A Systematic Tradeoff Methodology for Acquiring and Validating Imprecise Requirements

Requirement analysis is one of the most important phases in a software development process. Existing requirement methodologies are limited in specifying requirements that are usually vague and imprecise, and in supporting tradeoff analysis between the conflicting requirements. In this paper, the elasticity of imprecise requirements is captured using fuzzy logic to facilitate tradeoffs between conflicting requirements. Based on the marginal rate of substitution in decision science, we have developed a systematic approach to elicit the structures and the parameters of imprecise requirements, to validate the scheme for aggregating requirements, and to assess relative priorities of conflicting requirements

Authenticated Key Agreement Protocol Based on a Matrix Group and Polynomial Ring over a Finite Field

Alongside encryption and signatures, key agreement is one of the fundamental issues in modern cryptography and its security is the main concern in cloud computing and World Wide Web-based applications. In this paper, a novel type of more secure 3-pass key agreement protocol is proposed based on a recently proposed matrix-based key agreement protocol of Romańczuk and Ustimenko. By the hash-and-sign approach and immediate use of new session key, explicit key authentication, forward secrecy and bit security are achieved simultaneously. Cryptanalysis also shows that it is immune to the man-in-the-middle attack while matrix entries from a commutative ring provide an advantageous hiding mechanism

Human motion data refinement unitizing structural sparsity and spatial-temporal information

Human motion capture techniques (MOCAP) are widely applied in many areas such as computer vision, computer animation, digital effect and virtual reality. Even with professional MOCAP system, the acquired motion data still always contains noise and outliers, which highlights the need for the essential motion refinement methods. In recent years, many approaches for motion refinement have been developed, including signal processing based methods, sparse coding based methods and low-rank matrix completion based methods. However, motion refinement is still a challenging task due to the complexity and diversity of human motion. In this paper, we propose a data-driven-based human motion refinement approach by exploiting the structural sparsity and spatio-temporal information embedded in motion data. First of all, a human partial model is applied to replace the entire pose model for a better feature representation to exploit the abundant local body posture. Then, a dictionary learning which is for special task of motion refinement is designed and applied in parallel. Meanwhile, the objective function is derived by taking the statistical and locality property of motion data into account. Compared with several state-of-art motion refine methods, the experimental result demonstrates that our approach outperforms the competitors

PTH1-34 Alleviates Radiotherapy-Induced Local Bone Loss by Improving Osteoblast and Osteocyte Survival

Cancer radiotherapy is often complicated by a spectrum of changes in the neighboring bone from mild osteopenia to osteoradionecrosis. We previously reported that parathyroid hormone (PTH, 1–34), an anabolic agent for osteoporosis, reversed bone structural deterioration caused by multiple microcomputed tomography (microCT) scans in adolescent rats. To simulate clinical radiotherapy for cancer patients and to search for remedies, we focally irradiated the tibial metaphyseal region of adult rats with a newly available small animal radiation research platform (SARRP) and treated these rats with intermittent injections of PTH1–34. Using a unique 3D image registration method that we recently developed, we traced the local changes of the same trabecular bone before and after treatments, and observed that, while radiation caused a loss of small trabecular elements leading to significant decreases in bone mass and strength, PTH1–34 preserved all trabecular elements in irradiated bone with remarkable increases in bone mass and strength. Histomorphometry demonstrated that SARRP radiation severely reduced osteoblast number and activity, which were impressively reversed by PTH treatment. In contrast, suppressing bone resorption by alendronate failed to rescue radiation-induced bone loss and to block the rescue effect of PTH1–34. Furthermore, histological analyses revealed that PTH1–34 protected osteoblasts and osteocytes from radiation-induced apoptosis and attenuated radiation-induced bone marrow adiposity. Taken together, our data strongly support a robust radioprotective effect of PTH on trabecular bone integrity through preserving bone formation and shed light on further investigations of an anabolic therapy for radiation-induced bone damage

Xanthine oxidoreductase promotes the inflammatory state of mononuclear phagocytes through effects on chemokine expression, peroxisome proliferator-activated receptor-gamma sumoylation, and HIF-₁ alpha

The protective effects of pharmacological inhibitors of xanthine oxidoreductase (XOR) have implicated XOR in many inflammatory diseases. Nonetheless, the role played by XOR during inflammation is poorly understood. We previously observed that inhibition of XOR within the inflammatory mononuclear phagocytes (MNP) prevented neutrophil recruitment during adoptive transfer demonstrating the role of XOR in MNP-mediated neutrophil recruitment. To further explore the role of XOR in the inflammatory state of MNP, we studied MNP isolated from inflammatory lungs combined with analyses of MNP cell lines. We demonstrated that XOR activity was increased in inflammatory MNP following insufflation of Th-1 cytokines in vivo and that activity was specifically increased by MNP differentiation. Inhibition of XOR reduced levels of CINC-1 secreted by MNP. Expression of peroxisome proliferator-activated receptor γ (PPARγ) in purified rat lung MNP and MNP cell lines reflected both the presence of PPARγ isoforms and PPARγ SUMOylation, and XOR inhibitors increased levels of SUMO-PPARγ in MNP cell lines. Both ectopic overexpression of XOR cDNA and uric acid supplementation reduced SUMO-PPARγ in MNP cells. Levels of the M2 markers CD36, CD206, and arginase-1 were modulated by uric acid and oxonic acid, whereas siRNA to SUMO-1 or PIAS-1 also reduced arginase-1 in RAW264.7 cells. We also observed that HIF-1α was increased by XOR inhibitors in inflammatory MNP and in MNP cell lines. These data demonstrate that XOR promotes the inflammatory state of MNP through effects on chemokine expression, PPARγ SUMOylation, and HIF-1α and suggest that strategies for inhibiting XOR may be valuable in modulating lung inflammatory disorders

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

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

Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis.

Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis