple semiclassical calculations.

Abstract: We have known approximately 100 years that the Universe is expanding. But the striking discovery came at the end of 20th century, when we found that it is expanding with acceleration. Since then, many models have been developed in cosmology to explain this phenomenon. One of the possible elucidations is that the theory of gravity must be modified at the classical level. But many such models were already excluded by the gravitational wave experiments. Therefore, we must slowly start to ask a much more urgent question: could accelerated expansion of the Universe be a phenomenon of quantum gravity ? We review the basic models of how we explain the origin of dark energy or the cosmological constant in metastring theory, discrete approaches to quantum gravity, group field theory, non-commutative geometry, causal dynamical triangulation, asymptotic safety, models based on holography and entropic gravity. We mention at the end a newly formed approach to the quantization of gravity, the ring paradigm, which would, just after the application to cosmology, naturally model the late-time accelerated expansion epoch in the Universe. But what is completely striking is that the final formulation of this theory would ultimately solve the old problem of the cosmological constant.

Abstract: Living Wall Systems (LWS) are vertical vegetated building façade systems that offer environmental and social benefits; however, their adoption in South Africa, particularly within the Western Cape (WC), remains limited due to high capital and maintenance costs and the absence of regionally adapted design and cost models. This study investigates the viability and optimisation of LWS in the WC from a Quantity Surveying (QS) perspective, with the aim of developing a context-specific system utilising indigenous plant species and assessing its economic feasibility over the building life cycle. A mixed-method research approach was employed, comprising a review of relevant literature, semi-structured interviews with industry professionals, thematic analysis, cost modelling, and the preparation of a detailed Bill of Quantities (BOQ). Life cycle costing (LCC) techniques were applied to evaluate long-term cost implications. The study resulted in the development of an optimal LWS model, termed Viridis 5045, which satisfies identified environmental, technical, and contextual requirements for the WC. The BOQ, and LCC analyses provide projected capital and operational cost benchmarks for the proposed system. The findings indicate that Viridis 5045 is technically feasible and economically viable within the WC context, supporting its integration into sustainable construction practices. The study further identifies areas for future research, including the monetisation of long-term benefits, greywater integration, and the assessment of psychological impacts associated with green façades.

Abstract:

In recent years, the trend toward spacecraft miniaturization has led to the widespread adoption of micro- and nanosatellites, driven by their reduced development costs and simplified launch logistics. Operating these platforms in coordinated fleets, or swarms, represents a promising approach to overcoming the inherent limitations of individual spacecraft by distributing sensing and processing capabilities across multiple units. For systems of this scale, decentralized guidance and control architectures based on so-called behavioral strategies offer an attractive solution. These approaches are inspired by biological swarms, which exhibit remarkable robustness and adaptability through simple local interactions, minimal information exchange, and the absence of centralized supervision. This work investigates the feasibility of autonomous swarm maintenance under the stringent sensing and computational constraints typical of nanosatellite platforms. Each spacecraft is assumed to carry a single monocular camera aligned with the along-track direction. The proposed behavioral control framework enables decentralized formation keeping without ground intervention or centralized coordination. Since control actions rely on the relative motion of neighboring satellites, a lightweight relative navigation capability is required. The results indicate that complex vision pipelines can be replaced by simple blob-based image processing, although accurate reconstruction of relative parameters remains essential to avoid unnecessary control effort arising from suboptimal guidance decisions

Abstract: As the reliability and validity of forensic evidence, particularly in feature comparison disciplines, confront on-going scrutiny, forensic practitioners must ensure their processes, whether for investigative, intelligence or evidential purposes are robust, scientifically grounded, and validated. In forensic facial identification, morphological analysis is internationally recognized as the preferred method for facial image comparison, and is applied during the analysis and comparison steps of the Analysis, Comparison, Evaluation, Verification (ACE-V) process, commonly applied in feature comparison. While several international proficiency tests have assessed forensic facial examiners’ accuracy in comparing mated and non-mated pairs (black box tests), fewer opportunities have focused on evaluating inter-laboratory procedures and methods. To address this gap, members of a small border and immigration focused expert working group participated in an inter-laboratory collaborative exercise designed to analyse and harmonize best practices across member laboratories. There are limited published validation studies of facial image comparison methods. This paper presents the results of a collaborative exercise that compares the methodologies of three different agencies, highlighting key similarities and differences in examiner process and decision making, and provides a foundation for the development of similar future initiatives.

Abstract: Lipid sources are essential components in modern swine nutrition, not only due to their high energy density but also because of their positive effects on palatability, feed efficiency, and micronutrient absorption. However, rising raw material costs have encouraged the use of oxidized fats and oils (OxFO) as a cost-effective alternative in pig diets. These lipids, degraded by thermal and handling factors, undergo chemical alterations that negatively affect digestibility, energy metabolism, and animal health. This review critically examines the current scientific evidence regarding the impact of oxidized fat consumption in swine production systems. The physiological and biochemical mechanisms by which lipid oxidation products impair mitochondrial β-oxidation, cellular oxidative balance, energy efficiency, and meat quality are discussed. Moreover, the practical consequences on productive performance, muscle oxidative stability, and the expression of inflammatory and antioxidant markers are explored. Findings suggest that although the use of oxidized fats may offer economic savings, their metabolic and productive repercussions can compromise profitability and sustainability. The need to define safe inclusion thresholds (when replacement is not feasible), standardize analytical methods to assess oxidation status, and consider nutritional alternatives to mitigate adverse effects is emphasized.

