Search Results (62,536)

Existing studies on trust are mainly based on rational choice theory or the relational logic of the “differential mode of association,” while neglecting the contextuality of trust and the interaction of multiple factors. This study used a within-subjects situational experiment involving 252 participants, manipulating three variables: relationship type (kin, acquaintance, general other), entrusted matter (loans of 2000 yuan, 20,000 yuan, and 200,000 yuan), and trustee attributes (high ability and integrity vs. low ability and integrity). The Friedman test and Generalized Estimating Equations (GEE) were used to examine the effects of these three factors on trust intention and the mechanisms of their interaction. The results indicate that trust intention is influenced by relationship type, the importance of the entrusted matter, and trustee attributes, with significant interactions among the three. This indicates that trust is a contextual outcome shaped by multiple interacting factors rather than a linear result. This study provides contextualized evidence that relationship type, entrusted matter, and trustee attributes jointly shape trust intention. Full article

Background: Renal ischemia–reperfusion injury (RIRI) is a major cause of acute kidney injury (AKI) and contributes to delayed graft function and progression toward chronic kidney disease. In addition to oxidative stress and inflammation, RIRI induces profound metabolic derangements, particularly suppression of tubular fatty-acid β-oxidation (FAO), leading to energetic stress, lipid accumulation, and maladaptive repair. Peroxisome proliferator–activated receptor-α (PPARα) is a key regulator of tubular FAO, but whether Schisandrin B (Sch B) mitigates RIRI through restoration of a PPARα-associated metabolic program remains unclear. Objective: To determine whether Sch B alleviates RIRI in association with restoration of tubular FAO and attenuation of lipid accumulation and fibrotic remodeling. Methods: A unilateral murine renal I/R model and an HK-2 hypoxia/reoxygenation (H/R) model were used. Mice received Sch B (20 or 40 mg/kg/day) before I/R, and a subset was co-treated with the PPARα antagonist GW6471. Renal function, tubular injury, fibrosis, lipid accumulation, and FAO-related proteins were assessed by serum biochemistry, histopathology, Oil Red O staining, transmission electron microscopy, immunohistochemistry, immunofluorescence, and Western blotting. Bulk RNA-seq and public single-cell RNA-seq datasets were integrated to characterize metabolic pathway remodeling and cell-type-associated PPARα changes. Molecular docking and molecular dynamics simulations were performed to explore the potential interaction between Sch B and PPARα. Results: Sch B significantly improved renal function, reduced tubular injury, and attenuated interstitial collagen deposition after I/R. Sch B also reduced lipid droplet accumulation, preserved mitochondrial ultrastructure, and restored the expression of FAO-related proteins, including CPT1A, CPT2, and ACADM. In vivo and in vitro, Sch B decreased α-SMA, COL1A1, and vimentin expression, indicating attenuation of EMT-associated/profibrotic remodeling. Integrated transcriptomic analyses supported marked metabolic reprogramming after I/R, with enrichment of FAO- and PPAR-related pathways and reduced PPARα expression predominantly in tubular compartments. Sch B was associated with restoration of tubular PPARα expression, while docking and molecular dynamics analyses supported a plausible Sch B–PPARα interaction in silico. GW6471 blunted the beneficial effects of Sch B on fibrosis-related and FAO-related readouts. Conclusions: Sch B alleviates RIRI and limits subsequent fibrotic remodeling in association with restoration of a PPARα-related tubular FAO program, reduced lipid accumulation, and preservation of tubular metabolic homeostasis. These findings identify metabolic reprogramming as an important component of Sch B-mediated renoprotection, although the precise mode by which Sch B regulates PPARα requires further investigation. Full article

