SCRUM-PSP: Embracing Process Agility and Discipline

Abstract—With the research and debates on software process, the mainstream software processes can be grouped into two categories, the plan-driven (disciplined) processes and the agile processes. In terms of the classification, personal software process (PSP) is a typical plan-driven process while SCRUM is an agile-style instance. Although they are distinct from each other per se, our research found that PSP and SCRUM may also complement each other when SCRUM provides an agile process management framework, and PSP provides the skills and disciplines that a qualified team member needs to estimate, plan and manage his/her job. This paper proposes an integrated process model, SCRUM-PSP, which combines the strengths of each. We also verified that this integrated process by adopting it into a real project environment where typical agile processes are favored, i.e. change-prone requirements, rapid development, fast delivery, etc. As a result, manageability and predictability which traditional plan-driven processes usually benefit can also be achieved. The work described in this paper is a worthy attempt to embrace both process agility and discipline. Keywords- PSP SCRUM Integratio

Conversational Word Embedding for Retrieval-Based Dialog System

Human conversations contain many types of information, e.g., knowledge, common sense, and language habits. In this paper, we propose a conversational word embedding method named PR-Embedding, which utilizes the conversation pairs $\left\langle{post, reply} \right\rangle$ to learn word embedding. Different from previous works, PR-Embedding uses the vectors from two different semantic spaces to represent the words in post and reply. To catch the information among the pair, we first introduce the word alignment model from statistical machine translation to generate the cross-sentence window, then train the embedding on word-level and sentence-level. We evaluate the method on single-turn and multi-turn response selection tasks for retrieval-based dialog systems. The experiment results show that PR-Embedding can improve the quality of the selected response. PR-Embedding source code is available at https://github.com/wtma/PR-EmbeddingComment: To appear at ACL 202

Deficiency of IKKβ in neurons ameliorates Alzheimer's disease pathology in APP- and tau-transgenic mice

In Alzheimer's disease (AD) brain, inflammatory activation regulates protein levels of amyloid-β-peptide (Aβ) and phosphorylated tau (p-tau), as well as neurodegeneration; however, the regulatory mechanisms remain unclear. We constructed APP- and tau-transgenic AD mice with deletion of IKKβ specifically in neurons, and observed that IKKβ deficiency reduced cerebral Aβ and p-tau, and modified inflammatory activation in both AD mice. However, neuronal deficiency of IKKβ decreased apoptosis and maintained synaptic proteins (e.g., PSD-95 and Munc18-1) in the brain and improved cognitive function only in APP-transgenic mice, but not in tau-transgenic mice. Additionally, IKKβ deficiency decreased BACE1 protein and activity in APP-transgenic mouse brain and cultured SH-SY5Y cells. IKKβ deficiency increased expression of PP2A catalytic subunit isoform A, an enzyme dephosphorylating cerebral p-tau, in the brain of tau-transgenic mice. Interestingly, deficiency of IKKβ in neurons enhanced autophagy as indicated by the increased ratio of LC3B-II/I in brains of both APP- and tau-transgenic mice. Thus, IKKβ deficiency in neurons ameliorates AD-associated pathology in APPand tau-transgenic mice, perhaps by decreasing Aβ production, increasing p-tau dephosphorylation, and promoting autophagy-mediated degradation of BACE1 and p-tau aggregates in the brain. However, IKKβ deficiency differently protects neurons in APP- and tau-transgenic mice. Further studies are needed, particularly in the context of interaction between Aβ and p-tau, before IKKβ/NF-κB can be targeted for AD therapies

Gene expression profile analysis of human hepatocellular carcinoma using SAGE and LongSAGE

<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the second cancer killer in China. The initiation and malignant transformation of cancer result from accumulation of genetic changes in the sequences or expression level of cancer-related genes. It is of particular importance to determine gene expression profiles of cancers on a global scale. SAGE and LongSAGE have been developed for this purpose.</p> <p>Methods</p> <p>We performed SAGE in normal liver and HCC samples as well as the liver cancer cell line HepG2. Meanwhile, the same HCC sample was simultaneously analyzed using LongSAGE. Computational analysis was carried out to identify differentially expressed genes between normal liver and HCC which were further validated by real-time quantitative RT-PCR.</p> <p>Results</p> <p>Approximately 50,000 tags were sequenced for each of the four libraries. Analysis of the technical replicates of HCC indicated that excluding the low abundance tags, the reproducibility of SAGE data is high (R = 0.97). Compared with the gene expression profile of normal liver, 224 genes related to biosynthesis, cell proliferation, signal transduction, cellular metabolism and transport were identified to be differentially expressed in HCC. Overexpression of some transcripts selected from SAGE data was validated by real-time quantitative RT-PCR. Interestingly, sarcoglycan-ε (SGCE) and paternally expressed gene (PEG10) which is a pair of close neighboring genes on chromosome 7q21, showed similar enhanced expression patterns in HCC, implicating that a common mechanism of deregulation may be shared by these two genes.</p> <p>Conclusion</p> <p>Our study depicted the expression profile of HCC on a genome-wide scale without the restriction of annotation databases, and provided novel candidate genes that might be related to HCC.</p