Learning Human Aspects of Collaborative Software Development

Collaboration has become increasingly widespread in the software industry as systems have become larger and more complex, adding human complexity to the technological complexity already involved in developing software systems. To deal with this complexity, human-centric software development methods, such as Extreme Programming and other agile methods, have been developed and implemented. Aiming to prepare future software developers for today\u27s software industry, this paper presents a framework for developing collaborative learning tools and activities, and examples that were developed for the course Human Aspects of Software Engineering in order to assist students in learning collaborative software development. The learning processes and knowledge construction undergone by the students in the study were examined empirically, both in general and with respect to collaboration in particular. Results indicate that, based on their individual and group in-class experiences and reflections, students developed skills and constructed both practical and theoretical knowledge relating to successful collaborative software development

Enhancing Software Architecture Review Process via Knowledge Management

Software architecture is considered to have a significant influence on the final software product’s quality. A critical phase in ensuring and validating the quality of a suggested architecture is architecture review, conducted by experienced architects. While many evaluation methods have been researched thus far in the context of architecture review, little attention has been given to the review process and to the knowledge-related aspects embedded within it. In this paper we explore and analyze the architecture review process based on literature as well as empirical evidence obtained in a case study conducted in a large software development firm. For the aim of enhancing the review process to a systematic and scalable process, as well as expending its value to future architecture in addition to the reviewed artifacts, this research investigates the knowledge aspects of the review process and suggests a conceptual solution for enhancing the review process and embedding knowledge management within it

Investigating the growing population of massive quiescent galaxies at cosmic noon

We explore the build-up of quiescent galaxies using a sample of 28 469 massive (M⋆ ≥ 1011 M☉) galaxies at redshifts 1.5 < zz < 3.0, drawn from a 17.5 deg2 area (0.33 Gpc3 comoving volume at these redshifts). This allows for a robust study of the quiescent fraction as a function of mass at 1.5 < zz < 3.0 with a sample ∼40 times larger at log(M⋆/ M⊙)≥11.5M⊙)≥11.5 than previous studies. We derive the quiescent fraction using three methods: specific star formation rate, distance from the main sequence, and UVJ colour-colour selection. All three methods give similar values at 1.5 < zz < 2.0, however the results differ by up to a factor of 2 at 2.0 < zz < 3.0. At redshifts 1.5 < zz < 3.0, the quiescent fraction increases as a function of stellar mass. By zz = 2, only 3.3 Gyr after the big bang, the universe has quenched ∼25 per cent of M⋆ = 1011 M☉ galaxies and ∼45 per cent of M⋆ = 1012 M☉ galaxies. We discuss physical mechanisms across a range of epochs and environments that could explain our results. We compare our results with predictions from hydrodynamical simulations SIMBA and IllustrisTNG and semi-analytic models (SAMs) SAG, SAGE, and Galacticus. The quiescent fraction from IllustrisTNG is higher than our empirical result by a factor of 2-5, while those from SIMBA and the three SAMs are lower by a factor of 1.5-10 at 1.5 < zz < 3.0Fil: Sherman, Sydney. Department Of Astronomy; Estados UnidosFil: Jogee, Shardha. Department Of Astronomy; Estados UnidosFil: Florez, Jonathan. Department Of Astronomy; Estados UnidosFil: Stevans, Matthew L. Department Of Astronomy; Estados UnidosFil: Kawinwanichakij, Lalitwadee. Kavli Institute For The Physics And Mathematics Of The; JapónFil: Wold, Isak. Nasa Goddard Space Flight Center; Estados UnidosFil: Finkelstein, Steven L. Department Of Astronomy; Estados UnidosFil: Papovich, Casey. Department Of Physics And Astronomy; Estados UnidosFil: Ciardullo, Robin. Department Of Astronomy And Astrophysics; Estados UnidosFil: Gronwall, Caryl. Department Of Astronomy And Astrophysics; Estados UnidosFil: Cora, Sofia Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Hough, Tomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Vega Martínez, Cristian Antonio. Instituto de Investigación Multidisciplinar En Ciencia; Chil

The mating-specific Gα interacts with a kinesin-14 and regulates pheromone-induced nuclear migration in budding yeast

As a budding yeast cell elongates toward its mating partner, cytoplasmic microtubules connect the nucleus to the cell cortex at the growth tip. The Kar3 kinesin-like motor protein is then thought to stimulate plus-end depolymerization of these microtubules, thus drawing the nucleus closer to the site where cell fusion and karyogamy will occur. Here, we show that pheromone stimulates a microtubule-independent interaction between Kar3 and the mating-specific Gα protein Gpa1 and that Gpa1 affects both microtubule orientation and cortical contact. The membrane localization of Gpa1 was found to polarize early in the mating response, at about the same time that the microtubules begin to attach to the incipient growth site. In the absence of Gpa1, microtubules lose contact with the cortex upon shrinking and Kar3 is improperly localized, suggesting that Gpa1 is a cortical anchor for Kar3. We infer that Gpa1 serves as a positional determinant for Kar3-bound microtubule plus ends during mating. © 2009 by The American Society for Cell Biology

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Diversity and Relatedness Enhance Survival in Colour Polymorphic Grasshoppers

Evolutionary theory predicts that different resource utilization and behaviour by alternative phenotypes may reduce competition and enhance productivity and individual performance in polymorphic, as compared with monomorphic, groups of individuals. However, firm evidence that members of more heterogeneous groups benefit from enhanced survival has been scarce or lacking. Furthermore, benefits associated with phenotypic diversity may be counterbalanced by costs mediated by reduced relatedness, since closely related individuals typically are more similar. Pygmy grasshoppers (Tetrix subulata) are characterized by extensive polymorphism in colour pattern, morphology, behaviour and physiology. We studied experimental groups founded by different numbers of mothers and found that survival was higher in low than in high density, that survival peaked at intermediate colour morph diversity in high density, and that survival was independent of diversity in low density where competition was less intense. We further demonstrate that survival was enhanced by relatedness, as expected if antagonistic and competitive interactions are discriminately directed towards non-siblings. We therefore also performed behavioural observations and staged encounters which confirmed that individuals recognized and responded differently to siblings than to non-siblings. We conclude that negative effects associated with competition are less manifest in diverse groups, that there is conflicting selection for and against genetic diversity occurring simultaneously, and that diversity and relatedness may facilitate the productivity and ecological success of groups of interacting individuals