Facial recognition is widely employed in identification systems where access restriction is a desirable quality, providing greater security and preventing the access of unauthorized parties. With this problem in mind, this paper proposes a new texture descriptor that works in the RGB, YCbCr and HSV color modes. It obtains perceptual descriptive data from the photographs; the descriptor considers similarities between neighboring pixels and diminishing noise interference, making it robust to minor disturbances and bringing greater stability between similar images. Furthermore, the descriptor achieves good classification performance when used with both a neural network (NN) and the statistical classifier Support Vector Machine (SVM) on color images. A performance comparison of the proposed descriptor against LBP and OC_LBP employing three different face databases is presented to demonstrate that the proposed descriptor can work with the RGB, YCbCr and HSV color modes, presenting the best results when employing a neural network as a classifier with color image databases in the three studied color modes. Full article

Convolutional neural networks (CNN) have transformed visual recognition, yet robust geometric reasoning, reliable out-of-distribution generalization, and recognition from limited data remain substantially unsolved. CNNs draw their architectural inspiration from the mammalian visual cortex, but the translation from biology to engineering was selective and, in places, imprecise, and those imprecisions have consequences that are well documented. This paper examines where the biological fidelity holds and where it gives way, grounding the analysis in formal results that predate deep learning and in recent empirical findings on CNN failure modes. We identify three diagnosable architectural limitations. First, CNNs conflate visual modalities that the biological system separates structurally at the lateral geniculate nucleus, feeding raw RGB pixels into a single undifferentiated filter bank and entangling orientation, color, and texture signals from the first layer onward. Second, CNNs repeat a spatial subsampling operation across the full depth of the network, far beyond the early visual cortex stages where it has biological warrant. Barnard and Casasent established formally in 1990 that this operation discards positional information irreversibly at every layer where it is applied, and repeating it into regions that correspond to V4 and inferotemporal cortex compounds this loss without the compensating transition to qualitatively different computations that the biological hierarchy performs. Third, the pooling-as-complex-cell analogy that motivated this design reflects a misreading of what complex cells compute. The spatiotemporal energy model formalizes complex cell behavior as geometry extraction: detecting the presence and orientation of a local edge structure robustly, abstracting over photometric accidents of contrast polarity and sub-wavelength phase that are not geometrically meaningful. Pooling is a tolerable first-stage approximation of this behavior, but as a general-purpose invariance mechanism repeated across the full depth of the network, it is attempting something categorically different, namely object-level position invariance through spatial subsampling, which achieves its goal by discarding exactly the geometric information that the energy model preserves. Treating pooling as a scalable, indefinitely repeatable implementation of complex cell behavior—rather than as a first-stage approximation with a natural biological endpoint at V3—conflates two operations that differ not in degree but in kind, and crucially it removed the principled criterion for confining the S-C operation to early visual cortex: because pooling was understood as a general-purpose invariance mechanism, the field had no architectural reason to stop repeating it. We survey how capsule networks, group-equivariant CNNs, PDE-based networks, and vision transformers each address one or two of these limitations while leaving the others intact. We propose six desiderata that a more biologically complete architecture would need to satisfy and argue that satisfying them requires treating the visual cortex’s solution as a coherent package in which each component depends on the others working correctly, rather than as a menu of independently selectable principles. Full article

Research on contemporary Chinese comprehensive material painting has long focused on aesthetic qualities or relied on Western modernist frameworks, leaving the mechanism of material-to-symbol transformation under-theorized. This study investigates the generative logic of material meaning through a qualitative cross-case analysis of forty-eight works by twelve Chinese artists, integrating in-depth interviews and visual analysis. Through systematic analysis of images, material operations, and artists’ interpretations, the study proposes a three-stage semiotic mechanism: anchoring, exemplification, and differentiation. Findings demonstrate that material meaning is formed through continuous negotiation between bodily technique and material resistance, mediated by cultural techniques guided by pre-textual schemata. Material attributes are first filtered and anchored, reinforced through embodied operations, and eventually stabilized into stylistic structures articulating cultural identity. This research argues that Chinese comprehensive material painting constitutes a localized mode of cross-cultural symbolic production rooted in indigenous cultural experience and material praxis. Ultimately, it supplies a mechanism-based interpretive framework for this art form while contributing a localized perspective to global discussions on the relationship among subjectivity, materiality, and cultural identity. Full article

