SSCFormer: Revisiting ConvNet-Transformer Hybrid Framework from Scale-Wise and Spatial-Channel-Aware Perspectives for Volumetric Medical Image Segmentation.

Accurate and robust medical image segmentation is crucial for assisting disease diagnosis, making treatment plan, and monitoring disease progression. Adaptive to different scale variations and regions of interest is essential for high accuracy in automatic segmentation methods. Existing methods based on the U-shaped architecture respectively tackling intra- and inter-scale problem with a hierarchical encoder, however, are restricted by the scope of multi-scale modeling. In addition, global attention and scaling attention in regions of interest have not been appropriately adopted, especially for the salient features. To address these two issues, we propose a ConvNet-Transformer hybrid framework named SSCFormer for accurate and versatile medical image segmentation. The intra-scale ResInception and inter-scale transformer bridge are designed to collaboratively capture the intra- and inter-scale features, facilitating the interaction of small-scale disparity information at a single stage with large-scale from multiple stages. Global attention and scaling attention are cleverly integrated from a spatial-channel-aware perspective. The proposed SSCFormer is tested on four different medical image segmentation tasks. Comprehensive experimental results show that SSCFormer outperforms the current state-of-the-art methods.

Solidification/Stabilization of Chromium-Contaminated Soils by Polyurethane during Freeze-Thaw Cycles: Mechanical, Leaching and Microstructure Characterization.

The treatment of chromium-contaminated soil in seasonal frozen soil areas has been the subject of recent interest. Polyurethane (PU), as a polymer material with excellent freeze-thaw resistance and abrasion resistance, has the potential to solidify Chromium-Contaminated soil in seasonal frozen soil areas. However, there is a lack of research on the mechanism of PU involved in solidifying/stabilizing chromium-contaminated soil in seasonal frozen regions from the perspective of pore structure and functional group coordination bonds. In this study, the leaching behavior of PU with different contents under different freeze-thaw cycles was analyzed, and the mechanism of PU in seasonal frozen regions was explored from the perspective of pores and functional groups by combining various microscopic characterization methods. The results show that PU can effectively resist the deterioration of chromium-contaminated soil after freeze-thaw cycles and can better prevent the harm of secondary leaching. The leaching concentration of chromium ion is only 1.09 mg/L, which is below China's regulatory limits. PU is beneficial for inhibiting the expansion of ice crystals in chromium-contaminated soil in seasonal frozen soil areas. PU solidifies chromium by physical encapsulation and complexation reactions. The amide functional groups, methyl-CH3 and isocyanate groups in PU play a leading role in the complexation with chromium. Although the freeze-thaw cycle will destroy the coordination bond between the PU functional group and chromium, chromium cannot break through the bond of PU film. This study confirmed the feasibility of using PU to solidify Chromium-Contaminated soil in seasonal frozen soil areas, which can provide research support and reference for in situ engineering in the future.

Evolution analysis of research on disaster-causing mechanism and prevention technology of mine goaf disaster.

The goaf is an important factor that induces major accidents. Based on the quantitative analysis of the existing research results, summarize and sort out the research and prevention technology of the goaf disaster with the experience of experts. Temporally, the research on goaf disasters was divided into two stages: the embryonic stage and the rapid development stage. Spatially, a collaborative network with the United States, China, Germany, France, Turkey, and the United Kingdom as the core, including India, Japan, Belgium, Italy, South Korea, and Canada, was analyzed. By constructing a co-occurrence and clustering network of keywords and co-cited literature to explore the focus and hotspots of goaf disaster research, the hotspots of goaf disaster research are summarized into four main aspects, such as goaf detection technology, goaf disaster analysis, goaf risk assessment and goaf treatment technology, which grasp the content of goaf research from a macro perspective. The burst detection analysis of keywords and co-cited literature was conducted to obtain the research frontiers of goaf disaster research in different periods. At the current stage, the microstructural characteristics of surrounding rocks in the context of deep mining and complex goaf group effect and the mining technology of the integration of excavation, anchoring and supporting are the current frontier research directions. This combined qualitative and quantitative method is more helpful to grasp the development context of goaf disaster research and provides a new reference perspective for sorting out the process of goaf disaster research.

Collaborative networks of transformers and convolutional neural networks are powerful and versatile learners for accurate 3D medical image segmentation.

