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Article
Biology and Life Sciences
Food Science and Technology

Meta Leonie Boller

,

Christian Krupitzer

Abstract: Given the increasing relevance of sustainability certification in food supply chains and, at the same time, rising confusion among consumers about the multitude of labels on food products, concerns about the value of sustainability certification occur frequently. This paper aims to investigate consumers’ evaluation and purchase intentions, and willingness-to-pay (WtP) for blockchain-enabled sustainability certification in coffee. Utilizing a questionnaire guided by an extended model of Ajzen’s theory of planned behavior (TPB), an online survey was conducted with n = 400 German consumers. Data were analyzed using structural equation modeling and cluster analysis. The results revealed perceived behavioral control (PBC) and SN as the most influential factors on WtP, whereas intention to buy is shaped by PBC and environmental concerns. Three distinct clusters were identified with concise preference, intention, and WtP profiles, highlighting heterogeneous consumer motivations. The study is the first one exploring the topic in the German context. It provides novel insights for academics and industry stakeholders on sustainable coffee, blockchain technology, and factors influencing evaluation and purchase intentions for coffee with blockchain-enabled sustainability certifications. It also paves the way for future research on blockchain-enabled sustainability certification in other product groups. Moreover, the paper contributes to a more nuanced theoretical understanding of the TPB and its applications.

Article
Biology and Life Sciences
Horticulture

Muhammad Awais

,

Hafiz Muhammad Usman

,

Xiaoqiong Xu

,

Chunyu Zhang

,

Yukun Chen

,

Shengcai Liu

,

Yuji Huang

,

Xu XuHan

,

Muniba Shafiq

,

Yuling Lin

+1 authors

Abstract: The PP2C (protein phosphates 2C) are key regulators of abscisic acid (ABA) signaling that play a crucial role in plant stress responses. In this study, we performed a comprehensive genome-wide analysis and identified 71 DlPP2C genes in Dimocarpus longan which is an economically important fruit crop. The evolutionary analysis revealed that DlPP2C genes were classified into distinct subgroups based on phylogenetic relationships with Arabidopsis thaliana and Oryza sativa. Structural analysis demonstrated conserved motif composition and gene organization within subgroups, whereas chromosomal distribution and synteny analysis revealed that segmental duplication events contributed to gene family expansion. Promoter analysis findings identified numerous cis-acting elements related to hormone and stress responsiveness especially abscisic acid-responsive elements (ABREs), suggesting their potential involvement in ABA signaling pathways. Under exogenous ABA treatments, expression profiling of the DlPP2C genes exhibited dynamic, dose and time dependent response with several genes showing peak expression at 10 μM ABA after 16 h, especially the DlPP2C1 displayed a strong transcriptional response, indicating its potential role as a key regulator. Overexpression and GUS staining assays revealed enhanced activity under ABA treatment, further supporting its involvement in ABA-responsive regulation. Moreover, RNA sequencing analysis revealed a total of 1799 differentially expressed genes, with prevalence of downregulated genes, showing extensive transcriptional reprograming. Functional enrichment analysis demonstrated that these genes were largely associated with plant hormone signaling, stress response and metabolic pathways. Together, these findings propose that DlPP2C genes, especially DlPP2C1, play a key role in ABA-mediated regulatory networks and provide valuable insights intro stress adaption mechanisms during early somatic embryogenesis in longan.

Article
Computer Science and Mathematics
Computational Mathematics

Renhe Liu

,

Yanyan Yu

,

Mengqian Yue

Abstract: Numerical simulation of the multi-dimensional space-fractional Cahn-Hilliard equation faces two main computational challenges: the inherent temporal accuracy limitations of standard scalar auxiliary variable (SAV) methods and the escalating computational cost in high-dimensional domains. To address these issues, this study constructs a fully discrete algorithmic framework integrating a second-order backward differentiation formula (SAV-BDF2) with a sixth-order centered difference scheme. Under this formulation, we rigorously prove unconditional energy stability and establish the theoretical validity of the dual temporal and spatial accuracy. To solve the resulting indefinite algebraic systems, a minimal residual solver is paired with a sine-transform block diagonal preconditioner. Additionally, a hardware-level Vectorized Tensor Processing (VTP) architecture is deployed to resolve cache thrashing caused by non-contiguous memory access during multidimensional tensor evaluations. Numerical experiments in 3D to 8D domains demonstrate that the framework improves memory throughput and reduces execution time. By avoiding standard hardware execution inefficiencies, this integrated strategy provides an efficient numerical solution for large-scale simulations of high-dimensional fractional systems.

