Search Results (364)

Background/Objectives: Sexualized drug use (SDU) and chemsex have emerged as a growing public health concern globally, reflecting complex intersections between sexual practices, psychoactive substance use, and structural vulnerabilities. In Brazil, however, evidence on healthcare access among individuals who engage in SDU/chemsex remains limited and fragmented. This scoping review aimed to map and analyze the available literature on healthcare access in this population, identifying barriers, facilitators, and gaps in care. Methods: The review followed the Arksey and O’Malley framework and Joanna Briggs Institute recommendations, with searches conducted in six databases (MEDLINE/PubMed, Embase, Scopus, SciELO, LILACS, and PsycINFO) for studies published between 2014 and 2025. Results: Eleven studies met the inclusion criteria, predominantly quantitative and concentrated in large urban centers. Findings indicate that healthcare access is shaped by persistent structural and symbolic barriers, including stigma, discrimination, fear of disclosure, and limited professional preparedness. Care remains largely centered on human immunodeficiency virus (HIV) and sexually transmitted infections (STIs) services, with insufficient integration of primary care, mental health, and substance use services, contributing to fragmented care. Significant gaps were identified, including the underrepresentation of women, transgender, and non-binary populations, and the absence of studies focusing on healthcare professionals. Conclusions: Substance use patterns reflect both global trends and local specificities, particularly the prominence of alcohol and cocaine in Brazil. This review provides the first synthesis of Brazilian evidence on chemsex from a healthcare access perspective. The findings highlight critical inequities and support the need for integrated, stigma-free, and context-sensitive care within the Brazilian Unified Health System. Based on these findings, the VIP-SDU/Chemsex Model is proposed as a multilevel framework to explain how structural, symbolic, and programmatic factors shape access and health outcomes. Full article

We present a spectral-action framework for connecting generalized trace dynamics (GTD) to the structural form of the low-energy action of the observed Universe. The fundamental single-STM-atom Lagrangian is decomposed exactly into a purely bosonic sector, boson–fermion cross terms, and bifermionic terms. This sectorwise decomposition furnishes a dictionary to almost-commutative spectral geometry: the bosonic sector supplies a quadratic GTD Dirac functional built from the six split-biquaternionic differential directions together with octonionic vector/gauge fluctuations; the cross-sector supplies, under an explicit localization hypothesis, a sesquilinear fermionic pairing; and the bifermionic sector supplies the scalar/internal channel that is bosonized into the Higgs bridge field. We also record the principal-symbol link between the $\mathrm{SO}(3,3)$ BF variables and the four-dimensional leafwise Dirac operator. The two four-dimensional leaves of the six-dimensional base overlap in two common directions; from the observed (gravitational) leaf, the two nonintersecting directions of the complementary leaf are internal, so the second leaf is reinterpreted as the weak-interaction sector rather than as an independent spacetime—a reinterpretation stated here as an explicit hypothesis. Under stated assumptions—spontaneous localization, Euclidean continuation, six- to four-dimensional BF reduction, and a candidate observed-leaf finite geometry compatible with the $E_6/J_3\left({\mathbb{O}}_{\mathbb{C}}\right)$ inputs—the bosonic heat-kernel expansion yields the structural low-energy classes of terms: Einstein–Hilbert gravity, Yang–Mills kinetic terms, and scalar kinetic and potential terms. In addition, we provide a candidate finite spectral triple with explicit finite trace invariants, verify that the localization map respects the one-generation lepton/quark representation split, identify visible color-singlet scalar channels with electroweak quantum numbers $(\mathbf{1},\mathbf{2},\pm 1/2)$, and exhibit a smooth regulator family with explicit cutoff moments $(f_0,f_2,f_4)$. Conversely, the assembled low-energy spectral action admits a natural inverse bilinear lift back to split bioctonionic trace dynamics. Every arrow of the construction is classified as an exact algebraic identity, an imported result, a working hypothesis, or an open problem. Under this classification, the paper offers a possible architecture for obtaining low-energy gauge–gravity physics from GTD, with conditional consistency checks and reductions; it is not a completed first-principles derivation of the Standard Model coupled to gravity. Full article

