bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploiting OFDM method for quantum communication
Authors: Sabaawi Abdulbasit M. A. , Almasaoodi Mohammed R. , Imre Sándor 
Published: June 2024

AbstractOrthogonal frequency-division multiplexing (OFDM) is a crucial modulation method used in contemporary digital communication systems for its significant spectral efficiency, low latency, and robustness in challenging environments. This work examines the novel use of OFDM in quantum communication, an area that offers exceptional security and efficiency in information transfer using quantum mechanics principles. In the rapidly evolving field of quantum computing, understanding, and mitigating quantum bit errors is paramount. This paper presents a rigorous analysis of bit error rates (BER) in quantum circuits, focusing on the impact of the quantum Fourier transform and its inverse, contrasted against quantum circuits employing dynamic gate sequences. Our research methodology encompasses simulations over a diverse set of parameters, including varying qubit counts ranging from 2 to 8 and theta angles (15, 30, 45, and 60°), as well as random theta values, utilizing the advanced capabilities of the Qiskit framework. Our findings indicate that quantum OFDM substantially improves quantum communication, lowering errors and boosting security. The quantum model outperforms the reference model in BER, with further enhancements as qubits increase.
The representation, quantification, and nature of genetic information
Authors: Thorvaldsen Steinar , Øhrstrøm Peter , Hössjer Ola 
Published: June 2024

AbstractCurrent genetics studies often refer to notions from information science. The purpose of this paper is to summarize and structure the different notions of information used in biology, as a step towards developing a taxonomy of information. Within this framework we propose an extension of Floridi’s conceptual model of information. We also make use of the concept of specified information and show that functional information and many other notions of information are either special cases of, or are closely related to, specified information. Since functionality of the proteins that genes code serves as an external and independent specification, this makes it possible to define genetic information in a way that includes semantic aspects. In particular, we discuss how to understand the qualitative aspects of genetic information, how to measure its quantitative aspects, and how variants of Shannon’s information measure can be applied to molecular sequence data of protein families. While a mathematical framework may not be able to incorporate all that is included within biological information, some aspects of it allow for statistical modelling. This is especially true if we restrict our focus on the discipline of genetics. The concept of genetic information is still disputed because it attributes semantic traits to what seems to be regular biochemical entities. Some researchers maintain that the use of information in biology is just metaphorical and may even be misleading. We argue that the foundation of the metaphorical view is relatively weak given the current findings in bioinformatics and show that the present understanding of genetics fits well into the context of the modern philosophy of information. The paper concludes that informational concepts have robust scientific applications at the level of genes.
Toward a third-generation rational choice theory: the multiple player approach to collective action problems
Authors: Brandt Urs Steiner , Poulsen Anders , Svendsen Gert Tinggaard 
Published: June 2024

AbstractThis paper aims to contribute to the development of a “third-generation” rational choice theory by introducing a Multiple Player Approach for analysing collective action problems. Drawing on the foundational first and second generation works of Olson (The logic of collective action, Cambridge University Press, Cambridge, 1965) and Ostrom (Scand Polit Stud 23(1):3–16), we introduce five player types that we believe capture essential empirical features of many real world collective action problems: Blind Riders, Tough Riders, Hard Riders, Easy Riders, and Low Riders. We consider the complex interaction and dynamics that unfold among them. The main novelty of the analysis is to draw attention to the need for active societal support to effectively empower and reward hard riders for resolving collective action problems, particularly when facing external shocks such as the Covid-19 pandemic, Brexit, and financial crises.
Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model
Authors: Schnipper Jeffrey L. , Oreper Sandra , Hubbard Colin C. , Kurbegov Dax , Egloff Shanna A. Arnold , Najafi Nader , Valdes Gilmer , Siddiqui Zishan , O.’Leary Kevin J. , Horwitz Leora I. , Lee Tiffany , Auerbach Andrew D. 
Published: June 2024

Abstract
Background
Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge.

Objective
To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19.

Design
Multicenter retrospective observational cohort study, 2020–2021, with 30-day follow-up.

Participants
Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system.

Main Measures
Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN).

Key Results
The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model’s AUC for the internal validation set was 0.73 (95% CI 0.71–0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set.

Conclusions
This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.
Sociodemographic and psychological factors affecting motor vehicle crashes (MVCs): a classification analysis based on the contextual-mediated model of traffic-accident involvement
Authors: Tinella Luigi , Bosco Andrea , Koppel Sjaan , Lopez Antonella , Spano Giuseppina , Ricciardi Elisabetta , Traficante Sergio , Napoletano Rosa , Grattagliano Ignazio , Caffò Alessandro Oronzo 
Published: June 2024

AbstractThe study aimed to determine the sociodemographic and psychological profiles of drivers with a history of motor vehicle crashes (MVCs), following the contextual-mediated model of crash involvement, and trying to define similarities and differences with drivers without MVCs. Although road trauma prevention has become a central public health issue, the study of psychological determinants of MVCs does not have consistent results due to methodological and theoretical weaknesses. Three-hundred and forty-five active drivers (20% females) completed an extensive office-based fitness-to-drive evaluation including measures of cognition, personality, self-reported driving-related behaviors, attitudes, as well as computerized measures of driving performance. The Classification and Regression Tree method (CART) was used to identify discriminant predictors. The classification identified several relevant predictors; the personality trait of Discostraint (as a distal context variable; cut-point: 50 T points) and motor speed (as a proximal context variable; cut-point: 64 percentile ranks). The global classification model increased approximately 3 times the probability of identifying people with a history of MVC involvement, starting from an estimated prevalence of being involved in an MVC in a period of five years in the population of active drivers. Consistent with the ‘contextual-mediated model of traffic accident involvement’, the results of the present study suggest that road trauma analysis should focus on both distal and proximal driver-related factors by paying attention to their association in determining MVCs. These results represent a valuable source of knowledge for researchers and practitioners for preventing road trauma.
On the linkage of momentum and reversal – evidence from the G7 stock markets
Authors: Hofmann Daniel , Keiber Karl Ludwig , Luczak Adalbert 
Published: June 2024

AbstractThis paper studies the linkage of momentum and reversal in the G7 stock markets. We confirm Conrad and Yavuz’s (Rev Financ 21(2):555–581, 2017) finding that momentum is not linked to subsequent return reversal in the US stock market. In the stock markets of the remaining G7 countries, our results object the decoupling of momentum and return reversal. In these stock markets, the two return anomalies are linked to each other. In particular, momentum is followed by return reversal in the stock markets of Germany, the UK, Japan, Canada, France, and Italy. These observations obtain for momentum portfolios which are made up of different risk profiles with respect to size and book-to-market ratio. Our results hold true both in raw returns and in risk-adjusted returns.
Network Design and Control: Shape and Topology Optimization for the Turnpike Property for the Wave Equation
Authors: Gugat Martin , Qian Meizhi , Sokolowski Jan 
Published: June 2024

AbstractThe optimal control problems for the wave equation are considered on networks. The turnpike property is shown for the state equation, the adjoint state equation as well as the optimal cost. The shape and topology optimization is performed for the network with the shape functional given by the optimality system of the control problem. The set of admissible shapes for the network is compact in finite dimensions, thus the use of turnpike property is straightforward. The topology optimization is analysed for an example of nucleation of a small cycle at the internal node of network. The topological derivative of the cost is introduced and evaluated in the framework of domain decomposition technique. Numerical examples are provided.
Blick ins Innere: Analyse von 3D-Kulturen mittels Mikrokavitätenarrays
Authors: Zitzmann Franziska D. , Schmidt Sabine , Jahnke Heinz-Georg 
Published: June 2024

AbstractThree-dimensional cultures are a big step towards a more accurate mimicry of the in vivo environment. Given the limited availability of non-invasive analysis methods, especially beyond 2D cultures, we have developed a platform for multimodal bioelectronic monitoring in combination with our microcavity array technology for label-free real-time analysis of 3D cultures. This allows a wide range of cell-specific processes and drug responses to be studied with enhanced spatial resolution and in an automated setting.
Stressresistenz durch Adaption der mitochondrialen Form
Authors: Anton Vincent , Escobar-Henriques Mafalda 
Published: June 2024

AbstractMitochondria are dynamic cellular compartments that can remodel their own shape and activity. They sense and convert cellular signals into informative triggers, allowing the cell to adapt to its ever-changing needs. We discovered that under stress this adaptation is performed by the E4 enzyme Ufd2/UBE4B, which tags mitochondrial fusion factors called mitofusins, thus signalling their degradation. Our findings highlight therapeutic intervention cues for mitofusin-associated diseases.
Transformation privaträumlicher Lebenswelten
Authors: Retkowski Alexandra , Glunde Bettina , Hilbig Melanie 
Published: June 2024

ZusammenfassungDer Beitrag greift mit der Wohnraumberatung ein bislang in Deutschland öffentlich kaum wahrgenommenes und wissenschaftlich gering untersuchtes Tätigkeitsfeld von Fachleuten auf, die über eine Zusatzqualifikation verfügen und unterschiedlichen Grundberufen wie z. B. Sozialarbeiter*innen, Mitarbeiter*innen des Gesundheitsdienstes oder der Wohnungswirtschaft nachgehen oder aber ehrenamtlich tätig sind. Das Handlungsfeld ist mit Blick auf sozialökologische Transformationsprozesse von immenser Bedeutung, da es an der Schnittstelle von privater Lebenswelt, gesundheitsbezogener Daseinsvorsorge und auf Nachhaltigkeit ausgerichteten sozialräumlichen Entwicklungen liegt. Vor diesem Hintergrund entwirft der Beitrag mit dem Konzept der sozialräumlichen Resilienz einen Orientierungsrahmen für Professionalisierungsoptionen des Beratungsangebots zur Wohnraumanpassung älterer Menschen. Am Beispiel des Brandenburger Teils der Lausitz werden Fragen der präventiven Gesundheitsvorsorge mit den regional und besonders im ländlichen Raum gegebenen Krisenphänomenen des demografischen Wandels, des Fachkräftemangels im Sozial- und Gesundheitssektor sowie den ökologischen Dimensionen im Wohn- und Bausektor in Verbindung gebracht. Diese Perspektive auf Beratungsprozesse steht vor der besonderen Herausforderung, die Bedarfe und Bedürfnisse älterer Menschen nach Versorgung, Barrierefreiheit und Selbstständigkeit ins Verhältnis zu setzen zur Notwendigkeit, die ältere Bevölkerung gleichsam auch als Akteur*innen des sozialökologischen Strukturwandels zu adressieren. In diesem Zusammenhang kann Wohnraumberatung als Medium gesellschaftlicher, transdisziplinärer Aushandlungsprozesse verstanden werden, welche individuelle, sozialräumliche und ökologische Aspekte in der Daseinsvorsorge berücksichtigt.
The Implicit Equation of a Holditch Curve
Authors: Monterde Juan , Rochera David 
Published: June 2024

AbstractHolditch’s theorem is a classical geometrical result on the areas of a given closed curve and another one, its Holditch curve, which is constructed as the locus of a fixed point dividing a chord of constant length that moves with its endpoints over the given curve and that returns back to its original position after some full revolution. Holditch curves have already been studied from the parametric point of view, although numerical methods and approximations are often necessary for their computation. In this paper, implicit equations of Holditch curves of algebraic curves are studied. The implicit equations can be simply found from the computation of a resultant of two polynomials. With the same techniques, Holditch curves of two initial algebraic curves are also considered. Moreover, the use of implicit equations allows to find new and explicit parameterizations of non-trivial Holditch curves, such as in the case of having an ellipse as an initial curve.
Operational efficiency and sustainability in smart ports: a comprehensive review
Authors: Alzate Paola , Isaza Gustavo A. , Toro Eliana M. , Jaramillo-Garzón Jorge A. , Hernandez Sara , Jurado Isabella , Hernandez Diana 
Published: June 2024

AbstractThe challenges of optimizing logistics operations in all links of the supply chain have led to the development of new dynamics around the revolution 4.0 and the response of operational efficiency linked to environmental sustainability. Smart ports are born as a strategy to meet customer needs from a technological evolution that generates quality logistical and operational responses. The objective of this review is to identify and to analyze the research perspectives related to smart ports. The implemented methodology considered a scientific mapping to determine the most relevant publications in terms of authors, journals, and countries with the greatest scientific participation in the subject and a network analysis based on the implementation of the tree metaphor of the graph theory. The R-studio software and the Bibliometrix plugin were used to process the information. The review considered 204 documents from the Scopus and Web of Science databases, identifying a growing trend in the number of enhanced publications as of 2019, with China being the country with the largest number of papers. In relation to research trends, the adaptation of ports to industry 4.0, maritime ports and technological security, and green and smart ports are the perspectives on the subject of study. Finally, an agenda for future research is presented.
Towards Responsible Urban Geospatial AI: Insights From the White and Grey Literatures
Authors: Marasinghe Raveena , Yigitcanlar Tan , Mayere Severine , Washington Tracy , Limb Mark 
Published: June 2024

