Development of a New Fermentation Process for Hardly Degradable Rice Straw Agriculture Waste (Advanced Studies on Sustainable Animal Production: Interrelationships among Human, Animal and Environment, 8th International Symposium of Integrated Field Science)

Oral Sessio

Development of a High-Efficiency Methane Fermentation Process for Hardly Degradable Rice Straw

Symposium Pape

A One-dimensional HEVC video steganalysis method using the Optimality of Predicted Motion Vectors

Among steganalysis techniques, detection against motion vector (MV) domain-based video steganography in High Efficiency Video Coding (HEVC) standard remains a hot and challenging issue. For the purpose of improving the detection performance, this paper proposes a steganalysis feature based on the optimality of predicted MVs with a dimension of one. Firstly, we point out that the motion vector prediction (MVP) of the prediction unit (PU) encoded using the Advanced Motion Vector Prediction (AMVP) technique satisfies the local optimality in the cover video. Secondly, we analyze that in HEVC video, message embedding either using MVP index or motion vector differences (MVD) may destroy the above optimality of MVP. And then, we define the optimal rate of MVP in HEVC video as a steganalysis feature. Finally, we conduct steganalysis detection experiments on two general datasets for three popular steganography methods and compare the performance with four state-of-the-art steganalysis methods. The experimental results show that the proposed optimal rate of MVP for all cover videos is 100\%, while the optimal rate of MVP for all stego videos is less than 100\%. Therefore, the proposed steganography scheme can accurately distinguish between cover videos and stego videos, and it is efficiently applied to practical scenarios with no model training and low computational complexity.Comment: Submitted to TCSV

海洋微細藻類からのエネルギー回収を目指した太陽光利用型光触媒システムに関する研究

科学研究費助成事業 研究成果報告書：基盤研究(B)2015-2017課題番号 : 15H0285

Extraction of Pleurotus ostreatus Protein by the Aqueous Two-phase System and Its Characterization

To achieve green and efficient extraction of Pleurotus ostreatus protein (PP), the phase diagram of the PEG-(NH4)2SO4 aqueous two-phase system (ATPS) was constructed using the cloud point method. Protein extraction concentration was utilized as evaluation indicator to investigate the effects of ATPS factors such as the molecular weight and mass fraction of PEG, mass fraction of (NH4)2SO4, and proportion of added crude PP extraction. Furthermore, the basic components of PP including emulsification characteristics, foaming properties, and water and oil holding capacities were explored. The optimal process conditions for PP extraction were determined using response surface methodology, with PEG2000 mass fraction set at 19.5%, (NH4)2SO4 mass fraction at 22.6%, and protein crude extract mass fraction at 26%. Under these conditions, the extraction rate of protein reached 93.16%, with a protein content of 1.71 mg/mL. Analysis of the physical and chemical properties revealed uniform protein composition with an average particle size of approximately 220.2 nm. The total amino acid content was measured at 221.46 mg/g, with the highest aspartic acid (Asp) content at 25.06 mg/g. Moreover, PP exhibited exceptional emulsification stability 65.22%, foaming properties 79.87%, and water holding capacity 2.61±0.18 g/g. Compared with similar food proteins, PP protein had higher emulsifying stability, foaming ability, and water holding capacity. This study used a green, environmentally friendly, and low toxicity aqueous two-phase method to extract PP protein, providing a new approach for the green and sustainable development of protein extraction in the food industry, and a research foundation for the development of functional foods based on PP protein

Phylogeny more than plant height and leaf area explains variance in seed mass

Although variation in seed mass can be attributed to other plant functional traits such as plant height, leaf size, genome size, growth form, leaf N and phylogeny, until now, there has been little information on the relative contributions of these factors to variation in seed mass. We compiled data consisting of 1071 vascular plant species from the literature to quantify the relationships between seed mass, explanatory variables and phylogeny. Strong phylogenetic signals of these explanatory variables reflected inherited ancestral traits of the plant species. Without controlling phylogeny, growth form and leaf N are associated with seed mass. However, this association disappeared when accounting for phylogeny. Plant height, leaf area, and genome size showed consistent positive relationship with seed mass irrespective of phylogeny. Using phylogenetic partial R2s model, phylogeny explained 50.89% of the variance in seed mass, much more than plant height, leaf area, genome size, leaf N, and growth form explaining only 7.39%, 0.58%, 1.85%, 0.06% and 0.09%, respectively. Therefore, future ecological work investigating the evolution of seed size should be cautious given that phylogeny is the best overall predictor for seed mass. Our study provides a novel avenue for clarifying variation in functional traits across plant species, improving our better understanding of global patterns in plant traits

High-Dose siRNAs Upregulate Mouse Eri-1 at both Transcription and Posttranscription Levels

The eri-1 gene encodes a 3′ exonuclease that can negatively regulate RNA interference via siRNase activity. High-dose siRNAs (hd-siRNAs) can enhance Eri-1 expression, which in return degrade siRNAs and greatly reduces RNAi efficiency. Here we report that hd-siRNAs induce mouse Eri-1 (meri-1) expression through the recruitment of Sp1, Ets-1, and STAT3 to the meri-1 promoter and the formation of an Sp1-Ets-1-STAT3 complex. In addition, hd-siRNAs also abolish the 3′ untranslated region (UTR) mediated posttranscriptional repression of meri-1. Our findings demonstrate the molecular mechanism underlying the upregulation of meri-1 by hd-siRNA