This paper develops explicit equations for setting the reorder point s and the order-up-to level S in a periodic-review (R, s, S) inventory policy in a lost-sales environment. The objective is to support direct policy parameterization from demand level, demand variability, review period, lead time, and type-II unit fill-rate target. A long-horizon discrete-event simulation was combined with exhaustive enumeration of integer policy pairs to construct a policy-consistent reference dataset of five million observations. Symbolic regression was then used to convert this simulation-derived reference map into compact closed-form equations for both policy parameters. Over the full tested domain, the equations achieved R² = 0.941 for the reorder point s and R² = 0.989 for the order-up-to level S. On the common domain where analytical comparison is possible, the proposed equations reduced mean absolute error by approximately 65% for the reorder point and 85% for the order-up-to level. The equations also remain directly evaluable at the finite-horizon zero-lost-sales boundary corresponding to a 100% fill rate, where standard normal-loss logic has no finite safety-factor solution. The study provides an interpretable, auditable equation system for initial estimation of policy parameters for periodic-review lost-sales inventory policies within the tested normal-demand domain. Full article

Spontaneous movement analysis provides valuable information about the maturation of the central nervous system and the emergence of motor control strategies in very young babies. Nonlinear measures capture dynamic aspects of movement that cannot be represented by linear methods. However, their implementation in clinical practice faces challenges, including the lack of standardized protocols and accessible tools for routine use. This scoping review aimed to map and characterize the nonlinear measures used to analyze spontaneous infant movement, including assessment context, instruments, data collection protocols, and main variables. The review followed JBI methodology and PRISMA-ScR guidelines. Searches were conducted in PubMed^®, Web of Science™, IEEE Xplore^®, ScienceDirect^®, and Google Scholar for studies published from 1 January 2005 to 31 December 2025. Of 1166 records identified, 18 met the inclusion criteria. The nonlinear measures were grouped into five main methodological families: entropy-based measures (n = 10), state-space and dynamical systems measures (n = 4), recurrence-based analysis (n = 3), symbolic and discrete-state approaches (n = 3), and variance and frequency-based nonlinear descriptors (n = 1). Studies were conducted in laboratory settings (n = 6) and in hospital and/or home environments (n = 10). Two studies did not clearly specify the assessment context. Kinematic assessment was mainly performed using video-based systems (n = 7), accelerometers (n = 4), and wearable sensors (n = 2), with most studies focusing on the upper and lower limbs. Several investigations extended beyond single-joint analyses to examine inter-limb relationships and whole-body configurations, capturing spatial coordination patterns across multiple body segments. Kinetic assessment was conducted using pressure mats (n = 4) and force platforms (n = 1), with the center of pressure displacement as the primary outcome. Future research should prioritise methodological harmonisation and theoretical clarity. Consensus is needed regarding minimal data requirements, parameter selection, and reporting standards for commonly used nonlinear measures. Studies should also move beyond single-metric approaches and adopt multivariate frameworks that integrate complementary nonlinear metrics. The absence of standardised acquisition and analytical protocols currently limits cross-study comparability and hinders the clinical translation of nonlinear movement metrics as objective tools for early neurodevelopmental assessment. Full article

Grammatical Evolution is a technique for evolving structured solutions using a genotype-to-phenotype mapping based on formal grammar. Optimization is typically performed on the genotype values. However, the use of permutations to guide mapping has been shown to improve solution performance. Traditionally, the focus has been on single-level optimization of the genotype values or the order in which codons are consumed during mapping. This motivates the use of a bilevel approach that enables the simultaneous optimization of genotype values and their ordering. This paper proposes a bilevel Grammatical Evolution approach called BiGE, in which the upper level optimizes the genotype values, whereas the lower level optimizes the order in which these same values are used in the mapping process. The approach was implemented using both Depth-First (DF) and Breadth-First (BF) mapping processes, which are the canonical mapping strategies in Grammatical Evolution. The proposed approach was evaluated on the Symbolic Regression Problem and compared with state-of-the-art approaches under identical experimental conditions. Statistical tests were performed to determine whether significant differences existed among the compared approaches. The results revealed statistically significant differences, indicating that incorporating a bilevel optimization strategy into the mapping process can improve the quality of the generated solutions. Full article