Background and Objectives: Breast cancer remains one of the most common malignancies worldwide, and early detection plays a crucial role in improving treatment outcomes and reducing mortality. Several experimental studies using animal models of breast cancer have explored the potential of terahertz-based technologies in this field. However, their preclinical evidence base in breast cancer remains heterogeneous and has not been systematically synthesized with a focus on experimental models, imaging protocols, and barriers to translation. Methods: We conducted a descriptive systematic review, according to PRISMA guidelines, of 10 articles selected from a total of 372 identified across four databases—PubMed, Embase, Web of Science, and Cochrane—regarding the diagnostic performance of terahertz (THz) imaging in breast cancer animal models. We included studies that used rodent models diagnosed with breast cancer, subsequently confirmed through histological examination, and extracted relevant data. Results: The results were synthesized using a narrative approach. Most studies used C57BL/6J mice with E0771 cell line-induced breast tumors, with histopathology as the reference standard. In the reflection mode, at frequencies between 0.1 and 4 THz, the identification of tumoral, fibrous, fat, and muscle tissues was possible. Conclusions: Overall, the available preclinical evidence supports THz imaging as a promising proof-of-concept approach for breast tissue characterization, but not yet as a standardized or clinically translatable diagnostic platform. Future studies should use harmonized animal models, standardized acquisition and specimen-handling protocols, transparent reporting of classification workflows, and consistent outcome metrics to enable comparison across studies and to clarify the biological and biophysical determinants of THz contrast in breast cancer. Full article

This research investigates a vertically structured Ge-on-Si avalanche photodetector (APD) fabricated in a separate absorption, charge, and multiplication configuration. The application of ramp gating enables reverse bias beyond the punch-through voltage, allowing the device to operate in linear avalanche mode. A significant dark avalanche current is observed under steady conditions, exhibiting linear multiplication approximately proportional to the input gating and thermal generation rate. Notably, this linear behavior persists even at voltages beyond the Geiger mode. The observed results are attributed to Ge/Si interface traps caused by the 4.18% lattice mismatch and deep-level traps introduced during fabrication. Under 1550 nm short-wave infrared normal-incidence pulsed illumination, the device exhibits negative differential resistance, attributed to illumination-induced self-quenching of electric field in multiplication region and modification of the barrier at the Ge/Si interface. A light-induced slow transient decrease in the absolute dark-state current is followed by a sustained inverse quenching effect, restoring the large dark-state current. These findings offer insights into the dynamic behavior of Ge-on-Si APDs, with potential implications for advanced optoelectronic applications. Full article

This article examines the representation of mental illness, emergency treatment, and recovery, in Ned Vizzini’s 2006 Young Adult novel, It’s kind of a funny story. Existing criticism has predominantly pursued what we term “diagnostic realist” approaches, which evaluate fictional representations against clinical criteria. We both affirm what this work achieves and make the case for extending it. Drawing on work on disability representation in Young Adult Literature and perspectives from Mad Studies, we propose that a social model lens, which locates mental difference within social and structural contexts rather than within individual pathology, opens out further possibilities for understanding what this and related novels do. We then demonstrate how close attention to Vizzini’s artistry—including to his use of romance conventions, figurative language, intertextuality, and first-person focalisation—reveals a text that does not simply mirror mental illness realistically, but which actively dramatises how social environments, institutional structures, and modes of creative expression shape the experience of and recovery from mental ill health. Rather than displacing diagnostic approaches, we argue that these wider critical paradigms, inclusive of the social model and attendant attention to craft, can enhance understanding of the help such novels can provide for different kinds of readers. Full article

