Search Results (82)

Scene text detection aims to accurately localize text instances in images captured under complex environments. Its performance depends heavily on precise text boundary delineation and reliable semantic discrimination from cluttered backgrounds. However, existing methods still struggle in such complex scenes. Repeated downsampling gradually biases features toward low-frequency components, thereby weakening edge details and local structures that are critical to text morphology. Additionally, semantic information and local details are often modeled independently. This lack of coordination makes high-frequency responses vulnerable to background noise. To address these issues, we propose HFI-Former, a Transformer-based model designed for high-frequency enhancement and feature interaction. The framework consists of multi-scale feature extraction, frequency-enhanced representation, semantic-guided feature interaction, and deformable Transformer encoding. Frequency-domain enhancement is introduced to preserve high-frequency structural features degraded by repeated downsampling. Semantic-aware feature interaction further injects global context to regulate multi-scale feature fusion. Experiments on CTW1500, Total-Text and ICDAR1500 demonstrate competitive boundary localization accuracy and strong overall detection performance in complex scenes. Full article

Background/Objectives: Hereditary fructose intolerance (HFI) is an inherited metabolic disorder caused by a deficiency of the enzyme fructose-1,6-bisphosphate aldolase. Treatment consists of a lifelong diet restricted in fructose, sucrose, and sorbitol (FSS). The aim of this study was to determine dietary intake of FSS and to analyze the consumption patterns of vegetables, fruit, legumes, pulses, and dried fruit in a nationwide cohort of HFI patients. Methods: Overall, 36 HFI patients and 28 age-, sex- and BMI-matched healthy control subjects participated in this study. A self-administered three-day dietary record and an adapted quantitative food frequency questionnaire (FFQ) including frequency and portion sizes were collected. FSS intake was calculated using the DIAL Nutritional Calculation Program (ALCE INGENIERÍA). Total fructose intake was calculated as the sum of free fructose, 50% of sucrose, and sorbitol. Results: Protein intake was significantly higher in HFI patients compared to the controls (92.43 g/day [65.1–165.03] vs. 70.39 g/day [35.21–133.83]; p = 0.001). In most patients, total fructose intake was within the recommended limits (9.79 mg/kg bw/day [0.29–59.09]), with no significant differences between children and adults (p = 0.325). Although the established dietary recommendations did not always match the actual intake observed in a real-life setting, in general, foods with higher fructose content were consumed less frequently and in smaller quantities. Conclusions: Further research on the fructose content of various foods, particularly fruits and vegetables, and updated dietary recommendations for HFI patients are warranted to provide the best tools for the nutritional management of the disease. Full article

Background: Household food insecurity (HFI) adversely affects child development by restricting caloric intake, dietary diversity, and food quality. Since diet is a key factor influencing the gut microbiome, HFI may negatively impact health by altering microbial communities. However, direct evidence linking HFI to changes in the gut microbiome is limited. Therefore, we investigated the effects of HFI as a composite variable and used individual HFI assessment questions as specific proxies for dietary deprivation on the gut microbiome in a group of Ethiopian schoolchildren. Methods: Fecal samples were collected from 57 school-aged children in Ethiopia, and microbial profiles were established using 16S rRNA amplicon paired-end sequencing. Food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS). Results: We observed no significant differences in alpha diversity across food security status (Wilcoxon p > 0.05). However, beta diversity analysis revealed a significant shift in microbiome composition between food-secure and food-insecure individuals (Bray–Curtis dissimilarity; PERMANOVA, p < 0.05). Further analyses of individual HFIAS questions as specific proxies for dietary deprivation showed that limited dietary variety, consumption of disliked foods, and reduced meal size were each associated with significant changes in microbial compositions (PERMANOVA; all q < 0.05). Differential abundance analyses consistently identified Sutterella as significantly more abundant among food-insecure participants (composite model q = 0.11; component-specific models q < 0.05). Additionally, a microbial feature-based machine learning model accurately predicted food security status (AUC = 0.81), with Sutterella emerging as the top predictive feature. Conclusions: Our findings suggest that food insecurity metrics are associated with alterations in gut microbial composition. The consistent enrichment of Sutterella in food-insecure children in this study suggests the need for future mechanistic studies to explore its role in mediating the effects of food insecurity. Full article

