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The World Health Organization (WHO) articulated a vision in 1986, hoping that countries around the world would actively promote the construction and development of healthy cities. In the context of China, a paradigm shift in urban development has been triggered by the deep implementation of the Healthy China Strategy and the gradual completion of the comprehensive national spatial planning. This shift emphasizes a micro-level focus, advocating a human-centered approach to urban space exploration. In this paper, the Dingwangtai Area of Changsha City is selected as a case study. A street space health evaluation index system called “5D+” is constructed from six dimensions, namely, human perception, degree of mixing, density, distance to transit, destination accessibility, and devise. This research adopts the community as the fundamental unit of analysis, employing the Entropy-weighting TOPSIS method for the computation of indicators. The results of this study show that the Dingwangtai Area exhibits relative deficiencies in the dimensions of density, devise, and destination accessibility. Specifically, at the community level, the Ma Wang Street Community and the Fanhou Street Community have scored particularly low. In response, this paper proposes targeted measures and detailed recommendations aimed at optimizing the design of the street, enhancing the human experience, enriching functional attributes, and refining the street network. The ultimate goal is to propose a Healthy Streets Evaluation Index System based on the concept of a healthy city and to explore its relationship with healthy streets so as to provide valuable insights for the development of healthy city streets.

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.

Loop closure detection is an important component of the Simultaneous Localization and Mapping (SLAM) algorithm, which is utilized in environmental sensing. It helps to reduce drift errors during long-term operation, improving the accuracy and robustness of localization. Such improvements are sorely needed, as conventional visual-based loop detection algorithms are greatly affected by significant changes in viewpoint and lighting conditions. In this paper, we present a semantic spatial structure-based loop detection algorithm. In place of feature points, robust semantic features are used to cope with the variation in the viewpoint. In consideration of the semantic features, which are region-based, we provide a corresponding matching algorithm. Constraints on semantic information and spatial structure are used to determine the existence of loop-back. A multi-stage pipeline framework is proposed to systematically leverage semantic information at different levels, enabling efficient filtering of potential loop closure candidates. To validate the effectiveness of our algorithm, we conducted experiments using the uHumans2 dataset. Our results demonstrate that, even when there are significant changes in viewpoint, the algorithm exhibits superior robustness compared to that of traditional loop detection methods.

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.

The stiffness of a long-span cable-stayed bridge under construction may be much lower than that observed in service, making it more susceptible to wind effects, especially for a bridge designed using high piers crossing a deep canyon. To study the buffeting characteristics of such cable-stayed bridges under construction, a long-span cable-stayed bridge (the main span is 575 m) is taken as the engineering background. In this study, the buffeting responses and vibration countermeasures at three different construction states were systematically studied using time-domain analysis. It was found that the buffeting response enlarges with an increase in the wind attack angle. The RMS values of the vertical buffeting of the bridge deck end are relatively greater at the maximum double cantilever construction state and maximum single cantilever state. At maximum double cantilever construction state, the traditional wind-resistant cable connecting the bridge deck end to the bridge pile cap significantly reduces the vertical buffeting response, while the suppression effect on lateral and torsional buffeting is limited. When the bridge deck nears completion, wind-resistant cables installed at both cantilever ending in the ‘soft connection’ method would effectively suppress the vertical, lateral, and torsional buffeting. The suppression effect of cross-arranged wind-resistant cables is superior to that of the parallel arrangement. It is recommended that a reasonable wind-resistant cable layout scheme according to different construction conditions is selected.

This paper proposes an underwater broadband target depth estimation method based on the multipath arrival structure in medium and short-range deep-sea environments. The proposed approach involves separating the multipath rays arriving at the vertical line array using the matched filtering technique. The combined beamforming is then applied to the vector hydrophone vertical array (VHVA) to obtain more accurate elevation angle estimates. The components of the interference sound field at different distances are judged, and the signal received by the array is compensated using suitable estimated angles. Finally, the multipath time delay difference is extracted from the pulse peaks of the compensated signal, and the target depth is estimated by establishing the relationship among the multipath time delay difference, the elevation angle and depth. Simulations and experiments demonstrate the effectiveness of this method in reducing the depth estimation bias and avoiding the misjudgment of surface or submerged targets.

Septic shock management in the cardiac intensive care unit (CICU) is challenging due to the complex interaction of pathophysiology between vasodilatory and cardiogenic shock, complicating how to optimally deploy fluid resuscitation, vasopressors, and mechanical circulatory support devices. Because mixed shock portends high mortality and morbidity, familiarity with quality, contemporary clinical evidence surrounding available therapeutic tools is needed to address the resultant wide range of complications that can arise. This review integrates pathophysiology principles and clinical recommendations to provide an organized, topic-based review of the nuanced intricacies of managing sepsis in the CICU.

As the number of offshore wind turbines continues to rise and their proximity to navigational routes decreases, the risk of collisions between passing vessels and wind turbines increases, thereby presenting serious threats to the safety of personnel and equipment. Given that collisions between floating wind turbines and vessels entail a complex interplay of wind, wave, and mooring loads, this study established a bidirectional fluid-structure coupling simulation methodology based on Star-CCM+ and ABAQUS. Under the combined influences of wind, wave, and mooring loads, the study investigated the dynamic response of floating wind turbines following bow and side impacts from vessels. Analyses were conducted on the structural damage and deformation of floating wind turbines, the transformation of energy during collision processes, and the resultant motion response of the turbines. A sensitivity analysis was performed on parameters such as collision speed, collision angle, wind speed, and wave height. The findings indicate that the amplitude of pitching and heaving motions of the turbine exceed those observed under conditions devoid of collision loads, with the amplitude of motion intensifying with an increase in these parameters. The turbine’s floating body absorbed a minimal amount of internal energy, leading to minor damage, with the stress generated predominantly localized in the collision area of the floating body. The impact of a side collision from vessels exerted a larger influence on the structural dynamic response of floating wind turbines. The analysis results indicate that even though the offshore wind turbine structure is not critically damaged by ship impact, the equipment inside may still fail to work due to the high value of acceleration induced by ship impact. The research outcomes can benefit the safety design of offshore wind turbines in engineering practice.

Assessing Land Use and Land Cover Change (LULCC) related with aquaculture areas is vital for evaluating the impacts of aquaculture ponds on the environment and developing a sustainable aquaculture production system. Most studies analyze changes in aquaculture land in coastal areas, and little research focuses on the inland area, where the conversions between agriculture and aquaculture land is primarily driven by socioeconomic factors. This study assessed LULCC related to aquaculture areas in Qianjiang City, China, from 1990 to 2022, using multitemporal Landsat images and a combination of decision tree classifier and visual interpretation. The LULCC was analyzed by the transition matrix. Results showed that the main LULC type was farmland, which accounted for more than 70% of the study area from 1990 to 2022. The built-up and aquaculture land showed an increasing trend year by year. In contrast, there was a gradual decline in forest/grass land from 1990 to 2016, and then its area increased slightly from 2016 to 2022 due to the policy of returning farmland to forest. Water areas were mainly composed of rivers and ponds, with subtle changes during the study period. The main driving forces of LULCC in Qianjiang City were economic and policy factors, with rapid GDP growth and government policies being the dominant factors.

Promoting the transfer of rural residential land is paramount in enhancing the efficiency of its utilization. The willingness of farmers to transfer rural residential land is influenced by the number of permanent residents. Existing research has drawn different conclusions about the relationship between these two factors, but the differences have not been analyzed. This study is based on survey data collected from our field research in Deqing County, Zhejiang Province, and utilizes the Probit model and threshold effect model to investigate the role of per capita net income in the relationship between the number of permanent residents and the willingness to transfer rural residential land. The results indicate: (1) There is a non-linear impact of the number of permanent residents on the willingness of farmers who are willing to live in rural areas to transfer to their rural residential land with an income threshold. There is a non-linear impact of the number of permanent residents on the willingness of farmers who are willing to live in city areas to transfer out of their rural residential land, with two income thresholds. By comparing with the actual situation, the size and order of the thresholds are scientifically established. (2) The transfer of rural residential land can serve as a supplementary solution to individual household applications for rural residential land, addressing China’s historical legacy issues concerning rural residential land. Considering these findings, policymakers should first actively promote the reform of the rural residential land system while ensuring safeguards for farmers and then work to increase the value of rural residential land. Additionally, they should implement differentiated policies to promote rural residential land transfer. This study can provide a valuable reference for effectively revitalizing idle rural residential land.

Existing deep learning methods usually adopt deeper and wider network structures to achieve better performance. However, we found that this rule does not apply well to crop disease identification tasks, which inspired us to rethink the design paradigm of disease identification models. Crop diseases belong to fine-grained features and lack obvious patterns. Deeper and wider network structures will cause information loss of features, which will damage identification efficiency. Based on this, this paper designs a very lightweight disease identification network called VLDNet. The basic module VLDBlock of VLDNet extracts intrinsic features through 1 × 1 convolution, and uses cheap linear operations to supplement redundant features to improve feature extraction efficiency. In inference, reparameterization technology is used to further reduce the model size and improve inference speed. VLDNet achieves state-of-the-art model (SOTA) latency-accuracy trade-offs on self-built and public datasets, such as equivalent performance to Swin-Tiny with a parameter size of 0.097 MB and 0.04 G floating point operations (FLOPs), while reducing parameter size and FLOPs by 297 times and 111 times, respectively. In actual testing, VLDNet can recognize 221 images per second, which is far superior to similar accuracy models. This work is expected to further promote the application of deep learning-based crop disease identification methods in practical production.

Climate warming globally has a profound effect on the hydrological regime, amplifying evapotranspiration and precipitation and accelerating the processes of snow melt and permafrost thaw. However, in the context of small river basins—those encompassing less than 10,000 km2—the response of the hydrological regime to climate change is intricate and has not yet been thoroughly understood. In this study, the Zhizdra River Basin, a typical small river basin in the eastern European plain with a total drainage area of 6940 km2, was selected to investigate the long-term variability of the hydrological regime and its responses to climate warming. Our results show that during the period of 1958–2016, the average runoff in the Zhizdra River Basin was approximately 170 mm, with significant fluctuations but no trend. Sensitivity analysis by the Budyko framework revealed that the runoff was more sensitive to changes in precipitation (P) compared to potential evapotranspiration (E0), implying that the Zhizdra River Basin is limited by water availability and has a slightly dry trend. A comprehensive analysis based on the seasonality of hydrometeorological data revealed that temperature predominantly affects spring runoff, while P mainly controls autumn runoff. Both factors make significant contributions to winter runoff. In response to climate change, the nonuniformity coefficient (Cv) and concentration ratio (Cn) of runoff have noticeably declined, indicating a more stabilized and evenly distributed runoff within the basin. The insights gleaned from this research illuminate the complex hydrological responses of small river basins to climate change, underlining the intricate interrelation among evapotranspiration, precipitation, and runoff. This understanding is pivotal for efficient water resource management and sustainable development in the era of global warming.