Surface engineering strongly influences the performance, reliability, and safety of medical and biomedical devices, yet failures often originate at interfaces rather than in bulk materials alone. This review addresses the fragmented evidence base linking coating selection, interphase design, qualification testing, advanced characterization, and data-driven durability analysis. The objective is to provide an integrative, failure-mode-based framework for implants, reusable instruments, inhalation systems, diagnostics, wearables, and implantable electronics. A narrative synthesis of the peer-reviewed literature in coatings, biomaterials, electrochemistry, reliability, standards, and materials informatics was conducted, with qualitative tables used only when protocols were too heterogeneous for numerical pooling. The review compares physical vapor deposition (PVD), chemical and plasma-enhanced chemical vapor deposition (CVD/PECVD), atomic layer deposition (ALD), sol–gel/organically modified silica (ORMOSIL) hybrids, plasma polymers, parylene, bioactive or antimicrobial surfaces, and electronic encapsulation strategies. The main finding is that no universally superior coating exists; reliable performance depends on matching architecture and characterization to the dominant failure pathway, substrate compliance, geometry, sterilization or physiologic exposure, and the standards-constrained endpoint. The review further shows how electrochemical diagnostics, interfacial mechanics, multiphysics models, survival/reliability statistics, and carefully governed AI workflows can be combined to support service-life prediction and decision-oriented qualification. Full article

To address the issues of sluggish dynamic response, significant steady-state fluctuations, and poor disturbance rejection associated with traditional proportional–integral (PI) and conventional speed control methods, a novel sensorless sliding-mode speed control strategy for permanent magnet synchronous motors (PMSMs) based on the super-twisting algorithm (STA) is proposed. First, an advanced sliding-mode speed controller is designed by integrating an integral nonsingular fast terminal sliding-mode surface with the STA, thereby enhancing the dynamic response and transient stability of the PMSM under speed variations. Subsequently, to mitigate inherent sliding-mode chattering, a novel load torque observer is developed. This observer continuously feeds forward real-time load estimates to the speed controller, which substantially improves the system’s robustness against external disturbances. Furthermore, to eliminate the reliance on mechanical sensors and ensure reliable operation across diverse scenarios, an improved sliding-mode observer (SMO) incorporating the STA is utilized to achieve more precise rotor position and speed estimation. Finally, an experimental platform is established to conduct comprehensive variable-speed and variable-load tests on the PMSM. Experimental results demonstrate that the proposed method improves the dynamic response and disturbance immunity of the PMSM by 58.33% and 71.75%, respectively, while reducing steady-state fluctuations by 33.33%. These results demonstrate the effectiveness of the proposed sensorless sliding-mode control strategy and show improved speed regulation performance for PMSM drives. Full article

We develop a collection of nontrivial examples that illustrate and test recent stability results for linear control systems ($LCS$) on Lie groups. We treat the main structural classes: Abelian (${\mathbb{R}}^n$), nilpotent (Heisenberg), solvable non-nilpotent (rigid motions of the plane $SE\left(2\right)$), compact semisimple ($SO\left(3\right)$), noncompact semisimple ($SL(2,\mathbb{R})$ via Iwasawa decomposition) and mixed/Levi-type groups. The examples are designed to (i) show the sharpness of geometric boundedness criteria, (ii) exhibit typical failure modes (exponential escape, polynomial central drift, noncompact neutrals), and (iii) demonstrate how the canonical quotient and suitable outputs recover $BIBO$ stability. The executive framework ($ICS$ existence/uniqueness, canonical quotient $G/\Gamma$, $BIBO$ characterization, robustness and ISS-type bounds) is briefly recalled; the main part of the paper consists of detailed worked examples implementing the practical checklist for applying these theorems. Full article

The ongoing evolution of Industry 4.0 technologies necessitates novel and effective modes of human–machine interaction within production environments. This work presents a modular approach to the design and implementation of graphical user interfaces (GUI) in mixed reality, leveraging the Asset Administration Shell (AAS) standard. The proposed method enables the dynamic rendering of GUI elements in a Mixed Reality setting based on structured data retrieved from an AAS server. Developed for the Microsoft HoloLens 2 using the Unity engine and the Microsoft Reality Toolkit 3 (MRTK3), the system allows for the spatial placement of interface components either at predefined coordinates or in relation to specific elements of a production line model. Additionally, it incorporates a real-time distributed architecture utilizing OPC UA PubSub and MQTT protocols for processing and visualising live data. The prototype demonstrates the viability of using AAS as a flexible framework for defining and generating GUI components in immersive environments and lays the groundwork for further research into standardised, easily deployable user interface solutions for industrial applications. Full article

