Depolymerization of plastics by means of electrified spatiotemporal heating.

Depolymerization is a promising strategy for recycling waste plastic into constituent monomers for subsequent repolymerization1. However, many commodity plastics cannot be selectively depolymerized using conventional thermochemical approaches, as it is difficult to control the reaction progress and pathway. Although catalysts can improve the selectivity, they are susceptible to performance degradation2. Here we present a catalyst-free, far-from-equilibrium thermochemical depolymerization method that can generate monomers from commodity plastics (polypropylene (PP) and poly(ethylene terephthalate) (PET)) by means of pyrolysis. This selective depolymerization process is realized by two features: (1) a spatial temperature gradient and (2) a temporal heating profile. The spatial temperature gradient is achieved using a bilayer structure of porous carbon felt, in which the top electrically heated layer generates and conducts heat down to the underlying reactor layer and plastic. The resulting temperature gradient promotes continuous melting, wicking, vaporization and reaction of the plastic as it encounters the increasing temperature traversing the bilayer, enabling a high degree of depolymerization. Meanwhile, pulsing the electrical current through the top heater layer generates a temporal heating profile that features periodic high peak temperatures (for example, about 600 °C) to enable depolymerization, yet the transient heating duration (for example, 0.11 s) can suppress unwanted side reactions. Using this approach, we depolymerized PP and PET to their monomers with yields of about 36% and about 43%, respectively. Overall, this electrified spatiotemporal heating (STH) approach potentially offers a solution to the global plastic waste problem.

Programmable heating and quenching for efficient thermochemical synthesis.

Conventional thermochemical syntheses by continuous heating under near-equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways1-3. As an alternative, we present a non-equilibrium, continuous synthesis technique that uses pulsed heating and quenching (for example, 0.02 s on, 1.08 s off) using a programmable electric current to rapidly switch the reaction between high (for example, up to 2,400 K) and low temperatures. The rapid quenching ensures high selectivity and good catalyst stability, as well as lowers the average temperature to reduce the energy cost. Using CH4 pyrolysis as a model reaction, our programmable heating and quenching technique leads to high selectivity to value-added C2 products (>75% versus <35% by the conventional non-catalytic method and versus <60% by most conventional methods using optimized catalysts). Our technique can be extended to a range of thermochemical reactions, such as NH3 synthesis, for which we achieve a stable and high synthesis rate of about 6,000 µmol gFe-1 h-1 at ambient pressure for >100 h using a non-optimized catalyst. This study establishes a new model towards highly efficient non-equilibrium thermochemical synthesis.

Effluent quality prediction of the sewage treatment based on a hybrid neural network model: Comparison and application.

The accurate prediction and assessment of effluent quality in wastewater treatment plants (WWTPs) are paramount for the efficacy of sewage treatment processes. Neural network models have exhibited promise in enhancing prediction accuracy by simulating and analyzing diverse influent parameters. In this study, a back propagation neural network hybrid model based on a tent chaotic map and sparrow search algorithm (Tent_BP_SSA) was developed to predict the effluent quality of sewage treatment processes. The prediction performance of the propose hybrid model was compared with traditional neural network models using five performance indicators (MAE, RMSE, SSE, MAPE and R2). Specifically, in comparison with the prior Tent_BP_SSA, Tent_BP_SSA2 demonstrated notable enhancements, with the R2 increasing from 0.9512 to 0.9672, while MAE, RMSE, SSE, and MAPE decreased by 9.62%, 18.84%, 24.80%, and 47.10%, respectively. These indicators collectively affirm that the utilization of higher-order input parameters ensures improved accuracy of the Tent_BP_SSA2 hybrid model in predicting effluent quality. Moreover, the Tent_BP_SSA2 model exhibited robust prediction ability (R2 of 0.9246) when applied to assess the effluent quality of an actual sewage treatment plant. The incorporation of integrated models comprising the sparrow search optimizing algorithm, tent chaotic mapping, and higher-order magnitude decomposition of input parameters has demonstrated the capacity to enhance the accuracy of effluent quality prediction. This study illuminates novel perspectives on the prediction of effluent quality and the assessment of effluent warnings in WWTPs.

Genetic analysis of the causal relationship between gut microbiota and intervertebral disc degeneration: a two-sample Mendelian randomized study.

PURPOSE: Several recent studies have reported a possible association between gut microbiota and intervertebral disc degeneration; however, no studies have shown a causal relationship between gut microbiota and disc degeneration. This study was dedicated to investigate the causal relationship between the gut microbiota and intervertebral disc degeneration and the presence of potentially bacterial traits using two-sample Mendelian randomization. METHODS: A two-sample Mendelian randomization study was performed using the summary statistics of the gut microbiota from the largest available genome-wide association study meta-analysis conducted by the MiBioGen consortium. Summary statistics of intervertebral disc degeneration were obtained from the FinnGen consortium R8 release data. Five basic methods and MR-PRESSO were used to examine causal associations. The results of the study were used to examine the causal association between gut microbiota and intervertebral disc degeneration. Cochran's Q statistics were used to quantify the heterogeneity of instrumental variables. RESULTS: By using Mendelian randomization analysis, 10 bacterial traits potentially associated with intervertebral disc degeneration were identified: genus Eubacterium coprostanoligenes group, genus Lachnoclostridium, unknown genus id.2755, genus Marvinbryantia, genus Ruminococcaceae UCG003, family Rhodospirillaceae, unknown genus id.959, order Rhodospirillales, genus Lachnospiraceae NK4A136 grou, genus Eubacterium brachy group. CONCLUSION: This Mendelian Randomization study found a causal effect between 10 gut microbiota and intervertebral disc degeneration, and we summarize the possible mechanisms of action in the context of existing studies. However, additional research is essential to fully understand the contribution of genetic factors to the dynamics of gut microbiota and its impact on disc degeneration.

Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images.

BACKGROUND: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1 CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy. METHODS: Thirty-six patients with histologically confirmed ODGs underwent T1 CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1 CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist's assessment were also compared. RESULTS: Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1 CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists' assessment. CONCLUSIONS: Machine-learning based on radiomics of T1 CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

Fetal brain development at 25-39 weeks gestational age: A preliminary study using intravoxel incoherent motion diffusion-weighted imaging.

BACKGROUND: The fetal brain developmental changes of water diffusivity and perfusion has not been extensively explored. PURPOSE/HYPOTHESIS: To evaluate the fetal brain developmental changes of water diffusivity and perfusion using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). STUDY TYPE: Prospective. POPULATION: Seventy-nine normal singleton fetuses were scanned without sedation of healthy pregnant women. FIELD STRENGTH/SEQUENCE: 5 T MRI/T1 /2 -weighted image and IVIM-DWI. ASSESSMENT: Pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were calculated in the frontal (FWM), temporal (TWM), parietal (PWM), and occipital white matter (OWM) as well as cerebellar hemisphere (CH), basal ganglia region (BGR), thalamus (TH), and pons using an IVIM model. STATISTICAL TESTS: One-way analysis of variable (ANOVA) followed by Bonferroni post-hoc multiple comparison was employed to reveal the difference of IVIM parameters among the investigated brain regions. The linear and the nonlinear polynomial regression analyses were utilized to reveal the correlation between gestational age (GA) and IVIM parameters. RESULTS: There were significant differences in both D (F(7,623) = 96.64, P = 0.000) and f values (F(7,623) = 2.361, P = 0.0219), but not D* values among the varied brain regions. D values from TWM (r2 = 0.1402, P = 0.0002), PWM (r2 = 0.2245, P = 0.0002), OWM (r2 = 0.2519, P = 0.0002), CH (r2 = 0.2245, P = 0.0002), BGR (r2 = 0.3393, P = 0.0001), TH (r2 = 0.1259, P = 0.0001), and D* value from pons (r2 = 0.2206, P = 0.0002) were significantly correlated with GA using linear regression analysis. Quadratic regression analysis led to results similar to those using the linear regression model. DATA CONCLUSION: IVIM-DWI parameters may indicate fetal brain developmental alterations but the conclusion is far from reached due to the not as high-powered correlation between IVIM parameters and GA. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:899-909.

A comparative study on efficacy of modified endoscopic minimally invasive treatment and traditional open surgery for primary carpal tunnel syndrome.

BACKGROUND AND OBJECTIVE: Carpal tunnel syndrome (CTS) is the most common type of median nerve entrapment neuropathy. This study aims to comparatively assess the effectiveness and clinical efficacy of modified transforaminal endoscopic minimally invasive incision of transverse carpal ligament against traditional open incision of transverse carpal ligament in the treatment of CTS. METHOD: The clinical data of 35 patients (57 wrists) with primary CTS treated in Shanxi Bethune Hospital, China, were retrospectively analyzed. The patients were divided into observation group (21 cases, 33 wrists) and control group (14 cases, 24 wrists), respectively, who underwent modified endoscopic minimally invasive incision of transverse carpal ligament and traditional open incision of transverse carpal ligament release. The Boston Carpal Tunnel Questionnaire (BCTQ) was assessed at for points: before the operation; 2 weeks; 1 month; and 3 months after operation. The BCTQ scores of the two groups were compared on all four points. The incidence of intraoperative and postoperative complication was used as the evaluation index. The study variables were comparatively assessed before and postoperation and also between the groups. RESULTS: The BCTQ scores at 2 weeks, 1 month and 3 months after the operation were significantly lower than preoperative BCTQ scores (P < 0.005) for both the groups. There was no significant difference in BCTQ scores between the two groups at the four assessment points (P > 0.005). The scar size and wound healing time were significantly better with modified transforaminal endoscopic minimally invasive transverse carpal ligament incision. CONCLUSION: The clinical effects of both modified transforaminal minimally invasive incision of transverse carpal ligament and traditional open incision of transverse carpal ligament are significant, while the treatment efficacy of modified transforaminal minimally invasive transverse carpal ligament incision is better in terms of operation time, wound size, postoperative scar size and incision healing time.

