Search Results (483)

Vignetting introduces spatial radiometric nonuniformity into remote sensing images and degrades subsequent radiometric analysis, image interpretation, and calibration-related applications. To address this problem, this paper proposes a vignetting correction method based on low-rank modeling and polynomial fitting. The method constructs a multi-frame data matrix in the logarithmic domain, extracts the shared vignette component through rank-1 low-rank modeling, and further recovers a smooth vignette field through polynomial fitting. Experiments were conducted using real remote sensing images, simulated vignetted images, and star images. Among the three ablation variants, the proposed full method achieved the best performance, with MAE, MAD, Center-MAE, and Edge-MAE values of 0.48%, 3.65%, 0.14%, and 0.52%, respectively. Compared with the low-rank-only method, these metrics were reduced by 23.8%, 32.8%, 71.4%, and 20.0%, respectively. An additional all-frame comparison across 28 dataset settings showed that the proposed rank-1 model achieved mean accuracy comparable to nuclear-norm-based standard RPCA, while exhibiting lower cross-dataset variability in MAE, MAD, and Edge-MAE. For star images, the method reduced image-plane nonuniformity from 1.39–1.92% to 0.59–0.80% while preserving background-subtracted stellar DN values. These results demonstrate that the proposed method provides physically interpretable and stable vignetting correction while maintaining radiometric consistency. Full article

Background/Objectives: The muscle synergy framework suggests that the central nervous system simplifies hand motor control by recruiting coordinated groups of muscles. However, the organization of these synergies across functional grasp types representative of activities of daily living remains incompletely understood. This study aimed to characterize muscle synergies across functional grasps and identify shared coordination patterns relevant for neuromuscular assessment. Methods: Muscle synergies were analysed in 26 healthy participants using a publicly available surface electromyography dataset. Five representative functional grasp types were selected, (cylindrical, lateral pinch, lumbrical, oblique, and tridigital pinch) and synergies were extracted using non-negative matrix factorization. Results: Four to five muscle synergies accounted for more than 90% of EMG variance across all grasp types. Despite grasp-specific differences, a consistent set of shared synergies was identified across conditions, explaining 92.5% of the total variance and being flexibly modulated depending on task demands. Extensor-related components showed a particularly consistent contribution across grasps. Conclusions: Functional hand grasping relies on a compact and reusable set of muscle synergies that are flexibly adapted to task demands. These findings support a modular organization of neuromuscular control and provide normative references that may be useful for the assessment of altered motor control in neuromuscular disorders, with potential applications in neurorehabilitation and assistive technologies. Full article

Vulnerable-code auditing is critical within the Software Development Life Cycle (SDLC) as timely remediation reduces exploitation risks from sensitive-data exposure to full system compromise. Although Automatic Program Repair (APR) has advanced through Machine Learning (ML), Deep Learning (DL), and Transformer-based generative models, current approaches remain limited by reduced language coverage, weak grounding in documented vulnerabilities, incomplete patch validation, and lack of explicit normative guidance for secure-coding compliance. This study introduces FocalVulNORM, a normatively conditioned Multi-Task repair model that generates a secure patch from vulnerable code while simultaneously verifying whether the vulnerable pattern is removed, the patch preserves observable behavior, and the repair aligns with the applicable security control. FocalVulNORM uses a shared Transformer encoder, a Focal Attention Layer, and four jointly optimized objectives: Repair, Detection, Normative Compliance, and Semantic Equivalence. The normative text is derived from CWE descriptions and SDLC secure-coding guides and standards, providing the security condition used to guide and evaluate each repair. Using this normative input, FocalVulNORM is trained on 11,503 vulnerability–patch pairs across seven programming languages and eight Common Weakness Enumeration (CWE) types. The model achieves CodeBLEU $=0.8247$ and Token-Level Accuracy (TLA) $=0.8976$ for Repair, $F1=0.9926$ for Detection, $F1=0.9820$ for Normative Compliance, and $F1=0.9921$ for Semantic Equivalence. The results indicate that FocalVulNORM extends APR beyond patch generation by attaching each repair to explicit evidence of vulnerability removal, behavioral preservation, and security-control alignment. Full article

