Process and mechanism of preparing metallized blast furnace burden from metallurgical dust and sludge.

Metallurgical dust and sludge are solid waste resources with recycling value. In recent years, rotary hearth furnace has become the most important means to treat metallurgical dust and sludge because of its wide range of raw materials and strong treatment capacity. In this study blast furnace ash and converter sludge were selected as the research objects, and high-quality metallized pellets were prepared based on the rotary hearth furnace process. The strength changed of pellets, the reduction process of iron oxides and the removal process of zinc during the roasting of pellets in rotary hearth furnace were studied. To explore the reasonable roasting condition for preparing metallized pellets in rotary hearth furnace. The optimum roasting temperature of the pellets was 1250℃ and the roasting time was 25 min. The compressive strength, metallization rate and dezincification rate of metallized pellets reached 1361N, 97.44% and 95.67%, respectively. The efficient resource utilization of various metallurgical dust and sludge is realized.

Kinetics of Reduction in Stages of Pellets Prepared from the Bayan Obo Iron Ore Concentrate.

To explore the reduction swelling process of pellets prepared from the Bayan Obo iron ore concentrate, based on the iron oxide reduction theory of pellets, the reduction of pellets prepared from the Bayan Obo iron ore concentrate was analyzed by thermogravimetric experiments and kinetic calculations in three stages. The reason for the abnormal swelling of pellets prepared from the Bayan Obo iron ore concentrate was analyzed from the perspective of kinetics. The research results showed that carbon deposition occurred in the first stage of reduction. The second stage of reduction was controlled by an interfacial chemical reaction, and the activation energy of the reaction was 117.99 kJ/mol. The reaction energy barrier was higher and the reaction rate was slower, and therefore, the reduction swelling rate of pellets was lower at this stage. The third stage of reduction was controlled by internal diffusion, and the reaction activation energy was 15.9 kJ/mol. The reduction reaction of pellets occurs violently, and the reduction swelling behavior was remarkable at this stage.

Research on the Ash Melting Characteristics of Blended Coal Based on DFT Calculations.

Low-ash-melting-point bituminous coal and high-ash-melting-point anthracite coal are mixed and burned in different proportions. The ash melting characteristics of blended coal were determined experimentally. At the same time, the ash samples of bituminous coal, anthracite, and blended coal were analyzed by X-ray diffraction (XRD), and the ash melting characteristic improvement mechanism of blended coal was analyzed by quantum chemical calculations. The results show that when high-ash-melting-point anthracite is added, the ash melting characteristics of blended coal are improved, and the deformation temperature, softening temperature, hemispheric temperature, and flow temperature of the blended coal are significantly increased. The melting point of blended coal ash with a bituminous coal ratio of less than 50% can meet the requirements of blast furnace injection. The reason for the improved melting characteristics of the blended coal ash is that mullite in anthracite ash reacts with gehlenite in bituminous coal ash during the combustion process to produce anorthite.

Computerized Tomography Image Feature under Convolutional Neural Network Algorithm Evaluated for Therapeutic Effect of Clarithromycin Combined with Salmeterol/Fluticasone on Chronic Obstructive Pulmonary Disease.

This study was to explore the use of convolutional neural network (CNN) for the classification and recognition of computerized tomography (CT) images of chronic obstructive pulmonary disease (COPD) and the therapeutic effect of clarithromycin combined with salmeterol/fluticasone. First, the clinical data of COPD patients treated in hospital from September 2018 to December 2020 were collected, and CT and X-ray images were also collected. CT-CNN and X ray-CNN single modal models were constructed based on the LeNet-5 model. The randomized fusion algorithm was introduced to construct a fused CNN model for the diagnosis of COPD patients, and the recognition effect of the model was verified. Subsequently, the three-dimensional reconstruction of the patient's bronchus was performed using the classified CT images, and the changes of CT quantitative parameters in COPD patients were compared and analyzed. Finally, COPD patients were treated with salmeterol/fluticasone (COPD-C) and combined with clarithromycin (COPD-T). In addition, the differences between patients' lung function indexes, blood gas indexes, St. George respiratory questionnaire (SGRQ) scores, and the number of acute exacerbations (AECOPD) before and after treatment were evaluated. The results showed that the randomized fusion model under different iteration times and batch sizes always had the highest recognition rate, sensitivity, and specificity compared to the two single modal CNN models, but it also had longer training time. After CT images were used to quantitatively evaluate the changes of the patient's bronchus, it was found that the area of the upper and lower lung lobes of the affected side of COPD patients and the ratio of the area of the tube wall to the bronchus were significantly changed. The lung function, blood gas index, and SGRQ score of COPD-T patients were significantly improved compared with the COPD-C group (P < 0.05), but there was no considerable difference in AECOPD (P > 0.05). In summary, the randomized fusion-based CNN model can improve the recognition rate of COPD, and salmeterol/fluticasone combined with clarithromycin therapy can significantly improve the clinical treatment effect of COPD patients.

Spatial and temporal variations of the diatom communities in megacity streams and its implications for biological monitoring.

Diatoms have been proven to be good indicators of natural stream conditions, but little is known about the seasonal variability of diatom communities in megacity streams. We investigated the spatial and temporal variation of diatom communities along an urban-to-rural gradient in megacity streams, Beijing, China. We found that the composition and diversity of diatom community was significantly different along the urban-to-rural gradient in streams of Beijing city. The diatom community was subtle temporal variation in the reference stream and urban upstream, but the temporal variation of diatoms was relatively greater in the urban downstream. Overall, the composition of the diatom community was relatively stable in the streams among different seasons, and the dominant species did not change much over seasons. For example, during the sampling periods, the species Achnanthidium minutissimum in reference streams had the average relative abundance of 20.3 ± 3.5%; the species Pseudostaurosira brevistriata and Staurosira construens var. venter in urban upstream had average relative abundances of 17.0% ± 0.9% and 17.3% ± 1.2%, respectively; and the species Nitzschia palea in urban downstream had average relative abundances of 18.8 ± 4.7%. There were significant correlations between the relative abundances of the dominant species and environmental variables, suggesting that the environmental variables had significant effects on the diatom distribution. Our results demonstrate that the diatom communities are relatively stable among seasons in different sampling areas, suggesting that diatoms can be used as reliable indicators for the biological monitoring of water quality in megacity streams across seasons.

An enriched granger causal model allowing variable static anatomical constraints.

The anatomical connectivity constrains but does not fully determine functional connectivity, especially when one explores into the dynamics over the course of a trial. Therefore, an enriched granger causal model (GCM) integrated with anatomical prior information is proposed in this study, to describe the dynamic effective connectivity to distinguish the depression and explore the pathogenesis of depression. In the proposed frame, the anatomical information was converted via an optimized transformation model, which was then integrated into the normal GCM by variational bayesian model. Magnetoencephalography (MEG) signals and diffusion tensor imaging (DTI) of 24 depressive patients and 24 matched controls were utilized for performance comparison. Together with the sliding windowed MEG signals under sad facial stimuli, the enriched GCM was applied to calculate the regional-pair dynamic effective connectivity, which were repeatedly sifted via feature selection and fed into different classifiers. From the aspects of model errors and recognition accuracy rates, results supported the superiority of the enriched GCM with anatomical priors over the normal GCM. For the effective connectivity with anatomical priors, the best subject discrimination accuracy of SVM was 85.42% (the sensitivity was 87.50% and the specificity was 83.33%). Furthermore, discriminative feature analysis suggested that the enriched GCM that detect the variable anatomical constraint on function could better detect more stringent and less dynamic brain function in depression. The proposed approach is valuable in dynamic functional dysfunction exploration in depression and could be useful for depression recognition.

Correlation of interleukin-33 with Th cytokines and clinical severity of dry eye disease.

PURPOSE: The purpose of this study is to determine the tear and serum protein levels of interleukin-33 (IL-33) and its correlation with Th cytokines and disease severity in dry eye (DE) syndrome. METHODS: Tear and serum samples were collected from 30 healthy volunteers, 30 DE patients with non-Sjogren's syndrome DE (NSSDE) and 30 DE patients with primary SSDE. The eight most frequent symptoms of DE were scored. All patients underwent corneal and conjunctival staining, tear film breakup time (TBUT), and Schirmer I test. The serum and tear levels of IL-33 were measured by enzyme-linked immunosorbent assay. The levels of IL-33 expression and its correlation with Th cytokines and disease severity were also analyzed. RESULTS: We found that symptom scores and corneal staining grade were significantly higher in SSDE group compared with NSSDE and control group, whereas the results of TBUT and Schirmer I test were significantly lower in SSDE group compared with NSSDE and control group. The tear levels of IL-33 were significantly increased in tears of SSDE patients compared with those of controls and NSSDE patients (P < 0.05). Moreover, the elevated tear levels of IL-33 were positively correlated with symptom scores but negatively correlated with tear film breakup time and Schirmer I test in both NSSDE and SSDE patients (P < 0.05). The tear levels of IL-33 of both NSSDE and SSDE patients were also positively correlated with tear levels of IL-4 and IL-5 (P < 0.05). Correlation between the serum levels of IL-33 with Th1/17/Treg cytokines was not found. CONCLUSION: Elevated tear levels of IL-33 were associated with the Th2 cytokines and disease severity of DE. Therefore, IL-33 may have important roles in the immunopathogenesis of the DE.

Effects of magnesium isoglycyrrhizinate on AST, ALT, and serum levels of Th1 cytokines in patients with allo-HSCT.

This study aimed to investigate the protective effects of magnesium isoglycyrrhizinate (MGL) on aspartate aminotransferase (AST), alanine aminotransferase (ALT), and serum levels of T helper 1 (Th1) cytokines in patients with allogeneic hematopoietic stem cell transplantation (allo-HSCT). The study included 42 patients prepared for allo-HSCT, who were divided equally into MGL and reduced glutathione groups. The ALT and AST levels were detected 1day before pretreatment and transplantation, and 7, 14, and 21days after transplantation. The total days and times of fever, treatment time of patients in the laminar flow room, white blood cell (WBC) count, platelet (PTL) implantation time, and success rate of transplantation were recorded. The serum levels of Th1/Th2 cytokines were detected. MGL had a significant protective effect on AST 1day before transplantation and 7, 14, and 21days after transplantation, while ALT had a statistical difference only 7days after transplantation. MGL could shorten the duration of fever during transplantation and advance the WBC and PTL implantation time. Significant differences in Th1-like cytokines (P<0.05) and higher levels of Th2-like cytokines but with no statistical significance (P>0.05) were found in the MGL group compared with the control group. MGL had significant protective effects on AST after transplantation. MGL could reduce the duration of fever during transplantation, help the reconstruction and recovery of WBCs and PTLs, and regulate Th1 cytokines, revealing its protective effects on hepatic transaminases and graft versus host disease in allo-HSCT patients.

Boosting Up Performance of Inverted Photovoltaic Cells from Bis(alkylthien-2-yl)dithieno[2,3-d:2',3'-d']benzo[1,2-b:4',5'-b']di thiophene-Based Copolymers by Advantageous Vertical Phase Separation.

The photovoltaic cells (PVCs) from conjugated copolymers of PDTBDT-BT and PDTBDT-FBT with 5,10-bis(4,5-didecylthien-2-yl)dithieno[2,3-d:2',3'-d']benzo[1,2-b:4,5-b']dithiophene as electron donor moieties and benzothiadiazole and/or 5,6-difluorobenzothiadiazole as electron acceptor moieties are optimized by employing alcohol-soluble PFN (poly(9,9-bis(3'-(N,N-dimethylamino)propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene)) as cathode modification interlayer. The power conversion efficiencies (PCEs) of inverted PVCs (i-PVCs) from PDTBDT-BT and PDTBDT-FBT with devices configuration as ITO/PFN/active layer/MoO3/Ag are increased from 4.97% to 8.54% and 5.92% to 8.74%, in contrast to those for the regular PVCs (r-PVCs) with devices configuration as ITO/PEDOT:PSS/active layer/Ca/Al under 100 mW/cm2 AM 1.5 illumination. The optical modeling calculations and X-ray photoelectron spectroscopy (XPS) investigations reveal that the r-PVCs and i-PVCs from the copolymers exhibit similar light harvesting characteristics, and the enhancements of the PCEs of the i-PVCs from the copolymers are mainly contributed to the favorable vertical phase separation as the strongly polymer-enriched top surface layers and slightly PC71BM (phenyl-C71-butyric acid methyl ester)-enriched bottom surface layers are correspondingly connected to the anodes and cathodes of the i-PVCs, while they are opposite in the r-PVCs. As we known, it is the first time to experimentally verify that the i-PVCs with alcohol-soluble conjugated polymers cathode modification layers enjoy favorable vertical phase separation.

