The Current Status of Immune Checkpoint Inhibitors in Neuro-Oncology:A Systematic Review

The introduction of immune checkpoint inhibitors (ICI), as a novel treatment modality, has transformed the field of oncology with unprecedented successes. However, the efficacy of ICI for patients with glioblastoma or brain metastases (BMs) from any tumor type is under debate. Therefore, we systematically reviewed current literature on the use of ICI in patients with glioblastoma and BMs. Prospective and retrospective studies evaluating the efficacy and survival outcomes of ICI in patients with glioblastoma or BMs, and published between 2006 and November 2019, were considered. A total of 88 studies were identified (n = 8 in glioblastoma and n = 80 in BMs). In glioblastoma, median progression-free (PFS) and overall survival (OS) of all studies were 2.1 and 7.3 months, respectively. In patients with BMs, intracranial responses have been reported in studies with melanoma and non-small-cell lung cancer (NSCLC). The median intracranial and total PFS in these studies were 2.7 and 3.0 months, respectively. The median OS in all studies for patients with brain BMs was 8.0 months. To date, ICI demonstrate limited efficacy in patients with glioblastoma or BMs. Future research should focus on increasing the local and systemic immunological responses in these patients

NEXT: Generating tailored ERP applications from ontological enterprise models

Tailoring Enterprise Resource Planning (ERP) software to the needs of the enterprise still is a technical endeavor, often requiring the (de)activation of modules, modification of configuration files or even execution of database queries. Considering the large body of work on Enterprise Modeling and Model-Driven Software Engineering, this is remarkable: Ideally, one models one’s own enterprise and, at the press of a button, ERP software tailored to the needs of the modeled enterprise is generated. In this paper, we introduce NEXT, a novel model-driven software generation approach being developed with precisely this goal in mind. It uses the expressive power of ontological enterprise models (OEMs) to generate ERP cloud applications. An OEM only describes the real-world phenomena essential to the enterprise, using terms and customizations specific to the enterprise. We present our considerations during development of the OEM modeling language, which is designed to capture the specifics of enterprise phenomena in a way that technical details can be derived from it. We expect NEXT to drastically shorten the time-to-market of ERP software, from months–years to hours–days

Chromatic periodic activity down to 120 MHz in a Fast Radio Burst

Fast radio bursts (FRBs) are extragalactic astrophysical transients whose brightness requires emitters that are highly energetic, yet compact enough to produce the short, millisecond-duration bursts. FRBs have thus far been detected between 300 MHz and 8 GHz, but lower-frequency emission has remained elusive. A subset of FRBs is known to repeat, and one of those sources, FRB 20180916B, does so with a 16.3 day activity period. Using simultaneous Apertif and LOFAR data, we show that FRB 20180916B emits down to 120 MHz, and that its activity window is both narrower and earlier at higher frequencies. Binary wind interaction models predict a narrower periodic activity window at lower frequencies, which is the opposite of our observations. Our detections establish that low-frequency FRB emission can escape the local medium. For bursts of the same fluence, FRB 20180916B is more active below 200 MHz than at 1.4 GHz. Combining our results with previous upper-limits on the all-sky FRB rate at 150 MHz, we find that there are 3-450 FRBs/sky/day above 50 Jy ms at 90% confidence. We are able to rule out the scenario in which companion winds cause FRB periodicity. We also demonstrate that some FRBs live in clean environments that do not absorb or scatter low-frequency radiation.Comment: 50 pages, 14 figures, 3 tables, submitte

Why Factor Analysis Often is the Incorrect Model for Analyzing Bipolar Concepts, and What Model to Use Instead

Factor analysis of data that conform to the unfolding model often results in an extra factor. This artificial extra factor is particularly important when data that conform to a bipolar unidimensional unfolding scale are factor analyzed. One bipolar dimension is expected, but two factors are found and often are interpreted as two unrelated dimensions. Although this extra factor phenomenon was pointed out in the early 1960s, it still is not widely recognized. The extra factor phenomenon in the unidimensional case is reviewed here. A numerical illustration is provided, and a number of diagnostics that can be used to determine whether data conform to the unidimensional unfolding model better than to the factor model are discussed. These diagnostics then are applied to an empirical example. Index terms: factor analysis, factor interpretation problems, rating scales, unfolding diagnostics, unfolding model

