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Objective:. The impact of dairy fat on inflammatory bowel disease remained inconclusive. We aimed to compare the effects of whole-milk and skimmed-milk consumption on the risk of inflammatory bowel disease using a Mendelian randomization analysis. Methods:. We conducted a genome-wide association study of the preference for whole versus skimmed milk using data for 20,200 whole-milk consumers and 67,847 skimmed-milk consumers from the UK Biobank. The lead single nucleotide polymorphisms in the associated loci were identified at the genome-wide significance level, and were further employed as instrumental variables for whole-milk preference. We conducted a two-sample Mendelian randomization analysis with whole-milk preference as the exposure and inflammatory bowel disease as the outcome. The pleiotropic effects and heterogeneity of the instrumental variables were estimated using Mendelian randomization-Egger regression and Cochran Q test, respectively. This study was conducted using the UKB resources under the application “53536”. The UK Biobank was approved by the North West Multi-center Research Ethics Committee, the National Information Governance Board for Health and Social Care in England and Wales, and the Community Health Index Advisory Group in Scotland. Results:. The genome-wide association study identified five lead nucleotide polymorphisms associated with whole-milk preference. Mendelian randomization indicated that whole-milk preference significantly decreased the risk of inflammatory bowel disease (β=−1.735, P = 0.048). Of the two subtypes, whole-milk preference was associated with a lower risk of Crohn disease (β=−2.549, P = 0.032), but had no significant effect on the risk of ulcerative colitis (β=−1.002, P = 0.44). Conclusion:. Consumption of whole-milk fat may protect against Crohn disease, compared with skimmed milk. This conclusion was based on causal inference in a cohort study, and further validation in randomized controlled trials is warranted.

One of the major causes of the coronary heart disease is vascular stenosis and thrombosis that is generally caused by development of fibrous plaques. Therefore, detection of a fibrous plaque in coronary arteries for the diagnosis and treatment of coronary heart disease is of clinical significance. Technical challenges are in reading the optical coherence tomography (OCT) images which is tedious and inaccurate. In response, we propose an automated coronary artery fibrous plaque detection method based on deep learning with Convolutional Neural Networks (CNN). We present our novel techniques of identifying a contracting path to capture the context and a symmetric expanding path that enables the precise localization. The algorithm utilizes the features of the contracting path and the expanding path, so that the merged features can present the context and accurate localization, and uses the multi-scale feature maps for detection. Experimental results show that the proposed method achieved a coincidence of 91.04%, accuracy of 94.12%, and recall of 94.12%. Compared with the previously published work the proposed method is advantageous in both accuracy and robustness.

The construction of electricity retail market poses unprecedented opportunities and challenges for the sale of electricity. The traditional mode of electricity business marketing is not suitable for the new market environment, and it needs change in many aspects. How to serve customers well in the competitive environment, seize the market, and improve their own operating efficiency is an urgent problem for power grid enterprises. This paper regards the development of electricity retail market as the diffusion process of innovation. Based on the diffusion of innovations theory, this paper analyzes the characteristics of different development stages, and formulates service strategies according to their characteristics, so as to provide reference for power grid enterprises to seize the market.

Background Nursing work is associated with great pressure, and nurses are often overwhelmed. Therefore, correct emotional regulation is essential to improve nurses’ job well-being and promote better engagement in nursing work. The purpose of this study was to establish a structural model to estimate the impact of Chinese clinical nurses’ emotional intelligence on job well-being, using multiple intermediaries to explain the internal mechanisms underlying the relationship. Methods This was a cross-sectional study of 1475 registered nurses from a Chinese hospital who provided responses to emotional intelligence, empathy, communication satisfaction, and job well-being scales. Path analysis using a multiple mediation model was performed using AMOS 23.0. Results Among all clinical nurses who participated in the survey, 1475 (98.33 %) completed the questionnaire. The nurses’ job well-being score was 83.61 ± 12.63. There was a significant positive correlation between job well-being and communication satisfaction, emotional intelligence, and empathy ability (r = 0.346–0.570, P Conclusions It is recommended that hospital managers take actions to improve nurses’ emotional intelligence level, and conduct professional psychological training to improve nurses’ empathy and communication satisfaction, and ultimately improve their job well-being.

Identification of coronary atherosclerotic plaques and vulnerable plaques is of great clinical significance in the diagnosis and treatment of coronary artery diseases, such as myocardial infarction and sudden death. Optical coherence tomography (OCT) is a catheter-based intracoronary imaging technique with high resolution (

Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin4 receptor (MC4R) gene, one of the candidate genes for AIMD, has been under-studied in the Chinese patients. We conducted a pharmacogenetic study in a large cohort of Chinese patients with schizophrenia. In this study, we investigated the genetic variation of MC4R in Chinese population by genotyping two SNPs (rs489693 and rs17782313) in 1,991 Chinese patients and examined association of these variants with the metabolic effects that were often observed to be related to AIMD. Metabolic measures, including body mass index (BMI), waist circumference (WC), glucose, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were assessed at baseline and after 6-week antipsychotic treatment. We found that interaction of SNP×medication status (drug-naïve/medicated) was significantly associated with BMI, WC, and HDL change %, respectively. Both SNPs were significantly associated with baseline BMI and WC in the medicated group. Moderate association of rs489693 with WC, Triglyceride, and HDL change % were observed in the whole sample. In the drug-naïve group, we found recessive effects of rs489693 on BMI gain more than 7%, WC and Triglyceride change %, with AA incurring more metabolic adverse effects. In conclusion, the association between rs489693 and the metabolic measures is ubiquitous but moderate. Rs17782313 is less involved in AIMD. Two SNPs confer risk of AIMD to patients treated with different antipsychotics in a similar way.

To understand the role of hydrogen donation from solvents to the coal-generated free-radical fragments (coal radicals) in direct coal liquefaction (DCL), a coal with 72.4 wt % carbon was reacted at...