Façades play a decisive role in shaping the visual and symbolic character of historic urban environments. Recent European funding schemes promoting energy-efficient retrofitting have accelerated interventions on building envelopes. Although aligned with decarbonization objectives, these processes are generating significant chromatic and material transformations that risk eroding the visual coherence and cultural sustainability of consolidated urban areas. In the historic Ensanches of San Sebastián, the replacement of traditional envelope systems with new cladding solutions is leading to the loss of the architectural style of some facades and altering their materials, textures, and colors. A progressive “contagion effect” has been identified, whereby dissonant chromatic schemes—often associated with the proliferation of so-called “zebra blocks”, residential buildings with façades clad in alternating black and white stripes that have proliferated in recent urban developments—are replicated across adjacent buildings, gradually weakening spatial continuity and the genius loci of the neighborhood. In response to this phenomenon, this research develops a systematic methodology to analyze, quantify, and anticipate chromatic transformation in consolidated urban fabrics. The study combines historical morphological analysis, classification of architectural periods, and chromatic mapping of recent façade interventions. Based on this framework, a CARI, Chromatic Alteration Risk Index is proposed to evaluate the potential impact of façade alterations on urban chromatic coherence. Drawing on an epidemiological framework, the methodology enables the identification of critical transformation clusters, the assessment of contagion dynamics, and the definition of regulatory thresholds for color and material interventions. By integrating perceptual criteria, urban morphology, and spatial distribution patterns, the study moves beyond descriptive diagnosis and offers a transferable tool for municipal planning. The proposed approach supports the proactive regulation of façade rehabilitation processes, balancing energy efficiency objectives with the preservation of collective memory, material identity, and urban sensory quality. This study proposes a quantitative model of “urban chromatic contagion” to assess how façade color interventions propagate within a neighborhood. We define the Chromatic Integration Percentage (CIP) and the Chromatic Alteration Risk Index (CARI) of the analyzed area. Results indicate that poorly regulated façades show higher chromatic dissonance (low CIP) and act as contagion hotspots, while a clear risk gradient emerges: highly protected buildings present lower risk, whereas mixed typologies and recent rehabilitations concentrate higher CARI values. The model supports preventive urban color management by identifying areas at risk before visible alteration. Full article

The digitization of existing building stock often depends on legacy 2D raster floor plans (scanned drawings, PDF exports, or photographs) because structured building information models are frequently unavailable for older properties. Manual measurement and visual inspection of such documents are time consuming and error prone. This paper presents an integrated deep learning pipeline that extracts semantic information from unstructured two-dimensional floor plan images of existing structures and supports preliminary compliance screening via locally deployed large language models. The pipeline employs YOLOv8 for the localization and classification of 18 architectural symbols and furniture items, and a U-Net with a ResNet34 encoder for the semantic segmentation of walls and interior room spaces. To translate pixel-level predictions into physical metrics, we implement an area calculation module based on user-defined reference scale calibration. An LLM evaluation module, deployed locally via Ollama with a retrieval-augmented generation pipeline, interprets extracted room metrics and flags potential non-compliance against referenced residential design guidelines; it is intended for the assessment of existing layouts rather than generative co-design. We expand a core dataset of 101 manually annotated source floor plans to 303 augmented instances using label-aligned geometric transformations, while reporting generalization in terms of the 101 unique source plans. On the held-out validation split (10 source plans), YOLOv8 achieves 92.3% mAP50 versus 87.2% for a Faster R-CNN reference model on the same data split (detection baselines differ in training epochs and pretraining; see Experiments); U-Net achieves 95.71% mIoU, surpassing DeepLabv3+ (93.2%) under matched segmentation training settings. The system is deployed as an interactive web application for legacy building survey and preliminary regulatory review when only two-dimensional documentation is available. Full article

To address the limitations of vision-only defect detection, image–semantic misalignment, and spatial-logic conflicts in complex substation inspection scenarios, this paper proposes a camera-sensor-based multimodal defect sensing framework with cross-modal feature mapping for substation equipment monitoring. The proposed framework integrates field inspection images acquired by camera sensors, defect textual descriptions, and equipment topology knowledge and establishes a unified domain-adaptive pre-training–bidirectional cross-modal mapping–hierarchical reasoning workflow. First, a Contrastive Language–Image Pre-training (CLIP)-based domain-adaptive pre-training strategy is developed to enhance the representation of equipment categories, defect attributes, and inspection-scene semantics. Second, a bidirectional cross-modal feature mapping network is constructed to model fine-grained interactions between candidate visual regions and textual semantics, where uncertainty-aware fusion and prototype constraints are introduced to improve semantic alignment and defect discrimination. Third, a hierarchical neuro-symbolic reasoning module incorporates equipment topology and spatial rules for posterior verification, logical consistency checking, and false-positive suppression. Experiments on a substation inspection image dataset demonstrate that the proposed method achieves 90.8% mAP@0.5, 68.7% mAP@0.5:0.95, and 89.4% F1-score, outperforming mainstream and recent detection models. Full article

Fine-paste earthenware held symbolic significance in Hindu and Buddhist rituals and domestic use in Southeast Asia. Despite the influx of Chinese glazed ceramics from the ninth century onward, these locally produced vessels continued to circulate widely until the fourteenth century along maritime trade routes extending from northern Sumatra and Java to the southern Philippines and the Thai–Malay Peninsula. Integrated petrographic, Field Emission Scanning Electron Microscopy (FESEM), and Energy Dispersive X-ray Spectroscopy (EDS) analyses were employed to compare fine-paste earthenware from the Kok Moh production center in Songkhla Province, Thailand, and the Kota Cina consumption site in northern Sumatra, Indonesia. Petrographic observations indicate broadly similar mineralogical compositions in samples from both sites, consistent with the use of kaolin-rich clay materials. FESEM reveals that Kok Moh samples exhibit relatively dense and homogeneous microstructures with more continuous matrices, whereas Kota Cina specimens display coarser textures, more distinct mineral inclusions, and less consolidated matrices. EDS elemental mapping further demonstrates a more uniform distribution of major elements in the Kok Moh samples. Although both groups share broadly similar silica–alumina compositions, the observed microstructural differences suggest variations in clay preparation and firing practices rather than major differences in raw material selection. Comparison with published data from Nakhon Si Thammarat supports an association with kaolin-rich clay resources in southern Thailand. In contrast, the examined ceramics differ from fine-paste wares reported from northeastern Thailand, Myanmar, and India. These findings suggest that maritime Southeast Asian fine-paste ware developed as a localized technological tradition shaped by regional resources, production practices, and maritime exchange networks. Full article

Reasoning-intensive multimodal retrieval suffers from a counter-intuitive bottleneck: on MM-BRIGHT multimodal-to-text (Query+Image → Documents), the strongest dense multimodal encoder reaches only 27.6 nDCG@10 and the rest of the dense vision–language retrievers cluster between 10.0 and 23.0. The visual signal, encoded as a dense vector, adds noise rather than evidence; even augmenting strong text retrievers with raw image captions degrades performance by up to 12.0 points. We propose VISA, a Visual Symbolic Agent that re-casts multimodal-to-text as text retrieval over three parallel streams. A Vision LLM is dispatched in three roles via separate prompts: a zero-shot router that classifies the query image into up to three parser types from a fixed taxonomy of nine (chart, circuit, equation, screenshot, code, figure, diagram, map, photograph); typed parsers that extract structured text per type; and a holistic captioner. The agent constructs three text streams (raw query, query ⊕ symbolic, query ⊕ caption), scores each with a single frozen 4B-parameter retrieval LLM, and fuses the per-document scores via Reciprocal Rank Fusion or a confidence-weighted linear combination. The whole agent contains no trainable parameters. The key novelty is a change of substrate: rather than projecting the query image into a dense multimodal vector that competes with text, VISA is, to our knowledge, the first retrieval system to convert the image into typed symbolic text and keep retrieval entirely text-side, so that a frozen text retriever can match the literal tokens (axis values, variable names, function signatures) that answering documents actually contain. Across all 29 MM-BRIGHT multimodal-to-text domains, VISA achieves 32.4 nDCG@10, an absolute improvement of +4.8 over the strongest dense multimodal encoder and substantially larger margins over the remaining six dense vision–language baselines. Per-domain analysis shows VISA maintains its margin across STEM and software domains where image content is structure-heavy. In practical terms, VISA is training-free and model-agnostic: it requires no fine-tuning, reuses any off-the-shelf vision LLM and text retriever, caches all per-image parsing so re-runs cost only three query encodes, and can therefore be dropped into an existing text-retrieval stack to add reasoning-intensive multimodal capability without building or training a multimodal encoder. Full article

Pseudorandom number generators (PRNGs) used in deoxyribonucleic acid (DNA)-oriented computational workflows often generate outputs in the bit domain and then map them to DNA symbols. This indirect strategy may treat DNA-specific constraints, including GC balance, homopolymer limits, and short-range sequence dependencies, as separate from generation. This study proposes a constraint-aware, dual-head decoder-only Transformer framework for DNA-local PRNG generation directly in the adenine/cytosine/guanine/thymine (A/C/G/T) alphabet. The model generates the next DNA base and derives the bitstream through dynamic selection among eight equivalent DNA-to-bit coding rules. The framework was evaluated under R1 based on real genomic data, R1-ext as independent validation, R2 based on synthetic data, and R3 without training or reference data. For each setting, 10 independent runs were performed, each producing a 500,000-base DNA sequence and a 1,000,000-bit stream. Bit-level evaluation used NIST SP 800-22, SP 800-90B-inspired min-entropy/health indicators, and ENT, while DNA-level evaluation used GC balance, homopolymer control, and symbolic structural metrics. The reported NIST tests satisfied the acceptance criterion, t-tuple min-entropy lower bounds ranged from 0.9955 to 0.9964 bit/bit, and core DNA-compatibility constraints were preserved. Multi-stream and exact-match k-mer leakage analyses indicated no systematic bit-level dependence or direct long-fragment copying. Overall, the framework supports reproducible DNA-local PRNG generation and multilayer validation. Full article

Landscape Visual Assessment (LVA) has long examined how landscape elements influence visual perception and aesthetic response, yet the question of which elements attract attention remains underexplored in historic parks. Compared with urban parks, streetscapes, or natural landscapes, historic parks are shaped by a distinctive combination of natural features, cultural structures, and historically embedded symbolic meanings. In this study, we categorize landscape elements in historic parks into Natural Landscape Elements (NLE) and Cultural Landscape Elements (CLE), and investigate their relative visual salience in three historic parks in Beijing: Taoranting Park, the Summer Palace, and Beihai Park. We adopt a multi-method exploratory framework integrating cognitive maps, eye-tracking experiments, computational vision analysis, and GIS/UGC-based spatial analysis. The study draws on 30 cognitive maps, participant-level eye-tracking data from 30 valid participants, supplementary heatmap-based computational image analysis, and large-scale geotagged photo-density data. The results show that, within the exploratory sample, CLE were more frequently associated with strong memory impressions than NLE. In the pooled eye-tracking analysis, CLE showed higher attention scores overall, but this pattern was not stable across all parks and was strongly context-dependent. The computational and spatial analyses further suggest that attention distribution is influenced not only by the presence of specific elements, but also by color contrast, the spatial coupling of CLE and NLE, and the broader organization of park scenes and visitor activity zones. Rather than proposing a universal model of visual attention in historic parks, this study offers an exploratory, context-sensitive account of how cultural and natural landscape elements jointly shape attention across perceptual and spatial scales. The findings contribute to landscape visual assessment research by extending it into the specific setting of historic parks and by demonstrating the value of combining perceptual, computational, and spatial methods in a complementary framework. Full article

