Antagonism effect of residual S triggers the dual-path mechanism for water oxidation

Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of the residual chalcogen in the reconstructed layer is lacking in detail,and the corresponding catalytic mechanism remains controversial.Here,taking Cu_(1-x)Co_(x)S as a platform,we explore the regulating effect and existence form of the residual S doped into the reconstructive layer for oxygen evolution reaction(OER),where a dual-path OER mechanism is proposed.First-principles calculations and operando~(18)O isotopic labeling experiments jointly reveal that the residual S in the reconstructive layer of Cu_(1-x)Co_(x)S can wisely balance the adsorbate evolution mechanism(AEM)and lattice oxygen oxidation mechanism(LOM)by activating lattice oxygen and optimizing the adsorption/desorption behaviors at metal active sites,rather than change the reaction mechanism from AEM to LOM.Following such a dual-path OER mechanism,Cu_(0.4)Co_(0.6)S-derived Cu_(0.4)Co_(0.6)OSH not only overcomes the restriction of linear scaling relationship in AEM,but also avoids the structural collapse caused by lattice oxygen migration in LOM,so as to greatly reduce the OER potential and improved stability.

Additive manufacturing of Ni-based superalloys: Residual stress, mechanisms of crack formation and strategies for crack inhibition

The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in high-end industrial systems.However,the intense temperature gradient induced by the rapid heating and cooling processes of AM can generate high levels of residual stress and metastable chemical and structural states,inevitably leading to severe metallurgical defects in Ni-based superalloys.Cracks are the greatest threat to these materials’integrity as they can rapidly propagate and thereby cause sudden and non-predictable failure.Consequently,there is a need for a deeper understanding of residual stress and cracking mechanisms in additively manufactured Ni-based superalloys and ways to potentially prevent cracking,as this knowledge will enable the wider application of these unique materials.To this end,this paper comprehensively reviews the residual stress and the various mechanisms of crack formation in Ni-based superalloys during AM.In addition,several common methods for inhibiting crack formation are presented to assist the research community to develop methods for the fabrication of crack-free additively manufactured components.

Study on the disaster caused by the linkage failure of the residual coal pillar and rock stratum during multiple coal seam mining:mechanism of progressive and dynamic failure

Multi-seam mining often leads to the retention of a significant number of coal pillars for purposes such as protection,safety,or water isolation.However,stress concentration beneath these residual coal pillars can significantly impact their strength and stability when mining below them,potentially leading to hydraulic support failure,surface subsidence,and rock bursting.To address this issue,the linkage between the failure and instability of residual coal pillars and rock strata during multi-seam mining is examined in this study.Key controls include residual pillar spalling,safety factor(f.),local mine stiffness(LMS),and the post-peak stiffness(k)of the residual coal pillar.Limits separating the two forms of failure,progressive versus dynamic,are defined.Progressive failure results at lower stresses when the coal pillar transitions from indefinitely stable(f,>1.5)to failing(f,<1.5)when the coal pillar can no longer remain stable for an extended duration,whereas sud-den(unstable)failure results when the strength of the pillar is further degraded and fails.The transition in mode of failure is defined by the LMS/k ratio.Failure transitions from quiescent to dynamic as LMS/k.<1,which can cause chain pillar instability propagating throughout the mine.This study provides theoretical guidance to define this limit to instability of residual coal pillars for multi-seam mining in similar mines.

Clothing Parsing Based on Multi-Scale Fusion and Improved Self-Attention Mechanism

Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.This paper presents a convolutional structure with multi-scale fusion to optimize the step of clothing feature extraction and a self-attention module to capture long-range association information.The structure enables the self-attention mechanism to directly participate in the process of information exchange through the down-scaling projection operation of the multi-scale framework.In addition,the improved self-attention module introduces the extraction of 2-dimensional relative position information to make up for its lack of ability to extract spatial position features from clothing images.The experimental results based on the colorful fashion parsing dataset(CFPD)show that the proposed network structure achieves 53.68%mean intersection over union(mIoU)and has better performance on the clothing parsing task.

Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

Intelligent Fault Diagnosis Method of Rolling Bearings Based on Transfer Residual Swin Transformer with Shifted Windows

Due to their robust learning and expression ability for complex features,the deep learning(DL)model plays a vital role in bearing fault diagnosis.However,since there are fewer labeled samples in fault diagnosis,the depth of DL models in fault diagnosis is generally shallower than that of DL models in other fields,which limits the diagnostic performance.To solve this problem,a novel transfer residual Swin Transformer(RST)is proposed for rolling bearings in this paper.RST has 24 residual self-attention layers,which use the hierarchical design and the shifted window-based residual self-attention.Combined with transfer learning techniques,the transfer RST model uses pre-trained parameters from ImageNet.A new end-to-end method for fault diagnosis based on deep transfer RST is proposed.Firstly,wavelet transform transforms the vibration signal into a wavelet time-frequency diagram.The signal’s time-frequency domain representation can be represented simultaneously.Secondly,the wavelet time-frequency diagram is the input of the RST model to obtain the fault type.Finally,our method is verified on public and self-built datasets.Experimental results show the superior performance of our method by comparing it with a shallow neural network.

Effects of ultrasound monitoring of gastric residual volume on feeding complications,caloric intake and prognosis of patients with severe mechanical ventilation

BACKGROUND Monitoring of gastric residual is an important approach for assessing gastric emptying in patients with mechanical ventilation.By monitoring gastric contents,the enteral nutrition scheme can be adjusted in time to ensure feeding safety.AIM To investigate the effects of ultrasound monitoring on the incidence of feeding complications,daily caloric intake and prognosis of patients with severe mechanical ventilation.To analyze the clinical significance of ultrasound monitoring of gastric residual volume(GRV)up to 250 mL to provide a theoretical basis for clinical practice.METHODS Patients admitted to the department of emergency medicine of the Affiliated Hospital of Nantong University from January 2018 to June 2022 who received invasive mechanical ventilation and continuous enteral nutrition support within 24-48 h after admission were enrolled in this study.Medical records for patients within 7 d of hospitalization were retrospectively analyzed to compare the incidence of feeding complications,daily caloric intake and clinical prognosis between patients with gastric residual≥250 mL and<250 mL,as monitored by ultrasound on the third day.RESULTS A total of 513 patients were enrolled in this study.Incidences of abdominal distension,diarrhea,and vomiting in the<250 mL and≥250 mL groups were:18.4%vs 21.0%,23.9%vs 32.3%and 4.0%vs 6.5%,respectively;mortality rates were 20.8%vs 22.65%;mechanical ventilation durations were 18.30 d vs 17.56 d while lengths of stay in the intensive care units(ICU)were 19.87 d vs 19.19±5.19 d.Differences in the above factors between groups were not significant.Gastric residual≥250 mL was not an independent risk factor for death and prolonged ICU stay.However,target feeding time of patients in the≥250 mL group was longer than that of patients in the≥250 mL group,and caloric intake(22.0,23.6,24.8,25.3 kcal/kg/d)for patients in the≥250 mL group from the 4^(th) day to the 7^(th) day of hospitalization was lower than that of patients in the≥250 mL group(23.2,24.8,25.7,25.8 kcal/kg/d).On the 4^(th) day(Z=4.324,P=0.013),on the 5^(th) day(Z=3.376,P=0.033),while on the 6^(th) day(Z=3.098,P=0.04),the differences were statistically significant.CONCLUSION The use of ultrasound to monitor GRV and undertaking clinical interventions when the monitoring value is≥250 mL has no significant effects on incidences of feeding complications and clinical prognostic outcomes,however,it significantly prolongs the time to reach target feeding,reduces the daily intake of calories during ICU hospitalization,and increases the risk of insufficient nutrition of patients.The accuracy and necessity of monitoring gastric remnants and monitoring frequencies should be investigated further.

Micro-mechanisms of residual oil mobilization by viscoelastic fluids

Four typical types of residual oil, residual oil trapped in dead ends, oil ganglia in pore throats, oil at pore corners and oil film adhered to pore walls, were studied. According to main pore structure characteristics and the fundamental morphological features of residual oil, four displacement models for residual oil were proposed, in which pore-scale flow behavior of viscoelastic fluid was analyzed by a numerical method and micro-mechanisms for mobilization of residual oil were discussed. Calculated results indicate that the viscoelastic effect enhances micro displacement efficiency and increases swept volume. For residual oil trapped in dead ends, the flow field of viscoelastic fluid is developed in dead ends more deeply, resulting in more contact with oil by the displacing fluid, and consequently increasing swept volume. In addition, intense viscoelastic vortex has great stress, under which residual oil becomes small oil ganglia, and finally be carried into main channels. For residual oil at pore throats, its displacement mechanisms are similar to the oil trapped in dead ends. Vortices are developed in the depths of the throats and oil ganglia become smaller. Besides, viscoelastic fluid causes higher pressure drop on oil ganglia, as a driving force, which can overcome capillary force, consequently, flow direction can be changed and the displacing fluid enter smaller throats. For oil at pore corners, viscoelastic fluid can enhance displacement efficiency as a result of greater velocity and stress near the corners. For residual oil adhered to pore wall, viscoelastic fluid can provide a greater displacing force on the interface between viscoelastic fluid and oil, thus, making it easier to exceed the minimum interfacial tension for mobilizing the oil film.