This paper presents a comprehensive sensorless control approach for interior permanent magnet (IPM) motors, integrating high-frequency injection (HFI) and model-based observer techniques to ensure accurate rotor position estimation across a wide speed range. Two HFI strategies—pulsating and rotating—are investigated experimentally and compared in combination with two observer structures: the conventional Sliding Mode Observer (SMO) and Adaptive-Gain SMO (AG-SMO). The AG-SMO dynamically adjusts its observer gain according to the estimated back-electromotive force (back-EMF) amplitude, significantly reducing chattering and improving estimation performance under varying load and noise conditions. A Frequency-Adaptive Complex Coefficient Filter (FACCF) and an Orthogonal Phase-Locked Loop (PLL) are incorporated to eliminate phase delay and enhance demodulation accuracy. Simulation and experimental results obtained using a 30 W, 20 V IPM motor demonstrate that the pulsating HFI + AG-SMO configuration achieves superior stability and noise immunity, while the rotating HFI + AG-SMO provides smoother and more accurate estimation. Overall, the proposed hybrid control framework achieves robust, high-precision, and sensorless operation for IPM motors over the wide speed range, offering a practical solution for applications such as inverter-driven compressor systems operating in noisy environments. Full article

Over recent decades, planners in the U.S. have increasingly adopted mixed-use projects to reduce automobile dependency and strengthen local community identity, although results remain inconsistent across cities. Urban health and fitness outcomes are shaped by complex interactions between the built environment, socioeconomic factors, and demographic characteristics. This study introduces a Health and Fitness Index (HFI) for 28,758 U.S. ZIP codes, derived from normalized measures of walkability, healthcare facility density, and carbon emissions, to assess spatial disparities in health-supportive environments. Using four modeling approaches—lasso regression, multiple linear regression, decision trees, and k-nearest neighbor classifiers—we evaluated the predictive importance of 15 urban and socioeconomic variables. Multiple linear regression produced the strongest generalization performance (R² = 0.60, RMSE = 0.04). Key positive predictors included occupied housing units, business density, land-use mix, household income, and racial diversity, while income inequality and population density were negatively associated with health outcomes. This study evaluates five statistical formulations (Metropolis Hybrid Models) that incorporate different combinations of walkability, land-use mix, environmental variables, and socioeconomic indicators to test whether relationships between urban form and socioeconomic conditions remain consistent under different variable combinations. In cross-sectional multivariate regression, although mixed-use development in high-density areas is strongly associated with healthcare facilities, these areas tend to serve younger and more racially diverse populations. Decision tree feature importance rankings and clustering profiles highlight structural inequalities across regions, suggesting that enhancing business diversity, land-use integration, and income equity could significantly improve health-supportive urban design. This research provides a data-driven framework for urban planners to identify underserved neighborhoods and develop targeted interventions that promote walkability, accessibility to health infrastructure, and sustainability. It contributes to the growing literature on urban health analytics, integrating machine learning, spatial clustering, and multidimensional urban indicators to advance equitable and resilient city planning. Full article

Triarylmethyl radicals (TAMs) have recently emerged as highly effective polarizing agents in dynamic nuclear polarization (DNP) under viscous conditions, enabling substantial hyperpolarization via the solid-effect (SE) DNP mechanism even at room temperature. A comparable, though less pronounced, enhancement was observed for BDPA radicals embedded in phosphocholine-based lipid bilayers. Given the increasing interest in elucidating the structure and dynamics of biopolymers and their high-molecular-weight assemblies—such as cell membranes—this study focuses on the design, synthesis, and characterization of paramagnetic agents tailored for DNP-based structural biology. To this end, we synthesized a series of TAM derivatives functionalized with lipophilic substituents and characterized their magnetic resonance properties, including isotropic hyperfine interaction (HFI) constants on carbon nuclei and electron spin relaxation times (T₁ and T_m) at low temperatures (80 K). Echo-detected EPR spectra and electron spin echo envelope modulations (ESEEM) were recorded for novel TAM incorporated into liposomes composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC). These low-temperature measurements revealed that the radicals are localized either at the liposome surface or within the lipid bilayer, ensuring optimal accessibility to water molecules. Crucially, the presence of a single cholesterol moiety provides strong noncovalent anchoring within the hydrophobic core of the bilayer. Guided by these findings, we identify an amphiphilic TAM bearing a single cholesterol group and polar carboxyl functionalities as a highly promising candidate for DNP applications in membrane biology, combining efficient polarization transfer, bilayer integration, and aqueous accessibility. Full article

