Bringing Context Inside Process Research with Digital Trace Data

Context is usually conceptualized as “external” to a theory or model and treated as something to be controlled or eliminated in empirical research. We depart from this tradition and conceptualize context as permeating processual phenomena. This move is possible because digital trace data are now increasingly available, providing rich and fine-grained data about processes mediated or enabled by digital technologies. This paper introduces a novel method for including fine-grained contextual information from digital trace data within the description of process (e.g., who, what, when, where, why). Adding contextual information can result in a very large number of fine-grained categories of events, which are usually considered undesirable. However, we argue that a large number of categories can make process data more informative for theorizing and that including contextual detail enriches the understanding of processes as they unfold. We demonstrate this by analyzing audit trail data of electronic medical records using ThreadNet, an open source software application developed for the qualitative visualization and analysis of process data. The distinctive contribution of our approach is the novel way in which we contextualize events and action in process data. Providing new, usable ways to incorporate context can help researchers ask new questions about the dynamics of processual phenomena

Process multiplicity and process dynamics : weaving the space of possible paths

In research on process organization studies, the concept of multiplicity is widely used, but a fundamental confusion about what process multiplicity means persists. As a result, we miss some of the potential of this concept for understanding process dynamics and process change. In this paper, we define process multiplicity as a duality of ‘one’ and ‘many’, and we conceptualize ‘the many’ as a space of possible paths encompassed by a process. We use the notion of paths to operationalize process multiplicity and make it accessible for empirical research. When we see process as a multiplicity, process change can be understood as expanding, shifting or contracting the space of possible paths. We suggest that this concept of process multiplicity also has implications for a range of other theoretical and practical topics, including standards, standardization and flexibility as well as process replication, management and resilience

Initial Training for Mental Health Peer Support Workers: Systematized Review and International Delphi Consultation.

BACKGROUND: Initial training is essential for the mental health peer support worker (PSW) role. Training needs to incorporate recent advances in digital peer support and the increase of peer support work roles internationally. There is a lack of evidence on training topics that are important for initial peer support work training and on which training topics can be provided on the internet. OBJECTIVE: The objective of this study is to establish consensus levels about the content of initial training for mental health PSWs and the extent to which each identified topic can be delivered over the internet. METHODS: A systematized review was conducted to identify a preliminary list of training topics from existing training manuals. Three rounds of Delphi consultation were then conducted to establish the importance and web-based deliverability of each topic. In round 1, participants were asked to rate the training topics for importance, and the topic list was refined. In rounds 2 and 3, participants were asked to rate each topic for importance and the extent to which they could be delivered over the internet. RESULTS: The systematized review identified 32 training manuals from 14 countries: Argentina, Australia, Brazil, Canada, Chile, Germany, Ireland, the Netherlands, Norway, Scotland, Sweden, Uganda, the United Kingdom, and the United States. These were synthesized to develop a preliminary list of 18 topics. The Delphi consultation involved 110 participants (49 PSWs, 36 managers, and 25 researchers) from 21 countries (14 high-income, 5 middle-income, and 2 low-income countries). After the Delphi consultation (round 1: n=110; round 2: n=89; and round 3: n=82), 20 training topics (18 universal and 2 context-specific) were identified. There was a strong consensus about the importance of five topics: lived experience as an asset, ethics, PSW well-being, and PSW role focus on recovery and communication, with a moderate consensus for all other topics apart from the knowledge of mental health. There was no clear pattern of differences among PSW, manager, and researcher ratings of importance or between responses from participants in countries with different resource levels. All training topics were identified with a strong consensus as being deliverable through blended web-based and face-to-face training (rating 1) or fully deliverable on the internet with moderation (rating 2), with none identified as only deliverable through face-to-face teaching (rating 0) or deliverable fully on the web as a stand-alone course without moderation (rating 3). CONCLUSIONS: The 20 training topics identified can be recommended for inclusion in the curriculum of initial training programs for PSWs. Further research on web-based delivery of initial training is needed to understand the role of web-based moderation and whether web-based training better prepares recipients to deliver web-based peer support

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

Beliefs About Medication and Uptake of Preventive Therapy in Women at Increased Risk of Breast Cancer: Results From a Multicenter Prospective Study

Introduction Uptake of preventive therapies for breast cancer is low. We examined whether women at increased risk of breast cancer can be categorized into groups with similar medication beliefs, and whether belief group membership was prospectively associated with uptake of preventive therapy. Patients and Methods Women (n = 732) attending an appointment to discuss breast cancer risk were approached; 408 (55.7%) completed the Beliefs About Medicines and the Perceived Sensitivity to Medicines questionnaires. Uptake of tamoxifen at 3 months was reported in 258 (63.2%). The optimal number of belief groups were identified using latent profile analysis. Results Uptake of tamoxifen was 14.7% (38/258). One in 5 women (19.4%; 78/402) reported a strong need for tamoxifen. The model fit statistics supported a 2-group model. Both groups held weak beliefs about their need for tamoxifen for current and future health. Group 2 (38%; 154/406 of the sample) reported stronger concerns about tamoxifen and medicines in general, and stronger perceived sensitivity to the negative effects of medicines compared with group 1 (62%; 252/406). Women with low necessity and lower concerns (group 1) were more likely to initiate tamoxifen (18.3%; 33/180) than those with low necessity and higher concerns (group 2) (6.4%; 5/78). After adjusting for demographic and clinical factors, the odds ratio was 3.37 (95% confidence interval, 1.08-10.51; P = .036). Conclusion Uptake of breast cancer preventive therapy was low. A subgroup of women reported low need for preventive therapy and strong medication concerns. These women were less likely to initiate tamoxifen. Medication beliefs are targets for supporting informed decision-making

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis