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In order to investigate the evolution characteristics of the key groups and their thermal effects under the effect of oxygen-depleted, the thermal reaction process of coal under different oxygen concentrations and the change law of its microscopic groups were studied by using Differential Scanning Calorimetry experiments and in-situ Fourier Transform Infrared Spectroscopy experiments. The results indicate that the coal spontaneous combustion exothermic process can be divided into five stages: evaporation heat absorption, oxidation heat release, decomposition heat storage, combustion heat release, and burnout, and the groups can be categorized into four groups: aromatic hydrocarbon compounds, aliphatic hydrocarbon compounds, hydroxyl groups and carbon-oxygen groups. With the increase of reaction temperature, —C=C— in coal decreased gradually, aliphatic hydrocarbon compounds and carbon-oxygen groups first increased and then decreased, and hydroxyl groups showed a two-stage decreasing trend. With the decrease of oxygen concentration, the coal reaction heat flow curve and characteristic temperature shifted to the high temperature region, and the reaction intensity, heat release and exothermic characteristic parameters decreased. Oxygen did not change the laws of the coal spontaneous combustion exothermic process and variations of groups, but it would significantly affect its key temperature nodes. Further, the grey correlation and quantum chemical methods were used to determine the evolutionary characteristics of key groups and their reactive thermal effects. The results showed that the trend of the most key groups of exothermic process of coal spontaneous combustion at any oxygen concentration was —OH-1→—COO—→Ar—CH→Ar—CH, but the key groups were attributed to hydroxyl group → carbon-oxygen → aliphatic compound → carboxylic compound. The key groups and their attribution had not been changed in the exothermic process of coal spontaneous combustion in the oxygen-depleted state. The production of H2O and CO during coal spontaneous combustion is a spontaneous exothermic reaction, whereas the reaction of C2H4 and C2H2 production is a non-spontaneous absorptive reaction, and the sensitivity of C2H4 and C2H2 as spontaneous combustion indicator gases is stronger than that of the first two. The C2H2 generation reaction is one of the key reasons for the emergence of a significant endothermic peak in the coal oxidation exothermic stage, and the combustion of aromatic hydrocarbons to produce CO and CO2 is one of the main reasons for the intense exothermic process of coal combustion.

Abstract Background Computed tomography (CT) is widely in clinics and is affected by metal implants. Metal segmentation is crucial for metal artifact correction, and the common threshold method often fails to accurately segment metals. Purpose This study aims to segment metal implants in CT images using a diffusion model and further validate it with clinical artifact images and phantom images of known size. Methods A retrospective study was conducted on 100 patients who received radiation therapy without metal artifacts, and simulated artifact data were generated using publicly available mask data. The study utilized 11,280 slices for training and verification, and 2,820 slices for testing. Metal mask segmentation was performed using DiffSeg, a diffusion model incorporating conditional dynamic coding and a global frequency parser (GFParser). Conditional dynamic coding fuses the current segmentation mask and prior images at multiple scales, while GFParser helps eliminate high-frequency noise in the mask. Clinical artifact images and phantom images are also used for model validation. Results Compared with the ground truth, the accuracy of DiffSeg for metal segmentation of simulated data was 97.89% and that of DSC was 95.45%. The mask shape obtained by threshold segmentation covered the ground truth and DSCs were 82.92% and 84.19% for threshold segmentation based on 2500 HU and 3000 HU. Evaluation metrics and visualization results show that DiffSeg performs better than other classical deep learning networks, especially for clinical CT, artifact data, and phantom data. Conclusion DiffSeg efficiently and robustly segments metal masks in artifact data with conditional dynamic coding and GFParser. Future work will involve embedding the metal segmentation model in metal artifact reduction to improve the reduction effect.

Abstract Clean fire extinguishing systems applicable to the pottery jar liquor warehouse are in demand. In this study, taking 53vol% liquor as the research subject, fire models of various clean fire extinguishing systems comprising water mist, liquid carbon dioxide (LCO2) and liquid nitrogen (LN2) were established using a fire dynamic simulator to determine their fire extinguishing effect. A feasibility assessment of systems was performed under different fire source types, fire source sizes, and ventilation conditions. The fire extinguishing efficiency was analyzed in terms of the fire extinguishing time, oxygen concentration, and space temperature. The results showed that the success rate of the LCO2 and LN2 fire extinguishing systems was 100%, whereas the success rate of the water mist fire extinguishing system was 95%. In terms of reducing the oxygen concentration at the bottom of the space and the temperature in the space, the LCO2 system exhibited the best performance, followed by the LN2 system, and lastly the water mist. Under different ventilation conditions and fire source types, the LCO2 fire extinguishing system was least affected, whereas the effectiveness of the water mist fire extinguishing system reduced under natural ventilation conditions, and the extinguishing efficiency of the LN2 fire extinguishing system was affected by the fire source type. Overall, the LCO2 system presented more advantages in extinguishing fires in pottery jar liquor warehouses and can provide a new idea for the development and application of clean and efficient fire extinguishing systems.

In this study, coal samples' reactive group contents were changed using extractants, and the effects of the reactive group contents spontaneous coal combustion were investigated using infrared spectroscopy, thermogravimetry/derivative thermogravimetry, and differential scanning calorimetry. The results showed that the coal samples' hydroxyl group contents decreased in the order ethylenediamine (3.832 %) > N-methyl-2-pyrollidone mixed solution (2.091 %) > petroleum ether (0.882 %) > toluene (0.495 %) and that the hydroxyl group content was inversely related to the characteristic temperature point. RDG analysis showed that ethylenediamine formed N–H–O hydrogen bonds with hydroxyl-group-bearing molecules, coal molecules formed C–H–O hydrogen bonds with NMP molecules, petroleum ether generated a cumulative dispersive force with aliphatic side chains, and toluene molecules' benzene rings formed a very stable spatial structure with coal molecules' benzene rings. The thermogravimetry/derivative thermogravimetry curves showed that because the characteristic temperature points of the extracted coal samples moved to the high-temperature region from T5 onward, the coal samples had to be heated to a higher temperature to reach the energy required for the reaction. From the DSC thermograms, the exergy decreased in the order toluene (110.68 J/g) > NMP (110.52 J/g) > ethylenediamine (78.29 J/g) > petroleum ether (65.45 J/g). With increasing temperature from T1 to T6, the Pearson correlation coefficients of the alcoholic and phenolic hydroxyl groups were calculated at −0.7, −0.72, −0.93, −0.84, −0.8, −0.8, and −0.93 and −0.72, −0.91, −0.83, −0.79, −0.815, and −0.91, respectively, indicating that the hydroxyl group content influenced the coal's spontaneous combustion more than the other groups' contents.

IntroductionTo assess the prevailing trends in the incidence of ischemic heart disease (IHD) across 204 countries and territories from 1990 to 2019, and to elucidate their correlations with age, period, and birth cohort, a comprehensive analysis was conducted.MethodsFrom 1990 to 2019, we employed the Global Burden of Disease Study (GBD) Results Tool in conjunction with an age-period-cohort model. This approach facilitated the estimation of annual percentage changes in incidence, referred to as net drifts, encompassing the overall population. Additionally, we calculated annual percentage changes spanning ages 15 - 19 to 95 + years, denoted as local drifts. Furthermore, our analysis involved determining period and cohort relative risks, elucidating the effects associated with distinct periods and birth cohorts.ResultsGlobally, 21,203,479 [95% uncertainty interval (UI): 18,799,322 − 23,704,124] cases of IHD occurred in 2019. There were 33 countries with at least 100000 cases. Between 1990 and 2019, the net drift of IHD incidence exhibited a range from −1.7% per year [95% confidence interval (CI): −1.79, −1.61] in countries with a high socio-demographic index (SDI) to 0.08% per year (95% CI: 0.05, 0.11) in countries with a low SDI. Age effects across all countries and genders demonstrated an increasing trend over time, indicating age as a significant risk factor for IHD. Moreover, period and cohort effects in higher SDI countries exhibited a more rapid decline in both genders compared to lower SDI countries. The findings indicated that nations with a higher SDI manifested overall favorable trends in the relative risk of IHD incidence, both across time and in successive younger birth cohorts.DiscussionThe incidence of IHD serves as a valuable and accessible indicator for assessing trends in IHD provision, spanning from early youth through later life. Enhancements in IHD prevention have the potential to mitigate risks for successively younger cohorts and, over time, redistribute the risk across all age groups. Despite global declines in IHD incidence over the last three decades, decreasing trends in incidence have slowed and, in some countries, flattened. Many countries have experienced unfavorable period and cohort effects.

Emerging mycotoxins enniatins (ENNs) and beauvericin (BEA) pose potential health risks to humans through dietary exposure. However, research into their mechanisms of toxicity is limited, with a lack of comprehensive toxicological data. This study investigates from a hepatic lipid metabolism perspective, establishing a more precise and reliable 3D HepaRG hepatocyte spheroid model as an alternative for toxicity assessment. Utilizing physiological indices, histopathological analyses, lipidomics, and molecular docking techniques, it comprehensively elucidates the effects of ENNs and BEA on hepatic lipid homeostasis and their molecular toxicological mechanisms. Our findings indicate that ENNs and BEA impact cellular viability and biochemical functions, significantly altering lipid metabolism pathways, particularly those involving glycerophospholipids and sphingolipids. Molecular docking has demonstrated strong binding affinity of ENNs and BEA with key enzymes in lipid metabolism such as Peroxisome Proliferator-Activated Receptor α (PPARα) and Cytosolic Phospholipase A2 (cPLA2), revealing the mechanistic basis for their hepatotoxic effects and potential to impair liver function and human health. These insights enhance our understanding of the potential hepatotoxicity of such fungal toxins and lay a foundation for the assessment of their health risks.

Liquid organic hydrogen carriers (LOHCs), such as methanol and formic acid, offer a reliable solution for the challenges associated with transporting and storing gaseous hydrogen. However, the current industrial LOHCs are costly and in limited supply due to complex synthesis methods involving gasification and Fischer-Tropsch synthesis. An alternative approach utilizing efficient pyrolysis methods can convert biomass into substances that mimic LOHCs, making them a promising avenue for hydrogen storage. Compounds with a high hydrogen content, including glycolaldehyde, acetic acid, and acetol, hold potential as effective LOHCs. This study seeks to assess how the specific properties of biomass impact the resulting products and target molecules, focusing on identifying the primary sources of LOHC compounds. The experimental results indicate that glycolaldehyde primarily originates from cellulose, while acetic acid is mainly derived from hemicellulose. Acetol is produced from both cellulose and hemicellulose. At a pyrolysis temperature of 500 °C and a particle size of 0.38–0.83 mm, corn cob yields a higher quantity of glycolaldehyde, acetic acid, and acetol (107 mg/g) compared to rice husk (85.6 mg/g) and pine (68.9 mg/g) due to its significant cellulose and hemicellulose content. Notably, the primary sources of these hydrogen storage molecules during pyrolysis are the initial biomass pyrolysis products rather than secondary reactions.

Sodium zirconate (Na2ZrO3) is a promising material for pre-combustion CO2 capture due to its fast sorption kinetics and excellent cyclic stability at high temperatures under ideal condition (desorption in 100% N2). Still, there is a lack of study on the performance of Na2ZrO3 cyclic capture under harsh condition (desorption in high concentration CO2). In this study, Na2ZrO3 was prepared by wet-mixing and heated-drying, and the difference in the cyclic CO2 capture performance of the sample was compared between desorption under harsh condition and vacuum condition. The crystal structure of Na2ZrO3 was identified during the sorption-desorption cycles. The crystal structure was also modeled and simulated to analyze the reason for the superior capture performance from the monoclinic Na2ZrO3. It was found that the special interlocked and multilayered stacked structure of the monoclinic Na2ZrO3 allowed for high reactivity with CO2. It was found that high temperature solely had little help in the desorption of Na2ZrO3 under harsh condition, but vacuum condition promoted desorption of Na2ZrO3 in high fraction CO2, and vacuum desorption at 1000 °C-1050 °C resulted in Na2ZrO3 with both good capture performance and cycling stability. Vacuum desorption led to more complete reversion of Na2ZrO3 to the monoclinic state, benefiting for CO2 capture. This study attempted to simulate the harsh capture environments of real industrial applications and to explore the possibility of Na2ZrO3 as a carbon capture material for pre-combustion capture.

To study combustion and extinction characteristics of flames perturbed by acoustic waves, the evolution of the shape of the pool fire, mass loss rate (ma′) of fuel, and mechanisms of extinction of the flames under acoustic perturbations were studied. Moreover, based on parameters of combustion characteristics of flames, parametric models of ma′ and flame extinction were developed. The research results demonstrate that the shapes of unperturbed flames change during combustion, however, when perturbed by acoustic waves, the flame shapes become irregular and the flame fronts become disorderly. Compared with the combustion of unperturbed flames, ma′ is increased under acoustic perturbation. There are upper and lower limits for the change of ma′, so the models of upper and lower limits of ma′ in the concentrated area were established. Low–frequency acoustic waves tend to extinguish the pool fire, and the increased distance of acoustic response and acoustic source power can promote flame extinction. A linear relationship between flame extinction and acoustic frequency was semi-quantitatively characterized by a modified Damköhler (Da*) number. Based on the critical oscillation–induced displacement for extinguishing a pool fire, local acoustic parameters were characterized, and a critical model for local displacement during the extinction of the pool fire was established.

Phenol pollution is widely environmental and health problems that require new insights and urgent attention. A iron-bearing catalyst (FRM/2%A) was prepared with red mud by HCl dissolution, ascorbic acid reducing and precipitation of filter liquor, and activated H2O2 to degrade the phenol in synthetic wastewater. Results show that FRM/2%A had the highest degradation efficiency (99.3 %) in the reaction time of 5 min among investigative samples, due to the production of ferrous polymetallic oxides on the catalyst and the formation of mesoscopic particles and microcellular structures. The optimal conditions were 1 g/L of catalyst dosage, 5 mM of H2O2 concentration, 3–6 of initial pH and 100 mg/L of initial concentration of phenol in the FRM/2%A/H2O2 system. The degradation data fit into the pseudo-first-order kinetics model and the reaction rate constant (k) of FRM/2%A was 0.865 min−1. The removal efficiency (77 %) of COD below the value (99.3 %) of phenol degradation implied the intermediates generating during the phenol degradation. The possible degradation pathway was proposed as phenol → catechol → benzoquinone → muconic acid → small molecular organic acids → CO2 and H2O. The findings suggested a new way for the synthesis of the efficient catalyst with RM and optimal operating strategies for the treatment of phenol wastewater.

Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are taken as the features from the overall perspective. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. To address this issue, we proposed a framework to predict the cognitive function status in the patients with end-stage renal disease (ESRD) at a functional subnetwork scale (CFSFSS). The nodes from different network indicators were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combination with improved fitness was searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the parameters of support vector regression (SVR) and solve the global optimization problem of the predictive model. Experimental results indicated that CFSFSS achieved superior predictive performance compared to other methods, by which the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were up to 0.5951, 0.0281 and 0.9994, respectively. The functional subnetwork effectively identified the active brain regions associated with the cognitive function status, which offered more precise features. It not only helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients.

The Zn/Cr-MOFs/TiO2 composites were synthesized using the solvothermal method. XRD, FTIR, and SEM techniques were utilized to characterize the Zn/Cr-MOFs/TiO2 composites employed for simulating levofloxacin hydrochloride in wastewater. The impact of the mass of the Zn/Cr-MOFs/TiO2 composite, concentration of levofloxacin hydrochloride, solution pH, and temperature on the adsorption performance was investigated. Experimental findings indicated that at pH 6, the maximum removal efficiency of levofloxacin hydrochloride by the Zn/Cr-MOFs/TiO2 composite was achieved at 88.8%, with an adsorption capacity of 246.3 mg/g. To analyze the experimental data, both pseudo-first-order and pseudo-second-order kinetics models were applied, revealing that the pseudo-second-order model provided a better fit to the data. Additionally, Langmuir and Freundlich isotherm models were used to study equilibrium adsorption behavior and showed good agreement with both kinetic modeling and Langmuir isotherm analysis results. These observations suggest that monolayer adsorption predominates during the removal process of levofloxacin hydrochloride by Zn/Cr-MOFs/TiO2 composites.

M-cresol, one of phenolics, is highly toxic, refractory, and threatens human health and ecological safety. The study on the efficient m-cresol degradation technologies is crucial and helpful to restrain its discharge into water body. A composite of MnO-doped red mud (RM) to activate peroxymonosulfate (PMS) for the m-cresol degradation was fabricated and employed, favorable to the recycling and utilization of RM. Considering the catalytic activity and cost, 0.1 M/RM@G exhibited an excellent degradation capacity attributing to strong Fe3O4 and MnO synergy and was considered as the best catalyst among the investigative catalysts. 100 % of m-cresol and 71.4 % of COD could be degraded within 90 min under 2 g/L catalyst, 10 mM of PMS, 3-8 of initial pH and 50 mg/L m-cresol in the 0.1 M/RM@G/PMS system. The reaction rate constant (0.045 min−1) of 0.1 M/RM@G was much larger than RM@G (0.012 min−1), ARM (0.0048 min−1) and WRM (0.0028 min−1). Main Mn and Fe active components and abundant mesoporous structures on the catalyst surface could efficiently drove electron transfers, and further accelerated the redox cycles of Mn(III)Mn(II) and Fe(III)Fe(II) for activating PMS. 1O2 played a crucial role in degrading m-cresol. Based on the experiment data, the generation mechanism of radicals and the possible pathways of m-cresol degradation were proposed in the 0.1 M/RM@G/PMS system. This finding provides a new way for the synthesis of the efficient catalyst with RM and optimal operating strategies for the treatment of m-cresol wastewater.

Facilitating energy resource deficiency and environmental contamination, this work focuses on sustainable biodiesel production through the esterification reactions of oleic acid (OA) with methanol. To address the reaction, a novel heterogeneous acid catalyst, 12-tungstophosphoric acid (TPA) immobilized on Sn-based MOFs (Sn(II)-BDC) was synthesized via a simple, green solvent, and easy-to-implement synthesis strategy for the first time, and applied effectively for esterification process of OA to produce biodiesel. The structure and composition of as-obtained catalyst have been verified using XRD, FTIR, N2 physisorption, SEM, EDX, TG, Py-FTIR, TPD-NH3, and XPS techniques. The obtained TPA/Sn(II)-BDC catalyst was found to be the best with 60 wt% of TPA loading, which resulted in an OA conversion of 91.7 % at optimized conditions of 0.15 g catalyst loading and methanol to OA molar ratio of 20:1 at temperature of 120 °C in 4 h, and the excellent performance arises from available pores structure, large amounts of acidic sites, good stability and the synergistic catalytic effect of TPA and Sn(II)-BDC. Furthermore, the composite catalyst reusability has been studied for five cycles, and it exhibits an acceptable conversion. This research provides a green and large-scale synthesis route for the sustainable production of biofuels by constructing heteropolyacids/Sn-based MOFs synergistic catalysts.

To study the propagation of gas explosion shock wave and flame in coal mine heading face at real scale, the numerical simulation software of gas explosion was used to establish roadway models of different scales, and the influence of premixed gas concentration, premixed gas length and roadway spatial characteristics on the overpressure and flame propagation was studied. It is found that the maximum overpressure of gas explosion in heading face can reach 180-630 kPa under the original scale. The constraint degree of roadway section and premixed gas amount are important control factors of gas explosion pressure and flame range. The resistance of high-speed flame propagation will lead to slow flame diffusion and eventually make the flame expansion ratio tend to a certain value.

Abstract The objective of this study was to investigate the clinical significance and roles of tumor progression locus 2 (TPL2) and peptidyl-prolyl cis–trans isomerase 1 (Pin1) in the occurrence and development of breast invasive ductal carcinoma (IDC). Immunohistochemistry was used to detect the expression of TPL2 and Pin1 in human breast tissues, which included normal breast tissues (Normal), tissues with fibrocystic changes (FCC), ductal carcinoma in situ (DCIS), and IDC. The roles of TPL2 and Pin1 in the occurrence and development of IDC, as well as the correlation between their expression levels and clinicopathological parameters, were analyzed. Compared with Normal and FCC groups, the overexpression of TPL2 and Pin1 was significantly increased in DCIS and IDC groups (DCIS vs Normal: P = 0.002/P

A heterostructure film composed of graphene and h-BN has superlubricity and long-term anti-corrosion performance, enabling its potential applications as low-friction and corrosion-resistant coatings, especially in marine environments. However, the grain boundaries (GBs) and point defects formed during the preparation process may significantly affect the performance of the film. In this study, the tribological properties and wear mechanism of heterostructure films with different GB misorientation angles were studied with the molecular dynamics method. The results show that the high-energy atoms generated by strain-induced hillocks along the GBs can lead to stress concentration, thus deteriorating the wear resistance of the heterostructure film. Furthermore, point defects occurring on high-energy atoms can significantly alleviate the stress concentration, which is conducive to improving the wear resistance of the film. This study sheds light on improving the tribological characteristics of a graphene/h-BN heterostructure coating by properly controlling its microstructure.

In this study, Co/Cd-MOFs were synthesized via a solvothermal method. The resulting material was subjected to calcination at 900 °C for 2 h and characterized using FT-IR, XRD, and SEM techniques to assess its efficacy in moxifloxacin removal. The experimental findings revealed that the maximum adsorption capacity of Co/Cd-MOFs for moxifloxacin was observed at 350.4 mg/g within a 5 h timeframe. Furthermore, the analysis based on the pseudo-second-order kinetic model demonstrated that the adsorption process adhered to this specific model. Additionally, the adsorption isotherm analysis indicated that Freundlich multilayer adsorption provided the best description of the interaction between moxifloxacin and the Co/Cd-MOF material. These experimental and theoretical results collectively suggest that employing Co/Cd-MOFs as adsorbents holds promise for wastewater treatment applications.

The continuous annealing process (CAP) is a crucial process of steel production, which has a significant impact on the uniformity and stability of mechanical properties. A novel batch monitoring process based on kernel dissimilarity (KDISSIM) and Kmeans++ is proposed in this paper, focusing on problems such as unequal sample lengths between batches and nonlinearity between variables. First, KDISSIM is used to describe the dissimilarity between batches. Secondly, Kmeans++ is employed to improve the accuracy of clustering tasks based on historical batches. The largest cluster is considered to be at a relatively stable control level, and these batches are further used as training data. Then, the center batch and boundary batch of the training set are used as the reference batch and monitoring threshold for the monitoring model, respectively. Finally, the effectiveness of the proposed method is verified via the actual CAP data, providing a feasible solution for CAP batch monitoring.

The problem that the conventional double-exponential transient current model (DE model) can overdrive the circuit, which leads to the overestimation of the soft error rate of the logic cell, is solved. Our work uses a new and accurate model for predicting the soft error rate that brings the soft error rate closer to the actual. The piecewise double-exponential transient current model (PDE model) is chosen, and the accuracy of the model is reflected using the Layout Awareness Single Event Multi Transients Soft Error Rate Calculation tool (LA-SEMT-SER tool). The model can characterize transient current pulses piecewise and limit the peak current magnitude to not exceed the conduction current. TCAD models are constructed from 28 nm process library and cell layouts. The transfer characteristic curves of devices are calibrated, and functional timing verification is performed to ensure the accuracy of the TCAD model. The experimental results show that the PDE model is not only more consistent with TCAD simulation than the DE model in modeling the single event transient currents of the device, but also that the SER calculated by the LA-SEMT-SER tool based on the PDE model has a smaller error than the SER calculated by the LA-SEMT-SER tool based on the DE model.

Tantalum (Ta) has excellent prospects in the bone-implant field due to its satisfactory biocompatibility. Two novel Ta lattice structures were designed and printed by selective laser melting (SLM), including the imitation saddle surface (ISS) and the imitation arch bridge telescopic (IABT) structures. Quasi-static compression tests and finite element analysis were adopted to investigate the effects of design parameters on the mechanical properties, deformation modes, and energy absorption of lattice structures. Compared with the typical lattice structure body-centred cubic (BCC) structure, the ISS lattice structure had a higher yield-stress-to-elastic-modulus ratio, and the IABT lattice structure had higher energy absorption. The failure mode of the BCC and ISS lattice structures was shear band formation. The IABT lattice structure showed hierarchical deformation during compression and collapsed with vertical strut buckling. The results indicated that the ISS lattice is the most potential candidate for bone implant applications.

