bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimising the balance of acute and intermediate care capacity for the complex discharge pathway: Computer modelling study during COVID-19 recovery in England
Authors: Onen-Dumlu Zehra , Harper Alison L. , Forte Paul G. , Powell Anna L. , Pitt Martin , Vasilakis Christos , Wood Richard M. 
Published: June 2022

Objectives
While there has been significant research on the pressures facing acute hospitals during the COVID-19 pandemic, there has been less interest in downstream community services which have also been challenged in meeting demand. This study aimed to estimate the theoretical cost-optimal capacity requirement for ‘step down’ intermediate care services within a major healthcare system in England, at a time when considerable uncertainty remained regarding vaccination uptake and the easing of societal restrictions.

Methods
Demand for intermediate care was projected using an epidemiological model (for COVID-19 demand) and regressing upon public mobility (for non-COVID-19 demand). These were inputted to a computer simulation model of patient flow from acute discharge readiness to bedded and home-based Discharge to Assess (D2A) intermediate care services. Cost-optimal capacity was defined as that which yielded the lowest total cost of intermediate care provision and corresponding acute discharge delays.

Results
Increased intermediate care capacity is likely to bring about lower system-level costs, with the additional D2A investment more than offset by substantial reductions in costly acute discharge delays (leading also to improved patient outcome and experience). Results suggest that completely eliminating acute ‘bed blocking’ is unlikely economical (requiring large amounts of downstream capacity), and that health systems should instead target an appropriate tolerance based upon the specific characteristics of the pathway.

Conclusions
Computer modelling can be a valuable asset for determining optimal capacity allocation along the complex care pathway. With results supporting a Business Case for increased downstream capacity, this study demonstrates how modelling can be applied in practice and provides a blueprint for use alongside the freely-available model code.
Development and psychometric evaluation of the emergency nurses’ professional resilience tool
Authors: Norouzinia Roohangiz , Yarmohammadian Mohammad Hosein , Ferdosi Masoud , Masoumi Gholamreza , Ebadi Abbas 
Published: June 2022

Background
There is no specific tool for measuring the professional resilience of emergency nurses. Therefore, the present study aimed to design and psychometrically evaluate a new tool named the emergency nurses’ professional resilience tool.

Method
This mixed-method sequential exploratory study was conducted in two phases: (1) item generation using literature review and evaluation of the results of a qualitative study and (2) psychometric evaluation of the developed scale. The face, content, and construct validity (exploratory and confirmatory factor analysis), reliability (internal consistency, relative, and absolute), and accountability were assessed in the population of Iranian nurses (N = 465) during March 2019-June 2020.

Results
The tool designed for assessing the professional resilience of Iranian nurses included 37 items. The average scale content validity index (S-CVI/Ave) was equal to 0.94. The exploratory factor analysis revealed five factors, including professional competencies, emotional-cognitive characteristics, external support, in addition to behavioral and cognitive strategies, and explained 75.59% of the whole variance. Cronbach’s alpha and intraclass correlation were 0.915 and 0.888, respectively. Construct validity for five factors was established with acceptable model fit indices [Chi–square/df = 1336.56/619, p < .001]; [Comparative Fit Index [CFI] = 0.96]; [Non-Normed Fit Index [NNFI] = 0.96]; [Root Mean Square Error of Approximation (RMSEA) = 0.074 and 90 Percent Confidence Interval = (0.069; 0.080)]; and [SRMR = 0.095].

Conclusions
According to the findings of the current study, the emergency nurses’ professional resilience tool can be used by healthcare managers as a valid and reliable scale to evaluate the professional resilience of nurses to designate them as nurses working in emergency and disaster situations.
Magnitude of job satisfaction and intention to leave their present job among nurses in selected federal hospitals in Addis Ababa, Ethiopia
Authors: Woldekiros Aynye Negesse , Getye Elsabet , Abdo Ziyad Ahmed 
Published: June 2022

BackgroundJob dissatisfaction issues and health workers’ intention to leave is an increasing problem that threatens the function of the health care sector worldwide, especially in developing countries, including Ethiopia. As part of future evidence, this study was intended to assess nurses’ job satisfaction and intention to leave their current work and its associated factors in federal public hospitals in Addis Ababa, Ethiopia.MethodAn institutional based cross-sectional study design was used to conduct the study. A simple random sampling technique was employed to select 408 nurses from selected federal hospitals in Ethiopia. Self-administered questionnaire was used to collect the data. Logistic regression was employed to identify the predictor variables with consideration of statistical significance at P <0.05 adjusted odds ratios calculated at 95% CIs.ResultThe magnitudes of job satisfaction and intention to leave their current job among nurses in this study were 47.7% and 80.6%, respectively. Salary is imbalanced with demands [AOR = 2.85 (1.24, 6.57)], managers who have no personal plan for developing skills [AOR = 3.74 (1.58, 8.87)], stressful jobs [AOR = 0.28 (0.11, 0.71)], health problems are a reason for having thoughts about changing jobs [AOR = 3.02 (1.17, 7.79)], and a lack of development [AOR = 4.13 (1.51, 11.3)] were identified as determinant factors for intention to leave.ConclusionThe overall intention to leave their current job among nurses working in selected federal hospitals in Ethiopia was high. The government of Ethiopia should balance the salary of nurses with the current market level. Hospital leaders should plan the way nurses develop their educational and job carrier levels.
Compassion
Authors: Matos Marcela , Pereira Marco 
Published: June 2022