Article
Computer Science and Mathematics
Analysis

Dumitru Adam

Abstract: Our result is in line with the Beurling and Alcantara-Bode equivalent formulations of the Riemann Hypothesis (RH). Also, it intends as a numerical method to supply the lack of the methods in literature for investigation of the injectivity of linear bounded operators on separable Hilbert spaces. The criteria exploit the operator approximation positivity properties on finite dimension subspaces having their union a dense set covering a wide range of linear, bounded operators. For operators that are not positive definite, taking their associated Hermitian, it consists of: a Hermitian Hilbert-Schmidt operator whose family of finite rank approximations built on a dense set having the positivity parameters inferior bounded, has a null space containing only 0, i.e. containing no not null elements. We obtained the injectivity for the Alcantara-Bode integral operator connected to Riemann Zeta function, that is in fact the equivalent formulation of the RH.

Article
Arts and Humanities
Archaeology

Togrul Khalilov

Abstract: The article examines, on the basis of a comparative study, the place and scientific significance of Cyclopean structures located within the territory of the Nakhchivan Autonomous Republic in the context of Azerbaijani archaeology. The research focuses on the distribution area, chronology, and architectural features of these monuments in Nakhchivan. It has been determined that the fortress-type Cyclopean structures of Nakhchivan are monuments of great scientific and historical importance in Azerbaijani archaeology. These constructions reflect the formation and development of defensive architecture in the region and make it possible to study their chronology and evolutionary processes. The study demonstrates that these fortresses, built of large unworked stones without the use of mortar, reveal the military–strategic thinking of ancient tribes, their level of social organization, and the importance they attached to the protection of residential spaces. Their wide distribution across the territory of Nakhchivan proves that the region was located on important trade and migration routes and functioned as an active political and economic center. These monuments serve as invaluable sources for the study of early urbanization processes, cultural interactions, and stages of regional development within the territory of Azerbaijan. Keywords: Nakhchivan, Cyclopean structures, fortress, defensive fortification, architectural structure.

Article
Physical Sciences
Astronomy and Astrophysics

Richard Dvorsky

Abstract: This paper presents a further step in the development of scale invariant fully conformal cosmology (FCC), formulated in our previous study. Whereas the previous paper focused mainly on the global cosmological consequences of the fully conformal metric and their confrontation with selected astrophysical data, here we analyze its local gravitational and background consequences. On the background of the fully conformal metric we formulate an effective generalization of the weak Schwarzschild field in the corresponding FCC global coordinates and derive from it the associated modified intensity of the Newtonian central field. We further derive the cosmological state/constitutive equation p = − ε/3 as a direct consequence of the fully conformal metric rather than as an ad hoc additional postulate. Likewise, within the fully conformal metric, spatial flatness and the critical density ρcrit are understood as direct consequences of this metric structure rather than as independently postulated inputs. From the condition of global equilibrium between negative cosmological pressure and the gravitational cohesive pressure of homogeneously distributed matter, the effective particulate fraction is obtained as β ≈ 0.45 of the total critical density ρcrit. For the relatively well-confirmed baryonic matter fraction , this stable-equilibrium condition then leads to the corresponding particulate fraction of collisionless dark matter , which is in principle determined by the global cosmological equilibrium within this framework. Because direct identification of the entire dark fraction with standard collisionless cold dark matter would very probably be incompatible with the main structural observables, we discuss an effective phenomenological decomposition into a structuring cold dark matter component (cdm) and an almost homogeneous residual warm-dark-matter-like component (wdm). In this interpretation, the paper preserves the previously introduced global FCC framework while simultaneously providing a concrete background prediction for the matter content and a physically motivated basis for further testing of structure formation within scale invariant fully conformal cosmology.

Review
Medicine and Pharmacology
Obstetrics and Gynaecology

Vanessa Hitch

,

Claire Louise O’Brien

,

Jim Parker

Abstract: Chronic stress, circadian disruption, sedentary behavior, industrialized diets and disturbances in the gut microbiome have created an evolutionary mismatch between ancestral physiology and the modern environment. Generation X (Gen X) women (born between 1965–1980) are the first cohort to enter midlife having lived their entire adult lives within these conditions while also carrying distinct cohort-specific factors shaped by major economic and cultural transitions. The interaction of evolutionary mismatch and Gen X pressures destabilizes hormonal regulation, increases allostatic load and impairs mitochondrial function, contributing to fatigue, metabolic inflexibility and cognitive dysfunction during perimenopause and menopause, with implications for postmenopausal health and long-term disease risk. Women with polycystic ovary syndrome have reduced insulin sensitivity and a heightened proinflammatory response that makes them more susceptible to Gen X evolutionary mismatch pressures. This paper synthesizes evidence from evolutionary biology, endocrinology, neuroscience and lifestyle medicine to present an integrated model explaining the mechanisms driving midlife symptomatology in Gen X women. The model places midlife dysfunction within an evolutionary mismatch context, where modern environmental exposures and cohort-specific demands interact with hormonal, immune and metabolic changes to drive convergent pathophysiological mechanisms. A tiered recovery framework is proposed, targeting allostatic load reduction, circadian realignment, restoration of metabolic flexibility, and integration of mitochondrial, musculoskeletal and gut–brain–endocrine signaling systems.

Article
Environmental and Earth Sciences
Geophysics and Geology

Yushu Yang

,

Ying Guo

,

Zhe Hu

,

Jiayang Han

Abstract: The color origin of precious coral, a highly valued organic polycrystalline gemstone, has long remained elusive. In this study, an integrated approach employing spectrophotometry, Raman, FTIR, and UV-Vis spectroscopy, coupled with Spearman correlation analysis, was utilized to investigate a color-graded series of precious coral samples ranging from white to red. The results demonstrate that the calcareous skeleton consists exclusively of calcite. The actual chromophores are identified as a blend of multiple distinct polyene species, characterized by Raman shifts at 1126 and 1515 cm⁻¹. Inherently exhibiting a red-orange hue, the progressive accumulation of these polyenes drives a systematic color transition from orange to red.Both absorption bands at 314 nm and 532 nm in the UV-Vis spectra originate from the polyene pigment molecules. Specifically, the broad 532 nm band is dominated by π-π* electronic transitions. As the pigment concentration increases, this band exhibits pronounced broadening and enhancement, accompanied by a redshift of the maximum absorption peak. This spectral evolution leads to an intensified absorption in the yellow-orange region, elucidating the intrinsic mechanism underlying the color transition of precious coral from orange to red with increasing pigment content. This work lays a solid foundation for the non-destructive identification of precious corals and future research on their color genesis.

Article
Medicine and Pharmacology
Neuroscience and Neurology

Atsushi Nakayashiki

,

Kunihiko Umezawa

,

Yasuo Nishijima

,

Ryutaro Suzuki

,

Michiko Yokosawa

,

Hidenori Endo

Abstract: Background/Objectives: The optimal upfront modality selection for real-world aneurysmal subarachnoid hemorrhage (aSAH) remains uncertain. This study evaluated the clinical outcomes associated with an institutional practice change from an endovascular treatment (EVT)-first approach to a more individualized upfront modality-selection strategy. Methods: This single-center retrospective before-and-after cohort study included consecutive patients with aSAH who underwent aneurysm securing during two fixed time periods (pre-change: 1 May 2023 to 31 July 2024; post-change: 1 August 2024 to 31 October 2025). The primary outcome was a favorable 90-day modified Rankin Scale (mRS) score of 0–2. The primary adjusted analysis used Firth penalized logistic regression with adjustment for age (per 10-year increase), pre-morbid mRS ≥ 2, and admission World Federation of Neurosurgical Societies (WFNS) grade IV–V. Conventional logistic regression was performed as a sensitivity analysis. The full 90-day mRS distribution (0–6) was also evaluated using an adjusted proportional odds model. Results: A total of 104 patients were included (pre-change, n = 48; post-change, n = 56). The distribution of securing modalities changed substantially between the two periods (EVT, 79.2% vs. 37.5%; microsurgery, 20.8% vs. 62.5%; p < 0.001). Favorable outcomes occurred in 25/48 patients (52.1%) in the pre-change period and 36/56 patients (64.3%) in the post-change period (p = 0.235). In adjusted analyses, the post-change period was associated with higher odds of a favorable outcome (adjusted odds ratio [aOR], 3.82; 95% confidence interval [CI], 1.31–12.79; p = 0.009), consistent with the sensitivity analysis (aOR, 4.41; 95% CI, 1.43–15.95; p = 0.009). Shift analysis also favored the post-change period (adjusted common OR, 2.36; 95% CI, 1.15–4.91; p = 0.021). Secondary outcomes and perioperative complications were similar between the two periods. Conclusions: In this single-center retrospective before-and-after study, an institutional practice change toward more individualized upfront modality selection was associated with more favorable adjusted 90-day functional outcomes in patients with aSAH. These findings support the potential clinical relevance of individualized modality selection in real-world aSAH management, although confirmation in multicenter studies is warranted.