Understanding the Impact of Hydrogen Activation by SrCe0.8Zr0.2O3-δ Perovskite Membrane Material on Direct Non-Oxidative Methane Conversion.

Direct non-oxidative methane conversion (DNMC) converts methane (CH4) in one step to olefin and aromatic hydrocarbons and hydrogen (H2) co-product. Membrane reactors comprising methane activation catalysts and H2-permeable membranes can enhance methane conversion by in situ H2 removal via Le Chatelier's principle. Rigorous description of H2 kinetic effects on both membrane and catalyst materials in the membrane reactor, however, has been rarely studied. In this work, we report the impact of hydrogen activation by hydrogen-permeable SrCe0.8Zr0.2O3-δ (SCZO) perovskite oxide material on DNMC over an iron/silica catalyst. The SCZO oxide has mixed ionic and electronic conductivity and is capable of H2 activation into protons and electrons for H2 permeation. In the fixed-bed reactor packed with a mixture of SCZO oxide and iron/silica catalyst, stable and high methane conversion and low coke selectivity in DNMC was achieved by co-feeding of H2 in methane stream. The characterizations show that SCZO activates H2 to favor "soft coke" formation on the catalyst. The SCZO could absorb H2 in situ to lower its local concentration to mitigate the reverse reaction of DNMC in the tested conditions. The co-existence of H2 co-feed, SCZO oxide, and DNMC catalyst in the present study mimics the conditions of DNMC in the H2-permeable SCZO membrane reactor. The findings in this work offer the mechanistic understanding of and guidance for the design of H2-permeable membrane reactors for DNMC and other alkane dehydrogenation reactions.

[Effects of Microbial Fuel Cell Coupled Constructed Wetland with Different Support Matrix and Cathode Areas on the Degradation of Azo Dye and Electricity Production].

In this study, microbial fuel cell coupled constructed wetland (CW-MFC) was constructed for azo dye reactive brilliant red X-3B degradation and electricity production. The effects of support matrix and cathode areas on the degradation of X-3B and the electricity production of CW-MFC were investigated in this work to improve the performance of CW-MFC. The highest decolorization efficiency was 92.70% and was obtained when the CW-MFC was constructed with support matrix S3 with particle size of 10 mm and porosity of 30%. Small particle size increased the microbial biomass of the bottom layer of CW-MFC, which would promote the decolorization of X-3B in the bottom layer. However, it may cause the lack of nutrition in electrode layer and the increase in resistance of mass transfer, which would lead to the decline of electricity production. The decolorization efficiency and the power density of CW-MFC increased concomitantly with the increase of cathode areas, and the CW-MFC got the highest decolorization efficiency of 99.41% when the cathode area was 594 cm2. The electricity production performance became stable when the cathode area continued to increase, while the decolorization efficiency declined. This may be attributed to that more electrons were transferred to the cathode to produce current instead of used in degradation of X-3B.

Effects of electrode gap and wastewater condition on the performance of microbial fuel cell coupled constructed wetland.

The effects of electrode gap, PB solution concentration and azo dye on the wastewater treatment and electricity generation of microbial fuel cell coupled constructed wetland (CW-MFC) were studied. The electrode gap had obvious influence on the decolorization, while the influence of PB concentration on the decolorization was not obvious. The best decolorization efficiency was 91.05% and was gained when the electrode gap was 13.2 cm. The smaller the electrode gap, the smaller the ohmic resistance. However, a too small electrode gap would reduce the electricity generation. The best PB concentration in this study was 50 mM. In the glucose group, when the PB concentration was 50 mM, the power density was enhanced to 0.38 W/m3, while the PB concentration was 5 mM, the power density was only 0.14 W/m3. In the ABRX3 group, when the PB concentration was 50 mM, the power density was 0.18 W/m3, while when the PB concentration was 5 mM, the power density was 0.12 W/m3. The electricity generation performance of the CW-MFC was enhanced with an increase in running time. Long-time running CW-MFC got a higher cathode potential and a smaller internal resistance.