Two-dimensional Ruddlesden–Popper organic lead halide perovskites (2D RPPs) are semiconducting materials that have attracted widespread research attention recently. Fundamental understanding of heterovalent doping, a classical strategy to manipulate semiconductors′ optoelectronic and stability properties, is of great significance for their applications. Here we report the first series of heterovalent-doped 2D RPPs via Bi3+ doping for (BA)2(MA)n−1PbnI3n+1 (BA = n-C4H9NH3+; MA = CH3NH3+; n = 1, 2 and 3). Systematic experimental studies lead to the discovery of a positive correlation between the layer number and the doping level. Combined theoretical and experimental observations suggest the presence of two distinctive types of Bi3+ sites, a non-radiative recombination site at the organic/inorganic interface and a near-infrared (NIR) emission site at the middle Pb–I layer of the 3-layered 2D RPPs. Surprisingly, significantly improved photostability and environmental stability for the 2D RPPs were observed upon appropriate levels of Bi3+ doping. A fluorescence microscopy study suggests that a preferential doping-induced formation of 1L RPPs at the edges or cracks might act as a new mechanism to enhance the stability, providing an unprecedented strategy to improve the stability of perovskites and a new class of materials for device dimensionality engineering.

Background Examining associations between viral genomic loads of enteroviruses and clinical severity is important for promoting and improving development of antiviral drugs related to hand, foot and mouth disease (HFMD). Methods Throat swabs were collected from HFMD cases at acute phase of illness using a standardized technique in a prospective study. The viral genomic load was categorized into low, medium, and high groups using parameters of real-time reverse transcription-polymerase chain reaction. The clinical severities were assessed with four indicators, respectively. Findings We analysed 1109 HFMD cases, including 538 children with CV-A6, 231 with CV-A16, 156 with EV-A71, 78 with CV-A10, 59 with CV-A4, and 47 with CV-A2. EV-A71 genomic load categories were associated with risks of diagnoses of CNS complications (p = 0.016), requiring systemic corticosteroids or IVIG (p = 0.011), intensive care unit admission (p = 0.002) and length of hospital stay over 5 days (p = 0.048). In the multivariate analyses, point estimates of adjusted odds ratio (OR) tended to increase with viral genomic loads for all four severe outcomes and ORs of highest viral genomic load were all significantly larger than one for EV-A71. Interpretation HFMD clinical severities positively associate with viral genomic loads of EV-A71 in throat swabs. Specific antiviral drugs should be developed to reduce enterovirus load and to alleviate the clinical severities for HFMD cases. Funding National Science Fund for Distinguished Young Scholars

Background Understanding the patterns of treatment response is critical for the treatment of patients with schizophrenia; one way to achieve this is through using a longitudinal dynamic process study design. Aims This study aims to explore the response trajectory of antipsychotics and compare the treatment responses of seven different antipsychotics over 6 weeks in patients with schizoprenia (trial registration: Chinese Clinical Trials Registry Identifier: ChiCTR-TRC-10000934). Method Data were collected from a multicentre, randomised open-label clinical trial. Patients were evaluated with the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up at weeks 2, 4 and 6. Trajectory groups were classified by the method of k-means cluster modelling for longitudinal data. Trajectory analyses were also employed for the seven antipsychotic groups. Results The early treatment response trajectories were classified into a high-trajectory group of better responders and a low-trajectory group of worse responders. The results of trajectory analysis showed differences compared with the classification method characterised by a 50% reduction in PANSS scores at week 6. A total of 349 patients were inconsistently grouped by the two methods, with a significant difference in the composition ratio of treatment response groups using these two methods (χ2 = 43.37, P < 0.001). There was no differential contribution of high- and low trajectories to different drugs (χ2 = 12.52, P = 0.051); olanzapine and risperidone, which had a larger proportion in the >50% reduction at week 6, performed better than aripiprazole, quetiapine, ziprasidone and perphenazine. Conclusions The trajectory analysis of treatment response to schizophrenia revealed two distinct trajectories. Comparing the treatment responses to different antipsychotics through longitudinal analysis may offer a new perspective for evaluating antipsychotics.

Motor imagery (MI) electroencephalography (EEG) classification is an important part of the brain-computer interface (BCI), allowing people with mobility problems to communicate with the outside world via assistive devices. However, EEG decoding is a challenging task because of its complexity, dynamic nature, and low signal-to-noise ratio. Designing an end-to-end framework that fully extracts the high-level features of EEG signals remains a challenge. In this study, we present a parallel spatial-temporal self-attention-based convolutional neural network for four-class MI EEG signal classification. This study is the first to define a new spatial-temporal representation of raw EEG signals that uses the self-attention mechanism to extract distinguishable spatial-temporal features. Specifically, we use the spatial self-attention module to capture the spatial dependencies between the channels of MI EEG signals. This module updates each channel by aggregating features over all channels with a weighted summation, thus improving the classification accuracy and eliminating the artifacts caused by manual channel selection. Furthermore, the temporal self-attention module encodes the global temporal information into features for each sampling time step, so that the high-level temporal features of the MI EEG signals can be extracted in the time domain. Quantitative analysis shows that our method outperforms state-of-the-art methods for intra-subject and inter-subject classification, demonstrating its robustness and effectiveness. In terms of qualitative analysis, we perform a visual inspection of the new spatial-temporal representation estimated from the learned architecture. Finally, the proposed method is employed to realize control of drones based on EEG signal, verifying its feasibility in real-time applications. Published version

Objectives Enterovirus A71 (EV-A71) is the main pathogen of severe hand, foot, and mouth disease (HFMD). Commercial enzyme-linked immunosorbent assays (ELISAs) are widely used in Chinese hospitals for the rapid diagnosis of acute EV-A71 infections. We present an evaluation of the diagnostic performance of a commercial anti-EV-A71 IgM-capture ELISA kit. Methods A prospective, hospital-based HFMD cohort was established in Henan Children's Hospital (February 2017 - February 2018). Stool and blood specimens were collected from 1413 participants for diagnosing EVA71 by quantitative Real-Time Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) and anti-EV-A71 ELISA. Results Detection yields of EV-A71 IgM increased from 6.5 % (95 % CI:3.3 %–11.4 %) at 0∼24 h, to 42 % (95 % CI:28.3 %–57.8) at 120∼144 h from onset to sampling, and stabilized at ∼40 % after 144 h. With increased time from onset to sampling, the sensitivity of the commercial ELISA increased from 0.54 (95 % CI:0.25−0.81) to 0.74 (95 % CI:0.43−0.66), while specificity decreased from 0.97 (95 % CI:0.93−0.99) to 0.80 (95 % CI:0.69−0.89), and PPV decreased from 0.96 (95 % CI:0.92−0.99) to 0.84 (95 % CI:0.73−0.92). Multivariate analysis found age, EV-A71 vaccination, previous HFMD/Herpangina infection, disease severity, infection during peak EV-A71 season, and sampling time after symptom onset were significantly associated with the diagnostic performance of this anti-EV-A71 IgM-capture ELISA. Conclusion Achieving satisfactory specificity and sensitivity scores, this commercial anti-EV-A71 IgM-capture ELISA kit is suitable for clinical EV-A71 diagnosis, particularly in resource-poor areas. However, clinicians should interpret results in the context of patient history and epidemiological setting.