Review
Engineering
Energy and Fuel Technology

Tommaso Gallozzi

,

Felipe Micangeli

,

Daniele Bricca

,

Daniele Groppi

,

Davide Astiaso Garcia

Abstract: The growing adoption of distributed renewable energy systems (DRES) calls for ad-vanced planning methodologies capable of addressing their inherent complexity and multi-dimensional trade-offs. Multi-Criteria Decision-Making (MCDM) frameworks are widely used to balance diverse objectives, but their effectiveness depends heavily on the selection of criteria, weighting techniques, and integration methods. This paper undertakes a systematic review of existing literature to analyse how MCDM ap-proaches have been applied in the planning and optimization of DRES projects. The review focuses on the criteria considered in MCDM, the techniques used to assign their relative importance, and the methods employed to integrate these weights into mul-ti-objective evaluations. The analysis draws from a diverse set of peer-reviewed pa-pers, examining economic, technical, environmental, and social dimensions, as well as the relationships between project-specific features and the criteria selection process. Results show that social criteria remain underrepresented both in terms of frequency and of relative importance in the evaluation process, while economic criteria are the most used and influential, underlining the need for more balanced, context-sensitive, and socially inclusive MCDM frameworks. Among MCDM methods and weighting methods, TOPSIS and AHP are by far the most common approaches, respectively. This review provides a foundation for future research aimed at improving the adaptability and effectiveness of MCDM frameworks in DRES.

Article
Social Sciences
Behavior Sciences

Chen Liu

,

Xiaofen Wan

,

Zhihao Ni

,

Sheng Su

,

Chunhua Kang

Abstract: This paper proposes a novel framework, HyperGAT-BERT-RAS, that integrates: (1) a Hy perGraph Attention Network (HyperGAT) with BERT for enhanced semantic representa-tion; (2) a Reference Answer Set (RAS) constructed via clustering of full-score answers; (3) Siamese Neural Networks (SNNs) for similarity-based scoring; and (4) GPT-4-based data augmentation to address class imbalance. Experiments on the Ohsumed and ASAP-5 da-tasets demonstrate that: (i) HyperGAT-BERT achieves 0.7317 accuracy on Ohsumed text classification, outperforming baseline HyperGAT by 2.69%; (ii) the full Hyper-GAT-BERT-RAS achieves 0.7991 accuracy and 0.7956 F1-score, with RAS contributing the most to performance gains (4.34% accuracy drop when removed); (iii) GPT-4 augmentation improves Quadratic Weighted Kappa from 0.584 to 0.880 and minority-class (scores 2–3) F1 by 15.3%. These improvements translate into more reliable scoring of diverse student answers, reduced teacher grading burden, and enhanced feasibility of AI-assisted forma-tive assessment in real classrooms. Ablation and error analyses confirm the contribution of each component. The framework advances ASAG by synergizing graph-based relational modeling, pretrained language understanding, and knowledge-guided scoring.