Integrating transformers and convolutional neural networks represents a crucial and cutting-edge approach for tackling medical image segmentation problems. Nonetheless, the existing hybrid methods fail to fully leverage the strengths of both operators. During the Patch Embedding, the patch projection method ignores the two-dimensional structure and local spatial information within each patch, while the fixed patch size cannot capture features with rich representation effectively. Moreover, the calculation of self-attention results in attention diffusion, hindering the provision of precise details to the decoder while maintaining feature consistency. Lastly, none of the existing methods establish an efficient multi-scale modeling concept. To address these issues, we design the Collaborative Networks of Transformers and Convolutional neural networks (TC-CoNet), which is generally used for accurate 3D medical image segmentation. First, we elaborately design precise patch embedding to generate 3D features with accurate spatial position information, laying a solid foundation for subsequent learning. The encoder-decoder backbone network is then constructed by TC-CoNet in an interlaced combination to properly incorporate long-range dependencies and hierarchical object concepts at various scales. Furthermore, we employ the constricted attention bridge to constrict attention to local features, allowing us to accurately guide the recovery of detailed information while maintaining feature consistency. Finally, atrous spatial pyramid pooling is applied to high-level feature map to establish the concept of multi-scale objects. On five challenging datasets, including Synapse, ACDC, brain tumor segmentation, cardiac left atrium segmentation, and lung tumor segmentation, the extensive experiments demonstrate that TC-CoNet outperforms state-of-the-art approaches in terms of superiority, migration, and strong generalization. These illustrate in full the efficacy of the proposed transformers and convolutional neural networks combination for medical image segmentation. Our code is freely available at: https://github.com/YongChen-Exact/TC-CoNet.

Deep knowledge tracing with learning curves.

Knowledge tracing (KT) models students' mastery level of knowledge concepts based on their responses to the questions in the past and predicts the probability that they correctly answer subsequent questions in the future. Recent KT models are mostly developed with deep neural networks and have demonstrated superior performance over traditional approaches. However, they ignore the explicit modeling of the learning curve theory, which generally says that more practices on the same knowledge concept enhance one's mastery level of the concept. Based on this theory, we propose a Convolution-Augmented Knowledge Tracing (CAKT) model and a Capsule-Enhanced CAKT (CECAKT) model to enable learning curve modeling. In particular, when predicting a student's response to the next question associated with a specific knowledge concept, CAKT uses a module built with three-dimensional convolutional neural networks to learn the student's recent experience on that concept, and CECAKT improves CAKT by replacing the global average pooling layer with capsule networks to prevent information loss. Moreover, the two models employ LSTM networks to learn the overall knowledge state, which is fused with the feature learned by the convolutional/capsule module. As such, the two models can learn the student's overall knowledge state as well as the knowledge state of the concept in the next question. Experimental results on four real-life datasets show that CAKT and CECAKT both achieve better performance compared to existing deep KT models.

Funeral arrangements requested by suicide decedents in Shanghai and Wuhan, China.

This qualitative study analyzed suicide notes left by 591 decedents in Shanghai and Wuhan, in China. General guidelines and detailed requests with regard to funeral service were coded. In general, suicide decedents preferred untraditional funerals, which were simple and speedy rather than grand and costly funeral arrangements. These choices suggested that suicide decedents could fear stigmatization and discrimination. Some suicide decedents regarded suicides as vicious deaths, and thus wished their families to dispose of the cursed bodily remains and tombs as swiftly as possible.

Fire system safety risk cognition model and evaluation of major public safety risks.

Along with the expansion of city scale, and the increase in the density of population and buildings, the occurrence of a major public fire safety incident in cities will lead to a serious threat to the overall public safety and the sustainable economic and social development of the relevant region. A simple and practical safety risk assessment method of fire prevention in gas stations is of great value for disaster prevention and application in key industries. The constituent elements of a gas station fire prevention safety system are complex, and include equipment, materials, environment, operation, and other factors. This element of information has randomness and temporal dynamics. To promote the transformation of the safety supervision mechanism of gas stations, realize the dual objectives of risk classification and risk dynamic management, and control the gas stations' safety systems the gas stations safety systems are the objectives of our paper. By taking the "fire" risk point of fire prevention in gas stations' system as the research object, this paper puts forward the cognitive path of fire prevention in gas stations' safety system for risk disasters, and explains the coordination between characteristics of inherent, initial, and real risks and the structure of the risk system's attributes. A realistic risk assessment model of fire risk with inherent and dynamic risks is established. An example was introduced to apply the real risk model, and the results were consistent with the actual prediction results, thereby showing the effectiveness and practicability of this method. This risk assessment method can provide a scientific basis for the prevention of fires and control of the fire prevention safety system, showing the changes in risk levels in different stages, and providing risk warning for project managers in taking prompt corresponding risk control countermeasures and improving the efficiency of risk management.

Cement-Based Materials Modified by Colloidal Nano-Silica: Impermeability Characteristic and Microstructure.

Colloidal nano-silica (CNS) was used to improve the mechanical and impermeability characteristics of mortar in this study. The samples were prepared with 0%, 1%, 2% and 3% (solid content) CNS addition. The mechanical strength and permeability of each mixture was studied, and the mechanism behind was revealed by hydration heat evolution, XRD, DSC-DTG, 29Si MAS-NMR and SEM-EDS analysis. The compressive strength and impermeability characteristics of mortars incorporating CNS were significantly improved. The experimental results demonstrated that the incorporation of CNS promoted the early hydration process of cement, thus increasing the polymerization degree of hydrated calcium silicate, decreasing the porosity, and improving the microstructure of mortar. Furthermore, 3% CNS decreased the Ca/Si ratio of the interfacial transition zone (ITZ) from 3.18 to 2.22, thus the enrichment of CH was reduced and the density and strength were improved. This was mainly because of the high pozzolanic activity of CNS, which consumed plenty of calcium hydroxide and converted to C-S-H. Besides, nanoscale CNS and C-S-H particles filled the voids between hydrates, thus refining the pore size, increasing the complexity of pores, and improving the microstructure of ITZ which contributed to the improvement of the impermeability.

Investigation of CO2 Photoreduction in an Annular Fluidized Bed Photoreactor by MP-PIC Simulation.

Carbon dioxide (CO2) photoreduction is a promising process for both mitigating CO2 emissions and providing chemicals and fuels. A gas-solid two-phase annular fluidized bed photoreactor (FBPR) would be preferred for this process due to its high mass-transfer rate and easy operation. However, CO2 photoreduction using the FBPR has not been widely researched to date. The Lagrangian multiphase particle-in-cell (MP-PIC) simulation with computational fluid dynamic models is a new and robust approach to explore the multiphase reaction system in the gas-solid fluidized bed. Therefore, the purpose of this paper is to investigate CO2 photoreduction in the FBPR by MP-PIC modeling to understand the intrinsic mechanism of solid flow, species mass transfer, and CO2 photoreaction. The MP-PIC models for solid flow in the FBPR were validated by the bed expansion height and bubble size. The results showed the particle stress of the Lun model, the drag of the Ergun-WenYu (Gidaspow) model, and the coefficient of restitution e = 0.95 with the wall parameters e w = 0.9 and µw = 0.6 are the best fit to the experimental empirical correlations. The MP-PIC models developed in this work proved to be better than the Eulerian two-fluid modeling in the prediction of the bed expansion height and bubble size. It was also found from the simulation results that the maximum radiation intensity is in the half reactor height area, and the photocatalytic reaction mainly occurred around the inner wall. It showed that the gas velocity and catalyst loading were two crucial operating parameters to control the process. The results reported here can provide guidance for the operation and reactor design of the CO2 photoreduction process.

Self-Stigma and Its Relationship With Rates of Depression Diagnosis.

Background: Self-stigma about suicide might impede people seeking help from mental health professionals. There is little research about self-stigma expressed by suicide decedents. Aims: We aimed to explore (a) self-stigma about suicide through examination of suicide notes; and (b) whether the expression of self-stigma was associated with the formal diagnoses of depression. Method: Data were extracted from notes left by people who died by suicide in two major Chinese cities (Shanghai, 2004-2017; Wuhan, 2005-2019). Note content was examined and self-stigma items were coded. Demographics associated with self-stigma were reported. Rates of depression were compared between note-leavers who expressed self-stigma, and those who did not. Results: Notes were left by 567 suicide decedents (representing about 19% all suicides). Approximately 25% notes contained at least one self-stigma item. Older people made fewer self-stigma references, as did people from Wuhan. Depression was not associated with self-stigma. Limitations: Not all people dying from suicide leave notes, and suicide notes variably report self-stigma, thus self-stigma about suicide may be underestimated. Conclusion: Self-stigma items varied across regions and age groups, but not with depression. Therefore, self-stigma expressed by suicide decedents may not reflect help-seeking behaviours from professional mental health services.

Modulation of Structure and Optical Property of Nitrogen-Incorporated VO2 (M1) Thin Films by Polyvinyl Pyrrolidone.