Background: Cervical cancer remains a significant health issue in Indonesia, where structural barriers, fragmented information, and sociocultural norms continue to hinder timely diagnosis and treatment. Families play a central role throughout the illness journey, yet their perspectives are often overlooked in the development of digital patient navigation systems. This study explored family experiences, caregiving challenges, and expectations for a family-centered digital navigation model, DIVA.ID, by integrating Digital Health frameworks and Family Systems Theory. Methods: A qualitative descriptive approach was employed through semi-structured, in-depth interviews with 18 purposively selected family caregivers of women with cervical cancer at a major referral hospital in West Java. Participants were selected because they were directly involved in daily care, treatment decisions, logistical support, or emotional assistance. Interviews were conducted between August and October 2025 and continued until thematic saturation was reached, as indicated by repetition of categories and the absence of new major codes in the final interviews. Data were analyzed using inductive–deductive content analysis guided by Elo and Kyngäs, with five researchers conducting independent coding, iterative code comparison, consensus meetings, and theoretical mapping. Results: Four main themes emerged: (1) family involvement in decision-making, including collective discussion, shifting authority roles, and patient autonomy; (2) caregiver burden, involving physical exhaustion, psychological distress, social restriction, stigma, financial pressure, and employment disruption; (3) psycho-spiritual coping mechanisms, including emotional sharing, prayer, crying, patience, and surrender to God; and (4) digital healthcare needs, covering BPJS guidance, treatment information, scheduling, communication pathways, shelter support, and mental–spiritual support. Mapping these themes to Digital Health frameworks and Family Systems Theory clarified how DIVA.ID could translate family experiences into practical navigation functions. Conclusions: This study provides empirical foundations for a culturally sensitive, family-centered digital navigation model in Indonesia. Rather than demonstrating effectiveness, the findings identify design requirements for DIVA.ID that should be tested in subsequent feasibility, usability, and intervention studies. Full article

Data classification and grading is an information governance mechanism through which information resources are categorized, assigned responsibilities, linked to differentiated controls, and updated over time. Using China as the main case, this review examines how classification and grading has been operationalized across regulatory, local public data, and sectoral settings, and where its implementation remains incomplete. This study adopts a structured analytical review design, synthesizing academic studies, national laws and regulatory documents, standards and technical guidance, local public data normative documents, and sectoral implementation instruments, with a focused comparison of governance approaches in China, the United States, and the European Union. The review develops a five-dimensional information governance framework covering information stewardship roles, protected information assets and governance concerns, information categorization criteria and risk logics, differentiated information control mechanisms, and assessment and adaptive updating. The findings show that China has rapidly expanded regulatory and sector-specific arrangements for data classification and grading, especially in public data governance and in sectors such as telecommunications, finance, healthcare, and industry. However, significant operationalization gaps remain, including fragmented standards, weak cross-sector interoperability, uneven information stewardship capacity, limited translation of categories into access, handling, sharing, lifecycle, and audit controls, and underdeveloped feedback and updating mechanisms. By repositioning data classification and grading as information governance rather than only regulatory compliance, this review contributes to research on differentiated data management, information stewardship, and adaptive governance practice. Full article

