Optimal Heat Source Temperature For Supercritical Organic Rankine Cycle

Organic Rankine Cycle (ORC) enables power generation from low- to medium temperature heat sources. In an ORC, the organic medium shows different performances for different heat source temperatures. For a range of heat source temperatures, one temperature can be always identified corresponding to the best thermal match between the heat transfer fluid and working fluid. This temperature is defined as the Optimal Heat Source Temperature (OHST) and serves as an indicator for optimal efficiency. In this respect, the aim of this study is to investigate the OHST for supercritical fluid and its application in thermodynamic optimization. A simple ORC configuration is introduced and imposed with a set of constraints for establishing a cycle model. OHST is determined from parametric optimization and theoretical prediction, respectively. A comparative study is followed to examine the reliability of the theoretical prediction. In a subsequent case study, the OHST approach is compared with the conventional approach in thermodynamic optimization of a supercritical ORC. Optimal results from both approaches are compared, along with discussions and conclusions for further studies

Satiety regulation in children with loss of control eating and attention-deficit/hyperactivity disorder: a test meal study

Children with loss of control (LOC) eating and attention-deficit/hyperactivity disorder (ADHD) are at risk for excessive weight gain. However, it is unclear whether or not these children show disturbances in hunger and satiety regulation. The goal was to examine the food intake and sense of LOC over eating as well as LOC eating-related characteristics during test meal in children with LOC eating and ADHD. Children aged 8-13 y with LOC eating (n = 33), ADHD (n = 32), and matched healthy controls (n = 33), consumed a test meal consisting of their chosen lunch food, with the instruction to eat until feeling full. Sense of LOC over eating, desire to eat, feelings of hunger, and liking of food were repeatedly assessed during test meal. Children with LOC eating and ADHD did not show a higher food intake at maximum satiety compared to control children. Sense of LOC over eating was significantly higher in children with LOC eating compared to children with ADHD and matched controls. Secondary analyses revealed that children with LOC eating ate marginally faster than control children. Both children with LOC eating and ADHD reported greater desire to eat, feelings of hunger, and liking of food during test meal than control children. Even though the results did not reveal statistical evidence to support the assumption of a disturbed food intake in children with LOC eating and ADHD, LOC eating related characteristics were significantly higher in these children compared to the control children. Sense of LOC over eating was confirmed as a specific characteristic of LOC eating. The examination of behavioral indicators of hunger and satiety dysregulation should be complemented with physiological indicators in future research

Distribution and clinical comparison of restrictive feeding and eating disorders using ICD-10 and ICD-11 criteria.

OBJECTIVE Within the eleventh edition of the International Classification of Diseases (ICD-11), diagnostic criteria for feeding and eating disorders were revised and new diagnoses including avoidant/restrictive food intake disorder (ARFID) are classifiable; however, nothing is known about how these changes affect the prevalence of feeding and eating disorders. This study compared the distribution and clinical characteristics of restrictive feeding and eating disorders between ICD-10 and ICD-11. METHOD The Eating Disorder Examination (EDE), its child version, and the EDE ARFID module were administered to N = 82 patients (0-17 years) seeking treatment for restrictive feeding and eating disorders and their parents. Clinical characteristics were derived from medical records, questionnaires, and objective anthropometrics. RESULTS The number of residual restrictive eating disorders (rrED) significantly decreased from ICD-10 to ICD-11 due to a crossover to full-threshold disorders, especially anorexia nervosa (AN) or ARFID. Patients reclassified to ICD-11 ARFID were younger, had an earlier age of illness onset, more restrictive eating behaviors, and tended to have more somatic comorbidities compared to those reclassified to ICD-11 AN. Patients with rrED according to both ICD-10 and ICD-11 were younger, had an earlier age of illness onset, less shape concern, and more somatic comorbidities than patients who were reclassified from ICD-10 rrED to ICD-11 AN or ARFID. DISCUSSION This study highlights the inclusive approach of ICD-11 criteria, paving the way for more targeted treatment, and ARFID's high clinical relevance. Future studies considering nonrestrictive feeding and eating disorders across the life span may allow further analyses on diagnostic crossover. PUBLIC SIGNIFICANCE Changes in diagnostic criteria for restrictive eating disorders within the newly published ICD-11 led to an increase in full-threshold disorders, while the number of rrED was significantly lowered compared to ICD-10 criteria. The results thus highlight the diagnostic utility of ICD-11 criteria and may help providing adequate treatment to children and adolescents with rrED