VO2, as a promising material for smart windows, has attracted much attention, and researchers have been continuously striving to optimize the performance of VO2-based materials. Herein, nitrogen-incorporated VO2 (M1) thin films, using a polyvinylpyrrolidone (PVP)-assisted sol-gel method followed by heat treatment in NH3 atmosphere, were synthesized, which exhibited a good solar modulation efficiency (ΔTsol) of 4.99% and modulation efficiency of 37.6% at 2000 nm (ΔT2000 nm), while their visible integrated transmittance (Tlum) ranged from 52.19% to 56.79% after the phase transition. The crystallization, microstructure, and thickness of the film could be regulated by varying PVP concentrations. XPS results showed that, in addition to the NH3 atmosphere-N doped into VO2 lattice, the pyrrolidone-N introduced N-containing groups with N-N, N-O, or N-H bonds into the vicinity of the surface or void of the film in the form of molecular adsorption or atom (N, O, and H) filling. According to the Tauc plot, the estimated bandgap of N-incorporated VO2 thin films related to metal-to-insulator transition (Eg1) was 0.16-0.26 eV, while that associated with the visible transparency (Eg2) was 1.31-1.45 eV. The calculated Eg1 and Eg2 from the first-principles theory were 0.1-0.5 eV and 1.4-1.6 eV, respectively. The Tauc plot estimation and theoretical calculations suggested that the combined effect of N-doping and N-adsorption with the extra atom (H, N, and O) decreased the critical temperature (τc) due to the reduction in Eg1.

Origin and Genesis of Solid Bitumen from the Sinian Dengying Reservoir in the Deyang-Anyue Rift within the Sichuan Basin (SW China): Evidence from Biomarkers and Microscopic Features.

Deep-carbonate gas reservoirs are a significant field for conventional gas exploration in the Sichuan Basin, and industrial-grade gas reservoirs have recently been discovered in the second member of the Dengying Formation in the Deyang-Anyue rift. Drilling results have indicated that the large amount of solid bitumen that is commonly found in pores and fractures in the reservoir of the second member of the Dengying Formation. However, systematic studies have not yet been conducted on the solid bitumen of the second member of the Dengying Formation and its genesis and parent source remain unclear. This study is based on the systematic analysis of solid bitumen samples collected from new exploratory wells, with the aid of optical microscopy, scanning electron microscopy, and gas chromatography-mass spectrometry to clarify the genesis, thermal maturity, and parent source deposition environment of the solid bitumen. Electron microscopy and biomarker results indicate that bitumen is in a high-maturity stage and is a product of the thermal cracking of crude oil. Energy dispersive spectrometer results and the continuous distribution of n-alkanes indicate that the bitumen is not subjected to strong thermochemical sulfate reduction and biodegradation. Isoprenoids and terpenes suggest that the palaeoreserves associated with the bitumen of the second member of the Dengying Formation originate in reductive marine carbonate sediments. The combination of regional stratigraphic contact relationships, lithology, and biomarker characteristics implies that the Maidiping Formation muddy dolomite and the Dengying Formation algal dolomite are the potential parent sources of solid bitumen in the second member of the Dengying Formation.

Hydrocarbon Accumulation Process and Mechanism in the Lower Jurassic Reservoir in the Eastern Kuqa Depression, Tarim Basin, Northwest China: A Case Study of Well Tudong 2 in the Tugerming Area.

The Lower Jurassic reservoir has recently made a significant breakthrough in petroleum exploration in the Tugerming area of the eastern Kuqa depression, Tarim Basin, northwest China. Therefore, it is significantly essential to simulate the hydrocarbon charging process and analyze the accumulation mechanism in the study area. In our study, we mainly combine three geochemical techniques to identify the origin of crude oils and fluid inclusion characteristics in the target well (Tudong 2), including gas chromatography-mass spectrometry (GC-MS), comprehensive two-dimensional GC-time-of-flight MS (GC × GC-TOFMS), fluid inclusion analysis, and quantitative fluorescence technique. Combined comprehensive experiments with a set of burial history and tectonic thermal evolution history realize the reconstruction of the hydrocarbon charging process in the Yangxia formation. The results show that Jurassic coal-bearing source rocks are primary hydrocarbon sources, and there are three hydrocarbon charging events in the Lower Jurassic reservoir. First, the mature oils have expelled into the reservoir during the early-middle period (15-10 Ma) of the Miocene Kangcun Formation, forming yellow fluorescent oil inclusions and most of the quantitative grain fluorescence (QGF) indexes exceed 4. Second, numerous condensate oils have charged into the reservoir in the period of late Miocene Kangcun Formation-early Kuqa Formation (9-6 Ma), accompanied by blue-white oil inclusions and QGF on extract intensity greater than 4. Finally, vast natural gas has accumulated in the reservoir since Kuqa Formation (5-0 Ma), resulting in the adjustment of ancient reservoir and residual bitumen. Interestingly, we find that the hydrocarbon accumulation mechanism is characterized by self-generation and self-storage in the Jurassic Yangxia Formation, and the study area has prominent characteristics of late accumulation. Thus, the evidence obtained from our analysis suggests favorable geological conditions for the formation of a large oil and gas reservoir in the eastern Kuqa Depression.

Genetic Differentiation and Mixed Reproductive Strategies in the Northern Corn Leaf Blight Pathogen Setosphaeria turcica From Sweet Corn in Fujian Province, China.

The northern corn leaf blight (NCLB) pathogen Setosphaeria turcica (Luttrell) Leonard and Suggs is one of the main biotic constraints on sweet corn (Zea mays L.) yield and quality in Fujian Province, China. Currently, however, there is comparatively little information available regarding the distribution of mating types, population genetics, and reproductive strategies of this pathogen in Fujian. In this study, we investigated the distribution of mating types and population genetics of 117 isolates of S. turcica collected from seven of the main sweet corn-growing regions in Fujian Province, based on multiple polymerase chain reaction analyses using two mating type-specific primer pairs and 11 inter-simple sequence repeat markers. Furthermore, we examined the mode of reproduction of Fujian S. turcica populations. Both MAT1-1 and MAT1-2 mating types were detected throughout all seven sampling locations. The majority of MAT1-2 isolates were detected from Dongyou, Jian'ou, Pingnan, Songxi, and Longyan, whereas a large proportion of the detected MAT1-1 isolates were among those collected from Dongfeng and Nanjing. Furthermore, we detected five shared multi-locus haplotypes among S. turcica isolates from Dongyou, Jian'ou, Pingnan, Nanjing, and Songxi, whereas no shared haplotypes were observed between the Dongfeng (or Longyan) population and these five populations. Pairwise comparisons of the indices ΦPT and Nm, and population structure and principal coordinate analyses indicated genetic differentiation between both the regional and the mating type populations of S. turcica in Fujian. The skewed mating type ratio associated with low a haplotypic diversity and evident linkage disequilibrium reveals a mixed reproductive strategy for S. turcica populations in Fujian Province. The findings of this study advance our current understanding of the genetic diversity, population structure, and reproductive strategies of S. turcica populations infecting sweet corn in Fujian Province, and will potentially contribute to further resistance breeding efforts.

Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents.

The neurocognitive characteristics of mathematically gifted adolescents are characterized by highly developed functional interactions between the right hemisphere and excellent cognitive control of the prefrontal cortex, enhanced frontoparietal cortex, and posterior parietal cortex. However, it is still unclear when and how these cortical interactions occur. In this paper, we used directional coherence analysis based on Granger causality to study the interactions between the frontal brain area and the posterior brain area in the mathematical frontoparietal network system during deductive reasoning tasks. Specifically, the scalp electroencephalography (EEG) signal was first converted into a cortical dipole source signal to construct a Granger causality network over the θ-band and γ-band ranges. We constructed the binary Granger causality network at the 40 pairs of cortical nodes in the frontal lobe and parietal lobe across the θ-band and the γ-band, which were selected as regions of interest (ROI). We then used graph theory to analyze the network differences. It was found that, in the process of reasoning tasks, the frontoparietal regions of the mathematically gifted show stronger working memory information processing at the θ-band. Additionally, in the middle and late stages of the conclusion period, the mathematically talented individuals have less information flow in the anterior and posterior parietal regions of the brain than the normal subjects. We draw the conclusion that the mathematically gifted brain frontoparietal network appears to have more "automated" information processing during reasoning tasks.

Weighted Brain Network Metrics for Decoding Action Intention Understanding Based on EEG.

Background: Understanding the action intentions of others is important for social and human-robot interactions. Recently, many state-of-the-art approaches have been proposed for decoding action intention understanding. Although these methods have some advantages, it is still necessary to design other tools that can more efficiently classify the action intention understanding signals. New Method: Based on EEG, we first applied phase lag index (PLI) and weighted phase lag index (WPLI) to construct functional connectivity matrices in five frequency bands and 63 micro-time windows, then calculated nine graph metrics from these matrices and subsequently used the network metrics as features to classify different brain signals related to action intention understanding. Results: Compared with the single methods (PLI or WPLI), the combination method (PLI+WPLI) demonstrates some overwhelming victories. Most of the average classification accuracies exceed 70%, and some of them approach 80%. In statistical tests of brain network, many significantly different edges appear in the frontal, occipital, parietal, and temporal regions. Conclusions: Weighted brain networks can effectively retain data information. The integrated method proposed in this study is extremely effective for investigating action intention understanding. Both the mirror neuron and mentalizing systems participate as collaborators in the process of action intention understanding.

Putting the Blame on Others in Suicide Notes From Shanghai and Wuhan, China.

Background: Suicide note leavers sometimes blame others for their death. The blame could reveal extrinsic suicide risk factors and thus countermeasures may be ascertained. Aims: This study included suicide note leavers in Shanghai and Wuhan (n = 555) to examine (a) who was inclined to put the blame (b) on whom and (c) for what reason(s). Method: Logistic regressions were used to compare the note leavers who blamed others with those who did not. Cramer's V tests were used to examine the correlations between the note leavers' demographics and the targets of the blame. Results: Note leavers who used poisoning and cutting were more likely to blame others compared with those who used jumping, drowning, and hanging. Non-native note leavers tended to more frequently blame social problems and their workplaces compared with the natives. The common reasons for the blame on nonfamily members, children, and lovers/spouses were being mistakenly blamed for something, being disobedient, and having conflicts/hatred, respectively. Limitations: Some blame could have been made under the influence of psychiatric disorder/substances, and thus potentially deviated from the facts. Conclusion: Emotional/marriage consultations and family-therapy services should be made available to females experiencing love/family crises. Mental health services in the workplace could help reduce suicide risks.

A Study of the Characteristics of Suicide Notes in China.

Background: Suicide notes in China are rarely studied and seldom available. Aims: This study examines the characteristics of suicide note leavers and analyzes the contents of their suicide notes for the period of 2004-2016 in Pudong, Shanghai, which has more than 5.5 million inhabitants. Method: The characteristics of the note leavers (n = 458) and those who left no notes (n = 1949) were compared. Four major groupings of the suicide note content were identified, namely, addressees, mandates/requests, expressions, and difficulties. Results: Only 19.0% of the deceased left suicide notes and they were characterized by having no diagnosed psychiatric illnesses, being in debt, having a high education level, having made no previous suicide attempts, and having used suicide methods that required preparation. Wanting to hide their suicide information was not uncommon for these individuals (9.7%). Adolescents were likely to mention a negative interpersonal relationship with someone (27.4%). Illnesses/pain was frequently mentioned by adults (33.4%) and older people (61.5%). Limitations: Many features of suicide notes, e.g., interpersonal features of suicides, were not examined. Conclusion: Education level might be a key factor influencing the likelihood of leaving suicide notes. Most people who left suicide notes showed a negative attitude toward suicidal behavior. The myth of an afterlife should also be addressed.

Mortalities of methamphetamine, opioid, and ketamine abusers in Shanghai and Wuhan, China.

Studies on the mortalities of drug abusers in China are scarce. This study explores the deaths of methamphetamine, opioid, and ketamine abusers in Shanghai (2004-2017) and Wuhan (2005-2017). Chi-square/Fisher's exact tests were used to compare the differences in terms of region, gender, age, cause of death, and the method used in the last drug abuse. Poisson regression models were used to estimate the rate ratios ("RRs") and annual percentage changes ("APCs"). 314 heroin, 43 methamphetamine, and 4 ketamine abusers were included. Furthermore, simultaneously, 6 abusers used heroin and methamphetamine, and 7 abusers used methamphetamine and ketamine. Heroin-related deaths have declined in Shanghai (APC, -16.1; 95 % CI, -18.4 to -11.3) and Wuhan (APC, -16.0; 95 % CI, -18.9 to -10.6), whereas methamphetamine-related deaths have increased in Wuhan (APC, 12.8; 95 % CI, 0.0 to 29.2). On the whole, in the two cities, males were more frequently observed than females in heroin-related deaths (4.4, 230/52). However, the gender ratios for methamphetamine- (1.8, 34/19) and ketamine-related deaths (1.2, 6/5) were close to one. In view of the mortality rates of the drug abusers in most Chinese cities were still unclear, it is thus important to improve mortality surveillance of the drug abusers at the national level.