Developing abundant rare-earth iron perovskite electrodes for high-performance and low-cost solid oxide fuel cells.

The swift advancement of the solid oxide fuel cell (SOFC) sector necessitates a harmony between electrode performance and commercialization cost. The economic value of elements is frequently linked to their abundance in the Earth's crust. Here, we develop abundant rare-earth iron perovskite electrodes of Ln0.6Sr0.4FeO3-δ (Ln = La, Pr, and Nd) with high abundant rare-earth metals and preferred iron metal for SOFCs. All three symmetric electrode materials display a cubic perovskite phase and excellent chemical compatibility with Gd0.2Ce0.8O2-δ electrolyte. All three electrodes possess exceptional surface oxygen exchange ability. At 800°C, single cells with La0.6Sr0.4FeO3-δ, Pr0.6Sr0.4FeO3-δ, and Nd0.6Sr0.4FeO3-δ symmetric electrodes attained excellent open circuit voltages of 1.108, 1.101, and 1.097 V, respectively, as well as peak powers of 213.52, 281.12, and 254.58 mW cm-2. The results suggest that overall performance of abundant rare-earth iron perovskite electrodes has a favorable impact on the extensive expansion of SOFCs, presenting significant potential for practical applications.

Assessment of the observation management of sialocele after partial superficial parotidectomy.

PURPOSE: This study aimed to investigate the usefulness of management of sialocele formation and to evaluate the quality of life of patients under elective management post-parotidectomy. MATERIALS AND METHODS: A prospective study was performed including patients who underwent postoperative management with either compression therapy or observation. The self-filled questionnaire method was used to assess the quality of life of participants who changed from compression therapy to observation. Demographic and operative data, variables regarding wound complications and scores for quality of life were documented and analysed. RESULTS: A total of 86 patients met the eligibility criteria. The respective rates of sialocele formation within 1 month were 5.3% in the compression therapy group (2/38) and 16.0% in the observation group (4/25), but no significant difference was observed (p = 0.204). Meanwhile, both groups displayed comparable times of needle aspiration and time for sialocele resolution (p > 0.05). Based on 23 valid paired questionnaires, scores for physical and social-emotional function before changing from compression therapy to observation were significantly lower than scores after the change (p < 0.001). CONCLUSION: The application of observation after partial superficial parotidectomy appears to have acceptable clinical outcomes and considerable improvements in quality of life.

Identification of Groundwater Pollution Characteristics and Health Risk Assessment of a Landfill in a Low Permeability Area.

The shallow weathering fissure groundwater in the red-bed area of Southwest China is usually the only drinking water source for most rural residents. In this study, a typical landfill with surrounding residents drinking unpurified groundwater in red-bed area was selected and water quality detection, groundwater numerical simulation and human health risk assessment were used to identify and assess groundwater pollution in the region. The chemical type evolved from HCO3-SO4-Ca-Mg and HCO3-SO4-Ca to Na-Ca-Cl-HCO3 contaminated by the landfill. Na+ and Cl- were selected as factors for rapid identification of groundwater pollution. Subsequent analyses using these factors showed that the leachate pollution plume boundary was 190 m downstream of the landfill. Analysis of the redox conditions revealed that the area from the landfill to 5 m downstream was the reduction zone, while the area beyond 5 m was the oxidation zone. The migration and attenuation patterns of inorganic salts (such as SO42-) and heavy metals (such as Fe and Mn) in the oxidation and reduction zones differed obviously. Meanwhile, the organic pollutants in the leachate were reduced and decomposed into organic acids, which caused the groundwater 80 m downstream of the landfill to become weakly acidic (pH ranged from 6.51 to 6.83), and promoted re-entry of adsorbed heavy metals (such as Pb) into the groundwater. The groundwater risk assessment based on human health revealed that lead, manganese, chlorobenzene, dichloroethane and chloroform constituted a major health threat to the residents. The rank of non-carcinogenic risk was lead >manganese, and the maximum area of non-carcinogenic risk was 15,485 m2. The total carcinogenic risk caused by organic pollutants was 7.9 × 10-6, and the area of the carcinogenic risk zone was 11,414 m2. Overall, the results of this study provide a scientific basis for management of drinking water and groundwater remediation in the red-bed area with low permeability.

Health Risk Assessment of Groundwater Contaminated by Oil Pollutants Based on Numerical Modeling.

