Work and reversibility in quantum thermodynamics

It is a central question in quantum thermodynamics to determine how irreversible is a process that transforms an initial state $\rho$ to a final state $\sigma$, and whether such irreversibility can be thought of as a useful resource. For example, we might ask how much work can be obtained by thermalizing $\rho$ to a thermal state $\sigma$ at temperature $T$ of an ambient heat bath. Here, we show that, for different sets of resource-theoretic thermodynamic operations, the amount of entropy produced along a transition is characterized by how reversible the process is. More specifically, this entropy production depends on how well we can return the state $\sigma$ to its original form $\rho$ without investing any work. At the same time, the entropy production can be linked to the work that can be extracted along a given transition, and we explore the consequences that this fact has for our results. We also exhibit an explicit reversal operation in terms of the Petz recovery channel coming from quantum information theory. Our result establishes a quantitative link between the reversibility of thermodynamical processes and the corresponding work gain.Comment: 14 page

WorldSkills UK training managers: Midas touch or fool's gold?

This article focuses on the role of training managers (TMs) in UK participation in WorldSkills Competitions (WSC). The TM role is outlined, according to the perceptions of the TMs, and there is analysis of the benefits to them of participation, as well as the barriers they face, and the benefits and barriers available to participating further education colleges and employers. The article is based on analysis of semi-structured interviews with almost the full cohort of UK TMs preparing competitors for WorldSkills Brazil 2015, and concludes with reflections on the vision and purposes of UK WorldSkills participation

Policy and Procedure: Clinical Management of Human Trafficking Patients and/or Those at Risk for Exploitation

The Ohio Attorney General’s Office in its fight against human trafficking has created a Human Trafficking Initiative. Part of this initiative is the development of publications to assist providers in the care of and/or recognition of trafficked patients, data collection, and/or standards of service. This healthcare policy template is both evidence based and survivor informed. It will help to assist providers in understanding the basic guidelines of clinical management for human trafficking patients and/or those at risk for exploitation. This resource in addition to others can be found on the Ohio Attorney General’s website and is available to download and adopt as a reference/template for the development of healthcare policy and procedures

Euregio Mobility in der beruflichen Bildung. Über die Grenze gehen & denken

Wie kann berufliche Bildung in europäischen Grenzregionen auf- und ausgebaut werden? Am Beispiel von sechs berufsbildenden Schulen in der Euregio Rhein-Waal berichten die Autor:innen über Potenziale und Herausforderungen grenzüberschreitender Berufsbildung. Die Forschenden begleiteten Austausche in drei Tandempartnerschaften aus jeweils einer berufsbildenden Schule in Deutschland und den Niederlanden (ROC). Teil des Projekts waren die Bildungsgänge Einzelhandel, Erzieher/-in sowie Gartenbau. Im Mittelpunkt des Projektberichts stehen die Struktur der Tandempartnerschaften, die eine niedrigschwellige Partizipation sichert, sowie der Austausch der Lehrenden. Auch der Einsatz digitaler Tools wird mit Blick auf die Covid-19-Pademie analysiert. Insgesamt liefert die Publikation neue Perspektiven auf die Möglichkeiten grenzüberschreitender Bildungsprojekte und Argumente für eine breite Mobilitätspalette, mit der Lehrende und Lernende als Multiplikatoren im europäischen Raum wirken können. (DIPF/Orig.

Loss of inter-cellular cooperation by complete epithelial-mesenchymal transition supports favorable outcomes in basal breast cancer patients.

According to the sequential metastasis model, aggressive mesenchymal (M) metastasis-initiating cells (MICs) are generated by an epithelial-mesenchymal transition (EMT) which eventually is reversed by a mesenchymal-epithelial transition (MET) and outgrowth of life-threatening epithelial (E) macrometastases. Paradoxically, in breast cancer M signatures are linked with more favorable outcomes than E signatures, and M cells are often dispensable for metastasis in mouse models. Here we present evidence at the cellular and patient level for the cooperation metastasis model, according to which E cells are MICs, while M cells merely support E cell persistence through cooperation. We tracked the fates of co-cultured E and M clones and of fluorescent CDH1-promoter-driven cell lines reporting the E state derived from basal breast cancer HMLER cells. Cells were placed in suspension state and allowed to reattach and select an EMT cell fate. Flow cytometry, single cell and bulk gene expression analyses revealed that only pre-existing E cells generated E cells, mixed E/M populations, or stem-like hybrid E/M cells after suspension and that complete EMT manifest in M clones and CDH1-negative reporter cells resulted in loss of cell plasticity, suggesting full transdifferentiation. Mechanistically, E-M coculture experiments supported the persistence of pre-existing E cells where M cells inhibited EMT of E cells in a mutual cooperation via direct cell-cell contact. Consistently, M signatures were associated with more favorable patient outcomes compared to E signatures in breast cancer, specifically in basal breast cancer patients. These findings suggest a potential benefit of complete EMT for basal breast cancer patients

Speech Communication

Contains table of contents for Part IV, table of contents for Section 1 and reports on five research projects.Apple Computer, Inc.C.J. Lebel FellowshipNational Institutes of Health (Grant T32-NS07040)National Institutes of Health (Grant R01-NS04332)National Institutes of Health (Grant R01-NS21183)National Institutes of Health (Grant P01-NS23734)U.S. Navy / Naval Electronic Systems Command (Contract N00039-85-C-0254)U.S. Navy - Office of Naval Research (Contract N00014-82-K-0727

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks