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Uveal melanoma (UVM) is the most common primary ocular malignancy in adults and involves several types of regulated cell death. Cuproptosis is a novel method of regulating cell death by binding lipoylated TCA cycle proteins. There is still no research on the relationship between cuproptosis-related genes (CRGs) and UVM. Here, we aimed to develop a prognostic CRG signature for UVM. After a prognostic CRG signature was constructed, we determined the relationship between the signature and immune infiltration, bioinformatics analysis and experimental validation. Finally, a prognostic cuproptosis-related three-gene (CRTG) signature was constructed, which comprised ORAI2, ACADSB and SLC47A1. The risk score of the CRTG signature was negatively correlated with the overall survival (OS) and progression-free survival (PFS) of patients, which revealed strong predictive ability and its independent prognostic value. In addition, we found that the risk score was negative for chromosomes 3 and 6p, and positive for 8q, and high-risk UVM patients showed an increase in protumor immune infiltrates and a high expression of immune checkpoints. Finally, experimental validation verified that the migratory ability of MUM-2B cells was suppressed by the knockdown of the identified genes in vitro. We constructed a CRTG signature that is helpful in predicting prognosis and guiding treatment for patients with UVM. [ABSTRACT FROM AUTHOR]

Recently, deep convolutional neural networks have achieved great success for medical image segmentation. However, unlike segmentation of natural images, most medical images such as MRI and CT are volumetric data. In order to make full use of volumetric information, 3D CNNs are widely used. However, 3D CNNs suffer from higher inference time and computation cost, which hinders their further clinical applications. Additionally, with the increased number of parameters, the risk of overfitting is higher, especially for medical images where data and annotations are expensive to acquire. To issue this problem, many 2.5D segmentation methods have been proposed to make use of volumetric spatial information with less computation cost. Despite these works lead to improvements on a variety of segmentation tasks, to the best of our knowledge, there has not previously been a large-scale empirical comparison of these methods. In this paper, we aim to present a review of the latest developments of 2.5D methods for volumetric medical image segmentation. Additionally, to compare the performance and effectiveness of these methods, we provide an empirical study of these methods on three representative segmentation tasks involving different modalities and targets. Our experimental results highlight that 3D CNNs may not always be the best choice. Despite all these 2.5D methods can bring performance gains to 2D baseline, not all the methods hold the benefits on different datasets. We hope the results and conclusions of our study will prove useful for the community on exploring and developing efficient volumetric medical image segmentation methods. • We summarize the latest developments about 2.5D segmentation methods for volumetric medical image segmentation tasks. • We make a large-scale empirical comparison of 2.5D segmentation methods with 2D and 3D methods on three representative public datasets involving different modalities (CT and MRI) and targets (cardiac, prostate and abdomen) to systematically evaluate the performance of these methods on different segmentation tasks. • We make conclusions base on the experimental results which we hope will prove useful for the community on exploring and developing efficient volumetric medical image segmentation methods. [ABSTRACT FROM AUTHOR]

• High-speed impact dynamics and temperature changes are measured experimentally. • Theoretical models of drop and surface temperature changes (Δ T d and Δ T s ) are given. • Impact outcomes significantly affect the temperature variations. • Δ T d scaling laws are found for non-Leidenfrost drops: Δ T d ∼ t 3 / 2 first and then ∼ t. • Negligible temperature changes for Leidenfrost droplets due to a vapor layer. [Display omitted] Drop impact on heated surfaces plays a vital role in numerous applications, such as spraying, cooling, and combustion. In addition to impact dynamics, we investigate both droplet and surface temperature changes using a high-speed infrared (IR) camera and thermocouples when a Milli-Q water droplet impacts on a heated surface under various Weber numbers (1.6 ≤ W e ≤ 129 , which compares the drop kinetic to surface energy) and initial surface temperature (100 ∘ C ≤ T s i ≤ 445 ∘ C). Theoretical models of droplet and surface temperature changes are deduced using the energy conservation principle. Both theoretical and experimental results show that temperature variations are dramatically influenced by impact dynamics, which shows spreading, spreading/splashing atomization, or complete rebound depending on W e and T s i. For non-Leidenfrost droplets, the experimental results show that the mean droplet temperature change (Δ T d) is increased with increasing W e and T s i and scales with Δ T d ∼ t 3 / 2 and Δ T d ∼ t in the initial spreading and later-time sticking stages, respectively. The experimental results of solid surface temperature change, Δ T s c ≡ Δ T s (z = 0) , show that Δ T s c alters sharply with W e for W e < 30 , whereas insignificantly for W e > 30 with an identical T s i. Under the same W e , Δ T s c increases first for 100 ∘ C ≲ T s i ≲ 300 ∘ C and then reduces when 300 ∘ C ≲ T s i ≲ 445 ∘ C because of enhanced atomization at elevated temperatures. Finally, a negligible Δ T d and a nearly constant Δ T s c (≲ 4 ∘ C) are observed for Leidenfrost droplets due to the formation of an insulating vapor layer formed underneath the bouncing droplet. [ABSTRACT FROM AUTHOR]

This paper proposes a practical approach for dense-spectral-grid phase measurements based on a nonlinear vector network analyzer (NVNA). With the multitone outputs of commercial VSGs as both phase references and standards, a modified NVNA is presented to effectively obtain the phase spectra of modulated RF signals with spectral resolution of 1–100 kHz. Due to the limited tone number of a VSG multitone standard, a multistep phase calibration method is also proposed in this paper for multiplying the calibratable tone numbers in practice. A phase accuracy of ±2° has been experimentally achieved with both the VSG-based approach and the multistep phase calibration method at 2.4 GHz on a 1–100-kHz spectral grid. [ABSTRACT FROM AUTHOR]

High piezoelectric properties are desired for lead-free piezoelectric materials in consideration as a replacement for lead-based materials in applications. Due to the high piezoelectric coefficient, ( Ba100− x Ca x) ( Ti100− y Zr y) O3 ( BCTZ) piezoelectric ceramics have been considered as a promising lead-free alternate piezoelectric material. Here, six compositions were selected based on a prediction that all the compositions would have high piezoelectric coefficient at room temperature. The results confirmed all compositions exhibit well developed hysteresis loops and a large piezoelectric coefficient at room temperature. This is due to the coexistence of several phases where the major phase is likely to be orthorhombic and the second phase is proposed to be tetragonal. The phase transition was found to occur over a broad temperature range instead of at a specific temperature only. A relationship between the tetragonal-orthorhombic phase transition temperature and Ca2+ and Zr4+ content was proposed. This enables clear determination of BCTZ compositions with high piezoelectric coefficient at a desired operation temperature. [ABSTRACT FROM AUTHOR]

With rapid urbanization, the building stock and related winter heating demands are developing fast in the urban regions of Northern China. In addition to the national strategy to alleviate the air pollution, China has also pledged to achieve carbon neutrality in the future. Although the planning of heating system has been studied from national level, bottom-level regional plans are still lacking, which is especially crucial for a huge country as China that has significantly different characteristics across regions. Therefore, this study examined the transitions of the heating sectors towards 2035 and 2050 for 1047 third-level urban units in Northern China. Future changes in heating resources under the low-carbon transitions and future heating demands with the urbanization trend were investigated. Through geographic mapping of resources and demands for county-level units, the regional differences in future scenarios owing to the uneven socioeconomic development of Northern China were presented, which fill in the knowledge gap. By combining supply-side investigations and demand-side forecasts, various roadmaps were evaluated in terms of primary energy consumption, pollution emissions, and economic benefits. Although significant pollution reductions can be achieved in all proposed roadmaps, the clean heating roadmap with the optimal utilization of available resources presents a lower annualized cost than the business-as-usual roadmap, which simply relies on biomass and supplementary sources such as natural gas. In 2050, the primary energy consumption can be reduced to approximately 3 kgce/m2, with an annualized cost of 6 CNY/m2. Balancing the carbon emissions and economic performance, the optimal renovation pattern, together with supply side technologies, were identified in this study. • Regional investigations in 1047 urban units in Northern China. • Forecast of heating resources and demands in future conditions. • Heat roadmaps were evaluated for environmental and economic implications. • The CHR has lower annualized costs and carbon emissions than the BAU roadmap. • Optimal renovation pattern is identified based on climate and economic implication. [ABSTRACT FROM AUTHOR]

We report ultrafast charge migration in ionized iodo-alkyne chain I(CC)nH+ for n = 1, 2, ..., 5. The dynamics of electron density become more complicated with the increasing length of the molecular chain. However, the essential properties of charge migration in I(CC)nH+ can be clearly interpreted in terms of the electron flux. By systematic investigations of the dynamics of electron density, hole density, and the electron flux for different molecules, the size dependence of charge migration in I(CC)nH+ is discussed. [ABSTRACT FROM AUTHOR]

This study aimed to explore whether the defect of visual function is a risk factor of knee anterior cruciate ligament (ACL) sports injury and to provide a theoretical basis for the primary prevention of ACL sports injury. This cross-sectional study included 392 participants divided into two groups: the sports injury group (287 with sports injury of knee) and the control group (105 healthy volunteers). Participants in the sports injury group were further divided into the ACL-Intact group (133) and the ACL-Deficient group (154). Participants in the sports injury group received a questionnaire about the conditions of their injury (including injury action, site condition, weather, contact) and a visual examination by synoptophore (including binocular vision, subjective and objective oblique angle, visual fusion range, stereoacuity). Participants in the control group only received the visual examination. In the end, we found that low visual fusion range (p = 0.003) and injury action, especially quick turn (p = 0.001), sudden stop (p < 0.001) and jump (p = 0.001), are the major risk factors for ACL injury in the analysis of the integrated data. In addition, athletes with low vision fusion range have increased risk of ACL sports injury when they make a sudden stop on wooden floor, plastic floor or cement floor on cloudy days (OR = 13.208). Visual factors, especially low fusion range, significantly increase the risk of ACL sports injury. [ABSTRACT FROM AUTHOR]

Minuscule pressure/stress detection with high sensitivity can recognize and deal with potential hazards timely, which is crucial for guaranteeing the security of human and stability of social functioning. Lithium niobate (LiNbO 3) single crystal possessing excellent piezoelectric and ferroelectric properties is suitable for fabricating piezoelectric pressure sensors. Therefore, in this paper, the pressure sensors based on LiNbO 3 single crystals with parallel connected structure were researched. Sensors with parallel connected structure can improve the sensitivity from 4.86 V/N of single sheet structure to 8.71 V/N under the stress between 0.01 N and 0.2 N at 30 °C. Both types of the sensors can detect the minuscule stress low to 0.01 N and minuscule pressure generated by balloon pump, blowing largely or slowly. The influence of temperature on sensors was also researched, and the results exhibited that sensors performed well from 30 °C to 60 °C and still sustained high sensitivity of 5.26 V/N of parallel connected structure and 3.71 V/N of single sheet structure at 60 °C. Besides, the response time of sensors to the pressure of balloon pump is 60 ms under different temperature. These excellent properties indicate the great potential applications of fabricated sensors in practical minuscule pressure/stress detection. [ABSTRACT FROM AUTHOR]

Aging contributes significantly to cognitive decline. Aerobic exercise (AE) has been shown to induce substantial neuroplasticity changes, enhancing cognitive and brain health. Likewise, recent research underscores the cognitive benefits of foreign language learning (FLL), indicating improvements in brain structure and function across age groups. However, the lack of a comprehensive paradigm integrating language learning with exercise limits research on combined effects in older adults. In order to address this gap, we devised a novel approach using a virtual world tourism scenario for auditory-based language learning combined with aerobic cycling. Our study examines the impact of simultaneous AE and FLL integration on cognitive and language learning outcomes compared to FLL alone. A total of 20 older adults were randomly assigned to AE + FLL and FLL-only groups. The results revealed significantly improved Spanish language learning outcomes in both combined and language learning-only groups. Additionally, significant cognitive function improvement was observed in the FLL group following short-term language learning. [ABSTRACT FROM AUTHOR]

Semantic communication is a promising technology used to overcome the challenges of large bandwidth and power requirements caused by the data explosion. Semantic representation is an important issue in semantic communication. The knowledge graph, powered by deep learning, can improve the accuracy of semantic representation while removing semantic ambiguity. Therefore, we propose a semantic communication system based on the knowledge graph. Specifically, in our system, the transmitted sentences are converted into triplets by using the knowledge graph. Triplets can be viewed as basic semantic symbols for semantic extraction and restoration and can be sorted based on semantic importance. Moreover, the proposed communication system adaptively adjusts the transmitted contents according to channel quality and allocates more transmission resources to important triplets to enhance communication reliability. Simulation results show that the proposed system significantly enhances the reliability of the communication in the low signal-to-noise regime compared to the traditional schemes. [ABSTRACT FROM AUTHOR]

Plasma-enhanced atomic layer deposition (PEALD) has demonstrated its superiority at coating ultra-conformal high dielectric thin-films, which are essential to the fin field-effect transistors (FinFETs) as well as the advanced 3D V-NAND (vertical Not-AND) flash memory cells. Despite the growing research interest, the exploration of the optimal operation policies for PEALD remains a complicated and expensive task. Our previous work has constructed a comprehensive 3D multiscale computational fluid dynamics (CFD) model for the PEALD process and demonstrated its potential to enhance the understanding of the process. Nevertheless, the limitation of computational resources and the relatively long computation time restrict the efficient exploration of the operating space and the optimal operating strategy. Thus, in this work, we apply a 2D axisymmetric reduction of the previous 3D model of PEALD reactors with and without the showerhead design. Furthermore, a data-driven model is derived based on a recurrent neural network (RNN) for process characterization. The developed integrated data-driven model is demonstrated to accurately characterize the key aspects of the deposition process as well as the gas-phase transport profile while maintaining computational efficiency. The derived data-driven model is further validated with the results from a full 3D multiscale CFD model to evaluate model discrepancy. Using the data-driven model, an operational strategy database is generated, from which the optimal operating conditions can be determined for the deposition of Hafnium Oxide (HfO 2) thin-film based on an elementary cost analysis. [ABSTRACT FROM AUTHOR]

Black phosphorus (BP) was firstly and successfully synthesized in 1914. But it has given a new life after many years until the rediscovery of two-dimensional (2D) BP in 2014, which inspires the craze for studying BP once again. This review begins with the preparation of BP, which is divided into two parts: the preparation of bulk BP and 2D BP. This review highlights its catalytic potential on Oxygen Evolution Reaction no matter the morphology such as bulk BP, 2D BP and atomic doping, compared to that of the precious metals with high price. In addition, BP has excellent performance in sensors due to its special direct band gap and excellent electron mobility. BP owns specific high capacity making it stand out as a bright star as the electrode materials applied in Lithium battery. More importantly, the application restriction of BP is delicately analyzed and some suggestions are put forward. Finally, the outlook including future and development trends and application prospects lying in the road ahead of BP research are simultaneously discussed. • Black phosphorus owns merits of high charge-carrier mobility, tunable direct-bandgap and unique anisotropic structure. • Series of bulk and two-dimensional black phosphorus preparation methods and its potential applications have been introduced. • The doping of atoms and increase of surface to volume ratios have a dramatic change in properties of black phosphorus. • The article points out the research based on practical application requirements and introduce some constructive opinions. [ABSTRACT FROM AUTHOR]

Direct metal laser solidification (DMLS) has been receiving increasing research interest in the additive manufacturing (AM) industry due to its outstanding performance in producing parts with ultra-high precision and variable geometries. However, the lack of appropriate in-situ disturbance detection techniques specialized for DMLS makes real-time quality control extremely difficult. In this work, a first-principles-based finite element method (FEM) model focusing on the heat transfer behavior of the DMLS process is developed. The model-produced thermal data is processed to reproduce the outputs of two industrially used sensors: the optical tomography (OT) sensor and the melt pool monitoring (MPM) sensor. In-situ sensor data analytics is then performed through the use of a convolutional neural network (CNN) to automatically detect disturbances from each sensor data during the build process in real-time. Transfer learning is applied to the pre-trained AlexNet backbone to efficiently construct the disturbance detection CNNs for each sensor, and overall accuracy of 73.4% and 82.8% is observed for the melt pool and the OT CNN, respectively. To further increase the accuracy, a cross-validation scheme is proposed to combine the results from both CNNs based on their confidence levels. The final results demonstrate that the testing accuracy increases to 90.4% when cross-validation between both sensor data analytics is applied. The developed machine-learning-based algorithms provides a methodology to perform real-time process data analytics and thereby reducing defect formation and increasing production throughput. [ABSTRACT FROM AUTHOR]

• Operational Trend Prediction and Classification for Chemical Processes. • Convolutional Neural Network Method Based on Symbolic Hierarchical Clustering. • Application to a Chemical Plant via Industrial Data. • Favorable Comparison with Traditional Neural Network Methods. In modern industrial chemical engineering plants, the quality of the product is closely related not only to the process design but also to the efficiency of human operation. Currently, single-step prediction models are adopted by process engineers to estimate the immediate system response. However, those single-step prediction models are limited as they don't enable the operator to visualize the complete series of effects associated with the operation in the long run. In order to help make prescient predictions, this paper proposes a novel symbolic hierarchical clustering (SHC) based convolutional neural network (CNN) method for trend prediction and classification. Firstly, the raw historical operation data series are symbolized from numerical values to strings according to their distinct characteristics. Secondly, the hierarchical clustering method is used to eliminate the low-frequency operation trends and to determine and label the types of operational trends for the symbolized dataset. Subsequently, the categorized dataset and its respective label are fed into a specially tailored CNN for the training of the CNN model for trend classification. Finally, to demonstrate the effectiveness of the proposed SHC-CNN algorithm, the proposed method is applied to the methanol production process of Hainan Petrochemical Co., Ltd. to predict and classify its main operational trends. In addition, the superiority of SHC-CNN operational trend prediction is demonstrated through the comparison with traditional neural networks. [ABSTRACT FROM AUTHOR]

Plasma-enhanced atomic layer deposition (PEALD) is one of the most widely adopted deposition methods in the semiconductor industry. It is chosen largely due to its superior ability to deliver ultra-conformal dielectric thin-films with high aspect-ratio surface structures, which are encountered more and more often in the novel design of metal-oxide-semiconductor field-effect transistors (MOSFETs) in the NAND (Not-And)-type flash memory devices. Compared with the traditional thermal ALD method, PEALD allows for lower operating temperature and speeds up the deposition process with the involvement of plasma species. Despite its popularity, the development of PEALD operation policies remains a complicated and expensive task, which motivates the construction of an accurate and comprehensive simulation model. While existing models have described the individual or partially coupled domains, none of these models has captured all three domains in the PEALD process: surface reaction, macroscopic gas transport, and plasma generation. In this work, a comprehensive multiscale computational fluid dynamics (CFD) model is developed for a remote PEALD reactor used in the deposition of HfO 2 thin-films. First, a previously developed kinetic Monte-Carlo (kMC) model is adapted for the multiscale simulation to describe the surface reactions. Then, two macroscopic models, specifically tailored for the remote plasma reactor, are formulated to describe the dynamic behaviors of the plasma generation and bulk species transport domains, respectively. Additionally, an integrated message passing interface (MPI) scheme is built to couple and resolve the communication between different scales in the model. The model results are then validated with experimental data and an automated workflow is established for model calculations without human intervention. Finally, a set of baseline operating conditions derived from the model simulation results is proposed to guarantee the production of high-quality thin-films. [ABSTRACT FROM AUTHOR]

The 3 × 3 demodulation algorithm has been widely used in retrieving the phase information in the optical fiber sensing system, while the asymmetry of the 3 × 3 coupler can introduce some distortions. In this situation, the parameters of the 3 × 3 coupler can be calibrated by the ellipse fitting method to remove the distortions. Conducting a frequency modulation on the laser, together with an unbalanced Michelson interferometer, makes the ellipse fitting method implemented, which is more appropriate for all-optical sensing. Unexpectedly, the auxiliary amplitude modulation of the laser induced by the frequency modulation is inevitable, leading to the deterioration of the calibration. In this paper, the influence of the auxiliary amplitude modulation on the calibration of the asymmetric parameters is analyzed theoretically and verified experimentally, on the basis of which a convenient but highly efficient method for acquiring the output of the laser and removing related items from the interferometric signals is put forward. The feasibility and robustness of the proposed solution is tested experimentally, and the results show that the mean square errors of the fittings and the variation coefficients of the calibrated parameter sequences are at the scale of 10 − 5 and 10 − 4 , respectively, indicating that the method performs very well. [ABSTRACT FROM AUTHOR]

• The energy consumption of 38 Chinese district heating systems was investigated and compared. • Method to break down the consumption and evaluate the operational problems was presented. • Field measurements were conducted to evaluate problems leading to high energy consumption. • Overheating was responsible for 23% of total heat consumption. • Resistance, operation flow, and pump efficiency were three major problems in distribution networks. Worldwide, China has the largest district heating (DH) area and is also the fastest growing country. This paper presents field measurement results for operational energy consumption from 38 DHSs to fill in the gaps in understanding of the current operational issues of the district heating system (DHS). The average heat consumption during the heating period was 98.6 kWh/m2 and the monthly average electricity consumption for circulating pumps in the primary and secondary networks was 0.27 kWh/(m2 × month) and 0.29 kWh/(m2 × month), respectively. Thereafter, a systematic method for breaking down the energy consumption and quantitatively evaluating the underlying problems is presented. Based on several detailed measurements conducted in typical heat-exchange substations (HESs), it was found that overheating was the most prominent problem in energy-efficient buildings, constituting 23% of the total heat consumption. Another problem encountered was heat loss through pipes, which constituted approximately 5%–10% of the total heat consumption and was highly dependent on the actual conditions. In distribution networks, problems such as high resistance, high operational flow, and low pump efficiency were also identified and analyzed. Finally, practical energy-efficiency suggestions and future potential targets for the Chinese DHS are discussed from both a design and operational perspective. [ABSTRACT FROM AUTHOR]

When extracting flight data from airport terminal area, there are matters such as large volume, unclear features, and similar trend in time series. In order to deal with the related issues and to optimize the description, by combining with the TBO (Trajectory-Based Operation), an application proposed by the ICAO (International Civil Aviation Organization) in ASBU (Aviation System Block Upgrade), using multisource dynamic model to establish 4DDW (4D dynamic warping) algorithm, the multisource modeling integrated with evaluation system is proposed to realize the flight path optimization with time series characteristics and accord with the interval concept. The calculation results show that 4DDW can obtain the optimal solution for multiprofile calculation of TBO by comparing the composite trajectory deviation values and time dimension planning using the buffer and threshold values recommended by ICAO in airspace planning and flight procedure design. The results meet the requirements of high accuracy and convergence features of spatial waypoints and can improve the airport operation standards and terminal area capacity. [ABSTRACT FROM AUTHOR]

Zinc (Zn)–dysprosium (Dy) binary alloys are promising biodegradable bone fracture fixation implants owing to their attractive biodegradability and mechanical properties. However, their clinical application is a challenge for bone fracture healing, due to the lack of Zn–Dy alloys with tailored proper bio‐mechanical and osteointegration properties for bone regeneration. A Zn‐5Dy alloy with high strength and ductility and a degradation rate aligned with the bone remodeling cycle is developed. Here, mechanical stability is further confirmed, proving that Zn‐5Dy alloy can resist aging in the degradation process, thus meeting the mechanical requirements of fracture fixation. In vitro cellular experiments reveal that the Zn‐5Dy alloy enhances osteogenesis and angiogenesis by elevating SIRT4‐mediated mitochondrial function. In vivo Micro‐CT, SEM‐EDS, and immunohistochemistry analyses further indicate good biosafety, suitable biodegradation rate, and great osteointegration of Zn‐5Dy alloy during bone healing, which also depends on the upregulation of SIRT4‐mediated mitochondrial events. Overall, the study is the first to report a Zn‐5Dy alloy that exerts remarkable osteointegration properties and has a strong potential to promote bone healing. Furthermore, the results highlight the importance of mitochondrial modulation and shall guide the future development of mitochondria‐targeting materials in enhancing bone fracture healing. [ABSTRACT FROM AUTHOR]

As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang. [ABSTRACT FROM AUTHOR]

Photovoltaic power generation can directly convert solar energy into electricity, but most of the solar energy absorbed by the photovoltaic panel is converted into heat, which significantly increases the operating temperature leading to a reduction in the power generation efficiency of the panels. To reduce the working temperature of photovoltaic panels and improve the photoelectric conversion efficiency, this paper installs aluminum fins and air channels at the traditional photovoltaic cell back sheets and cools them with forced-circulation cooling through fans. The relationships between fin spacing, fin height, air channel inlet wind speed and panel temperature, power generation, and electrical efficiency were investigated. The results show that the temperature of the photovoltaic panel decreases and then increases with the decrease of the fin spacing during natural convection and gradually decreases with the increase of the fin height. The use of forced-circulation cooling technology can effectively reduce the PV panel temperature and increase the net power generation. When the solar radiation intensity is 1000 W/m2, the ambient temperature is 35°C, the fin spacing is 6 mm, the height is 80 mm, the inlet wind speed is 1 m/s, the net generating power reaches the maximum value, and the net generating power and the electrical efficiency are increased by 14.6% and 2.25%, respectively. [ABSTRACT FROM AUTHOR]

In rockfall hazard management, the investigation and detection of potential rockfall source areas on rock cliffs by remote-sensing-based susceptibility analysis are of primary importance. However, when the rockfall analysis results are used as feedback to the fieldwork, the irregular slope surface morphology makes it difficult to objectively locate the risk zones of hazard maps on the real slopes, and the problem of straightforward on-site visualization of rockfall susceptibility remains a research gap. This paper presents some of the pioneering studies on the augmented reality (AR) mapping of geospatial information from cyberspace within 2D screens to the physical world for on-site visualization, which directly recognizes the rock mass and superimposes corresponding rock discontinuities and rockfall susceptibility onto the real slopes. A novel method of edge-based tracking of the rock mass target for mobile AR is proposed, where the model edges extracted from unmanned aerial vehicle (UAV) structure-from-motion (SfM) 3D reconstructions are aligned with the corresponding actual rock mass to estimate the camera pose accurately. Specifically, the visually prominent edges of dominant structural planes were first explored and discovered to be a robust visual feature of rock mass for AR tracking. The novel approaches of visual-geometric synthetic image (VGSI) and prominent structural plane (Pro-SP) were developed to extract structural planes with identified prominent edges as 3D template models which could provide a pose estimation reference. An experiment verified that the proposed Pro-SP template model could effectively improve the edge tracking performance and quality, and this approach was relatively robust to the changes of sunlight conditions. A case study was carried out on a typical roadcut cliff in the Mentougou District of Beijing, China. The results validate the scalability of the proposed mobile AR strategy, which is applicable and suitable for cliff-scale fieldwork. The results also demonstrate the feasibility, efficiency, and significance of the geoinformation AR mapping methodology for on-site zoning and locating of potential rockfalls, and providing relevant guidance for subsequent detailed site investigation. [ABSTRACT FROM AUTHOR]

An improved adaptive particle swarm algorithm with guiding strategy (GSAPSO) was proposed, and it was applied to solve the reactive power optimization (RPO). Four kinds of particles containing the main particles, double central particles, cooperative particles and chaos particles were introduced into the population of the developed algorithm, which was to decrease the randomness and promote search efficiency through guiding particle position updating. Moreover, the cluster focus distance-changing rate was responsible for dynamically adjusting inertia weight. Then the convergence rate and accuracy of this algorithm would be elevated by four functions, which would test effectively the proposed. Finally, the optimized algorithm was verified on the RPO of the IEEE 30-bus power system. The performance of PSO, Random weight particle swarm optimization (WPSO) and Linearly decreasing weight of the particle swarm optimization algorithm (LDWPSO) were identified as the referential information, the proposed GSAPSO was more efficient from the comparison. Calculation results demonstrated that higher quality solutions were obtained and convergence rate and accuracy was significantly higher with regard to the GSAPSO algorithm. [ABSTRACT FROM AUTHOR]

The aggregation of the remaining battery capacity of electric vehicles (EVs) can be used as distributed energy storage to participate in the microgrid optimisation through vehicle‐to‐grid (V2G) technology. However, the reliability of this service to be delivered is affected by the uncertainty of EVs' behaviour. The un‐reliable service will bring risks in the operation of microgrid when EVs' V2G electricity is regarded as an important flexibility resource. This paper, first proposes an analytical method to quantify the reliability of EV aggregation's (EVA's) V2G electricity based on the analysis of historical charging data and compound Poisson process. Based on this model, electric vehicles aggregators can evaluate the V2G bid quantity for any time slot on day t+1 according to the reliability requirements. Secondly, an optimal operation model of microgrid with consideration of V2G's reliability is considered. Finally, a test system with photovoltaics (PVs) and EVA on top of the original IEEE 33‐node system is used to verify the effectiveness of the proposed model. The results show that with the proposed reliability evaluation method of V2G electricity, the optimal operation of the microgrid can be reached with appropriate evaluation of the capability of the EVA. [ABSTRACT FROM AUTHOR]

The application of standing surface acoustic wave (SSAW) tweezers based on backpropagation superposition to achieve precise behavior manipulation of microscale cells and even nanoscale bacteria has been widely studied and industrialized. However, the structure requires multiple transducer components or full channel resonance. It is very challenging to design a simple structure for nano-control by complex acoustic field. In this study, a reflector-interdigital transducer (R-IDT) acoustofluidic device based on unilateral coherence enhancement is proposed to achieve SSAW definition features of periodic particle capture positions. The SAW device based on a unilateral transducer can not only generate leaky-SAW in water-filled microchannel, but also have a contribution of spherical waves in the vibration area of the substrate-liquid interface due to the Huygens-Fresnel diffractive principle. Both of them form a robust time-averaged spatial periodicity in the pressure potential gradient, accurately predicting the lateral spacing of these positions through acoustic patterning methods. Furthermore, a reflector based on Bragg-reflection is used to suppress backward transmitted SAW and enhance forward conducted SAW beams. By using a finite element model, R-IDT structure's amplitude enhances 60.78% compared to single IDT structure. The particle manipulation range of the diffractive acoustic field greatly improves, verified by experimental polystyrene microspheres. Besides, biocompatibility is conformed through red blood cells and Bacillus subtilis. We investigate the overall shift of periodic pressure field that can still occur when the phase changes. This work provides a simpler and low-cost solution for the application of acoustic tweezer in biological cell culture and filtering. [ABSTRACT FROM AUTHOR]

Cortical gray to white matter signal intensity ratio (GWR) measured from T1‐weighted magnetic resonance (MR) images was associated with neurodegeneration and dementia. We characterized topological patterns of GWR during AD pathogenesis and investigated its association with cognitive decline. The study included a cross‐sectional dataset and a longitudinal dataset. The cross‐sectional dataset included 60 cognitively healthy controls, 61 mild cognitive impairment (MCI), and 63 patients with dementia. The longitudinal dataset included 26 participants who progressed from cognitively normal to dementia and 26 controls that remained cognitively normal. GWR was compared across the cross‐sectional groups, adjusted for amyloid PET. The correlation between GWR and cognition performance was also evaluated. The longitudinal dataset was used to investigate GWR alteration during the AD pathogenesis. Dementia with β‐amyloid deposition group exhibited the largest area of increased GWR, followed by MCI with β‐amyloid deposition, MCI without β‐amyloid deposition, and controls. The spatial pattern of GWR‐increased regions was not influenced by β‐amyloid deposits. Correlation between regional GWR alteration and cognitive decline was only detected among individuals with β‐amyloid deposition. GWR showed positive correlation with tau PET in the left supramarginal, lateral occipital gyrus, and right middle frontal cortex. The longitudinal study showed that GWR increased around the fusiform, inferior/superior temporal lobe, and entorhinal cortex in MCI and progressed to larger cortical regions after progression to AD. The spatial pattern of GWR‐increased regions was independent of β‐amyloid deposits but overlapped with tauopathy. The GWR can serve as a promising biomarker of neurodegeneration in AD. [ABSTRACT FROM AUTHOR]

The finned-tube heat exchanger is the core part of an air conditioning system. Its heat exchange performance directly affects the energy consumption and efficiency of the air conditioner. The shortage and rising price of copper have led to increasing replacement of copper tubes with aluminum tubes in finned-tube heat exchangers. This paper studies two kinds of such heat exchangers, one consisting of copper tubes and aluminum fins and the other consisting of aluminum tubes and aluminum fins. The influences of the different base tube materials on heat transfer are compared and analyzed in terms of heat transfer strength and cost per unit heat transfer. The results show that the heat transfer and heat transfer coefficient increase with increasing inlet wind speed. Under different inlet wind speeds, the heat transfer and heat transfer coefficient of the finned-tube heat exchanger with aluminum tubes are 4%–12% and 7%%–9% lower than those of an identically structured heat exchanger with copper tubes, respectively. The aluminum-aluminum exchanger achieves 67% higher heat transfer than that of the copper-aluminum exchanger at only 8% of the cost. These results are significant for guiding the development and application of finned-tube heat exchangers. [ABSTRACT FROM AUTHOR]

Background: Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. Methods: We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. Results: NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). Conclusions: By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace [ABSTRACT FROM AUTHOR]

Background/Aims: The aim of this study was to determine the optimal volume of peritoneal effusion required to diagnose malignant ascites. Patients and Methods: The authors recruited 123 patients with shifting dullness and obtained 123 peritoneocentesis fluid samples. The samples were divided into seven aliquots of 10, 50, 100, 150, 200, 250, and 300 mL for cytopathological examination. The sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were calculated for each aliquot. Results: The sensitivity for the diagnosis of malignant ascites gradually increased as the sample volume increased and reached a constant value at a volume of 200 mL. The sensitivity and NPV for the 10-, 100-, and 150-mL volumes were significantly different from those for the 200-mL sample. However, the sensitivity and NPV for the 250- and 300-mL volumes were not significantly different. The sensitivity for the diagnosis of malignant ascites is closely related to the volume of peritoneal fluid that is extracted by peritoneocentesis. Conclusion: We suggest a volume of 200 mL as the optimal minimum volume to confirm malignant ascites in patients with shifting dullness. [ABSTRACT FROM AUTHOR]

Background: Domains of unknown function (DUF) proteins are a number of uncharacterized and highly conserved protein families in eukaryotes. In plants, some DUFs have been predicted to play important roles in development and response to abiotic stress. Among them, DUF568-containing protein family is plant-specific and has not been described previously. A basic analysis and expression profiling was performed, and the co-expression and interaction networks were constructed to explore the functions of DUF568 family in rice. Results: The phylogenetic tree showed that the 8, 9 and 11 DUF568 family members from rice, Arabidopsis and maize were divided into three groups. The evolutionary relationship between DUF568 members in rice and maize was close, while the genes in Arabidopsis were more distantly related. The cis-elements prediction showed that over 82% of the elements upstream of OsDUF568 genes were responsive to light and phytohormones. Gene expression profile prediction and RT-qPCR experiments revealed that OsDUF568 genes were highly expressed in leaves, stems and roots of rice seedling. The expression of some OsDUF568 genes varied in response to plant hormones (abscisic acid, 6-benzylaminopurine) and abiotic stress (drought and chilling). Further analysis of the co-expression and protein–protein interaction networks using gene ontology showed that OsDUF568 − related genes were enriched in cellular transports, metabolism and processes. Conclusions: In summary, our findings suggest that the OsDUF568 family may be a vital gene family for the development of rice roots, leaves and stems. In addition, the OsDUF568 family may participate in abscisic acid and cytokinin signaling pathways, and may be related to abiotic stress resistance in these vegetative tissues of rice. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article by S. Blindbaek and J. Grauslund regarding the prophylactic treatment of retinal breaks.

Based on the characteristics of underdeveloped areas, this paper selects the panel data of 15 underdeveloped counties in Anhui Province from 2013 to 2019 and uses the panel threshold model to empirically analyze the sustainability of rural tourism development. The results show that: (1) Rural tourism development has a non-linear positive impact on poverty alleviation in underdeveloped areas and has a double threshold effect. (2) When the poverty rate is used to express the poverty level, it can be found that the development of rural tourism at a high level can significantly promote poverty alleviation. (3) When the number of poor people is used to express the poverty level, it can be found that the poverty reduction effect shows a marginal decreasing trend with the phased improvement of the development level of rural tourism. (4) The degree of government intervention, industrial structure, economic development, and fixed asset investment play a more significant role in poverty alleviation. Therefore, we believe that we need to actively promote rural tourism in underdeveloped areas, establish a mechanism for the distribution and sharing of rural tourism benefits, and form a long-term mechanism for rural tourism poverty reduction. [ABSTRACT FROM AUTHOR]

Background: The benefit-risk profile of direct oral anticoagulants (DOACs) compared with warfarin, and between DOACs in patients with atrial fibrillation (AF) and chronic liver disease is unclear. Methods: We conducted a new-user, retrospective cohort study of patients with AF and chronic liver disease who were enrolled in a large, US-based administrative database between January 1, 2011, and December 31, 2017. We assessed the effectiveness and safety of DOACs (as a class and individually) compared with warfarin, and between DOACs in patients with AF and chronic liver disease. The primary outcomes were hospitalization for ischemic stroke/systemic embolism and hospitalization for major bleeding. Inverse probability treatment weights were used to balance the treatment groups on measured confounders. Results: Overall, 10 209 participants were included, with 4421 (43.2%) on warfarin, 2721 (26.7%) apixaban, 2211 (21.7%) rivaroxaban, and 851 (8.3%) dabigatran. The incidence rates per 100 person-years for ischemic stroke/systemic embolism were 2.2, 1.4, 2.6, and 4.4 for DOACs as a class, apixaban, rivaroxaban, and warfarin, respectively. The incidence rates per 100 person-years for major bleeding were 7.9, 6.5, 9.1, and 15.0 for DOACs as a class, apixaban, rivaroxaban, and warfarin, respectively. After inverse probability treatment weights, the risk of hospitalization for ischemic stroke/systemic embolism was significantly lower between DOACs as a class (hazard ratio [HR], 0.64 [95% CI, 0.46–0.90]) or apixaban (HR, 0.40 [95% CI, 0.19–0.82]) compared with warfarin, but not significantly different between rivaroxaban versus warfarin (HR, 0.76 [95% CI, 0.47–1.21]) or rivaroxaban versus apixaban (HR, 1.73 [95% CI, 0.91–3.29]). Compared with warfarin, the risk of hospitalization for major bleeding was lower with DOACs as a class (HR, 0.69 [95% CI, 0.58–0.82]), apixaban (HR, 0.60 [95% CI, 0.46–0.78]), and rivaroxaban (HR, 0.79 [95% CI, 0.62–1.0]). However, the risk of hospitalization for major bleeding was higher for rivaroxaban versus apixaban (HR, 1.59 [95% CI, 1.18–2.14]). Conclusions: Among patients with AF and chronic liver disease, DOACs as a class were associated with lower risks of hospitalization for ischemic stroke/systemic embolism and major bleeding versus warfarin. However, the incidence of clinical outcomes among patients with AF and chronic liver disease varied between individual DOACs and warfarin, and in head-to-head DOAC comparisons. [ABSTRACT FROM AUTHOR]

A new facultative anaerobic exoelectrogenic strain LZ-1, belonging to Citrobacter freundii , has been isolated. This strain can produce current densities of 843.9 and 865.6 μA cm −2 using citrate or acetate as carbon source in a three-electrode configuration. The electricity generation performance was also analyzed in a dual-chamber MFC system, reaching a maximum power density of 1233 mW m −2 . In addition to acetate and citrate, other carbon sources such as pyruvate, formate, acetate, citrate and fumarate could also be utilized to produce current by strain LZ-1. Data supports the presence of electroactive c -type cytochromes in C. freundii sp. when grown on ITO electrodes, by linking spectroscopy and electrochemistry in situ . Since facultative strains possess many desirable properties compared to anaerobic strains, strain LZ-1 represents a promising exoelectrogenic species in engineering of biological catalysts for microbial electrochemistry. [ABSTRACT FROM AUTHOR]

Objectives This study aimed to investigate the high-resolution CT (HRCT) characteristics of anti-melanoma differentiation-associated gene 5 (MDA5) antibody positive dermatomyositis-associated interstitial lung disease (anti-MDA5 DM-ILD), and to clarify the underlying mechanisms of the clinical phenomenon. Methods Clinical data and HRCT patterns were compared between anti-MDA5 DM-ILD (n  = 32) and antisynthetase syndrome-associated ILD (ASS-ILD) (n  = 29). RNA sequencing of whole-blood samples from the two groups, and in vitro experiments using human embryonic lung fibroblasts (HELFs) were conducted to explore the potential mechanisms of the clinical findings. Results The anti-MDA5 DM-ILD subset had a significantly higher incidence of rapidly progressive ILD (RPILD) than ASS-ILD (65.6% vs 37.9%; P  = 0.031). The relative percentage of the lung fibrosis HRCT pattern was significantly lower in the anti-MDA5 DM-ILD group, especially the RPILD subgroup (P  = 0.013 and 0.003, respectively). RNA sequencing detected the upregulated genes including interferon-induced helicase C domain 1 (encoding MDA5), and a trend towards downregulated expression of TGF-β signalling components in anti-MDA5 DM-ILD. In vitro culture of HELFs revealed that upregulated expression of MDA5 in HELFs was correlated with the downregulated expression of alpha smooth muscle actin, connective tissue growth factor, collagen I and collagen III by suppressing the TGF-β signalling pathway. Conclusions Anti-MDA5 DM-ILD patients have significantly less lung fibrosis and elevated MDA5 expression. The upregulated expression of MDA5 has relations with the suppression of the pro-fibrotic function of fibroblasts via the TGF-β signalling pathway, which may partially explain the mechanism of the clinical phenomenon. [ABSTRACT FROM AUTHOR]

As energy yields of photovoltaic modules are highly related to local climate and ambient conditions, it is necessary to assess the energy-yield performance of PV modules under various operating conditions. This work compares commercial crystalline silicon (c-Si) based PV modules (including mono c-Si Al BSF, mono c-Si PERC, multi-crystalline (mc-Si) Al BSF, and n-type c-Si solar cells) sampled from 27 PV module manufacturers located in the Asia-Pacific region between 2016 and 2022. Several test items were compared including: (i) light-induced degradation (LID), (ii) irradiance-temperature-efficiency (GTE) matrix, (iii) angular response and (iv) temperature coefficients, which are correspondingly performed according to IEC 61215-1, -1-1, -2 and IEC 61853-1, -2. The coefficient of variation (CoV) was calculated to express the module-to-module differences within similar technology types. Benefiting from the technological innovation of c-Si based PV modules, emerging PV modules feature better performance in some extreme ambient conditions, such as low irradiance, high ambient temperature, and high ratio of diffuse irradiance. The analysis of CoV indicates that the difference of irradiance-dependent and thermal behavior between modules within the same technology may exceed the differences between different technologies. Using synthetic hourly meteorological data of 5 sites from MeteoNorm in PVsyst, the annual specific yield of four technology groups of PV modules were simulated and compared. Overall, it is shown that the maximum differences as large as 7.34% in terms of PV module's specific yield are expected within same PV technology, which exceeds the maximum difference of 2.16% obtained for specific yields of different PV technologies. [ABSTRACT FROM AUTHOR]

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor, or single-disease cases, and it is unclear whether the excellent performance can generalize on diverse datasets. This paper presents a large and diverse abdominal CT organ segmentation dataset, termed AbdomenCT-1K, with more than 1000 (1K) CT scans from 12 medical centers, including multi-phase, multi-vendor, and multi-disease cases. Furthermore, we conduct a large-scale study for liver, kidney, spleen, and pancreas segmentation and reveal the unsolved segmentation problems of the SOTA methods, such as the limited generalization ability on distinct medical centers, phases, and unseen diseases. To advance the unsolved problems, we further build four organ segmentation benchmarks for fully supervised, semi-supervised, weakly supervised, and continual learning, which are currently challenging and active research topics. Accordingly, we develop a simple and effective method for each benchmark, which can be used as out-of-the-box methods and strong baselines. We believe the AbdomenCT-1K dataset will promote future in-depth research towards clinical applicable abdominal organ segmentation methods. [ABSTRACT FROM AUTHOR]

Skeletal muscle fibers contain hundreds of nuclei, which increase the overall transcriptional activity of the tissue and perform specialized functions. Multinucleation occurs through myoblast fusion, mediated by the muscle fusogens Myomaker (MYMK) and Myomixer (MYMX). We describe a human pedigree harboring a recessive truncating variant of the MYMX gene that eliminates an evolutionarily conserved extracellular hydrophobic domain of MYMX, thereby impairing fusogenic activity. Homozygosity of this human variant resulted in a spectrum of abnormalities that mimicked the clinical presentation of Carey-Fineman-Ziter syndrome (CFZS), caused by hypomorphic MYMK variants. Myoblasts generated from patient-derived induced pluripotent stem cells displayed defective fusion, and mice bearing the human MYMX variant died perinatally due to muscle abnormalities. In vitro assays showed that the human MYMX variant conferred minimal cell-cell fusogenicity, which could be restored with CRISPR/Cas9-mediated base editing, thus providing therapeutic potential for this disorder. Our findings identify MYMX as a recessive, monogenic human disease gene involved in CFZS, and provide new insights into the contribution of myoblast fusion to neuromuscular diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] • The PM 2.5 associated premature deaths were estimated to be 965 thousand in 2019 in China. • A range of 816–1304 thousand PM 2.5 associated deaths was projected in 2035 under the indoor guideline of 35 µg/m3. • More stringent policy on indoor PM 2.5 is recommended to bring more benefits. In 2020, China for the first time developed guidelines for indoor fine particulate matter (PM 2.5) in the draft document of indoor air standards, while the associated health implication remains unclear. Here, we first estimated the PM 2.5 associated premature deaths was 965 thousand in 2019, with the indoor PM 2.5 of outdoor origin accounting for 72.9%. Then, we examined the dynamic mortalities under a scenario matrix of 36 conditions, by incorporating various shared socioeconomic pathways in 2035, the draft guidelines and the contributions of ambient PM 2.5 to indoor exposure. Although it may be improbable, the averages of premature deaths associated with ambient PM 2.5 will be 1018–1361 thousand in 2035 when the worst-case scenario of guidelines mandating a yearly (rather than daily) indoor PM 2.5 concentration of 75 µg/m3, compared to the averages of estimation were 816–1304 thousand for better-case scenario of 35 µg/m3. Under these scenarios, the increase in the number of premature deaths was mainly driven by population aging. In 2035, an ambitious target of yearly indoor PM 2.5 concentrations of 15 µg/m3 is anticipated to reduce the number of deaths associated with ambient PM 2.5 by approximately 25% of the 2019 baseline. Stricter guidelines to restrict the indoor PM 2.5 concentrations are recommended to mitigate the mortality risk in the future. [ABSTRACT FROM AUTHOR]

Surface water–groundwater interactions in arid zones are characterized by water exchange processes in a complex system comprising intermittent streams/terminal lakes, shallow aquifers, riparian zone evapotranspiration, and groundwater withdrawal. Notable challenges arise when simulating such hydrological systems; for example, field observations are scarce, and hydrogeological parameters exhibit considerable spatial heterogeneity. To reduce the simulation uncertainties, in addition to groundwater head and river discharge measurements, we adopted remote sensing-based evapotranspiration data and lake area dynamics as known conditions to calibrate the model. We chose the Ejina Basin, located in the lower reaches of the Heihe River Basin in arid northwest China, as the study area to validate our modelling approach. The hydrological system of this basin is characterized by intensive, spatiotemporally variable surface water–groundwater interactions. The areas of the terminal lakes into which all river runoff flows vary significantly depending on the ratio between river runoff and lake evaporation. Simulation results with a monthly time step from 2000 to 2017 indicate that river leakage accounted for approximately 61% of the total river runoff. Our study shows that for areas where surface water and groundwater observations are sparse, combining remote sensing product data of surface water areas and evapotranspiration can effectively reduce the uncertainty in coupled surface water and groundwater simulations. [ABSTRACT FROM AUTHOR]

[Display omitted] • WZ/TCM catalyst was suitable for co-catalytic removal of NO and dioxins. • NH 4 + at the Brønsted sites participated in the reaction at high temperature. • Chlorine atom was removed to reduce toxicity at low temperature. Co-catalytic removal of multiple pollutants was able to reduce operating costs of enterprises, which was the main development direction for the waste incineration industry. In this work, series W-Zr-O x /Ti-Ce-Mn-O x (WZ/TCM) catalysts were designed to investigate independent NH 3 -SCR, dioxins oxidation and co-catalytic removal of NO and chlorobenzene (CB, the substitute of dioxins). The W-Zr-O x mainly provided solid super acids; CeO 2 and MnO 2 enhanced the redox performance; and TiO 2 provided a large specific surface area. All these factors guaranteed the excellent performance of WZ/TCM catalyst. The NO conversion of WZ/TCM reached 100 %, and the oxidation activity of CB was also higher than 85 % at 350–500 ℃. Meanwhile, the WZ/TCM had high N 2 selectivity and excellent resistances to sulfur and water. In situ infrared diffuse reflectance spectra confirmed that ammonia gas mainly adsorbed on the Lewis acidic sites of the WZ/TCM catalyst and participated in the SCR reaction at low temperature. The ammonia species (NH 4 +) at the Brønsted sites participated in the reaction at high temperature. Furthermore, the chlorine atom on the chlorobenzene molecule was mainly removed to reduce toxicity when the oxidation of CB was at low temperature, which was deeply oxidized and had a variety of intermediate products at high temperature. [ABSTRACT FROM AUTHOR]

Transcranial focused ultrasound (FUS) is a noninvasive treatment for brain tumors and neuromodulation. Based on normal incidence, conventional FUS techniques use a focused or an array of ultrasonic transducers to overcome the attenuation and absorption of ultrasound in the skull; however, this remains the main limitation of using FUS. A dual-mode conversion technique based on Lamb waves is proposed to achieve high transmission efficiency. This concept was validated using the finite element analysis (FEA) and experiments based on changes in the incident angle. Aluminum, plexiglass, and a human skull were used as materials with different attenuations. The transmission loss was calculated for each material, and the results were compared with the reflectance function of the Lamb waves. Oblique incidence based on dual-mode conversion exhibited a better transmission efficiency than that of a normal incidence for all of the specimens. The total transmission losses for the materials were 13.7, 15.46, and 3.91 dB less than those associated with the normal incidence. A wedge transducer was designed and fabricated to implement the proposed method. The results demonstrated the potential applicability of the dual-mode conversion technique for the human skull. [ABSTRACT FROM AUTHOR]

• Cumulative and time-lag effects combined impact vegetation activities. • Solar radiation and temperature are the dominant climate factors in taiga and tundra. • The duration of temporal effects corresponds with ecosystem complexity. • The tundra converted to forests caused by warming enhanced the climate temporal effects. The Northern Hemisphere is experiencing amplified warming and greening; however, the responses of greening to warming remain unclear in terms of the cumulative and time-lag effects of climate factors. We chose Siberia, a hotspot in the Northern Hemisphere, as a study area and identified the relationships between the enhanced vegetation index (EVI) and climate factors (e.g., surface temperature, precipitation, and solar radiation) during 2000–2016. In the growing season, the average cumulative duration of the vegetation response to climate factors was 3.6 ± 2.0 months, and the time-lag period was 1.5 ± 1.2 months, with the longest duration in forests and the shortest duration in tundra. Solar radiation was the dominant driver of vegetation greening in 56% of the study area, followed by temperature (41%) and precipitation (3%). In addition, the temporal effects of the climate factors were separated through partial correlation analysis; vegetation responded most rapidly to solar radiation variations with a cumulative duration of 2.2 ± 1.2 months and a time-lag period of 1.8 ± 0.8 months, followed by temperature (2.3 ± 1.3 and 1.9 ± 1.0 months, respectively). Precipitation showed the longest cumulative effect (3.7 ± 1.5 months) and the shortest time-lag effect (1.2 ± 1.1 months). Our results suggest that vegetation activity is influenced by both cumulative and time-lag effects. The temporal effects vary among the land cover categories, and complex ecosystems generally correspond to long-term temporal effects, and vice versa. Thus, the conversion of tundra to boreal forest due to warming in Siberia enhances the temporal effects of climate. These temporal effects could be incorporated into Earth system models to improve our understanding and monitoring of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]