Background: While region-based models have informed pain neuroscience, chronic pain is now increasingly conceptualized as a network disorder. This narrative review aimed to critically examine the conceptual evolution of chronic pain models from region-based representations toward large-scale functional network frameworks across adult and pediatric populations while exploring how emerging artificial intelligence (AI)-driven approaches may support future precision pain medicine. Methods: A structured literature search was performed in PubMed, Scopus, and Web of Science, focusing on the scientific output addressing adult and pediatric chronic pain, pain-related neuroplasticity, functional network alterations, neuromodulation, and AI-based applications in pain medicine. Results: The reviewed literature supports a progressive conceptual shift from region-based representations of pain toward network-oriented models involving dysfunctional interactions among the salience, default mode, central executive, and sensorimotor networks. Although emerging evidence suggests developmental network alterations in pediatric chronic pain, current conclusions remain limited by the relative scarcity of longitudinal neuroimaging studies. Emerging AI applications demonstrate promising potential for objective pain assessment, trajectory prediction, and personalized therapeutic decision-making. Conclusions: The transition from the pain matrix to functional network models represents one of the most important conceptual advances in contemporary pain neuroscience. A network-based perspective may accelerate AI-enabled pain biomarkers and individualized interventions. Full article

The rapid growth of the sharing economy has improved resource utilization in car-sharing, yet it has also sharpened market competition and diversified user demand. A persistent obstacle is the low coordination efficiency between asset-heavy operating companies and traffic-driven platforms, whose misaligned objectives waste social resources. This paper uses differential game theory to analyze their dynamic coordination strategies and benefit allocation mechanisms. The Nerlove–Arrow model captures the evolution of brand goodwill, while the company’s decisions on station layout, vehicle dispatch, and pricing, together with the platform’s advertising investment, form the core decision variables in a two-party game framework linking the asset side and the traffic side. Compared with the non-cooperative Nash equilibrium, the cooperative mode removes the double marginalization effect, strengthens the investment incentives of both parties, and raises the system’s steady-state goodwill and total profit, achieving a Pareto improvement. To ground the cooperative framework in rigorous theory, we supply a verification theorem confirming that the linear candidate value functions satisfy the Hamilton–Jacobi–Bellman equations over the entire admissible state space. A formal proof of instantaneous rationality ensures that neither party falls into a cooperation trap on the horizon $[0,T]$, and the asymptotic stability of the steady-state goodwill trajectory is established. We further endogenize the revenue-sharing coefficient through a generalized Nash bargaining model that admits asymmetric bargaining structures, and introduce a Stackelberg leadership benchmark as a third comparative regime. Sensitivity analyses with respect to the discount rate and user heterogeneity confirm the robustness of the findings. A dedicated discussion section bridges the gap between idealized parameterization and data-driven calibration, describing practical pathways via A/B testing, user churn metrics, and econometric estimation of demand parameters. The results offer a scientific decision-making reference for strategic cooperation in the car-sharing industry. Full article

Urban mobility modeling plays a critical role in understanding transport infrastructure and improving its efficiency and sustainability. While existing tools are effective for modeling, they typically require extensive data acquisition, such as surveys, questionnaires, or tracking, as well as domain knowledge for calibration. We propose the Mobility Oracle, a framework that can algorithmically approximate urban mobility by incorporating human preferences in the routing process. The framework relies on open-source data and generates synthetic datasets for further analysis. It can be adapted to different contexts as it is reproducible, modular, and flexible. Both the theoretical components and the practical implementation are presented, along with a case study that illustrates the framework’s potential applications. Validation is carried out for Vienna (Austria) and Munich (Germany), comparing our approach against the official city-wide modal splits and a smaller tracked dataset within one of the cities. The resulting mode shares show an average difference of 4.7% at the city scale and a maximum of 1.9% for the tracked sample. These results demonstrate that the Mobility Oracle can be a useful tool to approximate human mobility. City planners and decision-makers can use it to systematically test and evaluate alternative planning scenarios across different urban contexts. Full article