Wideband direction-of-arrival (DOA) estimation is often formulated as a sparse signal recovery problem with multiple dictionaries, where the commonly adopted ℓ_2,1-norm minimization framework exploits the joint sparsity shared across different frequency bins. However, the resulting optimization problem involves a large number of variables and becomes computationally expensive as the problem scale increases. In this paper, a compact reformulation of the multi-dictionary ℓ_2,1-norm minimization problem is derived, which significantly reduces the number of optimization variables by introducing an equivalent diagonal representation. Under the special case of uniform linear arrays and harmonic sources, the proposed formulation is further extended to a gridless form, and its equivalence to wideband atomic norm minimization is discussed. For the grid-based compact formulation, an efficient block coordinate descent algorithm is developed, where each update admits a closed-form expression. For the gridless formulation, a first-order solver based on the alternating direction method of multipliers is employed to handle large-scale problems. Numerical simulations demonstrate that the proposed methods achieve substantial reductions in computational complexity, thereby enabling efficient wideband DOA estimation in large-scale scenarios. Full article

We present a family of compact, programmable wavelength demultiplexers enabled by an etchless silicon nitride platform integrated with the low-loss phase-change material Sb₂Se₃. Using topology optimization (LumOpt) with a p-norm (p = 2) figure-of-merit defined over a 10 nm bandwidth, we design several devices within a common 24 × 24 μm² design region: single-wavelength routers (1530, 1550, 1570, 1590 nm), two-channel (1550/1570 nm), three-channel (1530/1550/1570 nm), and four-channel (1530–1590 nm) coarse wavelength-division demultiplexers, all sharing the same input/output waveguide configuration. Simulation results show that all devices achieve low insertion loss at target wavelengths (peak transmission better than −1.21 dB across all channels), high average transmission over the respective 10 nm bands (typically within 0.1 dB of the peak), and suppressed crosstalk (worst case below −11.52 dB). Leveraging the reversible amorphous-to-crystalline phase transition of Sb₂Se₃ via laser pulses, all devices support post-fabrication reconfiguration, overcoming the static functionality of conventional etched photonic circuits. This work establishes a scalable, software-defined platform that combines inverse design and phase-change materials for high-density, reconfigurable wavelength-routing photonic integrated circuits. Full article

Food waste remains a persistent sustainability challenge within independent restaurants, where operational pressures, cultural norms, and resource constraints limit systematic waste management. This study examines how an industry–academia partnership enabled the co-creation of food-waste reduction practices between hospitality students and sixteen independent restaurant operators in Wellington, New Zealand. Adopting the Participatory Action Research (PAR) approach, data were gathered through semi-structured interviews with operators and focus group discussions with hospitality students. Findings reveal that food wastage in the study units is shaped by time pressure, customer service expectations, tacit kitchen routines, and uncertainty in forecasting the demand. The study identifies three mechanisms—emotional disruption, shared reflection and experimentation—through which sustainability competencies become a part in professional identity. It offers theoretical grounded and practically actionable insights for industry–academia collaboration in resource-constrained hospitality environments. Full article

Despite a century of learning research, why human beings desire to learn remains theoretically unresolved. Behaviorist, cognitivist, and constructivist paradigms explain the mechanisms of learning but presuppose rather than account for its motivational genesis—a gap this paper terms motivational minimalism. Drawing on René Girard’s mimetic anthropology, this paper develops Mimetic Learning Theory (MLT), grounded in philosophical anthropology (Plessner, Gehlen), hermeneutics (Rosa, Gadamer), and normative theory (Biesta, Honneth, Arendt). MLT reconceives learning as the reflective transformation of mediated desire. Humans do not merely copy actions but appropriate the desires of models who render knowledge, identity, and recognition worth striving for. Eight dominant learning paradigms are reread as partial articulations of this mimetic dynamic. Two novel constructs are introduced: mimetic load (the affective–cognitive tension from competing models of desire, complementing cognitive load theory) and zones of desire (a reformulation of Vygotsky’s zone of proximal development). MLT does not displace existing frameworks but re-grounds them in a shared anthropological logic—that learning begins not in the mind, but in the field of mediated desire. Full article