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.

The recognition of sheep faces based on computer vision has improved the efficiency and effectiveness of individual sheep identification, providing technical support for the development of smart farming. However, current recognition models have problems such as large parameter sizes, slow recognition speed, and difficult deployment. Therefore, this paper proposes an efficient and fast basic module called Eblock and uses it to build a lightweight sheep face recognition model called SheepFaceNet, which achieves the best balance between speed and accuracy. SheepFaceNet includes two modules: SheepFaceNetDet for detection and SheepFaceNetRec for recognition. SheepFaceNetDet uses Eblock to construct the backbone network to enhance feature extraction capability and efficiency, designs a bidirectional FPN layer (BiFPN) to enhance geometric location ability, and optimizes the network structure, which affects inference speed, to achieve fast and accurate sheep face detection. SheepFaceNetRec uses Eblock to construct the feature extraction network, uses ECA channel attention to improve the effectiveness of feature extraction, and uses multi-scale feature fusion to achieve fast and accurate sheep face recognition. On our self-built sheep face dataset, SheepFaceNet recognized 387 sheep face images per second with an accuracy rate of 97.75%, achieving an advanced balance between speed and accuracy. This research is expected to further promote the application of deep-learning-based sheep face recognition methods in production.

We have conducted a study on a very-low-frequency acoustic-velocity sensor which is based on a cantilever of distributed-feedback (DFB) fiber laser immersed in castor oil. A mathematical model of the frequency dependent response of the proposed sensor to the acoustic pressure signal influenced by the fluid viscosity is established. We have fabricated the proposed sensor and conducted experimental measurements in the standing wave tube. The results show that the sensor has an average phase sensitivity of −179.5 dB (0 dB = 1 rad/μPa) with ±1.45 dB fluctuation over the frequency range of 20–38 Hz. It has good cosine directivity with a directivity index of 32.5 dB and axial maximum asymmetry of 0.4 dB. The sensor presents promising applications for detecting very-low-frequency underwater acoustic signals.

Pyropia haitanensis, one of the most economically and ecologically important seaweed species, is often exposed to persistent or transient low irradiance (LI), resulting in limited yield and quality. However, the mechanisms mediating P. haitanensis responses to LI are largely unknown. In this study, LI-tolerant (LIT) and LI-sensitive (LIS) P. haitanensis strains were compared regarding their physiological and transcriptomic changes induced by 1 and 4 days of LI (5 μmol photons/m2·s). The results indicated that the inhibition of photomorphogenesis and decreases in photosynthesis and photosynthetic carbon fixation as the duration of LI increased are the key reasons for retarded blade growth under LI conditions. A potential self-amplifying loop involving calcium signaling, phosphatidylinositol signaling, reactive oxygen species signaling, and MAPK signaling may be triggered in blades in response to LI stress. These signaling pathways might activate various downstream responses, including improving light energy use, maintaining cell membrane stability, mitigating oxidative damage, to resist LI stress. Additionally, the LIT strain maintained transcriptional homeostasis better than the LIS strain under LI stress. Specifically, photosynthesis and energy production were relatively stable in the LIT strain, which may help to explain why the LIT strain was more tolerant to LI stress than the LIS strain. The findings of this study provide the basis for future investigations on the precise mechanisms underlying the LI stress tolerance of P. haitanensis.

Multifunctional, integrated, and reusable operating platforms are highly sought after in biochemical analysis and detection systems. In this study, we demonstrated a novel detachable, reusable acoustic tweezer manipulation platform that is flexible and versatile. The free interchangeability of different detachable microchannel devices on the acoustic tweezer platform was achieved by adding a waveguide layer (glass) and a coupling layer (polydimethylsiloxane (PDMS) polymer film). We designed and demonstrated the detachable multifunctional acoustic tweezer platform with three cell manipulation capabilities. In Demo I, the detachable acoustic tweezer platform is demonstrated to have the capability for parallel processing and enrichment of the sample. In Demo II, the detachable acoustic tweezer platform with capability for precise cell alignment is demonstrated. In Demo III, it was demonstrated that the detachable acoustic tweezer platform has the capability for the separation and purification of cells. Through experiments, our acoustic tweezer platform has good acoustic retention ability, reusability, and stability. More capabilities can be expanded in the future. It provides a simple, economical, and multifunctional reusable operating platform solution for biochemical analysis and detection systems.

Researchers increasingly report the therapeutic effect of exosomes derived from rat bone marrow mesenchymal stem cells (Exos-rBMMSC) on liver disease, while the optimal dose of Exos-rBMMSC in liver cirrhotic treatment has not been reported. In this study, we aimed to explore the efficacy and dose of Exos-rBMMSC in a hepatic cirrhosis rat model. The therapeutic effects of a low dose, medium dose and high dose of Exos-rBMMSC were assessed by liver function tests and histopathology. After four-weeks of Exos-rBMMSC therapy, pyroptosis-related expression levels in the medium dose and the high dose Exos-rBMMSC groups were significantly decreased compared to those in the liver cirrhosis group (p < 0.05). The hepatic function assay and histopathology results showed significant improvement in the medium dose and the high dose Exos-rBMMSCs groups. The localization of PKH67-labeled Exos-rBMMSC was verified microscopically, and these particles were coexpressed with the PCNA, NLRP3, GSDMD and Caspase-1. Our results demonstrated that Exos-rBMMSC accelerated hepatocyte proliferation and relieved liver fibrosis by restraining hepatocyte pyroptosis. More importantly, we confirmed that the high dose of Exos-rBMMSC may be the optimal dose for liver cirrhosis, which is conducive to the application of Exos-rBMMSC as a promising cell-free strategy.

The two-stage suspension system (TSSS) is designed for the fiber optic vector hydrophone (FOVH) to isolate the vibration from the mooring rope. The acceleration transmissibility of the TSSS is studied theoretically and experimentally. The results show that the TSSS has a major advantage over the traditional one-stage suspension system (OSSS). Typically, the vibration isolation of the TSSS is demonstrated to be over 25 dB higher than that of the OSSS at 100 Hz. Meanwhile, it is demonstrated that the TSSS has little negative influence on the in-band acceleration response of the FOVH. The TSSS has the prospect of reducing the mechanical noise of the FOVH, which is conducive to suppressing the self-noise and enhancing the ability of weak signal detection.

Modulation instability (MI) is the main limitation factor of the maximum optical power in long-haul phase-sensitive optical time domain reflectometry (Φ-OTDR), and induces signal fading and serious phase noise. In this paper, a method of coherent seed injection is proposed to suppress the MI-induced phase noise in long-haul Φ-OTDR. The spontaneous MI is suppressed by stimulating induced MI in an optical fiber. The visibility of the signal in Φ-OTDR is enhanced and the phase noise is suppressed significantly. This paper offers an effective method to increase the maximum input power with the MI-induced phase noise suppressed in the long-haul Φ-OTDR system. As a result, the maximum input power and sensing distance can be potentially increased, which is greatly beneficial to the enhancement of the performance of long-haul Φ-OTDR.

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.

In order to study the microstructure and properties of stainless steel after laser surface remelting, based on the theory of laser surface remelting, a simulation model of nanosecond-pulsed laser surface remelted stainless steel was established to study the evolution law of the Marangoni force of the molten pool during laser surface remelting. A single-lane laser remelting experiment was performed to study the variation of the scanning speed on the remelting width, roughness, and layer microtopography. The “S” scanning path was used to remelt the stainless steel surface to investigate the bonding force between the remelted layer and the substrate, the hardness, microscopic morphology, and corrosion resistance. The results show that the viscosity of the liquid metal in the molten pool increases with the increase of the scanning speed. Larger liquid viscosity and smaller surface tension temperature gradients promote a weaker flow of liquid metal, which reduces the velocity of the liquid metal flow in the molten pool. With the increase of scanning speed, the remelting width gradually decreases, but the roughness gradually increases. When the element content of Cr increases, the element content of Fe and O decreases. The surface is covered with an oxide film, the main components of which are oxides of Cr and Fe, the remelted layer is greater than that of the substrate, and the corrosion resistance is improved. Laser surface remelting technology can improve the structure and properties of 304 stainless steel.

As a member of the death-associated protein kinase (DAPK) family, STK17B plays an important role in the regulation of cellular apoptosis and has been considered as a promising drug target for hepatocellular carcinoma. However, the highly conserved ATP-binding site of protein kinases represents a challenge to design selective inhibitors for a specific DAPK isoform. In this study, molecular docking, multiple large-scale molecular dynamics (MD) simulations, and binding free energy calculations were performed to decipher the molecular mechanism of the binding selectivity of PKIS43 toward STK17B against its high homology STK17A. MD simulations revealed that STK17A underwent a significant conformational arrangement of the activation loop compared to STK17B. The binding free energy predictions suggested that the driving force to control the binding selectivity of PKIS43 was derived from the difference in the protein–ligand electrostatic interactions. Furthermore, the per-residue free energy decomposition unveiled that the energy contribution from Arg41 at the phosphate-binding loop of STK17B was the determinant factor responsible for the binding specificity of PKIS43. This study may provide useful information for the rational design of novel and potent selective inhibitors toward STK17B.

As a basis for biometric and chemical analysis, issues of how to dilute or concentrate substances such as particles or cells to specific concentrations have long been of interest to researchers. In this study, travelling surface acoustic wave (TSAW)-based devices with three frequencies (99.1, 48.8, 20.4 MHz) have been used to capture the suspended Polystyrene (PS) microspheres of various sizes (5, 20, 40 μm) in sessile droplets, which are controlled by acoustic field-induced fluid vortex (acoustic vortex) and aggregate into clusters or rings with particles. These phenomena can be explained by the interaction of three forces, which are drag force caused by ASF, ARF caused by Leaky-SAW and varying centrifugal force. Eventually, a novel approach of free transition between the particle ring and cluster was approached via modulating the acoustic amplitude of TSAW. By this method, multilayer particles agglomerate with 20 μm wrapped around 40 μm and 20 μm wrapped around 5 μm can be obtained, which provides the possibility to dilute or concentrate the particles to a specific concentration.

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.

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.

Ultraviolet-visible-near infrared broadband photodetectors have significant prospects in many fields such as image sensing, communication, chemical sensing, and day and nighttime surveillance. Hybrid one-dimensional (1D) and zero-dimensional (0D) materials are attractive for broadband-responsive photodetectors since its unique charges transfer characteristics and facile fabrication processes. Herein, a Si/ZnO nanowires/Ge quantum dots photodetector has been constructed via processes that combined electrospinning and spin-coating methods. A broadband response behavior from ultraviolet to near-infrared (from 250 to 1550 nm) is observed. The responsivity of the hybrid structure increases around three times from 550 to 1100 nm compared with the pure Si photodetector. Moreover, when the photodetector is illuminated by a light source exceeding 1100 nm, such as 1310 and 1550 nm, there is also a significant photoresponse. Additionally, the ZnO NWs/Ge quantum dots heterostructure is expected to be used in flexible substrates, which benefits from electrospinning and spin-coating processes. The strategy that combines 1D ZnO NWs and 0D solution-processed Ge QDs nanostructures may open a new avenue for flexible and broadband photodetector.

Bacterial infections in wounded skin are associated with high mortality. The emergence of drug-resistant bacteria in wounded skin has been a challenge. Toluidine blue (TB) is a safe and inexpensive photosensitizer that can be activated and used in near-infrared photodynamic therapy to effectively kill methicillin-resistant Staphylococcus aureus (MRSA). However, its aggregation-induced quenching effect largely affects its clinical applications. In this study, TB nanoparticles (NPs) were synthesized using an ultrasound-assisted coating method. Their physicochemical and biological properties were studied and evaluated by scanning electron microscopy and Fourier-transform infrared spectroscopy. The TBNPs had a broad-spectrum antibacterial activity against Gram-positive bacteria (MRSA) and Gram-negative bacteria (E. coli). In addition, MTT, hemolysis, and acute toxicity tests confirmed that TBNPs had good biocompatibility. The TBNPs exhibited a high photodynamic performance under laser irradiation and efficiently killed E. coli and MRSA through generated reactive oxygen species, which destroyed the cell wall structure. The potential application of TBNPs in vivo was studied using an MRSA-infected wound model. The TBNPs could promote wound healing within 7 days, mainly by reducing the inflammation and promoting collagen deposition and granulation tissue formation. In conclusion, the TBNPs offer a promising strategy for clinical applications against multiple-drug resistance.

Slot filling is a crucial component in task-oriented dialog systems that is used to parse (user) utterances into semantic concepts called slots. An ontology is defined by the collection of slots and the values that each slot can take. The most widely used practice of treating slot filling as a sequence labeling task suffers from two main drawbacks. First, the ontology is usually pre-defined and fixed and therefore is not able to detect new labels for unseen slots. Second, the one-hot encoding of slot labels ignores the correlations between slots with similar semantics, which makes it difficult to share knowledge learned across different domains. To address these problems, we propose a new model called elastic conditional random field (eCRF), where each slot is represented by the embedding of its natural language description and modeled by a CRF layer. New slot values can be detected by eCRF whenever a language description is available for the slot. In our experiment, we show that eCRFs outperform existing models in both in-domain and cross-domain tasks, especially in predicting unseen slots and values.

The incorporation of nonmetal group dopants into a graphitic carbon nitride (g-C3N4) framework is fabricated by adding a small amount of hexamethylenetetramine during the thermal polymerization process. The material shows an excellent visible-light photocatalytic H2 production performance that is eight times higher than bulk g-C3N4. This outstanding performance is ascribed to the introducing of N-doped carbon, which not only enhances the light absorption and favorsa narrower band gap, but also upshifts the conductionband (CB) potential, resulting in a better reduction ability of electrons. This discovery has potential significancefor the designing of high performance, economic, and environmental friendly photocatalyst for solar energy conversion.

Conventional Fused Filament Fabrication (FFF) equipment can only deposit materials in a single direction, limiting the strength of printed products. Robotic 3D printing provides more degrees of freedom (DOF) to control the material deposition and has become a trend in additive manufacturing. However, there is little discussion on the strength effect of multi-DOF printing. This paper presents an efficient process framework for multi-axis 3D printing based on the robot to improve the strength. A multi-DOF continuous toolpath planning method is designed to promote the printed part’s strength and surface quality. We generate curve layers along the model surfaces and fill Fermat spiral in the layers. The method makes it possible to take full advantage of the multi-axis robot arm to achieve smooth printing on surfaces with high curvature and avoid the staircase effect and collision in the process. To further improve print quality, a control strategy is provided to synchronize the material extrusion and robot arm movement. Experiments show that the tensile strength increases by 22–167% compared with the conventional flat slicing method for curved-surface parts. The surface quality is improved by eliminating the staircase effect. The continuous toolpath planning also supports continuous fiber-reinforced printing without a cutting device. Finally, we compared with other multi-DOF printing, the application scenarios, and limitations are given.

In this paper, we propose two control methods for driving a power-assisted cart made for walking assistance for the elderly. The optimal assistance ratio (OAR) and disturbance observer-based (DOB) methods properly adjust the motor output of the cart with high operational efficiency in response to changes in the environment. Healthy subjects walked with the cart on several road surfaces under various conditions, and the experimental results indicate the high operational efficiency of the two proposed methods. Meanwhile, their drawbacks are also discussed herein. The two methods can be used separately or combined according to the application. The OAR method is more suitable for indoor use, while the DOB method is applicable for outdoor applications. Combining these two methods could overcome the mentioned drawbacks.

The gravel packing completion method for horizontal wells has the advantages of maintaining high oil production for a long time, maintaining wellbore stability, and preventing sand production, so it has become the preferred completion method for horizontal wells. At present, this technology still faces the problems of high sand bed height and poor gravel migration. In order to improve the efficiency of gravel packing in horizontal wells, pulsed gravel packing technology for horizontal wells is proposed for the first time. Based on the mechanism of hydraulic pulse, the Eulerian–Eulerian model, k-ε model based on the renormalization group theory (RNG k-ε model), and Fluent are used to simulate the solid-liquid two-phase flow. By optimizing the parameters such as frequency and amplitude of pulse waveform, the optimal pulse waveform of pulsed gravel packing in horizontal wells is determined. The effects of parameters such as sand-carrying fluid displacement, sand-carrying fluid viscosity, sand-carrying ratio, gravel particle size, and string eccentricity on pulsed gravel packing in horizontal wells are studied, and the distribution law of gravel migration velocity and volume fraction in horizontal wells is obtained. According to the results, it can be seen that with the increase of displacement and viscosity of carrier fluid, the volume fraction of fixed bed and moving bed decreases gradually, while that of suspension bed increases gradually. With the increase of sand-carrying ratio, gravel particle size, and string eccentricity, the volume fraction of fixed bed and moving bed increases gradually, while that of suspended bed decreases gradually. Comparing the effects of conventional gravel packing and pulsed gravel packing in horizontal wells, it can be concluded that the efficiency of pulsed gravel packing in horizontal wells is higher. The volume fraction of fixed bed and moving bed decreased by 30% and 40% respectively, while the volume fraction of suspended bed increased by 20%. The migration velocity of moving bed and suspended bed increased by 40% and 25%, respectively, and the migration ability of gravel improved obviously.

This paper introduces a method for the range localization of a moving ship based on the vertical hydrophone line array. The main implementation steps of the proposed algorithm are as follows. First, the stable low-frequency line spectrum component of the broadband radiated noise from the moving ship was extracted through the Detection of Envelope Modulation on Noise (DEMON) spectrum analysis method. Second, the pressure difference between the two different ranges was derived, and the corresponding interference fringes were observed in the plane of time and time interval. Then, the radial velocity of the moving ship could be obtained based on the period of the pattern oscillations of the interference fringes. Further, we estimated the time and range information of the Closest Point of Approach (CPA) and computed the ship range versus time. Finally, each element of the vertical hydrophone line array was processed by the method proposed above, and data fusion technology was adopted to reduce the impact of ineffective elements and improve the range estimation accuracy. The results of the simulation and experiment of a 16-element vertical array performed in the South China Sea verified the effectiveness of the algorithm.

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.

In this paper, we propose a data fusion algorithm based on the weighted histogram statistics (DF-WHS) to improve the performance of direction-of-arrival (DOA) estimation for the vector hydrophone vertical array (VHVA). The processing frequency band is firstly divided into multiple sub-bands, and the high-resolution multiple signal classification (MUSIC) algorithm is applied to estimate the azimuth of each sub-band for each vector hydrophone. Then, the weighted least square (WLS) data fusion technique is used to fuse the sub-band estimation results of multiple sensors. Finally, the weighted histogram statistics method is employed to obtain the synthesis results in the frequency domain. We carried out a simulation and sea trial of the 16-element VHVA to evaluate the performance of the proposed algorithm. Compared to several traditional processing algorithms, the beam width of the proposed approach is significantly narrower, the side lobes are considerably lower, and the mean square error (MSE) is effectively smaller. In addition, the DF-WHS method is more suitable to accurately estimate the target azimuth with a low signal-to-noise ratio (SNR) because the noise sub-band is suppressed in the weighted histogram statistics step. The DF-WHS method in this article provides a new approach to improve the performance of deep-sea target detection for the VHVA.

Self-assembled MnGe quantum dots (QDs) were grown on Si (001) substrates using molecular beam epitaxy with different growth temperatures and Ge deposition thicknesses to explore the interaction among Mn doping, Ge deposition, the formation of intermetallics, and the ferromagnetism of QDs. With the introduction of Mn atoms, the QDs become large and the density significantly decreases due to the improvement in the surface migration ability of Ge atoms. The growth temperature is one of the most important factors deciding whether intermetallic phases form between Mn and Ge. We found that Mn atoms can segregate from the Ge matrix when the growth temperature exceeds 550 °C, and the strongest ferromagnetism of QDs occurs at a growth temperature of 450 °C. As the Ge deposition thickness increases, the morphology of QDs changes and the ferromagnetic properties decrease gradually. The results clearly indicate the morphological evolution of MnGe QDs and the formation conditions of intermetallics between Mn and Ge, such as Mn5Ge3 and Mn11Ge8.

The aging fracture of bonding wire is one of the main reasons for failure of insulated gate bipolar transistor (IGBT). This paper proposes an online monitoring method for IGBT bonding wire aging that does not interfere with the normal operation of the IGBT module. A quantitative analysis of aging degree was first performed, and the results of multivariate and univariate monitoring were compared. Based on the relationship between the monitoring parameters and the aging of the IGBT bonding wire, gradual damage of the IGBT bond wire was implemented to simulate aging failure and obtain the aging data. Moreover, the change of junction temperature was considered to regulate monitoring parameters. Then, the aging degree was evaluated by an artificial neural network (ANN) algorithm. The experimental results showed the effectiveness of the proposed method.

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.

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.

Terracing and vegetation are an effective practice for soil and water conservation on sloped terrain. They can significantly reduce the sediment yield from the surface area, as well as intercept the sediment yield from upstream. However, most hydrological models mainly simulate the effect of the terraces and vegetation on water and sediment reduction from themselves, without considering their roles in the routing process, and thus likely underestimate their runoff and sediment reduction effect. This study added the impact of terraces and vegetation practice on water and sediment routing using the time-area method. The outflow in each travel time zone was revised in each time step by extracting the watershed of the terrace units and the vegetation units and calculating the water or sediment stored by the terraces or held by the vegetation. The revised time-area method was integrated into the Land change Model-Modified Universal Soil Loss Equation (LCM-MUSLE) model. Pianguanhe Basin, in the Chinese Loess Plateau, was chosen as the study area and eight storms in the 1980s and 2010s were selected to calibrate and verify the original LCM-MUSLE model and its revised version. The results showed that the original model was not applicable in more recent years, since the surface was changed significantly as a result of revegetation and slope terracing, while the accuracy improved significantly when using the revised version. For the three events in the 2010s, the average runoff reduction rate in routing process was 51.02% for vegetation, 26.65% for terraces, and 71.86% for both terraces and vegetation. The average sediment reduction rate in routing process was 32.22% for vegetation, 24.52% for terraces, and 53.85% for both terraces and vegetation. This study provides a generalized method to quantitatively assess the impact of terraces and vegetation practice on runoff and sediment reduction at the catchment scale.

NAC transcription factors (TFs) participate in multiple biological processes, including biotic and abiotic stress responses, signal transduction and development. Cold stress can adversely impact plant growth and development, thereby limiting agricultural productivity. Prunus mume, an excellent horticultural crop, is widely cultivated in Asian countries. Its flower can tolerate freezing-stress in the early spring. To investigate the putative NAC genes responsible for cold-stress, we identified and analyzed 113 high-confidence PmNAC genes and characterized them by bioinformatics tools and expression profiles. These PmNACs were clustered into 14 sub-families and distributed on eight chromosomes and scaffolds, with the highest number located on chromosome 3. Duplicated events resulted in a large gene family; 15 and 8 pairs of PmNACs were the result of tandem and segmental duplicates, respectively. Moreover, three membrane-bound proteins (PmNAC59/66/73) and three miRNA-targeted genes (PmNAC40/41/83) were identified. Most PmNAC genes presented tissue-specific and time-specific expression patterns. Sixteen PmNACs (PmNAC11/19/20/23/41/48/58/74/75/76/78/79/85/86/103/111) exhibited down-regulation during flower bud opening and are, therefore, putative candidates for dormancy and cold-tolerance. Seventeen genes (PmNAC11/12/17/21/29/42/30/48/59/66/73/75/85/86/93/99/111) were highly expressed in stem during winter and are putative candidates for freezing resistance. The cold-stress response pattern of 15 putative PmNACs was observed under 4 °C at different treatment times. The expression of 10 genes (PmNAC11/20/23/40/42/48/57/60/66/86) was upregulated, while 5 genes (PmNAC59/61/82/85/107) were significantly inhibited. The putative candidates, thus identified, have the potential for breeding the cold-tolerant horticultural plants. This study increases our understanding of functions of the NAC gene family in cold tolerance, thereby potentially intensifying the molecular breeding programs of woody plants.

Simulating the hydrological processes of an inland river basin can help provide the scientific guidance to the policies of water allocation among different subbasins and water resource management groups within the subbasins. However, it is difficult to simulate the hydrological processes of an inland river basin with hydrological models due to the non-consistent hydrological characteristics of the entire basin. This study presents a solution to this problem with a case study about the hydrological process simulation in an inland river basin in China, Heihe River basin. It is divided into the upper, middle, and lower reaches based on the distinctive hydrological characteristics in the Heihe River basin, and three hydrological models are selected, applied, and tested to simulate the hydrological cycling processes for each reach. The upper reach is the contributing area with the complex runoff generation processes, therefore, the hydrological informatic modeling system (HIMS) is utilized due to its combined runoff generation mechanisms. The middle reach has strong impacts of intensive human activities on the interactions of surface and subsurface flows, so a conceptual water balance model is applied to simulate the water balance process. For the lower reach, as the dissipative area with groundwater dominating the hydrological process, a groundwater modeling system with the embedment of MODFLOW model is applied to simulate the groundwater dynamics. Statistical parameters and water balance analysis prove that the three models have excellent performances in simulating the hydrological process of the three reaches. Therefore, it is an effective way to simulate the hydrological process of inland river basin with multiple hydrological models according to the characteristics of each subbasin.

Online assessment of transient stability of power systems is critical for avoiding blackout. The increasing installation of phasor measurement units in power systems and the advancement of the wide-area measurement systems make it possible to develop methods for online assessment of power systems by using a large amount of real-time synchronous data. In this paper, we propose an approach based on the largest Lyapunov exponent (LLE) for online transient rotor angle stability assessment, using only wide-area measurement systems data. Through establishing a mathematical model that accounts for the LLE value and the rotor speed, as well as analyzing the post-fault phase-plane trajectory, we present a fast stability criterion to determine whether transient instability occurs. The proposed approach is model-free and does not need long-time LLE data to identify the final sign of the LLE. Furthermore, to reduce computational cost and realize online assessment for large-scale power systems, the critical generator pair (CGP) is recognized as the observation for the rotor angle stability assessment, and an effective algorithm for identifying the CGP is presented. Several case studies on the IEEE-39 bus test system and East China power grid are reported to demonstrate the accuracy and effectiveness of the proposed approach.

