Search Results (670)

The Yangtze River Economic Belt is a crucial driver of China’s economy, and its shoreline is a strategic, finite resource vital for ecological security, flood control, navigation, and socioeconomic development. However, intensive development has resulted in functional conflicts and ecological degradation, underscoring the need for accurate identification and suitability assessment of shoreline functions. Conventional methods, which predominantly rely on land use data and remote sensing imagery, are often limited in their ability to capture dynamic changes in large river systems. This study introduces an integrated framework combining macro-level “Three-Zone Space” (urban, agricultural, ecological) theory with micro-level Point of Interest (POI) data to rapidly identify shoreline functions along the Yichang section of the Yangtze River. We further developed a multi-criteria evaluation system incorporating ecological, production, developmental, and risk constraints, utilizing a combined AHP-Entropy weight method to assess suitability. The results reveal a clear upstream-downstream gradient: ecological functions dominate upstream, while agricultural and urban functions increase downstream. POI data enabled refined classification into five functional types, revealing that ecological conservation shorelines are extensively distributed upstream, port and urban development shorelines concentrate in downstream nodal zones, and agricultural production shorelines are widespread yet exhibit a spatial mismatch with suitability scores. The comprehensive evaluation identified high-suitability units, primarily in downstream urban cores with superior development conditions and lower risks, whereas low-suitability units are constrained by high geological hazards and poor infrastructure. These findings provide a scientific basis for differentiated shoreline management strategies. The proposed framework offers a transferable approach for the sustainable planning of major river corridors, offering insights applicable to similar contexts. Full article

The consequences of climate change and increasing anthropogenic pressure pose a growing threat to UNESCO World Heritage sites. Proper identification of environmental factors and their effective mitigation are crucial for preserving historic assets without unnecessary intervening in their material fabric. This article presents excerpts from a study conducted to develop the Master Plan for Preservation for the oldest part of the former Nazi extermination camp Auschwitz II—Birkenau, including non-standard, minimally invasive testing, and the successful implementation of the research findings. Drawing on experience from a multi-year, interdisciplinary research project carried out in close collaboration with the conservation team of the Auschwitz-Birkenau Museum and Memorial, as well as other research projects and surveys conducted in other UNESCO World Heritage sites, the authors critically engage with current standards for the monitoring, protection, and conservation of built cultural heritage. The role of comprehensive identification of different threats—including hydrogeological ones, exacerbated by anthropogenic pressure and climate change—points to the need for a broader approach, especially for the most valuable built-heritage sites that are either increasingly passive recipients of threats generated outside the protected area, or are vulnerable to the extent of standard methodologies for the conservation of cultural sites being no longer applicable. Full article

Objectivity is a fundamental requirement for vortex identification, ensuring that vortex structures observed remain invariant under changes in the reference frame. However, although most conventional vortex identification methods, including Liutex, are Galilean invariant, they are not objective. Since the accelerated motion of the observer does not affect the velocity gradient tensor at an instant of time, the rotational motion is only considered for the non-inertial frame. This paper proposes a method to recover the angular velocity of a rotating observer directly from flow field data measured in the rotating frame. The approach exploits the observation that, in an inertial frame, zero-vorticity points tend to dominate the region with an almost identical nonzero vorticity in the observer’s non-inertial coordinate system. By identifying the most frequently occurring vorticity within the domain, the observer’s angular velocity can be uniquely determined, enabling reconstruction of the objective velocity gradient tensor and, consequently, the objective Liutex. The key issue is to find a reference point (RP). The RP should have zero vorticity in the inertial coordinate system, and then the RP has the same angular speed as the observer. The RP can be found by comparing the vorticity of all points in the computational domain and the RP will correspond to the vorticity vector with the highest percentage in the non-inertial coordinate system. The proposed method is validated using DNS data of the boundary layer transition over a flat plate with an artificially imposed angular velocity. The recovered angular velocity agrees closely with the true value within an acceptable margin of error. Furthermore, the objective Liutex reconstructed from the rotating frame data is visually indistinguishable from the original inertial frame Liutex. These results demonstrate that the method provides a simple and accurate way to restore objectivity for Liutex and other vortex identification techniques. The objective Liutex will be equal to the original Liutex in an inertial coordinate system when the observer does not have rotational motion. Full article

