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Lake sediments record the environment during the lake sedimentation whose characteristics can infer environmental changes and human activities. In this study, the 210Pb chronologies and sedimentation rate of the sediment core in Honghu Lake were calculated by the Constant Rate of Supply model. The characteristics of the sedimentary environment were analysed by using physical and chemical indicators. Four stages were divided as follows: Stage A (before 1900): The relatively low sedimentation rate and nutrient content indicated an extremely stable sedimentary environment. Stage B (1900–1949): With the growth of population, the intensity of land use began to increase, with an averaged sedimentation rate of 0.252 g·cm−2·a−1. Stage C (1949–1980): The sedimentation rate and nutrient content increased markedly. The intense human activity has damaged the surrounding vegetation leading to soil erosion and accelerated sedimentation rate. With the deterioration of the lake water environment, the organic matter source was mainly the internal source represented by algae and bacteria. Stage D (1980–2011): Influenced by the difference in land use types along the coast, the sedimentation rate of HH-A (0.570 g·cm−2·a−1) is higher than that of HH-B (0.445 g·cm−2·a−1). The results are of significance to the management of rural lakes and reservoirs.

The metallurgical changes and micro defects after welding can influence the mechanical property, corrosion resistance and dimensional stability of the stainless steel wielding joints. It is necessary to explore an effective post-welded method to improve the service performance for stainless steel welding joints. Furthermore, the essential mechanism between microstructure changes and macro-property variation during this process needs deep reveal. Therefore, this paper aims at investigating the effects of different post-weld treatments including naturally aging, artificial aging and cryogenic treatment on the residual stress and mechanical properties of 304 stainless steel weldments. The microstructure evolution was also studied to reveal and establish the microstructure-performance relationship. The results showed that the distribution of residual stress was most uniform with lowest magnitude (decreased by up to 49%) after cryogenic treatment. At room temperature, weldments subjected to the three post treatments showed similar mechanical properties. At cryogenic temperature, cryogenic treatment exhibited an outstanding role on maintaining the mechanical properties of weldments. By contrast, the mechanical properties were obviously reduced by artificial aging. The transformation of δ-ferrite and the carbide precipitation in grain boundaries are the main reasons for the decrease of mechanical properties after artificially aging. Welding process was able to cause the transfer of the alloying elements and decrease the stability of austenite. Consequently, martensitic transformation can be induced during cryogenic treatment. The new formed martensite resulted in the refined microstructure and high mechanical properties of weldments, and also the release of residual stress after welding.

In order to accurately assess the risk of the hybrid AC/DC network under fault, a risk assessment method for the hybrid AC/DC system based on the transient energy function is proposed. First, based on the energy transfer relationship of the hybrid AC/DC power system, the transient energy function model of the hybrid AC/DC system is established. Based on the operating data of the power grid, the energy function is used as an efficiency variable, and the efficiency variable is integrated into the prior risk probability calculation of nodes in the network, and a Bayesian network-based risk assessment model of hybrid AC/DC system is established. Considering the dynamic update model of network cascading failures, the clique tree propagation algorithm is used to dynamically calculate the posterior risk probability of the node to realize the dynamic assessment of the network risk. Finally, the improved IEEE-39 node hybrid AC/DC system is used as an example for analysis. The results show that the proposed model can not only effectively evaluate the overall safety of the network, but also has feasibility in predicting faults, which can provide a theoretical basis for the stability control of the hybrid AC/DC system.

Electrochemical biosensors have emerged as powerful tools for the ultrasensitive detection of lung cancer biomarkers like carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and alpha fetoprotein (AFP). This review comprehensively discusses the progress and potential of nanocomposite-based electrochemical biosensors for early lung cancer diagnosis and prognosis. By integrating nanomaterials like graphene, metal nanoparticles, and conducting polymers, these sensors have achieved clinically relevant detection limits in the fg/mL to pg/mL range. We highlight the key role of nanomaterial functionalization in enhancing sensitivity, specificity, and antifouling properties. This review also examines challenges related to reproducibility and clinical translation, emphasizing the need for standardization of fabrication protocols and robust validation studies. With the rapid growth in understanding lung cancer biomarkers and innovations in sensor design, nanocomposite electrochemical biosensors hold immense potential for point-of-care lung cancer screening and personalized therapy guidance. Realizing this goal will require strategic collaboration among material scientists, engineers, and clinicians to address technical and practical hurdles. Overall, this work provides valuable insight for developing next-generation smart diagnostic devices to combat the high mortality of lung cancer.

MXene (Ti3C2Tx) is a promising electrode material for supercapacitors. However, the current MXene material preparation process often requires hydrofluoric acid, and the etched MXene is easily oxidized and stacked, which is not conducive to the transfer of electrons and ions. In this study, we proposed a high concentration of sodium hydroxide solution mixed with sodium hypochlorite solution as an etchant for the preparation of fluorine-free MXene (Ti3C2Tx). Based on the alkali-assisted hydrothermal method, Ti3AlC2 was used as the raw material, and 10 % NaClO aqueous solution was added as the oxidant during the etching process to accelerate the etching and in-situ generate TiO2 with excellent conductivity. When the oxidation time is 12 h and the amount of NaClO is 0.2 mL, the TiO2 particles in-situ generated by the oxidation of Ti element in MXene are evenly distributed on the surface and interlayer of the material, which effectively curbs the stacking problem between the Ti3C2Tx layers and improves the specific surface area of the material. The prepared MXene/TiO2 electrode in 1 M H2SO4 electrolyte, − 0.5–0.2 V voltage window, the highest mass specific capacity can reach 321F/g, and after 10,000 charge–discharge cycles, the capacitance retention rate can still reach 86.4 %, which is higher than the capacitance retention rate of Ti3C2Tx material (81.7 %).

The Augmented Transformer U-Net (AugTransU-Net) is proposed to address limitations in existing transformer-related U-Net models for brain tumor segmentation. While previous models effectively capture long-range dependencies and global context, these works ignore the hierarchy to a certain degree and need more feature diversity as depth increases. The proposed AugTransU-Net integrates two advanced transformer modules into different positions within a U-shaped architecture to overcome these issues. The fundamental innovation lies in constructing improved augmentation transformer modules that incorporate Augmented Shortcuts into standard transformer blocks. These augmented modules are strategically placed at the bottleneck of the segmentation network, forming multi-head self-attention blocks and circulant projections, aiming to maintain feature diversity and enhance feature interaction and diversity. Furthermore, paired attention modules operate from low to high layers throughout the network, establishing long-range relationships in both spatial and channel dimensions. This allows each layer to comprehend the overall brain tumor structure and capture semantic information at critical locations. Experimental results demonstrate the effectiveness and competitiveness of AugTransU-Net in comparison to representative works. The model achieves Dice values of 89.7%/89.8%, 78.2%/78.6%, and 80.4%/81.9% for whole tumor (WT), enhancing tumor (ET) and tumor core (TC) segmentation on the BraTS2019-2020 validation datasets, respectively. The code for AugTransU-Net will be made publicly available at https://github.com/MuqinZ/AugTransUnet.

The two-dimensional thermodynamically consistent phase field model, which consists of the anisotropic Allen-Cahn type equation and the heat equation, is used to study the morphological pattern of the particle in the initial stage of crystal growth. The results reveal the locally reversible growth of the particle in the initial stage of crystal growth. Specifically, some parts of the particle interface first grow inward, while others grow outward from the interface of critical nucleation, until the growth speed of the interface becomes zero. After this, the inward growth parts start to grow outward with other parts. The locally reversible growth of the particle leads to the development of a petal-like shape. The particle radius size dependence of the temperatures along the parts of the particle interface in different crystallographic directions at different time points is studied. By a series of results, the correlations between the morphological pattern selection of the particle and the model parameters, including undercooling and anisotropic strength, are analyzed. These results contribute to understanding the fundamental mechanism of the particle evolution during crystal growth.

IntroductionAutism Spectrum Disorder (ASD) has a significant impact on the health of patients, and early diagnosis and treatment are essential to improve their quality of life. Machine learning methods, including multi-classifier fusion, have been widely used for disease diagnosis and prediction with remarkable results. However, current multi-classifier fusion methods lack the ability to measure the belief level of different samples and effectively fuse them jointly.MethodsTo address these issues, a multi-classifier fusion classification framework based on belief-value for ASD diagnosis is proposed in this paper. The belief-value measures the belief level of different samples based on distance information (the output distance of the classifier) and local density information (the weight of the nearest neighbor samples on the test samples), which is more representative than using a single type of information. Then, the complementary relationships between belief-values are captured via a multilayer perceptron (MLP) network for effective fusion of belief-values.ResultsThe experimental results demonstrate that the proposed classification framework achieves better performance than a single classifier and confirm that the fusion method used can effectively fuse complementary relationships to achieve accurate diagnosis.DiscussionFurthermore, the effectiveness of our method has only been validated in the diagnosis of ASD. For future work, we plan to extend this method to the diagnosis of other neuropsychiatric disorders.

Currently, impacts of rapid cropland reclamation and its intense structural changes in internal paddy-upland on ecosystem service are insufficient in Sanjiang Plain, China. Further, land management systems of Sanjiang Plain consist of state-owned and private farms; however, exploring the impact of different land management systems on “land use–landscape–ecosystem service” is still lacking. To reveal this issue, the integrated methodology of “land dynamic tracking–landscape index–improved ecosystem service assessment” was established. Results are displayed below: From 1990 to 2020, land use was featured by decreases in forest (−3308.62 km2), grassland (−6030.86 km2), waters (−475.81 km2), and unused land (−3037.27 km2), with a slight increase in constructed land (+403.25 km2) and a rapid increase in cropland (+12,447.56 km2). Although nearly equal increments of cropland on state-owned and private farms (i.e., 6156.70 km2 vs. 6290.86 km2) were monitored, different cropland structure changes were still revealed, namely a drastic expansion of paddy fields (13,788.32 km2) and an acute decrease in upland crops (−7631.62 km2) on state-owned farms, but both a slight increments in paddy fields (5920.08 km2) and upland crops (370.78 km2) on private farms. For landscape, private farms were more fragmented (SHDI = +0.63%), causing a decrease in aggregation (AI = −0.56%) and a more complex shape (LSI = +23.3%), by contrast, state-owned farms displayed an increased integrity (SHDI = −9.88%), along with an increase in aggregation (AI = +0.43%) and simplified shape (LSI = −13.30%). Evaluated ecosystem service value changed from 338.62 to 296.25 billion yuan from 1990 to 2020, a loss rate of 12.58% in Sanjiang Plain. Then, a new finding showed a higher loss rate on state-owned than private farms (i.e., 30.15% vs. only 6.18%). This study revealed differentiated processes of “land use–landscape–ecosystem service” in different land management system regions in China, providing new findings in the fields of land management system, ecological landscape, and environment.

Supply chain coordination has been a research hot spot in supply chain management. This paper constructs a secondary supply chain system. Taking the abatement of the bullwhip effect and the double marginal effect as the coordination objective, a simulation study of supply chain decision coordination was conducted using system dynamics. First, by controlling the lead time, it was found that in the decentralized decision-making model, the profit of the supplier and the whole supply chain increases with the shortening of the lead time, and vice versa for the retailer. In the centralized decision-making model with the addition of information sharing and contract, it was found that the retailer’s profit is consistent with the trend of the supplier and the supply chain as a whole, and the supplier’s profit is lower than that of decentralized decision making in the pre-cooperation period. In addition, it is also found that adjusting the contract parameters can effectively improve the situation. Finally, the above models were analyzed for supply chain coordination decisions based on two scenarios: “cooperative stability” or “balance of effects”.

The effects of post-weld aging and cryogenic treatment on self-fusion welded austenitic stainless steel thick plates were investigated in the present work. The results showed that fusion zone microstructure consisted of austenite matrix and vermicular ferrite. Aging treatment promoted the decomposition of δ-ferrite into σ-ferrites as well as the precipitation of carbides. Isothermal martensitic transformation in the Tungsten Inert Gas Welding (TIG) specimen was induced by cryogenic treatment, and stacking faults were increased. The fusion zone microstructure of Electron Beam Welding (EBW) and Laser Welding (LW) was finer than that of TIG, with acicular ferrite distributed in the austenite matrix. A large number of twins were generated in the austenite matrix after LW. Cryogenic treatment produced a large number of sub-grains in LW specimens, which was due to the entanglement and accumulation of dislocations in the vicinity of ferrite. Post-weld aging and cryogenic treatment have no influence on the strength of weldments with different welding methods while cryogenic treatment could improve the impact toughness of EBW and LW weldments by the extent of 7.4% and 8.8%, respectively. The aging treatment reduced the impact toughness by 49%, 33% and 15.5%, as well as the uniform elongation by 44%, 39% and 17% for TIG, EBW and LW, respectively. Aging treatment reduced the surface residual stress of TIG weldment by 58.8% in Y direction and 61.2% in X direction. Cryogenic treatment at could also release the surface residual stress of TIG weldment by 36.8% in X direction and 16.3% in Y direction.

In recent years, significant oil and gas discoveries have been achieved in the Permian Upper Wuerhe Formation and the Triassic Baikouquan Formation on the marginal slope of oil generation sag, Junggar Basin. However, in the central sag of the basin, no oil or gas show has been discovered in target formations, and low production has been made only by two wells. As a result, it is necessary to deepen the understanding of the mechanisms of oil and gas accumulation and clarify the main controlling factors. The analyses of the accumulation conditions in the central sag and some wells show that the direct reason for the failure to find oil and gas in the sag is the lack of local source-connecting faults and poor reservoir properties. An accumulation model with source in the lower section and reservoir in the upper section controlled by both source-connecting faults and favorable sand bodies was established for the Permian and Triassic strata in the sag. The sandbody lithologic reservoirs of fan-delta front subfacies in the Upper Wuerhe and Baikouquan formations under the background of stratigraphic overlap are the primary direction of exploration, covering an area about 3 600 km2. The comprehensive exploration of unconventional oil and gas in the Middle-Lower Permian source rocks and conventional oil and gas in multiple layers outside the source area should be targeted.

Study region: This study interrogates a landslide in ice-rich permafrost region in the Eastern Qinghai–Tibet Plateau, China. Study focus: Climate warming has increased the frequency and intensity of rainfall events, changing hydrothermal processes and the soil mechanical properties, thus affecting slope stability in permafrost region. The purpose of this paper is to elucidate the variations in soil volumetric water content (VWC) which may influence the mechanical properties of unstable slopes in ice-rich permafrost region under different rainfall conditions. New hydrological insights for the region: This paper integrates the rainfall infiltration boundary conditions and Mohr–Coulomb criterion into a thermo–hydro–mechanical (THM) model and analyzes a landslide case in the permafrost regions. The results show that the THM model can effectively account for the impacts of VWC variation under different rainfall conditions. The influence of rainfall on the VWC diminishes as depth increases, with a more pronounced effect observed at depths less than 1 m. At depths exceeding 1 m, the impact is relatively minor. Under the condition of low-intensity, long-duration rainfall, with accumulated precipitation exceeding 60 mm, the cohesion and internal friction angle decrease to 4.2kPa and 8.1°, respectively, with a deep-layer integral slippage. In contrast, under the condition of high-intensity, short-term rainfall, the accumulated rainfall exceeds 75 mm and the internal friction angle decreases from 39° to 26°, with shallow-layer slippage. The results add on to our understanding engineering problems and periglacial geomorphic processes under the influence of climate warming.

Rapid advancements in construction technologies have accelerated the development of complex and deep underground structures, raising concerns about the impact of groundwater on structures, particularly anti-floating measures. Traditional tensioned anchors, commonly used for preventing flotation, suffer from limitations like low pull-out bearing capacity, shallow critical anchoring depth, and localized stress concentration. To overcome these limitations, this paper introduces a tension–compression dispersed composite anchor, which combines casing, load-bearing plates, and tensioned anchors. Comparative tests were conducted between these composite anchors and traditional tensioned anchors to analyze their anchoring behavior. Our results show that tensioned anchors exhibit a stable axial force distribution as anchoring length increases. By identifying abrupt changes in the axial force curve, optimal anchoring lengths for load-dispersed anchors can be determined, thereby enhancing rock and soil strength utilization. The tension–compression-dispersed composite anchor outperforms tensioned anchors, with 1.44 times the ultimate bearing capacity for equivalent anchoring lengths and 1.1 times the capacity for an additional 1 m length. It also displays superior deformation adaptability and structural ductility under high-bearing loads compared to tensioned anchors with extended anchoring lengths. Effectively mobilizing the strength of the lower anchoring segment within the rock and soil results in a lower critical anchoring depth and a more uniform distribution of lateral friction resistance. In conclusion, the tension–compression-dispersed composite anchor offers significant advantages, making it a promising engineering solution for anti-floating anchor systems in complex underground environments.

We consider the Cox–Ingersoll–Ross (CIR) model in time-dependent domains, that is, the CIR process in time-dependent domains reflected at the time-dependent boundary. This is a very meaningful question, as the CIR model is commonly used to describe interest rate models, and interest rates are often artificially set within a time-dependent domain by policy makers. We consider the most fundamental question of recurrence versus transience for normally reflected CIR process with time-dependent domains, and we examine some precise conditions for recurrence versus transience in terms of the growth rates of the boundary. The drift terms and the diffusion terms of the CIR processes in time-dependent domains are carefully provided. In the transience case, we also investigate the last passage time, while in the case of recurrence, we also consider the positive recurrence of the CIR processes in time-dependent domains.

Carbon molecular deposition in sediments removes organic carbon (OC) from the biosphere-atmosphere carbon cycle and therefore limits the emission of greenhouse gases (i.e. CH4 and CO2) from natural water systems. At present, the occurrence characteristics, deposition fluxes, and driving force of OC components in the river-lake ecotone are unclear. Here, the tempo-spatial distribution of polycyclic aromatic hydrocarbons (PAHs) and Σn-alkanes (nC13–nC32) related to organic nitrogen (ON) and OC in the estuarine sediments from Poyang Lake and their sources and effects were investigated. The ON and OC contents in the sediment cores ranged from 0.35−0.64 % and 1.9–4.24 %, respectively, and the PAH fluxes varied between 672.19 and 24703.97 ng cm−2 a-1, showing an upward risk to the water bodies and human health. In particular, it is worth noting that the 5–6 ring monomers were dominant, accounting for 66.48 % of the ΣPAHs in the sediment profile. The sources were mainly derived from biomass combustion and automobile exhaust emissions, while the latter proportion has increased in recent decades. In the sediment profile, the n-alkane abundance peak was found at nC31 with a marked odd-even predominance. The deposition flux for Σn-alkanes ranged between 10.92 and 73.46 μg cm−2 a-1. In addition, long-chain monomers dominated the Σn-alkanes and were found to be herbaceous in origin. An analysis of the environmental indicators in the sediment layers showed that forest restoration and the eutrophication of water bodies caused by anthropogenic stress and climate change were mainly responsible for the relatively large contribution made by vascular plants and autochthonous organisms.

Abstract To study the spatial occurrence, sources, and ecological risks of 16 PAHs, surface sediments had been collected from seven major areas of Taihu Lake, China in April 2021. Results showed that the concentrations of ∑16PAHs varied between 1381.48 and 4682.16 ng g−1, and the contents of BghiP in each sample were the highest. The PAHs concentrations in the sediments near the lakeshore were much higher than those in the central area of the lake. The sedimentary ∑16PAHs were mainly composed of molecular-weight monomers and 4-ring PAHs showed superiority (35.69–45.02%). According to the ratio of PAH monomer, the sedimentary PAHs in Taihu Lake were dominantly derived from the combustion. Through the biological toxicity assessment and the BaP equivalent (BaPE), great biological risks of PAHs monomers i.e. DahA and IcdP were found. Both concentrations of ∑16PAHs and dominant 4–6-ring monomers accompanied by carcinogenic risks in many areas of Taihu Lake increased. It is necessary to strengthen monitoring and take measures to control the input of organic pollutants.

Carbon burial in lake sediments has a profound impact on the global carbon cycle. In this study, the burial characteristics of organic carbon (OC) in typical sediments from the Poyang basin over the past hundred years were investigated and the influencing factors and driving mechanism were determined. The results showed that carbon burial in the Poyang basin sediments was mainly driven by human activities, whereas the change in the OC accumulation rate was related to precipitation, forest land area, water area, construction land area, urbanization rate, application of agricultural fertilizers, per capita GDP and population.

(1) Objective: to accelerate the digitalization of the elderly care service industry and the construction of the smart elderly care industry, this paper designs an intelligent e-procurement system for elderly suppliers selecting from the perspective of smart elderly care, which can enhance the efficiency of elderly care supply chains and assist manufacturers of elderly products in choosing a reliable, high-quality supplier during trades. (2) Methods: the e-procurement system, including six modules, is built with an improved dynamic Markov Decision Process selection model combined with an Analytic Network Process, bringing dynamic evolution of both inventory cost and purchasing cost into long-term reward calculation, and taking into account 15 common indexes and 7 specific indexes when evaluating suppliers’ competitiveness. (3) Results: a real sample shows that when facing 50 suppliers with 50 different quotations, the e-procurement system selects a stable and reliable supplier that brings the best long-term profits for demand enterprises in ten purchase periods, and it makes the selecting process more efficient and more prompt. (4) Conclusions: the model can be used in the circumstance where an elderly product producer is forced to decide on a long-term strategy or reselect a new stable supplier since it is focused on choosing long-term and high-quality suppliers over numerous periods.

The rapid economic development in the Yangtze River Delta has affected the carbon (C) pool in lake sediments, which has become a serious environmental management issue. To explore the characteristics of composition, spatial distribution and burial of organic C (OC) in lacustrine sediments, a typical shallow lake was targeted to compare the heavy fraction OC (HFOC), light fraction OC (LFOC), and dissolved OC (DOC) in the surface sediments of different lake areas using the specific gravity separation approach. The effects of environmental factors on the form of OC present were identified by a redundancy analysis. The results showed a regional difference of DOC, LFOC, and HFOC concentrations in Taihu Lake, and HFOC was dominant in the OC buried in lake sediments. The deposition rate of OC in Taihu Lake sediments varied in a ranged of 31.91–114.47 g C m−2 a-1. The LFOC levels in the sediments were lower than those in other lakes. Both sedimentary LFOC and HFOC were significantly correlated with the nitrogen (N) content, indicating that the C sink was enhanced by an increase in N in the sediments. The grass-type lake zone stimulated C accumulation in Taihu Lake sediments.

Aluminum matrix composites have been widely used in aerospace and automotive fields due to their excellent physical properties. Cryogenic treatment was successfully adopted to improve the performance of aluminum alloy components, while its effect and mechanism on the aluminum matrix composite remained unclear. In this work, the effects of cryogenic treatment on the microstructure evolution and mechanical properties of 15%SiCp/2009 aluminum matrix composites were systematically investigated by means of Thermoelectric Power (TEP), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The results showed that TEP measurement can be an effective method for evaluating the precipitation characteristics of 15%SiCp/2009 aluminum matrix composites during aging. The addition of cryogenic treatment after solution and before aging treatment promoted the precipitation from the beginning stage of aging. Furthermore, the aging time for the maximum precipitation of the θ″ phase was about 4 h advanced, as the conduction of cryogenic treatment accelerates the aging kinetics. This was attributed to the great difference in the linear expansion coefficient between the aluminum alloy matrix and SiC-reinforced particles, which could induce high internal stress in their boundaries for precipitation. Moreover, the lattice contraction of the aluminum alloy matrix during cryogenic treatment led to the increase in dislocation density and micro defects near the boundaries, thus providing more nucleation sites for precipitation during the aging treatment. After undergoing artificial aging treatment for 20 h, the increase in dispersive, distributed precipitates after cryogenic treatment improved the hardness and yield strength by 4% and 16 MPa, respectively.

The Qinghai-Tibetan Plateau (QTP) has undergone an increase in rainfall and a drastic alteration in the moisture-heat regime in active layers and engineering. To investigate the water and heat responses of natural ground and engineering to rainfall, the differences in energy on the ground surface and the thermal-moisture dynamics of different permafrost underlying surfaces were discussed. Based on the meteorological data in 2013 observed at the Beiluhe observation station, three types of underlying surfaces (i.e., natural ground, asphalt pavement, and gravel pavement) were selected to compare the differences in energy balance at the ground surface, water-energy transport process, and coupling mechanism in active layers under rainfall conditions by a coupled water vapor-heat model of the unsaturated frozen soil. The results show that the asphalt pavement greatly increases the surface net radiation and soil surface heat flux, decreases the surface evaporation latent heat, and cuts off the moisture migration between the atmosphere and the active layer. The gravel pavement significantly increases the surface evaporation latent heat to lower the soil surface heat flux, and the amount of moisture in shallow soil is strongly influenced by rainfall and evaporation. Therefore, the moisture migration and accumulation under the asphalt pavement are dominated by the water vapor flux under thermal gradients, whereas the liquid water under the water potential gradients is the major source of moisture migration under the gravel pavement. The heat transfer in the shallow active layer is dominated by heat conduction. The effect of heat conduction, water vapor migration, and phase transition on the soil temperature is evident for the asphalt pavement, while the impact of liquid water migration on the shallow soil temperature for the gravel pavement is significant in the thawing period. As a result, the soil temperature relationship between different underlying surfaces is asphalt pavement>gravel pavement>natural ground. The thickness of the active layer gradually decreases. Although rainfall infiltration promotes the liquid water convection of the gravel pavement, the decrease in heat flux is less than the increase in thermal conductivity. In general, the construction of asphalt pavement and gravel pavement accelerates the degradation of permafrost. The results can provide theoretical and simulated guidance for the stability prediction and analysis of various underlying surfaces in the central QTP where rainfall is increasing.

Special environmental condition with strong wind and large diurnal temperature range is not conducive for the control of crack development during the curing of mass concrete in the cold environment of Northwest China. In this study, the temperature at four measured points along the vertical profile of a mass concrete was measured over 14 days. Then, a thermal-mechanical model with the optimized initial condition, thermal parameters, boundary conditions, and the effects of rebar on temperature stress of concrete was built. Based on the observations and numerical model, the effects of environmental factor on the peak temperature, temperature fluctuation amplitude, and maximum temperature stress of the mass concrete are analyzed. The result showed that increasing wind speed can reduce the temperature of the concrete, but an opposite result is observed with increase in diurnal temperature range. Moreover, the more obvious diurnal variation of concrete temperature with the increase in wind speed and diurnal temperature range is not conducive to the thermal stability of the structure, especially for horizontal and side surfaces. Accordingly, increasing wind speed and diurnal temperature range will increase the peak temperature stress of the concrete and the overall stress level. Strong wind and large diurnal temperature range significantly increase the temperature stress and its duration for the side surface. The high temperature stress and intensive daily variation of temperature stress at the horizontal surface affect the durability of the concrete material. Therefore, the temperature stresses of the horizontal surface under wind speed levels 3, 4, 5, and 1.25 times large diurnal temperature range easily exceed the tensile strength; then, the temperature crack will appear. Combined with the research results, the temperature control and crack prevention measures are proposed under the condition of ensuring concrete strength. The study will further guide the improvement and optimization of mass concrete construction in an extreme environment.

Objective: To investigate the clinical utility of ultrasound-guided balloon occlusion in cesarean section in patients with sinister placenta previa. Methods: The Interventional and Ultrasound Departments of the authors’ center assisted obstetrics to complete cesarean section in cases of sinister placenta previa. A total of 130 patients with implanted sinister placenta previa were diagnosed using obstetrical ultrasound and magnetic resonance imaging (MRI). Before cesarean section, the balloon was positioned in the bilateral radial or abdominal aorta. Immediately after delivery of the fetus, the balloon was temporarily filled to transiently seal the target vessel. According to the obstetrician’s assessment of hemostasis, the balloon was withdrawn at the appropriate time. Among the 130 patients, there was one case of abdominal aortic occlusion, with 129 cases blocked by the bilateral common iliac artery. Results: All 130 cases were successfully blocked, with an average blocking time of

To improve the visual quality of noisy medical images acquired by low radiation dose imaging, medical image denoising is highly desirable for clinical disease diagnosis. In this paper, a geometric regularization method is proposed for medical image denoising. To the best of our knowledge, this is the first work aiming at reconstructing surface by minimizing the gradient error and approximation error of the surface to suppress the noise in medical images. The proposed denoising method consists of two stages: one is to output a basic estimate and the other is for the residual noise reduction. Specifically, the method first exploits a biquadratic polynomial surface to generate an initial estimate of the noise-free image. The surface is constructed by dividing its coefficients into two groups. With the reconstruction error constraint, one group is used to minimize the gradient of the surface, and the other is to minimize the approximation accuracy of the surface. Then the residual noise in the initial result is further reduced by using the singular value thresholding mechanism, which exploits the self-similarity of medical images and the intrinsic low-rank property. Unlike the traditional truncated singular value thresholding scheme, the proposed singular value thresholding is derived by optimizing an objective function with a constraint. Experimental results on a real clinical data set demonstrate the effectiveness of the proposed denoising method, especially in detail-preserving. Compared with several widely used denoising methods, our method can achieve a better performance in terms of both quantitative metrics and subjective visual quality.

Convolutional neural networks (CNNs) require large amounts of data for training, beyond what can be acquired for current radiomics models. We hypothesize that deep entropy features (DEFs) derived from existing CNNs can be applied to MRI images of prostate cancers (PCa) to reliably predict the Gleason score (GS) of PCa lesions. In this study, we analyzed 112 lesions acquired from 99 PCa patients, either pre-biopsy or pre-treatment, their associated GS, and multi-parametric MRI (mpMRI) sequences. Our approach is based on the extraction of DEF features produced in individual layers of 9 pre-trained CNN models. We first analyze DEFs from separate CNNs using the Wilcoxon test and Spearman correlation to find significant features associated with GS. In a multivariate analysis, we then use the combined DEFs of all CNNs as input to a random forest (RF) classifier for predicting the Gleason grade group of patients. Among the 9 pre-trained CNNs, the NASNet-mobile architecture offered the features most correlated to GS ( $\rho =0.47$ ; p < 0.05). From the 7,857 combined features, 11 DEFs could differentiate GS < 8 from GS ≥8 (corrected p < 0.05). Moreover, the RF classifier discerned GS of 6, 3+4, 4+3, 8 and ≥9 with an AUC (%) of 80.08, 85.77, 97.30, 98.20, and 86.51, respectively. Our results suggest that the DEFs can be used to differentiate GS of PCa lesions with the highest accuracy of GS ≥8 based on mpMRI. DEFs could improve diagnosis accuracy, reduce the risks of misclassification, help to better assess prognosis, and individualize patient care approaches.

The regional multi-energy system (RMES) can realize the coupling and complementation of different energy sectors, including electricity, heat, and gas, with the advantage of energy cascade utilization. With the development of hydrogen fuel cell vehicle (FCV) technology, hydrogen has great application potential in the transportation sector. The use of surplus electricity to produce hydrogen through water electrolysis technology can increase renewable energy penetration in power systems. This paper proposed an optimal design and operation method of RMES that considers system reliability constraints under different-level renewable energy penetrations. The RMES includes renewable generation devices, conversion devices such as fuel cells and electric boilers, and emerging devices such as electrolysis cells and hydrogen storage tanks. In order to improve the reliability of the planning results, we consider the reliability constraints of crucial devices in the planning model. In addition, we paid attention to the potential of hydrogen storage tanks for inter-seasonal energy complementation. In the solution of the model, the optimization model can be transformed into a mixed-integer linear programming (MILP) problem by linearizing the non-linear constraints, which can be directly solved by CPLEX, showing good performances in practical applications. Finally, case studies are performed to show the superiority of the planning model.

This paper focused on three application problems of the traditional Deep Deterministic Policy Gradient(DDPG) algorithm. That is, the agent exploration is insufficient, the neural network performance is unsatisfied, the agent output fluctuates greatly. In terms of agent exploration strategy, network training algorithm and overall algorithm implementation, an improved DDPG method based on double-layer BP neural network is proposed. This method introduces fuzzy algorithm and BFGS algorithm based on Armijo-Goldstein criterion, improves the exploration efficiency, learning efficiency and convergence of BP neural network, increases the number of layers of BP neural network to improve the fitting ability of the network, and adopts periodic update to ensure the stable operation of the algorithm. The experimental results show that the deep learning network based on the improved DDPG algorithm has greatly improved the performance compared with the traditional method after multiple rounds of self-learning under variable working conditions. This study lays a theoretical and experimental foundation for the extended application of deep learning algorithm.

Improving the accuracy and speed of integrated energy system load forecasting is a great significance for improving the real-time scheduling and optimized operation of the integrated energy system. In order to achieve rapid and accurate forecasting of the integrated energy system, this paper proposes an adaptive integrate energy system (IES) load forecasting method based on the octopus model. This method uses long short-term memory (LSTM), support vector machines (SVMs), restricted Boltzmann machines (RBMs), and Elman neural network as the octopus model quadrupeds. Through taking over differences in different data and training principles and utilizing the advantages of the octopus quadruped model, a special octopus-head and XGBoost algorithm were adopted to set the weight of the octopus’ quadruped and prevent local minimum points in the model. We train the octopus model through RMSProp adaptive learning algorithm, constrain the learning rate, get the best parameters, and improve the model’s adaptability to different types of data. In addition, for the incomplete comprehensive energy load data, the generative confrontation network is used to fill it. The simulation results show that compared with other prediction methods, the effectiveness and feasibility of the method proposed in this paper are verified.

The extensive anthropogenic activities and their potential impacts on lakes during the Anthropocene could be recorded in the sediments. In this study, the composition of biomarkers (i.e., n-alkanes and n-fatty acids), total organic carbon (TOC), and particle size in 210Pb-dated sediment cores from West Dongting Lake were investigated to trace the historical trend of anthropogenic inputs and their environmental significance. The TOC content was in the range of 3.15–27.32 mg g−1. The n-alkanes and n-fatty acids were distributed from C11–C33 and C12:0–C34:0, respectively. The short- and long-chain biomarkers accounted for a significant proportion of the total. Aquatic plants and algae living in West Dongting Lake were the main source (short-chain) followed by leaf waxes derived from terrestrial C3 plants (long-chain), as demonstrated by their concentrations. The variations of the key indicators i.e., the carbon preference index (CPI), aquatic plant n-alkane proxy (Paq), vascular plant n-alkane proxy (Pwax), and the ratio of unit short- to long-chain n-alkanes (L/H) also indicated that the aliphatic hydrocarbon fractions were mainly composed of short- and long-chain biomarkers. The sedimentary biomarkers had a significant temporal heterogeneity, which was controlled by different factors and sedimentary processes. Fine particles (

The rapid increase in the proportion of the elderly population in China has increased the demand for aged services. It is a huge challenge for the Chinese government to establish the aged service system to meet such a large demand in a short time. In its 14th Five-Year Development plan, to promote a more rational allocation of health services, the Chinese government plans to build a health service system for the elderly. Based on the aged service resource allocation model established in the previous research, this paper proposes optimization measures and improves the model. The second-order matrix sensitivity analysis is performed on 30 parameters in the improved model, and the influence law of parameters on the whole system under a different amplitude of variation is explored. The results show that the disability rate of the elderly population, the service capacity of aged service institutions, per capita disposable income, and other factors have a great impact on the balance between the supply and demand of aged service resources. Therefore, when formulating policies related to the allocation of aged service resources, we can focus on improving the health level of the elderly, increasing the investment of social funds in aged service, and improving people’s consumption levels, so as to further improve the aged service system.

The annual electricity trade scheduling is the basis of long-term power generation scheduling. In recent decades, the ratio of new energy generation in China has increased annually, and the electricity market has operated under the “market electricity” and “planned electricity” double track mode in recent years. However, the existing annual electricity trade scheduling methods are extensive and cannot adapt to the new situation of “market electricity” and large-scale new energy generation. The annual scheduled energy of the power units is set as a decision variable, and a novel annual energy scheduling optimization model based on Gini coefficient of fairness is presented in this paper. In this model, “market electricity” capacity is conversed monthly, considering peaking reserve demand and monthly characteristics of new energy generation. The fairness constraint set based on Gini coefficient is introduced into the optimization model to solve various fairness problems. Simulation results show that the introduction of the Gini coefficient and the optimization model considering the monthly conversion of marketing electricity capacity can obtain more accurate and reasonable electricity distribution results, and the peaking demand can be considered more fairly and effectively. The proposed method provides a feasible solution to the annual electric energy scheduling for dual-track operation country such as China.

Lung cancer remains the leading cause of cancer mortality worldwide. Small cell lung cancer (SCLC) accounts for 10–15% of cases and has an overall 5-years survival rate of only 15%. Neuron-specific enolase (NSE) has been identified as a useful biomarker for early SCLC diagnosis and therapeutic monitoring. This work reports an electrochemical immunosensing platform based on a graphene-graphitic carbon nitride (g-C3N4) nanocomposite for ultrasensitive NSE detection. The g-C3N4 nanosheets and graphene nanosheets were synthesized via liquid exfoliation and integrated through self-assembly to form the nanocomposite. This nanocomposite was used to modify screen-printed carbon electrodes followed by covalent immobilization of anti-NSE antibodies. The unique properties of the graphene-g-C3N4 composite facilitated efficient antibody loading while also enhancing electron transfer efficiency and electrochemical response. Systematic optimization of experimental parameters was performed. The immunosensor exhibited a wide linear detection range of 10 pg/mL to 100 ng/mL and low limit of detection of 3 pg/mL for NSE along with excellent selectivity against interferences. Real serum matrix analysis validated the applicability of the developed platform for sensitive and accurate NSE quantifica-tion at clinically relevant levels. This novel graphene-g-C3N4 nanocomposite based electro-chemical immunoassay demonstrates great promise for early diagnosis of SCLC. [ABSTRACT FROM AUTHOR]

Natural images often have self-similarity, which can be used to remove noise. Therefore, many current denoising methods denoise by processing similar image block matrix. Aiming at the problem that these methods will destroy the two-dimensional structure of image blocks when they are expanded into one-dimensional column vectors, a new image denoising method based on high-order singular value decomposition is proposed. Several similar image blocks are stacked into three-dimensional arrays and treated as a third-order tensor; then, higher-order singular value decomposition can be performed. For the core tensor obtained by decomposition, an iterative algorithm with adaptive hard threshold coefficient shrinkage is proposed. The experimental results show that the proposed method outperforms the state-of-the-art methods in peak-signal-to-noise ratio, structural similarity, and visual effects.

With the rapid growth of the elderly population of China in recent years, the service demands of older Chinese people continue to increase. The increasingly severe situation with respect to the elderly population is an important social problem that China will face for a long time into the future. It is urgent to solve the problem of how to scientifically carry out allocation planning of service resources for the aged and guide the effective supply of service resources. This paper analyzes the factors affecting service resources for the aged, divides China’s service resource supply and demand system into a supply subsystem, a demand subsystem, and a population and economy subsystem. Using system dynamics methods to analyze the causal relationship between variables and the state space method to build a mathematical model and perform simulation analysis, we research the the current situation of China’s service resources supply and demand balance for the aged. In addition, we put forward resource configuration optimization measures for the future allocation of service resources for the aged, providing a practical basis for future decision-making.

As a promising method with excellent characteristics in terms of resilience and dependability, distributed methods are gradually used in the field of energy management of microgrid. However, these methods have more stringent requirements on the working conditions, which will make the system more sensitive to communication failures and cyberattacks. As a result, it is both theoretical merits and practical values to investigate the malicious effect of cyber attacks on microgrid. This paper studies the distributed economic dispatch problem (EDP) under denial-of-service (DoS) attacks for the microgrid, in which each generator can communicate with its neighbors and has the computational capability to implement local operation. Firstly, a DoS attack model is proposed, in which the DoS attacker intentionally jams the communication channel to deteriorate the performance of the microgrid. Then, the evolution mechanism of the dispatch system of the microgrid under different attack scenarios is adequately discussed. On this basis, an optimal attack strategy based on enumerating-search algorithm is presented to allocate the limited attack resources reasonably, so as to maximize the effect of DoS attacks. Finally, the validity of the theoretical studies about the attack effect under different scenarios and the effectiveness of the proposed enumerating-search-based optimal attack strategy are illustrated through the simulation examples on the IEEE 57-bus system and IEEE 39-bus system, respectively.

Estuarine zones are regarded as the ecotones connecting the rivers and lakes. Sediment dredging is a conventional treatment technology that is widely used to remove the internal loading in estuarine zones worldwide. However, what is the characteristic of nutrient release in the gate-controlled estuary and how long this practice is effective are still unclear. Hence, sediment and water samples were collected from dredged and undredged regions around the gate-controlled estuary of northern Taihu Lake for laboratory experiments, in which they were subjected to different temperatures, depths, and disturbance levels. The total nitrogen (TN) and total phosphorus (TP) concentrations of the dredged region were lower than those from the undredged region under stable hydrodynamic conditions. A high dynamic release rate (R) of nutrients in the dredged sediments (RTN = 164.75 mg/m2·d and RTP = 5.83 mg/m2·d) existed under dynamic release conditions (stirring speeds: 90 and 120 r/min). The effect of disturbance and temperature on release rate and nutrient form was completely different for the static and dynamic release cases. The nutrient loads from dynamic release were 4–17 times greater than those from static release. For unstable hydrodynamic conditions, the release rate from the bottom sediment exceeded that from the surface sediment in the undredged region. These results indicated that, under stable hydrodynamic conditions, dredging improves long-term water quality. However, dredging alone in unstable hydrodynamic conditions may not remove the potential risk of internal release in the long term. Specific ecological and engineering measures should be combined with dredging practice to restore estuary habitats and minimize the release of internal pollutants.

Freeze-thaw cycles can significantly change the hydrologic and thermal state of slopes in cold regions and affect their stability. Landslides occur continuously in the slip area of seasonally frozen soil area during the freezing period. The freeze-thaw action and the difference in the characteristics of the underlying surface of the slope are important factors inducing landslides. Taking Heifangtai slope in Gansu Province as an example, the freezing-thawing characteristics of the slope surfaces under different underlying surface conditions were analyzed by field monitoring. A thermohydromechanical coupling model was established to reconstruct the frozen stagnant water process of the Heifangtai landslide zone, and the impact of freeze-thaw action on the loess landslide zone was studied. The results show that differences in the underlying surface led to different freezing-thawing characteristics between the unsaturated area and the groundwater overflow zone. During the freezing period, the soil freezing depth was greater, and the freezing duration was longer in the unsaturated area. The frozen stagnant water effect of the Heifangtai loess landslide zone is obvious. The maximum difference in the groundwater level between February and August could reach nearly 1 m. Meanwhile, the frozen stagnant water process of the Heifangtai landslide zone has a slip-promoting action on the slope. The factor of safety declined during the freezing period and increased during the thawing period. It reached a minimum of 1.42 in February.

Accurate prediction of individuals’ brain age is critical to establish a baseline for normal brain development. This study proposes to model brain development with a novel non-negative projective dictionary learning (NPDL) approach, which learns a discriminative representation of multi-modal neuroimaging data for predicting brain age. Our approach encodes the variability of subjects in different age groups using separate dictionaries, projecting features into a low-dimensional manifold such that information is preserved only for the corresponding age group. The proposed framework improves upon previous discriminative dictionary learning methods by incorporating orthogonality and non-negativity constraints, which remove representation redundancy and perform implicit feature selection. We study brain development on multi-modal brain imaging data from the PING dataset (N = 841, age = 3−21 years). The proposed analysis uses our NDPL framework to predict the age of subjects based on cortical measures from T1-weighted MRI and connectome from diffusion weighted imaging (DWI). We also investigate the association between age prediction and cognition, and study the influence of gender on prediction accuracy. Experimental results demonstrate the usefulness of NDPL for modeling brain development.