Flow-slide characteristics and failure mechanism of shallow landslides in granite residual soil under heavy rainfall

Affected by typhoons over years, Fujian Province in Southeast China has developed a large number of shallow landslides, causing a long-term concern for the local government. The study on shallow landslide is not only helpful to the local government in disaster prevention, but also the theoretical basis of regional early warning technology. To determine the whole-process characteristics and failure mechanisms of flow-slide failure of granite residual soil slopes, we conducted a detailed hazard investigation in Minqing County, Fujian Province, which was impacted by Typhoon Lupit-induced heavy rainfall in August 2021. Based on the investigation and preliminary analysis results, we conducted indoor artificial rainfall physical model tests and obtained the whole-process characteristics of flow-slide failure of granite residual soil landslides. Under the action of heavy rainfall, a granite residual soil slope experiences initial deformation at the slope toe and exhibits development characteristics of continuous traction deformation toward the middle and upper parts of the slope. The critical volumetric water content during slope failure is approximately 53%. Granite residual soil is in a state of high volumetric water content under heavy rainfall conditions, and the shear strength decreases, resulting in a decrease in stability and finally failure occurrence. The new free face generated after failure constitutes an adverse condition for continued traction deformation and failure. As the soil permeability(cm/h) is less than the rainfall intensity(mm/h), and it is difficult for rainwater to continuously infiltrate in short-term rainfall, the influence depth of heavy rainfall is limited. The load of loose deposits at the slope foot also limits the development of deep deformation and failure. With the continuous effect of heavy rainfall, the surface runoff increases gradually, and the influence mode changes from instability failure caused by rainfall infiltration to erosion and scouring of surface runoff on slope surface. Transportation of loose materials by surface runoff is an important reason for prominent siltation in disaster-prone areas.

Mechanism and control of ground residual deformation over longwall goaf

The deformation of rupture rock mass in goaf is the main reason for ground terrene residual deformation. Based on field measurement and similar material simulation, the rupture strata structure and its residual deformation characteristics in the longwall goaf and its overburden are pointed out. On the basis of these achievements, the authors propose the mechanism of strengthening rupture rock mass ground and the control measures of deformation resistant structure. Using the case of main coal building in Xinzhuangzi Coal Processing Plant, this paper introduces the influence of strengthening rupture rock mass and deformation resistant structure.

Keyphrase Generation Based on Self-Attention Mechanism

Keyphrase greatly provides summarized and valuable information.This information can help us not only understand text semantics,but also organize and retrieve text content effectively.The task of automatically generating it has received considerable attention in recent decades.From the previous studies,we can see many workable solutions for obtaining keyphrases.One method is to divide the content to be summarized into multiple blocks of text,then we rank and select the most important content.The disadvantage of this method is that it cannot identify keyphrase that does not include in the text,let alone get the real semantic meaning hidden in the text.Another approach uses recurrent neural networks to generate keyphrases from the semantic aspects of the text,but the inherently sequential nature precludes parallelization within training examples,and distances have limitations on context dependencies.Previous works have demonstrated the benefits of the self-attention mechanism,which can learn global text dependency features and can be parallelized.Inspired by the above observation,we propose a keyphrase generation model,which is based entirely on the self-attention mechanism.It is an encoder-decoder model that can make up the above disadvantage effectively.In addition,we also consider the semantic similarity between keyphrases,and add semantic similarity processing module into the model.This proposed model,which is demonstrated by empirical analysis on five datasets,can achieve competitive performance compared to baseline methods.

