Distribution Of Scatterers Research Articles

Interferometric phase reconstruction with temporal decorrelation model constraints for time-series InSAR surface deformation monitoring

ABSTRACT The time series interferometric synthetic aperture radar (InSAR) (TSInSAR) is an effective technique for monitoring surface deformation with wide coverage and millimeter accuracy. There are two types of scatterers in the SAR field of view, including the permanent scatterer (PS) and the distributed scatterer (DS). Compared to PS with temporarily stable scattering behavior, the filtered interferometric phases are not consistent for DS susceptible to the decorrelation effect. To overcome the phase inconsistency degradation problem of the decorrelated DSs, the phase linking (PL) theory is introduced to recover the equivalent single-reference (ESR) phases from all interferometric combinations. However, the optimization performance of the PL theory is affected by the uncontrollable estimation error of coherence magnitude. Here, we present a novel enhanced PL (EPL) by incorporating with a priori temporal decorrelation model (TDM) to enhance the weight of the short-term interferograms and suppress the abrupt coherence jump with the long temporal baseline. Real experiment selects the Daguangbao landslide triggered by the ‘5.12’ Wenchuan Mw 7.9 earthquake as the study area to verify the algorithm’s effectiveness. Compared to traditional PL methods, the new EPL method can recover the interferometric phase fringe more clearly and obtain a smoother deformation velocity spatially with higher estimation accuracy.

Mountain Landslide Monitoring Using a DS-InSAR Method Incorporating a Spatio-Temporal Atmospheric Phase Screen Correction Model

The detection of potential rural mountain landslide displacements using time-series interferometric Synthetic Aperture Radar has been challenged by both atmospheric phase screens and decoherence noise. In this study, we propose the use of a combined distributed scatterer (DS) and the Prophet_ZTD-NEF model to rapidly map the landslide surface displacements in Diqing Tibetan Autonomous Prefecture, China. We conducted tests on 28 full-resolution SENTINEL-1A images to validate the effectiveness of our methods. The conclusions are as follows: (1) Under the same sample conditions, confidence interval estimation demonstrated higher performance in identifying SHPs compared to generalized likelihood ratio test. The density of DS points was approximately eight times and five times higher than persistent scatterer interferometry and small baseline subset methods, respectively. (2) The proposed Prophet_ZTD-NEF model considers the spatial and temporal variability properties of tropospheric delays, and the root mean square error of measured values was approximately 1.19 cm instead of 1.58 cm (PZTD-NEF). (3) The proposed Prophet_ZTD-NEF method reduced the mean standard deviation of the corrected interferograms from 1.88 to 1.62 cm and improved the accuracy of the deformation velocity solution by approximately 8.27% compared to Global Position System (GPS) measurements. Finally, we summarized the driving factors contributing to landslide instability.

Magnetotelluric image of the Patagonian slab window: Constraints on upper mantle physical properties and sources of intraplate magmatism

The Patagonian slab window (PSW) is a region of the Southamerican subduction zone where the absence of subducted slabs is interpreted, due to the subduction of the Chile Mid-Ocean Ridge at the Chile Triple Junction. Here we report the results of a long-period magnetotelluric (MT) study conducted in two 300 km-long trench-parallel transects crossing the northern boundary of the PSW in the proximal backarc. We modeled the MT data using 3-D inversion, obtaining an electrical resistivity model of the continental crust and upper mantle up to a depth of ∼150 km. Our model shows a heterogeneous resistivity structure in the uppermost mantle, dominated by resistivities >300 Ωm below the array of sites even within the PSW, and some low-resistivity zones (LRZs, <10 Ωm) mainly at the edge of the array. Using petrophysical models, we estimated the mantle temperature, water content, melt fraction, and viscosity based on obtained resistivity values and a preexistent model of P-wave velocity (Vp) at 50 km and 100 km depth. These estimates suggest that the uppermost mantle within the PSW region is heterogeneous and dominated by high-viscosity blocks, compatible with the continental mantle lithosphere or even subducted slabs. Based on relatively hot and low-viscosity zones estimated in the periphery of LRZs, we interpret the presence of asthenospheric mantle in areas where LRZs coincide with relatively low Vp. According to this interpretation, asthenospheric upwelling in the study area at depths ≤150 km would be localized rather than ubiquitous over the interpreted extent for the PSW. Such localized asthenosphere upwelling processes in the past could explain the scattered distribution of Neogene basaltic lavas in the southern Patagonia backarc. The continental crust exhibits LRZs in the upper and lower crust. Remarkably, ensembles of LRZs at different crustal depths within the presumable area of the PSW were found below the General Carrera Lake, and towards the North Patagonian Icefield, likely indicating the presence of hidden intraplate magmatic and/or hydrothermal systems.

Speciation and diversification of the Bupleurum (Apiaceae) in East Asia.

Bupleurum, belonging to the Apiaceae, is widely distributed across the Eurasian continent. The origin and species diversification of Bupleurum in East Asia, remain incompletely resolved due to the limited samples in previous studies. To address these issues, we have reconstructed a robust phylogenetic framework for Bupleurum in East Asia based on the ITS and three plastid genes. Our phylogenetic analysis confirms the monophyly of Bupleurum with strong support. Both ITS and chloroplast dataset divided the Bupleurum in East Asia into East Asia Group I and East Asia Group II in this study. The divergence time and ancestral area reconstruction of ITS dataset indicated that the Bupleurum originated in the Mediterranean basin and its adjacent areas around 50.33 Ma. subg. Penninervia and subg. Bupleurum diverged at about 44.35 Ma, which may be related to the collision of India with the Eurasian continent. Both East Asia Group I and East Asia Group II originated from a common ancestor in the Mediterranean, East Asia Group I divergence around 12.95 Ma; East Asia Group II divergence around 13.32 Ma. The character reconstruction showed that the morphological characters and altitude distribution analyzed in this study exhibit a scattered distribution in East Asian Group I and East Asian Group II. Additionally, diversification rate analysis shows that the East Asian Group I and East Asian Group II exhibited no significant shifts in diversification rates in the evolutionary history according to ITS and combined dataset. Both molecular and morphological data supports that East Asian Bupleurum is a museum taxon, meaning that the species diversity of East Asian Bupleurum has gradually accumulated over time.

The impact of genetic similarity and environment on the flavonoids variation pattern of Cyclocarya paliurus

The leaves of Cyclocarya paliurus (Batalin) Iljinskaja, an endemic tree with a scattered distribution in subtropical China, are rich in flavonoids with beneficial, health-promoting properties. To understand the impact of environment and genetic similarity on the variation pattern of flavonoids in this species, we analyzed C. paliurus germplasm resources from 26 different populations previously sampled from the main distribution area. Environmental, genetic and biochemical data was associated by genetic structure analysis, non-parametric tests, correlation analysis and principal component analysis. We found that populations with higher flavonoid contents were distributed at higher elevations and latitudes and fell into two groups with similar genetic diversities. Significant accumulations of isoquercitrin and kaempferol 3-O-glucoside were detected in the higher flavonoid-content resources. In addition, the genetic clusters with higher flavonoid contents exhibited broader environmental-adaptive capacities. Even in the presence of environmental factors promoting C. paliurus flavonoid accumulation, only those populations having a specific level of genetic similarity were able to exploit such environments.

Spatio-temporal Situation, Regional Differences, and Dynamic Evolution of the Distribution of Ecological Compensation in the Yellow River Basin

In the context of regional coordinated development and modernization of ecological and environmental governance capacity, the spatial collaborative governance of transboundary river basins has received extensive attention, but the ecological compensation of river basins is faced with the intertwined relationship of rights and responsibilities, and the horizontal ecological compensation mechanism has not yet been perfected. Based on the emergy ecological footprint model, the ecological compensation amount of 90 cities in the Yellow River Basin in 2007-2021 was measured, and the spatiotemporal pattern, regional differences, and dynamic evolution characteristics of distribution were explored by combining exploratory spatial data analysis, Dagum Gini coefficient, kernel density estimation, and spatial Markov chain analysis. The results showed that： ① The spatiotemporal pattern of ecological compensation in the Yellow River Basin was different, the ecological compensation amount decreased slightly in the fluctuation and increased from the northwest to southeast gradient in general, and the high-value areas were concentrated in the areas with a superior ecological background or developed economy, and some upstream cities had given up many development opportunities to maintain the ecological security of the Yellow River Basin, however, failed to obtain reasonable ecological compensation. ② A significant positive spatial agglomeration phenomenon was observed in ecological compensation and the overall spatial distribution trend was "cold in the north and hot in the south." The number of low-payment areas and low-compensation areas gradually decreased, showing a gradually shrinking agglomeration layout from the periphery to the center, whereas the number of high-payment areas and high-compensation areas continued to increase and formed a spatial evolution characteristic of the coexistence of scattered distribution and group distribution. ③ The overall regional differences in ecological compensation expanded. The over-variation density was the main source of the overall differences, and the focus on alleviating the intra-regional and inter-regional differences was located in the downstream areas. ④ A slight multi-level differentiation phenomenon was present in ecological compensation. The influence of different neighbors on the horizontal transfer of ecological compensation was quite different. This spatial spillover effect easily formed a "space club convergence" phenomenon within a certain geographical spatial range, but with the expansion of time, the probability of maintaining the original level of ecological compensation in each city decreased, and mobility gradually increased. Therefore, increasing the investment in ecological compensation in different fields, strengthening the coordinated development between regions, and giving full play to the spatial spillover effect are important ways to solve the current spatial imbalance of ecological compensation in the Yellow River Basin.

Phytohormonal dynamics in the abscission zone of Korla fragrant pear during calyx abscission: a visual study.

Phytohormones play a crucial role in regulating the abscission of plant organs and tissues. In this study, the ultrastructure of the sepals of Korla fragrant pears was observed using a transmission electron microscope, and high-performance liquid and gas chromatography were used to analyze the dynamic changes of phytohormones in the abscission zone during the calyx abscission process of Korla fragrant pears, and mass spectrometry imaging was applied to ascertain the spatial distribution of phytohormones. The results revealed that the mitochondria in the abscission zone of the decalyx fruits were regularly distributed around the cell wall, and the chloroplasts were moderately present. In contrast, in the persistent calyx fruit, the corresponding parts of the abscission zone showed a scattered distribution of mitochondria within the cells, and there was a higher number of chloroplasts, which also contained starch granules inside. Mass spectrometry imaging revealed that ABA was enriched in the abscission zone of the decalyx fruit, and their ionic signal intensities were significantly stronger than those of the persistent calyx fruit. However, the ionic signal intensities of Indole-3-acetic acid (IAA) and Gibberellin A3 (GA3) of the persistent calyx fruit were significantly stronger than those in the abscission zone of the decalyx fruit and were concentrated in the persistent calyx fruit. 1-Aminocyclopropanecarboxylic Acid (ACC) did not show distinct regional distribution in both the decalyx and persistent calyx fruits. Furthermore, before the formation of the abscission zone, the levels of IAA, GA3, and zeatin (ZT) in the abscission zone of the decalyx fruits were significantly lower than those in the persistent calyx fruits by 37.9%, 57.7%, and 33.0%, respectively, while the levels of abscisic acid (ABA) and ethylene (ETH) were significantly higher by 21.9% and 25.0%, respectively. During the formation of the abscission zone, the levels of IAA, GA3, and ZT in the abscission zone of the decalyx fruits were significantly lower than those in the persistent calyx fruits by 41.7%, 71.7%, and 24.6%, respectively, while the levels of ABA and ETH were significantly higher by 15.2% and 80.0%, respectively. After the formation of the abscission zone, the levels of IAA and GA3 in the abscission zone of the decalyx fruits were lower than those in the persistent calyx fruits by 20.8% and 47.8%, respectively, while the levels of ABA and ETH were higher by 271.8% and 26.9%, respectively. In summary, during the calyx abscission process of Korla fragrant pears, IAA and GA3 in the abscission zone inhibited abscission, while ABA and ETH promoted calyx abscission. These research findings enrich the understanding of the regulatory mechanism of plant hormones on calyx abscission and provide a theoretical basis for the study of exogenous plant growth regulators for regulating calyx abscission in Korla fragrant pear.

Measurable structure factors of dense dispersions containing polydisperse optically inhomogeneous particles.

Here, it is investigated how optical properties of single scatterers in interacting multi-particle systems influence measurable structure factors. Both particles with linear gradients of their scattering length density and core-shell structures evoke characteristic deviations between the weighted sum 〈S(Q)〉 of partial structure factors in a multi-component system and experimentally accessible measurable structure factors S M(Q). While 〈S(Q)〉 contains only the structural information of self-organizing systems, S M(Q) is additionally influenced by the optical properties of their constituents, resulting in features such as changing amplitudes, additional peaks in the low-wavevector region or splitting of higher-order maxima, which are not related to structural reasons. It is shown that these effects can be systematically categorized according to the qualitative behaviour of the form factor in the Guinier region, which enables assessing the suitability of experimentally obtained structure factors to genuinely represent the microstructure of complex systems free from any particular model assumption. Hence, a careful data analysis regarding size distribution and optical properties of single scatterers is mandatory to avoid a misinterpretation of measurable structure factors.

Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring

Monitoring displacement at transport infrastructure using Sentinel‑1 Interferometric Synthetic Aperture Radar (InSAR) faces challenges due to the sensor’s medium spatial resolution, which limits the pixel coverage over the infrastructure. Therefore, carefully selecting coherent pixels is crucial to achieve a high density of reliable measurement points and to minimize noisy observations. This study evaluates the effectiveness of various pixel selection methods for displacement monitoring within transport infrastructures. We employ a two-step InSAR time series processing approach. First, high-quality first-order pixels are selected using temporal phase coherence (TPC) to estimate and correct atmospheric contributions. Then, a combination of different pixel selection methods is applied to identify coherent second-order pixels for displacement analysis. These methods include amplitude dispersion index (ADI), TPC, phase linking coherence (PLC), and top eigenvalue percentage (TEP), targeting both point-like scatterer (PS) and distributed scatterer (DS) pixels. Experiments are conducted in two case studies: one in Germany, characterized by dense vegetation, and one in Spain, with sparse vegetation. In Germany, the density of measurement points was approximately 30 points/km², with the longest segment of the infrastructure without any coherent pixels being 2.8 km. In Spain, the density of measurement points exceeded 500 points/km², with the longest section without coherent pixels being 700 meters. The results indicate that despite the challenges posed by medium-resolution data, the sensor is capable of providing adequate measurement points when suitable pixel selection methods are employed. However, careful consideration is necessary to exclude noisy pixels from the analysis. The findings highlight the importance of choosing a proper method tailored to infrastructure characteristics. Specifically, combining TPC and PLC methods offers a complementary set of pixels suitable for displacement measurements, whereas ADI and TEP are less effective in this context. This study demonstrates the potential of Sentinel‑1 InSAR for capturing both regional-scale and localized displacements at transport infrastructure.

An improved time series SAR interferometry (TSInSAR) for investigating earthquake-induced active unstable slopes (AUS) in Pakistan

ABSTRACT Time series interferometric SAR (TSInSAR) techniques face challenges related to the availability of highly coherent point targets in non-urban, vegetated, and mountainous regions. In this study, we tested an improved TSInSAR approach with the help of distributed scatterers (DS) detected through the fast statistically homogeneous pixel selection (faSHP) approach and jointly processed with persistent scatterers (PS) within the interferometric point target analysis (IPTA) framework. The method is applied to a seismically active and highly gradient terrain to investigate the earthquake-induced active unstable slopes (AUS) in the Muzaffarabad-Balakot region of northern Pakistan, particularly using sixteen PALSAR-2 images acquired between October 2014 and May 2020. However, its effectiveness was also assessed by using Sentinel-1 data from the same time period. The quantitative assessment showed the effectiveness of the method in delineating the sliding surfaces of the unstable slopes and achieving approximately four times higher point density as compared to the standard PSI approach when applied to PALSAR-2 data and approximately nine times higher point targets when Sentinel-1 data is used. Exhibiting an average deformation rate varying between −40 mm yr−1 and 20 mm yr−1 along the line of sight (LOS) direction, the obtained results from PALSAR-2 data revealed the existence of 451 AUS in the region. The study also reports the discovery of a giant destabilized slope (~2.30 sq. km) located near Patika Village along the Neelam River. The majority of these unstable slopes are found at altitudes above 780 m, with slope angles ranging from 15 to 50 degrees. The study also found a significant correlation between deformation patterns and local precipitation. The rainwater gradually penetrates into the joints and cracks, accelerating the processes of deformation and slope failure. The research and its findings could help decision-making entities by providing first-hand information for managing the risks associated with slope failure.

The mean scatterer spacing estimation with the Gabor atoms selected based on the Nakagami distribution

Abstract Mean scatterer spacing (MSS) is a quantitative signature for disease diagnosis and tissue characterization. However, it is difficult to objectively extract the coherent components from the ultrasound RF echo signals to improve the accuracy performance of the MSS estimation. In the present study, a novel MSS estimation method with the matched Gabor atoms selected based on Nakagami parameters is proposed. Firstly, the ultrasound signals are decomposed into a series of Gabor atoms, and the envelopes of the residual signals are fitted with the Nakagami distribution. Then, the second order difference (SOD) of the shape parameters in Nakagami distribution is calculated to select the optimal atoms to match the coherent components. Finally, the locations of the selected Gabor atoms are used to estimate the MSS. In order to evaluate the performance of the proposed method, the simulated RF echo signals are modelled based on four regular degrees of the scatterer distributions, and then the optimally matched atoms are selected to estimate MSSs. The results based on simulated signals demonstrate that the propose method can provide accurate MSS estimation, which are advantageous for improving quantitative diagnosis of diseases and tissue characterization

Adsorption and retention of fracturing fluid and its impact on gas transport in tight sandstone with different clay minerals

To elucidate the adsorption characteristics and retention mechanisms of fracturing fluids in diverse clay minerals, we conducted on-line nuclear magnetic resonance (NMR) and atomic force microscopy (AFM) experiments. The depth and extent of solid phase damage are determined by the ratio between the size of fine fractions in fracturing fluid residue and the pore-throat size in experiments. Poor physical properties (K < 0.5 mD) result in a more preferential flow pathway effect during flowback, and the stepwise incremental pressure differential proves to be more effective for the discharge of fracturing fluid in submicron pore throats. The permeability is significantly influenced by the differential distribution of retained fracturing fluid, as supported by direct experimental evidence. The presence of good physical properties (K > 0.5 mD) combined with a scattered distribution of retained fracturing fluid is associated with high gas phase recovery permeability, whereas a continuous sheet-like distribution results in low recovery permeability. The expansive surface area and presence of filamentous illite minerals facilitate the multiple winding and adsorption of fracturing fluids, demonstrating strong hydrogen-bonding, multi-layering and multiple adsorption properties. The geological characteristics of the main gas formations exhibit significant variation, and the severity of damage caused by fracturing fluids occurs in diverse sequences. To address this issue, a differentiated strategy for optimizing fracturing fluids has been proposed.

Engineering transmitted light speckle statistics with field-tunable magnetic nanofluid scatterers

The active manipulation of electromagnetic wave scattering cross-sections within disordered media is crucial for understanding mesoscopic physics. An adaptable strategy for exploring the parameter space in order to control the scattering cross-section of such systems involves employing external field-tunable disorder. In this study, we utilize magnetic nanofluid as an in-situ tunable scattering medium, whose scattering parameters like scatterer number, density, size, and shape can be adjusted by an external magnetic field which is administered either constantly or with varying ramp rates. Our study on the transmitted light and the associated speckle statistics reveals intriguing behavior in response to changes in the strength and duration of the applied magnetic field. We observe that this tunable system remains within the weak scattering regime across various scattering scenarios: Rayleigh (for scatterer sizes smaller than the light wavelength, λ), Mie (when scatterer size approaches λ), and Geometric (for scatterer sizes exceeding λ) under both constant and ramped magnetic field application. Further, the transmitted speckle patterns deviate from Rayleigh behavior, with speckle contrast values increasing over time until it reaches a saturation point. However, the speckle patterns display intriguing dynamics with faster ramp rates resulting in larger speckle contrast values. This phenomenon arises from the inability of equilibrium field-induced structures to form rapidly under faster ramp rates, leading to a broader size distribution of scatterers and consequently a wider range of phase differences among scattered light components. Our study illuminates the dynamic behavior of wave transport through a tunable disordered media and underscores the potential of magnetic nanofluid as a versatile tool for controlling mesoscopic transport.

Global Context Relation-Guided Feature Aggregation Network for Salient Object Detection in Optical Remote Sensing Images

With the rapid development of deep neural networks, salient object detection has achieved great success in natural images. However, detecting salient objects from optical remote sensing images still remains a challenging task due to the diversity of object types, scale, shape and orientation variations, as well as cluttered backgrounds. Therefore, it is impractical to directly leverage methods designed for natural images to detect salient objects in optical remote sensing images. In this work, we present an end-to-end deep neural network for salient object detection in optical remote sensing images via global context relation-guided feature aggregation. Since the objects in remote sensing images often have a scattered distribution, we design a global context relation module to capture the global relationships between different spatial positions. In order to effectively integrate low-level appearance features as well as high-level semantic features for enhancing the final performance, we develop a feature aggregation module with the global context relation information as guidance and embed it into the backbone network to refine the deep features in a progressive manner. Instead of using traditional binary cross entropy as a training loss which treats all pixels equally, we design a weighted binary cross entropy to capture local surrounding information of different pixels. Extensive experiments on three public datasets are conducted to validate the efficiency of the proposed network and the results demonstrate that our proposed method consistently outperforms other competitors.

Ultrasound normalized cumulative residual entropy imaging: Theory, methodology, and application

Background and Objective:Ultrasound information entropy imaging is an emerging quantitative ultrasound technique for characterizing local tissue scatterer concentrations and arrangements. However, the commonly used ultrasound Shannon entropy imaging based on histogram-derived discrete probability estimation suffers from the drawbacks of histogram settings dependence and unknown estimator performance. In this paper, we introduced the information-theoretic cumulative residual entropy (CRE) defined in a continuous distribution of cumulative distribution functions as a new entropy measure of ultrasound backscatter envelope uncertainty or complexity, and proposed ultrasound CRE imaging for tissue characterization. Methods:We theoretically analyzed the CRE for Rayleigh and Nakagami distributions and proposed a normalized CRE for characterizing scatterer distribution patterns. We proposed a method based on an empirical cumulative distribution function estimator and a trapezoidal numerical integration for estimating the normalized CRE from ultrasound backscatter envelope signals. We presented an ultrasound normalized CRE imaging scheme based on the normalized CRE estimator and the parallel computation technique. We also conducted theoretical analysis of the differential entropy which is an extension of the Shannon entropy to a continuous distribution, and introduced a method for ultrasound differential entropy estimation and imaging. Monte-Carlo simulation experiments were performed to evaluate the estimation accuracy of the normalized CRE and differential entropy estimators. Phantom simulation and clinical experiments were conducted to evaluate the performance of the proposed normalized CRE imaging in characterizing scatterer concentrations and hepatic steatosis (n = 204), respectively. Results:The theoretical normalized CRE for the Rayleigh distribution was π/4, corresponding to the case where there were ≥10 randomly distributed scatterers within the resolution cell of an ultrasound transducer. The theoretical normalized CRE for the Nakagami distribution decreased as the Nakagami parameter m increased, corresponding to that the ultrasound backscattered statistics varied from pre-Rayleigh to Rayleigh and to post-Rayleigh distributions. Monte-Carlo simulation experiments showed that the proposed normalized CRE and differential entropy estimators can produce a satisfying estimation accuracy even when the size of the test samples is small. Phantom simulation experiments showed that the proposed normalized CRE and differential entropy imaging can characterize scatterer concentrations. Clinical experiments showed that the proposed ultrasound normalized CRE imaging is capable to quantitatively characterize hepatic steatosis, outperforming ultrasound differential entropy imaging and being comparable to ultrasound Shannon entropy and Nakagami imaging. Conclusion:This study sheds light on the theory and methodology of ultrasound normalized CRE. The proposed ultrasound normalized CRE can serve as a new, flexible quantitative ultrasound envelope statistics parameter. The proposed ultrasound normalized CRE imaging may find applications in quantified characterization of biological tissues. Our code will be made available publicly at https://github.com/zhouzhuhuang.

Modeling Bamboo Window Blinds in Classrooms: Assessing Daylighting Performance by Simulation Incorporating BSDF

ABSTRACT The purposes of this study are 1) providing a rating framework, including model layout, simulation settings and method, for assessing the daylighting performance of fenestration systems in typical Chinese classrooms, 2) exploring if fast-growing plant made shade layer could replace polyester fabric in terms of daylight availability and visual comfort. The rating framework was introduced, and the simulation method incorporating Bidirectional Scattering Distribution Function (BSDF) was validated by a sample case of physical model composing bamboo window blinds. Eight sets of bamboo blinds with varied dimensional parameters and four sets of woven fabrics with varied openness factors were compared in the proposed rating framework. The results show that bamboo blinds with expected parameters outperform shading fabrics on daylighting performance. Besides, bamboo blinds offered a sustainable and environmentally friendly alternative, providing a connection to nature and enhancing the overall window view. The findings highlight the potential of bamboo blinds in creating comfortable and visually appealing learning environments while promoting sustainability in architectural design. Overall, this study contributes to the understanding of the benefits and design considerations of natural material for building applications.

Research on the construction of intangible cultural heritage corridors in the Yellow River Basin based on geographic information system (GIS) technology and the minimum cumulative resistance (MCR) model

Objectively and accurately identifying the spatial structure and protection scope of intangible cultural heritage and constructing intangible cultural heritage corridors are crucial for the comprehensive systematic protection of intangible cultural heritage and the synergistic development of the region. However, the current research on intangible cultural heritage is limited to the protection and development of intangible cultural heritage in specific locations or specific areas. Thus, systematic and holistic research perspectives are relatively limited. Therefore, this study employs geographic information system spatial analysis and the minimum cumulative resistance model to construct an intangible cultural heritage corridor in the Yellow River Basin. This study aims to establish a systematic protection method and framework for intangible cultural heritage. The results show the following: (1) The intangible cultural heritage in the Yellow River Basin has a large-scale centralized distribution and small-scale scattered distribution, which provides an important spatial basis for the construction of intangible cultural heritage corridors. (2) Overall, intangible cultural heritage corridors can be more effectively constructed in the eastern region of the Yellow River Basin than in the western region, with 84.6% of the area being suitable and 15.4% being unsuitable. (3) Based on the suitability analysis, the "18 + N" corridor system of intangible cultural heritage in the Yellow River Basin, distributed across the eastern, central and southern regions, is constructed. The major corridor has a suitable width of 60–100 km, a total length of 11,935 km, and an area of 625,976 km2–919,942 km2, and can connect 634–711 intangible cultural heritage sites in series. On this basis, this study proposes a multilevel construction system for intangible cultural heritage corridors in the Yellow River Basin that integrates the "network structure–spatial scope" and "element–axis–region" levels. This approach culminates in a pattern of intangible cultural heritage protection and development in the Yellow River Basin characterized by "connecting points into lines, distributing in groups, and linking regions." This study reveals that combining geographic information system spatial analysis tools with a minimum cumulative resistance model effectively identifies potential heritage corridor networks and clarifies the hierarchical relationships of heritage element protection in the study area. This approach provides a reference model for the comprehensive protection and systematic development of intangible cultural heritage in the Yellow River Basin. Furthermore, the effectiveness and universality of this framework make it applicable to the protection and development of other similar international heritage areas.

Comparison of Multiple Machine Learning Models for the Classification of Cell States Based on Impedance Features

Abstract Microfluidic impedance flow cytometry (IFC) enables high-throughput single-cell analysis in label-free manner. Tens of thousands of cells can be measured in several minutes under multiple frequencies, which give rise to impedance features with rich information ideal for machine learning (ML)-based cell classification. Conventional data processing approach for IFC typically exploits the scattered distribution of the measured cells which correlates the impedance features (e.g., the impedance amplitude and phase at different frequencies, the amplitude ratio between high to low frequencies) and exhibits resolved cell clusters in scatter plot. By manually gating on the distributed dots plot, the cell subgroups get mapped to different cell type or cellular states. ML-based data processing for IFC not only reduces the human workload, and more importantly, it also eliminates the human interference to manual gating strategy, and thus potentially leading to more concise and accurate cell classification results. Here, we demonstrate the ML-based classification of different cell states for tumor cells subject to anticancer drug treatment. IFC-measured impedance data of H1650 cells and Hela cells under drug-induced mitosis block state and apoptosis state have been applied for ML-based cell state identification. Three machine learning models, including the random forest (RF), support vector machine (SVM) and K-nearest neighbours (KNN) have been trained for impedance features extracted from cell signals at both 500 kHz and 10 MHz. In comparison, the RF model give rise to the highest classification accuracies among all trained models here. For H1650 cells, 84.01% and 85.96% accuracies have been respectively achieved for G1/S state vs. apoptosis and G2/M vs. apoptosis. For the classification between G2/M vs. apoptosis for the paclitaxel-treated Hela cells, the RF model produces high accuracy of 98.70%.

Proteome-wide Characterization and Pathophysiology Correlation in Non-ischemic Cardiomyopathies.

Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue-based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography-mass spectrometry. Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Technical note: A GPU-based shared Monte Carlo method for fast photon transport in multi-energy x-ray exposures.

The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time. This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures. The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases. The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation. The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.