Secondary prevention is an important strategy in gastric cancer. Low-grade intraepithelial neoplasia (LGIN) is the last stage of precancerous lesion, and its timely diagnosis can greatly improve the detection rate of early gastric cancer. We performed a prospective study to analyze the risk factors of gastric LGIN in asymptomatic subjects undergoing physical examination. A total of 3437 subjects were included in this study, and 2259 asymptomatic subjects were investigated from March 2015 to April 2018. Risk factors were evaluated, and the endoscopic features of LGIN and prognosis were described. The overall incidence of LGIN was 19.73% (678/3437), while the incidence of LGIN in the asymptomatic and symptomatic groups was 19.65% (444/2259) and 19.86% (234/1178), respectively (P=0.884). The rate of Helicobacter pylori infection in this physical examination population was 39.13% (35.8% asymptomatic group, 45.5% symptomatic group; P≤0.001). Risk factors including age, H. pylori infection, history of antibiotic misuse, and spicy and high-fat diet (all P

Based on specimens from twenty-one herbaria from China and USA, as well as observations using SEM, the genus Botrydium is resurrected as Neobotrydium. It has a number of distinctive characters: the plants are covered with granular hairs and granulated globular gland-grains, strong smell, and dichasia. Neobotrydium is removed from Chenopodium. The differences between Neobotrydium and Chenopodium, as well as circumscriptions of five glandular genera, Neobotrydium, Cycloloma, Roubieva, Ambrina, and Dysphania are discussed. Neobotrydium comprises twenty species which occur in Asia, Europe, North Africa, North America to Northwest of South America and Australia. Four new species are described: Neobotrydium corniculatum and Neobotrydium ornithopodum from China, Neobotrydium peruensis from South America, and Neobotrydium burundiensis from Africa. A diagnostic key is presented.

Abstract Since the first intercalation of layered silicates by using supercritical CO2 as a processing medium, considerable efforts have been dedicated to intercalating and exfoliating layered two‐dimensional (2D) materials in various supercritical fluids (SCFs) to yield single‐ and few‐layer nanosheets. Here, recent work in this area is highlighted. Motivating factors for enhancing exfoliation efficiency and product quality in SCFs, mechanisms for exfoliation and dispersion in SCFs, as well as general metrics applied to assess quality and processability of exfoliated 2D materials are critically discussed. Further, advances in formation and application of 2D material–based composites with assistance from SCFs are presented. These discussions address chemical transformations accompanying SCF processing such as doping, covalent surface modification, and heterostructure formation. Promising features, challenges, and routes to expanding SCF processing techniques are described.

Sub-synchronous oscillation may occur when the wind-thermal-bundled system sent out via AC/DC transmission (WTBH) is integrated in power grid. Causing large-scale wind-turbine tripping, even lead the system to collapse. First, in this study the mechanism of sub-synchronous oscillation of this system is analysed. Second, the influencing factors such as the ratio of the wind-thermal-bundled installed capacity, the series compensation parameters of AC transmission line, the different operating conditions of wind power etc., are analysed, which can cause different degree impact on the sub-synchronous oscillation. Finally, the system is simulated under the Power Systems Computer Aided Design (PSCAD) environment. The results show that under the same conditions, the higher series compensation, the greater transmission capacity of the AC line, the greater risk of the sub-synchronous oscillation. Under the condition of full load, the greater proportion of installed capacity of Doubly fed Induction Generator (DFIG) is, the less risk of sub-synchronous oscillation; Under the lower wind speed condition, reducing the number of wind turbine can eliminate the risk of sub-synchronous oscillation, and the oscillation frequency vary with the number of wind turbine.

Tugarinovia (Family Asteraceae) is a monotypic genus. It's sole species, Tugarinovia mongolica Iljin, is distributed in the northern part of Inner Mongolia, with one additional variety, Tugarinovia mongolica var ovatifolia, which is distributed in the southern part of Inner Mongolia. The species has a limited geographical range and declining populations. To understand the phylogeographic structure of T. mongolica, we sequenced two chloroplast DNA regions (psbA-trnH and psbK-psbI) from 219 individuals of 16 populations, and investigated the genetic variation and phylogeographic patterns of T. mongolica. The results identified a total of 17 (H1-H17) chloroplast haplotypes. There were no haplotypes shared between the northern (T. mongolica) and southern groups (T. mongolica var. ovatifolia), and they formed two distinct lineages. The regional split was also supported by AMOVA and BEAST analyses. AMOVA showed the main variation that occurred between the two geographic groups. The time of divergence of the two groups can be dated to the early Pleistocene epoch, when climate fluctuations most likely resulted in the allopatric divergence of T. mongolica. The formation of the desert blocked genetic flow and enhanced the divergence of the northern and southern groups. Our results indicate that the genetic differences between T. mongolica and T. mongolica var. ovatifolia are consistent with previously proposed morphological differences. We speculate that the dry, cold climate and the expansion of the desert during the Quaternary resulted in the currently observed distribution of extant populations of T. mongolica. In the northern group, the populations Chuanjinsumu, Wuliji and Yingen displayed the highest genetic diversity and should be given priority protection. The southern group showed a higher genetic drift (FST = 1, GST = 1), and the inbreeding load (HS = 0) required protection for each population. Our results propose that the protection of T. mongolica should be implemented through in situ and ex situ conservation practices to increase the effective population size and genetic diversity.

Climatic fluctuations during the Quaternary significantly affect many species in their intraspecific divergence and population structure across northwest China. In order to investigate the impact of climate change on herbaceous plants, we studied Panzerina lanata (Lamiaceae), a widely distributed species. Sequences of two chloroplast DNA (cpDNA) intergenic spacers (trnH-psbA and rpoB-trnC) and a nuclear ribosomal region (nrDNA, ITS) were generated from 27 populations of Panzerina lanata and resulted in the identification of seven chloroplast haplotypes and thirty-two nuclear haplotypes. We applied AMOVA, neutrality test and mismatch distribution analysis to estimate genetic differentiation and demographic characteristics. The divergence times of the seven cpDNA haplotypes were estimated using BEAST. Our results revealed high levels of genetic diversity (cpDNA: Hcp = 0.6691, HT = 0.673; nrDNA: Hnr = 0.5668, HT = 0.577). High level of genetic differentiation (GST = 0.950) among populations was observed in the cpDNA sequences, while the genetic differentiation values (GST = 0.348) were low in nuclear sequences. AMOVA results revealed major genetic variation among the three groups: northern, central, and eastern group. However, the genetic differentiation in ITS data was not found. The species distribution modeling and demographic analysis indicated that P. lanata had not experienced recent range expansion. The occurrence of divergence between seven cpDNA haplotypes, probably during Pleistocene, coincides with aridification and expansion of the desert across northwest China that resulted in species diversification and habitat fragmentation. In addition, we discovered that the deserts and the Helan Mountains acted as effective geographic barriers that promoting the intraspecific diversity of P. lanata.

The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor’s grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa’s grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.