To compare longitudinal metabolic effects of 7 antipsychotics, including body mass index (BMI), waist circumference (WC), blood pressure (BP), glucose, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C); to investigate risk factors for metabolic syndrome (MetS); and to make recommendations on frequency and timing of monitoring metabolic measurements.This randomized, open-label, pharmacologic trial was conducted among patients with schizophrenia (DSM-IV) in 32 hospitals across China. Patients were randomly assigned to 7 groups and assessed at baseline, 2, 4, and 6 weeks. Linear mixed-effect models were used to assess changes of metabolic measures over time. Multivariable logistic regression analysis was performed to investigate the risk factors for MetS.In total, 2,550 (718 drug-naïve) of 2,774 patients finished the study between July 6, 2010, and November 30, 2011. We found significant (P.05) changes for BMI, WC, TG, and LDL-C, with TG and LDL-C reaching a plateau. Interactions between baseline metabolic condition and changes over time were observed for BMI (χ² = 43.11, P.001), WC (χ² = 36.34, P.001), systolic BP (χ² = 11.92, P = .002), glucose (χ² = 6.09, P = .01), and TG (χ² = 6.01, P = .01). Antipsychotics generally had greater adverse effects on patients who were initially screened as metabolically normal. After controlling for other associated factors, we found that antipsychotics resulted in differing risk for incident MetS, with a similar pattern to findings in other populations: olanzapine (odds ratio [OR] = 3.36, P.001)quetiapine (OR = 3.29, P.001)perphenazine (OR = 2.73, P = .007)risperidone (OR = 2.21, P = .02)aripiprazole (OR = 1.74, P = .15) ≈ haloperidol (OR = 1.75, P = .22) ≈ ziprasidone (OR = 1, reference).Metabolic traits should be monitored frequently in early stages of antipsychotic treatment due to rapid and substantial changes. Clinicians should not assume low risk for patients with normal metabolic parameters at baseline.Chinese Clinical Trial Registry identifier: ChiCTR-TRC-10000934.

It is demonstrated that EBIC imaging technique is superior in quick localizing polysilicon defect of metal-oxide-semiconductor field-effect transistors (MOSFETs). Once polysilicon leakage phenomena are examined, relying on EBIC imaging analysis, we can rapidly isolate nanoscale defect in tens of microns length range. Although faulty polysilicon is employed by more than one MOSFET, it turns out to be unnecessary to characterize all devices after EBIC imaging analysis. By comparative studies, it is concluded that 2-probe EBIC imaging is preferred for mega-Ohm range resistive defect localization while 1-probe configuration is only applicable for kilo-Ohm range. Nanoprobe I-V measurement of the isolated device uncovers the abnormal electrical characteristic which fairly aligns with EBIC imaging analysis. Focused ion beam (FIB) and transmission electron microscopy (TEM) findings imply the EBIC imaging has submicron level spatial resolution toward resistive defects. Therefore it overcomes traditional limits in terms of technical method and lowers failure analysis (FA) difficulty considerably. Ultimately, a simplified model is proposed to explain the physical mechanism of this application. Our modeling describes the strong dependance of EBIC imaging on hot excess carrier behavior within shallow p-n junction when electron beam (e-beam) penetrates into bulk silicon. The work improves the understanding of excess minority carriers transport properties in p-n junction under scanning e-beam irradiation. And this paper may make EBIC imaging be a more promising way to identify minute material defect of future advanced MOSFET.

This paper presents a high-performance algorithm for diagnosing coronary artery disease (CAD) through a blindfold strategy and subject-specific data with ECG signals.In the proposed method,multi-grained scanning with sliding window is constructed to ensure the validity of the features extracted in the ECG segments.Completely random forests and random forests are used for extracting diverse features automatically.This allows the proposed algorithm to achieve excellent detection accuracy with subject-specific data and different-scale training data. Moreover, the gain comparison of the cascade forests is used inherently to optimize model parameters automatically, thereby avoiding errors caused by the manual setting of parameters. The proposed algorithm achieves an accuracy with 100% when 10% of the training data are used. Even in the case where the training set ratio is 0.1%, the detection accuracy of the proposed model is 99.86%. Additionally, the classification performance of the proposed algorithm on subject-specific data reaches 99.98%. Due to its robustness to perturbations in the scale of the training data and efficiency regarding specific subject data, the proposed system is applicable to CAD diagnosis.

Optical coherence tomography (OCT) is a novel technology used in coronary artery disease diagnosis for its high resolution. It has numerous advantages in 3D vessel modeling and vulnerable plaque quantification. This paper proposes a robust vessel intimal extraction algorithm using active contours. A pre-processing module, that takes into consideration the characteristics of coronary OCT imagery, is introduced to eliminate a variety of visual disruptions. Then, a monotonically decreasing function is added into the Chan-Vese (CV) method in order to avoid over segmentation. This is done by controlling the evolution speed in closing the boundary area. A postprocess is followed after CV segmentation to weaken the rotation distortion influence on the extraction result. We use 281 clinical coronary OCT images gathered from Peking Union Medical College Hospital to validate our algorithm. Then we compare our results to manual expert evaluations and a conventional CV method. The extraction results can be used in clinical applications and can provide a basis to further plaque classification.

The swelling and sorption experiments were carried out simultaneously for two block coal samples under CO 2 and CH 4 pressure (up to 16 MPa) at three temperatures (25, 45 and 65 °C). The absolute sorption isotherms present type- II pattern and can be described by a modified BET model. The swelling isotherms present L -type pattern and can be described by a modified Langmuir model. The relationship between swelling ratio and absolute sorption amount presents S -type pattern and can be described by a modified Gompertz function (a logistic function). It is interesting to find that the correlations of normalized properties have a single relationship that is independent of experimental conditions, coals and gases. When the sorption amount approaches to the monolayer sorption coverage ( n a / n m = 1), the swelling ratio reaches ∼93% of the maximum swelling ratio. It implies the importance of the mutual contact between coal and sorbate. The differential characteristic of swelling process shows that the swelling rate with respect to sorption amount varies with the sorbate coverage; the swelling rate peaks at n a / n m ≈ 0.37 and approches zero at n a / n m ≈ 1.5. In addition, a theoretical model correlating swelling and sorption was established. The concept of reduction of surface free energy by sorption was taken into account. It is encouraged that the experiment data match of model is generally acceptable.