AbstractObjective The brain neuromechanism in maintenance hemodialysis patients (MHD) with cognitive impairment (CI) remains unclear. The study aimed to probe the relationship between spontaneous brain activity and CI by using resting-state functional magnetic resonance imaging (rs-fMRI) data.Methods Here, 55 MHD patients with CI and 28 healthy controls were recruited. For baseline data, qualitative data were compared between groups using the χ2 test; quantitative data were compared between groups using the independent samples t-test, ANOVA test, Mann–Whitney U-test, or Kruskal–Wallis test. Comparisons of ALFF/fALFF/ReHo values among the three groups were calculated by using the DPABI toolbox, and then analyzing the correlation with clinical variables. p

The coal spontaneous combustion disaster seriously threatens the mine safety production. Mastering the correlation between the micro group and characteristic temperature of coal spontaneous combustion plays a positive role in the prevention and control of coal spontaneous combustion disaster. In order to determine the change and correlation of characteristic temperature and coal microstructure in the process of spontaneous combustion of coal with different metamorphic degrees, the mass change characteristics and microstructure of four coal samples with different metamorphic degrees were tested by thermogravimetric experiment and Fourier infrared spectrum experiment, and the relationship between them was determined by Pearson correlation coefficient method. The results show that with the increase of metamorphic degree, the content of aromatic hydrocarbons and aliphatic hydrocarbons in coal increases and the content of oxygen-containing functional groups decreases. The groups with the highest content in the three types of groups are C=C, —CH3 and —OH respectively. The weight loss curve and characteristic temperature of high metamorphic coal gradually move to the high temperature zone, and the spacing between characteristic temperatures increases. The characteristic temperature of coal spontaneous combustion increases with the increase of aromatic hydrocarbon content and decreases with the increase of oxygen-containing functional group content. The higher the content of aromatic hydrocarbons, the more difficult coal spontaneous combustion is, while the oxygen-containing functional groups are just the opposite. The calculation results of Pearson correlation coefficient show that with the increase of temperature, the functional groups with the largest positive correlation coefficient are C—H, C—H, C—H, substituted benzene, C=C and C=C, and the functional groups with the largest negative correlation are COO—, COO—, C—O—, COO—, oh and —Oh, respectively. On the whole, C—H has the greatest positive correlation with the characteristic temperature, while COO— has the greatest negative correlation with the characteristic temperature. The change of characteristic temperature has an obvious linear relationship with the content of the maximum functional group. Based on the results of Pearson correlation coefficient, a multiple linear regression model of coal spontaneous combustion tendency is established by using the contents of C—H and coo functional groups which have the greatest correlation with characteristic temperature.

Abstract The power system dynamics have consistently challenged the rapid and persistent proliferation of photovoltaic (PV) systems in power systems. In this paper, the authors propose the generalized discrete‐time equivalent model (GDEM) of PV power generation system using a fourth‐order dynamic equivalent model for representing the physical characteristics of PV power stations in power system dynamic studies. In addition, the authors propose a grid‐connected system model which includes modelling interfaces (MIs) for the GDEM of power grid and the GDEM of PV power generation system in dynamic studies. The proposed equivalent models of the power grid and PV power generation system will improve the simulation accuracy and speed in dynamic power system studies. The authors have used the IEEE 14‐bus system and simulated various types of short‐circuit faults and PV penetration levels in their study to demonstrate the merits of the proposed GDEM of grid‐connected system in power systems. The pertinent simulation results are analyzed and conclusions are presented.

With the rapid development of semiconductor technology, the reduction in device operating voltage and threshold voltage has made integrated circuits more susceptible to the effects of particle radiation. Moreover, as process sizes decrease, the impact of charge sharing effects becomes increasingly severe, with soft errors caused by single event effects becoming one of the main causes of circuit failures. Therefore, the study of sensitivity evaluation methods for integrated circuits is of great significance for promoting the optimization of integrated circuit design, improving single event effect experimental methods, and enhancing the irradiation reliability of integrated circuits. In this paper, we first established a device model for the charge sharing effect and simulated it under reasonable conditions. Based on the simulation results, we then built a neural network model to predict the charge amounts in primary and secondary devices. We also propose a comprehensive automated method for calculating soft errors in unit circuits and validated it through TCAD simulations, achieving an error margin of 2.8–4.3%. This demonstrated the accuracy and effectiveness of the method we propose.

Objective(s): Patient-derived xenograft (PDX) model becomes a more and more important tool for tumor research. This study aimed to establish a colorectal cancer PDX model and verify its applicability.Materials and Methods: Fresh human colorectal cancer tissue was surgically removed and subcutaneously inoculated into immunodeficient mice to establish the PDX model. Hematoxylin and eosin (HE) staining and immunohistochemical staining were used to evaluate the model. The successful PDX model was selected to study the efficacy of capecitabine in treating colorectal cancer. Results: HE staining showed that the PDX mice model of colorectal cancer could preserve the histological characteristics of the primary tumor. Immunohistochemistry staining showed α-fetoprotein (AFP), carcinoembryonic antigen (CEA), and E-cadherin were strongly positively expressed in primary human and PDX tumor tissues, with a high degree of similarity. Capecitabine significantly inhibited PDX tumor growth and reduced the expression of AFP and CEA proteins in the tumor tissues (all Ps

Sound source separation is the separation of targeted sounds from a noisy environment, which plays an important role in signal processing and has been studied extensively. However, most of these researches only extract audio information for processing, ignoring visual information, resulting in the waste of feature information. In addition, some researchers have fused the extracted features but have not noticed the weights of different features, resulting in a poor model effect. This paper uses multi-modal information to separate sound sources to solve these problems. We constructed a multi-modal Audio-Visual separation model integrating the Dual-channel Attention mechanism named AVDA. The model realizes sound source separation through the dynamic fusion of visual and audio features. Specifically, firstly, we take audio video as input for data preprocessing and segment it to obtain video frames and audio. Then they are introduced into the visual and audio feature extractors, which integrate the attention mechanism to extract features. Finally, the extracted visual and audio features are introduced into the fusion prediction component to obtain the predicted spectrogram, which is compared with the ground truth spectrogram for subjective evaluation. In addition, three indexes of signal distortion ratio (SDR), signal interference ratio (SIR) and signal artifact ratio (SAR) are introduced for quantitative comparison. The experimental results on MUSIC-21 data set show that the model achieves 10.96, 17.91 and 12.77 respectively in three indexes, and its performance is significantly better than other models in audio-visual separation tasks.

Red mud of low cost is regarded as a promising alternative to heterogeneous catalysts for activating peroxymonosulfate (PMS) to degrade m-cresol. Improper valence states of metal oxides and coated active substances in red mud greatly hampered its wide application. To solve this problem, the modified red mud (WRMG/700) was prepared by the pyrolysis reduction of glucose in N2 atmosphere. X-ray diffraction (XRD), scanning electron microscopy (SEM) and X-ray photoelectron spectrum (XPS) analysis confirmed the production of Fe3O4, MnO and NiO in red mud and their gathering on the surface of particles. WRMG/700 exhibited the excellent performance toward PMS activation for the m-cresol degradation with 99.02% degradation efficiency and a pH-independent catalytic activity between initial pH 3–8. The removal efficiency of COD increased with the reaction time under the optimized degradation conditions. The free radical scavenging experiments and electron paramagnetic resonance (EPR) test confirmed 1O2 played a dominant role during m-cresol degradation in the WRMG/700/PMS system, implying m-cresol degradation was a non-radical oxidation process. Accordingly, the possible reaction mechanism was proposed. WRMG/700 retained its activation performance even after five recycles. This study showed a low cost and simple operation process for m-cresol elimination. HIGHLIGHTS The washed red mud and glucose were annealed at 700 °C in N2 atmosphere and exhibited the excellent performance for m-cresol degradation (WRMG/700).; Fe3O4, MnO and NiO forming in WRMG/700 played a crucial role during m-cresol degradation.; WRMG/700 exhibited a pH-independent catalytic activity between initial pH 3–8.; WRMG/700 retained its activation performance even after five recycles.;

The particle acceleration of blazar jets is crucial to high-energy astrophysics, yet the acceleration mechanism division in blazar subclasses and the underlying nature of these mechanisms remain elusive. In this work, we utilized the synchrotron spectral information (synchrotron peak frequency, $\mathrm{log}{\nu }_{\mathrm{sy}}$ , and corresponding curvature, b _sy ) of 2705 blazars from the literature and studied the subject of particle acceleration in blazar jets by analyzing the correlation between $\mathrm{log}{\nu }_{\mathrm{sy}}$ and 1/ b _sy . Our results suggested that the entire sample follows an energy-dependent probability acceleration (EDPA). Specifically, the low inverse Compton peak sources (LCPs) follow the mechanism of fluctuations of fractional gain acceleration (FFGA), while the high inverse Compton peak sources (HCPs) follow an acceleration mechanism of EDPA. Our results indicated that the separation between LCPs and HCPs results from the electron peak Lorentz factor ( γ _p ), and the differentiation should originate from different acceleration mechanisms. Moreover, our study revealed a transition in the acceleration mechanism from FFGA to EDPA around $\mathrm{log}{\nu }_{\mathrm{sy}}\sim 15$ through a detailed analysis of binned- $\mathrm{log}{\nu }_{\mathrm{sy}}$ . The mechanism of FFGA dominates the particle acceleration in LCP jets because of stronger jets and the EDPA dominates the particle energy gain in the HCPs due to a more efficient acceleration process.

The complex mechanical characteristics of the Xiyu conglomerate significantly influence the resistance and deformation features of its caverns’ surrounding rock, thereby constraining the construction of related water diversion tunnels. This paper introduces an improved SegFormer framework developed for the detection of mesoscale geomaterial structures. Computerized tomography (CT) scan images of the Xiyu conglomerate were employed to establish a high-precision numerical model. From the results of segmentation, the proposed algorithm outperformed UNet, HRNet, and the original SegFormer neural network. The segmentation results were used to calculate the porosity, and biaxial compression numerical simulation experiments based on the real structure were carried out using the particle flow code (PFC). We observed the failure process of the model and obtained the shear strength of the Xiyu conglomerate. We explored the causes and influencing factors of the anisotropy of the Xiyu conglomerate from the microstructure perspective and provide a micro-observation basis for establishing an anisotropic mechanical model.

In this paper, a single-event transient model based on the effective space charge for MOSFETs is proposed. The physical process of deposited and moving charges is analyzed in detail. The influence of deposited charges on the electric field in the depletion region is investigated. The electric field decreases in a short time period due to the neutralization of the space charge. After that, the electric field increases first and then decreases when the deposited charge is moved out. The movement of the deposited charge in the body mainly occurs through ambipolar diffusion because of its high-density electrons and holes. The derivation of the variation in electric field in the depletion region is modeled in the physical process according to the analysis. In combination with the ambipolar diffusion model of excessive charge in the body, a physics-based model is built to describe the current pulse in the drain terminal. The proposed model takes into account the influence of multiple factors, like linear-energy transfer (LET), drain bias, and the doping concentration of the well. The model results are validated with the simulation results from TCAD. Through calculation, the root-mean-square error (RMSE) between the simulation and model is less than 3.7 × 10−4, which means that the model matches well with the TCAD results. Moreover, a CMOS inverter is simulated using TCAD and SPICE to validate the applicability of the proposed model in a circuit-level simulation. The proposed model captures the variation in net voltage in the inverter. The simulation result obviously shows the current plateau effect, while the relative error of the pulse width is 23.5%, much better than that in the classic model. In comparison with the classic model, the proposed model provides an RMSE of 7.59 × 10−5 for the output current curve and an RMSE of 0.158 for the output voltage curve, which are significantly better than those of the classic model. In the meantime, the proposed model does not produce extra simulation time compared with the classic double exponential model. So, the model has potential for application to flow estimation of the soft error rate (SER) at the circuit level to improve the accuracy of the results.

The contact between the tool and the workpiece/chip in metal cutting is complex, resulting in high local temperatures and stresses, which may cause severe tool wear and failure. Developments in cryogenic-assisted machining have shown an ecological alternative to the classical metal working fluids, besides tool wear reduction during machining difficult-to-cut materials due to the good ability to dissipate the heat generated by this process. The objective of this work is to analyze the tribological conditions and performance of new coatings specially developed for cryogenic-assisted machining in terms of friction coefficient, volume of build-up material (adhesion) to the tool, and tool temperature. The results have shown that the sliding speed and cooling/lubrication strategy are two main factors that affect the friction coefficient and adhesion of Ti–6Al–4V alloy to the pins. These tribological tests should allow us to select the best coating(s) to be used in cutting tools for further tool wear analysis. Moreover, the obtained friction coefficients could be further implemented into metal cutting models to predict the machining outcomes, including the surface integrity of the machined parts and tool wear.

Vocal learning is a complex acquired social behavior that has been found only in very few animals. The process of animal vocal learning requires the participation of sensorimotor function. By accepting external auditory input and cooperating with repeated vocal imitation practice, a stable pattern of vocal information output is eventually formed. In parallel evolutionary branches, humans and songbirds share striking similarities in vocal learning behavior. For example, their vocal learning processes involve auditory feedback, complex syntactic structures, and sensitive periods. At the same time, they have evolved the hierarchical structure of special forebrain regions related to vocal motor control and vocal learning, which are organized and closely associated to the auditory cortex. By comparing the location, function, genome, and transcriptome of vocal learning-related brain regions, it was confirmed that songbird singing and human language-related neural control pathways have certain analogy. These common characteristics make songbirds an ideal animal model for studying the neural mechanisms of vocal learning behavior. The neural process of human language learning may be explained through similar neural mechanisms, and it can provide important insights for the treatment of language disorders.

Zebra finches are essential animal models for studying learned vocal signals. The robust nucleus of the arcopallium (RA) plays an important role in regulating singing behavior. Our previous study showed that castration inhibited the electrophysiological activity of RA projection neurons (PNs) in male zebra finches, demonstrating that testosterone modulates the excitability of RA PNs. Testosterone can be converted into estradiol (E2) in the brain through aromatase; however, the physiological functions of E2 in RA are still unknown. This study aimed to investigate the electrophysiological activities of E2 on the RA PNs of male zebra finches through patch-clamp recording. E2 rapidly decreased the rate of evoked and spontaneous action potentials (APs) of RA PNs, hyperpolarized the resting membrane potential, and decreased the membrane input resistance. Moreover, the G-protein–coupled membrane-bound estrogen receptor (GPER) agonist G1 decreased both the evoked and spontaneous APs of RA PNs. Furthermore, the GPER antagonist G15 had no effect on the evoked and spontaneous APs of RA PNs; E2 and G15 together also had no effect on the evoked and spontaneous APs of RA PNs. These findings suggested that E2 rapidly decreased the excitability of RA PNs and its binding to GPER suppressed the excitability of RA PNs. These pieces of evidence helped us fully understand the principle of E2 signal mediation via its receptors to modulate the excitability of RA PNs in songbirds.

Primary intestinal malignancies account for only 1%–3% of all malignant gastrointestinal tumors. Adenocarcinomas are uncommonly located in the ileum. Ileal adenocarcinoma (IA) is rare and difficult to diagnose because of its location. IA is common in older men and rare in young pregnant women. A 23-year-old pregnant woman was hospitalized several times for repeated vomiting and abdominal pain. Her symptoms were relieved after symptomatic treatment. She exhibited no typical manifestations of intestinal obstruction, such as abdominal distension, difficulty passing gas and defecation. Unfortunately, she was misdiagnosed with acute gastroenteritis. On the second day after delivery, the patient stopped passing gas and computed tomography (CT) revealed an intestinal obstruction. She was treated as paralytic ileus. However, in view of failed conservative management, she was decided for an exploratory laparotomy. A malignant ileal tumor 5cm from the ileocecal valve was found incidentally and was surgically excised accompanied with End-to-side anastomosis of ileal and transverse colon. The operation lasted 195 minutes. Pathological examination revealed an IA. Pregnant woman who experience symptoms of intestinal obstruction should be alert to the possibility of malignancy in the small intestine. IA is an insidious tumor in pregnant women. An “IA triad” can be defined as refractory vomiting, vague abdominal pain, and weight loss (or inadequate weight gain in pregnant women). Pregnant women with an IA triad should undergo investigation with endoscopy or, if necessary, magnetic resonance imaging (MRI).

In this study, we summarize recent advances in the synthesis of magnetic catalysts utilized for biodiesel production, particularly focusing on the physicochemical properties, activity, and reusability of magnetic mixed metal oxides, supported magnetic catalysts, ionic acid-functionalized magnetic catalysts, heteropolyacid-based magnetic catalysts, and metal–organic framework-based magnetic catalysts. The prevailing reaction conditions in the production of biodiesel are also discussed. Lastly, the current limitations and challenges for future research needs in the magnetic catalyst field are presented.

The widespread rumors on social media seriously disturb the social order, and we urgently need practical methods to detect rumors. Most existing deep learning methods focus on mining news text content, user information, and propagation features but ignore the rumor diffusion structural features. Rumors spread in a vertical chain and diffusion in a horizontal network. Both are essential features of rumors. In addition, existing models need more effective methods to extract higher-order features of multiple resource information. To address these problems, we propose a multi-source information heterogeneous graph model in this paper, called jointly Multi-Source information and Local-Global relationship of heterogeneous network model named MSLG. It extracts multi-source information such as rumors content, user information, propagation, and diffusion structure. Firstly, we extract the higher order semantic representation of rumors content by graph convolution network and integrate local relational attention to strengthen the critical semantic. At the same time, we construct the rumors and users as heterogeneous graphs to capture the propagation and diffusion structure of the rumors. We are finally fusing global relational attention to measure submodules’ importance. Experiments on two real-world datasets show that the proposed method achieves state-of-the-art results in fake news detection.

Under the background of promoting the construction of ecological civilization and the goal of carbon peak and carbon neutralization, it is of great significance to explore the measurement method and improvement strategy of the carbon effect of agricultural land consolidation. Based on a quantitative analysis and the whole life cycle of land consolidation, this study constructed a carbon effect accounting and analysis framework of agricultural land consolidation project from three stages of project initiation and design, project implementation, and operation management. Taking the agricultural land consolidation project in the Shiyan town on the urban edge of the Three Gorges Reservoir Area as a case, this study made empirical analysis and calculation and analyzed the carbon effect and influencing factors in different consolidation stages. The results showed that the overall carbon effect in the project area was a carbon source. The net carbon emission generated by the project construction was 8358t, which was mainly from workers input and concrete carbon emission; the carbon storage brought about by the adjustment of land use structure was 2,378.20t, which mainly came from the carbon storage increment of newly cultivated land; the carbon storage generated by the agricultural ecosystem was 1,100.04t, which was mainly based on the increase of cultivated land and the improvement of cultivated land quality; the carbon emission from agricultural production activities was 18.18t. Research conclusions: ① the carbon source effect of engineering construction is obvious. Artificial input and concrete are the main carbon sources in the hilly area at the edge of the metropolis; ② the adjustment of land use structure is manifested as a carbon sink effect, which mainly comes from the contribution of carbon storage of newly increased cultivated land; ③ the carbon effect of project operation and management may be a carbon source in the short term, and the long-term effect should be exerted; and ④ based on the concept of whole life cycle, promoting ecological land consolidation, optimizing project design, reasonably arranging consolidation projects, and strengthening operation management are effective measures to improve the carbon effect of land consolidation projects, which are conducive to the realization of the “double carbon” goal.

The static random-access memory (SRAM) cells used in the high radiation environment of aerospace have become highly vulnerable to single-event effects (SEE). Therefore, a 12T SRAM-hardened circuit (RHB-12T cell) for the soft error recovery is proposed using the radiation hardening design (RHBD) concept. To verify the performance of the RHB-12T, the proposed cell is simulated by the 28 nm CMOS process and compared with other hardened cells (Quatro-10T, WE-Quatro-12T, RHM-12T, RHD-12T, and RSP-14T). The simulation results show that the RHB-12T cell can recover not only from single-event upset caused by their sensitive nodes but also from single-event multi-node upset caused by their storage node pairs. The proposed cell exhibits 1.14×/1.23×/1.06× shorter read delay than Quatro-10T/WE-Quatro-12T/RSP-14T and 1.31×/1.11×/1.18×/1.37× shorter write delay than WE-Quatro-12T/RHM-12T/RHD-12T/RSP-14T. It also shows 1.35×/1.11×/1.04× higher read stability than Quatro-10T/RHM-12T/RHD-12T and 1.12×/1.04×/1.09× higher write ability than RHM-12T/RHD-12T/RSP-14T. All these improvements are achieved at the cost of a slightly larger area and power consumption.

Adenoid cystic carcinoma (ACC) of the breast (breast ACC) is a rare tumor, especially in men, with only 17 cases reported in the literature. Owing to this rarity, male breast ACC is susceptible to missed or incorrect diagnoses, and data on treatment options and prognosis is also scarce. Herein, we report a case of a male patient with primary breast ACC and performed a detailed clinicopathological analysis of the 17 cases reported in the literature. A 38-year-old Chinese man patient developed right-sided breast nipple retraction in 2013 and presented to our hospital in 2015 with a palpable mass in the right breast for four days. B-scan ultrasound indicated the presence of a solid space-occupying lesion in the right breast. Breast Imaging Reporting and Data System (BI-RADS) classified the lesion as category 4B, and mammography showed a right breast nodule classified as BI-RADS 4C. Modified radical mastectomy for breast cancer was performed on the right breast. Microscopic examination of the excised tissue revealed diffuse tumor invasion of the subcutaneous fibers and adipose tissue, with tumor cells arranged in cribriform, tubular, and microcystic patterns. Immunohistochemical staining indicated that the glandular epithelial cells were positive for CD117, CK7, and Ki67 (approximately 30%) and negative for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, while the myoepithelial/basal cells were positive for P63, CK5/6 and S-100. Moreover, basement membrane materials were positive for collagen type IV. Molecular pathology analysis by fluorescence in situ hybridization revealed that the tumor was negative for MYB rearrangements. The patient was followed up for 82 months with no tumor recurrence or metastasis. According to the current literature, mastectomies have a better prognosis than lumpectomy. Accurately identifying the diagnosis of male breast ACC and considering the surgery of mastectomy may be the key factors for patients to obtain a good prognosis based on the microscopic characteristics of the tumor.

The utilization of crop straw biomass resources is highly emphasized by governments and academia in recent decades. Based on the core databases of the literature in China National Knowledge Infrastructure (CNKI) academic journals, CiteSpace software is used to analyze and process the hotspots, and this study proposed the primary coverage and evolutionary trends of research on the utilization of crop straw resources. The thesis proposes the research development trend for improving the institutional mechanism of the utilization of crop straw resources, strengthening technology research and development, exploring the economic model of green cycle agriculture, accelerating the construction of the industrial system, and designing new paths of resource utilization in multiple ways, which helps estimate the development trend of the utilization of crop straw resources and provide inspiration and direction for future research and practices.

A series of bimetallic Zn-Zr metal-organic frameworks (Zn-Zr MOFs) with different Zn:Zr molar ratios has been synthesized via a green hydrothermal method. The structures and morphologies of these photocatalysts have been characterized and analyzed by FTIR, XRD, SEM, and nitrogen adsorption-desorption. The prepared Zn-Zr MOFs had large specific surface areas and pore volumes, favoring the adsorption of pollutant molecules, which in turn led to an improved photocatalytic effect. The photocatalytic activities of the Zn-Zr MOFs under visible light irradiation have been studied towards rhodamine B (RhB) as a target pollutant. The extent of degradation of RhB in a 40 mg/L aqueous solution reached 97.4%. The optimal photocatalyst could also degrade other dyes, suggesting a certain degree of universality.