A Classical Nernst Engine

We introduce a simple model for an engine based on the Nernst effect. In the presence of a magnetic field, a vertical heat current can drive a horizontal particle current against a chemical potential. For a microscopic model invoking classical particle trajectories subject to the Lorentz force, we prove a universal bound 3-2*sqrt(2) simeq 0.172 for the ratio between maximum efficiency and Carnot efficiency. This bound, as the slightly lower one 1/6 for efficiency at maximum power, can indeed be saturated for large magnetic field and small fugacity irrespective of the aspect ratio.Comment: 5+6 pages, 2 figure

Role of Bilayer Tilt Difference in Equlibrium Membrane Shapes

Lipid bilayer membranes below their main transition have two tilt order parameters, corresponding to the two monolayers. These two tilts may be strongly coupled to membrane shape but only weakly coupled to each other.We discuss some implications of this observation for rippled and saddle phases, spontaneous breaking bilayer tubules, and bicontinuous phases. Tilt difference introduces a lengthscale into the elastic theory of tilted fluid membranes. It can drive an instability of the flat phase; it also provides a simple spontaneous breaking of inversion symmetry seen in some recent experiments

Thermodynamic Evaluation of the system Ta–O and Preliminary Assessment of the Systems Al–Nb–O and Al–Ta–O

The binary tantalum–oxygen system is assessed using the CALculation of PHase Diagrams (CALPHAD) method with experimental data from the literature. The oxygen solubility in the Ta solid-solution phase is discussed and modeled. The low- and high-temperature modifications of Ta₂O₅ are described as stoichiometric compounds. This dataset is extended into the ternary Al–Ta–O system by complementing it with binary datasets for Al–O and Al–Ta from the literature and adding mixed-oxide AlTaO₄. The dataset for the ternary system Al–Nb–O is created by combining the three corresponding binary datasets from the literature and by assessing the quasibinary section Al₂O₃–Nb₂O₅. The ternary aluminum niobates are described as stoichiometric compounds. Phase equilibria between refractory metals and alumina at high temperature are discussed

Methodische Bewertung von Originalartikeln zu Radiomics und Machine Learning für Outcome-Vorhersagen basierend auf der Positronen-Emissions-Tomografie (PET)

AIM Despite a vast number of articles on radiomics and machine learning in positron emission tomography (PET) imaging, clinical applicability remains limited, partly owing to poor methodological quality. We therefore systematically investigated the methodology described in publications on radiomics and machine learning for PET-based outcome prediction. METHODS A systematic search for original articles was run on PubMed. All articles were rated according to 17 criteria proposed by the authors. Criteria with >2 rating categories were binarized into "adequate" or "inadequate". The association between the number of "adequate" criteria per article and the date of publication was examined. RESULTS One hundred articles were identified (published between 07/2017 and 09/2023). The median proportion of articles per criterion that were rated "adequate" was 65% (range: 23-98%). Nineteen articles (19%) mentioned neither a test cohort nor cross-validation to separate training from testing. The median number of criteria with an "adequate" rating per article was 12.5 out of 17 (range, 4-17), and this did not increase with later dates of publication (Spearman's rho, 0.094; p = 0.35). In 22 articles (22%), less than half of the items were rated "adequate". Only 8% of articles published the source code, and 10% made the dataset openly available. CONCLUSION Among the articles investigated, methodological weaknesses have been identified, and the degree of compliance with recommendations on methodological quality and reporting shows potential for improvement. Better adherence to established guidelines could increase the clinical significance of radiomics and machine learning for PET-based outcome prediction and finally lead to the widespread use in routine clinical practice

ACM Classification Keywords

In many contexts, pen and paper are the ideal option for collecting information despite the pervasiveness of mobile devices. Reasons include the unconstrained nature of sketching or handwriting, as well as the tactility of moving a pen over a paper that supports very fine granular control of the pen. In particular in the context of hospitals, many writing and note taking tasks are still performed using pen and paper. However, often this requires time-consuming transcription into digital form for the sake of documentation. We present Penbook – a system providing a touch screen together with a built-in projector integrated with a wireless pen and a projection screen augmented with Anoto paper. This allows using the pen to write or sketch digital information with light on the projection surface while having the distinct tactility of a pen moving over paper. The touch screen can be used in parallel with the projected information turning the tablet into a dual-display device. In this paper, we present the Penbook concept, detail specific applications in a hospital context, and present a prototype implementation of Penbook

CoDaMine: Supporting Privacy and Trust Management in Ubiquitous Environments Through Communication Data Mining

In ubiquitous environments an increasing number of sensors capture information on users and at the same time an increasing number of actuators are available to present information to users. This vast capturing of information potentially enables the system to adapt to the users. At the same time the system might violate the users' privacy by capturing information that the users do not want to share, and the system might disrupt the users by being too obtrusive in its adaptation or information supply. In this paper we present CoDaMine - a novel approach for providing users with system - generated feedback and control in ubiquitous environments giving them the freedom they need while reducing their effort. Basically, CoDaMine captures and analyses the users' online communication to learn about their social relationships in order to provide them with recommendations for inter-personal privacy and trust management