The integrity of real-time monitoring data is paramount to the accuracy of scientific research and the reliability of decision-making. However, data incompleteness arising from transmission interruptions or extreme weather disrupting equipment operations severely compromises the validity of statistical analyses and the stability of modelling. From a mathematical view, real-time monitoring data may be regarded as continuous functions, exhibiting intricate correlations and mutual influences between different indicators. Leveraging their inherent smoothness and interdependencies enables high-precision data imputation. Within the functional data analysis framework, this paper proposes a Diversity Constraint and Adaptive Graph Multi-View Functional Matrix Completion (DCAGMFMC) method. Integrating multi-view learning with an adaptive graph strategy, this approach comprehensively accounts for complex correlations between data from different views while extracting differential information across views, thereby enhancing information utilization and imputation accuracy. Random simulation experiments demonstrate that the DCAGMFMC method exhibits significant imputation advantages over classical methods such as KNN, HFI, SFI, MVNFMC, and GRMFMC. Furthermore, practical applications on meteorological datasets reveal that, compared to these imputation methods, the root mean square error (RMSE), mean absolute error (MAE), and normalized root mean square error (NRMSE) of the DCAGMVNFMC method decreased by an average of 39.11% to 59.15%, 54.50% to 71.97%, and 43.96% to 63.70%, respectively. It also demonstrated stable imputation performance across various meteorological indicators and missing data rates, exhibiting good adaptability and practical value. Full article

Global climate change is accelerating and human pressures are intensifying, exerting profound impacts on biodiversity and ecosystem service functions. The accurate prediction of species distributions has thus become a critical research direction in ecological conservation and restoration. This study selected Puccinellia tenuiflora, a species distributed across China, as its research subject. Utilizing 169 occurrence records and 10 environmental variables, we applied a parameter-optimized MaxEnt model to simulate the species’ current and future (2050s–2090s) potential suitable habitats under the SSP126, SSP370, and SSP585 scenarios. The results identified the human footprint index (HFI, 43.3%) and temperature seasonality (Bio4, 26.9%) as the dominant factors influencing its distribution. The current suitable area is primarily concentrated in northern China, covering approximately 258.26 × 10⁴ km². Under all future scenarios, a contraction of suitable habitat is projected, with the most significant reduction observed under SSP585 by the 2090s (a decrease of 56.2%). The distribution centroid is projected to shift northeastward by up to 145.36 km. This study elucidates the response mechanism of P. tenuiflora distribution to climate change and human activities. The projected habitat contraction and spatial displacement highlight the potential vulnerability of this species to future climate change. These findings, derived from a rigorously optimized and spatially validated model, provide a scientific basis for the conservation, reintroduction, and adaptive management of P. tenuiflora under climate change. Full article

Under the combined influence of global climate change and intensified human activities, ecosystem services (ESs) are undergoing substantial transformations. Identifying their nonlinear driving mechanisms is crucial for promoting regional sustainable development. Taking Anhui Province as a case study, this research evaluates the spatial patterns and temporal dynamics of six key ecosystem services from 2000 to 2020—namely, biodiversity maintenance (BM), carbon fixation (CF), crop production (CP), net primary productivity (NPP), soil retention (SR), and water yield (WY). The InVEST and CASA models were employed to quantify service values, and the XGBoost–SHAP framework was used to reveal the nonlinear response paths and threshold effects of dominant drivers. Results show a distinct “high in the south, low in the north” spatial gradient of ES across Anhui. Regulatory services such as BM, NPP, and WY are concentrated in the southern mountainous areas (high-value zones > 0.7), while CP is prominent in the northern and central agricultural zones (>0.8), indicating a clear spatial complementarity of service types. Over the two-decade period, areas with significant increases in NPP and CP accounted for 50% and 64%, respectively, suggesting notable achievements in ecological restoration and agricultural modernization. CF remained stable across 98.3% of the region, while SR and WY exhibited strong sensitivity to topography and precipitation. Temporal trend analysis indicated that NPP rose from 395.83 in 2000 to 537.59 in 2020; SR increased from 150.02 to 243.28; and CP rose from 203.18 to 283.78, reflecting an overall enhancement in ecosystem productivity and regulatory functions. Driver analysis identified precipitation (PRE) as the most influential factor for most services, while elevation (DEM) was particularly important for CF and NPP. Temperature (TEM) and potential evapotranspiration (PET) affected biomass formation and hydrothermal balance. SHAP analysis revealed key threshold effects, such as the peak positive contribution of PRE to NPP occurring near 1247 mm, and the optimal temperature for BM at approximately 15.5 °C. The human footprint index (HFI) exerted negative impacts on both BM and NPP, highlighting the suppressive effect of intensive anthropogenic disturbances on ecosystem functioning. Anhui’s ES exhibit a trend of multifunctional synergy, governed by the nonlinear coupling of climatic, hydrological, topographic, and anthropogenic drivers. This study provides both a modeling toolkit and quantitative evidence to support ecosystem restoration and service optimization in similar transitional regions. Full article

