Search Results (531)

High-frequency induction hardening enhances the surface wear resistance and contact fatigue life of high-speed linear guides, but simultaneously produces an inhomogeneous, layered cross-sectional structure comprising a high-strength, low-ductility outer hardened layer and a low-strength, high-ductility inner core. This structural heterogeneity renders conventional straightening stroke prediction models—predicated on homogeneous material assumptions—fundamentally inadequate. Moreover, the iterative trial-bending operations ubiquitous in industrial practice progressively accumulate plastic strain, causing guide rails to exhibit erratic positive-to-negative deflection reversal during sequential straightening passes. To address these critical challenges, this study proposes a novel two-stage hybrid straightening strategy based on inverse finite element analysis (FEA) and closed-loop experimental feedback. An equivalent hardened layer depth (HD₀) is introduced as a parametric descriptor to construct a layered elastoplastic finite element model, and an inverse simulation strategy is developed to generate a comprehensive three-dimensional stroke–residual deflection prediction dataset encompassing both vertical and lateral straightening conditions across multiple support spans. Displacement-controlled three-point bending experiments validate the layered model and elucidate the mechanism by which cumulative plasticity progressively amplifies cross-sectional plastic sensitivity under repeated loading. Grounded in this physical insight, a hybrid straightening algorithm is formulated, combining dataset-driven initial stroke prediction for rapid large-deformation elimination with an upper-bound constraint and a measurement-feedback-driven sequential reduction compensation scheme for fine-tuning. Comparative experiments demonstrate that the proposed strategy effectively suppresses the oscillatory over-straightening characteristic of conventional empirical trial-and-error approaches, consistently reducing residual deflection below 0.05 mm within two to three loading cycles. This work bridges the gap between theoretical simulation and the complex physical state of actual machining, substantially improving both the efficiency and precision of straightening for guide rails with induction-hardened layers. Full article

Background and Objectives: High-risk pregnancy increases vulnerability to psychological distress, but protective mechanisms remain poorly understood. This study compared emotional distress and coping strategies between women with high- and low-risk pregnancies and investigated whether active coping and marital satisfaction moderated associations between negative pregnancy experiences, prenatal depression and perceived stress. Materials and Methods: A cross-sectional study was conducted among 195 pregnant women aged 18–51 years (M = 31.76, SD = 5.32), including 102 women with high-risk pregnancies and 93 women with low-risk pregnancies. Participants completed the EPDS, STAI, PSS-10, PRAS, PES, COPE, and CSI. Independent-samples t tests, correlation analyses, and moderation analyses were conducted. Results: Women with high-risk pregnancies reported significantly higher levels of prenatal depression (p = 0.032) and pregnancy-related anxiety (p < 0.001) than women with low-risk pregnancies. They also reported lower socio-emotional support (p = 0.036) and mental disengagement coping (p = 0.022). Negative pregnancy experiences were positively associated with state anxiety, pregnancy-related anxiety, prenatal depression, and perceived stress after controlling for pregnancy risk status (all p < 0.001). Maladaptive coping was generally associated with higher emotional distress, whereas adaptive coping, particularly positive reinterpretation and planning, was associated with lower levels of prenatal depression and anxiety. Active coping moderated the association between negative pregnancy experiences and perceived stress (β = −0.16, p = 0.016). Marital satisfaction moderated the association between prenatal depression and perceived stress among women with high-risk pregnancies (β = −0.21, p = 0.016). Conclusions: Active coping and marital satisfaction were associated with lower psychological distress and may represent potentially modifiable psychological resources for women experiencing high-risk pregnancies. Although the cross-sectional design precludes causal inferences, these findings highlight the potential value of integrating psychological screening, coping-focused interventions, and partner involvement into prenatal care, particularly for women with high-risk pregnancies. Full article

Background/Objectives: Poly(lactide-co-glycolide) (PLGA) microspheres support long-acting drug delivery, but their release profiles are difficult to predict because burst release, diffusion, polymer degradation, and formulation-dependent effects interact across multiple time scales. This study aimed to develop a continuous-time model that combines accurate release prediction with physically admissible trajectories and release-component attribution. Methods: MC-NODE encodes ten drug, polymer, and formulation descriptors, decomposes the non-negative release rate into burst, diffusion, degradation-associated late-stage, and neural-residual components, and applies a formulation-dependent plateau through a semi-analytical state map. The model was evaluated on a literature-curated dataset containing 321 in vitro release curves, 4913 observations, 89 drugs, and 113 publications using DOI-grouped five-fold cross-validation, complementary extrapolation and sparse-sampling protocols, synthetic mechanism-recovery experiments, and retrospective orthogonal consistency analysis. Results: MC-NODE achieved an RMSE of $0.094\pm 0.005$ and an $R^2$ of $0.854\pm 0.018$, with all 321 out-of-fold trajectories satisfying monotonicity and range criteria. It recovered synthetic contribution labels more accurately than the ablated variants. The degradation-associated late-stage contribution showed positive associations with experimental degradation, molecular-weight loss, pore-evolution, and mass-loss indicators, while the diffusion contribution was positively associated with an experimental diffusion indicator. Dominant-process agreement was 83.3%, and matched external or out-of-fold trajectories achieved an RMSE of $0.108\pm 0.020$. Under drug-grouped, chemical-cluster, and alternative sparse-sampling evaluations, MC-NODE retained the lowest absolute trajectory-level errors among the compared models. Conclusions: MC-NODE improves formulation-level PLGA release prediction while preserving continuous, monotonic, and bounded trajectories. Its component outputs provide experimentally supported, model-attributed summaries for comparative formulation analysis. Full article

The regular practice of physical exercise is often associated with promoting benefits for practitioners. In recent decades, street running has become popular worldwide, with most participants being recreational runners who engage in the activity primarily to promote health, well-being, leisure, and quality of life, although some also participate with competitive goals. Among the psychological aspects related to exercise, studies have shown that some individuals may become susceptible to “exercise dependence,” a condition in which exercise takes a central role in a person’s life. As a result, individuals may exhibit characteristics such as excessive training, injuries; weight control issues, withdrawal symptoms when unable to exercise and even problems in social relationships when exercise is exclusively prioritized. Background/Objectives: The aim of this study was to investigate and analyze levels of susceptibility to running dependence and its relationship with exercise volume and mood states (tension, depression, anger, vigor, fatigue, and mental confusion). Methods: This was a quantitative cross-sectional study involving 761 regular Brazilian runners (59.8% male and 40.2% female) who consented to participate and answered the Sociodemographic Questionnaire, the Escala de Dependência de Corrida (EDC), a Brazilian Portuguese adaptation of the Negative Addiction Scale (NAS), and the Brunel Mood Scale (BRUMS). The analysis plan was conducted through descriptive statistics (mean, standard deviation, median, 1st and 3rd quartiles, interquartile range, and 95% confidence intervals) and inferential statistics (Spearman’s Correlation and Kruskal–Wallis Test). In all tests, the significance level adopted was p < 0.05. Results: The sample was divided into three groups of susceptibility to exercise dependence: low (37.6%), moderate (36.4%), and high (26%). Scores indicative of greater susceptibility to exercise dependence showed positive correlations with running practice volume (years of experience, weekly training frequency, weekly training duration, and weekly mileage), as well as with vigor. Although a statistically significant correlation was also observed for tension, its magnitude was trivial (rs = 0.080). Comparisons using the Kruskal–Wallis test showed that higher susceptibility levels were associated with greater running volumes and higher raw vigor scores, whereas no significant group differences were observed for the remaining mood states. Conclusions: Higher susceptibility to exercise dependence was associated with greater running volume and higher raw vigor scores. No consistent associations were observed with negative mood states, except for a trivial correlation with tension. These findings suggest that greater susceptibility to exercise dependence among runners was primarily associated with higher raw vigor scores rather than with broader alterations in mood states. Full article

To address the complexities associated with highly nonlinear phase transitions in subbase materials subjected to unidirectional freezing—where direct observation of internal states is challenging—and the limitations of conventional numerical methods in concurrently reconstructing multiphysical fields from sparse experimental data, this study investigates saturated subbase materials from the Dashixia Project. Laboratory freezing experiments were performed, and a two-dimensional axisymmetric physics-informed neural network (PINN) model integrating thermomechanical behavior, phase transition, and deformation was developed. The model incorporated the heat conduction equation (accounting for latent heat), the freezing fraction relaxation equation, and the effective deformation equation into the loss function, employing a continuous freezing fraction to represent phase-change phenomena. Additionally, constraints on the average displacement of the top surface, enhanced sampling near the freezing front, and a dynamic weighting strategy were introduced to improve model performance. This approach enabled the simultaneous prediction of temperature, freezing fraction, and displacement fields. The model achieved a temperature prediction root mean square error (RMSE) of 4.112 °C with an R² of 0.600, and a top-surface displacement prediction RMSE of 0.0051 with an R² of 0.993. Observations indicated that the freezing front predominantly progressed from the top downward, while the displacement field exhibited a partitioned pattern characterized by negative displacement in the lower region and positive displacement in the upper region. The proposed methodology offers a novel framework for multi-field reconstruction and frost heave prediction in subgrade materials under conditions of limited observational data. Full article