Towards a Rule-based Manufacturing Integration Assistant

Recent developments and steadily declining prices in ICT enable an economic application of advanced digital tools in wide areas of manufacturing. Solutions based on concepts and technologies of the “Internet of Things” or “cyber physical systems” can be used to implement monitoring as well as self-organization of production, maintenance or logistics processes. However, integration of new digital tools in existing heterogeneous manufacturing IT systems and integration of machines and devices into manufacturing environments is an expensive and tedious task. Therefore, integration issues on IT and manufacturing level significantly prevent agile manufacturing. Especially small and medium-sized enterprises do not have the expertise or the investment possibilities to realize such an integration. To tackle this issue, we present the approach of the Manufacturing Integration Assistant - MIALinx. The objective is to develop and implement a lightweight and easy-to-use integration solution for small and medium-sized enterprises based on recent web automation technologies. MIALinx aims to simplify the integration using simple programmable, flexible and reusable “IF-THEN” rules that connect occurring situations in manufacturing, such as a machine break down, with corresponding actions, e.g., an automatic maintenance order generation. For this purpose, MIALinx connects sensors and actuators based on defined rules whereas the rule set is defined in a domain-specific, easy-to-use manner to enable rule modeling by domain experts. Through the definition of rule sets, the workers’ knowledge can be also externalized. Using manufacturing-approved cloud computing technologies, we enable robustness, security, and a low-effort, low-cost integration of MIALinx into existing manufacturing environments to provide advanced digital tools also for small and medium-sized enterprises

Embrace the Gap: VAEs Perform Independent Mechanism Analysis

Variational autoencoders (VAEs) are a popular framework for modeling complex data distributions; they can be efficiently trained via variational inference by maximizing the evidence lower bound (ELBO), at the expense of a gap to the exact (log-)marginal likelihood. While VAEs are commonly used for representation learning, it is unclear why ELBO maximization would yield useful representations, since unregularized maximum likelihood estimation cannot invert the data-generating process. Yet, VAEs often succeed at this task. We seek to elucidate this apparent paradox by studying nonlinear VAEs in the limit of near-deterministic decoders. We first prove that, in this regime, the optimal encoder approximately inverts the decoder -- a commonly used but unproven conjecture -- which we refer to as {\em self-consistency}. Leveraging self-consistency, we show that the ELBO converges to a regularized log-likelihood. This allows VAEs to perform what has recently been termed independent mechanism analysis (IMA): it adds an inductive bias towards decoders with column-orthogonal Jacobians, which helps recovering the true latent factors. The gap between ELBO and log-likelihood is therefore welcome, since it bears unanticipated benefits for nonlinear representation learning. In experiments on synthetic and image data, we show that VAEs uncover the true latent factors when the data generating process satisfies the IMA assumption.Comment: 47 pages, accepted at NeurIPS202

Supplemental Materials: Novel Isotypic g/z-Subunits Reveal Three Coatomer Complexes in Mammals

Fig. A 1 shows a Western blot analyzing the specificity of the antibodies against g- and z-isotypes. These antibodies were probed in different mammalian species (Fig. A 2). Coatomer was labeled with [35S]-methionine for different time periods, and the incorporation of [35S]-methionine as well as the corresponding stoichiometries of the coatomer subunits are shown in Fig. A 3. Characterization of anti-coatomer antibody 883 is depicted in Fig. A 4

