bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemikerin statt Guerillera
Authors: Purrer Ulrike 
Published: October 2023

AbstractDie Kolumbianerinnen Karen Cuero und Camila López kommen aus Tumaco, einer Stadt, die immer wieder vom bewaffneten Konflikt in Kolumbien betroffen war. Die Hauptwirtschaftszweige dieser Stadt sind Landwirtschaft, Fischerei, Holzwirtschaft und Tourismus – doch die beiden Frauen studieren Chemieingenieurwesen.
Interview: Regulierung per‐ und polyfluorierter Substanzen
Authors: Neubauer Uta 
Published: October 2023

AbstractDie Europäische Chemikalienagentur Echa bereitet die Regulierung per‐ und polyfluorierter Alkylsubstanzen, kurz PFAS, vor. Allein die Umweltpersistenz der Substanzen rechtfertige ein umfassendes Verbot, meint Juliane Glüge von der ETH Zürich. Sie vertritt die European Chemical Society in Sitzungen der Echa, die sich mit dem PFAS‐Verbot beschäftigen. PFAS gehören seit dem Jahr 2019 zu ihren Arbeitsschwerpunkten. Studiert hat sie Biosystemtechnik an der Universität Magdeburg.
Trendbericht Theoretische Chemie 2023 (2/3): Berechnungen von Molekülschwingungen in der Thermodynamik
Authors: Perlt Eva , Khanifaev Jamoliddin , Schrader Tim 
Published: October 2023

AbstractMaschinelles Lernen: Bisher zielten Anwendungen vor allem auf das Lernen von Potenzialenergiehyperflächen, derzeit zeigen sich viele neue Forschungsrichtungen. Molekülschwingungen in der Thermodynamik: Berechnung in Theorie und Simulation. Ultrakurze Laserpulse zum Beobachten molekularer Dynamik: Da die Bewegung von Elektronen genauso schnell ist wie die zeitliche Ausdehnung der Pulse, sind die Pulseigenschaften bei Simulationen explizit zu berücksichtigen.
Je kleiner, desto blauer
Authors: Osterath Brigitte 
Published: October 2023

AbstractDie diesjährigen Chemienobelpreisträger Alexei Ekimov, Louis Brus und Moungi Bawendi haben Quantenpunkte hergestellt: Halbleiterkristalle, die so klein sind, dass Quantenphänomene ihre Eigenschaften bestimmen. Über die Größe der Nanopartikel lässt sich daher ihre Farbe einstellen.
Numerical algorithm with fifth‐order accuracy for axisymmetric Laplace equation with linear boundary value problem
Authors: Li Hu , Huang Jin 
Published: October 2023

AbstractIn order to obtain the numerical solutions of the axisymmetric Laplace equation with linear boundary problem in three dimensions, we have developed a quadrature method to solve the problem. Firstly, the problem can be transformed to a integral equation with weakly singular operator by using the Green's formula. Secondly, A quadrature method is constructed by combing the mid‐rectangle formula with a singular integral formula to solve the integral equation, which has the accuracy of and low computational complexity. Thirdly, the convergence of the numerical solutions is proved based on the theory of compact operators and the single parameter asymptotic expansion of errors with odd power is got. From the expansion, we construct an extrapolation algorithm (EA) to further improve the accuracy of the numerical solutions. After one extrapolation, the accuracy of the numerical solutions can reach the accuracy of . Finally, two numerical examples are presented to demonstrate the efficiency of the method.
The dyadic effects of individual resilience on family resilience among Chinese parents and children during COVID‐19
Authors: Feng Li , Jin Jialu , An Yuanyuan , Zhao Jiaqi , Zhu Yi , Li Xiaohui 
Published: October 2023

AbstractPrevious studies have mainly focused on examining families' struggles during the adaptive process of adversity, while the strength of family and how it arises were neglected. This study aims to explore the relationships between individual and family resilience among parents and children in families during COVID‐19. Guided by the longitudinal actor–partner interdependence model, one parent and a child in 136 Chinese families completed assessments of pandemic media exposure and individual resilience in mid‐February 2020 and family resilience in early March. Results showed that the child's individual resilience was positively associated with their own and their parents’ family resilience, while parents' resilience was only positively associated with their own. The evidence indicated that a child's individual resilience was critical for all core family members' perceived family resilience and provided implications for family intervention programs.
Persistent chest pain following COVID‐19 infection – A scoping review
Authors: Kubrova Eva , Hallo‐Carrasco Alejandro J. , Klasova Johana , Pagan Rosado Robert D. , Prusinski Christian C. , Trofymenko Oleksandr , Schappell Justin B. , Prokop Larry J. , Yuh Clara I. , Gupta Sahil , Hunt Christine L. 
Published: October 2023

AbstractPersistent chest pain (PCP) following acute COVID‐19 infection is a commonly reported symptom with an unclear etiology, making its management challenging. This scoping review aims to address the knowledge gap surrounding the characteristics of PCP following COVID‐19, its causes, and potential treatments. This is a scoping review of 64 studies, including observational (prospective, retrospective, cross‐sectional, case series, and case–control) and one quasi‐experimental study, from databases including Embase, PubMed/MEDLINE, Cochrane CENTRAL, Google Scholar, Cochrane Database of Systematic Reviews, and Scopus. Studies on patients with PCP following mild, moderate, and severe COVID‐19 infection were included. Studies with patients of any age, with chest pain that persisted following acute COVID‐19 disease, irrespective of etiology or duration were included. A total of 35 studies reported PCP symptoms following COVID‐19 (0.24%–76.6%) at an average follow‐up of 3 months or longer, 12 studies at 1–3 months and 17 studies at less than 1‐month follow‐up or not specified. PCP was common following mild—severe COVID‐19 infection, and etiology was mostly not reported. Fourteen studies proposed potential etiologies including endothelial dysfunction, cardiac ischemia, vasospasm, myocarditis, cardiac arrhythmia, pneumonia, pulmonary embolism, postural tachycardia syndrome, or noted cardiac MRI (cMRI) changes. Evaluation methods included common cardiopulmonary tests, as well as less common tests such as flow‐mediated dilatation, cMRI, single‐photon emission computed tomography myocardial perfusion imaging, and cardiopulmonary exercise testing. Only one study reported a specific treatment (sulodexide). PCP is a prevalent symptom following COVID‐19 infection, with various proposed etiologies. Further research is needed to establish a better understanding of the causes and to develop targeted treatments for PCP following COVID‐19.
Spherically confined hydrogenic atoms under classical non‐ideal plasmas: Scaling law for the critical cage size
Authors: Das Netai , Das Biswajit , Ghoshal Arijit 
Published: October 2023

AbstractAn elegant calculation is carried out to investigate the effects of the non‐ideality of classical plasma on the energy levels of the hydrogenic atoms held in a spherical cage. Organized effect of the non‐ideal classical plasma is described by an analytical pseudopotential which contains the Debye length and non‐ideality parameter as parameters. Convergent results for the bound states are obtained variationally by utilizing a large trail function containing cosine term which automatically takes care of the requisite boundary conditions. For the plasma‐free case, our results are in excellent agreement with the most accurate results available in the literature. An inclusive study is made to explore the changes emerging in the energy levels due to the variation of the plasma parameters and cage size. Special emphasis is made on the determination of critical cage size precisely. The present study specifically reveals that the increasing plasma non‐ideality leads to the elongation of the critical cage size. Moreover, it is empirically found that the critical cage size for a given hydrogenic atom can be obtained from a scaling law.
Reconfigurable Hexapartite Cluster States by Four‐Wave Mixing Processes with a Spatially Structured Pump
Authors: Zhang Kai , Guo Yu , Jing Jietai 
Published: October 2023

AbstractThe universal quantum computation provides a new paradigm for information processing. One feasible approach is measurement‐based one‐way quantum computation utilizing cluster states. Generally, the generation of cluster states with different structures for implementing on‐demand quantum computation needs different experimental setup, which limits its scalability. Here, the reconfigurable hexapartite cluster states created by postprocessing the quadrature information of hexapartite entangled state are demonstrated. Without altering the experimental layout, nine quantum correlated states with different structures, especially three cluster states, are implemented. In particular, such method can effectively reduce the excess noise introduced by creating cluster states under limited squeezing resources. This approach provides an avenue for realizing large‐scale reconfigurable cluster states without changing the experimental architecture.
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
Authors: Molnar Christoph , Freiesleben Timo , König Gunnar , Herbinger Julia , Reisinger Tim , Casalicchio Giuseppe , Wright Marvin N. , Bischl Bernd 
Published: October 2023

AbstractScientists and practitioners increasingly rely on machine learning to model data and draw conclusions. Compared to statistical modeling approaches, machine learning makes fewer explicit assumptions about data structures, such as linearity. Consequently, the parameters of machine learning models usually cannot be easily related to the data generating process. To learn about the modeled relationships, partial dependence (PD) plots and permutation feature importance (PFI) are often used as interpretation methods. However, PD and PFI lack a theory that relates them to the data generating process. We formalize PD and PFI as statistical estimators of ground truth estimands rooted in the data generating process. We show that PD and PFI estimates deviate from this ground truth not only due to statistical biases, but also due to learner variance and Monte Carlo approximation errors. To account for these uncertainties in PD and PFI estimation, we propose the learner-PD and the learner-PFI based on model refits and propose corrected variance and confidence interval estimators.
Cost of Explainability in AI: An Example with Credit Scoring Models
Authors: Dessain Jean , Bentaleb Nora , Vinas Fabien 
Published: October 2023

AbstractThis paper examines the cost of explainability in machine learning models for credit scoring. The analysis is conducted under the constraint of meeting the regulatory requirements of the European Central Bank (ECB), using a real-life dataset of over 50,000 credit exposures. We compare the statistical and financial performances of black-box models, such as XGBoost and neural networks, with inherently explainable models like logistic regression and GAMs. Notably, statistical performance does not necessarily correlate with financial performance. Our results reveal a difference of 15 to 20 basis points in annual return on investment between the best performing black-box model and the best performing inherently explainable model, as cost of explainability. We also find that the cost of explainability increases together with the risk appetite.To enhance the interpretability of explainable models, we apply isotonic smoothing of features’ shape functions based on expert judgment. Our findings suggest that incorporating expert judgment in the form of isotonic smoothing improves the explainability without compromising the performance. These results have significant implications for the use of explainable models in credit risk assessment and for regulatory compliance.
The absence of observable proton decay in a global SU(5) F-theory model
Authors: Clemens Herbert , Raby Stuart 
Published: October 2023

Abstract
We begin with an E8× E8 Heterotic model broken to an SU(5)gauge× U(1)X and a twin SU(5)gauge× U(1)X, where one SU(5) and its spectrum is identified as the visible sector while the other can be identified as a hidden twin sector. In both cases we obtain the minimal supersymmetric standard model (MSSM) spectrum after Wilson-line symmetry-breaking enhanced by a low energy R-parity and $$ {\mathbb{Z}}_4^R $$

ℤ
4
R

symmetry. We argue that there will not be any observable proton decay in this model.
The Relationship Between Parent-Child Movement Synchrony and Social Behavior of Children Diagnosed with Autism Spectrum Disorder and Children Diagnosed with Down Syndrome
Authors: van der Steen Steffie , Hill Yannick , F. A. Cox Ralf 
Published: October 2023

AbstractPurpose: Dyadic synchrony is positively associated with social competence. Although children diagnosed with Autism Spectrum Disorder (ASD) and children diagnosed with Down Syndrome (DS) both have trouble with dyadic synchrony, the origin of their difficulties is fundamentally different. In this mixed method study, we investigated differences in dyadic synchrony and social behavior between children diagnosed with ASD and DS. Methods: Twenty-seven children diagnosed with ASD (10 cisgender females; Mage = 10.98 years; SD = 2.21) and twenty-five children diagnosed with DS (11 cisgender females; Mage = 11.91 years; SD = 2.27) performed a collaborative drawing task with a parent in which they had to synchronize their drawing movements. We continuously tracked their dominant hand movements using wearable accelerometers, and performed Cross-Recurrence Quantification Analysis to extract synchrony measures. Additionally, we compared the social behaviors (interpersonal synchrony, emotion regulation, and social cognition, motivation, and confidence) of these children using quantitative parental questionnaires. Results: Parent-child synchrony measures were significantly higher for children diagnosed with ASD. Yet, parents were significantly more positive about the social behaviors of children diagnosed with DS. No significant correlation between the synchrony and questionnaire measures was found. Conclusion: While children diagnosed with ASD synchronize better during a collaborative task, the social behavior of the children diagnosed with DS (including social synchrony) is more positively evaluated by their parents. Possible reasons for this discrepancy are discussed.
Spirulina and Thymoquinone Protect Against Methotrexate-Induced Hepatic Injury in Rats
Authors: Behairy Alaa , Elkomy Ashraf , Elsayed Faten , Gaballa Mohamed M. S. , Soliman Ahmed , Aboubakr Mohamed 
Published: October 2023

AbstractMethotrexate is a chemotherapy medication frequently used to treat various forms of cancer. The purpose of this research was to examine if the administration of Arthrospira platensis (Spirulina) and/or thymoquinone could ameliorate the liver injury resulting from methotrexate. The rats were randomly assigned to seven groups, each containing seven rats. The groups included a control group that received only saline, a group that received A. platensis orally at a dose of 500 mg/kg, a group that received thymoquinone orally at a dose of 10 mg/kg, a group that received a single i.p. dose of 20 mg/kg methotrexate, a group that received both A. platensis and methotrexate, a group that received both thymoquinone and methotrexate, and a group that received A. platensis, thymoquinone, and methotrexate. The injection of methotrexate caused an increase in the levels of alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, cholesterol, triacylglycerides, and low-density lipoprotein-cholesterol, and a decrease in high-density lipoprotein-cholesterol (HDL-cholesterol). The liver tissues also showed an increase in malondialdehyde and a decrease in reduced glutathione, superoxide dismutase, and catalase, along with pathological lesions and increased expression of TNF-α and caspase-3. However, administration of A. platensis and thymoquinone alone or in combination reduced the toxicity and apoptosis induced by methotrexate.
Graphical Abstract
Outcome domains and measurement instruments of patient-relevant improvement of structure and processes as a new set of outcomes for evaluating and approving digital health applications: systematic review
Authors: Scheibe Madlen , Knapp Andreas , Harst Lorenz , Schmitt Jochen 
Published: October 2023

Abstract
Background
In October 2020, digital health applications (DiGAs) became part of standard care in Germany. For approval, DiGA manufacturers must demonstrate medical benefit or patient-relevant improvement of structure and processes (PISP). PISP refers to an innovative outcome core area in terms of proof of benefits and reimbursement decisions. These are subdivided into 9 outcome domains, including for example health literacy, facilitating access to care, and coping with illness-related difficulties in everyday life. Their implementation aims at empowering patients, encouraging shared decision-making, and increasing patient-centeredness in healthcare delivery. Given the novelty of PISP, no standardized set of outcomes and outcome measurement instruments currently exists to operationalize the domains. Learning from previous evaluation studies can help operationalize and standardize PISPs for evaluation studies of digital health applications. Therefore, we investigated the outcomes and outcome measurement instruments, used in controlled trials to assess DiGA-compliant applications, published before the Digital Health Applications Ordinance of April 2020.

Methods
We conducted a systematic review of studies published between 01/2015 and 04/2020, via MEDLINE and Embase, complemented by forward/backward searches. Controlled trials assessing interventions adhering to the definition of DiGA were eligible, if they applied a validated outcome measurement instrument, and if results were presented in German or English. Title-abstract screening, full-text screening, data extraction and narrative synthesis were conducted independently by two researchers.

Results
Out of 2,671 references identified, 6 studies collecting a total of 48 outcomes were included. 14 outcomes (29.2%) addressed PISP by using 13 different measurement instruments. The outcomes corresponded to 5 of 9 PISP outcome domains with health literacy being the most common (7/14, 50.0%).