The solid-state landscape of pharmaceutical compounds is often characterized by the occurrence of polymorphs, hydrates, and solvates, which may significantly influence their physicochemical and biopharmaceutical properties. In contrast, some active pharmaceutical ingredients exhibit a remarkable resistance to crystal form diversification, despite extensive experimental investigation. In the present work, vinpocetine was subjected to an extensive solid-form screening campaign aimed at exploring its propensity to generate alternative polymorphs, hydrates, and solvates. Mechanochemical experiments were performed under neat grinding and liquid-assisted grinding conditions using a broad range of organic solvents and water, including two-step milling procedures and formulations containing surfactants. Additional investigations included high-energy planetary milling, high-pressure compaction, exposure to controlled humidity, thermal cycling, slurry-bridging experiments in various media, and crystallization after mechanochemical neutralization of vinpocetine salts. The resulting solids were systematically characterized by powder X-ray diffraction, and thermal and morphological analyses. In all cases, the recovered solid corresponded to the commercially available crystalline form of vinpocetine, with no evidence of alternative polymorphs, solvates, or hydrates. These results demonstrate the unusual robustness of vinpocetine crystal structure across a wide range of mechanical, thermal, and solvent-mediated conditions. Notably, this behavior contrasts with the well-established ability of vinpocetine to form numerous salts and salt cocrystals, suggesting that solid-state diversification in this compound is primarily driven by proton-transfer processes rather than by neutral polymorphism or solvent incorporation. The present study provides experimentally defined boundaries for the solid-state landscape of vinpocetine and contributes valuable data for future crystal-form prediction and pharmaceutical development studies. Beyond the specific findings reported herein, the systematic documentation of both successful and unsuccessful experimental outcomes represents a valuable source of experimentally validated positive and negative data that may support the future development and validation of AI-assisted crystal-form prediction tools. Full article

This paper conducts a comprehensive empirical evaluation of macroeconomic outcomes under two competing policy paradigms that have governed the United States since the end of World War II: the Keynesian-inflected New Deal Order (1946–1980), rooted in John Maynard Keynes’s theory of aggregate demand management, and the Neoliberal Order (1981–2024), shaped by the price mechanism epistemics of Friedrich A. Hayek and the monetarist counter-revolution of Milton Friedman. Drawing on the historiographical frameworks we operationalize the 1981 policy transition as a natural experiment and apply a fourteen-component analytical pipeline to an annual panel of fifteen Federal Reserve Economic Data (FRED) series spanning 1946–2024. Our methods include: Pruned Exact Linear Time (PELT) structural break detection; normality-adaptive hypothesis testing with Cohen’s d effect sizes; Principal Component Analysis (PCA); a gradient-boosted XGBoost classifier with SHAP interpretability; static and rolling Phillips curve estimation; bootstrapped fiscal multiplier analysis using the corrected Federal Surplus/Deficit ratio; Composite Macroeconomic Performance Index (CMPI) construction; Pearson correlation structure comparison; regime-stratified Okun’s Law analysis; real federal fund rate and yield curve decomposition; M2 velocity and monetary transmission analysis; k-means sub-period temporal clustering; and government debt trajectory with decade-level performance benchmarking. The Keynesian era produced significantly higher mean real GDP growth (3.7% vs. 2.7%), lower structural unemployment (5.0% vs. 6.2%), and a functioning Phillips curve trade-off that collapsed entirely under neoliberalism ($\widehat{\beta }\approx 0$, $p=0.94$). The real federal fund rate averaged negative under the Keynesian regime and turned persistently positive after the Volcker shock. M2 velocity declined sharply in the neoliberal era, refuting the stable quantity theory link central to monetarist policy prescriptions. Temporal clustering recovers five distinct macroeconomic epochs that only partially align with the 1981 historiographical boundary, revealing substantial heterogeneity within each broad regime. The Reagan-era debt expansion, made visible by the corrected debt/GDP trajectory, constitutes a striking empirical contradiction to neoliberal fiscal rhetoric. Together, these results support the interpretation that the two policy regimes represent genuinely distinct macroeconomic equilibria with persistent and measurable consequences for growth, employment, price stability, monetary transmission, and fiscal sustainability. A battery of robustness checks addressing confounding structural shocks, alternative regime boundaries, policy endogeneity, model complexity, and index-construction sensitivity confirms that the core findings are not artifacts of the 1981 periodization, and a cluster-validity analysis formally supports a five-epoch, rather than strictly binary, characterization of the postwar policy landscape. Full article

Food insecurity remains a structural impediment to rural welfare in sub-Saharan Africa (SSA), with smallholder farming households in northern Nigeria among the most severely affected. This study examined the socioeconomic determinants of food security among farming households in Kano State, Nigeria, with emphasis on the role of institutional credit access, using the Food Consumption Score (FCS) methodology. Data were collected through semi-structured face-to-face interviews using multi-stage cluster sampling and analyzed using descriptive statistics, chi-square analysis, one-way ANOVA, and multiple linear regression. Slightly fewer than half of the sampled households met the food-secure threshold, and food security status was significantly associated with the level of access to institutional credit, with a noticeable gap in food security status between high-access and no-access households. Multiple regression confirmed that access to institutional credit, farming experience, and farm size were significant and positive determinants of food security, while household size was a significant negative determinant. These findings demonstrate that institutional credit is an important, policy-actionable pillar of rural food security in Kano State Nigeria, best pursued alongside corresponding investments in farmer experience-transfer, land access, and household welfare. Full article

Research has demonstrated the intergenerational effects of parents’ adverse and positive experiences. Despite growth in the literature, previous reviews have primarily focused on the intergenerational effects of parents’ childhood experiences. This scoping review aimed to characterize the intergenerational research on the associations between parental adverse and positive experiences across the life course (including childhood and adulthood) and the developmental, psychological and behavioral outcomes of their offspring. Following a search of ten databases, seven articles met the inclusion criteria. The majority of studies were cross-sectional (n = 4) and published in the United States (n = 6). Female caregivers dominated the data set (84.6%), with the large majority having a sample size above n = 1000. All studies reported a significant association between parent adversity and negative offspring outcomes; however, mixed findings were found for the protective properties of parents’ positive experiences. Findings indicate a need for further exploration, underscoring the importance of adequately powered studies inclusive and diverse in nature. Full article

Ultra-wideband (UWB) localization is widely used in indoor positioning because it provides high temporal resolution and direct geometric range constraints. In complex indoor environments, however, UWB ranging is affected by non-line-of-sight propagation, multipath reflection, heterogeneous measurement quality, and link-dependent persistent bias, producing long-tailed errors and trajectory drift. This paper proposes HBR-PGD, a heteroscedastic bias-robust projected gradient descent framework for UWB-only indoor localization. Its central idea is a role-separated error-source formulation that assigns packet-level quality degradation, anchor-channel persistent bias, and sparse instantaneous NLOS anomalies to different roles in a unified constrained residual model. Packet-level quality features are mapped to heteroscedastic uncertainty scales, robust loss shape parameters, and non-negative NLOS correction priors; anchor-channel soft gating limits residual-correction freedom; and target trajectories and bounded structural bias states are jointly estimated in overlapping sliding windows. Experiments on a public indoor UWB dataset show that HBR-PGD achieves RMSE values of 0.107 m, 0.068 m, and 0.204 m in residential-apartment, small-apartment, and workshop/industrial environments, respectively. Compared with WLS, MCC-VC-TOA, SR-MCC, and AR-PNN, HBR-PGD consistently improves overall accuracy and high-percentile robustness, with the largest gain in the workshop/industrial environment. Ablation results verify the contributions of heteroscedastic weighting, structural-bias estimation, gated correction, and information-weighted fusion. These results suggest that HBR-PGD is a practical UWB-only localization framework for complex indoor environments with heterogeneous measurement quality, persistent link bias, and sparse NLOS anomalies. Full article