Abstract: Gibson’s concept of optic flow established that perception is grounded in lawful, action-generated structure rather than in discrete sensory signals. While optic flow specifies self-motion visually, no corresponding framework has been formally established for the mechanical and kinesthetic information generated during skilled action. This study introduces haptic flow as a screw-structured, symmetry-bearing invariant that specifies kinesthetic information in human movement. Using screw theory, we model haptic flow as the continuous evolution of instantaneous screw axes and pitch, capturing the coupled rotational–translational dynamics of the body–object system. This framework is applied to the golf swing as a paradigmatic case of skilled manipulation. Motion data from proficient and novice performers reveal clear geometric differences: proficient performance is characterized by coherent alignment between instantaneous screw axes and the club’s principal inertia axis, stabilization of pitch through impact, and the emergence of harmonic screws lying on a common cylindroid. In contrast, novice performance exhibits fragmented screw organization, elevated pitch variability, and pronounced geometric asymmetry. These results demonstrate that skilled manipulation is structured by a continuous, internally generated flow of mechanical information that is invariant across critical phases of action. Interpreted in Gibsonian terms, harmonic screws function as perceivable affordances—symmetry-stabilized modes that couple inertia and potential and guide action without reliance on explicit feedback or internal models. The proposed concept of haptic flow thus extends ecological perception–action theory into the mechanical domain and provides a quantitative symmetry-based framework for analyzing skilled human movement.

Abstract: Galectin-3 (Gal-3) is a β-galactoside-binding lectin implicated in metabolic inflammation, cardiovascular and renal dysfunction, neurodegenerative disorders, and obesity-related pathologies. Although Gal-3 is recognized as a clinically relevant biomarker, the mechanisms controlling its tissue expression and circulating abundance remain poorly defined. O-GlcNAcase (Oga; encoded by Mgea5), the enzyme that removes O-linked β-N-acetylglucosamine (O-GlcNAc) from proteins, regulates nutrient-sensitive signaling and transcriptional processes that overlap with Gal-3 associated disease pathways. To investigate the relationship between metabolic status and Gal-3 expression, male mice were fed a high fat diet (HFD) for eight weeks to induce obesity. HFD-fed mice exhibited significant increases in body weight and fasting and fed blood glucose levels compared with lean controls, confirming metabolic dysregulation. ELISA revealed approximately threefold higher serum and plasma Gal-3 concentrations in obese mice, indicating enhanced Gal-3 production in diet-induced obesity. To determine whether Oga regulates Gal-3 expression, Oga wild-type (WT), heterozygous (HET), and knockout (KO) mice were analyzed. Circulating Gal-3 protein levels were significantly reduced in Oga KO mice, with intermediate levels in Oga HET animals. RT-qPCR revealed genotype-dependent modulation of Gal-3 (Lgals3) mRNA expression across multiple tissues, demonstrating tissue-specific regulation by Oga. These findings establish Oga as a critical regulator of Gal-3 expression and systemic abundance. The data reveal a mechanistic link between O-GlcNAc signaling and lectin-mediated metabolic inflammation, suggesting that Oga activity influences Gal-3 homeostasis and may affect its interpretation as a biomarker in metabolic disease.

Abstract: In Türkiye, where agriculture consumes 75% of available water and national irrigation efficiency is only 51.3%, irrigation modernization—the conversion of classical open-channel irrigation systems to pressurized pipe systems—presents a primary strategy to achieve significant water savings. This study provides a comprehensive economic assessment of the potential of this strategy. A twofold methodology was employed: first, a cost-benefit analysis (CBA) of the 36,108 ha Ivriz irrigation project, and second, a national model to simulate the economic impact of modernizing nation’s 4.9 million hectares currently irrigated by such classical systems. The Ivriz case study reveals that project viability is entirely contingent on the on-farm efficiency achieved post-modernization. At 60% efficiency, water savings are insufficient to make the project economically feasible, whereas at 90% efficiency, substantial water savings render the project highly profitable. At the national level, the analysis indicates that the conserved water could be used to expand Türkiye’s irrigated area by 1.77-2.98 million hectares, generating an additional $3.47-$5.84 billion in annual agricultural income. The findings conclude that while modernization represents a powerful investment, its success requires a comprehensive policy framework that not only funds infrastructure conversion but also mandates integrated support programs to ensure farmers adopt the high-efficiency technologies needed to achieve these savings.

Abstract: Over-the-air (OTA) updates in edge computing systems face practical challenges due to unstable network conditions and heterogeneous node capacities. To address this, we propose a task scheduling framework that integrates Deep Q-Network (DQN) reinforcement learning with a genetic algorithm. The model was tested with 120 OTA tasks across 50 industrial edge nodes. Results show that the proposed method reduces average scheduling latency by 23.9% and energy use by 18.5% compared to static baseline methods. Under network delays up to 300 ms, the task success rate remained at 99.2%, significantly outperforming FIFO and fixed-priority schedulers by 27.6%. The load distribution, measured by the coefficient of variation (COV), improved from 0.42 to 0.17. This indicates better task balancing among nodes. The framework adapts to fluctuating network conditions and provides a reliable solution for industrial and vehicle-mounted systems. However, long-term deployment effects and scalability in real-world environments require further investigation.