Background: Diabetic retinopathy (DR) is a common diabetes complication and was considered as the major cause of blindness among young adults. MiRNAs are a group of small non-coding RNAs regulating the expression of target genes, and have been reported to be associated with the development of diabetic retinopathy in a variety of molecular mechanisms. In this study, we aimed to identify miRNAs that are differentially expressed in the serum of DR patients. Methods: We recruited 21 type 2 diabetes mellitus (T2DM) inpatients of Chinese Han ancestry, consisted of 10 non-proliferative DR patients (DR group) and 11 non-DR T2DM patients (NDR group). MiRNA was extracted from fasting peripheral serum and quantified by RNA-seq. The expression levels of miRNA was evaluated and compared between the two groups, with the adjustment of age. The validated target genes of miRNAs were subjected to a pathway analysis. We also constructed a weighted polygenic risk score using the differentially expressed miRNA and evaluated its predictive power. Results: Five miRNAs were differentially expressed between DR and NDR groups (p value ≤ 0.01, LFC ≥ 2 or LFC ≤ -2). These included miR-4448, miR-338-3p, miR-190a-5p, miR-485-5p, miR-9-5p. In total, these miRNAs was validated to regulate 55 target genes. Four target genes were found to overlap with the NAD metabolism, sirtuin and aging pathway, which was thought to control the vascular growth and morphogenesis. The predictive power of our polygenic risk score was apparently high (AUC = 0.909). However, it needs to be interpreted with caution. Conclusion: In this study, we discovered novel DR-specific miRNAs in human serum samples. These circulating miRNAs may represent the pathological changes in the retina in response to diabetes and may serve as non-invasive biomarkers for early DR risk prediction.

Importance The underlying mechanism for individual differences in patient response to antipsychotic medication remains unknown. Objective To discover genes and gene sets harboring rare variants associated with short-term antipsychotic medication efficacy. Design, Setting, and Participants In this multicenter, open-label, randomized clinical trial conducted between July 6, 2010, and December 31, 2011, 3023 patients recruited in China of Chinese Han descent with schizophrenia with total Positive and Negative Syndrome Scale (PANSS) score ≥ 60 received a 6-week treatment of antipsychotic medications randomly chosen from 5 atypical and 2 typical antipsychotic medications. Whole-exome sequencing (WES) was performed in 316 participants (grouped into those with the best response [n=156] and those who had no response [n=160] to the antipsychotic medication prescribed), according to the total PANSS score reduction rate after 6 weeks of treatment. Validation was performed using targeted sequencing in an independent sample of 1920 patients. Data analyses was performed between March 15, 2016, and March 1, 2017. Main Outcomes and Measures Drug efficacy at week 6 was assessed according to the change in PANSS scores from baseline. Extremely good and extremely poor responders were selected for an initial WES association study, from which a subset of genes showing putative association was selected for independent replication with a targeted sequencing approach. Results Of the 3023 patients (1549 [51.24%] female and 1474 [48.8%] male; mean [SD] age, 31.2 [7.9] years), 2336 (77.3%) were eligible for genetic analysis. After quality-control exclusions, 316 patients (10.5%) were included for WES and 1920 (63.5%) were included for replication. In the WES discovery stage, 2 gene sets (reduced NMDA [N-methyl-D-aspartate]–mediated synaptic currents and reduced AMPA [α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid]–mediated synaptic currents) were found to be enriched with rare damaging variants in the nonresponder group, suggesting the involvement of these gene sets in antipsychotic medication efficacy. Reduced NMDA–mediated synaptic currents gene set was further replicated in an independent sample using targeting sequencing. No statistically significant differences in antipsychotic drug response were found among the patients who received different antipsychotic drugs. Conclusions and Relevance Genetic variation in glutamatergic or NMDA neurotransmission is implicated in short-term antipsychotic medication efficacy; WES may have utility in the study of rare genetic variation in pharmacogenetics. Trial Registration Chinese Clinical Trials Registry Identifier:ChiCTR-TRC-10000934

Objective. Motor imagery (MI) electroencephalography (EEG) classification is regarded as a promising technology for brain–computer interface (BCI) systems, which help people to communicate with the outside world using neural activities. However, decoding human intent accurately is a challenging task because of its small signal-to-noise ratio and non-stationary characteristics. Methods that directly extract features from raw EEG signals ignores key frequency domain information. One of the challenges in MI classification tasks is finding a way to supplement the frequency domain information ignored by the raw EEG signal. Approach. In this study, we fuse different models using their complementary characteristics to develop a multiscale space-time-frequency feature-guided multitask learning convolutional neural network (CNN) architecture. The proposed method consists of four modules: the space-time feature-based representation module, time-frequency feature-based representation module, multimodal fused feature-guided generation module, and classification module. The proposed framework is based on multitask learning. The four modules are trained using three tasks simultaneously and jointly optimized. Results. The proposed method is evaluated using three public challenge datasets. Through quantitative analysis, we demonstrate that our proposed method outperforms most state-of-the-art machine learning and deep learning techniques for EEG classification, thereby demonstrating the robustness and effectiveness of our method. Moreover, the proposed method is employed to realize control of robot based on EEG signal, verifying its feasibility in real-time applications. Significance. To the best of our knowledge, a deep CNN architecture that fuses different input cases, which have complementary characteristics, has not been applied to BCI tasks. Because of the interaction of the three tasks in the multitask learning architecture, our method can improve the generalization and accuracy of subject-dependent and subject-independent methods with limited annotated data.

Efficient recovery of coal liquids from direct coal liquefaction residue (DCLR) is beneficial for improving the economics of the direct coal liquefaction process. An attempt was made to evaluate the possibility of extracting coal liquids from DCLR using subcritical water (SBCW). The properties of water are compared with those of typical organic solvents. With regard to the ability of dissolving/emulsifying organic components, SBCW compares favorably with some typical organic solvents under certain conditions. This is evidenced by the fact that the SBCW3 (320 °C/11.7 MPa) extraction yield is similar to the n-hexane extraction yield, although the SBCW1 (250 °C/5.2 MPa) and SBCW2 (300 °C/8.9–11.6 MPa) extraction yields are lower than the n-hexane extraction yields under comparable conditions. The recovery rate of coal liquids from DCLR by SBCW3 extraction can be higher than the maximum recovery rate by n-hexane or methanol extraction when the (SBCW3/DCLR)mass is high enough. In comparison with n-hexane-extra...

