Brain connectivity patterns derived from aging-related alterations in dynamic brain functional networks and their potential as features for brain age classification.

Objective.Recent studies have demonstrated that the analysis of brain functional networks (BFNs) is a powerful tool for exploring brain aging and age-related neurodegenerative diseases. However, investigating the mechanism of brain aging associated with dynamic BFN is still limited. The purpose of this study is to develop a novel scheme to explore brain aging patterns by constructing dynamic BFN using resting-state functional magnetic resonance imaging data.Approach.A dynamic sliding-windowed non-negative block-diagonal representation (dNBDR) method is proposed for constructing dynamic BFN, based on which a collection of dynamic BFN measures are suggested for examining age-related differences at the group level and used as features for brain age classification at the individual level.Results.The experimental results reveal that the dNBDR method is superior to the sliding time window with Pearson correlation method in terms of dynamic network structure quality. Additionally, significant alterations in dynamic BFN structures exist across the human lifespan. Specifically, average node flexibility and integration coefficient increase with age, while the recruitment coefficient shows a decreased trend. The proposed feature extraction scheme based on dynamic BFN achieved the highest accuracy of 78.7% in classifying three brain age groups.Significance. These findings suggest that dynamic BFN measures, dynamic community structure metrics in particular, play an important role in quantitatively assessing brain aging.

Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation.

Generative approaches to molecular design are an area of intense study in recent years as a method to generate new pharmaceuticals with desired properties. Often though, these types of efforts are constrained by limited experimental activity data, resulting in either models that generate molecules with poor performance or models that are overfit and produce close analogs of known molecules. In this paper, we reduce this data dependency for the generation of new chemotypes by incorporating docking scores of known and de novo molecules to expand the applicability domain of the reward function and diversify the compounds generated during reinforcement learning. Our approach employs a deep generative model initially trained using a combination of limited known drug activity and an approximate docking score provided by a second machine learned Bayes regression model, with final evaluation of high scoring compounds by a full docking simulation. This strategy results in molecules with docking scores improved by 10-20% compared to molecules of similar size, while being 130 × faster than a docking only approach on a typical GPU workstation. We also show that the increased docking scores correlate with (1) docking poses with interactions similar to known inhibitors and (2) result in higher MM-GBSA binding energies comparable to the energies of known DDR1 inhibitors, demonstrating that the Bayesian model contains sufficient information for the network to learn to efficiently interact with the binding pocket during reinforcement learning. This outcome shows that the combination of the learned latent molecular representation along with the feature-based docking regression is sufficient for reinforcement learning to infer the relationship between the molecules and the receptor binding site, which suggest that our method can be a powerful tool for the discovery of new chemotypes with potential therapeutic applications.

Study on the Voltage Reference Noise at Sub-Millihertz Frequencies for Developing an Ultra-Stable Temperature Measurement Subsystem.

A temperature measurement subsystem (TMS) is a critical piece of infrastructure of the space gravitational wave detection platform, necessary for monitoring minuscule temperature changes at the level of 1µK/Hz1/2 within the electrode house, in the frequency range of 0.1mHz to 1Hz. The voltage reference (VR), a key component of the TMS, must possess low noise characteristics in the detection band to minimize the impact on temperature measurements. However, the noise characteristics of the voltage reference in the sub-millihertz range have not been documented yet and require further study. This paper reports a dual-channel measurement method for measuring the low-frequency noise of VR chips down to 0.1mHz. The measurement method makes use of a dual-channel chopper amplifier and an assembly thermal insulation box to achieve a normalized resolution of 3×10-7/Hz1/2@0.1mHz in the VR noise measurement. The seven best-performance VR chips documented at a common frequency range are tested. The results show that their noise at sub-millihertz frequencies can significantly differ from that around 1Hz.

Identifying the evolution of primary oxidation mechanisms and pollutant degradation routes in the electro-cocatalytic Fenton-like systems.