Conclusions
This review provides an overview of the characteristics of PISPs used in previous evaluation studies of DiGA-compliant applications. It shows which outcomes and validated outcome measurement instruments can be used to measure PISP and where knowledge is still lacking. These results serve as a starting point for operationalizing and standardizing PISPs and help to increase the outcome measurement quality of PISPs.
Deployable optics for the Buccaneer Main Mission (BMM)
Authors: Agenbag F. , Alvino P.S. , Bandara D.C. , Bennett H.E. , Hollick M. , James A.M. , Kaduparambil-Jose J. , Lingard D.M. , Lorenzin F. , Lucas B. , McKinnon A. , Nelson J.D. , Peck C.V. , Raddock C. , Raj A. , Stephenson P.C.L. , Strachan A. , Teske T. , Thornton P. 
Published: October 2023

AbstractDefence Science and Technology Group (DSTG) is currently preparing for the launch of the Buccaneer Main Mission (BMM) satellite, the successor to the Buccaneer Risk Mitigation Mission (BRMM). BMM hosts a high-frequency (HF) antenna and receiver to contribute to the calibration of the Jindalee Operational Radar Network (JORN). Verification of the successful deployment and stability of the large HF antenna is critical to the success of the mission. A bespoke deployable optics payload has been developed by DSTG to fulfil the dual purpose of direct verification of the deployed state of the HF antenna and capturing images of the Earth through a rotatable, dual-surfaced mirror and a variable-focus liquid lens. The payload advances research at DSTG in several fields of space engineering, including deployable mechanisms, precision actuation devices, radiation-tolerant electronics, advanced metal polishing and optical metrology. This paper discusses the payload design, material selection, trade-offs considered for the deployable optics payload and preliminary test results.
Implementing a mentoring program for clinical research professionals: A novel professional development initiative for university health research staff
Authors: Samuels Elias , Champagne Ellen , Lyden Angela K. , Harrington Gloria J. , Kadri Reema , Miner Jennifer A. , Shaikh Sana , Ianni Phillip A. , Eakin Brenda , Murphy Susan 
Published: October 2023

Abstract
Clinical and translational research relies on a well-trained workforce, but mentorship programs designed expressly for this workforce are lacking. This paper presents the development of a mentoring program for research staff and identifies key programmatic outcomes. Research staff participating in this program were matched with a senior mentor. Focus groups were conducted to identify key program outcomes. Surveys were administered throughout the program period to assess participants’ experience, gains in skill, and subsequent careers. Analysis of the resultant qualitative and quantitative data are used to characterize the implementation and impact of the program. A total of 47 mentees and 30 mentors participated in program between 2018 and 2023. A comprehensive logic model of short-, intermediate- and long-term outcomes was developed. Participants reported positive valuations of every programmatic outcome assessed including their program experience, learning and research careers. The pool of available mentors also grew as new mentors were successfully recruited for each cohort. This mentorship program developed and implemented by senior research staff successfully provided junior research staff with professional development support, mentorship, and professional development opportunities. Junior and senior health research staff built mentoring relationships that advanced their clinical and translational research careers.
Development and use of a novel tool for assessing and improving researcher embeddedness in learning health systems and applied system improvements
Authors: Shippee Nathan D. , Danan Elisheva R. , Linzer Mark , Parsons Helen M. , Beebe Timothy J. , Enders Felicity T. 
Published: October 2023

Abstract
This paper outlines the development, deployment and use, and testing of a tool for measuring and improving healthcare researcher embeddedness – i.e., being connected to and engaged with key leverage points and stakeholders in a health system. Despite the widely acknowledged importance of embeddedness for learning health systems and late-stage translational research, we were not aware of useful tools for addressing and improving embeddedness in scholar training programs. We developed the MN-LHS Embeddedness Tool covering connections to committees, working groups, leadership, and other points of contact across four domains: patients and caregivers; local practice (e.g., operations and workflows); local institutional research (e.g., research committees and agenda- or initiative-setting groups); and national (strategic connections within professional groups, conferences, etc.). We used qualitative patterns and narrative findings from 11 learning health system training program scholars to explore variation in scholar trajectories and the embeddedness tool’s usefulness in scholar professional development. Tool characteristics showed moderate evidence of construct validity; secondarily, we found significant differences in embeddedness, as a score, from baseline through program completion. The tool has demonstrated simple, practical utility in making embeddedness an explicit (rather than hidden) part of applied and learning health system researcher training, alongside emerging evidence for validity.