To provide theoretical support for the protection of dispersed drinking water sources of groundwater, we need to accurately evaluate the time and scope of groundwater pollution hazards to human health. This helps the decision-making process for remediation of polluted soil and groundwater in service stations. In this study, we conducted such an evaluation by coupling numerical modeling with a health risk assessment. During the research, soil and groundwater samples were collected and analyzed for 20 pollutants. Fifty-six percent of the heavy contaminants and 100% of the organic contaminants exhibited maximum values at the location of the oil depot. Gray correlation analysis showed that the correlation between background samples and soil underlying the depot was 0.375-0.567 (barely significant to insignificant). The correlation between the reference sequence of other points was 0.950-0.990 (excellent correlation). The correlation of environmental impact after oil depot leakage followed the order: organic pollutants > heavy metals > inorganic pollutants. The groundwater simulation status and predictions indicated that non-carcinogenic health risks covered 25,462 m2 at the time of investigation, and were predicted to extend to 29,593 m2 after five years and to 39,873 m2 after 10 years. Carcinogenic health risks covered 21,390 m2 at the time of investigation, and were predicted to extend to 40,093 m2 after five years and to 53,488 m2 after 10 years. This study provides theoretical support for the protection of a dispersed drinking water source such as groundwater, and also helps the decision-making process for groundwater and soil environment improvement.

Perioperative outcomes and hospital costs associated with flowable gelatin hemostatic matrix for lumbar surgeries in real world hospital setting.

Background: Efficient hemostasis during lumbar surgery (LS) is associated with better perioperative outcomes. Flowable gelatin hemostatic matrix (FGHM) is a new type of absorbable hemostatic agent, which is effective to control bleeding during spinal surgery. This study aimed to assess the impact of FGHM on perioperative outcomes and hospital costs associated with LS. Methods: This study retrospectively analyzed medical and billing records of patients who underwent LS for spinal degenerative disease in a Chinese tertiary care hospital from 2014 to 2016. The identified patients were further stratified into a FGHM group (n = 108) (using the combination of FGHM and gelatin sponge) and a historical control group (using oxidized cellulose and/or collagen, n = 82) for the adjusted comparisons of the perioperative outcomes using a propensity score matching method. Multiple generalized linear regression was conducted to assess the impact of using FGHM on total hospitalization costs. Results: Comparisons of 64 propensity score matched pairs showed a significantly lower blood transfusion rate (34.4% vs 64.1%, p = 0.005), lower blood transfusion volume (182.7 ± 312.4 vs 301.3 ± 281.0 mL, p = 0.045), reduced post-surgery drainage tube placement rate (82.8% vs 93.8%, p = 0.046), and shorter post-operative days on antibiotics (6.0 ± 2.6 vs 7.1 ± 2.4 days, p = 0.010) in the FGHM group. Although with a relatively high acquisition price, the use of FGHM for hemostasis in LS did not increase the total hospitalization costs (coefficient = -0.001, p = 0.972). Conclusions: The use of FGHM in LS improved perioperative outcomes related to hemostatic effects without increasing overall hospital costs in a real-world hospital setting.

Assessment of Trichogramma japonicum and T. chilonis as Potential Biological Control Agents of Yellow Stem Borer in Rice.

Two species of Trichogramma wasps were assessed for their effectiveness against yellow stem borer Scirpophaga incertulas. A laboratory cage test with T. japonicum and T. chilonis showed that both species parasitized yellow stem borer egg masses at 60.0% ± 9.13% and 40.7% ± 7.11%, respectively, with egg parasitism rates of 15.8% ± 22.2% for T. japonicum and 2.8% ± 5.0% for T. chilonis. Once the host eggs were parasitized, emergence rates were high for both species (95.7% ± 0.12% for T. japonicum and 100% for T. chilonis). In paddy field trials, the two Trichogramma species were released at three densities (50,000/ha, 100,000/ha and 200,000/ha) in Southwestern China. Egg mass parasitism was 9% ± 7.7% for T. japonicum and 15% ± 14.1% for T. chilonis, and again only a relatively small fraction of eggs was successfully parasitized. No clear conclusion could be drawn on the most efficient release rate as no significant differences were found among the three release rates. A comparison of field-collected T. japonicum with T. japonicum and T. chilonis mass reared on Corcyra cephalonica showed significantly larger body size and ovipositor length in field-collected wasps, suggesting potentially higher effectiveness on yellow stem borer eggs after at least one generation on the target host. Factors contributing to the low field parasitism rates are discussed.

Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics.

MOTIVATION: Next-generation sequencing (NGS) technologies generate large amounts of short read data for many different organisms. The fact that NGS reads are generally short makes it challenging to assemble the reads and reconstruct the original genome sequence. For clustering genomes using such NGS data, word-count based alignment-free sequence comparison is a promising approach, but for this approach, the underlying expected word counts are essential.A plausible model for this underlying distribution of word counts is given through modeling the DNA sequence as a Markov chain (MC). For single long sequences, efficient statistics are available to estimate the order of MCs and the transition probability matrix for the sequences. As NGS data do not provide a single long sequence, inference methods on Markovian properties of sequences based on single long sequences cannot be directly used for NGS short read data. RESULTS: Here we derive a normal approximation for such word counts. We also show that the traditional Chi-square statistic has an approximate gamma distribution ,: using the Lander-Waterman model for physical mapping. We propose several methods to estimate the order of the MC based on NGS reads and evaluate those using simulations. We illustrate the applications of our results by clustering genomic sequences of several vertebrate and tree species based on NGS reads using alignment-free sequence dissimilarity measures. We find that the estimated order of the MC has a considerable effect on the clustering results ,: and that the clustering results that use a N: MC of the estimated order give a plausible clustering of the species. AVAILABILITY AND IMPLEMENTATION: Our implementation of the statistics developed here is available as R package 'NGS.MC' at http://www-rcf.usc.edu/∼fsun/Programs/NGS-MC/NGS-MC.html CONTACT: fsun@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing.

With the development of next-generation sequencing (NGS) technologies, a large amount of short read data has been generated. Assembly of these short reads can be challenging for genomes and metagenomes without template sequences, making alignment-based genome sequence comparison difficult. In addition, sequence reads from NGS can come from different regions of various genomes and they may not be alignable. Sequence signature-based methods for genome comparison based on the frequencies of word patterns in genomes and metagenomes can potentially be useful for the analysis of short reads data from NGS. Here we review the recent development of alignment-free genome and metagenome comparison based on the frequencies of word patterns with emphasis on the dissimilarity measures between sequences, the statistical power of these measures when two sequences are related and the applications of these measures to NGS data.

[Removal of mixed waste gases by the biotrickling filter].

A biotrickling filter (BTF) was designed for treating mixed waste gases, which contained hydrogen sulfide (H2S), tetrahydrofuran (THF) and dichloromethane (DCM) at the start-up and steady states. The removal efficiency of H2S and DCM could maintain about 99% and 60%, respectively, and the removal efficiency of DCM was reduced from 90% to 37% with the shortening empty bed retention time (EBRT) form 50 to 20 seconds when the inlet concentrations were 200, 100, 100 mg x m(-3) of H2S, THF, DCM, respectively. In the theoretical study, the biodegradation efficiency of contaminants was H2S > THF > DCM by analyzing the Michaelis-Menten Dynamic model.

Classifier assessment and feature selection for recognizing short coding sequences of human genes.

With the ever-increasing pace of genome sequencing, there is a great need for fast and accurate computational tools to automatically identify genes in these genomes. Although great progress has been made in the development of gene-finding algorithms during the past decades, there is still room for further improvement. In particular, the issue of recognizing short exons in eukaryotes is still not solved satisfactorily. This article is devoted to assessing various linear and kernel-based classification algorithms and selecting the best combination of Z-curve features for further improvement of the issue. Eight state-of-the-art linear and kernel-based supervised pattern recognition techniques were used to identify the short (21-192 bp) coding sequences of human genes. By measuring the prediction accuracy, the tradeoff between sensitivity and specificity and the time consumption, partial least squares (PLS) and kernel partial least squares (KPLS) algorithms were verified to be the most optimal linear and kernel-based classifiers, respectively. A surprising result was that, by making good use of the interpretability of the PLS and the Z-curve methods, 93 Z-curve features were proved to be the best selective combination. Using them, the average recognition accuracy was improved as high as 7.7% by means of KPLS when compared with what was obtained by the Fisher discriminant analysis using 189 Z-curve variables (Gao and Zhang, 2004 ). The used codes are freely available from the following approaches (implemented in MATLAB and supported on Linux and MS Windows): (1) SVM: http://www.support-vector-machines.org/SVM_soft.html. (2) GP: http://www.gaussianprocess.org. (3) KPLS and KFDA: Taylor, J.S., and Cristianini, N. 2004. Kernel Methods for Pattern Analysis. Cambridge University Press, Cambridge, UK. (4) PLS: Wise, B.M., and Gallagher, N.B. 2011. PLS-Toolbox for use with MATLAB: ver 1.5.2. Eigenvector Technologies, Manson, WA. Supplementary Material for this article is available at www.liebertonline.com/cmb.