AbstractArtificial intelligence (AI) has increasingly been integrated into various domains, significantly impacting geospatial applications. Machine learning (ML) and computer vision (CV) are critical in urban decision-making. However, urban AI implementation faces unique challenges. Academic literature on responsible AI largely focuses on general principles, with limited emphasis on the geospatial domain. This important gap in scholarly work could hinder effective AI integration in urban geospatial applications. Our study employs a multi-method approach, including a systematic academic literature review, word frequency analysis and insights from grey literature, to examine potential challenges and propose strategies for effective geospatial AI (GeoAI) integration. We identify a range of responsible practices relevant to the complexities of using AI in urban geospatial planning and its effective implementation. The review provides a comprehensive and actionable framework for responsible AI adoption in the geospatial domain, offering a roadmap for urban researchers and practitioners. It highlights ways to optimise AI benefits while minimising potential negative consequences, contributing to urban sustainability and equity.
Integrated Dataset-Preparation System for ML-Based Medical Image Diagnosis with High Clinical Applicability in Various Modalities and Diagnoses
Authors: Nguyen My N. , Harada Kotori , Yoshimoto Takahiro , Duong Nam Phong , Sowa Yoshihiro , Sakai Koji , Fukuzawa Masayuki 
Published: June 2024

AbstractThis study proposed an integrated dataset-preparation system for ML-based medical image diagnosis, offering high clinical applicability in various modalities and diagnostic purposes. With the proliferation of ML-based computer-aided diagnosis using medical images, massive datasets should be prepared. Lacking of a standard procedure, dataset-preparation may become ineffective. Besides, on-demand procedures are locked to a single image-modality and purpose. For these reasons, we introduced a dataset-preparation system applicable for a variety of modalities and purposes. The system consisted of a common part including incremental anonymization and cross annotation for preparing anonymized unprocessed data, followed by modality/subject-dependent parts for subsequent processes. The incremental anonymization was carried out in batch after the image acquisition. Cross annotation enabled collaborative medical specialists to co-generate annotation objects. For quick observation of dataset, thumbnail images were created. With anonymized images, preprocessing was accomplished by complementing manual operations with automatic operations. Finally, feature extraction was automatically performed to obtain data representation. Experimental results on two demonstrative systems dedicated to esthetic outcome evaluation of breast reconstruction surgery from 3D breast images and tumor detection from breast MRI images were provided. The proposed system successfully prepared the 3D breast-mesh closures and their geometric features from 3D breast images, as well as radiomics and likelihood features from breast MRI images. The system also enabled effective voxel-by-voxel prediction of tumor region from breast MRI images using random-forest and k-nearest-neighbors algorithms. The results confirmed the efficiency of the system in preparing dataset with high clinical applicability regardless of the image modality and diagnostic purpose.
Shear strengthening of damaged reinforced concrete beams with iron-based shape memory alloy (Fe-SMA) strips: numerical and parametric analysis
Authors: Tabrizikahou Alireza , Białasik Jan , Borysiak Sławomir , Fabisiak Mateusz , Łasecka-Plura Magdalena , Jesionowski Teofil , Kuczma Mieczysław 
Published: June 2024

AbstractShape memory alloys (SMAs) are metallic materials that are characterized by their ability to restore their original shape after large deformation when activated by heating. This unique property renders SMAs appealing for various civil engineering applications. Iron-based SMAs (Fe-SMAs), including alloys like Fe–Mn–Si, stand out due to their cost-effectiveness and high strength. The primary focus of this research lies in the computational modeling of Fe-SMA strips utilized to reinforce damaged concrete structures. To achieve this, details from an experimental test are leveraged for the computational simulation of real-scale reinforced concrete beams that were first loaded to some level of damage, then released and strengthened, and subsequently retested. The strengthening approach involves the application of external Fe-SMA strips wrapping around the beams. This paper presents an original computational modeling setup that incorporates a switch option for the Fe-SMA material. This feature enables one to use a single simulation platform for the whole process. The significance of this method originates from its capacity to ensure a robust analysis that includes all simulation steps-testing unstrengthened beams, installing and heating Fe-SMA strips, and testing both damaged and strengthened beams—in a single, multi-step analysis. The computational simulation results were compared with the outcomes of the experimental test, revealing an acceptable level of agreement. The findings indicate a substantial increase in both shear strength and ductility as a result of the application of Fe-SMA strips. Additionally, parametric and mesh sensitivity studies were conducted. These aimed to investigate the mesh dependency of the model and to identify the optimal mesh size. Furthermore, variations in the details of the Fe-SMA strips, including thickness, width, quantity, and effect of applied temperature were explored to compare the outcomes of different applications of these strips.