Inter-basin water transfer projects are designed to relieve water scarcity around the world. However, ecological problems relating to reductions in protection zone functions can occur during inter-basin transfers. This paper uses the largest inter-basin water transfer project in the world, namely, the South-to-North Water Transfer Project (SNWTP) in China, as an example to analyze the variation of Miyun Reservoir’s inner protection zone functions when water is transferred. Specifically, a riparian model (RIPAM) coupled with remote sensing data were used to calculate the nitrogen (N) and phosphorus (P) losses due to plant uptake, and these results were validated by in situ survey data. Then, correlations between water levels and N and P removal were analyzed. The results show that water table disturbances resulting from elevated water levels strongly influence the growth of plants and have obvious negative impacts on N and P removal in the inner protection zone. With the implementation of the middle route of the SNWTP, the water level of Miyun will rise to 150 m in 2020, and subsequently, the total net primary productivity (NPP) could decline by more than 40.90% from the level in 2015, while the N and P uptake could decline by more than 53.03% and 43.49%, respectively, from the levels in 2015, according to the modeling results. This will lead to declines in the inner protection zone’s defense effectiveness for N and P interception and increases in risks to the security of water resources. The results of this study provide useful knowledge for managing the defense function of the terminal reservoir’s inner protection zone and for ensuring that water quality is maintained during the diversion process.

In a district cooling system (DCS), the distribution system (i.e., cooling water system or chilled water system) will continue to be a critical consideration because it substantially contributes to the total energy consumption. Thus, in this paper, a new distributed variable-frequency pump (DVFP) system with water storage (WS) for cooling water is adapted to a DCS with large end-use cooling load fluctuations. The basic principle and energy saving potential of the new system is analyzed. A case study of a DCS with a conventional central circulating pump (CCCP) system is presented to compare the energy consumption and the operating performance of CCCP and DVFP systems that are exposed to various weather conditions. The methods to perform this case study include, cooling load simulation and the modeling of two water distribution networks and systems via several commercial software packages. By replacing the throttling valves with a DVFP, the pump efficiency is increased and transportation energy consumption is reduced. Additionally, by introducing water tank storage, the cooling water is cooled at night and is released at a peak hour during the daytime, thereby further reducing the energy cost. As compared to the field test results of the CCCP system, the daily electrical energy saved by the DVFP and WS system is approximately 57% for a cooling water pump system on the hottest day in summer. This value also corresponds to approximately 10% of the energy saved for the entire system. Furthermore, additional energy could be saved under partial loading conditions.

The water leak-off during hydraulic fracturing in shale gas reservoirs is a complicated transport behavior involving thermal (T), hydrodynamic (H), mechanical (M) and chemical (C) processes. Although many leak-off models have been published, none of the models fully coupled the transient fluid flow modeling with heat transfer, chemical-potential equilibrium and natural-fracture dilation phenomena. In this paper, a coupled thermo-hydro-mechanical-chemical (THMC) model based on non-equilibrium thermodynamics, hydrodynamics, thermo-poroelastic rock mechanics, and non-isothermal chemical-potential equations is presented to simulate the water leak-off process in shale gas reservoirs. The THMC model takes into account a triple-porosity medium, which includes hydraulic fractures, natural fractures and shale matrix. The leak-off simulation with the THMC model involves all the important processes in this triple-porosity medium, including: (1) water transport driven by hydraulic, capillary, chemical and thermal osmotic convections; (2) gas transport induced by both hydraulic pressure driven convection and adsorption; (3) heat transport driven by thermal convection and conduction; and (4) natural-fracture dilation considered as a thermo-poroelastic rock deformation. The fluid and heat transport, coupled with rock deformation, are described by a set of partial differential equations resulting from the conservation of mass, momentum, and energy. The semi-implicit finite-difference algorithm is proposed to solve these equations. The evolution of pressure, temperature, saturation and salinity profiles of hydraulic fractures, natural fractures and matrix is calculated, revealing the multi-field coupled water leak-off process in shale gas reservoirs. The influences of hydraulic pressure, natural-fracture dilation, chemical osmosis and thermal osmosis on water leak-off are investigated. Results from this study are expected to provide a better understanding of the predominant leak-off mechanisms for slickwater fracturing-fluids in hydraulically fractured shale gas reservoirs.

Lake evaporation is a critical component of the hydrological cycle. Quantifying lake evaporation in hyper-arid regions by measurement and estimation can both provide reliable potential evaporation (ET0) reference and promote a deeper understanding of the regional hydrological process and its response towards changing climate. We placed a floating E601 evaporation pan on East Juyan Lake, which is representative of arid regions’ terminal lakes, to measure daily evaporation and conducted simultaneous bankside synoptic observation during the growing season of 2013–2015. A semi-empirical evaporation model derived from Dalton model was parameterized and validated with measured data. The model was then used to estimate lake evaporation during 2002–2015. According to in situ measurements, maximum, minimum and mean lake evaporation were 8.1, 3.7 and 6.5 mm/day, and growing season evaporation was 1183.3 mm (~80% of the annual amount). Adding up non-growing season evaporation that we converted from φ20 pan evaporation at Ejina weather station, the annual mean lake evaporation, 1471.3 mm, was representative of lower Heihe River’s ET0. Model inter-comparison implied our model performed well both in simplicity and accuracy and has potential utilization in a data-sparse area. In 2002–2015, estimated mean daily evaporation was 6.5 mm/day and growing season evaporation was 1233.7 mm. Trend analysis of estimated evaporation proved the evaporation paradox’s existence in this hyper-arid region and validated complementary relationship theory’s adaptability.