Summary Background Antipsychotic drugs improve schizophrenia symptoms and reduce the frequency of relapse, but treatment response is highly variable. Little is known about the genetic factors associated with treatment response. We did a genome-wide association study of antipsychotic treatment response in patients with schizophrenia. Methods The discovery cohort comprised patients with schizophrenia from 32 psychiatric hospitals in China that are part of the Chinese Antipsychotics Pharmacogenomics Consortium. Patients who met inclusion criteria were randomly assigned (1:1:1:1:1:1) to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and haloperidol or perphenazine; those assigned to haloperidol or perphenazine were subsequently assigned [1:1] to one or the other) for 6 weeks. Antipsychotic response was quantified with percentage change on the Positive and Negative Syndrome Scale. Single-nucleotide polymorphisms (SNPs) were tested for their association with treatment response. Linkage-disequilibrium-independent SNPs that exhibited potential associations (ie, p −5 ) were tested in a validation cohort comprising patients from the Chinese Antipsychotics Pharmacogenetics Consortium from five collaborative hospitals, who were treated with olanzapine, risperidone, or aripiprazole for 8 weeks. Findings The discovery cohort contained 2413 patients and the validation cohort 1379 patients. In the discovery cohort, we identified three novel SNPs (rs72790443 in MEGF10 [p=1·37 × 10 −8 ], rs1471786 in SLC1A1 [p=1·77 × 10 −8 ], and rs9291547 in PCDH7 [p=4·48 × 10 −8 ]) that were associated with antipsychotic treatment response at a genome-wide significance level. These associations were confirmed in the validation cohort (p MEGF10 [p=1·40 × 10 −9 ], rs1471786 in SLC1A1 [p=2·33 × 10 −9 ], rs9291547 in PCDH7 [p=3·24 × 10 −9 ], rs12711680 in CNTNAP5 [p=2·12 × 10 −8 ], and rs6444970 in TNIK [p=4·85 × 10 −8 ]). In antipsychotic-specific groups, after the combination of results from both samples, the rs2239063 SNP in CACNA1C was associated with treatment response to olanzapine (p=1·10 × 10 −8 ), rs16921385 in SLC1A1 was associated with treatment response to risperidone (p=4·40 × 10 −8 ), and rs17022006 in CNTN4 was associated with treatment response to aripiprazole (p=2·58 × 10 −8 ). Interpretation We have identified genes related to synaptic function, neurotransmitter receptors, and schizophrenia risk that are associated with response to antipsychotics. These findings improve understanding of the mechanisms underlying treatment responses, and the identified biomarkers could eventually guide choice of antipsychotic in patients with schizophrenia. Funding National Key Technology R&D Program of China, National Natural Science Foundation of China.

Arrhythmia classification is crucial in electrocardiogram (ECG) based automatic cardiovascular disease diagnosis, e.g., to help prevent stroke or sudden cardiac death. However, the complex individual differences in ECG morphology make it challenging in accurately categorizing arrhythmia heartbeats. To promote robustness of the algorithm for individual differences, we propose a novel ECG arrhythmia classification method with stacked sparse auto-encoders (SSAEs) and a softmax regression (SF) model. The SSAEs is employed to hierarchically extract high-level features from huge amount of ECG data. Features are extracted automatically such that no individual difference in feature selection will bias extraction accuracy. Moreover, the input can be reconstructed completely by the features in each level of the auto-encoder. The SF is then trained to serve as a classifier for discriminating six different types of arrhythmia heartbeats. Computational experiments and comparative analyses are presented to validate the effectiveness of the theoretical models.

The aim of this study is to understand details about the sample size influence on the CH 4 and CO 2 sorption behaviors of coals. Two anthracites (YQ and QS) were selected, ground and sieved. Four size fractions (from powder size −0.354 mm to the lump size 4–10 mm) were tested. The manometric method was used to determine the CH 4 and CO 2 sorption isotherms and kinetics. The unipore diffusion model was selected for sorption kinetic modeling. Although the compositions of the different size fractions generally exhibit slight variations the isotherms with different sample basis (air-dried, ash-free or dry-ash-free) are not apparently different, except for the largest size YQ sample that contains significantly higher amounts of minerals. However, the “ash correction” or the “ash-moisture correction” made the sorption isotherm of the largest size YQ sample deviate from the main trend. The predicted effective diffusion coefficients of CH 4 and CO 2 for both coal samples increase, however, unexpectedly with the increase of the sample size. It is probably due to the differences in the mineral contents, the improper estimation of sample size, and the differences in pore structures.

Carbon dioxide sequestration in unmineable coalbeds combined with enhanced coalbed methane recovery is attracting attention as one of the possible methods for carbon capture and storage. Sorption a...

Mercury (Hg) is a volatile and toxic trace element in coal. Its emission to the environment can cause long-term contamination problems to human health and the environment. In this study, Hg in six Chinese coals from different ranks was characterized by temperature-programmed decomposition–atomic fluorescence spectroscopy (TPD–AFS) and acid-leaching techniques. The results show that TPD–AFS is an effective method to assist the characterization of Hg in coals. With the aid of acid leaching, the thermal behavior of the grouped Hg-containing components can be obtained. Generally, the content of organic-bound Hg is in the range of 16–36% and releases in the temperature range of 220–600 °C. The content of silicate-bound Hg is in the range of 10–26% and releases in the temperature range of >600 °C. The content of pyrite-bound Hg is in the range of 5–44% and releases in the temperature range of 250–630 °C. The content of HCl-soluble Hg is in the range of 10–34% and releases at the lower temperature range. The the...

The fluid transport phenomena were studied on a cleat-plug (with cleats) and a matrix-plug (cleat-free) of a Chinese coal under controlled confining stresses (10−40 MPa). The single-phase fluid flo...

To better understand the coal swelling kinetics in solvent, a kinetic model based on a pseudopolymolecular reaction is proposed to model the swelling data up to the quasi-equilibrium stage. The swelling isotherms of a Chinese sub-bituminous coal, named Coal-1, in carbon disulfide (CS 2 ), N-methyl-2-pyrrolidinone (NMP), and CS 2 /NMP mixtures with the different volumetric mixing ratios at various temperatures were obtained by a so-called linear variable differential transformer (LVDT) deformation transducer, continually. The corresponding kinetic parameters, including the rate constants, order of the pseudopolymolecular reaction, apparent activation energy, and pre-exponential factor, were obtained with the coefficients of determination, R 2 , range between 0.851 and 0.999. The kinetic parameters obtained with obvious meanings which are useful for better understanding the mechanism of the coal swelling in solvent as well as the structure of coal. The apparent activation energy for Coal-1 swelling in CS 2 is 8.9 kJ/mol, which corresponds to the dissociation energy barrier of van der Waals forces. It is less than that for Coal-1 swelling in NMP, 40.9 kJ/mol, which corresponds to the dissociation energy barrier of hydrogen bonds. It implies that the dissociation of the noncovalent bonds in coal is crucially important during coal swelling in solvent. The CS 2 in the test system appeared as "catalyst", accelerating the swelling rate by lowering the energy barrier.

The operation and numerical simulation of CO2-ECBM processes requires a thorough understanding of the fluid conductivity properties of the coal matrix. Therefore, single phase (water) and two-phase (water and gas) fluid flow tests on a cylindrical anthracite coal matrix plug of 28.5 mm in diameter and about 20 mm in length were conducted in a triaxial flow cell at a confining pressure and axial load of 20 MPa. The absolute permeability coefficient, determined by single phase steady-state water flow tests, was about 2.0 ∙ 10− 20 m2 (20 nDarcy). Two-phase flow tests ("gas breakthrough tests") were performed by imposing high differential gas pressures (up to 7 MPa) on the water-saturated sample and monitoring the pressure changes over time in closed upstream and downstream reservoirs. Argon (Ar), methane (CH4) and carbon dioxide (CO2) showed significant differences in their pressure transient curves during gas breakthrough tests, which indicated different controlling processes. The inert gas Ar exhibited capillary pressure-controlled breakthrough behavior. The maximum effective permeability, measured after gas breakthrough at maximum gas saturation, was 1.8 ∙ 10− 21 m2 (1.8 nDarcy); a residual pressure difference referred to as the “capillary threshold pressure” was 0.9 MPa for the Ar–water–coal system. The sorbing gas CH4 exhibited solely diffusion-controlled transport behavior, and no indications of capillary pressure effects. The reactive and sorbing gas CO2 showed initially capillary pressure-controlled and subsequently diffusion-controlled breakthrough behavior. The mass balance of the gas breakthrough tests indicated that the bulk of CO2 and CH4 were taken up by the coal sample. Sorption accounted for the strong uptake of CH4 by the coal sample, whereas both sorption and, to a lesser extent, CO2–water–mineral reactions were inferred for CO2.

Direct coal liquefaction residue (DCLR) is, commonly, designed to be used as a feed stock for gasification or combustion. Use of DCLR as a value added product is very important for improving overall economy of direct coal liquefaction processes. This study shows that the DCLR may be used as a pavement asphalt modifier. The modification ability is similar to that of Trinidad Lake Asphalt (TLA), a superior commercial modifier. Asphalts modified by two DCLRs meet the specifications of ASTM D5710 and BSI BS-3690 designated for the TLA-modified asphalts. The required addition amount for the DCLRs tested is less than that for TLA due possibly to the high content of asphaltene in DCLRs. Different compatibility was observed for the asphalts with the same penetration grade but from the different origin. Different components in the DCLR play different roles in the modification. Positive synergetic effects among the fractions were observed, which may due to the formation of the stable colloid structure. Unlike polymer-type modifier, the structure of asphalt-type modifier has a similarity with petroleum asphalts which favors the formation of a stable dispersed polar fluid (DPF) colloid structure and improves the performance of pavement asphalt. 12 refs., 1 fig., 6 tabs.

Mercury (Hg) is a toxic and ubiquitous trace element in coal. Monitoring its release behavior during coal processing is a challenging problem. This paper presents a method that is capable of online measurement of the dynamic release behavior of elemental Hg (Hg0) from thermal decomposition of coal. The method couples a temperature-programmed decomposition unit with an atomic fluorescence spectrometry detector (TPD-AFS). The AFS signal can be converted to Hg content for quantitative analysis through calibration. The main advantage of the TPD-AFS system is that it can provide either real-time or accumulated data. It was confirmed that the amount of Hg0 determined by this method agreed well with that by the Ontario-Hydro method, and the results are reproducible with a high accuracy. The method can be used to characterize the release behavior of Hg in coals upon heating and may be used to identify the forms of occurrence of Hg in coals.

For hydrogenation of heavy liquids in direct coal liquefaction residue (DCLR) within the direct coal liquefaction (DCL) process, heavy liquids in a DCLR derived from a bench-scale Shenhua DCL process using Shenhua coal are evaluated under two conditions. One simulates the coal liquefaction conditions of the Shenhua plant in the presence of a Fe-based Shenhua catalyst; the other one simulates the online hydrotreating conditions in the presence of a NiMo/Al2O3 catalyst. The results show that the heavy liquids of DCLR can be hydrogenated under these two conditions yielding less heavy products; hydrogenating the heavy liquids under the online hydrotreating conditions is more effective than that under the coal liquefaction conditions; the preasphaltene fraction is a main problem that yields non-soluble materials under these hydrogenation conditions. The results suggest that hydrogenation of toluene soluble and tetrahydrofuran soluble fractions of the DCLR under the coal liquefaction and online hydrotreating conditions is feasible, but their conversion to lighter products are inapparent under the coal liquefaction conditions, and elimination of the formation of tetrahydrofuran insoluble fraction in the online hydrotreator should be considered.

Forms of arsenic in a Chinese bituminous coal, Yima, and their transformation behaviors during coal pyrolysis were investigated. The chemical leaching method was used to characterize the forms of a...

The mercury release behavior during thermal decomposition of three Chinese coals with different types was studied under nitrogen, carbon dioxide and air at temperatures of 800, 900, 1,000 and 1,100 °C. The thermal treatment experiments were carried out in a quartz tube reactor. Results showed that the release ratio of total mercury during thermal decomposition of coals increases with the increasing temperature. The order of the amount of mercury released under the three atmospheres is nitrogen carbon dioxide>air for all three coals. The release behavior of the total mercury under air is independent of the coal type. Under the other two atmospheres the release behavior is distinguished by the coal type.

Breast carcinoma is the most common malignancy in Chinese women. The purpose of this study is to evaluate the predictive value of serum anti-p53 antibodies (p53 Abs), carcino-embryonic antigen (CEA), carbohydrate antigen (CA) 15-3, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER)-2 in taxane-based and anthracycline-based neoadjuvant chemotherapy (NAC). Sixty-eight patients with locally advanced breast carcinoma were included. Thirty-two were treated with taxane (the taxane group) and 36 with anthracycline (the anthracycline group). The standard dosage of docetaxel was 100 mg/m2 (day 1) and those of cyclophosphamide, adriamycin and 5-flurouracil were 500 mg/m2 (day 1-8), 40 mg/m2 (day 1) and 500 mg/m2 (day 1-8), respectively. The p53 Abs were detected by enzyme-linked immunosorbent assay; CEA and CA15-3 were detected by Elecsys 2010 Disc System; ER, PR and HER-2 were detected by immunohistochemistry staining. The biomarkers p53 Abs, CEA and CA15-3 were detected in serum samples, and the immunohistochemistry staining for ER, PR and HER-2 was performed in tumor samples before and after NAC. The expression of p53 Abs was significantly reduced by taxane (P = 0.006). The serum CEA and CA15-3 levels were significantly affected by both taxane (P = 0.004 and P = 0.008) and anthracycline (P = 0.002 and P = 0.000) drugs. HER-2-negative status (pre-neoadjuvant) was correlated with a high objective response rate (OR) in both taxane-based and anthracycline-based chemotherapy (P = 0.022 and P = 0.025), whereas p53 Ab-negative status (pre-neoadjuvant) was correlated with high OR rate in anthracycline-based chemotherapy (P = 0.039). This study shows that the serum p53 Ab level is easily changed by taxane. CEA and CA15-3 levels are easily changed by taxane and anthracycline. The p53 Ab-negative patients may predict a high clinical OR rate in anthracycline-based NAC. HER-2-negative may predict a high OR in both taxane-based and anthracycline-based NAC.

Direct coal liquefaction residue (DCLR) contains a significant fraction of heavy liquids. Better use of DCLR is an important task to overall economy of direct coal liquefaction. This paper studies hydro-treatment of a DCLR and its solvent-extraction components under typical direct coal liquefaction conditions. The DCLR is found hydro-treatable, resulting in more light products and less heavy products. In one case, 40 wt% heavy fractions in the DCLR are converted into light fractions. Hexane soluble fraction (HS) is the most stable while pre-asphaltene fraction (PA) is the most active during the hydro-treatment. Some synergetic effect can be observed when DCLR is treated as whole. The fractions of DCLR, before and after the hydro-treatment, are subjected to FTIR and NMR analyses, which show increase in hydrogen content and decrease in oxygen content in HS fractions after the hydro-treatment. GPC analysis reveals that the hydro-treatment results in slight decreases in molecular weight of HS fraction. The data seem to suggest that separation and hydro-treatment of liquid fractions from a DCLR is a viable option for high oil yield.

Activated carbon honeycomb (ACH) monoliths were prepared by extruding of a mixture of bituminous coal and organic additives and subsequent carbonization and steam activation. Preparation parameters that were varied were carbonization temperature and activation time. The carbonization conditions were 500, 650 and 800 °C for 1 h and the steam activation conditions were 850 °C for 2, 4 and 6 h. The monoliths at various states were characterized by SEM, XRD, nitrogen adsorption and compression test. It was found that carbonization temperature has significant effects on pore size distribution and mechanical strength of ACH monoliths. The ACH monoliths prepared from high carbonization temperatures exhibited lower values of the BET surface area and total pore volume and higher value of the mechanical strength than those of the ACH monoliths prepared from low carbonization temperatures. This was attributed to the effect of high temperature carbonization that results in the formation of relatively less defective structures.

A systematic study was made on the identification and quantitative determination of polynuclear aromatic hydrocarbons (PAHs) in heavy products derived from coal and petroleum with high performance liquid chromatography (HPLC). After the separation of PAHs by a high-resolution column, identification was made through four methods: (1) the relative retention time (RRT) method, (2) the stop-flow-UV scanning method, (3) the method of fluorescence characteristic index Φ′ and (4) the method of V′ index at different UV wavelengths. For the quantitative determination of the components, methods of external standard (E-X), internal standard (I-N) and external standard-response factors (E-F) were compared. The E-F method was recommended by the present paper. For the determination of quantitative response factors (F) two methods were studied, including the HPLC peak-area method (Peak-area method) and the UV absorbance method using a UV spectrometer (absorbance method). The absorbance method was better and is recommended by the present paper. The F values of 30 PAHs from the two different methods are given. The samples analyzed include a coal tar pitch, a thermal cracking residue oil and a residual oil from ethylene production.

Premature ventricular contraction (PVC) is one of the most serious arrhythmias. Without early diagnosis and proper treatment, PVC can result in significant complications. In this paper, a novel feature extraction method based on a sparse auto-encoder (SAE) and softmax regression (SR) classifier was used to differentiate PVCs from other common Non-PVC rhythms, including normal sinus (N), left bundle branch block (LBBB), right bundle branch block (RBBB), atrial premature contraction (APC), and paced beat (PB) rhythms. The proposed method was analyzed using 40 ECG records obtained from the MIT-BIH Arrhythmia Database. The proposed method exhibited an overall accuracy of 99.4%, with a PVC recognition sensitivity and positive predictability of 97.9% and 91.8%, respectively.

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.

Because of ineffective management, it appears schedule delay, materials supply not in time, cost overruns, human resource management confusion, security management and quality management activities carried out in disorder during the process of wind turbines service projects at this time. The paper designs an advanced service project management system based on ODPS platform which can be integrated with other systems in order to standardize the management of wind turbines service project management, realize the scientific process of information and automation, and enhance the competitiveness of wind turbines service enterprises. KEYWORD: ODPS Platform; Wind Turbine; Service Project Management System

Release behaviors of fluorine and chlorine during thermal treatments of two Chinese coals, DT and JC, were studied in a quartz tube reactor. The thermal treatments included temperature programmed decomposition (TPD, 300-1000 degrees C) in N2 and gasification (800-1100 degrees C) under a H2O or CO2 atmosphere. The TPD results show that F and Cl in the two coals can be classified into three forms of occurrence, evolving in three temperature ranges, 150350 degrees C, 350-750 dgrees C, and870 degrees C. Fluorine in the coals is significantly more stable than Cl during the TPD process. Both elements in DT coal are more volatile than that in JC coal, which may be attributed to coexisting F or Cl salts with minerals in JC coal. Gasification under a H2O or CO2 atmosphere may promote the release of F and CI. The promotion effect is more significant in a H2O steam, which is due possibly to reactions of H2O with F and Cl salts in the coals. For both coals, the release ratios are close to 94% for F and 98% for Cl at 1000 degrees C in a H2O steam. Under these conditions, the difference in release ability of F and Cl from the two coals diminishes. No clear correlation can be found between the release ratio of F or Cl with the corresponding volatile yield of the coals.

Dynamic behaviors of gaseous sulfur-containing compounds evolved from pyrolysis of six Chinese coals were studied in the temperature range of up to 800°C under N2 and H2. The released amount of total sulfur-containing gases was traced by an online flame photometric detector (FPD). Simultaneously, the changes of different sulfur forms, including H2S, SO2, COS and CS2, also were investigated using an online mass spectrometer (MS). FPD results show that the effect of H2 on gaseous sulfur evolved is complex, which promoted certain peak and suppresses other peaks. Based on the data from MS, it is suggested that a series of competitive reactions between active sulfur and other active matters during pyrolysis may impact on the sulfur form in gas phase. Interactions between active sulfur-containing intermediates and the coal matrix are attributed to be the main factor determining the dynamic behavior.

Trinidad lake asphalt (TLA) is regarded as a high quality paving asphalt modifier for better road performance and has been used in many countries. However, the high price limits its application to only heavy load surfaces. A co-processing process of fluidized catalytic cracking slurry with coal was developed to produce heavy product (named CS) with asphalt modification ability similar to that of TLA. As a typical example, CS-modified asphalt with CS to base asphalt ratio of 20/80 meets the specifications of ASTM D5710 and BS 3690 for TLA-modified asphalt. The properties of CS-modified asphalt concrete are similar to that of TLA-modified asphalt concrete and satisfy the specifications of JTJ 036-98. Depended on the co-processing conditions used, the yields of the modifier are in the range of 65–80%, with softening point of 90–180 °C and penetration value of 0–8 (1/10 mm) at 25 °C. Asphaltenes content in CS is about 20–70 wt.%, preasphaltenes about 5–30 wt.%, and organic residues bout 5–60 wt.%. Hydrogen content and hydrogen distribution of CS vary with the co-processing conditions. The atomic ratio of H/C of CS is lower than that of TLA.

To simulate coal-like environment, five organic sulfur compounds, representing some of the organic sulfur structures in coal, were impregnated on a charcoal and subjected to pyrolysis in N 2 . The pyrolysis was carried out in a temperature-programmed reactor at a heating rate of 5 °C min −1 up to 800 °C. The gases released (including H 2 S, COS, SO 2 , CS 2 and the main hydrocarbons) from the pyrolysis were analyzed by an on-line mass spectrometer (MS). It is found that the behavior of sulfur-containing compounds evolved into the gas phase depends on the structure of the compounds as well as on the functional groups on the charcoal. Sulfur radical is likely to be the main intermediate sulfur form which has strong interactions with the charcoal to form H 2 S, COS, SO 2 and CS 2 , and stable non-volatile sulfur compounds which crack at higher temperatures to form also H 2 S, COS, SO 2 and CS 2 . The carbon in COS and CS 2 are likely to come from the charcoal, and the oxygen in COS, SO 2 have close relation with the evolution of CO and CO 2 , respectively. Dibenzothiophene is stable under the conditions employed.

The forms and pyrolysis behavior of arsenic in three Chinese coals was studied. The arsenic in the coals and the coal-derived pyrolysis chars were characterized into five forms using a sequential extraction method where a series of solutions with increasing acidity and oxidizability were used. The five arsenic forms are named as ion exchangeable, bound to carbonates, bound to Fe–Mn oxides, bound to organic matter and remained in residue. XRD, SEM-EDX and TOF-SIMS techniques were also used to characterize the coals and the chars. Results show that bleeding ratio of arsenic in the three coals increases with increasing pyrolysis temperature. The type of coal and the arsenic distribution in the coal have significant effect on the pyrolysis behavior of arsenic. The different volatility of arsenic was attributed to its chemical stability and thermal stability. Ion exchangeable arsenic and the arsenic bound to carbonates are not present in the three coals. Other arsenic forms undergo transformation during the pyrolysis, from the solid phase to the vapor phase and from one chemical form to other chemical forms. The main arsenic remained in the residue may include resistant sulfides.

A flame ionization detector (FID) and a flame photometric detector (FPD) with a sulfur filter are coupled with a fixed-bed micro-reactor for temperature-programmed decomposition (TPD), TPD-FPD&FID, to allow simultaneously analysis of gaseous sulfur compounds and gaseous hydrocarbons released during pyrolysis of coals. As an example, a Chinese bituminous coal is used. Detailed experimental and quantification procedures are discussed. The results, mass of gaseous sulfur compounds and mass of gaseous hydrocarbons released as functions of pyrolysis temperature, can be used to analyze pyrolysis behavior and characteristics of sulfur and organic matrix in the coal. The results show that the method is reproducible with high accuracy in a wide range of experimental conditions, and the total amounts of sulfur determined by the FPD measurements are highly comparable to that obtained using a standard wet chemistry method.

Release behavior and chemical form distribution of As, Pb, Cr, Cd and Mn in Datong coal during pyrolysis was studied in a simulated drop-tube reactor at a heating rate of about 1000 °C/s, including effects of temperature (300–1000 °C), atmosphere (N 2 and H 2 ), and holding time (0.3–10 min). Results show that the bleeding ratios of As, Pb, Cr, Cd and Mn increase with increasing pyrolysis temperature and holding time. Reductive environment results in higher emission of the elements. Among the five trace elements, As, Pb and Cd show similar behavior with volatilities higher than that of Cr and Mn at 1000 °C. The five trace elements in the coal and coal-derived chars are separated into five fractions through an extraction procedure. Ion exchangeable form of the elements is not found in the coal and the chars, and the elements remained in the residue fraction is the most dominant occurrence form in the coal and the chars for As, Pb, Cd and Cr. All the forms for all the elements undergo transformation in the pyrolysis resulting in reduced content in the chars.

Chlorine emission from Datong bituminous coal of China during fast heat treatments was reported. The heat treatment experiments were carried out in a closed simulated dropping tube reactor (∼1000 °C s−1). Effects of temperature (300–700 °C), N2 pressure (0.1–4 MPa), and heating time under N2 atmosphere on chlorine release were studied. Influence of atmosphere (N2 and H2) was also investigated. Results show that the bleeding ratio of chlorine increases with increases in heating temperature and time. High N2 pressure restrains chlorine emission. H2 environment promotes chlorine emission. The data implies that secondary reactions may play an important role in chlorine release and reducing environment is beneficial for chlorine release.