Contribution of exopeptidases to formation of nonprotein nitrogen during ensiling of alfalfa

The experiment was conducted to investigate the exopeptidase classes in alfalfa (Medicago sativa L.) leaves, and to determine their contribution to the formation of nonprotein nitrogen (NPN) components during ensiling. Six classes of inhibitors that included bestatin (aminopeptidase inhibitor), potato carboxypeptidase inhibitor (PCI, carboxypeptidase inhibitor), 1,10-phenanthroline (dipeptidase inhibitor), diprotin A (dipeptidyl-peptidase inhibitor), butabindide (tripeptidyl-peptidase inhibitor), and dipeptide Phe-Arg (peptidyl-dipeptidase inhibitor) were used. To determine the contribution of each exopeptidase to the formation of NPN products, aqueous extracts of fresh alfalfa were fermented to imitate the proteolytic process of ensiled alfalfa and to ensure that each class of exopeptidase inhibitor would have immediate contact with the proteases in the alfalfa extract. Five classes of exopeptidases; namely, aminopeptidase, carboxypeptidase, dipeptidase, dipeptidyl-peptidase, and tripeptidyl-peptidase, were shown to be present in alfalfa leaves, each playing a different role in alfalfa protein degradation. Aminopeptidase, carboxypeptidase, and dipeptidase were the main exopeptidases contributing to the formation of NH3-N. Among the 5 exopeptidases, tripeptidyl-peptidase appeared to be the principal exopeptidase in hydrolyzing forage protein into peptides, whereas carboxypeptidase and dipeptidase appeared to be more important in contributing to the formation of amino acid-N. Dipeptidyl-peptidase and tripeptidyl-peptidase did not play a role in the formation of NH3-N or amino acid-N. Dipeptidase, carboxypeptidase, and tripeptidyl-peptidase were the principal exopeptidases for hydrolyzing forage protein into NPN during ensilage, and treatment with a mixture of the 5 inhibitors reduced the total NPN concentration in the fermented alfalfa extract to about 45% of that in the control after 21 d of fermentation

Designing ultrafine lamellar eutectic structure in bimodal titanium alloys by semi-solid sintering

We report on a novel approach to design typical ultrafine lamellar eutectic structure in bimodal alloys fabricated by semi-solid sintering (SSS) of a eutectic mixture. In our work ultrafine lamellar eutectic structure was implemented by controlling the phase composition of eutectic reaction and consequently by regulating the structure of eutectic reaction-induced liquid phase through varying component number. Microstructure analysis indicate that although all SSSed alloys have the same three phase constitutions of bcc beta-Ti(Fe Co) and fcc Ti-2(Co Fe) the morphology and distribution of the eutectic structure transforms from limited length and minor quantity to partial fine alternating bcc beta-Ti and bcc Ti(Fe Co) lamellae and further to typical complete ultrafine alternating continuous lamellae in the SSSed ternary Ti-Fe-Co quaternary Ti-Fe-Co-Nb and quinary Ti-Fe-Co-Nb-Al alloys. Interestingly the SSSed Ti-Fe-Co-Nb-Al alloy presents a novel bimodal microstructure of coarse fcc Ti-2(Co Fe) surrounded by an ultrafine lamellar eutectic matrix containing ultrafine bcc beta-Ti and bcc Ti(Fe Co) lamellae. This bimodal microstructure exhibits ultra-high yield strength of 2050 MPa with plasticity in compression of 19.7% which exceed published values of equivalent materials. Our results provide a novel pathway for fabricating new-structure metallic alloys for high-performance structural applications. (C) 2017 Elsevier B.V. All rights reserved.</p

Back stress strengthening and strain hardening in gradient structure

We report significant back stress strengthening and strain hardening in gradient structured (GS) interstitial-free (IF) steel. Back stress is long-range stress caused by the pileup of geometrically necessary dislocations (GNDs). A simple equation and a procedure are developed to calculate back stress basing on its formation physics from the tensile unloading-reloading hysteresis loop. The gradient structure has mechanical incompatibility due to its grain size gradient. This induces strain gradient, which needs to be accommodated by GNDs. Back stress not only raises the yield strength but also significantly enhances strain hardening to increase the ductility. [GRAPHICS]

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Passenger-Oriented Timetable Rescheduling in Railway Disruption Management

Railway systems are vulnerable to unexpected disruptions, which usually result in track blockages for a few hours. In practice, disruptions are handled manually and the resulting impact to passengers is rarely considered. To enable disruption management more efficiently, operator-friendly and passenger-friendly, this thesis develops mathematical models and solution methods for dynamic passenger assignment, timetable rescheduling, and the integrated passenger assignment with timetable rescheduling during disruptions.TRAIL Thesis Series no. T2019/16, The Netherlands TRAIL Research SchoolTransport and Plannin

Attack pattern ontology: A common language for attack information sharing between organizations

Cyber attack nowadays is increasingly being reported. Defenders need a good understanding of attacker’s perspective in order to accurately anticipate threats and effectively mitigate attacks. This understanding can be obtained through sharing attack pattern. However, in the existing researches the consideration about information sharing is not integrated into the attack pattern concept. In this paper, we propose an attack pattern ontology as a common language of information sharing; the goal is to demonstrate how this ontology may effectively support cyber security information sharing. Based on the existing theories about attack pattern, we developed an ontological model to present attack information. The research can be further developed to integrate attacker profile ontology with the attack pattern ontology, which enables more systematic analysis of cyber attacks.Information and communication technologyTechnology, Policy and Managemen

On predicting individual video viewing experience: The value of user information

Experience prediction is one key component in today’s multimedia delivery. Knowing user’s viewing experience allows online video service providers (e.g., Netflix, YouTube) to create value for their customers by providing personalized content and service. However, individual experience prediction is a challenging problem since viewing experience (defined as Quality of Experience in this thesis) is a multifaceted quantity and it is rather personal and subjective. The existing methods for quantifying Quality of Experience (QoE) target at estimating how the video quality is perceived by users, neglecting the hedonic part of experience (the degree of enjoyment of a user watching a video). Quite naturally, these methods consider only factors related to video perceptual quality (purely from video), which is insufficient to properly assess viewing experience. The research reported in this thesis attempts for the first time at shifting the paradigm for perceptual quality modeling, towards measuring and predicting the level of enjoyable viewing experience a user has with a video. In particular, it focuses on exploiting the potential value of user factors (information from users) and investigate their influences on QoE prediction.The goal of this thesis is to develop a feasible method for predicting the individual viewing experiences in terms of perceptual quality and enjoyment by taking multiple influencing factors into account. Here, the influencing factors are taken from both video (e.g., related to perceptual quality) and user (user factors, e.g., interest. personality). We take three major steps to accomplish this goal. We first deploy a subjective experiment to understand the relationship between perceptual quality and enjoyment, and how their influencing factors form the final viewing experience. With a set of identified influencing factors, we then propose a new QoE prediction model which processes both user and video information to predict individual experience (i.e., either perceptual quality or enjoyment). We show that combining information from video and user enables better prediction performance as compared to only considering information from video related to perceptual quality. Our third step tackles the problem of reliable data collection for the individual QoE research. We developed an open-sourced Facebook application, named YouQ, as an experimental platform for automatic user information collection from social media while performing an online QoE subjective experiment. We show that YouQ can produce reliable results as compared to a controlled laboratory experiment, both in terms of QoE and of quantification of user factors and traits. As a result, a complete, feasible method for individual QoE prediction is presented in this thesis. Based on the findings presented in this thesis, we reflect on the contribution and make recommendations for future research directions, which we think are substantial and promising for individual QoE prediction.Multimedia Computin