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In the context of “zero discharge” of mine water and the reverse distribution of coal and water resources in the western mining areas, the direct discharge of high-salinity mine water without proper treatment not only causes immeasurable damage to the local ecological environment, but also leads to serious water resource waste, ultimately constraining the green development of coal industry and the development of ecological civilization. The traditional zero discharge technology for high-salinity wastewater mainly relies on evaporation and crystallization to transform inorganic salts from a solution state to a crystalline state for recovery. From an economic perspective, this technology faces issues such as high investment, high operating costs, and low added value of inorganic salts. Based on this, this paper takes the mine water from a western mine as the raw water, aiming to achieve the resource utilization and desalination of mine water through the membrane integration technology, and focuses on exploring the influence of different operating conditions (operating voltage, feed solution concentration, temperature, acidity and alkalinity, current density, etc.) on the desalination performance of electrodialysis and the acid-base performance of bipolar membrane electrodialysis. Then, based on the experimental data and an economic evaluation model, the economic feasibility is explored, aiming to explore the membrane integration technology suitable for the treatment of high-salinity mine water in the western mining areas, and provide some new research ideas for the development of green resource utilization processes for high-salinity mine water. Through the exploration of the electrodialysis-bipolar membrane electrodialysis experimental process, it is found that the feed solution concentration of the bipolar membrane system should not exceed 80 g/L, the appropriate operating voltage is 18 V, the suitable feed solution temperature is 25 ℃, the feed solution pH should be kept neutral, and constant voltage operation is more suitable. In addition, it is confirmed that the membrane integration system centered on bipolar membrane electrodialysis can achieve the green resource utilization of high-salinity mine water. Taking the total salt content of the electrodialysis system feed solution as an example (20 g/L), the overall net profit is ￥18604299 per year, and it has a significant carbon dioxide emission reduction effect when coupled with a photovoltaic power supply system, with a carbon dioxide emission reduction of over 3162 tons per year, demonstrating good economic and social benefits.

Remaining useful life (RUL) prediction is widely applied in prognostic and health management (PHM) of turbofan engines. Although some of the existing deep learning-based models for RUL prediction of turbofan engines have achieved satisfactory results, there are still some challenges. For example, the spatial features and importance differences hidden in the raw monitoring data are not sufficiently addressed or highlighted. In this paper, a novel multi-head self-Attention fully convolutional network (MSA-FCN) is proposed for predicting the RUL of turbofan engines. MSA-FCN combines a fully convolutional network and multi-head structure, focusing on the degradation correlation among various components of the engine and extracting spatially characteristic degradation representations. Furthermore, by introducing dual multi-head self-attention modules, MSA-FCN can capture the differential contributions of sensor data and extracted degradation representations to RUL prediction, emphasizing key data and representations. The experimental results on the C-MAPSS dataset demonstrate that, under various operating conditions and failure modes, MSA-FCN can effectively predict the RUL of turbofan engines. Compared with 11 mainstream deep neural networks, MSA-FCN achieves competitive advantages in terms of both accuracy and timeliness for RUL prediction, delivering more accurate and reliable forecasts.

Micro/nanoplastics (MNPs), as emerging pollutants, have been detected in both the maternal and fetal sides of the placenta in pregnant women, and their reproductive toxicity has been demonstrated in in vivo and in vitro experimental models. The Targeted Risk Assessment of Environmental Chemicals (TRAEC) strategy has been innovatively devised to facilitate valid risk assessment, encompassing a comprehensive evaluation of reliability, correlation, outcome fitness, and integrity across four dimensions based on the included published evidence and our own findings. This study serves as an application case of TRAEC, with 40 items of research evidence on the toxicity of MNPs to the placenta, which were rigorously screened and incorporated into the final scoring system. The final score for this TRAEC case study is 5.63, suggesting a moderate-to-low risk of reproductive toxicity associated with MNPs in the placenta, which may potentially increase with decreasing particle size. It is essential to emphasize that the findings also report original data from assays indicating that exposure to high-dose groups (100 μg/mL, 200 μg/mL) of 50 nm and 200 nm polystyrene nanoplastics (PS-NPs) induces HTR8/SVneo cell cycle arrest and cell apoptosis, which lead to reproductive toxicity in the placenta by disrupting mitochondrial function. Overall, this study employed the TRAEC strategy to provide comprehensive insight into the potential reproductive health effects of ubiquitous MNPs.