The PIOLab: Building global physical input-output tables in a virtual laboratory

Informed environmental-economic policy decisions require a solid understanding of the economy’s biophysical basis. Global physical input-output tables ( gPIOTs) collate a vast array ofinformation on the world economy’s physical structure and its interdependence with the environment. However, building gPIOTs requires dealing with mismatched and incompleteprimary data with high uncertainties, which makes it a time-consuming and labor-intensive endeavor. We address this challenge by introducing the PIOLab: A virtual laboratory for building gPIOTs. It represents the newest branch of the Industrial Ecology virtual laboratory (IELab) concept, a cloud-computing platform and collaborative research environment through which participants can use each other’s resources to assemble individual input-output tables targeting specific research questions. To overcome the lack of primary data, the PIOLab builds extensively upon secondary data derived from a variety of models commonly used in Industrial Ecology. We use the case of global iron-steel supply chains to describe the architecture of the PIOLab and highlight its analytical capabilities. A major strength of the gPIOT is its ability to provide mass-balanced indicators on both apparent/direct and embodied/indirect flows, for regions and disaggregated economic sectors. We present the first gPIOTs for 10 years (2008-2017), covering32 regions, 30 processes and 39 types of iron/steel flows. Diagnostic tests of the data reconciliation show a good level of adherence between raw data and the values realized in the gPIOT. We conclude with elaborating on how the PIOLab will be extended to cover other materials and energyflows.Series: Ecological Economic Paper

The role of structured reporting and structured operation planning in functional endoscopic sinus surgery

Computed tomography (CT) scans represent the gold standard in the planning of functional endoscopic sinus surgeries (FESS). Yet, radiologists and otolaryngologists have different perspectives on these scans. In general, residents often struggle with aspects involved in both reporting and operation planning. The aim of this study was to compare the completeness of structured reports (SR) of preoperative CT images and structured operation planning (SOP) to conventional reports (CR) and conventional operation planning (COP) to potentially improve future treatment decisions on an individual level. In total, 30 preoperative CT scans obtained for surgical planning of patients scheduled for FESS were evaluated using SR and CR by radiology residents. Subsequently, otolaryngology residents performed a COP using free texts and a SOP using a specific template. All radiology reports and operation plannings were evaluated by two experienced FESS surgeons regarding their completeness for surgical planning. User satisfaction of otolaryngology residents was assessed by using visual analogue scales. Overall radiology report completeness was significantly higher using SRs regarding surgically important structures compared to CRs (84.4 vs. 22.0%, p<0.001). SOPs produced significantly higher completeness ratings (97% vs. 39.4%, p<0.001) regarding pathologies and anatomical variances. Moreover, time efficiency was not significantly impaired by implementation of SR (148 s vs. 160 s, p = 0.61) and user satisfaction was significantly higher for SOP (VAS 8.1 vs. 4.1, p<0.001). Implementation of SR and SOP results in a significantly increased completeness of radiology reports and operation planning for FESS. Consequently, the combination of both facilitates surgical planning and may decrease potential risks during FESS

Katastrophenschutzübung in Salzburg: Neue Methoden und Technologien für Einsatzkräfte

Im Rahmen des AIFER Forschungsprojektes fand am Samstag, den 29.04.2023, unter gemeinsamer Leitung des Österreichischen und des Bayerischen Roten Kreuz sowie der Paris Lodron Universität Salzburg und dem Deutschen Zentrum für Luft- und Raumfahrt eine Katastrophenschutzübung (FEx Field Exercise) statt . Dabei wurde der Einsatz innovativer Entwicklungen und Technologien in einem nach der Dienstvorschrift 100 (DV 100) stabsdienstlich organisierten Lagezentrum anhand eines Hochwasserszenarios getestet und von Experten verschiedener Einsatzorganisationen und Behörden bewertet