The governance of traditional medical knowledge faces persistent challenges from biopiracy and the inadequacy of conventional intellectual property regimes. This article examines the transformative potential and limitations of blockchain technology in governing traditional Chinese medicine (TCM) knowledge, adopting a framework that integrates legal validity, procedural justice, and governance implications. Drawing on normative legal analysis of Chinese statutes, empirical case studies of recent blockchain initiatives in China, and comparative analysis of the Nagoya Protocol and WIPO frameworks, the article advances three arguments. First, blockchain-enabled registration can generate legally cognizable evidence of prior existence, though its validity as a property right requires statutory recognition. Second, blockchain can enhance procedural justice by mitigating evidentiary asymmetry, expanding participation, and increasing benefit-sharing transparency. Third, the governance implications demand hybrid institutional designs that combine technological infrastructure with legal frameworks. The article identifies critical limitations—the oracle problem, accessibility barriers, and jurisdictional fragmentation—and proposes targeted optimizations, including statutory presumptions for blockchain records and enhanced international coordination. China’s experience offers actionable insights for equitable, legally embedded, and technologically sophisticated traditional medical knowledge governance globally. Full article

The article examines conservative rhetoric and discourse in Israel toward the LGBTQ+ community from a sociolinguistic perspective that conceptualizes language as an arena of socio-cultural struggle over identity, power, and normativity. Drawing on queer linguistics theory and identity politics, the study explores how language constructs reality through metaphors of illness, sin, and existential threat, as well as through theological framing and appeals to family and national values. These rhetorical strategies produce a social hierarchy in which heteronormativity is positioned as a “natural truth” while queer identities are labelled as deviant or threatening. From sociological perspective, the study reveals how conservative discourse establishes social boundaries and reinforces collective identity through the exclusion of the Other, thereby reproducing power relations and hierarchies. The article calls for the development of an alternative public discourse grounded in pluralism, inclusion, and the recognition of diverse identities as a means of strengthening democracy and social justice. While existing studies have examined conservative discourse toward LGBTQ+ communities primarily in Western contexts, this study contributes to the field by centering the Israeli case as a distinctive site of analysis, where conservative voices emerge from multiple and ideologically heterogeneous traditions: national-religious, ultra-Orthodox, and Muslim-Arab. By examining how rhetorically divergent speakers converge around shared mechanisms of exclusion, the study reveals that heteronormative discourse is not the product of a single ideological source, but a cross-sectoral phenomenon embedded in the specific political and cultural tensions of Israeli society. Full article

Values are cultural tools that pre-service teachers can use in situations that require discernment and integrity. Promoting an axiological framework in the training of future educators is an urgent necessity for coexistence in today’s world. This study aimed to understand the preferences and meanings that third-year students studying to become primary school teachers of mathematics, Spanish, and English as a foreign language attribute to values, as well as how values are transmitted in degree programs and at selected universities. An exploratory case study was used as the research design. Thirty-two students were selected using purposive sampling until theoretical saturation was reached. Data were collected through semi-structured interviews with the participants. Reflective thematic analysis was used to analyze the data. The findings revealed three themes: students’ value preferences are conditioned by their pedagogical training; values, as constructions of shared meaning, are conceived as normative guidelines that orient human action in all its dimensions; and teacher educators transmit values linked to the pedagogical role and teacher identity, while universities emphasize moral values oriented toward professional development, thus articulating two complementary levels of training. The study provides an empirical framework for moving from spontaneous value education to intentional communication, both in teacher training curricula and in the educational activities of each university. Full article