Microfluidic label-free selection of mesenchymal stem cell subpopulation during culture expansion extends the chondrogenic potential

Mesenchymal stem cells (MSCs) have been shown as potential candidates for cell-based therapies for a diverse range of tissue regenerative applications. Therapeutic use of MSCs usually requires culture expansion, which increases the heterogeneity of MSCs in vitro, thus affecting the potency of the MSCs for more specific indications. The capacity for identifying and isolating special subsets of MSCs for treatment of specific diseases therefore holds great clinical significance. An important therapeutic application of MSC is for the regeneration of cartilage tissue. We and others have previously developed label-free microfluidic means to isolate subpopulations of culture expanded MSCs based on distinct biophysical characteristics. Here we utilize a spiral micro-channel device to separate culture expanded MSCs into five subgroups according to cell size, and study their proliferation and chondrogenesis at early, middle and late passages. Results show that in all passages, the medium-size subpopulation (cell size of 17-21 μm), compared to other subpopulations, displays significantly higher proliferation rate and chondrogenic capacity in terms of cartilage extracellular matrix formation. Also, the small cell subpopulation (average cell size of 11-12 μm) shows lower viability, and large cell subpopulation (average cell size 23-25 μm) expresses higher level of senescence-associated β-galactosidase. Finally, we show that repeated microfluidic exclusion of MSCs larger than 21 μm and smaller than 17 μm at every passage during continuous culture expansion result in selected MSCs with faster proliferation and better chondrogenic potential as compared to MSC derived from conventional expansion approach. This study demonstrates the significant merit and utility of size-based cell selection for the application of MSCs in cartilage regeneration

Reliability Evaluation of NC Machine Tools considering Working Conditions

Reliability evaluation is the basis for reliability design of NC machine tools. Since traditional reliability evaluation methods do not consider the working conditions' effects on reliability, there is a great error of a result of a traditional method compared with an actual value. A new reliability evaluation model of NC machine tools is proposed based on the Cox proportional hazards model, which describes the mathematical relation between the working condition covariates and the reliability level of NC machine tools. Firstly, the coefficients of working condition covariates in the new reliability evaluation model are estimated by the partial likelihood estimation method; secondly, the working condition covariates which have no effects on the reliability of NC machine tools are eliminated by the likelihood ratio test; then parameters of the baseline failure rate function are estimated by the maximum likelihood estimation method. Thus, the reliability evaluation model of NC machine tool is obtained under different working conditions and the reliability level of NC machine tools is obtained. Case study shows that the proposed method could establish the relation between the working condition covariates and the reliability level of NC machine tools, and it would provide a new way for the reliability evaluation of NC machine tools

Accuracy of steps measured by smartphones-based WeRun compared with ActiGraph-GT3X accelerometer in free-living conditions

ObjectivesThe purpose of this study was to evaluate the accuracy and reliability of steps tracked by smartphone-based WeChat app compared with Actigraph-GT3X accelerometer in free-living conditions.DesignA cross-sectional study and repeated measures.MethodsA total of 103 employees in the Pudong New Area of Shanghai, China, participated in this study. The participants wore an ActiGraph-GT3X accelerometer during the period of August to September 2019 (Time 1), December 2019 (Time 2) and September 2020 (Time 3). Each time, they wore the ActiGraph-GT3X accelerometer continuously for 7 days to assess their 7-day step counts. The smartphone-based WeRun step counts were collected in the corresponding period when subjects wore accelerometers. The subjects were invited to complete basic demographic characteristics questionnaires and to perform physical examination to obtain health-related results such as height, body weight, body fat percentage, waist circumference, hip circumference, and blood pressure.ResultsBased on 103 participants' 21 days of data, we found that the Spearman correlation coefficient between them was 0.733 (P < 0.01). The average number of WeRun steps measured by smartphones was 8,975 (4,059) per day, which was higher than those measured by accelerometers (8,462 ± 3,486 per day, P < 0.01). Demographic characteristics and different conditions can affect the consistency of measurements. The consistency was higher in those who were male, older, master's degree and above educated, and traveled by walking. Steps measured by smartphone and accelerometer in working days and August showed stronger correlation than other working conditions and time. Mean absolute percent error (MAPE) for step counts ranged from 0.5 to 15.9%. The test-retest reliability coefficients of WeRun steps ranged from 0.392 to 0.646. A multiple regression analysis adjusted for age, gender, and MVPA/step counts measured during Time 1 showed that body composition (body weight, BMI, body fat percentage, waist circumference, and hip circumference) was correlated with moderate-to-vigorous intensity physical activity, but it was not correlated with WeRun step counts.ConclusionsThe smartphone-based WeChat app can be used to assess physical activity step counts and is a reliable tool for measuring steps in free-living conditions. However, WeRun step counts' utilization is potentially limited in predicting body composition