High-frequency injection (HFI) is widely adopted for the sensorless control of permanent magnet synchronous motors (PMSMs) at low speeds. However, conventional HFI strategies relying on fixed-frequency carrier modulation and square-wave injection concentrate current harmonic energy within narrow spectral bands, thereby inducing pronounced high-frequency motor vibrations and noise. To mitigate this issue, this paper proposes a noise suppression strategy based on synchronized periodic frequency modulation (PFM) of both the carrier and high-frequency square-wave signals. By innovatively synchronizing the periodic modulation of the triangular carrier in space vector pulse width modulation (SVPWM) with the injected high-frequency square wave, harmonic energy dispersion and noise reduction are achieved, substantially lowering peak acoustic emissions. First, the harmonic characteristics of the voltage-source inverter output under symmetric triangular carrier SVPWM are analyzed within a sawtooth-wave PFM framework. Concurrently, a harmonic current model is developed for the high-frequency square-wave injection method, enabling the precise derivation of harmonic components. A frequency-synchronized modulation strategy between the carrier and injection signals is proposed, with a rigorous analysis of its harmonic suppression mechanism. The rotor position is then estimated via high-frequency signal extraction and a normalized phase-locked loop (PLL). Comparative simulations and experiments confirm significant noise peak attenuation compared to conventional methods, while position estimation accuracy remains unaffected. This work provides both theoretical and practical advancements for noise-sensitive sensorless motor control applications. Full article

The complex interaction between nature and human factors has led to frequent forest fires, but their combined effects in different areas remain unclear. Taking the Northeast China forest as the study area, this study integrates structural equation modeling (SEM) and Vine Copula analysis to quantify these drivers over 2001–2022. Results show that 70.42% of forest fires were caused by humans, clustering in populated low-elevation areas. SEM revealed partial correlations of 0.48 (weather conditions) and 0.59 (human activities) with forest fire frequency; canopy moisture was negatively correlated with fire (−0.38). Vine Copula indicated a joint probability of 0.32 between the human footprint index (HFI) and forest fires under high temperatures. This study can provide a framework for region-specific fire management in temperate forests by combining the effects of various influences. Full article

Biodiversity loss is a global environmental concern, mainly driven by human-induced factors, encompassing both direct and indirect drivers. This study investigates the long-term relationship between either the Human Footprint Index (HFI), which measures the extent of human pressures (i.e., direct drivers), or the Gross Domestic Product (GDP), a measure of economic growth (i.e., indirect driver) and biodiversity change, using bird population trends as indicators. The analysis was based on time-series data for Portugal (2004–2023) aggregated at national and sub-national scales, representative of different socio-economic contexts. Multi-species indices were regressed against either the HFI or GDP using Autoregressive Distributed Lag (ARDL) to identify long-run relationships. Bird population trends varied by species group (common, agricultural, and forest birds) and socio-economic context underscoring the importance of sub-national assessments. The HFI and GDP had varying predictive value across species groups and socio-economic contexts, with the HFI showing greater consistency, particularly as a predictor for agricultural birds. While most models showed a negative association between species abundance and either the HFI or GDP, revealing a signal of socio-economic pressures on bird populations at sub-national scales, some models suggested mixed results, indicating that conservation policies must take local contexts into account. Full article

This work involves the development of a hydrodynamic fertilizer injector (HFI), which uses an integrated axial-flow turbine (AFT) and a diaphragm pump to absorb liquid fertilizer. Three structural parameters—the number of impellers (M₁), average number of blades per impeller (M₂), and arrangement pattern (M₃)—are considered, and 12 AFT designs are developed. Using a combination of CFD numerical simulations and hydraulic performance testing, the response of the AFT output power (P), blade negative pressure (NP), and fertilizer injection flow rate (Q_inj) to structural parameters and inlet pressure (H) is investigated. The results show that the normalized root mean square error between the simulated outlet flow rate (Q_s) and the measured flow rate (Q_m) is 5.1%, indicating high accuracy in the grid motion simulation method. P increases first and then decreases with the increase in impeller speed (n). The maximum P (P_max) ranges from 150.1 to 201.4 W. P_max increases with H, decreases with increasing M₁ and M₂, and shows little change with M₃. At H = 0.14 MPa, M₁ and M₂ have a significant influence, and at H ≥ 0.14 MPa, M₁ becomes the most significant factor (p < 0.05). Low-speed flow and negative pressure cavitation zones at the leading edge of the blade suction surface cause flow blockage and affect the lifespan of the AFT. These regions decrease in size as H increases but increase with M₁. The negative pressure (NP) decreases as M₂ increases. When M₁, M₂, and M₃ are 2, 3, and identical (D33), the P_max of the AFT is maximized, increasing by 6.7% to 33.5% compared with those of the other combinations. The Q_inj of D33, D34, D43, and D44 at H = 0.12~0.18 MPa range from 288.6 to 847.3 L/h, which is 38.7% to 461.0% higher than that of domestic and international venturi injectors. When considering cavitation issues and the manufacturing cost of the AFT mold, D44 may be chosen. Although its Q_inj is 7.0% lower than that of D33, NP is reduced by 37.9%. These findings provide a basis for the development of the HFI with AFT as the driving unit. Full article

Background: Household food insecurity (HFI) is a serious public health concern in Lebanon. Adverse mental health issues have been reported among food insecure households in addition to physical and nutritional complications. Caregivers in food insecure families tend to adopt different coping mechanisms to mitigate the effects of food insecurity (FI) on their children. Objective: This cross-sectional observational study aimed to explore the relationship between FI, maternal depression, child malnutrition, and differential coping mechanisms adopted by mothers. Methods: A total of 219 women were enrolled in this study; FI was assessed using the household food insecurity assessment (HFIAS), maternal depression using the patient health questionnaire (PHQ-9), and their children’s nutritional status through recall of anthropometric measurements. Pearson’s correlations and logistic regressions were performed to evaluate the associations between HFI, maternal depression, and children’s nutritional status. Results: A strong positive correlation between HFI and maternal depression (p = 0.001) and children’s nutritional status (p = 0.008) was shown. Logistic regressions revealed that being food secure decreased the risk of maternal depression (OR = 0.328, 95% CI 0.125–0.863, p = 0.024), while it did not predict children’s nutritional status. Eight main themes related to coping mechanisms were identified. Conclusions: This study highlights the understudied relationship between food insecurity and maternal depression, showing an increased prevalence of HFI among residents in Lebanon with a positive correlation with increased maternal depression. Further investigation is warranted to better explore how to mitigate the negative impact of food insecurity on mental health, maternal nutritional needs, and Infant and Young Child Feeding (IYCF) practices in Lebanon. Full article

The comprehensive protection and restoration of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts is critical for enhancing ecological environmental quality and fulfilling the aspirations of ecological civilization in the modern era. Centered on the key project area of the Mountain-River Project within the Luohe River Basin of the Eastern Qinling Mountains, this study employs the InVEST model to assess spatiotemporal variations in habitat quality (HQ), water yield (WY), carbon sequestration (CS), and soil retention (SR) for the years 2000, 2010, and 2020. This study further examines the trade-offs and synergies among these ecosystem services, integrates the Ordered Weighted Averaging (OWA) and GIS methodology with human activity patterns, determines the optimal management scenario, and offers targeted recommendations for optimization. The findings reveal that areas of high habitat quality, carbon sequestration, and soil retention are predominantly concentrated in the western and southwestern regions of the basin, whereas high-value zones of water yield are primarily situated in the southern and southwestern sectors. Habitat quality demonstrates significant synergies with other ecosystem services, whereas water yield presents a notable trade-off with soil retention. By conducting a comparative analysis of protection efficiency, we identified priority conservation areas predominantly located in the southern and southwestern regions of the basin. Moreover, through overlaying the priority conservation zones with the Human Footprint Index (HFI), the priority conservation area was precisely delineated to encompass 5.41 × 10⁵ hectares. This methodology provides critical guidance for the implementation of the Mountain-River Project and offers substantial value in scientifically advancing ecological restoration initiatives. Full article