This study provides an empirical investigation into the impact of corporate sustainability practices on financial performance in Boursa Kuwait over the period 2015 to 2025. While existing literature has largely focused on firm-level analyses of ESG practices, limited attention has been given to their aggregated effect on market-level outcomes, particularly in emerging markets such as Kuwait. Moving beyond these gaps, the research conceptualizes sustainability as a potential systemic determinant of market behavior, examining its influence on the All Share, Main Market, and Premier Market indices. The study evaluates how variations in environmental performance, governance quality, and transparency of sustainability disclosures are transmitted into various market outcomes, including index returns, volatility, and market capitalization. Employing a combination of regression analysis and time-series modeling, the framework captures both short-term fluctuations and long-term structural dynamics, enabling a nuanced understanding of the complex interplay between ESG practices and market performance. Anticipated findings suggest that improvements in governance mechanisms and sustainability disclosure standards are likely to stabilize market dynamics, mitigate volatility, and support consistent index performance in the longer term, while short term expectations are more difficult to speculate upon. Additionally, the adoption of ESG practices is hypothesized exert positive influence on investor confidence and market participation, as it’s considered to reflect a gradual alignment of Kuwait’s capital market with global sustainability norms. Full article

Background: Procrastination is a voluntary and irrational delay in taking action despite negative consequences. We aimed to conceive/suggest a definition of procrastination, assess the behavior, and determine its psychopathological features (within the contexts of attention-deficit/hyperactivity disorder and obsessive–compulsive disorder. Method: In this scoping study, we systematically reviewed original research studies with conceptual and clinical data related to procrastination. Data were extracted regarding definitions, populations, instruments used, and psychopathology. Results: A total of 387 studies were included. Only 13% utilized clinical/subclinical populations. Definitions of procrastination showed no single consensus. The most cited elements involved irrational delay, awareness of consequences, task aversiveness, and self-regulation failure. The most frequently used assessment tool was Lay’s General Procrastination Scale. A considerable number of studies identified associations between procrastination and clinical constructs such as impulsivity, perfectionism, executive dysfunction, low self-esteem, and mood instability. Few studies directly assessed procrastination in formal diagnostic categories, suggesting that procrastination shares neurocognitive and emotional regulation deficits with these disorders, especially in domains involving task initiation, inhibitory control, and intolerance of discomfort. Conclusions: Procrastination is a transdiagnostic construct rather than a unitary behavioral trait. Its multifactorial nature calls for further clinical investigation, particularly in structured diagnostic settings. A unified definition is needed to distinguish between normative delay and clinically relevant procrastination. Full article

Background: Cognitive difficulties are common after SARS-CoV-2 infection, yet their neurobiological underpinnings remain uncertain. Cognitive symptoms in post-COVID-19 condition (PCC) are often characterised by attentional and executive dysfunction, although the relationship between subjective symptoms and objective neurobiological changes remains uncertain. Methods: Adults previously hospitalised with COVID-19 who reported persistent cognitive symptoms underwent neuropsychological testing and 3 T MRI. The protocol included high-resolution volumetric imaging, diffusion-based tractography, and magnetic resonance spectroscopy (MRS) of frontal white matter. Data were compared with age- and sex-matched controls from a pre-COVID-19 cohort and against pooled normative MRS datasets. Analyses adjusted for intracranial volume, sex, and time since infection, with false-discovery-rate correction. This study was exploratory and hypothesis-generating in design. Results: Thirty participants were recruited; twenty-nine completed MRI acquisition. Participants (mean age 58 years; 62% female; approximately two years post-infection) demonstrated selective impairments in attention, working memory, and verbal fluency. No widespread volumetric or white-matter differences were identified, although reduced posterior hypothalamic volume and altered occipito-parietal connectivity were observed. MRS demonstrated reduced N-acetylaspartate and elevated choline, myo-inositol, and glutamate-glutamine ratios relative to normative reference ranges. No significant associations were observed between imaging measures and cognitive or symptoms outcomes after correction. Conclusions: PCC is characterised by circumscribed cognitive changes and subtle neural differences, but these objective changes do not closely align with subjective symptom severity. This mismatch shares phenotypic features with functional cognitive disorder and suggests that post-COVID-19 “brain fog” is not driven by structural or neurochemical changes alone. Instead, it potentially reflects a combination of mild neurobiological effects and functional cognitive processes. Together, these findings highlight the importance of considering both brain-based and functional contributors to persistent cognitive complaints after SARS-CoV-2 infection. Full article