Fucoidan inhibits angiogenesis induced by multiple myeloma cells.

Multiple myeloma (MM) remains an incurable hematological neoplasms. Our previous studies showed that Fucoidan possessed anti-myeloma effect by inducing apoptosis and inhibiting invasion of myeloma cells. In this study, we evaluated the effect of Fucoidan on angiogenesis induced by human myeloma cells and elucidated its possible mechanisms. Multiple myeloma cells were treated with Fucoidan at different concentrations, then the conditioned medium (CM) was collected. The levels of VEGF in the CM were tested by ELISA. The results showed that Fucoidan significantly decreased VEGF secretion by RPMI-8226 and U266 cells. The tube formation assay and migration test on human umbilical vein endothelial cells (HUVECs) were used to examine the effect of Fucoidan on angiogenesis induced by human myeloma cells. The results showed that Fucoidan decreased HUVECs formed tube structures and inhibited HUVECs migration, and suppressed the angiogenic ability of multiple myeloma RPMI-8226 and U266 cells in a dose-dependent manner. The study also showed that Fucoidan downregulated the expression of several kinds of proteins, which may be correlated with the reduction of angiogenesis induced by myeloma cells. Moreover, results were compared from normoxic and hypoxic conditions, they showed that Fucoidan had anti-angiogenic activity. Furthermore, in a multiple myeloma xenograft mouse model, it indicated that Fucoidan negatively affected tumor growth and angiogenesis in vivo. In conclusion, our results demonstrate that Fucoidan was able to interfere with angiogenesis of multiple myeloma cells both in vitro and in vivo and may have a substantial potential in the treatment of MM.

Recent Advances in Organic Photovoltaics: Device Structure and Optical Engineering Optimization on the Nanoscale.

Organic photovoltaic (OPV) devices, which can directly convert absorbed sunlight to electricity, are stacked thin films of tens to hundreds of nanometers. They have emerged as a promising candidate for affordable, clean, and renewable energy. In the past few years, a rapid increase has been seen in the power conversion efficiency of OPV devices toward 10% and above, through comprehensive optimizations via novel photoactive donor and acceptor materials, control of thin-film morphology on the nanoscale, device structure developments, and interfacial and optical engineering. The intrinsic problems of short exciton diffusion length and low carrier mobility in organic semiconductors creates a challenge for OPV designs for achieving optically thick and electrically thin device structures to achieve sufficient light absorption and efficient electron/hole extraction. Recent advances in the field of OPV devices are reviewed, with a focus on the progress in device architecture and optical engineering approaches that lead to improved electrical and optical characteristics in OPV devices. Successful strategies are highlighted for light wave distribution, modulation, and absorption promotion inside the active layer of OPV devices by incorporating periodic nanopatterns/nanostructures or incorporating metallic nanomaterials and nanostructures.

Design and photovoltaic characterization of dithieno[3,2-b:2',3'-d]silole copolymers with positioning phenyl groups.

A two-dimensional (2D) low bandgap polymer () based on dithieno[3,2-b:2',3'-d]silole (DTS) with phenyl substitution on the bridging silicon atom and thiazolo[5,4-d]thiazole (TTz) was designed and synthesized for photovoltaic applications. The impact of conjugated side chains on the optical, electrochemical and energy levels of the polymer was studied. The phenyl substituted DTS polymer exhibited a 0.16 eV down-shifted highest occupied molecular orbital (HOMO) energy level and ca. 0.1 eV narrowed bandgap in comparison to the corresponding polymers with alkyl substitution on the silicon bridge. The influence of the blend weight ratio, the PFN layer, mixed solvent, THF exposure and polar solvent treatment and thermal annealing on the performance of :PC71BM devices was studied. : PC71BM (1 : 1, weight ratio) devices delivered the highest power conversion efficiency of 2.14% by using the PFN layer and THF annealing. Thermal annealing was found to exert a negative effect on the device performance. The morphology evolution of blend films processed with different solvents explained the difference in device performance. The results indicate that phenyl substitution is an effective way to tune the HOMO and bandgap of polymer donors for enhanced photovoltaic performance with the as-demonstrated 2D-conjugated DTS structure.

Abnormal brain anatomical topological organization of the cognitive-emotional and the frontoparietal circuitry in major depressive disorder.

PURPOSE: Despite the increasing understanding of major depressive disorder (MDD) using neuroimaging techniques, the topological organization of anatomical networks underlying MDD remains unclear. METHODS: The topological organization of brain anatomical networks was explored using complex network approaches. Diffusion tensor image data of 29 MDD patients and 30 healthy controls were collected. Network metrics such as strength, efficiency, and centrality were computed after the construction of brain anatomical networks. Between-group differences and correlations with clinical measurements were further explored. RESULTS: Compared with the healthy controls, MDD patients exhibited widely damaged information interactions in both cognitive-emotional circuitry and frontoparietal circuitry. Moreover, the centralities in the right prefrontal cortex involving the right middle frontal gyrus and the right gyrus rectus were negatively correlated with the duration of disease. Additionally, the centrality in the right inferior frontal gyrus (triangular part) and the efficiency in the right superior frontal gyrus (orbital part) were both positively related to the depression severity. CONCLUSION: These findings suggest that altered connectivity involved in affective and cognitive processing procedures might contribute to the pathogenesis of MDD.

Predicting depression based on dynamic regional connectivity: a windowed Granger causality analysis of MEG recordings.

Abnormal inter-regional causalities can be mapped for the objective diagnosis of various diseases. These inter-regional connectivities are usually calculated over an entire scan and used to characterize the stationary strength of the connections. However, the connectivity within networks may undergo substantial changes during a scan. In this study, we developed an objective depression recognition approach using the dynamic regional interactions that occur in response to sad facial stimuli. The whole time-period magnetoencephalography (MEG) signals from the visual cortex, amygdala, anterior cingulate cortex (ACC) and inferior frontal gyrus (IFG) were separated into sequential time intervals. The Granger causality mapping method was used to identify the pairwise interaction pattern within each time interval. Feature selection was then undertaken within a minimum redundancy-maximum relevance (mRMR) framework. Typical classifiers were utilized to predict those patients who had depression. The overall performances of these classifiers were similar, and the highest classification accuracy rate was 87.5%. The best discriminative performance was obtained when the number of features was within a robust range. The discriminative network pattern obtained through support vector machine (SVM) analyses displayed abnormal causal connectivities that involved the amygdala during the early and late stages. These early and late connections in the amygdala appear to reveal a negative bias to coarse expression information processing and abnormal negative modulation in patients with depression, which may critically affect depression discrimination.

Dynamic connectivity laterality of the amygdala under negative stimulus in depression: a MEG study.

Depression is a mental disorder characterized by emotional and cognitive dysfunction, which is related to the abnormal activity in brain regions involving emotion processing such as amygdala (AMYG). The laterality of AMYG during emotional information processing has always been a controversial issue in any depression study, however, the dynamic characteristic of laterality in the AMYG has been ignored. In this paper, we proposed to explore the time-varying functional coupling between the anterior cingulate cortex (ACC) and the bilateral AMYG in the time-frequency domain. As a result, an emotional facial expression paradigm was undertaken in this study. Using magnetoencephalogram (MEG) data acquired from 16 patients with major depression disorder and 16 matched healthy controls, we calculated the wavelet coherence. The research led to the conclusion that, after sad facial stimuli, the ACC-bilateral AMYG connectivity in depressive patients showed a significant decrease in the beta band during the first 100 ms. In addition, the ACC-left AMYG connectivity led to a significant increase in the gamma band around 400 ms and in beta band around 700 ms. Our work suggests a lack of sufficient inhibition of the ACC on the bilateral AMYG in the early period and the lateralized dysregulation of the ACC on the left AMYG in late period during the sad facial information processing task. We hypothesized that the clinical manifestations of depression may partly result from it.

Multichannel matching pursuit of MEG signals for discriminative oscillation pattern detection in depression.

Magnetoencephalography (MEG) power topography may be useful for obtaining discriminative brain activity patterns that can distinguish depressed patients from healthy control subjects at the individual level. However, the application is still limited due to the lack of adequate analysis strategies to remove artifacts from the MEG signals. In this study, the multichannel matching pursuit (MMP) method was designed; in this technique, a linear decomposition method that provides components by iteratively reanalysing a residual signal after removing previously found components,. Forty-four subjects, half depressed patients and half healthy subjects, were recruited for MEG scanning whilst watching a video of sad faces. MMP was implemented to manage multichannel, multi-trial MEG signals. The representative post-MMP analysis signals were utilised to calculate the power topography over the whole brain and designed as inputs for a Support Vector Machine (SVM) classifier. A statistically significant discriminative accuracy of 86% (p=0.002) after a permutation test was achieved. Comparing the system classification performance to that of the ensemble averaging method and the established Independent Component Analysis (ICA), we demonstrated the ability of MMP to represent critical MEG information and, in turn, to mark the abnormality of oscillatory activities under negative stimuli using images of sad faces.

Impaired prefrontal-amygdala effective connectivity is responsible for the dysfunction of emotion process in major depressive disorder: a dynamic causal modeling study on MEG.

Depression is proved to be associated with the dysfunction of prefrontal-limbic neural circuit, especially during emotion processing procedure. Related explorations have been undertaken from the aspects of abnormal activation and functional connectivity. However, the mechanism of the dysfunction of coordinated interactions remains unknown and is still a matter of debate. The present study gave direct evidence of this issue from the aspect of effective connectivity via dynamic causal modeling (DCM). 20 major depressive disorder (MDD) patients and 20 healthy controls were recruited to attend facial emotional stimulus during MEG recording. Bayesian model selection (BMS) was applied to choose the best model. Results under the optimal model showed that top-down endogenous effective connectivity from the dorsolateral prefrontal cortex (DLPFC) to the amygdala was greatly impaired in patients relative to health controls; while bottom-up endogenous effective connectivity from the amygdala to the anterior cingulate cortex (ACC) as well as modulatory effective connectivity from ACC to DLPFC was significantly increased. We inferred the incapable DLPFC failed to exert influence on amygdala, and finally lead to enhanced amygdala-ACC and ACC-DLPFC bottom-up effects. Such impaired prefrontal-amygdala connectivity was supposed to be responsible for the dysfunction in MDD when dealing with emotional stimuli.

Depression recognition using resting-state and event-related fMRI signals.

PURPOSE: This paper aimed to develop a method for depression detection using blood-oxygen-level-dependent (BOLD) response estimated from event-related signals and resting-state functional magnetic resonance imaging (fMRI) signals together. MATERIALS AND METHODS: Thirteen patients with unipolar depression and matched healthy subjects were recruited. Resting state data of each subject were collected. Thereafter, event-related paradigm was undertaken using sad facial stimuli. The resting-state fMRI signal was deemed as the baseline of each subject's activity. Coefficient marks were designed to sort and select temporal independent components of event-related signals. Thereafter, stimulus-evoked BOLD response components inside event-related signal were extracted and taken as features to discriminate depressive patients from healthy controls. RESULTS: Accuracy rate for depression recognition was 77.27% with P value of .017 for whole-brain analysis and 81.82% with P value of .009 for region-of-interest analysis. The effectiveness and the superiority of the proposed method for disease recognition were demonstrated via the performance comparison with three other typical methods. CONCLUSIONS: The proposed model was effective in depression recognition.