Herein, electro-catalysis (EC) as the electron donor to accelerate the continuable Fe(III)/Fe(II) cycles in different inorganic peroxides (i.e., peroxymonosulfate (PMS), peroxydisulfate (PDS) and hydrogen peroxide (HP)) activation systems were established. These electro-cocatalytic Fenton-like systems exhibited an excellent degradation efficiency of sulfamethoxazole (SMX). A series of analytical and characterization methods including quenching experiments, probe experiments, and electron paramagnetic resonance spectrometry (EPR) were implemented to systematically sort out the source and yield of reactive oxygen species (ROS). A wide kind of ROS including hydroxyl radical (•OH), singlet oxygen (1O2), and sulfate radical (SO4•-), which contributed 38%, 37%, and 24% were produced in EC/Fe(III)/PMS system, respectively. •OH was the dominant ROS in both EC/Fe(III)/PDS and EC/Fe(III)/HP processes. According to the analysis of SMX degradation routes and biotoxicity, abundant degradation pathways were identified in EC/Fe(III)/PMS process and lower environmental impact was achieved in EC/Fe(III)/HP process. The diversiform ROS of EC/Fe(III)/PMS system makes it exhibit greater environmental adaptability in complex water matrixes and excellent low-energy consumption performance in many organic pollutants degradation. Continuous flow treatment experiments proved that the three systems have great sustainability and practical application prospect. This work provides a strong basis for constructing suitable systems to achieve different treatment requirements.

Elevated serum FGF21 levels predict heart failure during hospitalization of STEMI patients after emergency percutaneous coronary intervention.

Background: Fibroblast growth factor 21 (FGF21) has multiple cardioprotective effects including modulation of glucolipid metabolism, anti-inflammation, and anti-oxidative stress, but its association with the heart failure during hospitalization in patients with ST-segment elevation myocardial infarction (STEMI) undergoing emergency percutaneous coronary intervention (PCI) has not been reported. Methods: A total of 348 STEMI patients treated with emergency PCI were included from January 2016 to December 2018. Relevant biochemical indicators were measured by central laboratory. Serum FGF21 levels were measured by ELISA. The occurrence of heart failure during hospitalization was recorded. Patients' cardiac function was assessed by echocardiography. Results: Serum FGF21 levels were significantly higher in the STEMI group with heart failure than in the group without heart failure (249.95 ± 25.52 vs. 209.98 ± 36.35, P < 0.001). Serum FGF21 levels showed a strong positive correlation with N-terminal precursor B-type natriuretic peptide (NT-proBNP) in STEMI patients (r = 0.749, P < 0.001). FGF21 was found to be an independent risk factor for the development of heart failure during hospitalization in STEMI patients by binary logistic regression analysis. The area under curve (AUC) for FGF21 to predict the development of heart failure during hospitalization in STEMI patients was 0.816 (95% CI [0.770-0.863]) according to the receiver operating characteristic (ROC) curve analysis. Conclusion: Elevated serum FGF21 levels have been shown to be a strong predictor of heart failure during hospitalization in patients with STEMI after emergency PCI.

Recognition of unilateral lower limb movement based on EEG signals with ERP-PCA analysis.

It has been confirmed that motor imagery (MI) and motor execution (ME) share a subset of mechanisms underlying motor cognition. In contrast to the well-studied laterality of upper limb movement, the laterality hypothesis of lower limb movement also exists, but it needs to be characterized by further investigation. This study used electroencephalographic (EEG) recordings of 27 subjects to compare the effects of bilateral lower limb movement in the MI and ME paradigms. Event-related potential (ERP) recorded was decomposed into meaningful and useful representatives of the electrophysiological components, such as N100 and P300. Principal components analysis (PCA) was used to trace the characteristics of ERP components temporally and spatially, respectively. The hypothesis of this study is that the functional opposition of unilateral lower limbs of MI and ME should be reflected in the different alterations of the spatial distribution of lateralized activity. Meanwhile, the significant ERP-PCA components of the EEG signals as identifiable feature sets were applied with support vector machine to identify left and right lower limb movement tasks. The average classification accuracy over all subjects is up to 61.85% for MI and 62.94% for ME. The proportion of subjects with significant results are 51.85% for MI and 59.26% for ME, respectively. Therefore, a potential new classification model for lower limb movement can be applied on brain computer interface (BCI) systems in the future.