Article
Medicine and Pharmacology
Oncology and Oncogenics

Branko Dujovic

,

Aleksandar Popovic

,

Amina Jalovcic Suljevic

,

Bojana Cikota-Aleksic

,

Mirjana Balic

,

Igor Salatic

,

Jovana Pavlica

,

Philipp Schnecko

,

Tanja Mesti

,

Muamer Terzo

+2 authors

Abstract: Background/Objectives: This study evaluates the prognostic value of baseline inflam-matory biomarkers neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII) and pan-immune-inflammation value (PIV) in advanced cutaneous melanoma treated with first-line immunotherapy. Methods: This multicenter retrospective study included 162 patients with unresectable stage III/IV cutaneous melanoma treated with first-line pembrolizumab, nivolumab, or nivolumab plus ipilimumab. Biomarkers were calculated from complete blood counts obtained within 30 days before treatment start. Cut-offs were defined by ROC analysis. Progression free survival (PFS) and overall survival (OS) were analyzed using Kaplan–Meier and Cox regression. Response was assessed by RECIST v1.1. Results: Higher baseline NLR, PLR, MLR, SII and PIV were more common in patients with adverse baseline features, including liver metastases, elevated LDH and poorer ECOG performance status. Patients with biomarker values below the cut-offs had sig-nificantly longer PFS and OS. In multivariable models adjusted for clinical covariates, PIV remained independently associated with the duration of PFS and OS; MLR inde-pendently predicted PFS, while PLR independently predicted OS. Conclusions: Baseline inflammatory biomarkers from routine blood counts provide useful prognostic information in advanced melanoma treated with first-line ICIs. PIV showed the most consistent independent association with survival outcomes and may support initial risk stratification alongside LDH, ECOG and metastasis pattern. However, prospective validation in independent cohorts is needed before routine clinical implementation.

Article
Engineering
Mechanical Engineering

Chen Qian

,

Alexander Martinez-Marchese

,

Chinedum Okwudire

Abstract: Metal binder jetting (MBJ) is an additive manufacturing (AM) process that offers advantages such as high speed, low cost, and low residual stress, compared to the prevalent fusion-based metal AM methods. However, a major barrier to MBJ is the low density of manufactured parts, which restricts part quality and limits its applications. One key process parameter that affects part density is the packing density of the powder bed. In general, a higher packing density is preferable in MBJ. Although research has been conducted to enhance the packing density ex-situ, most proposed approaches lack robustness when applied to real-world printing, where environmental variations and stochastic powder behavior introduce inconsistencies. An in-situ sensing method for packing density can mitigate these issues in several ways. It enables the implementation of feedback control strategies to regulate packing density during printing, contributes to comprehensive in-situ process monitoring, and provides quantitative data to support post-processing analysis and optimization. However, effective in-situ methods for accurately sensing packing density remain limited. To fill this research gap, two methods, namely ultrasound (acoustic) and recoating-force sensing, are proposed as potential approaches for in-situ sensing of powder packing density. Using a dedicated test platform, their responses to different powder bed packing densities are measured and compared. The results show a strong correlation between packing density and the sensor measurements, with differing levels of estimation confidence, demonstrating promising potential for their implementation as in-situ packing density sensors. Furthermore, the concept of sensor fusion is tested by combining the force-sensing and acoustic-sensing data, leading to improvements in the estimation confidence.

Article
Medicine and Pharmacology
Dentistry and Oral Surgery

Hyunsuk Choi

,

Yong-Suk Moon

,

Hyung-Gyun Kim

,

Dong-Seok Sohn

Abstract: When placing dental implants, xenografts are most commonly used clinically to compensate for insufficient bone volume of patients. However, xenografts have limitations including low osteoinductive capacity and prolonged healing time. The aim of this study was to evaluate the effects of non-thermal plasma-treated bovine cancellous bone graft on new bone formation, graft resorption, bone marrow formation, and vascularization in a rabbit calvarial defect model. Twenty-four adult male New Zealand white rabbits received bilateral 8-mm critical-size calvarial defects. One defect was filled with untreated SANTA-OSS® (control) and the contralateral defect with plasma-treated SANTA-OSS using the ACTILINK™ Reborn device. Animals were sacrificed at 2, 4, and 8 weeks (n=8 per group) for histomorphometric analysis. The plasma-treated group showed significantly higher new bone area (14.12 ± 0.69%, 18.93 ± 0.68%, and 32.72 ± 0.61% at 2, 4, and 8 weeks) than the control at all time points (p < 0.05). In addition, the experimental group exhibited accelerated graft resorption, larger bone marrow area, greater blood vessel area, and more TRAP-positive osteoclasts compared with the control (p < 0.05). Within the limitations of this study, plasma treatment significantly enhanced new bone formation, accelerated graft resorption, promoted bone marrow development, and increased vascularization.

Article
Biology and Life Sciences
Horticulture

Miaohong Liu

,

Duyen Nguyen

,

Song Gao

,

Michiko Takagaki

,

Kun Xu

,

Na Lu

Abstract: Soil salinization severely limits the stable production of garlic (Allium sativum L.) and compromises the postharvest storability of seed cloves as industrial planting materials. This study evaluated the morpho-physiological, photosynthetic (JIP-test), and postharvest responses of a shoot-dominant ('C-P') and a root-dominant ('J-L') garlic cultivar to graded salinity (0, 50, 200 mM NaCl) in a hydroponic system, with or without seed-clove priming using a novel commercial biostimulant. Results showed 50 mM NaCl significantly inhibited shoot growth, while 200 mM nearly arrested growth and induced clove decay. Under moderate salinity, LE priming exhibited cultivar-dependent mitigation. In 'C-P', it promoted root branching, enhanced soluble sugar accumulation, and improved postharvest tissue hydration. In 'J-L', biostimulant elevated leaf SPAD values, fully reversed stress-induced clove yellowing, and significantly suppressed postharvest fungal decay during cold storage. In conclusion, garlic's response to salinity is fundamentally dictated by intrinsic resource allocation strategies. Rather than merely promoting growth, biostimulant priming optimizes photosynthetic energy fluxes and reshapes metabolism. This tailored approach effectively preserves the visual marketability of susceptible cultivars while enhancing Osmo protectant accumulation and hydration in vigorous morphotypes, providing a sustainable strategy to safeguard industrial raw materials in salinized controlled cultivation systems.

Article
Computer Science and Mathematics
Logic

Igor Durdanovic

Abstract: Mathematics, as actually practiced, operates as a federated system: practitioners work within autonomous domain-specific axiomatizations (geometry, algebra, analysis) and construct explicit bridges only when cross-domain reasoning is required. This organization is not accidental; it is a structural adaptation that safeguards local decidability and algorithmic efficiency. Yet the dominant foundational narrative still operates on the Compiler Myth—the belief that all mathematics must theoretically compile down into ZFC set theory to achieve rigor. We argue that this monolithic reductionism confuses representational universality with logical priority. Embedding a decidable (tame) domain into an undecidable (wild) one does not clarify foundations; it imposes a crippling epistemic overhead. It buries efficient, domain-specific decision procedures under general proof search and destroys the native structural immunities of the object. We introduce the Decidability Threshold — a litmus test based on Negation, Representability, and Discrete Unboundedness — to explain why mathematicians instinctively isolate tame domains from wild ones. Finally, we distinguish the Mathematician (builder of formal systems) from the Scientist (consumer modeling empirical reality). We argue that federalism is not a failure of unification, but the primary safeguard preventing the scientist from inadvertently importing uncomputable, undecidable paradoxes into physical theories. We show that for empirical applications, syntactic safety is insufficient; valid scientific modeling must be strictly confined to the constructively computable sub-fragments of these domains.

Article
Business, Economics and Management
Accounting and Taxation

Edman Padilla Flores

Abstract: Following the global financial crisis, the transition to IFRS 9’s forward-looking Ex-pected Credit Loss (ECL) model has introduced significant implementation complexity, particularly in emerging markets facing data limitations. This study investigates the heterogeneous ECL compliance strategies adopted within the Cambodian banking sector during a period of heightened credit stress, marked by a system-wide non-performing loan ratio of 8.6%. Utilizing a multiple-case study design and replication logic, a quali-tative content analysis was conducted on the 2024 audited financial statements of 13 representative institutions, ranging from market leaders to international subsidiaries. The findings reveal a pronounced technical divide: market leaders utilize advanced internal statistical methods, such as cohort analysis, while international subsidiaries rely on top-down parent-group proxy models to bridge local data gaps. A “macro-correlation paradox” was identified, where certain institutions prioritize faithful representation by excluding macroeconomic variables when statistical links to historical defaults remain weak. Furthermore, a significant transparency gap exists, where granular disclosures are leveraged as strategic communication tools to signal institutional safety. These results suggest that ECL compliance in data-limited environments is a strategic management choice rather than a standardized technical exercise, highlighting the need for regulatory standardization of modeling assumptions to improve inter-bank comparability.

