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To address the key problems in the application of intelligent technology in geothermal development, smart application scenarios for geothermal development are constructed. The research status and existing challenges of intelligent technology in each scenario are analyzed, and the construction scheme of smart geothermal field system is proposed. The smart geothermal field is an organic integration of geothermal development engineering and advanced technologies such as the artificial intelligence. At present, the technology of smart geothermal field is still in the exploratory stage. It has been tested for application in scenarios such as intelligent characterization of geothermal reservoirs, dynamic intelligent simulation of geothermal reservoirs, intelligent optimization of development schemes and smart management of geothermal development. However, it still faces many problems, including the high computational cost, difficult real-time response, multiple solutions and strong model dependence, difficult real-time optimization of dynamic multi-constraints, and deep integration of multi-source data. The construction scheme of smart geothermal field system is proposed, which consists of modules including the full database, intelligent characterization, intelligent simulation and intelligent optimization control. The connection between modules is established through the data transmission and the model interaction. In the next stage, it is necessary to focus on the basic theories and key technologies in each module of the smart geothermal field system, to accelerate the lifecycle intelligent transformation of the geothermal development and utilization, and to promote the intelligent, stable, long-term, optimal and safe production of geothermal resources.

The proven geological reserves of the Shenfu deep coalbed methane (CBM) field on the eastern margin of the Ordos Basin exceed 100 billion cubic meters. It is of great significance to realizing the efficient development of deep CBM in this region to ensure the national energy supply. However, the complexity of the geological environment which includes high stress, medium-high temperatures, low permeability, strong heterogeneity, and wide developed cleats and natural fractures, makes it challenging for the existed shallow and medium CBM fracturing techniques to be fully applicable to deep CBM resources. As a result, the stimulation scale and parameters for deep coalbed fracturing are still in the trial-and-error stage. In order to explore the stimulation techniques which are compatible with the geological conditions of deep coalbeds, the Shenfu block in the Ordos Basin was taken as the geological background and the large-scale hydraulic fracturing of deep coal seams was conducted as an engineering practice. The authors designed the idea of “Push the limit to the beyond + balanced propagation + effective support”, and proposed the massive hydraulic fracturing techniques based on “multi-stage multi-clusters with moderate-dense cutting + perforation with equal apertures, deep penetration and limited flow + integrated variable viscosity (rock breaking by higher viscous slick water + complex fracture network generating by lower viscous slick water) + high pumping rate with high proppant concentration + pre-acid treatment to reduce the breakdown pressure + graded proppants with multiple sizes to support fractures”. Then, the authors put forward an integrated “Geology-Engineering-AI” workflow to perform post-frac analysis, through double matching and correcting the fracturing pumping pressure and production rate automatically, accurately characterized the stimulated reservoir volume (SRV) and drained rock volume (DRV), and predicted the estimated ultimate recovery (EUR) under different fracturing scales and well types. Finally, by statistically analyzing the gas production characteristics of multiple wells in the Shenfu block and utilizing the random forest method, the primary controlling factors affecting the production capacity of deep CBM were quantitatively analyzed. The results demonstrate that after reservoir stimulation, directional wells can achieve a maximum daily gas production rate exceeding 10 000 m3/d, while horizontal wells can achieve a maximum daily gas production rate exceeding 20 000 m3/d. It indicates that the deep coal beds have good fracturing properties and great development potential. The primary impact factors for peak gas production rate are gas content, coalbed thickness and proppant concentration, while the major impact factors for cumulative gas production include gas content, proppant concentration, and total volume of proppants.

Abstract Background There is insufficient research on how gender-affirming hormone therapy (GAHT) affects body fat modifications in transwomen from China. It is unclear whether hormone therapy affects the prevalence of obesity and blood lipid levels within this population. The current research aimed to assess how GAHT and treatment duration had an impact on the change in and redistribution of body fat in Chinese transwomen. Methods This study included 40 transwomen who had not received GAHT and 59 who had. Body fat, blood lipid, and blood glucose levels were measured. GAHT is mainly a pharmacologic (estrogen and anti-androgen) treatment. The study also stratified participants based on the duration of GAHT to assess its impact on body fat distribution. The duration of GAHT was within one year, one to two years, two to three years, or more than three years. Results After receiving GAHT, total body fat increased by 19.65%, and the percentage of body fat increased by 17.63%. The arm, corrected leg, and leg regions showed significant increases in fat content (+ 24.02%, + 50.69%, and + 41.47%, respectively) and percentage (+ 25.19%, + 34.90%, and + 30.39%, respectively). The total visceral fat content decreased (-37.49%). Based on the diagnostic standards for a body mass index ≥ 28 or total body fat percentage ≥ 25% or 30%, the chance of developing obesity did not change significantly. Blood glucose levels significantly increased (+ 12.31%). Total cholesterol levels (-10.45%) decreased significantly. Fat changes in those who received GAHT for one to two years were significantly different from those who did not receive GAHT. Conclusion After receiving GAHT, total body fat and regional fat increased in Chinese transwomen, and the body fat distribution changed from masculine to feminine, especially during the first two years. However, neither the increase in total body fat percentage nor the decrease in visceral fat content didn’t bring about significant changes in the incidence of obesity, nor did triglycerides or low-density lipoprotein-cholesterol.

Deep reinforcement learning (DRL) methods have emerged as a feasible solution for addressing the power resource allocation problem in ultra-dense small-cell networks (UDSCNs). In this paper, we propose a novel actor-critic-based low-coupling policy optimization (LCPO) framework. Our framework aims to achieve practicality by employing a design that consists of training and execution modules with low coupling. By adopting policy optimization methods, including advantage actor-critic (A2C) and proximal policy optimization (PPO) with state-dependent exploration (SDE) technique, LCPO demonstrates stable performance. In this study, we define the research problem of power resource allocation in UDSCNs and present the mathematical algorithm employed in the LCPO framework. We compare the performance of LCPO with other algorithms, such as deep deterministic policy gradient (DDPG) and fractional programming (FP) algorithms. Through extensive simulations, our proposed LCPO framework outperforms DDPG and FP algorithms in terms of both performance and execution time. Furthermore, to provide an up-to-date overview of the current state-of-the-art, we incorporate recent research papers in the field. The inclusion of these papers enhances the relevance of our study and allows readers to gain insights into the latest advancements in power resource allocation in UDSCNs. The results of our research highlight the effectiveness of the LCPO framework in addressing the power resource allocation problem in UDSCNs. The proposed framework offers superior performance compared to existing algorithms, making it a promising solution for optimizing power allocation in UDSCNs.

Graph convolutional networks (GCN) have been widely utilized in Alzheimer's disease (AD) classification research due to its ability to automatically learn robust and powerful feature representations. Inter-patient relationships are effectively captured by constructing patients magnetic resonance imaging (MRI) data as graph data, where nodes represent individuals and edges denote the relationships between them. However, the performance of GCNs might be constrained by the construction of the graph adjacency matrix, thereby leading to learned features potentially overlooking intrinsic correlations among patients, which ultimately causes inaccurate disease classifications. To address this issue, we propose an Alzheimer's disease Classification network based on MRI utilizing diffusion maps for multi-scale feature fusion in graph convolution. This method aims to tackle the problem of features neglecting intrinsic relationships among patients while integrating features from diffusion mapping with different neighbor counts to better represent patients and achieve an accurate AD classification. Initially, the diffusion maps method conducts diffusion information in the feature space, thus breaking free from the constraints of diffusion based on the adjacency matrix. Subsequently, the diffusion features with different neighbor counts are merged, and a self-attention mechanism is employed to adaptively adjust the weights of diffusion features at different scales, thereby comprehensively and accurately capturing patient characteristics. Finally, metric learning techniques enhance the similarity of node features within the same category in the graph structure and bring node features of different categories more distant from each other. This study aims to enhance the classification accuracy of AD, by providing an effective tool for early diagnosis and intervention. It offers valuable information for clinical decisions and personalized treatment. Experimentation on the publicly accessible Alzheimer's disease neuroimaging initiative (ADNI) dataset validated our method's competitive performance across various AD-related classification tasks. Compared to existing methodologies, our approach captures patient characteristics more effectively and demonstrates superior generalization capabilities.