When determining subgroups with heterogeneous treatment effects in cancer clinical trials, the threshold of a variable that defines subgroups is often pre-determined by physicians based on their experience, and the optimality of the threshold is not well studied, particularly when the mixture cure rate model is considered. We propose a mixture cure model that allows optimal subgroups to be estimated for both the time to event for uncured subjects and the cure status. We develop a smoothed maximum likelihood method for the estimation of model parameters. An extensive simulation study shows that the proposed smoothed maximum likelihood method provides accurate estimates. Finally, the proposed mixture cure model is applied to a colon cancer study to evaluate the potential differences in the treatment effect of levamisole plus fluorouracil therapy versus levamisole alone therapy between younger and older patients. The model suggests that the difference in the treatment effect on the time to cancer recurrence for uncured patients is significant between patients younger than 67 and patients older than 67, and the younger patient group benefits more from the combined therapy than the older patient group. Full article

Optimizing energy conversion in photovoltaic (PV) systems is crucial for maximizing energy conversion efficiency and ensuring reliable operation. Achieving this requires that the PV array consistently operates at the Global Maximum Power Point (GMPP). Conventional Maximum Power Point Tracking (MPPT) algorithms, such as Perturb and Observe (P&O) and Incremental Conductance (INC), perform effectively under uniform irradiance but fail to track the GMPP under partial shading conditions (PSCs), resulting in energy losses and degraded system efficiency. To overcome this limitation, this paper proposes a hybrid MPPT method that integrates the Crayfish Optimization Algorithm (COA), a bio-inspired metaheuristic, with the P&O technique. The proposed approach combines the global exploration ability of COA with the fast convergence of P&O to ensure accurate and stable GMPP identification. The algorithm is validated under multiple irradiance patterns and benchmarked against established MPPT methods, including voltage-source and current-source region detection, Improved Variable Step Perturb and Observe and Global Scanning (VSPO&GS), and a hybrid Particle Swarm Optimization (PSO)-P&O method. Simulation studies performed in MATLAB/Simulink demonstrate that the proposed technique achieves higher accuracy, faster convergence, and enhanced robustness under PSCs. Results show that the proposed method reliably identifies the global peak, limits steady-state oscillations to below 1%, restricts maximum overshoot to 0.5%, and achieves the fastest settling time, stabilizing at the new power point significantly faster following major step changes, thereby enhancing overall PV system performance. Full article

Accurate species identification in blackberries (Rubus spp.) is difficult because of morphological similarity and frequent hybridization. We studied 56 wild accessions from the Sirius Federal Territory (Russia), representing coastal and foothill ecosystems of the Black Sea region. Multilocus DNA barcoding with the plastid rbcL gene and nuclear ITS1 and ITS2 regions revealed signals of hybridization and hidden diversity. The rbcL marker showed low variation, grouping most accessions into two clusters with several singletons, which limited its use for distinguishing species. In contrast, ITS1 and ITS2 showed higher variation, forming six clusters and eight singletons, and allowed for clear separation of taxa such as Rubus caesius L., R. irritans Focke, and R. amabilis Focke. Accession 3 carried a raspberry (closely to R. corchorifolius L.fil) plastid haplotype, pointing to a hybrid origin. We also found groups of nearby plants with identical mutations, which likely reflect clonal spread with fixed somatic changes or the persistence of recent hybrid lineages. At the same time, accessions collected up to 140 km apart did not form separate clusters, showing weak geographic structuring along the coast. The results demonstrate that multilocus barcoding can reveal not only species boundaries but also evolutionary processes among Rubus such as hybridization, clonal propagation, and early stages of speciation. Full article

Chronic kidney disease (CKD) affects nearly 850 million people worldwide, and most patients with kidney failure are treated with kidney replacement therapy. Despite technological progress, venous congestion remains a major determinant of morbidity and mortality, and is often underdetected by conventional tools such as clinical evaluation, weight changes, blood pressure measurement, or bioimpedance. Point-of-care ultrasonography (PoCUS) has transformed this diagnostic landscape by providing real-time, physiology-based insights into both left- and right-sided filling pressures. In dialysis care, multiple or confluent B-lines and subtle pleural irregularities suggest elevated pulmonary capillary wedge pressure, while a dilated inferior vena cava (IVC) with reduced collapsibility and increased portal vein pulsatility indicate elevated right atrial pressures. Integrating these sonographic findings into a multiparametric assessment that also includes clinical assessment, bioimpedance, and biosensor feedback enhances diagnostic sensitivity and refines fluid management. Advanced practice nurses (APNs) trained in PoCUS can perform focused examinations of the lungs, IVC, portal venous system, arteriovenous access, and skeletal muscle, translating ultrasound findings into physiological interpretations that guide individualized ultrafiltration strategies and patient care. Nutritional ultrasound (NUS) further complements congestion assessment by quantifying muscle mass and quality, linking nutritional reserve and functional status with hemodynamic tolerance. The implementation of structured education, competency-based training, and standardized scanning protocols allows nurses to incorporate these techniques safely and reproducibly into daily dialysis workflows. By integrating PoCUS and NUS within interdisciplinary decision-making, nursing practice evolves from procedural to diagnostic, supporting early identification of congestion, protection of vascular access, and detection of malnutrition. This multiparametric, physiology-guided approach exemplifies the concept of precision nursing, where patient evaluation becomes continuous, individualized, and grounded in real-time pathophysiological insight. Full article

The timely identification of rock fractures is crucial in deep subterranean engineering. However, it remains necessary to identify reliable warning indicators and establish effective warning levels. This study introduces the Acoustic Emission Transformer for FRActure Prediction (AET-FRAP) multi-input time series forecasting framework, which employs acoustic emission feature parameters. First, Empirical Mode Decomposition (EMD) combined with Fast Fourier Transform (FFT) is employed to identify and filter periodicities among diverse indicators and select input channels with enhanced informative value, with the aim of predicting cumulative energy. Thereafter, the one-dimensional sequence is transformed into a two-dimensional tensor based on its predominant period via spectral analysis. This is coupled with InceptionNeXt—an efficient multiscale convolution and amplitude spectrum-weighted aggregate—to enhance pattern identification across various timeframes. A secondary criterion is created based on the prediction sequence, employing cosine similarity and kurtosis to collaboratively identify abrupt changes. This transforms single-point threshold detection into robust sequence behavior pattern identification, indicating clearly quantifiable trigger criteria. AET-FRAP exhibits improvements in accuracy relative to long short-term memory (LSTM) on uniaxial compression test data, with R² approaching 1 and reductions in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). It accurately delineates energy accumulation spikes in the pre-fracture period and provides advanced warning. The collaborative thresholds effectively reduce noise-induced false alarms, demonstrating significant stability and engineering significance. Full article

Signs of aging in the upper face arise from multimodal changes in facial anatomy, contributing to concerns such as eyebrow ptosis and forehead lines. While neurotoxin injections are widely used to address these lines, the anatomical variability of the frontalis muscle presents procedural challenges. This retrospective analysis aimed to introduce and preliminarily evaluate a structured injection pattern for forehead treatment, developed with attention to the biomechanics of upper facial musculature. A total of 24 patients (mean age 42.5 ± 9.1 years) treated with a standardized injection scheme using letibotulinumtoxinA were included. All subjects also received concomitant glabellar treatment. The protocol incorporated identification of the line of convergence and targeted injections at defined points to balance elevation, optimize muscular activity, and minimize the risk of eyebrow descent. Forehead line severity was assessed at rest and during animation, and three-dimensional surface imaging was used to quantify vertical skin displacement. At baseline, 79.2% of patients presented with severe dynamic forehead lines, and 29.1% exhibited severe static lines. After two weeks, 62.5% showed no dynamic lines and 41.7% showed no static lines. All subjects demonstrated a ≥1-point improvement in dynamic line severity, with 87.5% achieving a ≥2-point improvement. For static lines, 95.8% achieved a ≥1-point improvement and 20.8% showed a ≥2-point improvement after two weeks. The mean dosage was 17.8 ± 0.7 U. Two patients (8.3%) required a touch-up, and no adverse events were observed. These findings suggest that this structured injection approach may offer a consistent method for addressing forehead lines; however, the results should be interpreted within the limitations of a small, uncontrolled retrospective series. Prospective controlled studies with larger populations are needed to further validate the technique. Full article

In hyperspectral images, ghost image residuals exceeding a certain threshold not only reduce the recognition accuracy of the imaging detection system but also decrease the target identification rate. Ghost image residuals affect both the recognition accuracy of the detection system and the accuracy of spectral calibration, thereby influencing qualitative and quantitative inversion. Conventional ghost image residual correction methods can significantly affect both the relative and absolute calibration accuracy of hyperspectral images. To minimize the impact on spectral calibration accuracy during ghost image residual correction, we propose a ghost image degradation model and an iterative optimization algorithm. In the proposed approach, a ghost image residual degradation model is constructed based on the point spread function (PSF) of ghost image residuals and their energy distribution characteristics. Using the proportion of ghost image residuals and the accuracy of hyperspectral image calibration as constraints, we iteratively optimized typical regional target ghost image residuals across different spectral channels, achieving automated correction of ghost image residuals in various spectral bands. The experimental results show that the energy proportion of ghost image residuals at different wavelengths decreased from 4.6% to 0.3%, the variations in spectral curves before and after correction were less than 0.8%, and the change in absolute radiometric calibration accuracy was below 0.06%. Full article

Spatial distribution similarity analysis has extensive application value in multiple domains including geographic information science, urban planning, and engineering site selection. However, traditional regional similarity analysis methods face three key challenges: high sensitivity to directional changes, limitations in feature interpretability, and insufficient adaptability to multi-type data. Addressing these issues, this paper proposes a rotation-invariant spatial distribution similarity analysis method based on ring vectors. This method comprises three stages. First, the traversal starting point of the ring vector is dynamically selected based on the maximum value point of the regional feature matrix. Next, concentric ring features are extracted according to this starting point to achieve multi-scale characterization. Finally, the bidirectional weighted comprehensive distance of ring vectors between regions is calculated to measure the similarity between regions. Three experimental sets verified the method’s effectiveness in terrain matching, engineering site selection, and urban functional area identification. These results confirm its rotational invariance, feature interpretability, and adaptability to multi-type data. This research provides a new technical approach for spatial distribution similarity analysis, with significant theoretical and practical implications for geographic information science, urban planning, and engineering site selection. Full article

Dynamic developmental states of follicles are regarded to be determinants of sexual maturation in fish ovaries. However, it is still a challenge to identify the critical points at which the developmental processes of different types of follicles interact and affect the ovarian development. In this study, four subtypes of the primary follicle (PF) in the ovarian folliculogenesis of zebrafish, i.e., the so-called PF-i, PF-ii, PF-iii, and PF-iv, are first identified by discontinuous NaCl-Percoll gradient centrifugation, as well as their respective morphological features. Then, for the four subtypes of PFs, stage-specific comparative analysis is employed to identify the differentially expressed genes and the differentially methylated regions, which have been validated to be significantly enriched in biological processes encompassing ribosomal biogenesis, meiotic progression, transcriptional regulation, and mitochondrial respiration. Results from transcriptional analysis further demonstrate significant changes in the expression profiles at different developmental stages from the PF-ii to the PF-iii. By molecular biology identification, it is shown that the enhancement of Notch and mTOR pathways can significantly regulate the ovarian development through the pacing effect of primary follicles. Clearly, all these uncovered results could provide a deeper understanding of the initial regulation of ovarian maturation, as well as a new multidisciplinary analytic tool to study follicle candidate regulators in the developmental process of other fish. Full article

Freshwater ecosystems are undergoing rapid species loss due to climate change and human impact. In this context, biomonitoring has become essential for species censusing and biodiversity conservation. In recent years, environmental DNA (eDNA) metabarcoding has emerged as a powerful, non-invasive alternative to traditional sampling and morphological identification methods. This study is the first to apply eDNA analysis to the characterization of invertebrate communities in the Oreto River, Sicily (Italy). Water samples were collected at three points of the river (upstream, midstream, downstream), and eDNA was extracted for metabarcoding. Overall, the analysis identified 40 species belonging to different phyla, including Annelida, Arthropoda, Cnidaria, Mollusca, Porifera and Rotifera. Twelve species appear to be newly recorded in Sicily, including confirmed identifications (Simulium trifasciatum, Rotaria rotatoria, Euchlanis dilatata, Lecane clostero-cerca) and other potential new identifications (Microchironomus tener, Micropsectra pallidula, Tinodes dives, Philodina flaviceps, Buchholzia appendiculata, Lecane bulla, Drosophila incompta, Corynoneura coronata). The study also confirmed the presence of alien species (Physella acuta, Craspedacusta sowerbii). Furthermore, species composition varied among the three sampling points, with most taxa detected in the upstream section. These results provide a preliminary snapshot of the biodiversity of river invertebrates, highlighting the potential of eDNA to complement traditional methods. Full article

Terrestrial water storage includes soil water storage, groundwater storage, surface water storage, snow water equivalent, plant canopy water storage, biological water storage, etc., which can comprehensively reflect the total change in water volume during processes such as precipitation, evapotranspiration, runoff, and human water use in the basin hydrological cycle. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a powerful tool and a new approach for observing changes in terrestrial water storage and groundwater storage. The North China Plain (NCP) is a major agricultural region in the northern arid area of China, and long-term overexploitation of groundwater has led to increasingly prominent ecological vulnerability issues. This study uses GRACE and Global Land Data Assimilation System (GLDAS) hydrological model data to assess the spatiotemporal patterns of groundwater drought in the NCP and its various sub-regions from 2003 to 2022, identify the locations, occurrence probabilities, and confidence intervals of seasonal and trend mutation points, quantify the complex interactive effects of multiple climate factors on groundwater drought, and reveal the propagation time from groundwater drought to agricultural drought. The results show that: (1) from 2003 to 2022, the linear tendency rate of groundwater drought index (GDI) was −0.035 per 10 years, indicating that groundwater drought showed a gradually worsening trend during the study period; (2) on an annual scale, the most severe groundwater drought occurred in 2021 (GDI = −1.59). In that year, the monthly average GDI in the NCP ranged from −0.58 to −2.78, and the groundwater drought was most severe in July (GDI = −2.02); (3) based on partial wavelet coherence, the best univariate, bivariate for groundwater drought were soil moisture (PASC = 19.13%); and (4) in Beijing, Tianjin and Hebei, the propagation time was mainly concentrated in 1–5 months, with average lag times of 2.87, 3.20, and 2.92 months, respectively. This study can not only reduce and mitigate the harm of groundwater drought to agricultural production, social life, and ecosystems by monitoring changes in groundwater storage, but also provide a reference for the quantitative identification of the dominant factors of groundwater drought. Full article

Cancer remains a leading cause of mortality worldwide. Chemotherapy is effective but can cause febrile neutropenia, deplete neutrophils, and increase infection risk. Although timely fever detection is critical to prevent complications, periodic temperature monitoring has inherent limitations. Wearable devices (WDs) for real-time body temperature (RBT) monitoring are emerging as tools for early fever detection, though their clinical feasibility and usability remain unverified. This study assessed the clinical feasibility of a novel WD by comparing its temperature concordance and fever detection capability against a standard reference in patients with cancer. The RBT system’s clinical maturity, including its capacity for early fever detection and monitoring treatment-related changes, was evaluated. Furthermore, satisfaction among clinicians and patients was analyzed in a hospital setting. In this prospective study, patients with hematologic malignancies at high infection risk admitted to the Chonnam National University in Hwasun Hospital, South Korea, were enrolled. Data from 47 patients were analyzed to compare MT100D as WD (SEERS Technology Co., Ltd., South Korea) readings with axillary thermometers. Temperature concordance was evaluated using the intraclass correlation coefficient (ICC), and diagnostic performance was compared with the reference thermometer. The early fever detection performance of the MT100D was analyzed to evaluate the clinical effectiveness of the early response system. Usability was evaluated through a five-point Likert scale survey completed by clinical nurses. The MT100D demonstrated good agreement with the reference thermometer (mean difference: −0.19 ± 0.35 °C; ICC: 0.78). The RBT system achieved sensitivity, specificity, and area under the receiver operating characteristic curve values of 81.50%, 96.32%, and 96.60%, respectively. The early fever detection rate was 77.1%, with the RBT system detecting fever an average of 1.13 ± 1.28 h earlier than the reference. Usability and satisfaction assessments showed high patient satisfaction (mean 4.69 ± 0.5; range 4.57–4.80) and moderate clinician satisfaction (mean 3.63 ± 0.75; range 2.89–4.11). Among patients with cancer, including those at risk of febrile neutropenia, the MT100D demonstrated strong concordance with standard thermometry, enabling early fever detection. The RBT system shows promise for the early identification of neutropenic risk during chemotherapy. Full article