An Initial Residual Stress Inference Method by Incorporating Monitoring Data and Mechanism Model

Initial residual stress is the main reason causing machining deformation of the workpiece,which has been deemed as one of the most important aspects of machining quality issues.The inference of the distribution of initial residual stress inside the blank has significant meaning for machining deformation control.Due to the principle error of existing residual stress detection methods,there are still challenges in practical applications.Aiming at the detection problem of the initial residual stress field,an initial residual stress inference method by incorporating monitoring data and mechanism model is proposed in this paper.Monitoring data during machining process is used to represent the macroscopic characterization of the unbalanced residual stress,and the finite element numerical model is used as the mechanism model so as to solve the problem that the analytic mechanism model is difficult to establish;the policy gradient approach is introduced to solve the gradient descent problem of the combination of learning model and mechanism model.Finally,the initial residual stress field is obtained through iterative calculation based on the fusing method of monitoring data and mechanism model.Verification results show that the proposed inference method of initial residual stress field can accurately and effectively reflect the machining deformation in the actual machining process.

Study on Residual Oil HDS Process with Mechanism Model and ANN Model

Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur content of hydrogenated residual oil. The established ANN model covered 4 input variables, 1 output variable and 1 hidden layer with 15 neurons. The comparison between the results of two models was listed. The results showed that the predicted mean relative errors of the two models with three different sample data were less than 5% and both the two models had good predictive precision and extrapolative feature for the HDS process. The mean relative error of 5 sets of testing data of the ANN model was 1.62%—3.23%, all of which were smaller than that of the common mechanism model (3.47%— 4.13%). It showed that the ANN model was better than the mechanism model both in terms of fitting results and fitting difficulty. The models could be easily applied in practice and could also provide a reference for the further research of residual oil HDS process.

Bioavailability of bound residue derived from ^(14)C-labeled chlorsulfuron in soil and its mechanism of phytotoxicity

The bioavailability of bound residue(BR) derived from 14 C-labeled chlorsulfuron in soil and effect of the main components of the BR on growth of rape(brassica napus) and rice(Oryza sativa L.) were investigated. The results showed that the BR with the concentration of 0 28 and 0 56 nmol/g air-dried soil, which was calculated by special radioactivity of 14 C-labeled chlorsulfuron parent compound, resulted in significant depression effect on growth of rape seedling. It was assured that the main components(2-amino-4-methoxyl-6-methyl-1,3,5-triazine, 2-amino-4-hydroxyl-6-methyl-1,3,5-triazine, and 2-chloro-benzenesul-f onamide) of the BR did not inhibit the growth of rape and rice. LC-MS analysis demonstrated that the parent compound previously bound to the soil matrix could be again released and transformed into methanol-extractable residue during the course of rape growth. It was concluded that the molecular leading to the phytotoxicity to rape and rice in the BR is still the parent compound.

Mechanisms and characteristics of mesocarbon microbeads prepared by co-carbonization of coal tar pitch and direct coal liquefaction residue

DCLR-P was prepared by direct coal liquefaction residue (DCLR) with ash removal.In the present experiments,mesocarbon microbeads (MCMBs) were prepared by co-carbonization of coal tar pitch (CTP) and DCLR-P.With the increase of DCLR-P content,the yield of MCMBs increased from 47.8% to 56.8%.At the same time,the particle sizes distribution of MCMBs was narrowed,resulting in the decrease of D9o/D10 ratio from 154.88 to 6.53.The results showed that DCLR-P had a positive effect on the preparation of MCMBs.1H-NMR,FTIR,SEM and XRD were used to analyze the mechanisms and characteristics of MCMBs prepared by co-carbonization of CTP and DCLR-P.The results showed that the Proton Donor Quality Index (PDQI) of DCLR-P was 13.32,significantly higher than that of CTP (0.83).This indicated that DCLR-P had more naphthenic structure than CTP,which leads to hydrogen transferring in polycondensation reaction.The aliphatic structure of DCLR-P can improve the solubility and fusibility of mesophase,thereby making the structure of MCMBs more structured.The microstructure of the graphitized MCMBs had a substantially parallel carbon layer useful for its electrical performance.The performance of graphitized MCMBs as a negative electrode material for Li-ion batteries was tested.The particle sizes,tap density,specific surface area and initial charge-discharge efficiency of graphitized MCMBs met the requirements of CMB-I in GB/T-24533-2009.However,the initial discharge capacity of graphitized MCMB was only 296.3 mA h g-1 due to the low degree of graphitization of MCMBs.

Residual Mechanical Properties and Explosive Spalling Behavior of Ultra-High-Strength Concrete Exposed to High Temperature

In order to explore the characteristics of ultra-high-strength concrete exposed to high temperature,residual mechanical properties and explosive spalling behavior of ultra-high-strength concrete( UHSC) and high strength concrete( HSC) exposed to high temperatures ranging from 20 ℃ to 800 ℃ were determined. The microstructure of the specimens after exposure to elevated temperature was analyzed by means of scanning electron microscope( SEM) and mercury intrusion porosimetry( MIP). The residual compressive strengths of UHSC and HSC were first increased and then decreased as temperature increased. After exposure to 800 ℃,the compressive strengths of UHSC and HSC were 24. 2 % and 22. 3 % of their original strengths at 20 ℃,respectively. The residual splitting tensile strengths of both UHSC and HSC were consistently decreased with the temperature increasing and were approximately 20% of their original strengths after 800 ℃. However,the residual fracture energies of both concretes tended to ascend even at 600 ℃. The explosive spalling of UHSC was more serious than that of HSC. Moisture content of the specimens governs the explosive spalling of both concretes with a positive correlations,and it is more pronounced in UHSC. These results suggest that UHSC suffers a substantial loss in load-bearing capacity and is highly prone to explosive spalling due to high temperature. The changes in compressive strength are due to the changes in the density and the pore structure of concrete. The probability and severity of explosive spalling of UHSC are much higher than those of HSC due to the higher pore volume in HSC.

Microstructure and Mechanical Properties of AZ31 Alloys Processed by Residual Heat Rolling

To produce high strength and ductility Mg alloys with high productivity and low energy consumption,the residual heat rolling (RHR) process was initially proposed.The microstucture and mechanical properties of AZ31 processed by RHR were investigated by optical micrscopy (OM),electron backscatter diffraction (EBSD),and electron universal testing machine.The yield strength (YS),ultimate tensile strength (UTS),and elongation to failure of RHRed AZ31 sheet were 194 MPa,311 MPa,and 22%,respectively.The RHRed AZ31 alloys after annealing have very fine and homogeneous grains.The symmetrical rolled (SR) and RHRed AZ31 exhibit typical {0002} basal textures.The RHRed AZ31 has double-peak basal texture distribution.The basal poles of RHRed AZ31 split from normal direction (ND) to rolling direction (RD).There are few hard orientation distributions on the basal slip and more soft orientation distributions on the prismatic slip in the RHRed AZ31 sheets than those in the SRed AZ31sheets.

融合Residual Network-50残差块与卷积注意力模块的地震断层自动识别

传统的断层识别是由地质解释人员以人工标记的方式进行检测,不仅耗时长、效率低,且识别结果存在一定的人为误差。为解决以上问题,提高断层识别的精度,提出了一种基于深度学习的断层识别方法,利用注意力机制聚焦目标特征的能力,在U-Net网络的解码层引入了卷积注意力模块(Convolutional Block Attention Module,CBAM),在编码层引入了ResNet-50残差块,建立基于卷积神经网络(Convolutional Neural Networks,CNN)的断层识别方法(Res-CBAM-UNet)。将合成地震数据与相应的断层标签进行数据增强操作,新生成的训练数据集作为输入对网络模型进行训练,以提高模型的泛化能力。随后将该模型与CBAM-UNet、ResNet34-UNet和ResNet50-UNet网络进行对比分析,利用实际工区地震数据进行测试。结果表明,设计的Res-CBAM-UNet网络对断层具有较好的识别效果,且识别出的断层连续性好,计算效率高。

Residual Stress Distribution of Si_(3)N_(4)/SiC Gradient Material and the Effect of Residual Stress on Material Properties

The Si_(3)N_(4)/SiC gradient material with a gradient composition structure was prepared by a hot pressing sintering.The sinterability,distribution of residual stress and the effect of residual stress on mechanical properties of Si_(3)N_(4)/SiC gradient materials were studied.The research results show that,at 1750℃,Si_(3)N_(4)/SiC gradient materials with different ratios can achieve co-sintering,and the overall relative density of the sample reaches 98.5%.Interestingly,the flexural strength of Si_(3)N_(4)/SiC gradient material is related to its loading surface.The flexural strength of SiC as the loading surface is about 35%higher than that of Si_(3)N_(4)as the loading surface.The analysis of the residual stress of the material in the gradient structure shows that the gradient stress distribution between the two phases is a vital factor affecting the mechanical properties of the material.With the increase of SiC content in the gradient direction,the fracture toughness of each layer of Si_(3)N_(4)/SiC gradient materials gradually decreases.The surface hardness of the pure SiC side is lower than that reported in other literature.