Zero-temperature thermodynamics of dense asymmetric strong-interaction matter

Employing constraints derived from the microscopic theory of the strong interaction, we estimate the zero-temperature phase structure of dense isospin-asymmetric matter with two quark flavors. We find indications that strong-interaction matter along trajectories relevant for astrophysical applications undergoes a first-order phase transition from a color-superconducting phase to an ungapped quark-matter phase when the density is increased. Such a phase transition is found to be absent in isospin-symmetric matter. Moreover, by taking into account constraints from $\beta$-equilibrium, charge neutrality, and color neutrality, we provide an estimate for the speed of sound in neutron-star matter. Notably, we observe that the speed of sound in neutron-star matter exceeds the asymptotic value associated with the noninteracting quark gas and even increases towards lower densities across a wide range, in agreement with recent results for isospin-symmetric matter. Considering results from studies based on chiral effective field theory at low densities, our findings suggest the existence of a maximum in the speed of sound for $n/n_0 \lesssim 10$, where $n_0$ is the nuclear saturation density.Comment: 16 pages, 9 figure

MEET YOUR NEW COLLE(AI)GUE – EXPLORING THE IMPACT OF HUMAN-AI INTERACTION DESIGNS ON USER PERFORMANCE

Artificial Intelligence (AI) has an increasing impact on industries, establishing a new way of solving tasks and automating work routines. While AI-based systems have become new colleagues for some processes, the tasks of some humans have shifted towards supervising AI. Essentially, humans need to adapt to a new form of interaction with AI-based systems because AI functioning is more similar to cognitive processes of humans than traditional information systems, e.g., in terms of their intransparent decision making. Previous research indicates that AI adds new challenges to human-computer interaction, and new frameworks for human-AI interaction are developed. However, current research lacks empirical research on the design of such interactions. We conducted a 2x2x2 experiment of AI-supported information extraction and measured the ability of participants to validate the extracted information by the AI. Our results indicate that the design of human-AI interaction significantly impacts users’ supervising performance

Acetylcholinesterase activity influenced by lipid membrane area and surface acoustic waves

According to the current model of nerve propagation, the function of acetylcholinesterase (AChE) is to terminate synaptic transmission of nerve signals by hydrolyzing the neurotransmitter acetylcholine (ACh) in the synaptic cleft to acetic acid (acetate) and choline. However, extra-synaptic roles, which are known as ‘non-classical’ roles, have not been fully elucidated. Here, we measured AChE activity with the enzyme bound to lipid membranes of varying area per enzyme in vitro using the Ellman assay. We found that the activity was not affected by density fluctuations in a supported lipid bilayer (SLB) induced by standing surface acoustic waves. Nevertheless, we found twice as high activity in the presence of small unilamellar vesicles (SUV) compared to lipid-free samples. We also showed that the increase in activity scaled with the available membrane area per enzyme

Segmentation, tracking and cell cycle analysis of live-cell imaging data with Cell-ACDC

Background: High-throughput live-cell imaging is a powerful tool to study dynamic cellular processes in single cells but creates a bottleneck at the stage of data analysis, due to the large amount of data generated and limitations of analytical pipelines. Recent progress on deep learning dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and tools spanning the complete range of image analysis are still needed. Results: We present Cell-ACDC, an open-source user-friendly GUI-based framework written in Python, for segmentation, tracking and cell cycle annotations. We included state-of-the-art deep learning models for single-cell segmentation of mammalian and yeast cells alongside cell tracking methods and an intuitive, semi-automated workflow for cell cycle annotation of single cells. Using Cell-ACDC, we found that mTOR activity in hematopoietic stem cells is largely independent of cell volume. By contrast, smaller cells exhibit higher p38 activity, consistent with a role of p38 in regulation of cell size. Additionally, we show that, in S. cerevisiae, histone Htbl concentrations decrease with replicative age. Conclusions: Cell-ACDC provides a framework for the application of state-of-the-art deep learning models to the analysis of live cell imaging data without programming knowledge. Furthermore, it allows for visualization and correction of segmentation and tracking errors as well as annotation of cell cycle stages. We embedded several smart algorithms that make the correction and annotation process fast and intuitive. Finally, the open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation, tracking, and downstream image analysis.Peer reviewe

A Generic Liquid Chromatography-Tandem Mass Spectrometry Exposome Method for the Determination of Xenoestrogens in Biological Matrices.

We are constantly exposed to a variety of environmental contaminants and hormones, including those mimicking endogenous estrogens. These highly heterogeneous molecules are collectively referred to as xenoestrogens and hold the potential to affect and alter the delicate hormonal balance of the human body. To monitor exposure and investigate potential health implications, comprehensive analytical methods covering all major xenoestrogen classes are needed but not available to date. Herein, we describe a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of multiple classes of endogenous as well as exogenous estrogens in human urine, serum, and breast milk to enable proper exposure and risk assessment. In total, 75 analytes were included, whereof a majority was successfully in-house validated in the three matrices. Extraction recoveries of validated analytes ranged from 71% to 110% and limits of quantification from 0.015 to 5 μg/L, 0.03 to 14 μg/L, and 0.03 to 4.6 μg/L in urine, serum, and breast milk, respectively. The applicability of the novel method was demonstrated in proof-of-principle experiments by analyzing urine from Austrian individuals and breast milk from Austrian and Nigerian individuals. Thereby, we proved the methods' feasibility to identify and quantify different classes of xenoestrogens simultaneously. The results illustrate the general importance of multiclass exposure assessment in the context of the exposome paradigm. Specifically, they highlight the need for estimating total estrogenic burden rather than single analyte or chemical class measurements and its potential impact in endocrine disruption and hormone related diseases including cancers

