Unraveling the MNE wage premium

Whereas IB has extensively studied MNEs’ generic (positive) impact on host economies, but rarely on employee wages, economics research has only shown an overall MNE wage premium. We ‘unravel’ this premium, considering multiple levels of analysis and accounting for host-country contextual contingencies, to unveil MNEs different (positive or negative) distributional effects. Using unique micro-level data from over 40,000 employees in 13 countries, we examine MNEs’ distributional effects for employees’ gender, experience, and immigrant status; the influence of host-country property rights protection and labor regulation; and interplays with region and industry effects. MNEs’ distributional effects show marked differences that largely depend on the host-country context, and that are positive for experienced and foreign-born employees in developed countries but negative for females working in developing countries. Whereas in developed countries the gender wage gap is smaller in MNEs than in domestic firms as hypothesized, we find evidence of a larger wage gap in developing countries. The analysis also reveals that the higher host-countries’ level of property rights protection, the lower the MNE wage premium. Our study points at the need to reassess statements about the generic positive impact of MNEs in host countries, particularly in developing countries, and discusses (further) research implications

PEN as self-vetoing structural Material

Polyethylene Naphtalate (PEN) is a mechanically very favorable polymer. Earlier it was found that thin foils made from PEN can have very high radio-purity compared to other commercially available foils. In fact, PEN is already in use for low background signal transmission applications (cables). Recently it has been realized that PEN also has favorable scintillating properties. In combination, this makes PEN a very promising candidate as a self-vetoing structural material in low background experiments. Components instrumented with light detectors could be built from PEN. This includes detector holders, detector containments, signal transmission links, etc. The current R\&D towards qualification of PEN as a self-vetoing low background structural material is be presented.Comment: 4 pages, 7 figures, contribution to Proceedings of the sixth workshop on Low Radioactivity Techniques 2017, 23-27 May 2017 Seoul, to be published at AIP, editor: D. Leonar

Three method factors explaining the low correlations between assessment center dimension ratings and scores on personality inventories

In general, correlations between assessment centre (AC) ratings and personality inventories are low. In this paper, we examine three method factors that may be responsible for these low correlations: differences in (i) rating source (other versus self), (ii) rating domain (general versus specific), and (iii) rating format (multi- versus single item). This study tests whether these three factors diminish correlations between AC exercise ratings and external indicators of similar dimensions. Ratings of personality and performance were combined in an analytical framework following a 2 × 2 × 2 (source, domain, format) completely crossed, within subjects design. Results showed partial support for the influence of each of the three method factors. Implications for future research are discussed. Copyright © 2004 John Wiley & Sons, Ltd

Charge dependent azimuthal correlations in Pb--Pb collisions at sNN=2.76\sqrt{s_{NN}} = 2.76 TeV

Separation of charges along the extreme magnetic field created in non-central relativistic heavy--ion collisions is predicted to be a signature of local parity violation in strong interactions. We report on results for charge dependent two particle azimuthal correlations with respect to the reaction plane for Pb--Pb collisions at $\sqrt{s_{NN}} = 2.76$ TeV recorded in 2010 with ALICE at the LHC. The results are compared with measurements at RHIC energies and against currently available model predictions for LHC. Systematic studies of possible background effects including comparison with conventional (parity-even) correlations simulated with Monte Carlo event generators of heavy--ion collisions are also presented.Comment: Published in the proceedings of "Quark Matter 2011", Annecy-Franc

Extending the IMQ Model:Deep Characterization of the Human TLR7 Response for Early Drug Development

Imiquimod (IMQ; brand name Aldara®) is a registered topical agent that has been proven to induce local inflammation via the Toll-like receptor (TLR)7 pathway. The purpose of this study was to characterize TLR7-mediated inflammation following 7 days (168 h) of topical IMQ exposure in healthy volunteers, and to compare the effects of short exposure (48 h-72 h) with prolonged exposure (120 h-168 h). IMQ (100mg) was applied under occlusion to 5 different tape-stripped treatment sites on the back of 10 healthy participants for a maximum of 7 consecutive days. Erythema and skin perfusion were measured daily up to 168h. Biopsies for immunohistochemical staining and RNA sequencing were collected at 0h, 48h, 72h, 120h and 168h post IMQ application. IMQ triggered an inflammatory response starting at 48h after application, including erythema and perfusion of the skin. At the transcriptomic level, IMQ induced TLR7 signalling, IRF involvement and activation of TNF signalling via NF-κB. Furthermore, an enhanced inflammatory response at the cellular level was observed after prolonged IMQ exposure, with cellular infiltration of dendritic cells, macrophages and T cells which was also corroborated by transcriptomic profiles. No difference was found in the erythema and perfusion response after 168h of IMQ exposure compared to 72h. Prolonged IMQ exposure revealed enhanced cellular responses and additional pathways with modulated activity compared to short exposure and can therefore be of interest as a model for investigational compounds targeting innate and adaptive immune responses.</p

CD34-related coexpression of MDR1 and BCRP indicates a clinically resistant phenotype in patients with acute myeloid leukemia (AML) of older age

Clinical resistance to chemotherapy in acute myeloid leukemia (AML) is associated with the expression of the multidrug resistance (MDR) proteins P-glycoprotein, encoded by the MDR1/ABCB1 gene, multidrug resistant-related protein (MRP/ABCC1), the lung resistance-related protein (LRP), or major vault protein (MVP), and the breast cancer resistance protein (BCRP/ABCG2). The clinical value of MDR1, MRP1, LRP/MVP, and BCRP messenger RNA (mRNA) expression was prospectively studied in 154 newly diagnosed AML patients ≥60 years who were treated in a multicenter, randomized phase 3 trial. Expression of MDR1 and BCRP showed a negative whereas MRP1 and LRP showed a positive correlation with high white blood cell count (respectively, p < 0.05, p < 0.001, p < 0.001 and p < 0.001). Higher BCRP mRNA was associated with secondary AML (p < 0.05). MDR1 and BCRP mRNA were highly significantly associated (p < 0.001), as were MRP1 and LRP mRNA (p < 0.001) expression. Univariate regression analyses revealed that CD34 expression, increasing MDR1 mRNA as well as MDR1/BCRP coexpression, were associated with a lower complete response (CR) rate and with worse event-free survival and overall survival. When adjusted for other prognostic actors, only CD34-related MDR1/BCRP coexpression remained significantly associated with a lower CR rate (p = 0.03), thereby identifying a clinically resistant subgroup of elderly AML patients

Large Process Models: Business Process Management in the Age of Generative AI

The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point of the challenges that purely statistics-based approaches have in terms of safety and trustworthiness. As a framework for contextualizing the potential, as well as the limitations of LLMs and other foundation model-based technologies, we propose the concept of a Large Process Model (LPM) that combines the correlation power of LLMs with the analytical precision and reliability of knowledge-based systems and automated reasoning approaches. LPMs are envisioned to directly utilize the wealth of process management experience that experts have accumulated, as well as process performance data of organizations with diverse characteristics, e.g., regarding size, region, or industry. In this vision, the proposed LPM would allow organizations to receive context-specific (tailored) process and other business models, analytical deep-dives, and improvement recommendations. As such, they would allow to substantially decrease the time and effort required for business transformation, while also allowing for deeper, more impactful, and more actionable insights than previously possible. We argue that implementing an LPM is feasible, but also highlight limitations and research challenges that need to be solved to implement particular aspects of the LPM vision