High serum fibroblast growth factor 21 levels were related to the prognosis and ventricular remodeling of heart failure patients with mildly reduced and reduced ejection fraction.

INTRODUCTION: Previous studies have shown that fibroblast growth factor 21 (FGF21) is involved in the ventricular remodeling process in heart failure with preserved ejection fraction (HFpEF). We hypothesized that high levels of FGF21 correlated with the ventricular remodeling of heart failure patients with mildly reduced (HFmrEF) and reduced ejection fraction (HFrEF). METHODS: A total of 203 participants with HFmrEF or HFrEF were enrolled and followed up from June 2018 to June 2021. 68 subjects without heart failure (HF) underwent physical examinations during the same time were selected as the control group. The primary endpoint was the occurrence of major adverse cardiovascular events (MACEs), which were defined as all-cause or cardiac mortality and rehospitalization for decompensation. Serum FGF21 levels were measured early the next morning after admission using enzyme-linked immunosorbent assay (ELISA). RESULTS: The FGF21 levels were significantly higher in patients with HFmrEF or HFrEF than that in the control group (213.57 ± 42.65 pg/mL, 222.93 ± 34.36 pg/mL vs 171.00 ± 12.86 pg/mL, p < .001). The serum levels of FGF21 and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were both higher in the endpoint event group than those of non-endpoint event group regardless of the HFmrEF or HFrEF group (p < .001). Spearman's correlation revealed that FGF21 was positively correlated with left ventricular end-systolic diameter left ventricular end-diastolic diameter left ventricular mass index (p < .01). Moreover, there was a negative correlation between FGF21 and left ventricular ejection fraction in addition to relative wall thickness (p < .001). The area under the receiver operating characteristic (ROC) curve (AUC) of FGF21 was 0.874. The optimal cut-off value of FGF21 determined by ROC curve was 210.11 pg/mL. The Kaplan-Meier analysis demonstrated that the low FGF21 levels group had an increased MACE-free survival rate compared with the high FGF21 levels group. On univariate and multivariate Cox analysis, it was seen that both serum FGF21 and NT-proBNP were independent predictors of a poor prognosis in HF patients. CONCLUSION: Baseline levels of FGF21 and NT-proBNP were related to the ventricular remodeling of patients with a mildly reduced or reduced ejection fraction. FGF21 and NT-proBNP both had good prognostic value for MACEs in heart failure patients with a mildly reduced and reduced ejection fraction.

Experimental study of a tapered fiber temperature sensor with a liquid seal based on multimode interference.

Studying high-sensitivity fiber-optic temperature sensors is vital in pursuing high-precision temperature measurement. We propose a liquid-sealed multimode interference fiber temperature sensor with a double-taper structure. The influence of structure and sealed-liquid material on the temperature sensitivity of the sensor is analyzed experimentally. The results show that the tapered structure can effectively improve the temperature sensitivity of the sensor, and the effect becomes more evident with the increased refractive index of the sealed liquid. As the refractive index of the sealed liquid increases, the temperature sensitivity of the sensor can be effectively improved. However, the sealed liquid with a high refractive index will increase the failure temperature of the sensor. Near the failure temperature, the sensor achieves an ultra-high-temperature sensitivity of -8.28nm/K. The results also prove that further increasing the refractive index of the sealed liquid no longer has a significant gain in temperature sensitivity. It is expected that the relevant research will contribute to the development of high-precision temperature-sensing systems.

A Deep Learning Model for Three-Dimensional Nystagmus Detection and Its Preliminary Application.

Symptoms of vertigo are frequently reported and are usually accompanied by eye-movements called nystagmus. In this article, we designed a three-dimensional nystagmus recognition model and a benign paroxysmal positional vertigo automatic diagnosis system based on deep neural network architectures (Chinese Clinical Trials Registry ChiCTR-IOR-17010506). An object detection model was constructed to track the movement of the pupil centre. Convolutional neural network-based models were trained to detect nystagmus patterns in three dimensions. Our nystagmus detection models obtained high areas under the curve; 0.982 in horizontal tests, 0.893 in vertical tests, and 0.957 in torsional tests. Moreover, our automatic benign paroxysmal positional vertigo diagnosis system achieved a sensitivity of 0.8848, specificity of 0.8841, accuracy of 0.8845, and an F1 score of 0.8914. Compared with previous studies, our system provides a clinical reference, facilitates nystagmus detection and diagnosis, and it can be applied in real-world medical practices.

Elevated Serum Fibroblast Growth Factor 21 Is Relevant to Heart Failure Patients with Reduced Ejection Fraction.

OBJECTIVE: The aim of this study was to evaluate the roles of fibroblast growth factor 21 (FGF21) in heart failure patients with reduced ejection fraction and its association with Heart Failure with reduced Ejection Fraction (HFrEF). METHODS: The level of FGF21 was measured by enzyme-linked immunosorbent assay (ELISA) in 199 subjects enrolled in this study, including 128 subjects with HFrEF and 71 control subjects. The mean follow-up time was 13.36 months. The left ventricular end-diastolic diameter (LVEDD) and left ventricular ejection fraction (LVEF) percentage were evaluated by the 2D echocardiography. Serum brain natriuretic peptide (BNP) was measured in the routine clinical laboratory. RESULTS: The serum FGF21 level was evidently higher in patients with HFrEF than in the control group (228.72 ± 24.04 vs. 171.60 ± 12.98, p < 0.001). After 1 year of follow-up, 61 patients (47.66%) with heart failure were readmitted to the hospital, including 8 deaths (13.11%). The AUC of the receiver operating characteristic (ROC) curve for the predictive value of FGF21 for prognosis was 0.964. Kaplan-Meier analysis results showed that there were significant differences in the 1-year mortality and heart failure readmission events between the grouped subjects. A poor prognosis was correlated with the serum level of FGF21, BNP, LVEDD, and LVEF, which was confirmed by the univariate Cox analysis. CONCLUSION: FGF21 was independently associated with an increased risk of mortality and readmission HFrEF patients. Therefore, FGF21 has the potential to be a biomarker for the progression of HFrEF in patients.

Brain Fingerprinting and Lie Detection: A Study of Dynamic Functional Connectivity Patterns of Deception Using EEG Phase Synchrony Analysis.

This study investigated the brain functional connectivity (FC) patterns related to lie detection (LD) tasks with the purpose of analyzing the underlying cognitive processes and mechanisms in deception. Using the guilty knowledge test protocol, 30 subjects were divided randomly into guilty and innocent groups, and their electroencephalogram (EEG) signals were recorded on 32 electrodes. Phase synchrony of EEG was analyzed between different brain regions. A few-trials-based relative phase synchrony (FTRPS) measure was proposed to avoid the false synchronization that occurs due to volume conduction. FTRPS values with a significantly statistical difference between two groups were employed to construct FC patterns of deception, and the FTRPS values from the FC networks were extracted as the features for the training and testing of the support vector machine. Finally, four more intuitive brain fingerprinting graphs (BFG) on delta, theta, alpha and beta bands were respectively proposed. The experimental results reveal that deceptive responses elicited greater oscillatory synchronization than truthful responses between different brain regions, which plays an important role in executing lying tasks. The functional connectivity in the BFG is mainly implicated in the visuo-spatial imagery, bottom-top attention and memory systems, work memory and episodic encoding, and top-down attention and inhibition processing. These may, in part, underlie the mechanism of communication between different brain cortices during lying. High classification accuracy demonstrates the validation of BFG to identify deception behavior, and suggests that the proposed FTRPS could be a sensitive measure for LD in the real application.

Elevated serum FGF21 predicts the major adverse cardiovascular events in STEMI patients after emergency percutaneous coronary intervention.

BACKGROUND: Although there have been several studies related to serum fibroblast growth factor 21 (FGF21) levels and acute myocardial infarction, the value of serum FGF21 levels in ST-segment elevation myocardial infarction (STEMI) patients after emergency percutaneous coronary intervention (PCI) has not been previously investigated. METHODS: A total of 348 STEMI patients who underwent emergency PCI were enrolled from January 2016 to December 2018. The primary endpoint was the occurrence of major adverse cardiovascular events (MACEs), with a median follow-up of 24 months. Eighty patients with stable angina (SA) who underwent selective PCI served as the control group. Serum FGF21 levels were measured by ELISA. RESULTS: Serum FGF21 levels were significantly higher in the STEMI group than in the SA group (225.03 ± 37.98 vs. 135.51 ±  34.48, P < 0.001). Multiple linear regression analysis revealed that serum FGF21 levels were correlated with NT-proBNP (P < 0.001). According to receiver operating characteristic (ROC) analysis, the areas under the ROC curve (AUCs) of FGF21 and NT-proBNP were 0.812 and 0.865, respectively. The Kaplan-Meier curves showed that STEMI patients with lower FGF21 levels had an increased MACE-free survival rate. Cox analysis revealed that high FGF21 levels (HR: 2.011, 95% CI: [1.160-3.489]) proved to be a powerful tool in predicting the risk of MACEs among STEMI patients after emergency PCI. CONCLUSION: Elevated FGF21 levels on admission have been shown to be a powerful predictor of MACEs for STEMI patients after emergency PCI.

Fibroblast Growth Factor 21 Correlates with the Prognosis of Dilated Cardiomyopathy.

OBJECTIVES: The goal of this study was to evaluate whether serum fibroblast growth factor 21 (FGF21) levels can be used to predict the prognosis of dilated cardiomyopathy (DCM). METHODS: 241 patients with DCM and 80 control subjects were recruited and followed up for an average of 16.12 months. A 2-dimensional (2-D) echocardiography technique was performed to calculate the left ventricular end-diastolic diameter (LVEDD) and left ventricular ejection fraction (LVEF) percentages. The levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and creatinine were measured in routine clinical laboratory tests. Serum FGF21 levels were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: The levels of serum FGF21 were significantly higher in the DCM groups than in the control groups (225.85 ± 32.57 vs. 145.36 ± 30.57, p < 0.001). Serum FGF21 levels were positively correlated with the NYHA functional classification of heart failure (HF) (r = 0.610, p < 0.001) and NT-proBNP levels (r = 0.741, p < 0.001). Moreover, a negative correlation was observed between the serum FGF21 levels and the LVEF (r = -0.402, p < 0.001). FGF21, NT-proBNP, the LVEF and a history of atrial fibrillation (AF) correlated significantly with NYHA class IV (p < 0.05). The AUC of NT-proBNP for predicting NYHA class IV in DCM patients was greater than that of FGF21 (0.830 vs. 0.772, p < 0.001). Overall, 133 patients with DCM were recorded at the end point. Kaplan-Meier analysis results showed that the survival probability of those individuals with high levels of FGF21 and NT-proBNP was significantly lower than of those with low levels of these factors (p < 0.001). In the multivariate Cox analysis, FGF21 (HR 2.561; 95% CI 1.705-3.849) and NT-proBNP (HR 4.458; 95% CI 2.645-7.513) were independent predictors of a poor prognosis in DCM patients. CONCLUSIONS: Serum FGF21 levels were associated with the risk factors, severity, and prognosis of DCM. Therefore, FGF21 may serve as a novel biomarker for the prognosis of DCM.

Random matrix theory for analysing the brain functional network in lower limb motor imagery.

We use random matrix theory (RMT) to investigate the statistical properties of brain functional networks in lower limb motor imagery. Functional connectivity was calculated by Pearson correlation coefficient (PCC), mutual information (MTI) and phase locking value (PLV) extracted from EEG signals. We found that when the measured subjects imagined the movements of their lower limbs the spectral density as well as the level spacings displayed deviations from the random matrix prediction. In particular, a significant difference between the left and right foot imaginary movements was observed in the maximum eigenvalue from the PCC, which can provide a theoretical basis for further study on the classification of unilateral movement of lower limbs.

Macromolecule crowding effects on the phase separation of semi-flexible polymer in spherical confined space.

Current works focus on detecting macromolecule crowding effects on the phase separation of the mixture between semi-flexible polymer and crowders (hydrophilic polymers) in confined space by Monte Carlo simulations. With the increasing addition of crowders into the spherical confined space, the semi-flexible polymer was first compressed into a condensed state from the initial coil state, and then the condensed conformation expanded and deposited on the inner surface of the spherical confined space with an extended state. The phase diagram in the phase space of the volume fraction of crowders and the scaled radius of spherical confined space by crowder diameter, and the direct conformation transition of semi-flexible polymer have validated the phase transition process successfully. In addition, the deposition of extended conformation on the inner surface of the spherical confined space was qualified by the vertex density, its curve shifted along the radial direction with the increasing volume fraction of crowder. During the phase separation process, the critical volume fraction φ∗ relates to the crowder diameter approximately linearly and the relation between the critical volume fraction and the crowder diameter strongly depends on the size of the spherical confined space.

EEG-based Classification of Lower Limb Motor Imagery with Brain Network Analysis.

This study aims to investigate the difference in cortical signal characteristics between the left and right foot imaginary movements and to improve the classification accuracy of the experimental tasks. Raw signals were gathered from 64-channel scalp electroencephalograms of 11 healthy participants. Firstly, the cortical source model was defined with 62 regions of interest over the sensorimotor cortex (nine Brodmann areas). Secondly, functional connectivity was calculated by phase lock value for α and ß rhythm networks. Thirdly, network-based statistics were applied to identify whether there existed stable and significant subnetworks that formed between the two types of motor imagery tasks. Meanwhile, ten graph theory indices were investigated for each network by t-test to determine statistical significance between tasks. Finally, sparse multinomial logistic regression (SMLR)-support vector machine (SVM), as a feature selection and classification model, was used to analyze the graph theory features. The specific time-frequency (α event-related desynchronization and ß event-related synchronization) difference network between the two tasks was congregated at the midline and demonstrated significant connections in the premotor areas and primary somatosensory cortex. A few of statistically significant differences in the network properties were observed between tasks in the α and ß rhythm. The SMLR-SVM classification model achieved fair discrimination accuracy between imaginary movements of the two feet (maximum 75% accuracy rate in single-trial analyses). This study reveals the network mechanism of the discrimination of the left and right foot motor imagery, which can provide a novel avenue for the BCI system by unilateral lower limb motor imagery.

Serum level of transforming growth factor beta 1 is associated with left atrial voltage in patients with chronic atrial fibrillation.

BACKGROUND: Atrial tissue fibrosis can cause electrical or structural remodeling in patients with atrial fibrillation. Transforming growth factor beta 1(TGF-ß1) signaling acts as a central role in fibroblast activation. In this report, we aimed to investigate the relationship between serum level of TGF-ß1 and mean left atrial voltage in patients with chronic atrial fibrillation (CAF). METHODS: A total of 16 consecutive adult patients with CAF who underwent catheter ablation were enrolled. Blood samples for measurement of TGF-ß1 were collected from periphery veins and coronary sinus before pulmonary vein isolation. The measurement was performed with a commercially available ELISA kit. Cardiac indices were measured using echocardiography. The left atrial electroanatomic mapping was performed after pulmonary vein isolation. RESULTS: Serum level of TGF-ß1 in peripheral blood was higher than that in coronary sinus (p < 0.001). TGF-ß1 serum level in coronary sinus negatively correlated with mean left atrial voltage (r = -0.650, p = 0.012), While periphery TGF-ß1 level tended to be negatively correlated with mean left atrial voltage(r = -0.492, p = 0.053). Patients who treated with angiotensin II receptor antagonists had lower coronary sinus TGF-ß1 serum level than those who did not treated with angiotensin II receptor antagonists (p = 0.046). CONCLUSION: Level of TGF-ß1 in peripheral serum is higher than that in coronary sinus, and serum level of TGF-ß1 in coronary sinus is negatively associated with mean left atrial voltage in patients with CAF, angiotensin II receptor antagonists could affect TGF-ß1 serum level.

Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials.

To better characterize the cognitive processes and mechanisms that are associated with deception, wavelet coherence was employed to evaluate functional connectivity between different brain regions. Two groups of subjects were evaluated for this purpose: 32 participants were required to either tell the truth or to lie when facing certain stimuli, and their electroencephalogram signals on 12 electrodes were recorded. The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the prefrontal/frontal and left parietal regions. These results indicate that these brain regions play an important role in executing lying responses. Additionally, three time- and frequency-dependent functional connectivity networks were proposed to thoroughly reflect the functional coupling of brain regions that occurs during lying. Furthermore, the wavelet coherence values for the connections shown in the networks were extracted as features for support vector machine training. High classification accuracy suggested that the proposed network effectively characterized differences in functional connectivity between the two groups of subjects over a specific time-frequency area and hence could be a sensitive measurement for identifying deception.

Advanced treatment of effluents from an industrial park wastewater treatment plant by ferrous ion activated persulfate oxidation process.

The advanced oxidation technology, ferrous ion (Fe(II)) activated persulfate (PS) producing sulfate radicals, was used for the advanced treatment of effluent from an integrated wastewater treatment plant in a papermaking industrial park. Separate and interactive effects of PS dosage, Fe(II)/PS ratio and initial pH on chemical oxygen demand (COD) removal were analyzed by the response surface methodology (RSM). The results showed that Fe(II)-PS system was effective in COD removal from the secondary effluent. PS dosage was the most dominant factor with positive influence on COD removal, followed by initial pH value. The optimum conditions with COD removal of 54.4% were obtained at PS/COD of 2.2, initial pH of 6.47 and Fe(II)/PS of 1.89. UV-visible spectrum analysis showed that after RSM optimization, Fe(II)-PS system effectively degraded large organic molecules into small ones, and decreased humification degree of the effluent. Three-dimensional fluorescence analysis demonstrated that aromatic protein and fulvic substances were fully decomposed by the Fe(II)-PS treatment.

[Advanced Treatment of Effluent from Industrial Park Wastewater Treatment Plant by Ferrous Ion Activated Sodium Persulfate].

Fe(II) activated sodium persulfate (PS) technology was used for advanced treatment of effluent from industrial park wastewater treatment plant. Separate and combined effects of PS/COD, Fe(II)/PS and pH on COD and TOC removal were analyzed by the response surface methodology. Variations of organic substances before and after Fe(II)-PS oxidation were characterized by UV-Vis spectrometry, gel chromatography and three-dimensional fluorescence. PS/COD and Fe(II)/PS had significant effect on COD removal, while all the three factors had significant effect on TOC removal. The combined effect of PS/COD and pH had significant effect on COD removal. COD and TOC removal efficiencies reached 50.7% and 60.6% under optimized conditions of PS/COD 3.47, Fe(II)/PS 3.32 and pH 6.5. Fe(II)-PS oxidation converted macromolecular organic substances to small ones, and reduced contents of protein-, humic- and fulvic-like substances.