Background/Objectives: Many HIV-positive (HIV+) males receiving highly active antiretroviral therapy (HAART) experience metabolic complications, including non-alcoholic fatty liver disease (NAFLD); lipodystrophy; and intestinal dysbiosis, often characterized by a Prevotella-rich enterotype. Gut microbial fermentation produces short-chain fatty acids (SCFAs), which play important roles in host metabolism. This study investigated the relationships among HAART, anthropometrics, diet, intestinal permeability, gut microbiota composition, and lipodystrophy in HIV+ males. Methods: Forty males aged 23–60 years were enrolled, including 19 HIV+ participants recruited from the East Tennessee State University (ETSU) Health Infectious Diseases Specialty Clinic and 20 HIV-negative (HIV−) controls recruited through standard methods. Participants provided a stool sample for 16S rRNA gene sequencing, SCFA analysis by gas chromatography, and proximate analysis, and completed a food frequency questionnaire. Lipodystrophy-related measures included body mass index (BMI), hip-to-waist ratio (H:W), and liver health assessment using FibroScan. Blood samples were collected by venipuncture. Serum markers of intestinal permeability, including Claudin-21, flagellin, and intestinal fatty acid-binding protein (IFABP), were quantified by enzyme-linked immunosorbent assay (ELISA). Results: HIV+ males exhibited significantly higher H:W ratios (p = 0.001) and hepatic steatosis (p = 0.0047) than HIV− controls (Welsh’s t-test). Concentrations of isobutyrate (p = 0.0024), isovalerate (p = 0.0008), and valerate (p = 0.0329) were elevated in HIV+ participants, whereas butyrate (p = 0.0014) and total acetate/propionate/butyrate (APB) (p = 0.0046) were higher in HIV− males (Welsh’s t-test). HIV+ participants also showed greater abundances of Prevotella and Lachnospiraceae (Analysis of Compositions of Microbiomes; ANCOM). Retrospective analysis revealed that all HIV+ participants were men who have sex with men (MSM). Conclusions: HIV+ males demonstrated distinct gut microbiome profiles, altered SCFA production, and markers of disrupted lipid metabolism. These findings provide a foundation for future investigations of microbiome-metabolism interactions in HIV+ MSM. Full article

The route to wellbeing is often divided into hedonic (pleasure or relaxation) and eudaimonic (meaning or growth) pathways. Positive technology is a growing research area which aims to use technology to facilitate engagement in wellbeing-supporting activities. While virtual reality (VR) is increasingly used to support day-to-day wellbeing, the mechanisms underlying these effects remain unclear and VR research typically determines success based on outcomes. This leaves a gap whereby the processes which facilitate outcomes are less understood. This exploratory study examined the relative effects, on participant emotion responses (N = 35), of hedonic (nature vs. urban setting) and eudaimonic (personally meaningful vs. not personally meaningful) VR environments. Results showed that the level of personal meaning associated with an environment influenced emotion outcomes and visual setting did not. Notably, meaningful environments elicited a “mixed-emotional” state, increasing both positive and negative emotional responses. The results highlight the potential for short, personalised virtual experiences to elicit emotionally complex responses that are theoretically consistent with eudaimonic processes like meaningful reminiscence. Results are discussed in relation to the relative influence of hedonic and eudaimonic stimuli to be explored in future research that builds on these findings. Full article

We present a unifying thesis which posits that the biological resolution of uncertainty is a fundamental adaptation to entropy’s negative impact on the highly ordered molecular structures required to maintain the living state. These molecular biological adaptations are highly conserved and play a critical role in the survival of the earliest multicellular organisms and the vertebrates thereafter. The imperative to reduce cognitive uncertainty is effected through the dopaminergic Medial Forebrain Bundle (MFB) Reward Prediction Error (RPE) mechanism, or its homologous equivalents, to compute a biological valuation of information. This hypothesis is supported by the central role of the MFB seeking system as the neural substrate of exploratory behavior that leads to the reduction of uncertainty when information is apprehended and cognitively assimilated. We define the human experience of intellectual beauty as the subjective emotional reward that is activated by the MFB seeking system. Accordingly, humans experience intellectual beauty when a high-entropy state of confusion is suddenly resolved into a low-entropy state of insight. In humans, the neuroanatomical substrates of inductive reasoning, inquiry, and the intellectual beauty to which they lead are present at birth. What develops postnatally is synaptic plasticity in the connections among these neurons that is activated in the loving didactic relationship that is established between mother and child during infancy. This dynamic is critically dependent on observational learning on the part of the child. It is supported by the joyful engagement and emotional support of the mother. This provides a paradigm of joy in learning that we propose is the developmental origin of intellectual beauty. This is the reinforcement that maintains inquiring behavior in the search for information that is needed to resist the adverse effects of entropy on life. This paper traces the continuous thread of uncertainty resolution from its phylogenetic origins in associative learning to the intuitive science of early childhood, and ultimately to the highest levels of human inquiry in science, as well as literary, musical and visual arts. The intuitive scientific method gives rise to the collective intelligence of groups, an evolved trait that likely contributed to the success of our hominin ancestors. At the societal level, this collective intelligence scales into the institutional working of markets, driving the macroeconomic price discovery of new information to counter entropy. Importantly, we compare the cost of information across the disparate domains of pharmaceutical drug discovery and the contemporary art market to demonstrate that the imperative to reduce uncertainty manifests as a universal, falsifiable mechanism for the “price discovery” of information. Full article