The main coal producing areas in western China have the problems of dry climate and water shortage, and the mine water produced by coal mining generally has the characteristics of high salinity and high hardness. At present, the zero-discharge treatment of high-salinity mine water generally has the problems of complex process and high operating cost. In order to shorten the treatment process and improve the treatment efficiency, in this study, the vacuum membrane distillation technology was applied to replace the existing multi-stage reverse osmosis membrane concentration technology for the high-salinity mine water concentration and desalination treatment process. The high-salinity mine water after a lime-soda softening treatment was treated with different concentration ratios, and the membrane fouling mechanism and membrane cleaning method during the concentration process were studied. The results showed that with the increase of the concentration ratio, the membrane flux and desalination rate of the polyvinylidene fluoride (PVDF) hollow fiber membrane gradually decreased, while the conductivity of the produced water increased slowly. When the concentration ratio was up to 27 times, the membrane flux was 8.87 L/(m2·h), the salt rejection rate was 99.7%, and the water conductance was 26.6 μS/cm. The membrane distillation process was inhibited by the membrane fouling caused by the scaling of calcium and magnesium ions in mine water, and the inorganic salt deposits could not be removed by physical methods such as backwashing and ultrasonic cleaning. After 96 hours of continuous operation, the PVDF membrane flux reduced from 12.85 L/(m2·h) to 5.21 L/(m2·h). The pretreatment process of hardness removal had obvious influence on the calcium and magnesium scaling in the membrane distillation process. When the hardness removal rate exceeded 95%, the desalting rate and membrane flux attenuation of PVDF membrane were obviously weakened. The membrane fouling caused by the calcium and magnesium precipitation could be effectively removed by the citric acid cleaning agent. Under the optimized conditions of citric acid concentration of 0.87 mol/L, the cleaning temperature of 38 ℃ and the cleaning time of 40 min, the membrane cleaning efficiency could reach 99.5%. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) were used to characterize the microscopic morphology and structure of the original film, the contaminated film and the film after chemical cleaning. The results showed that the deposited pollutants on the surface of the cleaned film were significantly reduced, but the surface morphology and microscopic structure were irreversibly changed.

Heat treatment, particularly solution heat treatment, is a critical process in the preparation of powder metallurgy superalloys, where the cooling process significantly impacts the microstructure. This study, based on thermodynamic and kinetic databases as well as the precipitation mechanism of strengthening phases, delves into the influence of cooling process, especially the cooling path, on the material’s microstructure. The results indicate that under slow cooling rates, the precipitated phases are more likely to exhibit a multimodal size distribution, while under rapid cooling rates, a unimodal distribution may form. The average cooling rate does not consistently accurately reflect the growth of the precipitated phases; even with the same average cooling rate, different cooling paths can lead to significant differences in the size of the precipitates. To accurately predict the size of the precipitates, it is necessary to consider the specific cooling process. Constant cooling rate experiments designed for the study and the dissection testing of full-size turbine discs produced in manufacturing validated the calculated results of the precipitates. Therefore, optimizing cooling through simulation calculations can effectively and accurately control the precipitates, thereby obtaining a microstructure that can meet performance requirements.

Regulating the microstructure of powder metallurgy (P/M) nickel-based superalloys to achieve superior mechanical properties through heat treatment is a prevalent method in turbine disk design. However, in the case of dual-performance turbine disks, the complexity and non-uniformity of the heat treatment process present substantial challenges. The prediction of yield strength is typically derived from the analysis of microstructures under various heat treatment regimes. This method is time-consuming, expensive, and the accuracy often depends on the precision of microstructural characterization. This study successfully employed a coupled method of Artificial Neural Network (ANN) and finite element analysis (FEA) to reveal the relationship between the heat treatment process and yield strength. The coupled method accurately predicted the location specified and temperature-dependent yield strength based on the heat treatment parameters such as holding temperatures and cooling rates. The root mean square error (RMSE) and mean absolute percentage deviation (MAPD) for the training set are 50.37 and 3.77, respectively, while, for the testing set, they are 50.13 and 3.71, respectively. Furthermore, an integrated model of FEA and ANN is established using a Abaqus user subroutine. The integrated model can predict the yield strength based on temperature calculation results and automatically update material properties of the FEA model during the loading process simulation. This allows for an accurate calculation of the stress–strain state of the turbine disk during actual working conditions, aiding in locating areas of stress concentration, plastic deformation, and other critical regions, and provides a novel reliable reference for the rapid design of the turbine disk.

Fluoride ions are widely distributed in surface rivers and groundwater bodies in China, especially in the mining areas along the Yellow River in the western Yellow River basin that there is a widespread problem of excessive fluoride in the mine water, which poses a potential threat to the local ecological environment and human health. The status quo of fluoride pollution in China is mostly at a low concentration pollution level, which leads to it difficult to remove efficiently through conventional water treatment technologies. The adsorption method is considered to be an effective way to remove low concentration fluoride ions because of its high adsorption efficiency and convenient operation. The research status of fluoride removal by commonly used adsorption materials such as carbon based, minerals, metals and metal organic frameworks (MOFs) was reviewed and summarized before summarizing the influence of different factors on the fluoride removal efficiency and adsorption mechanism of these adsorption materials. Then the application effect and operation cost of adsorption method in mine water treatment were emphatically analyzed, and the development direction of adsorption method in the treatment of low concentration (

Cell cycle-dependent kinase 2 (CDK2) is located downstream of CDK4/6 in the cell cycle and regulates cell entry into S-phase by binding to Cyclin E and hyper-phosphorylating Rb. Proto-oncogene murine double minute 2 (MDM2) is a key negative regulator of p53, which is highly expressed in tumors and plays an important role in tumorigenesis and progression. In this study, we identified a dual inhibitor of CDK2 and MDM2, III-13, which had good selectivity for inhibiting CDK2 activity and significantly reduced MDM2 expression. In vitro results showed that III-13 inhibited proliferation of a wide range of tumor cells, regardless of whether Cyclin E1 (CCNE1) was overexpressed or not. The results of in vivo experiments showed that III-13 significantly inhibited proliferation of tumor cells and did not affect body weight of mice. The results of the druggability evaluation showed that III-13 was characterized by low bioavailability and poor membrane permeability when orally administered, suggesting the necessity of further structural modifications. Therefore, this study provided a lead compound for antitumor drugs, especially those against CCNE1-amplified tumor proliferation.

Volatile organic compounds (VOCs) exposure has been found to be associated with neurological dysfunction, with depression often being one of the classic symptoms of the disease, and indoor environments are more likely to be enriched with concentrations of VOCs. This cross-sectional study measured VOCs levels in whole blood, and estimated level of depression with the Patient Health Questionnaire in adults from NHANES 2013–2018. We found benzene (β = 0.40, 95%CI: 0.19, 0.61) and ethylbenzene (β = 0.22, 95%CI: 0.05, 0.39) were associated with depression adjusted for covariates in general linear regression models (GLM), and remained the consistent trend in quantile regression models. In indoor subgroup with higher VOCs level, benzene (β = 0.71, 95%CI: 0.21, 1.22), ethylbenzene (β = 0.47, 95%CI: 0.15, 0.78), and m-/p-xylene (β = 0.41, 95%CI: 0.15, 0.68) showed significant association with depression adjusted for covariates including cotinine in GLMs. Weighted quantile sum (WQS) model was used to assess the contribution of each VOC in mixed exposure. Results from WQS analyses revealed significantly positive associations between the mixed exposure and depression (β = 1.70, 95%CI: 1.18, 2.47), in which, benzene and ethylbenzene contributed 56% and 26%. We found statistically association between mixed exposure and depression before cotinine adjustment (β = 3.53, 95%CI: 2.78, 4.47). Our founding indicated a positive association between benzene and ethylbenzene exposure and depression, also with the most important effect in the mixture. Additionally, indoor VOCs sources of environmental pollution still cannot be ignored given the higher exposure level and health risk.

Introduction: Schizophrenia is a serious mental illness that requires effective treatment with minimal adverse effects. As preclinical and clinical research progresses, trace amine-associated receptor 1 (TAAR1) is becoming a potential new target for the treatment of schizophrenia.Methods: We used molecular docking and molecular dynamics (MD) simulations to discover TAAR1 agonists. The agonistic or inhibitory effects of compounds on TAAR1, 5-HT1A, 5-HT2A, and dopamine D2-like receptors were determined. We used an MK801-induced schizophrenia-like behavior model to assess the potential antipsychotic effects of compounds. We also performed a catalepsy assay to detect the adverse effects. To evaluate the druggability of the compounds, we conducted evaluations of permeability and transporter substrates, liver microsomal stability in vitro, human ether-à-go-go-related gene (hERG), pharmacokinetics, and tissue distribution.Results: We discovered two TAAR1 agonists: compounds 50A and 50B. The latter had high TAAR1 agonistic activity but no agonistic effect on dopamine D2-like receptors and demonstrated superior inhibition of MK801-induced schizophrenia-like behavior in mice. Interestingly, 50B had favorable druggability and the ability to penetrate the blood-brain barrier (BBB) without causing extrapyramidal symptoms (EPS), such as catalepsy in mice.Conclusion: These results demonstrate the potential beneficial role of TAAR1 agonists in the treatment of schizophrenia. The discovery of a structurally novel TAAR1 agonist (50B) may provide valuable assistance in the development of new treatments for schizophrenia.

A new grain growth model was developed by introducing the ultimate grain size to the traditional model. The grain growth behavior and its ultimate size under the Zenner pinning force are also discussed. This model was applied to the nickel-based superalloy and integrated into an FEM code. The grain evolution of a forged third-generation powder superalloy heat treated at different temperatures and holding times was studied. A gradient heat treatment setup was designed and implemented for a full-size turbine disc based on the model prediction to meet the accurate dual-microstructure requirements of an advanced aero-engine turbine disc design. The predicted temperature was validated by thermal couple measurements. The relative error between the prediction and the measurements is less than 2%. The metallographic examination of the whole turbine disk through sectioning showed that the grain size was ASTM 7-8 at the rim area and ASTM 11-12 at the bore region, which agrees well with the prediction. The predicted values of the three measurement areas are ASTM 12.1, ASTM 9.1, and ASTM 7.1, respectively, with a maximum error of 5% compared to the measured values. The proposed model was validated and successfully applied to help manufacture a dual-microstructure aero-engine turbine disc.

Pyridaben (PY) is a widely used organochlorine acaricide, which can be detected in the peripheral blood of pregnant women. Available evidence suggests that PY has reproductive toxicity. However, it remains uncertain whether prenatal PY exposure impacts neurobehavioral development in offspring. Here, we administered PY to pregnant mice at a dose of 0.5 and 5 mg kg−1 day−1 via gavage and observed anxiety-like behaviors in PY offspring aged five weeks. We then integrated the metabolome and transcriptome of the offspring's brain to explore the underlying mechanism. Metabolome data indicated that the vitamin B6 metabolism pathway was significantly affected, and the pyridoxal 5′-phosphate (PLP) concentration and the active form of vitamin B6 was significantly reduced. Moreover, the transcriptome data showed that both PLP generation-related Pdxk and anxiety-related Gad1 were significantly down-regulated. Meanwhile, there was a decreasing trend in the concentration of GABA in the hippocampal DG region. Next, we supplemented PLP at a dose of 20 mg kg−1 day−1 to the PY offspring via intraperitoneal injection at three weeks. We found up-regulated expression of Pdxk and Gad1 and restored anxiety-like behaviors. This study suggests that prenatal exposure to PY can disrupt vitamin B6 metabolism, reduce the concentration of PLP, down-regulate the expression levels of Pdxk and Gad1, inhibit the production of GABA, and ultimately lead to anxiety-like behaviors in offspring.

The S-wave DD⁎ scattering in the isospin I=0,1 channels is studied in Nf=2 lattice QCD at mπ≈350 MeV. It is observed that the DD⁎ interaction is repulsive in the I=1 channel when the DD⁎ energy is near the DD⁎ threshold. In contrast, the DD⁎ interaction in the I=0 channel is definitely attractive in a wide range of the DD⁎ energy. This is consistent with the isospin assignment I=0 for Tcc+(3875). By analyzing the components of the DD⁎ correlation functions, it turns out that the quark diagram responsible for the different properties of I=0,1 DD⁎ interactions can be understood as the charged ρ meson exchange effect. This observation provides direct information on the internal dynamics of Tcc+(3875).

A large amount of mine water is generated during coal production, which not only damages the surface environment and ecology but also wastes groundwater resources in the mining area, exacerbating regional water scarcity. In this work, a novel zero liquid discharge technology combining selectrodialysis (SED) and bipolar membrane electrodialysis (BMED) was developed for the resourceful treatment of low-salinity mineralized wastewater. The SED stack had demonstrated to be workable for the elimination of multivalent ions. The BMED stack converts brine into acid and base. After SED, a high pure crude salt (~98%) was attained. Furthermore, under the conditions of a current density of 20 mA/cm2, a flow velocity of 20 L/h, and an initial acid/base concentration of 0.10 mol/L, the maximum concentrations of acid and base were found to be 0.75 mol/L and 0.765 mol/L, respectively, for a feed conductivity of 55 mS/cm. The cost of the entire electrodialysis stage was evaluated to be USD 1.38/kg of NaOH. Therefore, this combined UF-RO-SED-BMED process may be an effective strategy for the sustainable treatment of low-salinity mineralized wastewater.

We carry out the first lattice QCD derivation of the mixing energy and the mixing angle of the pseudoscalar charmonium and glueball on two gauge ensembles with Nf=2 degenerate dynamical charm quarks. The mixing energy is determined to be 49(6) MeV on the near physical charm ensemble, which seems insensitive to charm quark mass. By the assumption that X(2370) is predominantly a pseudoscalar glueball, the mixing angle is determined to be approximately 4.6(6)∘, which results in a +3.9(9) MeV mass shift of the ground state pseudoscalar charmonium. In the mean time, the mixing can raise the total width of the pseudoscalar charmonium by 7.2(8) MeV, which explains to some extent the relative large total width of the ηc meson. As a result, the branching fraction of ηc→γγ can be understood in this cc¯-glueball mixing framework. On the other hand, the possible discrepancy of the theoretical predictions and the experimental results of the partial width of J/ψ→γηc cannot be alleviated by the cc¯-glueball mixing picture yet, which demands future precise experimental measurements of this partial width.

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences. Public summary: • “Can machines think?” The goal of artificial intelligence (AI) is to enable machines to mimic human thoughts and behaviors, including learning, reasoning, predicting, and so on. • “Can AI do fundamental research?” AI coupled with machine learning techniques is impacting a wide range of fundamental sciences, including mathematics, medical science, physics, etc. • “How does AI accelerate fundamental research?” New research and applications are emerging rapidly with the support by AI infrastructure, including data storage, computing power, AI algorithms, and frameworks.

In this paper, we present an efficient amplitude shift keying (ASK)-aided orthogonal chaotic vector PSK (ASK-OCVPSK) non-coherent modulation scheme with considerations of different quality of service (QoS) demands. In our ASK-OCVPSK design, the reference chaotic signal is generated recursively from the shifted chaotic vectors orthogonalized by the Gram-Schmidt transform buffered in the shift register. Then, we embed the information on both the position and the amplitude of the chaotic sequence. The binary information bitstream is divided into two segments, which are modulated, respectively, by the parallel concatenated position shift keying (PSK) scheme and the ASK scheme. Next, the ASK symbol is further modulated by the PSK modulated chaotic vector, and the resultant symbol is transmitted together with the reference chaotic vector. Notably, with the aid of the shift register, only one chaotic vector is transmitted and the reference chaotic sequences can be easily regenerated recursively at the receiver for information recovery. Furthermore, we derive the theoretical bit error rate (BER) expressions for the proposed system over additive white Gaussian noise (AWGN) channel. Then, the spectrum efficiency and the complexity of the proposed scheme are analyzed and compared with those of the counterpart schemes. Simulations are performed over the AWGN channel and multipath Rayleigh fading channel, and the results demonstrate that the theoretical BER matches the simulation results. Moreover, the results verify that the presented scheme are more efficient and more reliable than the counterpart schemes and can provide different BER performances without changing the modulator structure to meet the different QoS demands of the users.

We have studied the dynamic scanning of liquid-crystalline(LC) poly(p-phenyleneterephthalamide) sulfuric acid (PPTA-H2SO4) solution, and its blend with single-walled carbon nanotubes (SWNTs), by using a flat plate rotational rheometer. The effects of weight concentration and molecular weight of PPTA, as well as operating temperature, on dynamic viscoelasticity of the PPTA-H2SO4 LCsolution system are discussed. The transition from a biphasic system to a single-phase LC occurs in the weight concentration range of SWNTs from 0.1% to 0.2%, in which complex viscosity reaches the maximum at 0.2 wt% and the minimum at 0.1 wt%, respectively, of SWNTs. With increasing SWNT weight concentration, the endothermic peak temperature increases from 73.6 to 79.9 °C. The PPTA/SWNT/H2SO4 solution is in its plateau zone and storage modulus (G´) is a dominant factor within the frequency (ω) range of 0.1–10 rad/s. As w increases, the G´ rises slightly, in direct proportion to the w. The loss modulus (G´´) does not rise as a function of ω when ω < 1 s−1, then when ω > 1 s−1 G´´ increases faster than G´, yet not in any proportion to the ω.