Environmental supply-chain governance increasingly requires firms to trace climate accountability across buyer–supplier relationships. This study examines whether downstream customer climate pressure is associated with suppliers’ green supply-chain management and value-chain carbon accountability among Chinese listed firms. We construct an exposure-weighted customer pressure measure by combining disclosed top-customer relationships with customer climate-accountability signals, and we decompose this measure into disclosure-based and non-disclosure-based components so that symbolic and substantive accountability can be separated. We then link this measure to supplier green supply-chain indicators, value-chain carbon-disclosure components, Scope 3 disclosure, environmental investment, and reported environmental performance indicators, including air emissions, water pollutant discharge, resource consumption, and environmental tax. Using firm-year panel regressions with fixed effects, alternative pressure measures, selection corrections, and extended outcome tests, we find an association between customer climate pressure and supplier value-chain disclosure. The depth of the association is concentrated where customer carbon-disclosure visibility is observed and is not separately identified in the smaller climate-only subsample, while the value-chain interaction association is positive but imprecisely estimated there. The value-chain disclosure associations are robust to a year-stratified randomization-inference placebo test. We do not find evidence that customer pressure is associated with supplier emissions, resource use, environmental investment, or environmental tax in the available matched samples. The pattern is consistent with symbolic compliance in supply-chain carbon accountability: customer disclosure visibility maps into supplier disclosure visibility, while we do not observe parallel movement in substantive environmental outcomes. The central finding is therefore that downstream customer climate pressure is associated with what suppliers disclose rather than with what they emit, shaping supplier disclosure behavior rather than substantive emission reduction. The estimates apply to supplier-year observations with disclosed and mappable listed-customer links, which we treat as the scope condition of the study rather than as an incidental data limitation. Full article

As an important medium for conveying rich historical and cultural information, the decorative elements of ancient Chinese timber architecture still lack a systematic understanding of their intrinsic cultural logic in current research and conservation practices. Guided by the cultural gene theory, this study systematically analyzes the wooden decorations of the Luzhai complex in Dongyang, Zhejiang, and constructs a “tangible–intangible” gene map comprising 24 relevant factors, including form, craftsmanship, and symbolic meaning. Through AHP-FCE (Analytic Hierarchy Process- Fuzzy Comprehensive Evaluation) quantitative analysis, 126 typical components from 427 decorative samples (including 165 from the Ming Dynasty and 262 from the Qing Dynasty) in the Ming and Qing Dynasty Luzhai in Dongyang were coded and quantitatively evaluated. The results indicate that the Ming-dynasty wooden architectural decorations in the Luzhai complex are characterized by botanical patterns, relief carving, and Confucian ethics, embodying restraint and ritual order; whereas Qing-dynasty decorations are characterized by animal patterns, round carving, and status symbols, reflecting sociocultural and economic transformation. This study provides a methodological framework for interpreting regional architectural decoration and offers theoretical and practical support for the conservation and digital preservation of traditional architectural heritage. Full article

Potentially toxic elements (PTE) pollution from lead–zinc (Pb–Zn) production poses significant ecological risks, requiring systematic assessment across the industrial chain. This study investigated soil, surface water, and sediments near a Pb–Zn mining area, integrating pollution indices (I_geo, NIPI, RI) with human health risk models. A spatial analysis framework was established by combining proportional symbol mapping and Thiessen polygons to analyze contamination patterns under small-sample conditions. Results showed a clear pollution hierarchy: smelting > beneficiation > tailings ≈ mining. Smelting and beneficiation zones exhibited multi-element pollution; Hazard Index (HI) exceedance probabilities reached 89% and 95%, respectively, while carcinogenic risk (CR) exceedance approached 100% across all zones. Cd was the dominant ecological risk factor, particularly in mining and tailings zones, where risk was mainly driven by a single element. Source apportionment identified two industrial groups—smelting-related (Pb, Hg, Zn, Se) and ore-associated (As, Cd, Cu, Sb)—whereas Cr, Ni, Co, and V were mainly derived from natural sources. These results indicate the need for coordinated management of beneficiation and smelting processes and provide a spatial analysis approach for small-sample assessment. Full article