Objectives This study aimed to evaluate the effectiveness of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) in predicting 24-hour in-hospital mortality among patients aged 65 years and older with isolated traumatic brain injury (TBI).Design A retrospective, single-centre cohort study.Setting This study was conducted at a government-run tertiary comprehensive hospital.Participants This study included 982 patients aged 65 years or older with isolated TBI, who were admitted to the emergency department between 1 January 2020 and 31 December 2021.Interventions None.Primary outcome 24-hour in-hospital mortality was the primary outcome.Results Among the 982 patients, 8.75% died within 24 hours of admission. The non-survivors typically had higher TRIAGES and lower GCS scores. Logistic regression showed significant associations of both TRIAGES and GCS with mortality; the adjusted ORs were 1.98 (95% CI 1.74 to 2.25) for TRIAGES and 0.72 (95% CI 0.68 to 0.77) for GCS. Receiver operating characteristic (ROC) analysis indicated an area under the ROC curve of 0.86 for GCS and 0.88 for TRIAGES, with a significant difference (p=0.012). However, precision–recall curve (PRC) analysis revealed an area under the PRC of 0.38 for GCS and 0.47 for TRIAGES, without a significant difference (p=0.107).Conclusions The TRIAGES system is a promising tool for predicting 24-hour in-hospital mortality in older patients with TBI, demonstrating comparable or slightly superior efficacy to the GCS. Further multicentre studies are recommended for validation.

The Tibetan Plateau is a pristine environment with limited human disturbance, with its aerosol microbiome being primarily influenced by the monsoon and westerly circulations. Additionally, the diversity and abundance of airborne microorganisms are also affected by anthropogenic activities, such as animal farming, agriculture, and tourism, which can lead to increased risks to the ecosystem and human health. However, the impact of anthropogenic activities on airborne microbes on the Tibetan Plateau has been rarely studied. In this work, we investigated the airborne bacteria of areas with weak (rural glacier) and strong human disturbance (urban building), and found that anthropogenic activities increased the diversity of airborne bacteria, and the concentration of potential airborne pathogens. Moreover, airborne bacteria in rural aerosols demonstrated significant differences in their community structure during monsoon- and westerly-affected seasons, while this pattern was weakened in urban aerosols. Additionally, urban aerosols enriched Lactobacillus sp. (member of genus Lactobacillus), which are potential pathogens from anthropogenic sources, whereas rural aerosols enriched A. calcoaceticus (member of genus Acinetobacter) and E. thailandicus (member of genus Enterococcus), which are both speculated to be sourced from surrounding animal farming. This study evaluated the impact of human activities on airborne bacteria in the Tibetan Plateau and contributed to understanding the enrichment of airborne pathogens in natural and anthropogenic background.

Abstract Background Metabolomic changes during pregnancy have been suggested to underlie the etiology of gestational diabetes mellitus (GDM). However, research on metabolites during preconception is lacking. Therefore, this study aimed to investigate distinctive metabolites during the preconception phase between GDM and non-GDM controls in a nested case–control study in Singapore. Methods Within a Singapore preconception cohort, we included 33 Chinese pregnant women diagnosed with GDM according to the IADPSG criteria between 24 and 28 weeks of gestation. We then matched them with 33 non-GDM Chinese women by age and pre-pregnancy body mass index (ppBMI) within the same cohort. We performed a non-targeted metabolomics approach using fasting serum samples collected within 12 months prior to conception. We used generalized linear mixed model to identify metabolites associated with GDM at preconception after adjusting for maternal age and ppBMI. After annotation and multiple testing, we explored the additional predictive value of novel signatures of preconception metabolites in terms of GDM diagnosis. Results A total of 57 metabolites were significantly associated with GDM, and eight phosphatidylethanolamines were annotated using HMDB. After multiple testing corrections and sensitivity analysis, phosphatidylethanolamines 36:4 (mean difference β: 0.07; 95% CI: 0.02, 0.11) and 38:6 (β: 0.06; 0.004, 0.11) remained significantly higher in GDM subjects, compared with non-GDM controls. With all preconception signals of phosphatidylethanolamines in addition to traditional risk factors (e.g., maternal age and ppBMI), the predictive value measured by area under the curve (AUC) increased from 0.620 to 0.843. Conclusions Our data identified distinctive signatures of GDM-associated preconception phosphatidylethanolamines, which is of potential value to understand the etiology of GDM as early as in the preconception phase. Future studies with larger sample sizes among alternative populations are warranted to validate the associations of these signatures of metabolites and their predictive value in GDM.

Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures.

Background and Aims: Polycystic ovarian syndrome (PCOS) afflicts 4-20% of all women at reproductive age and is a common cause of infertility. Elevated anti-Mullerian hormone levels (AMH), a clinical marker for ovarian reserve, are routinely associated with PCOS, however, an exact cut-off value has remained elusive. Interestingly, observational studies reported that women with PCOS have purported higher ovarian reserves, implied from higher AMH levels, and later age of menopause delayed by 2 years when compared to women without PCOS. Our study focuses on the Asian population, a demographic frequently under-represented in cohort studies. We posit that our results will bridge the gap in the collective understanding of PCOS and how age and lifestyle effects on ovarian reserves in Asian women. Method: A large retrospective study was conducted at a tertiary-care hospital in Singapore from 2016-2020. AMH and clinical demographics from 3,739 Asian women aged 21-53 years were collected. Wilcoxon Rank Sum was used to analyze the data and significance was established if p25 and smoking status affected AMH levels with higher BMI and smoking associated with lower AMH. An ethnic stratification revealed that average AMH levels of Malay women with PCOS were lower than Chinese and Indian women in each age group (Fig. 2). The constructed model incorporating all variables had an ROC AUC=0.89. Conclusion: This study highlights the importance of improving the resolution of PCOS diagnosis through AMH profiling, especially in Asian populations. The results from this study suggest potential beneficial effects of lifestyle modifications such as maintaining a healthy BMI and stopping smoking, especially in Asian women with PCOS.

Background and Aims: Non-obstructive azoospermia (NOA) is the most common form of male infertility, characterized by an absence of sperm in ejaculate and is caused by testicular failure. While NOA afflicts 10-38.3% of infertile males, there is no specific recommendations in EAA/EAU guidelines on its clinical diagnosis or WHO guidelines on semen analysis. Therefore, we conducted a global survey to assess the standard approach of practitioners in the diagnosis and management of NOA. Method: The Global Andrology Forum (GAF) conducted a survey on 436 independent practicing entities from 55 countries. We compiled data from 336 respondents (andrologists, urologists, fertility specialists). Information collected included frequency of NOA, varicocele, frequency of obtaining semen, interval between obtaining semen samples, hormone evaluation (FSH, LH, prolactin, total/free testosterone, SHBG, estradiol, inhibin), genetic testing (karyotype, Y-chromosome deletion, CFTR, Kal1) and referral to genetic counsellors. Results: The majority of participants (80%) either reported

Background and Aims: Sperm DNA fragmentation (SDF) is caused by apoptosis, oxidative stress or incomplete chromatin maturation and can result in male infertility and poor reproductive outcomes. Despite growing trends, there are no specific recommendations on specific diagnostic tests used, assay cut-offs or abstinence periods prior to SDF testing. Therefore, we conducted a global survey to evaluate the approaches used to diagnose SDF, towards a consensus in the field of SDF research and clinical management. Method: The survey collected cross-sectional global data from 55 countries following the CHERRIES protocol. 436 respondents included clinicians, researchers and reproductive biologists from academic, public and private health sectors, all of whom utilize SDF testing in their routine patient care and practice (Fig. 1). Results: Survey results showed that TUNEL (28.6%), SCSA (24.1%), SCD (19.1%) and Comet (5.3%) were most frequently used to diagnose SD (Fig. 2A). Assays were chosen primarily due to their availability (70.0%), cost (44.05%) and accuracy (35.48%). Published evidence on assays (25.71%), training of staff (25.48%), cost to patients (21.67%), assay time (18.81%), ease of interpretation (18.33%) and performance (17.38%) were taken lesser into consideration when selecting SDF diagnostic tests (Fig. 2B). Assay cut-offs of “30% or higher” (33.7%) were most frequently used to diagnose SDF (Fig. 2C). Finally, an abstinence period of 3-5 days was mostly recommended (53.6%; Fig. 2D). The results of this survey provide valuable data on SDF assays used in clinical practice as well as factors affecting assay choices such as availability of resources, personnel and complexity in assay processing. As decreased abstinence period is associated with lower SDF, testing is recommended with an abstinence period of less than five days. We observed that there was a lack of standard cut-off values, and every laboratory should establish its own reference values based on predictive values for fertility outcomes. Conclusion: We present new data associated with SDF testing in real-world practice, on a global scale. The trends and conclusions derived from the study are recommended for inclusion into the 6[Formula: see text] Edition WHO Manual, towards optimized patient care.

The surface energy budget over the Qinghai-Tibet Plateau (QTP) and the Arctic significantly influences the climate system with global consequences. The performances of 30 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models were evaluated based on six sites in the QTP and Arctic. The simulation results for latent heat flux (LE) were more accurate in the QTP, where the correlation coefficient and root mean square error (RMSE) were 0.9 and 30 W m−2, respectively. The results for sensible heat flux (H) were more accurate in the Arctic, the correlation coefficient and RMSE were 0.8 and 24 W m−2, respectively. Furthermore, the multiple models mean results revealed that the surface energy flux had seasonal variation and regional differences over the QTP and the Arctic. In the QTP, H was the lowest in winter, increased in spring, and reached the maximum in summer. However, the transitional changes in spring and autumn were not apparent in the Arctic, mainly due to seasonal net radiation difference between the two places. LE was affected by precipitation and surface soil moisture content. This work is important for understanding land-atmosphere interactions and useful for improving the accuracy of land surface models simulations.

Abstract Our study sought to examine the impact of the pandemic and the Circuit-breaker (CB) measures on dietary behaviours of healthcare workers (HCW). In addition, the association between self-regulatory eating behaviours and psychological stress was explored. Our study employed a cross-sectional anonymous survey that examined the demographics, dietary habits, self-regulatory eating behaviours (SR) and their association to stress levels of healthcare workers (HCWs) before and during the Circuit Breaker (CB) in Singapore. The survey was conducted over four weeks from May 17 to June 18, 2020. Snowball sampling was performed in the final week. A total of 707 participants took part in the survey. Due to the CB measures and modifications of work scope and work areas, there were significant changes in their dietary behaviors before CB versus during the CB period (n = 707), with many reducing the intake of vegetables (p = 0.018) while increasing their intake of unhealthy food choices such as canned drinks (p = 0.002), convenience food (p ≤ 0.001) and alcoholic drinks (p = 0.034). Before the CB period, 91.8% (602/656) of participants who intended to have a healthy diet were classified in medium-to-high SR groups whereas during the CB period, 87.7% (575/656) were in medium-to-high SR groups and the difference was statistically significant (p = 0.011). Nurses, administrative staff, HCWs of Chinese and Indian ethnicities, staff who did not complete university education and those who did not have domestic helpers were more likely to have reduced SR. Importantly, amongst participants who intended to have a healthy diet, 70.9% displayed no change or improved eating habits and showed medium-to-high levels of SR during CB. Participants with no changes in SR were 2.11 times more likely to be stress-free as compared to those who had deteriorated SR (OR 2.11 95% CI 1.27–3.48, p = 0.004). Due to CB measures and work modifications, dietary behaviours of HCWs deteriorated with increased intake of unhealthy food choices. HCWs who maintain their self-regulatory eating behaviour are more likely to be stress-free. Short screening questionnaires based on SR changes should be developed and explored as surveillance tools for assessment of HCWs’ general well-being such that personalized interventions to vulnerable groups of workers could be implemented effectively on the ground.

Background: The COVID-19 pandemic placed unprecedented strain on healthcare globally, which exacerbated factors leading to unplanned pregnancies. Objectives: The primary objective was to analyze the effect of COVID-19 on abortion services globally. Secondary objectives were to discuss issues regarding access to safe abortion and provide recommendations on continued access during pandemics. Search strategy: A search for relevant articles was conducted by utilizing multiple databases (PubMed, Cochrane, etc.). Selection criteria: Studies on COVID-19 and abortion were included. Data collection & analysis: The legislation governing abortion services across the globe was examined, inclusive of modifications to service provision during the pandemic. Global data on abortion rates and analyses of selected articles were also included. Main results: 14 countries instituted legislative changes related to the pandemic, 11 relaxed abortion regulations, while three restricted abortion access. An increase in abortion rates was seen particularly where telemedicine was available. Where abortions were postponed, second-trimester abortions increased after services resumed. Conclusions: Legislation, risk of exposure to infection, and access to telemedicine affect access to abortion. The use of novel technologies, maintaining existing infrastructure and enhancing the roles of trained manpower for safe abortion access is recommended to avoid the marginalization of women's health and reproductive rights.

Study region: Northern part of China (NPC) Study focus: Along with rapid economic development and population growth, the NPC has been identified as a water scarcity hotspot. Previous studies attributed the intensified water scarcity primarily to increasing human water withdrawal over the NPC in the 20th century. However, water withdrawal has stagnated since the beginning of 21st century, which raises a question of whether the trend of water scarcity changes, particularly when considering the contribution of water availability that is subject to climate variability. Based on the water stress index (WSI), we detected the trends of water scarcity by a piecewise linear regression approach and investigated their associated drivers in the NPC by using survey-based datasets and hydro-climate model simulations. New hydrological insights for the region: Results show that the trends of WSI changed from positive to negative after 2001. Increased water withdrawal was the dominant factor for the aggravated water scarcity before 2001. However, as the rising precipitation offsets the effect of increasing evapotranspiration, climate change has increased water availability and become the major contributor to the alleviated water scarcity during 2001–2020. Furthermore, future projections suggest that climate change would further alleviate future water scarcity over the NPC by increasing water availability. The results suggest the growing role of climate change in affecting water scarcity, which are significant for guiding regional water policy-making.

Background and Aims: The mTORC1 pathway is known to play a critical role in longevity and is a central regulator for various pathways including cellular, inflammation, and metabolic pathways. Age-related functional decline in tissue was associated with dysregulation of the mTORC1 pathway. mTORC1 suppression has been shown to improve ovarian function in mice, but the underlying cause remains elusive. We aim to investigate a common denominator of mTOR1, ribosomal protein S6 (rpS6), and its role in reproductive longevity through transient inhibition of the rps6 axis using murine models. Method: Selective inhibition of the mTORC1 pathway and the rpS6 axis were achieved using rapamycin and LY2584702 Tosylate respectively. Subcutaneous injection of both drugs was administered to 48-week-old female virgin C57BL/6J mice for thrice weekly for 8 weeks. Reproductive outcomes such as mating frequencies, fecundity, and lifespan were recorded. Results: Reproductive parameters measured revealed that these 48-week-old female virgin treated mice resulted in the increase in serum Anti-Mullerian hormone levels, total number of ovarian follicles, mating frequencies and probability of live births. Untreated control mice at 62 weeks old did not yield any live births. Comparison between the two treatment groups suggested that selective inhibition of rpS6 demonstrated higher probability of live births and higher average number of live offspring per litter. Conclusion: This study provides novel insights into the roles of mTORC1 and rpS6 in both reproductive and healthy longevity. Our findings suggest temporary rpS6 inhibition successfully rejuvenated ageing ovaries, with the novel discovery in the improvement of fecundity of LY2584702 treated mice.

The improved delayed detached eddy simulation method with shear stress transport model was used to analyze the evolution of vortex structure, velocity and pressure fields of swirling jet. The influence of nozzle pressure drop on vortex structure development and turbulence pulsation was investigated. The development of vortex structure could be divided into three stages: Kelvin-Helmholtz (K-H) instability, transition stage and swirling flow instability. Swirling flow could significantly enhance radial turbulence pulsation and increase diffusion angle. At the downstream of the jet flow, turbulence pulsation dissipation was the main reason for jet velocity attenuation. With the increase of pressure drop, the jet velocity, pulsation amplitude and the symmetry of velocity distribution increased correspondingly. Meanwhile the pressure pulsation along with the axis and vortex transport intensity also increased significantly. When the jet distance exceeded about 9 times the dimensionless jet distance, the impact distance of swirling jet could not be improved effectively by increasing the pressure drop. However, it could effectively increase the swirl intensity and jet diffusion angle. The swirling jet is more suitable for radial horizontal drilling with large hole size, coalbed methane horizontal well cavity completion and roadway drilling and pressure relief, etc.

The rapid development of the Internet of Things (IoTs) has driven the progress of intelligent transportation systems (ITS), which provides basic elements, such as vehicles, traffic lights, cameras, roadside units (RSUs) and their interconnected 5G communications, to constitute the Internet of vehicles (IoVs). In the IoVs, an intelligent vehicle can not only share information with the infrastructures like RSUs by vehicle to infrastructure (V2I) communication but also with vehicles on the road through vehicle-to-vehicle (V2V) communications. We thus expect that vehicles can collaborate with other well-resourced and idling vehicles, making full use of the wasted resources. However, existing approaches cannot achieve this goal due to the increasing strict delay constraints and the dynamic characteristics of the IoVs tasks. To improve the utilization of resources and perform better resource management, in this paper, we propose a hybrid task offloading scheme (HyTOS) based on deep reinforcement learning (DRL), which achieves the vehicle-to-edge (V2E) and V2V offloading by jointly considers the delay constraints and resource demand. To perform optimal offloading decision-making, we introduce a dynamic decision-making method, namely deep Q networks (DQN). To verify the effectiveness of this approach, we choose three baseline offloading approaches (one game theory-based and two single-scenario approaches) and perform a series of simulation experiments. The simulation results demonstrate that, compared to the baseline offloading approaches, our approach can effectively reduce task delay and energy consumption, achieving high-efficiency resource management.

Thin-walled structures, when used for high-speed railways, can effectively mitigate the irreversible destruction when a malfunction occurs. Nested thin-walled tubes, as energy-absorbing structures, possess excellent specific energy absorption (SEA) and crushing force efficiency (CFE). This paper conducts multi-objective optimization by focusing on a square corrugation nested structure with a double octagon inner wall, namely SCOD, to ameliorate the crashworthiness of the nested structure. The finite element model of the SCOD is constructed and validated by test data. A set of experimental design points with good spatial distribution are obtained using the optimal Latin hypercube (LHC) method. The polynomial response surface (PRS) method was applied to establish the fitting relationship between design variables and optimization objectives, and validation is accomplished. The DCNSGA-III algorithm is employed for optimization, resulting in a Pareto alternative solution set with good population diversity and convergence. In addition, to observe the optimized performance, a set of optimal solutions considering a single objective value is derived, and a comprehensive optimal solution is obtained by applying the minimum distance selection method (TMDSM). Finally, the proposed optimized system is analyzed and validated. According to the alternative reference solutions, the initial peak force (IPCF) reduces by 53.75% and CFE increases by 8.7%. This paper provides some reference for the optimization design in practical engineering.

Liquid nitrogen fracturing is one of the potential feasible technologies for improving the stimulation efficiency of coalbed methane (CBM) reservoirs. At present, the visualization of pore-throat connectivity and microscopic seepage characteristics in coal rocks under liquid nitrogen thermal shock is still lack of studying. Hence, the influence of liquid nitrogen thermal shock on the micro-nano pore structure and mechanical property of coal rocks are not understood clearly. In order to provide theoretical basis for the stimulation behavior of liquid nitrogen fracturing in coal beds, this paper investigates the change of micro-nano pore structure and mechanical property of coal rocks before and after liquid nitrogen treatment means of CT scanning and atomic force microscope (AFM). In addition, the influence of liquid nitrogen thermal shock on the seepage routes of coal rock are revealed. The following research results can be obtained. First, the number and scales of pores in the coal increase after liquid nitrogen thermal shock. In this experiment, porosity is increased by 200%, micro-fracture is dominant and its volume proportion is increased to 90.0% from 7.7% before liquid nitrogen treatment. Second, the three-dimensional pore structure reconstruction model obtained by CT shows that after the liquid nitrogen treatment, the number, total length and total volume of throats in the coal rock are increased by 170%, 140% and 130% and the pore connectivity is improved greatly. Third, after liquid nitrogen treatment, the sample's absolute permeability is improved significantly. In this experiment, the absolute permeability of coal after liquid nitrogen treatment is 77 times higher than that before liquid nitrogen cooling. The micro-fractures induced by thermal stress are the main percolation routes in coal after liquid nitrogen cooling. Fourth, pores and fractures are newly formed on both matrix and mineral domains, and the surface roughness is increased. In the meantime, the elastic modulus in matrix and mineral domains of coal drops, and the average elastic modulus drops by 81% and 91%, respectively. In conclusion, liquid nitrogen thermal shock leads to the increase of microscopic defects in coal and the deterioration of mechanical property. Liquid nitrogen fracturing is expected to be a new kind of efficient and green CBM reservoir stimulation technology.

Skeletal muscle is one of the largest organs in the body and the largest protein repository. Mitochondria are the main energy-producing organelles in cells and play an important role in skeletal muscle health and function. They participate in several biological processes related to skeletal muscle metabolism, growth, and regeneration. Adenosine monophosphate-activated protein kinase (AMPK) is a metabolic sensor and regulator of systemic energy balance. AMPK is involved in the control of energy metabolism by regulating many downstream targets. In this review, we propose that AMPK directly controls several facets of mitochondrial function, which in turn controls skeletal muscle metabolism and health. This review is divided into four parts. First, we summarize the properties of AMPK signal transduction and its upstream activators. Second, we discuss the role of mitochondria in myogenesis, muscle atrophy, regeneration post-injury of skeletal muscle cells. Third, we elaborate the effects of AMPK on mitochondrial biogenesis, fusion, fission and mitochondrial autophagy, and discuss how AMPK regulates the metabolism of skeletal muscle by regulating mitochondrial function. Finally, we discuss the effects of AMPK activators on muscle disease status. This review thus represents a foundation for understanding this biological process of mitochondrial dynamics regulated by AMPK in the metabolism of skeletal muscle. A better understanding of the role of AMPK on mitochondrial dynamic is essential to improve mitochondrial function, and hence promote skeletal muscle health and function.

BackgroundThis study aimed to explore the impact of hypoxic hepatitis (HH) on survival in heart failure (HF) patients and to develop an effective machine learning model to predict 30-day mortality risk in HF patients with HH.MethodsIn the Medical Information Mart for Intensive Care (MIMIC)-III and IV databases, clinical data and survival situations of HF patients admitted to the intensive care unit (ICU) were retrospectively collected. Propensity Score Matching (PSM) analysis was used to balance baseline differences between HF patients with and without HH. Kaplan Meier analysis and multivariate Cox analysis were used to determining the effect of HH on the survival of CF patients. For developing a model that can predict 30-day mortality in CF patients with HH, the feature recurrence elimination (RFE) method was applied to feature selection, and seven machine learning algorithms were employed to model construction. After training and hyper-parameter optimization (HPO) of the model through cross-validation in the training set, a performance comparison was performed through internal and external validation. To interpret the optimal model, Shapley Additive Explanations (SHAP) were used along with the Local Interpretable Model-agnostic Explanations (LIME) and the Partial Dependence Plot (PDP) techniques.ResultsThe incidence of HH was 6.5% in HF patients in the MIMIC cohort. HF patients with HH had a 30-day mortality rate of 33% and a 1-year mortality rate of 51%, and HH was an independent risk factor for increased short-term and long-term mortality risk in HF patients. After RFE, 21 key features (21/56) were selected to build the model. Internal validation and external validation suggested that Categorical Boosting (Catboost) had a higher discriminatory capability than the other models (internal validation: AUC, 0.832; 95% CI, 0.819–0.845; external validation: AUC, 0.757 95% CI, 0.739–0.776), and the simplified Catboost model (S-Catboost) also had good performance in both internal validation and external validation (internal validation: AUC, 0.801; 95% CI, 0.787–0.813; external validation: AUC, 0.729, 95% CI, 0.711–0.745).ConclusionHH was associated with increased mortality in HF patients. Machine learning methods had good performance in identifying the 30-day mortality risk of HF with HH. With interpretability techniques, the transparency of machine learning models has been enhanced to facilitate user understanding of the prediction results.

The nontuberculous mycobacterial pulmonary disease (NTM-PD) caused by Mycobacterium species has increased in prevalence all over the world. The distributions of NTM-PD are possibly determined by the westerly wind traveling at high altitudes over East Asia. However, the long-range transport of Mycobacterium species has not been demonstrated by analyzing the bacterial communities in aerosols such as desert mineral particles and anthropogenic pollutants transported by the westerly wind. Here, airborne bacterial compositions were investigated including Mycobacterium species in high-elevation aerosols, which were captured in the snow cover at 2,450 m altitude on Mt. Tateyama. This was further compared to the ground-level or high-altitude aerosols collected at six sampling sites distributed from Asian-dust source region (Tsogt-Ovoo) to downwind areas in East Asia (Asian continental cities; Erenhot, Beijing, Yongin, Japanese cities; Yonago, Suzu, Noto Peninsula). The cell concentrations and taxonomic diversities of airborne bacteria decreased from the Asian continent to the Japan area. Terrestrial bacterial populations belonging to Firmicutes and Actinobacteria showed higher relative abundance at high-elevation and Japanese cities. Additionally, Mycobacterium species captured in the snow cover on Mt. Tateyama increased in relative abundance in correspondence to the increase of black carbon concentrations. The relative abundance of Mycobacterium sequences was higher in the aerosol samples of Asian continental cities and Japanese cities than in the desert area. Presumably, anthropogenic pollution over East Asia carries potential Mycobacterium species, which induce NTM-PD, thereby impacting upon the public health.

Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fetal DNA methylation. No strong differences in metabolic parameters were seen.

Light-absorbing aerosols such as black carbon (BC), organic carbon (OC), and dust can cause the warming and melting of glaciers by absorbing sunlight. Further research is needed to understand the impact of light-absorbing aerosols on the Hindukush–Karakoram–Himalaya region in northern Pakistan. Therefore, spatiotemporal variation in absorbing surface mass concentration retrieved from Modern-Era Retrospective analysis for Research and Applications, optical properties such as aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD) from the ozone monitoring instrument, and meteorological parameters from the European Centre for Medium-Range Weather Forecasts Reanalysis were investigated over northern Pakistan from 2001 to 2021. The BC concentration was lowest in May and highest in November, having a seasonal maximum peak in winter (0.31 ± 0.04 µg/m3) and minimum peak in spring (0.17 ± 0.01 µg/m3). In addition, OC concentration was found to be greater in November and smaller in April, with a seasonal higher peak in autumn (1.32 ± 0.32 µg/m3) and a lower peak in spring (0.73 ± 0.08 µg/m3). The monthly and seasonal variabilities in BC and OC concentrations are attributed to solid fuels, biomass burning, changes in vegetation, agricultural activities, and meteorology. In contrast, the dust concentration was high in July and low in December, with a seasonal average high concentration in summer (44 ± 9 µg/m3) and low concentration in winter (13 ± 2 µg/m3) due to drier conditions, dust activity, long-range transport, and human activities. Moreover, the seasonal variation in AOD and AAOD was identical and higher in the summer and lower in the winter due to dust aerosol loading and frequent dust activities. AOD and AAOD followed a similar pattern of spatial variation over the study area. Meteorological parameters greatly impact light-absorbing aerosols; therefore, low temperatures in winter increase BC and OC concentrations due to shallow boundary layers, while severe precipitation in spring decreases concentrations. During summer, dry conditions cause soil erosion and increase the amount of dust suspended in the atmosphere, leading to higher AOD and AAOD values. Conversely, higher precipitation rates and speedy winds disperse the dust aerosols in winter, resulting in lower AOD and AAOD values.

A practical solution to the power allocation problem in ultra-dense small cell networks can be achieved by using deep reinforcement learning (DRL) methods. Unlike traditional algorithms, DRL methods are capable of achieving low latency and operating without the need for global real-time channel state information (CSI). Based on the actor–critic framework, we propose a policy optimization of the power allocation algorithm (POPA) for small cell networks in this paper. The POPA adopts the proximal policy optimization (PPO) algorithm to update the policy, which has been shown to have stable exploration and convergence effects in our simulations. Thanks to our proposed actor–critic architecture with distributed execution and centralized exploration training, the POPA can meet real-time requirements and has multi-dimensional scalability. Through simulations, we demonstrate that the POPA outperforms existing methods in terms of spectral efficiency. Our findings suggest that the POPA can be of practical value for power allocation in small cell networks.

Dust aerosol vertical profiles are very essential to accurately evaluate their climate forcing and trans-subcontinental transportation to downstream areas. We initiated a joint comprehensive field experiment to investigate the vertical profiles and optical characteristics of dust aerosol in the hinterland of Taklimakan Desert (TD) during summer 2019. After smoothing the raw signals, the CHM15k ceilometer could distinctly detect a moderate intensity of dust layer, cloud layer, and subsequent rainfall process. The results showed that dust events frequently occurred in TD during the entire period; the overall mean PM2.5, PM10, PM2.5/PM10, and Ångström exponent are 110.4 ± 121.0 μg/m3, 317.2 ± 340.0 μg/m3, 0.35 ± 0.07, and 0.28 ± 0.12, respectively, suggesting that dust particles are predominant aerosol types in TD. There was an obvious summertime dust stagnation layer persistently hanged over the desert at 1.5–3.0-km height. A deep and intense daytime convective structure was also detected by the ceilometer, with maximum aerosol mixing layer height of ∼3 km that appeared at 12:00 UTC, which was in favor of lifting the ground-generated dust particles into the upper atmosphere. The normalized range-corrected signal log10(RCS), aerosol extinction σ(z), and backscattering coefficient β(z) of the ceilometer were higher than 6.2, 0.5 km−1, and 0.01 km−1 sr−1 for heavy dust storms, respectively, and the corresponding vertical optical range was smaller than 1.0 km. The aerosol lidar ratio was equal to 50 sr, which was greatly different from those of clear-sky cases. The retrieved σ(z) values were about 2.0, 0.5, 0.14, and 0.10 km−1 at 200-m height, respectively, under strong dust storm, blowing dust, floating dust, and clear-sky conditions. This indicated that the aerosol extinction coefficients under dust events were about 3–10 times greater than those of clear-sky cases. The statistics of the aerosol optical parameters under different dust intensities in TD were very helpful to explore and validate dust aerosols in the application of climate models or satellite remote sensing.

Understanding the vertical structures of cloud condensation nuclei (CCN) and ice-nucleating particle (INP) number concentrations in desert source regions is crucial for examining dust-cloud interactions and other related impacts. To explore the vertical profiles of the CCN and INP number concentrations and their possible atmospheric–dynamic influence factors at the center of the Taklimakan Desert, intensive observations were conducted by employing a ground-based polarization Raman lidar, sounding balloons, and a sun photometer in Tazhong (83.39° E, 38.58° N, 1103 m above sea level) during the summer of 2019. Based on the GRASP algorithm, the extinction-to-volume conversion factor of dust aerosols was 0.85 × 10−12 Mmm3 m−3, and the extinction-to-number conversion factor was predicted to be 0.20 Mm cm−3 on the basis of the sun photometer observations. Thus, the vertical CCN and INP number concentration profiles obtained with different parameterization schemes in the presence of various pollution levels were calculated by combining dust extinction coefficients retrieved by lidar and meteorological data observed by sounding balloon observations. The achieved results indicated that the CCN number concentration varied from 10−2 to 102 cm−3 and decreased from ground level to 12 km with an average value of 36.57 cm−3 at the 10–12 km height range, while the INP number concentration based on parameterization schemes D10 and D15 mainly varied from 10−1 to 102 L−1 and from 1 L−1 to 103 L−1, with average values of 3.50 L−1 and 7.80 L−1, respectively. Moreover, we observed a strong relationship between the INP number concentration of scheme D10 and the wind speed, with an R2 value of 0.72, but a weak relationship between the CCN number concentration and the relative humidity in the boundary layer, with a Spearman’s rank correlation coefficient R2 value of 0.38. The present study provides original and valuable information regarding the CCN and INP number concentrations and their related influencing factors at the center of the Taklimakan Desert and can improve our understanding of the vertical distributions of dust–cloud–atmosphere dynamic interactions, as well as of the roles of dust aerosols in the desert hydrological cycle.

Glaciers are generally believed to be subjugating by global warming but the Karakoram glaciers are reportedly maintaining their balance. Earlier studies in the Karakoram and its sub-basins have mostly addressed a short span of time and used complex models to understand the phenomenon. Thus, this study is based on a long-term trend analysis of the computed runoff components using satellite data with continuous spatial and temporal coverage incorporated into a simple degree day Snowmelt Runoff Model (SRM). The trends of melt runoff components can help us understanding the future scenarios of the glaciers in the study area. The SRM was calibrated against the recorded river flows in the Hunza River Basin (HRB). Our simulations showed that runoff contribution from rain, snow, and glaciers are 14.4%, 34.2%, and 51.4%, respectively during 1995–2010. The melting during the summer has slightly increased, suggesting overall but modest glacier mass loss which consistent with a few recent studies. The annual stream flows showed a rising trend during the 1995–2010 period, while, rainfall and temperatures showed contrasting increasing/decreasing behavior in the July, August, and September months during the same period. The average decreasing temperatures (0.08 °C per annum) in July, August, and September makes it challenging and unclear to explain the reason for this rising trend of runoff but a rise in precipitation in the same months affirms the rise in basin flows. At times, the warmer rainwater over the snow and glacier surfaces also contributed to excessive melting. Moreover, the uncertainties in the recorded hydrological, meteorological, and remote sensing data due to low temporal and spatial resolution also portrayed contrasting results. Gradual climate change in the HRB can affect river flows in the near future, requiring effective water resource management to mitigate any adverse impacts. This study shows that assessment of long-term runoff components can be a good alternative to detect changes in melting glaciers with minimal field observations.

Introduction: Asian patients may have more difficulty seeking help for their sexual problems because of a largely conservative culture. Residents from both obstetrics and gynecology (OBGYN) and family medicine (FM) departments are ideally placed to address sexual problems. Aim: This survey explored the experience of residents from OBGYN and FM in managing sexual problems and their views on training in sexual medicine (SM). Method: An anonymized questionnaire collecting data on trainee characteristics, exposure to male and female sexual problems, and training in SM was sent to all FM and OBGYN residents in Singapore. These residents had completed their medical registration with the Singapore Medical Council and were at various stages of specialty training in both FM and OBGYN residency programs in Singapore. Main Outcome Measure: Trainees’ exposure to male and female sexual problems and their views on training in Sexual Medicine. Results: The overall response from the survey was 63.5% (122/192)—54% (70/129) and 69% (52/75) of FM and OBGYN residents responded, respectively. 63% were female, with 22% being senior residents, and 55% attended Singaporean medical schools. About one quarter (30/122) of the respondents encountered patients with sexual problems at least monthly. Most would refer these patients directly to specialists, psychologists, and sex therapists. More than 80% of residents were not confident in managing sexual problems in either sex (89% for male problems; 83% for female problems). Among the recognized categories, only 30% felt confident to manage erectile dysfunction, 26% for vaginismus, while less than 10% felt confident to manage libido, arousal, or orgasm disorders. 95% of the residents agreed that SM should be part of both training curricula, with 70% and 25% suggesting at junior and senior residency, respectively. 93% of them were interested to obtain further knowledge and skills in SM through their core training curriculum and from seminars. Conclusions: This survey reported a significant number of residents in OBGYN and FM departments are regularly exposed to patients with sexual problems but lack the skills to manage them. OBGYN residents were more familiar with managing female sexual problems while FM residents tend to have more experience in male sexual problems. Almost universally, the residents in FM and OBGYN were very keen to acquire skills in SM, and the results support the incorporation of appropriate knowledge and skills into both national residency program curricula.Huang Z, Choong DS, Ganesan AP, et al. A Survey on the Experience of Singaporean Trainees in Obstetrics/Gynecology and Family Medicine of Sexual Problems and Views on Training in Sexual Medicine. J Sex Med 2019;8:107–113. Key Words: Sexual Problems, Training in Sexual Medicine, OBGYN, Family Medicine Residents

The parallel processing of the service function chain (SFC) is expected to provide better low-delay service delivery, because it breaks through the bottleneck of traditional serial processing mode in which service delay increases linearly with the SFC length. However, the provision of parallelized SFC (PSFC) is much more difficult due to the unique construction of PSFCs, inevitable parallelization overhead, and delay balancing requirement of PSFC branches; therefore, existing mechanisms for serial SFC cannot be directly applied to PSFC. After a comprehensive review of recent related work, we find that traffic scheduling mechanisms for PSFCs is still lacking. In this paper, a delay-aware traffic scheduling mechanism (DASM) for PSFCs is proposed. DASM first transforms PSFC into several serial SFCs by releasing the upstream VNF constraints so as to handle them independently while keeping their parallel relations. Secondly, DASM realizes delay-aware PSFC traffic scheduling based on the reinforcement learning (RL) method. To the best knowledge of the authors, this is the first attempt to address the PSFC traffic scheduling problem by transforming them into independent serial SFCs. Simulation results show that the proposed DASM outperforms the advanced PSFCs scheduling strategies in terms of delay balance and throughput.

Recently, analyses of the air quality in Pakistan have received significant interest, especially regarding the impact of air pollutant concentrations on human health. The Atlas of Baseline Environmental Profiling along the China-Pakistan Economic Corridor (CPEC) at five locations in Gilgit-Baltistan (GB) is a major landmark in this regard due to the presence of massive glaciers in the region, which are considered as water reserves for the country. Using various statistical measurements, the air quality was analyzed at the studied geographic locations. Further, air quality was evaluated based on air pollutant data acquired from ambient air monitoring laboratories. For example, 24 h concentrations of particulate matter (PM2.5) were found to range from 25.4 to 60.1 µg/m3, with peaks in the winter season at Gilgit. It was found that PM2.5 values were 1.7 and 1.3 times greater than National Environmental Quality Standards (NEQS) standards only at Gilgit and Chilas, respectively, and 1.5 to 4 times greater than the World Health Organization (WHO) standards at all locations. Similarly, PM2.5 concentrations were found to range from 31.4 to 63.9 µg/m3, peaking at Chilas in summer 2020. The observed values were 1.1 to 1.8 times and 2 to 4.2 times greater than the NEQS and WHO standards, respectively, at all locations. In addition, the average peaks of black carbon (BC) were measured at Gilgit, both in winter (16.21 µg/m3) and summer (7.83 µg/m3). These elevated levels could be attributed to the use of heavy diesel vehicles, various road activities and different meteorological conditions. Pollutants such as carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOX) and ozone (O3) were found to be within NEQS and WHO limits. Based on air quality metrics, the effect of PM2.5 on air quality was found to be moderate in Sost, Hunza and Jaglot, while it was at unhealthy levels at Gilgit and Chilas in the winter of 2019; moderate levels were observed at Sost while unhealthy levels were detected at the remaining locations in the summer of 2020. There are no specific guidelines for BC. However, it is associated with PM2.5, which was found to be a major pollutant at all locations. The concentrations of CO, SO2 and O3 were found to be at safe levels at all locations. The major fraction of air masses is received either locally or from transboundary emissions. This study demonstrates that PM2.5 and BC are the major and prevailing air pollutants within the study region, while other air pollutants were found to be within the permissible limits of the WHO and NEQS.

Accurately determining the atmospheric boundary layer height (ABLH) is needed when one is addressing the air quality-related issues in highly urbanized areas, as well as when one is investigating issues that are related to the emission and transport of dust aerosols over the source region. In this study, we propose a new ABLH retrieval method, which is named ADEILP (ABLH that is determined by polarization lidar); it is based on the short-term polarized lidar observation that took place during the intensive field campaign in July 2021 in Tazhong, the hinterland of Taklimakan Desert. Furthermore, we conducted comparisons between the ABLH that was identified using a radiosonde (ABLHsonde), the ABLH that was identified by ERA5 (ABLHERA5) and the ABHL that was identified by ADELIP (ABLHADELIP), and we discussed the implications of the dust events. The ADELIP method boasts remarkable advancements in two parts: (1) the lidar volume linear depolarization ratio (VLDR) that represented the aerosol type was adopted, which is very effective in distinguishing between the different types of boundary layers (e.g., mixing layer and residual layer); (2) the idea of breaking up the entire layer into sub-layers was applied on the basis of the continues wavelet transform (CWT) method, which is favorable when one is considering the effect of fine stratification in an aerosol layer. By combining the appropriate height limitations, these factors ensured that there was good robustness of the ADELIP method, thereby enabling it to deal with complex boundary layer structures. The comparisons revealed that ABLHADELIP shows good consistency with ABLHsonde and ABLHERA5 for non-dust events. Nevertheless, the ADELIP method overestimated the stable boundary layer and underestimated the heights of the mixing layer. The dust events seem to be a possible reason for the great difference between ABLHERA5 and ABLHsonde. Thus, it is worth suggesting that the influence that is caused by the differences of the vertical profile in the ERA5 product should be carefully considered when the issues on dust events are involved. Overall, these findings support the climatological analysis of the atmosphere boundary layer and the vertical distribution characteristics of aerosols over typical climatic zones.

Abstract In this study, we examine the spatial and temporal characteristics of water stress in China for the historical (1971–2010) and the future (2021–2050) periods using a multimodel simulation approach. Three water stress indices (WSIs), that is, the ratios of water withdrawals to locally generated runoff (WSIR), to natural streamflow (WSIQ), and to natural streamflow minus upstream consumptive water withdrawals (WSIC), are used for the assessment. At the basin level, WSIR estimates generally match the reported data and indicate severe water stress in most northern basins. At the grid cell level, the WSIs show distinct spatial patterns of water stress wherein WSIR (WSIQ) estimates higher (lower) water stress compared to WSIC. Based on the WSIC estimates, 368 million people (nearly one third of the total population) are affected by severe water stress annually during the historical period, while WSIR and WSIQ suggest 595 and 340 million, respectively. Future projections of WSIC indicate that more than 600 million people (43% of the total) might be affected by severe water stress, and half of China's land area would be exposed to stress. The found aggravating water stress conditions could be partly attributed to the elevated future water withdrawals. This study emphasizes the necessity of considering explicit upstream and downstream relations with respect to both water availability and water use in water stress assessment and calls for more attention to increasing levels of water stress in China in the coming decades.

To address the high rock strength and low drilling rate issues in deep oil/gas and geothermal exploitation, we performed mechanical property tests on three kinds of rock samples (granite, shale and sandstone) subjected to liquid nitrogen (LN2) cooling and conducted rock-breaking experiments using LN2 jet. Rock-breaking characteristics and mechanisms of LN2 jet, heat transfer features between LN2 and rock and thermal stress evolution in rock were analyzed. A novel high-pressure LN2 jet assisted drilling method was proposed accordingly. The study results show that LN2 thermal shock can significantly reduce uniaxial compression strength and elastic modulus of rock. Rock damage and corresponding mechanical deterioration become more pronounced with increasing rock temperature. The LN2 jet has merits of high rock-breaking efficiency and low threshold rock-breaking pressure. Rock failure under LN2 jet impact is characterized by large volume breakage and the rock-breaking performance becomes more significant with increase of rock temperature. Under the impact of LN2 jet, the damage of granite is the most remarkable among the three rock samples. Thus, this method works better for high temperature granite formations. It has a good application prospect in speeding up drilling rate in deep hot dry rock geothermal reservoirs. Key words: liquid nitrogen jet, cold shock, jet impact, rock-breaking experiment, assisted drilling, drilling rate improvement

It is a common phenomenon during CBM drilling and production that reservoir damage is not eliminated completely. In view of this, a technical idea of composite pulsating hydraulic fracturing of radial horizontal wells which is conducive to blockage removing and stimulation was put forward in this paper. Speaking of the hydraulic jetting in a multi-branch radial well, it is to conduct pulsating hydraulic fracturing moderately through a high-diversion radial hole, so as to crush and break coal beds near the main hole to the uttermost. Thus, an extensive pressure relief and permeability increase area where high-diversion pathways are combined with fracture networks is formed. Then, to verify its technical principles, laboratory tests on pulsating hydraulic fracturing of radial wells were designed and carried out. Besides, the relationships of the features of acoustic emission (AE) response during the formation of fractures by composite fracturing of radial horizontal wells vs. coal breaking degree and macro fracture morphology were experimentally studied by using a pulse servo fatigue testing machine and an acoustic emission detector. And the following research results were obtained. First, under experimental conditions, fractures initially occur when the pressure of composite pulsating hydraulic fracturing of radial horizontal wells is 1/3–1/4 of the peak pressure of conventional fracturing, and the amount of its AE events is 1.38–7.07 times that of conventional fracturing. Second, when composite pulsating hydraulic fracturing of radial horizontal wells is conducted, AE emission signals respond strongly, the peak pressure for macro fracturing is lower and a larger fracture network can be generated more easily under the same condition. Third, radial laterals amount, borehole length, dynamic loading frequency and amplitude are the important factors affecting the effect of composite pulsating hydraulic fracturing of radial horizontal wells. In conclusion, composite pulsating hydraulic fracturing of radial horizontal wells provides a new idea of removing the blockages in CBM reservoirs and developing CBM efficiently, realizing effective blockage removing and stimulation of CBM wells. Keywords: Coalbed methane, Reservoir damage, Stimulation, Radial horizontal well, Composite pulsating hydraulic fracturing, Blockage removing, Laboratory

The vertical structure of dust properties in desert sources is crucial for evaluating their long-range transportation and radiative forcing. To investigate vertical profiles of dust optical properties in the Taklimakan Desert, we conducted ground-based polarization Raman lidar measurements in Tazhong (83.39°E, 38.58°N, 1103 m above sea level), located at the center of the Taklimakan Desert in the summer of 2019. The lidar system developed by Lanzhou University for continuous network observation is capable of measuring polarization at 532 and 355 nm and detecting Raman signals at 387, 407, and 607 nm. The results indicate that dust aerosols in the central Taklimakan Desert were regularly lifted over 6 km during the summer with a mass concentration of 400–1000 µg m−3, while the majority of the dust remained restricted within 2 km. Moreover, the height of the boundary layer can reach 5–6 km in the afternoon under the strong convention. Above 3 km, dust is composed of finer particles with an effective radius (Reff.) less than 3 μm and a Ångström exponent (AE) related to the extinction coefficient (AEE)532,355 greater than 4; below 3 km, however, dust is dominated by coarser particles. In addition, the particle depolarization ratios (PDR) of Taklimakan dust are 0.32 ± 0.06 at 532 nm and 0.27 ± 0.04 at 355 nm, while the lidar ratios (LRs) are 49 ± 19 sr at 532 nm and 43 ± 12 sr at 355 nm. This study firstly provides information on dust vertical structure and its optical properties in the center of the desert, which may aid in further evaluating their associated impacts on the climate and ecosystem.

Vibration drilling technology induced by hydraulic pulse can assist the bit in breaking rock at deep formation. Simultaneously, the pulsed jet generated by the hydraulic pulse promotes removal of the cuttings from the bottom hole. Nowadays, the cuttings removal mechanism of the pulsed jet is not clear, which causes cuttings to accumulate at the bottom hole and increases the risk of repeated cutting. In this paper, a pressure-flow rate fluctuation model is established to analyze the fluctuation characteristics of the pulsed jet at the bottom hole. Based on the model, the effects of displacement, well depth, drilling fluid viscosity, and flow area of the pulsed jet tool on the feature of instantaneous flow at the bottom hole are discussed. The results show that the pulsed jet causes flow rate and pressure to fluctuate at the bottom hole. When the displacement changes from 20 L/s to 40 L/s in a 2000 m well, the pulsed jet generates a flow rate fluctuation of 4–9 L/s and pressure fluctuation of 0.1–0.5 MPa at the bottom hole. With the flow area of the tool increasing from 2 cm2 to 4 cm2, the amplitude of flow rate fluctuation decreases by 72.5%, and the amplitude of pressure fluctuation decreases by more than 60%. Combined with the fluctuation feature of the flow field and the water jet attenuation law at the bottom hole, the force acting on the cuttings under the pulsed jet is derived. It is found that flow rate fluctuation improves the mechanical state of cuttings and is beneficial for cuttings tumbled off the bottom hole. This research provides theoretical guidance for pulsed jet cuttings cleaning at the bottom hole.

Central Asia is one of the most important sources of mineral saline dust worldwide. A comprehensive understanding of Central Asian dust transport is essential for evaluating its impacts on human health, ecological safety, weather and climate. This study first puts forward an observation-based climatology of Central Asian dust transport flux by using the 3-D dust detection of Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP). The seasonal difference of transport flux and downstream contribution are evaluated and compared with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Central Asian dust can be transported not only southward in summer under the effect of the South Asian summer monsoon, but also eastward in other seasons under the control of the westerly jet. Additionally, the transport of Central Asian dust across the Pamir Plateau to the Tibetan Plateau is also non-negligible, especially during spring (with a transport flux rate of 150 kg m−1 day−1). The annual CALIOP-based downstream contribution of Central Asian dust to South Asian (164.01 Tg) is 2.1 times that to East Asia (78.36 Tg). This can be attributed to the blocking effect of the higher terrain between Central and East Asia. Additionally, the downstream contributions to South and East Asia from MERRA-2 are only 0.36 and 0.84 times that of CALIOP, respectively. This difference implies the overestimation of the wet and dry depositions of the model, especially in the low latitude zone. The quantification of the Central Asian dust transport allows a better understanding of the Central Asian dust cycle, and supports the calibration/validation of aerosol-related modules of regional and global climate models.

The current study investigates the variation and physicochemical properties of ambient particulate matter (PM) in the very important location which lies in the foothills of the Hindu Kush ranges in northern Pakistan. This work investigates the mass concentration, mineral content, elemental composition and morphology of PM in three size fractions, i.e., PM1, PM2.5 and PM10, during the year of 2019. The collected samples were characterized by microscopic and spectroscopic techniques like Fourier transform infrared spectroscopy, X-ray diffraction spectroscopy and scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) spectroscopy. During the study period, the average temperature, relative humidity, rainfall and wind speed were found to be 17.9 °C, 65.83%, 73.75 mm and 0.23 m/s, respectively. The results showed that the 24 h average mass concentration of PM10, PM2.5 and PM1 were 64 µgm−3, 43.9 µgm−3 and 22.4 µgm−3, respectively. The 24 h concentration of both PM10 and PM2.5 were 1.42 and 2.92 times greater, respectively, than the WHO limits. This study confirms the presence of minerals such as wollastonite, ammonium sulphate, wustite, illite, kaolinite, augite, crocidolite, calcite, calcium aluminosilicate, hematite, copper sulphate, dolomite, quartz, vaterite, calcium iron oxide, muscovite, gypsum and vermiculite. On the basis of FESEM-EDX analysis, 14 elements (O, C, Al, Si, Mg, Na, K, Ca, Fe, N, Mo, B, S and Cl) and six groups of PM (carbonaceous (45%), sulfate (13%), bioaerosols (8%), aluminosilicates (19%), quartz (10%) and nitrate (3%)) were identified.

Previous studies have shown that dust aerosols may accelerate the melting of snow and glaciers over the Tibetan Plateau. To investigate the vertical structure of dust aerosols, we conducted a ground-based observation by using multi-wavelength polarization lidar which is designed for continuous network measurements. In this study, we used the lidar observation from September to October 2020 at the Ruoqiang site (39.0°N, 88.2°E; 894 m ASL), located at the junction of the Taklimakan Desert–Tibetan Plateau. Our results showed that dust aerosols can be lifted up to 5 km from the ground, which is comparable with the elevation of the Tibetan Plateau in autumn with a mass concentration of 400–900 μg m−3. Moreover, the particle depolarization ratio (PDR) of the lifted dust aerosols at 532 nm and 355 nm are 0.34 ± 0.03 and 0.25 ± 0.04, respectively, indicating the high degree of non-sphericity in shape. In addition, extinction-related Ångström exponents are very small (0.11 ± 0.24), implying the large values in size. Based on ground-based lidar observation, this study proved that coarse non-spherical Taklimakan dust with high concentration can be transported to the Tibetan Plateau, suggesting its possible impacts on the regional climate and ecosystem.

Based on bubble dynamics theory, a mathematic model describing the cavitation bubble size variation in the flow field of self-resonating cavitating jet was developed considering the pressure field and mass and heat exchange between cavitation bubble and ambient fluid. With this model, the influence factors on the cavitation intensity are investigated. The results show that the destructiveness of cavitating jet in breaking rocks depends on the bubble's first collapse, with decreasing intensity in the subsequent collapses. The self-resonating effect significantly enhances the cavitation intensity by promoting the collapse pressure and elongating its duration. Hydraulic parameters are proven to be the dominating factors influencing cavitation intensity: while collapse intensity monotonously increases with jet velocity, there exists an optimum ambient pressure where highest collapse intensity can be achieved. Conversely, the fluid properties show minor influences: cavitation intensity only slightly decreases with the increasing of fluid's density and barely changes with the variation of viscosity and surface tension. The results from this investigation help to uncover the mechanism of the enhanced erosion potential of self-resonating cavitating jet. The conclusions can be used to further improve the performance of self-resonating cavitating jet in field applications. Key words: self-resonating cavitating jet, cavitating bubble, collapse intensity, hydraulic parameters, fluid properties

As the main source of dust in Asia, China often suffers from dust events. The temporal and spatial characteristics of dust events change with the variations of geography, climate and human activities. Based on the criteria of selecting dust events proposed recently by the China Environmental Monitoring Station, the hourly concentration of PM10 and PM2.5 of 336 cities in China from 2015 to 2020 were used to study the temporal and spatial characteristics of dust events more accurately and objectively. The results showed that all of the dust events in China clearly decreased, but the strong dust events did not decrease. There were 334 cities that had dust events except Shenzhen and Dongguan, 299 cities were seriously polluted due to dust events, 134 cities encountered dust level III and 56 cities encountered dust level IV. The high frequencies of dust events were mainly distributed in Northern China, especially in Northwest China. The dust contribution of PM10 to the cities in Northwest China was more than 10% and about 5–10% for PM2.5. The most likely month for dust was May. The starting time of dust was bimodally distributed, and the most common starting time was 10:00–11:00 BJT, followed by 22:00–23:00 BJT. According to the PSCF (Potential Source Contribution Function) results, the dust potential source contribution of different cities mainly came from the northwest, and was mainly affected by Mongolia in addition to the local dust in China. In addition, Beijing was obviously affected by dust recirculation. This study is of great significance to the improvement of the forecast of dust weather and the warning of heavy pollution caused by dust events.

Dust storms have occurred frequently in northwest China and can dramatically reduce visibility and exacerbate air quality in downwind regions through long-range transport. In order to study the distribution characteristics of dust particles sizes, structures and concentrations in the process of dust storm, especially for the vertical distributions, the multi-observation platform composed of six Lidars and nine aerosol analytical instruments is first used to detect a severe dust storm event, which occurred in Northwest China on 3 May 2020. As a strong weather system process, the dust storm has achieved high intensity and wide range. When the intensity of a dust storm is at its strongest, the ratios of PM2.5 (particulate matter with diameter < 2.5 µm) and PM10 (particulate matter with diameter < 10 µm) (PM2.5/PM10) in cities examined were less than 0.2 and the extinction coefficients became greater than 1 km−1 based on Lidar observations. In addition, the growth rates of PM2.5 were higher than that of PM10. The dust particles mainly concentrated at heights of 2 km, after being transported about 200–300 km, vertical height increased by 1–2 km. Meanwhile, the dust concentration decreased markedly. Furthermore, the depolarization ratio showed that dust in the Tengger Desert was dominated by spherical particles. The linear relationships between 532 nm extinction coefficient and the concentration of PM2.5 and PM10 were found firstly and their R2 were 0.706 to 0.987. Our results could give more information for the physical schemes to simulate dust storms in specific models, which could improve the forecast of dust storms.

The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.

A series of novel compounds 6a−h, 8i−1, 10s−v, and 16a−d were synthesized and evaluated, together with the known analogs 11a−f, for their inhibitory activities towards acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The inhibitory activities of AChE and BChE were evaluated in vitro by Ellman method. The results show that some compounds have good inhibitory activity against AChE and BChE. Among them, compound 8i showed the strongest inhibitory effect on both AChE (eeAChE IC50 = 0.39 μM) and BChE (eqBChE IC50 = 0.28 μM). Enzyme inhibition kinetics and molecular modeling studies have shown that compound 8i bind simultaneously to the peripheral anionic site (PAS) and the catalytic sites (CAS) of AChE and BChE. In addition, the cytotoxicity of compound 8i is lower than that of Tacrine, indicating its potential safety as anti-Alzheimer’s disease (anti-AD) agents. In summary, these data suggest that compound 8i is a promising multipotent agent for the treatment of AD.

With the rapid progress of petroleum engineering, liquid nitrogen jet is expected to be used for perforation and jet fracturing, and then provide a new method for unconventional reservoirs efficient development. In order to research the flow field characteristics and evaluate the impact capability of liquid nitrogen jet, a computation fluid dynamic model was built by coupling the nitrogen physical property equations to simulate the flow field of liquid nitrogen jet. The results indicated that given the same simulation conditions, the impact pressure of liquid nitrogen jet was equivalent to that of water jet. The liquid nitrogen jet presented more excellent impact capability than water jet because of its higher axial and radial velocities. The impact capability of liquid nitrogen jet increased with the growth of nozzle pressure drop and nozzle diameter, decreased with the increasing of standoff distance, and was slightly influenced by fluid temperature. The confining pressure hardly affected the impact capability of liquid nitrogen jet, so it can be neglected in the engineering application. This study uncovered the flow field characteristics of liquid nitrogen jet and could provide theoretical guidance for the application of perforation and fracturing with liquid nitrogen jet.