Predictive Trajectory Control with Online MTPA Calculation and Minimization of the Inner Torque Ripple for Permanent-Magnet Synchronous Machines

This paper presents an extended predictive trajectory control scheme combined with an inner torque ripple minimization considering the current-, flux-linkage-, and voltage-planes of permanent magnet synchronous machines. The extension of a fundamental machine model with flux-linkage harmonics allows the calculation of the inner torque ripple and enables its minimization. For this, the control is divided in two cases: (1) The dynamic operation or large signal behavior which uses the maximal torque gradient for the trajectory strategy during each control period for fastest dynamic operation, and (2) The stationary operation or small signal behavior, utilizing a real time capable polynomial approximation of the rotor position dependent torque hyperbolas (iso-torque curves) of permanent magnet synchronous machines for the ideal torque to current reference values. Since dynamic and steady-state operation is covered, torque to current look-up tables, such as maximum torque per ampere (MTPA)/maximum torque per volt/voltage (MTPV) look-up tables, are not required anymore. The introduced, new control approach is implemented in Matlab/Simulink based on finite element analysis and measured data. Furthermore, test-bench implementations based on measurement data are presented to show the real-time capability and precision

Comparable outcome of liver transplantation with Histidine-Tryptophan-Ketoglutarate vs. University of Wisconsin preservation solution: a retrospective observational double-center trial

I studien har 12 elevgrupper från 10 kommunala skolor i Malmö studerats statistiskt frånläsåren 2005/06 till 2013/14. Utifrån elevernas socioekonomiska bakgrund undersöktes effekten av skolornas resursutbud för PISA-resultaten i årskurs 9. Genom teorier om skolan som arena för social reproduktion av medelklassens värden, visade analysen att skolan inte uppväger för arbetarklasselever utan eftergymnasialt utbildade föräldrar. Slutsatserna visade att observationsgruppernas höga lärarbehörighet kombinerat med ökad lärartäthet för utsatta elevgrupper, inte ensamt utjämnar bakgrundsrelaterad skolsegregation. Som insatskomplement bör skolornas elevsammansättning ses som en administrativt förändringsbar resurs, jämte utökat arbete för bredare konsensus mellan hem och skola kring utbildningens betydelse och form.This study carries out a Qualitative Comparative Analysis [QCA] of 12 groups of studentsfrom 10 public schools in Malmoe. Based on students’ socioeconomic background, the study examines the effect of school resources across 9 years of elementary school; on PISA results in grade 9. Using the theoretical framework that school is an institution to promote social reproduction of middle-class values; the analysis demonstrates that school does not compensate working class students. The study's conclusions where that the observation groups generally high teaching qualifications; combined with increased teacher ratio for vulnerable student groups, not alone were sufficient resources to equalize background related school segregation. These need to be complemented with a broader consensus between home and school about the importance of education and its execution. Also the school pupil homogeneous composition should thereto be seen as an administrative opportunity to level the playing field in the present segregated school situation

Irradiation-dependent topology optimization of metallization grid patterns and variation of contact layer thickness used for latitude-based yield gain of thin-film solar modules

We show that the concept of topology optimization for metallization grid patterns of thin-film solar devices can be applied to monolithically integrated solar cells. Different irradiation intensities favor different topological grid designs as well as a different thickness of the transparent conductive oxide (TCO) layer. For standard laboratory efficiency determination, an irradiation power of 1000W/m$^{2}$ is generally applied. However, this power rarely occurs for real-world solar modules operating at mid-latitude locations. Therefore, contact layer thicknesses and also lateral grid patterns should be optimized for lower irradiation intensities. This results in material production savings for the grid and TCO layer of up to 50 % and simultaneously a significant gain in yield of over 1% for regions with a low annual mean irradiation

Implementation of service robots in Swiss hospitals and hotels : an investigation of the barriers to use

This poster delves into the realm of service robots within the context of Swiss hospitality, focusing on both hospitals and hotels. The study uncovers potential applications for service robots, ranging from medical deliveries in hospitals to enhancing guest experiences in hotels. Furthermore, it identifies and examines the barriers of to the use of service robots into the hospitality landscape. The research not only sheds light on the dynamics between humans and robots but also delves into the technological concerns, the establishments' culture, economical barriers and architectural limitations. While the study offers valuable insights into the Swiss scenario, it acknowledges the limitations of a regional sample. Ultimately, this endeavor contributes to a deeper understanding of the opportunities and obstacles in harnessing service robots to augment hospitality services in Switzerland

Response of intestinal HT-29 cells to the trichothecene mycotoxin deoxynivalenol and its sulfated conjugates

Abstract The sulfated forms of the Fusarium toxin deoxynivalenol (DON), deoxynivalenol-3-sulfate (DON-3-Sulf) and deoxynivalenol-15-sulfate (DON-15-Sulf) were recently described, however little is known about their mechanism of action in mammalian cells. DON-3-Sulf and DON-15-Sulf were taken up by HT-29 colon carcinoma cells, although to a lesser extent compared to DON. All three compounds were found to enhance the intracellular ROS level in the dichlorofluorescein assay (≥ 1μM), even though substantial differences were observed in their cytotoxic potential. In silico modelling highlighted that DON-sulfates do not share the classical mechanism of action of DON, being unable to fit into the ribosomal pocket and trigger the classical ribotoxic stress response. However, DON-3-Sulf and DON-15-Sulf sustained a distinctive proliferative stimulus in HT-29 and activated autophagy. The mechanisms of action of DON-3-Sulf and DON-15-Sulf suggest a potential interplay between the onset of ribosomal inhibition and autophagy activation as an alternative and/or complementary mode of action for DON and its sulfated analogues