Mobile phone use can distract drivers; however, mobile applications may also improve safety by delivering timely traffic and cooperative intelligent transport system warnings. This pilot study evaluated the user experience of the DARS Traffic Plus (DT+) mobile application and examined simulator sickness and affective burden during its use in a professional driving simulator. Thirty-nine participants were recruited and thirty-three completed all scenarios in a within-subject, counterbalanced design. Following a familiarization scenario, participants completed two comparable driving scenarios: one without DT+ support (S1) and one with DT+ support (S2). User experience was assessed using the User Experience Questionnaire (UEQ), the meCUE 2.0 questionnaire based on the component model of user experience, and a post-interview, while simulator sickness and participant state were measured using the Simulator Sickness Questionnaire (SSQ), Fast Motion Sickness Scale (FMS), and Positive and Negative Affect Schedule (PANAS), complemented by exploratory eye-tracking observations. Both UEQ and meCUE 2.0 indicated positive user experience, with generally higher ratings in scenario S2 using the DT+ mobile application. UEQ showed a significant difference for Perspicuity, and meCUE 2.0 showed significantly higher scores for usefulness, visual aesthetics, commitment, intention to use, product loyalty, and overall evaluation. SSQ and FMS showed that simulator sickness effects occurred in a subset of participants. PANAS revealed no significant change in positive affect, while negative affect decreased significantly by the end of the evaluation. The findings suggest that DT+ was positively experienced in the simulator setting and that combining user experience measures with sickness monitoring is useful in simulator-based evaluation of driving-related mobile applications. Full article

Rapid and reliable landslide mapping from satellite observations is essential for hazard assessment, emergency response, and reservoir-area risk management, yet automatic segmentation remains challenging in mountainous regions because landslide scars are spectrally heterogeneous, terrain-constrained, morphologically irregular, and frequently confused with other exposed surfaces. This study proposes GeoSlide-XMamba, a terrain-conditioned spectral-topographic boundary-aware state-space network for pixel-wise landslide semantic segmentation. The model first separates Sentinel-2 spectral bands and DEM/slope-derived topographic layers into modality-specific branches, integrates them through spectral-topographic adaptive fusion (STAF++), and then performs terrain-conditioned selective state-space scanning in the XMamba bottleneck. Unlike direct token concatenation, the proposed bottleneck uses terrain descriptors to dynamically weight directional selective scan branches so that long-range feature propagation is guided by slope-related morphology. Boundary-aware decoding, signed-distance supervision, and hard-negative mining are further introduced to improve inventory-oriented geometric quality and suppress common false positives. Experiments were conducted on the Landslide4Sense benchmark using 14-channel multispectral-topographic inputs. Among the compared methods, GeoSlide-XMamba achieved the highest validation performance under a unified five-seed protocol, with precision = 0.729, recall = 0.626, F1-score = 0.673, IoU = 0.507, kappa = 0.666, Boundary-F1 = 0.466, and HD95 = 3.45 pixels. Five-seed experiments produced F1 = 0.673 ± 0.003, IoU = 0.507 ± 0.002, Boundary-F1 = 0.466 ± 0.002, and HD95 = 3.45 ± 0.13 pixels, with a 95% CI of [0.670, 0.676] for F1. Relative to the strong 14-channel concatenation baseline, the proposed model improves mean F1 by 0.045 and reduces HD95 by 1.42 pixels. Expanded qualitative inference on Jinsha River patches indicates that the learned spectral-topographic representation transfers plausibly to high-relief reservoir-canyon terrain. These results show that terrain-conditioned state-space modeling can improve both segmentation accuracy and boundary geometry for remote sensing landslide mapping. Full article