Article
Computer Science and Mathematics
Computer Vision and Graphics

Tianzhi Jia

,

Shikui Wei

,

Yao Zhao

Abstract: Low-light image enhancement aims to recover high-quality visuals from poorly illuminated inputs, yet existing methods often suffer from over-enhancement, noise amplification, and semantic inconsistency in complex scenes. In this paper, we propose SeMaNet, a novel semantic-guided framework that integrates textual priors with a hybrid Transformer-Mamba architecture for controllable and efficient low-light enhancement. Our approach begins by leveraging pre-trained CLIP to generate semantically meaningful attention maps from natural language prompts, enabling interpretable region-aware enhancement without requiring pixel-level annotations. These semantic priors are then fused with illumination estimates and raw image features through a cross-attention mechanism, allowing dynamic interaction among multi-modal cues. To balance global context modeling and computational efficiency, we design a U-Net-based restoration network that interleaves Transformer blocks for long-range dependency capture and Mamba layers for linear-time sequence processing. Furthermore, our method explicitly models the image formation process via a perturbation-aware Retinex decomposition, enhancing physical plausibility. Extensive experiments on LOL v1, LOL-v2-real, LOL-v2-synthetic, SID, SMID, and SDSD-out datasets demonstrate that SeMaNet achieves state-of-the-art performance in both quantitative metrics (PSNR, SSIM) and qualitative quality, particularly excelling in preserving semantic coherence and fine details under challenging lighting conditions. The hybrid architecture also offers superior inference efficiency compared to pure Transformer-based models.

Article
Physical Sciences
Quantum Science and Technology

Bin Li

Abstract: We propose a structural framework for understanding quantum computational advantage based on admissible continuation of configurations. Within this framework, quantum computation is interpreted as the organization of admissible histories whose contributions combine through phase coherence, in a manner related to path-integral formulations of quantum mechanics. We identify three fundamental structural resources: the multiplicity of admissible histories, the persistence of phase coherence, and the non-factorizable structure of continuation constraints (entanglement). We introduce the notion of effective coherent multiplicity as a measure of the portion of history space that contributes constructively to computational outcomes, and formulate a structural speedup conjecture relating superpolynomial quantum advantage to its growth under bounded instability. This perspective provides a unified explanation of both the power and the limitations of quantum computation, clarifying why unstructured problems admit limited speedup while problems with strong global structure can exhibit substantial advantage. The framework complements standard circuit-based complexity theory by relating computational power to the organization of admissible-history space.

Article
Public Health and Healthcare
Other

Joaquin Garcia-Estrada

,

Diana Emilia Martínez-Fernández

,

Iris del Socorro Pérez Alcaraz

,

Carlos Joel Mondragón Gomar

,

Irene G. Aguilar-García

,

Sonia Luquin

,

David Fernández-Quezada

Abstract: Background: Substance Use Disorder (SUD) is characterized by recurrent craving episodes frequently associated with emotional dysregulation and altered reward processing. This study aimed to evaluate whether emotional states associated with craving episodes can be detected through automated facial emotion recognition during controlled emotional induction. Methods: Forty-one participants completed a 14-day ecological momentary assessment (EMA) monitoring anxiety and craving levels, followed by an emotional induction task using standardized stimuli from the EmoMadrid database and addiction-related images. Facial expressions were recorded and analyzed in real time using a computational facial emotion recognition model trained on the FER-2013 dataset. Results: Participants with SUD exhibited significantly reduced positive emotional valence and activation in response to positive stimuli compared with HC (p &lt; 0.01). Item-level analyses revealed that most differences occurred in stimuli depicting social interactions. Positive emotions and energy were linked to less intense cravings and shorter substance use. People with SUD showed more fear and less disgust in their facial expressions than controls (p = 0.02). Conclusions: These results suggest that people with SUD have changes in how they process emotions, showing less response to positive things and unique facial expressions related to craving.

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