If the SOK Fits, Wear It: Pragmatic Process Improvement through Software Operation Knowledge

Abstract. Knowledge of in-the-field software operation is nowadays acquired by many software-producing organizations. Vendors are effective in acquiring large amounts of valuable software operation data to improve the quality of their software products. For many vendors, however, it remains unclear how their actual product software processes can be advanced through structural integration of such information. In this paper, we present a template method for integration of software operation information with product software processes, and present four lessons learned that are identified based on a canonical action research study of ten months, during which the method was instantiated at a European software vendor. Results show that the template method contributes to significant software quality increase, by pragmatic but measurable improvement of software processes, without adhering to strict requirements from cumbersome maturity models or process improvement frameworks

The Power of Propagation: On the Role of Software Operation Knowledge within Software Ecosystems

ABSTRACT Knowledge of in-the-field software operation is still unrecognized as an essential pulse in the veins of software ecosystems. Although software-producing organizations are aware of the ecosystems in which they operate and their relationships with other ecosystem participants, all too often, vendors are unsuccessful in recognizing the potential value and role of such knowledge in their software ecosystems. This paper presents a classification of successful operational software ecosystem practices that may help software-producing organizations to effectively utilize and propagate knowledge of the in-the-field operation of their software, and therewith address challenges that result from ecosystem participation. Analysis of these practices confirms that infrastructures for acquisition, utilization and propagation of such knowledge, allow ecosystem participants to use the 'power of many' in increasing the quality and robustness of their software, and provide them with competitive advantage in terms of software quality, end-user satisfaction, ecosystem stability and ecosystem attractiveness

NEXT: Generating Tailored ERP Applications from Ontological Enterprise Models

Part 1: Regular PapersInternational audienceTailoring Enterprise Resource Planning (ERP) software to the needs of the enterprise still is a technical endeavor, often requiring the (de)activation of modules, modification of configuration files or even execution of database queries. Considering the large body of work on Enterprise Modeling and Model-Driven Software Engineering, this is remarkable: Ideally, one models one’s own enterprise and, at the press of a button, ERP software tailored to the needs of the modeled enterprise is generated. In this paper, we introduce NEXT, a novel model-driven software generation approach being developed with precisely this goal in mind. It uses the expressive power of ontological enterprise models (OEMs) to generate ERP cloud applications. An OEM only describes the real-world phenomena essential to the enterprise, using terms and customizations specific to the enterprise. We present our considerations during development of the OEM modeling language, which is designed to capture the specifics of enterprise phenomena in a way that technical details can be derived from it. We expect NEXT to drastically shorten the time-to-market of ERP software, from months–years to hours–days

NEXT: Generating tailored ERP applications from ontological enterprise models

Tailoring Enterprise Resource Planning (ERP) software to the needs of the enterprise still is a technical endeavor, often requiring the (de)activation of modules, modification of configuration files or even execution of database queries. Considering the large body of work on Enterprise Modeling and Model-Driven Software Engineering, this is remarkable: Ideally, one models one’s own enterprise and, at the press of a button, ERP software tailored to the needs of the modeled enterprise is generated. In this paper, we introduce NEXT, a novel model-driven software generation approach being developed with precisely this goal in mind. It uses the expressive power of ontological enterprise models (OEMs) to generate ERP cloud applications. An OEM only describes the real-world phenomena essential to the enterprise, using terms and customizations specific to the enterprise. We present our considerations during development of the OEM modeling language, which is designed to capture the specifics of enterprise phenomena in a way that technical details can be derived from it. We expect NEXT to drastically shorten the time-to-market of ERP software, from months–years to hours–days