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The size of the elderly population in China has been increasing, and according to UN standards and relevant data, China has entered an aging society. With the aging of the population, residents' pension has become the focus of attention of the public and governments at all levels. Therefore, based on the life cycle theory, this paper considers the index and conversion coefficient of community coverage and elderly population coverage of pension service facilities in Hefei, Anhui Province. The problems existing in the spatial allocation of urban pension service facilities were also examined. This study developed the evaluation criteria for the rationality of spatial allocation of urban elderly service facilities in Hefei and analyzed their construction and spatial distribution characteristics by using GIS spatial methods, such as kernel density and network analysis. The rationality of spatial allocation was evaluated from three different spatial scales—cities, administrative regions, and streets—to provide a theoretical basis for the formulation of optimization measures. The results were as follows: 1) The supply of urban elderly care in Hefei is mainly based on community elderly care services, and the number and volume of care facilities are quite different among the four administrative regions. 2) The spatial distribution and configuration rationality of pension service facilities decrease from the urban center to the surrounding areas. The new urban area is weak in terms of pension service supply. The coverage rate of the elderly population in old urban areas is significantly higher than that in new areas. 3) The rationality of spatial allocation of urban pension service facilities is more significant at the street level, and the coverage of similar streets shows obvious spatial aggregation characteristics. Based on the residential area coverage rate of pension service facilities, this paper proposes the concept of elderly population coverage rate, and establishes the conversion coefficient between the two, which is the innovation of the research method adopted in this study. In addition, the rationality evaluation standard of spatial allocation of pension service facilities is constructed, providing a basis for rationality evaluation analysis. Through a comparative study of different spatial levels of cities, administrative districts, and streets, it was found that the evaluation of spatial allocation rationality of pension service facilities is closely related to the spatial scale: the smaller the spatial scale, the more accurate the evaluation. The results of this study could be useful for relevant research on other similar cities. Further, this study has practical significance for the allocation and layout of urban elderly service facilities. In other words, in the process of constructing the life cycle, the spatial distribution characteristics of service objects should be fully considered in the allocation of public service facilities, and attempts should be made to achieve a high spatial matching between "people" and "facilities".

The household's electricity consumption behaviour follows a unique sequential pattern and can be identified by analyzing the electricity consumption data with fine granularity in a smart home context. This particular sequence is concretely embodied in a series of electrical activities with temporal association relationships, thus forming a unique household electrical appliance activity-based chain (EAAC). In this study, we propose a method that combines an improved Apriori algorithm and Social Network to construct a household EAACs. First, we improved the Apriori algorithm (Apriori (1,1)) by combining the temporal and transactional sequences and used it to mine the time-series activity associations among different household appliances. After that, we used the Sliding Window concept to splice the time-series associations and obtain the unique EAACs for each household. Next, we visualized the EAACs using the Social Network analysis to reflect the unique sequential features of household electricity consumption behaviours. Finally, the model was validated by analyzing two families' actual household electricity consumption data, and future research directions were given. [ABSTRACT FROM AUTHOR]

Summary: The dysregulation of the Janus family tyrosine kinase‐signal transducer and activator of transcription (JAK‐STAT) is closely related to acute lymphoblastic leukaemia (ALL), whereas the clinical value of phosphorylated STAT5 (pSTAT5) remains elusive. Herein we performed a prospective study on clinical significance of flow cytometry‐based pSTAT5 in adult B‐ALL patients. A total of 184 patients were enrolled in the Precision‐Classification‐Directed‐Target‐Total‐Therapy (PDT)‐ALL‐2016 cohort between January 2018 and December 2021, and STAT5 phosphorylation was detected by flow cytometry at diagnosis. Based on flow‐pSTAT5, the population was classified into pSTAT5low (113/184, 61.1%) and pSTAT5high (71/184, 38.9%). Overall survival (OS) and event‐free survival (EFS) were inferior in pSTAT5high patients than in those with pSTAT5low (OS, 44.8% vs. 65.2%, p = 0.004; EFS, 23.5% vs. 52.1%, p < 0.001), which was further confirmed in an external validation cohort. Furthermore, pSTAT5 plus flow‐based minimal residual disease (MRD) postinduction defines a novel risk classification as being high risk (HR, pSTAT5high + MRD+), standard risk (SR, pSTAT5low + MRD−) and others as moderate‐risk group. Three identified patient subgroups are distinguishable with disparate survival curves (3‐year OS rates, 36.5%, 56.7% and 76.3%, p < 0.001), which was confirmed on multivariate analysis (hazard ratio 3.53, p = 0.003). Collectively, our study proposed a novel, simple and flow‐based risk classification by integrating pSTAT5 and MRD in favour of risk‐guided treatment for B‐ALL. [ABSTRACT FROM AUTHOR]

Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids. [ABSTRACT FROM AUTHOR]

Laser Time Transfer (LTT) has proven to be able to improve remote time transfer accuracy compared to microwave technology. The impact of satellite clock errors and atmospheric delays during LTT will be further reduced in the common-view mode. The challenge is presented as an optimization problem that is limited by satellite trajectories. This paper introduces an improved simulated annealing algorithm designed to maximize the common-view possibility among various station pairs within regional Satellite Laser Ranging (SLR) networks by optimizing satellite orbit trajectories. The study proposes a system model that integrates LTT principles with satellite visibility considerations. The simulated annealing algorithm is improved with new annealing strategies that incorporate control strategies, and modify the cooling function. Comparative simulation analyses demonstrate the effectiveness of the algorithm, resulting in a significant reduction in computation time by over 10 times. The optimized orbits exhibit common-view windows between 3.337 and 8.955 times longer than existing orbits. Further simulations are conducted to optimize the orbits, and common-view models are established for 45 pairs among 10 stations. The optimizations result in common-view times ranging from 6.183 to 60.633 min in the Asia-Pacific region and from 5.583 to 61.75 min in the Europe-to-Asia region. This can provide valuable references for designing satellite constellations. [ABSTRACT FROM AUTHOR]

The prognostic impact of TP53 mutations (TP53mut) in adult acute lymphoblastic leukemia (ALL) remains debatable. Herein, we determined the clinical significance of TP53mut in 283 adult ALL patients treated with a pediatric-type regimen. TP53mut were found in 11.0% (31) of patients, including 19 cases in adolescent and young adult (AYA) patients and 12 cases in non-AYA patients. Patients with TP53mut had poorer overall survival (OS) and event-free survival (EFS) in the non-AYA subgroup (n = 64) (3-year OS, 18.2% vs 50.9%, p =.0033; 3-year EFS, 0 vs 45.3%, p =.00028). however, this had to be taken cautiously due to a limited number of patients. In the AYA subgroup (n = 219), TP53mut did not impact OS or EFS (3-year OS, 60.6%vs71.0%, p =.55; 3-year EFS, 52.5%vs59.6%, p =.57). Collectively, our data reveal that the pediatric-type regimen eliminated the poor prognostic impact of TP53mut in AYA ALL. However, in non-AYA ALL patients, TP53mut remain a potential biomarker associated with poor outcomes. [ABSTRACT FROM AUTHOR]

The real-time light curve classification of transients is helpful in searching for rare transients. We propose a new algorithm based on machine learning, namely the Temporary Convective Network and Light Gradient Boosting Machine Combined with Weight Module Algorithm (TLW). The TLW algorithm can classify the photometric simulation transients data in g, r, i bands provided via PLAsTiCC, typing Tidal Disruption Event (TDE), Kilonova (KN), Type Ia supernova (SNIa), and Type I Super-luminous supernova (SLSN-I). When comparing the real-time classification results of the TLW algorithm and six other algorithms, such as Rapid, we found that the TLW algorithm has the best comprehensive performance indexes and has the advantages of high precision and high efficiency. The average accuracy of TLW is 84.54%. The average implementation timings of the TLW algorithm for classifying four types of transients is 123.09 s, which is based on TensorFlow's architecture in windows and python. We use three indicators to prove that the TLW algorithm is superior to the classical Rapid algorithm, including Confusion Matrix, PR curve, and ROC curve. We also use the TLW algorithm to classify ZTF real transients. The real-time classification results for ZTF transients show that the accuracy of the TLW algorithm is higher than the other six algorithms. [ABSTRACT FROM AUTHOR]

Cells are highly sensitive to their geometrical and mechanical microenvironment that directly regulate cell shape, cytoskeleton and organelle, as well as the nucleus morphology and genetic expression. The emerging two-dimensional micropatterning techniques offer powerful tools to construct controllable and well-organized microenvironment for single-cell level investigations with qualitative analysis, cellular standardization, and in vivo environment mimicking. Here, we provide an overview of the basic principle and characteristics of the two most widely-used micropatterning techniques, including photolithographic micropatterning and soft lithography micropatterning. Moreover, we summarize the application of micropatterning technique in controlling cytoskeleton, cell migration, nucleus and gene expression, as well as intercellular communication. [ABSTRACT FROM AUTHOR]

In order to ensure that the power supply can be restored quickly and efficiently under extreme conditions, an evaluation and decision-making method for mobile energy storage site selection and capacity planning considering the behaviour of decision makers is proposed. The prospect value is calculated based on the prospect theory to describe the bounded rationality and loss aversion of decision makers, and the attribute weight is calculated based on the relative closeness, and then the comprehensive value is obtained. Based on this, we can choose a mobile energy storage installation plan that is more in line with the psychology of decision makers.

Fighters have increasingly demanding performance on both aerodynamic and stealth. To adapt the design requirement of various irregular-shaped supersonic inlets integrated with flat fuselages, a design method for non-axisymmetric generalized internal conical (NAGIC) flowfield is discussed and then developed. By osculating axisymmetric flow concept and method of characteristics, the developed supersonic NAGIC flowfield can be inversely designed with arbitrary capture curves, controllable incident/terminal shock wave geometries, and post terminal shock wave pressure. Employing the streamline tracing technique, a set of external-compression inward-turning inlets with triangle-like flat capture shapes for supersonic stealth fighters are obtained to verify the design method. The study find that the internal contraction ratio and flow distortion of the inlet are reduced significantly by replacing the weak reflected shock wave in the original hypersonic NAGIC flowfield with a strong one. Thus, the compatibility between inlet and engine is improved in a relatively wide range. In addition, the irregular-shaped curved-compression inlet has high mass ratio and total pressure recovery ratio with negligible cross flow and uniform flow at throat. The performance of inlets with complex configurations can be further improved by matching the entrance geometries of basic flowfields and inlets. [ABSTRACT FROM AUTHOR]

Actin cytoskeleton plays crucial roles in various cellular functions. Extracellular matrix (ECM) can modulate cell morphology by remodeling the internal cytoskeleton. To define how geometry of ECM regulates the organization of actin cytoskeleton, we plated individual NIH 3T3 cells on micropatterned substrates with distinct shapes and sizes. It was found that the stress fibers could form along the nonadhesive edges of T-shaped pattern, but were absent from the opening edge of V-shaped pattern, indicating that the organization of actin cytoskeleton was dependent on the mechanical environment. Furthermore, a secondary actin ring was observed on 50 μ m circular pattern while did not appear on 30 μ m and 40 μ m pattern, showing a size-dependent organization of actin cytoskeleton. Finally, osteoblasts, MDCK and A549 cells exhibited distinct organization of actin cytoskeleton on T-shaped pattern, suggesting a cell-type specificity in arrangement of actin cytoskeleton. Together, our findings brought novel insight into the organization of actin cytoskeleton on micropatterned environments. [ABSTRACT FROM AUTHOR]

Serial section transmission electron micro-scopy (ssTEM) reveals biological information at a scale of nanometer and plays an important role in the ultrastructural analysis. However, due to the imperfect preparation of biological samples, ssTEM images are usually degraded with various artifacts that greatly challenge the subsequent analysis and visualization. In this paper, we introduce a unified deep learning framework for ssTEM image restoration which addresses three main types of artifacts, i.e., Support Film Folds (SFF), Staining Precipitates (SP), and Missing Sections (MS). To achieve this goal, we first model the appearance of SFF and SP artifacts by conducting comprehensive analyses on the statistics of real degraded images, relying on which we can then simulate a large number of paired images (degraded/artifacts-free) for training a deep restoration network. Then, we design a coarse-to-fine restoration network consisting of three modules, i.e., interpolation, correction, and fusion. The interpolation module exploits the adjacent artifacts-free images for an initial restoration, while the correction module resorts to the degraded image itself to rectify the artifacts. Finally, the fusion module jointly utilizes the above two results to further improve the restoration fidelity. Experimental results on both synthetic and real test data validate the significantly improved performance of our proposed framework over existing solutions, in terms of both image restoration fidelity and neuron segmentation accuracy. To the best of our knowledge, this is the first unified deep learning framework for ssTEM image restoration from different types of artifacts. Code is available at https://github.com/sydeng99/ssTEM-restoration. [ABSTRACT FROM AUTHOR]

Understanding terrestrial water storage (TWS) dynamics and associated drivers (e.g., climate variability, vegetation change, and human activities) across climate zones is essential for designing water resources management strategies in a changing environment. This study estimated TWS anomalies (TWSAs) based on the corrected Gravity Recovery and Climate Experiment (GRACE) gravity satellite data and derived driving factors for 214 watersheds across six climate zones in China. We evaluated the long-term trends and stationarities of TWSAs from 2004 to 2014 using the Mann–Kendall trend test and Augmented Dickey-Fuller stationarity test, respectively, and identified the key driving factors for TWSAs using the partial correlation analysis. The results indicated that increased TWSAs were observed in watersheds in tropical and subtropical climate zones, while decreased TWSAs were found in alpine and warm temperate watersheds. For tropical watersheds, increases in TWS were caused by increasing water conservation capacity as a result of large-scale plantations and the implementation of natural forest protection programs. For subtropical watersheds, TWS increments were driven by increasing precipitation and forestation. The decreasing tendency in TWS in warm temperate watersheds was related to intensive human activities. In the cold temperate zone, increased precipitation and soil moisture resulting from accelerated and advanced melting of frozen soils outweigh the above-ground evapotranspiration losses, which consequently led to the upward tendency in TWS in some watersheds (e.g., Xiaoxing'anling mountains). In the alpine climate zone, significant declines in TWS were caused by declined precipitation and soil moisture and increased evapotranspiration and glacier retreats due to global warming, as well as increased agriculture activities. These findings can provide critical scientific evidence and guidance for policymakers to design adaptive strategies and plans for watershed-scale water resources and forest management in different climate zones. [ABSTRACT FROM AUTHOR]

This study aims to compare the relative sensitivity between scene-independent and scene-dependent eye metrics in assessing trainees' performance in simulated psychomotor tasks.Eye metrics have been extensively studied for skill assessment and training in psychomotor tasks, including aviation, driving, and surgery. These metrics can be categorized as scene-independent or scene-dependent, based on whether predefined areas of interest are considered. There is a paucity of direct comparisons between these metric types, particularly in their ability to assess performance during early training.Thirteen medical students practiced the peg transfer task in the Fundamentals of Laparoscopic Surgery. Scene-independent and scene-dependent eye metrics, completion time, and tool motion metrics were derived from eye-tracking data and task videos. K-means clustering of nine eye metrics identified three groups of practice trials with similar gaze behaviors, corresponding to three performance levels verified by completion time and tool motion metrics. A random forest model using eye metrics estimated classification accuracy and determined the feature importance of the eye metrics.Scene-dependent eye metrics demonstrated a clearer linear trend with performance levels than scene-independent metrics. The random forest model achieved 88.59% accuracy, identifying the top four predictors of performance as scene-dependent metrics, whereas the two least effective predictors were scene-independent metrics.Scene-dependent eye metrics are overall more sensitive than scene-independent ones for assessing trainee performance in simulated psychomotor tasks.The study’s findings are significant for advancing eye metrics in psychomotor skill assessment and training, enhancing operator competency, and promoting safe operations. [ABSTRACT FROM AUTHOR]

Nature-based efforts could further climate mitigation and help limit warming to 1.5°C, given that proper and immediate solutions are implemented with similar ambition as in energy and industry sectors; however, omission of natural solutions or delays in overall climate action would substantially undermine the climate target of Paris Agreement. GLO:EVN/15jan23:gcb16479-toc-0001.jpg PHOTO (COLOR): . gl Significant reduction of greenhouse gas (GHG) emissions is urgently required in order to limit global temperature rise with a reasonable possibility. Our results show that NCS, depending on its size of emissions mitigation (Figure 1a), can further lower the global temperature by 0.2-0.4°C, such that global temperature rise by 2100 relative to preindustrial level (1850 s-1900 s) can be limited to around or below 1.5°C (Figure 1b). [Extracted from the article]

Background: miRNAs are crucial regulators of angiogenesis, but there have been no detailed studies on the role of miR-191-5p in cerebral infarct angiogenesis. Here, we investigated the role of miR-191-5p in regulating cerebral infarction angiogenesis.Material and Methods: Mice were injected intracerebroventricularly with antagomir negative control (NC-antagomir), miR-191-5p antagomir, or pcDNA-BDNF 2 h before middle cerebral artery occlusion (MCAO), followed by neurobehavioral score and foot-fault test. The cerebral infarct volume was performed by TTC staining. The microvessel density was detected by FITC-dextran. RT-qPCR was used to detect the levels of miR-191-5p and its target gene BDNF. Western blotting was applied to detect the protein levels of BDNF. The luciferase reporter assay verified that miR-191-5p targeted BDNF.Results: We found an increased level of miR-191-5p in the brain tissue of mice to MCAO. Down-regulation of miR-191-5p reduced the infarct volume and ameliorated neurological deficits in MCAO mice. Further investigation showed that miR-191-5p directly targeted BDNF and that the protective effect of miR-191-5p inhibition in angiogenesis was achieved by regulating BDNF.Conclusions: Our results indicated that miR-191-5p disturbed the angiogenesis in the mouse models of cerebral infarction by inhibiting BDNF. [ABSTRACT FROM AUTHOR]

In this work, a novel fiber optic sensor based on Fabry–Pérot interferometry is adopted in an optical coherence photoacoustic microscopy (OC-PAM) system to enable high-resolution in vivo imaging. The complete OC-PAM system is characterized using the fiber optic sensor for photoacoustic measurement. After characterization, the performance of the system is evaluated by imaging zebrafish larvae in vivo. With a lateral resolution of 3.4 μm and an axial resolution of 3.7 μm in air, the optical coherence microscopy subsystem visualizes the anatomy of the zebrafish larvae. The photoacoustic microscopy subsystem reveals the vasculature of the zebrafish larvae with a lateral resolution of 1.9 μm and an axial resolution of 37.3 μm. As the two modalities share the same sample arm, we obtain inherently co-registered morphological and vascular images. This OC-PAM system provides comprehensive information on the anatomy and vasculature of the zebrafish larvae. Featuring compactness, broad detection bandwidth, and wide detection angle, the fiber optic sensor enables a large field of view with a static sensor position. We verified the feasibility of the fiber optic sensor for dual-modality in vivo imaging. The OC-PAM system, as a non-invasive imaging method, demonstrates its superiority in the investigation of zebrafish larvae, an animal model with increasing significance in developmental biology and disease research. This technique can also be applied for functional as well as longitudinal studies in the future. [ABSTRACT FROM AUTHOR]

Summary: How to mitigate coke and improve heat sink is the critical factor for thermal management system of turbine‐based combined cycle (TBCC). A novel thermal management method using multi‐stage coating structure to mitigate coke and improve heat sink is developed in this study. The multi‐stage coating structure includes catalytic steam reforming (CSR) and catalytic steam gasification (CSG) catalyst coatings. Coke is removed by CSG, which provides coke self‐removal. In addition, the CSG is a strong endothermic reaction, which enables the increase of the chemical heat sink. The numerical study for the multi‐stage coating structure was conducted using a heated channel. Results indicate that the multi‐stage coating structure can reduce coke by 50% and increase chemical heat sink by 50%, when the mass ratio of secondary steam injection is 2%. In addition, it is found by a comparative study that the increase of secondary steam addition is helpful to remove coke and increase chemical heat sink. Both coke production and chemical heat sink are significantly affected by the rate distribution of CSG. The optimal performance of multi‐stage coating structure can be obtained by properly regulating rate distribution of CSG. [ABSTRACT FROM AUTHOR]

• Climate change can yield both direct and indirect effects on forest hydrology. • The impacts of climate change on the forest-water nexus are complex among watersheds. • The interactions among forest, water, and climate change introduce more complexities. Climate change can directly affect forest hydrology by altering precipitation, evapotranspiration, and streamflow generation, or indirectly by changing disturbance regimes and forest structures at multiple scales. Climate change impacts on the forest-water nexus across biomes are pervasive characterized by a great complexity and uncertainty, significantly impeding the design of adaptive forest watershed management to mitigate climate change risks. This paper reviews our current knowledge on the interactions between climate change and the forest-water nexus at the scales of individual tree, stand, and watershed. We found that climate change dramatically altered watershed hydrology in many parts of the world, with varying hydrological responses at multiple scales of tree species, forest types, climate types, and hydrological regimes. The streamflow response was often more pronounced in snow-dominated or water-limited watersheds, especially in watersheds with increasing droughts due to climate change and intensively managed plantations of either non-native tree species (e.g., Eucalyptus plantations in Brazil, Chile, Uruguay, and Australia) or young coniferous species. Climate change impacts can be compounded or offset by forest changes (i.e., deforestation, and forestation) through forest-climate interactions and feedbacks. Forest management can mitigate or aggravate the negative hydrologic impacts of climate change. Adaptive forest management is a prerequisite for managing the forest-water nexus in the face of climate change. Various forest management strategies aiming at maintaining optimal forest structure and high species diversity are recommended to enhance forest resistance and resilience to climate change and sustain water provision services from forests and other beneficial ecosystem services while minimizing negative impacts and risks of climate change. [ABSTRACT FROM AUTHOR]