Compassion is an ancient concept but novel hot topic across the social sciences, from psychology, to sociology, to health, to communication and media, to politics and beyond. Burgeoning research has demonstrated the benefits of compassion for mental health and emotion regulation (e.g., MacBeth & Gumley, 2012; Matos et al., 2022), physiological health (e.g., Fredrickson et al., 2013; Kim et al., 2020; Klimecki et al., 2014), and interpersonal and social relationships (e.g., Crocker & Canevello, 2012; Yarnell & Neff, 2013). In particular, self-compassion has been shown to be a protective factor, increasing resilience to common mental health issues (e.g., shame, self-criticism; MacBeth & Gumley, 2012; Muris & Petrocchi, 2017) and promoting wellbeing (Zessin et al., 2015). In addition to compassion offering wellbeing benefits, compassion and self-compassion can also be cultivated and enhanced through interventions, in diverse populations and contexts, where they have been shown to promote well-being and to diminish mental health difficulties (e.g., depression, anxiety, stress, shame, self-criticism) (e.g., Craig et al., 2020; Ferrari et al., 2019; Kirby et al., 2017).
Given the global challenges facing our world and the need for collective action, and inspired by the notion in evolutionary science that a conscious evolution toward a more compassionate world is possible (see Wilson, 2020), this special issue of the journal Psychologica presents research, applications and multi-cultural considerations related to compassion. In this special issue, several researchers and clinicians, including prominent names in the field and history of compassion, such as Prof. Paul Gilbert, made valuable contributions to expand the science of compassion and disseminate this knowledge into community, educational, clinical and public health settings. These studies are focused on different cultures (Portuguese, Australian, Singaporean), populations (clinical and nonclinical), age groups (adolescents and adults), clinical conditions (Borderline Personality Disorder, Social Anxiety Disorder Hoarding Disorder), and applications (compassion-based programs for adolescents and adults, for distinct clinical conditions and with different formats). Let us give you a short-guided tour through the headlines of this special issue. (...)
Analysis of sentiments on the onset of Covid-19 using Machine Learning Techniques
Authors: Arya Vishakha , Mishra Amit Kumar Mishra , González-Briones Alfonso 
Published: June 2022

The novel coronavirus (Covid-19) pandemic has struck the whole world and is one of the most striking topics on social media platforms. Sentiment outbreak on social media enduring various thoughts, opinions, and emotions about the Covid-19 disease, expressing views they are feeling presently. Analyzing sentiments helps to yield better results. Gathering data from different blogging sites like Facebook, Twitter, Weibo, YouTube, Instagram, etc., and Twitter is the largest repository. Videos, text, and audio were also collected from repositories. Sentiment analysis uses opinion mining to acquire the sentiments of its users and categorizes them accordingly as positive, negative, and neutral. Analytical and machine learning classification is implemented to 3586 tweets collected in different time frames. In this paper, sentiment analysis was performed on tweets accumulated during the Covid-19 pandemic, Coronavirus disease. Tweets are collected from the Twitter database using Hydrator a web-based application. Data-preprocessing removes all the noise, outliers from the raw data. With Natural Language Toolkit (NLTK), text classification for sentiment analysis and calculate the score subjective polarity, counts, and sentiment distribution. N-gram is used in textual mining -and Natural Language Processing for a continuous sequence of words in a text or document applying uni-gram, bi-gram, and tri-gram for statistical computation. Term frequency and Inverse document frequency (TF-IDF) is a feature extraction technique that converts textual data into numeric form. Vectorize data feed to our model to obtain insights from linguistic data. Linear SVC, MultinomialNB, GBM, and Random Forest classifier with Tfidf classification model applied to our proposed model. Linear Support Vector classification performs better than the other two classifiers. Results depict that RF performs better.
Linguistic and Cognitive Essence of Relations in Dialect Worldview of Kuban Region Inhabitants (Based on the Example of Blood Relatives Microfield) (part 2)
Authors: Kostina Ludmila , Olga Borisova 
Published: June 2022

The second part of the article presents a description of the linguistic and cognitive essence of blood relatives relations in the dialect worldview of Kuban region inhabitants. The study defines the connotation content of the analyzed microfield representatives by stereotyping the family role and position of blood relatives, their interrelations and qualities, which are vital from the Kuban dialect carriers’ point of view. It demonstrates various cognitive potential of microfield constituents which involves some notions having (in peoples’ mind) conjoined meanings and others lacking some. The article demonstrates, that children are a cognitive dominant idea of the Blood Relatives microfield, that leads to their natural ranking into categories, which is manifested in a range of relevant concept-building characteristics. Statements of dialect carriers prove the importance of a traditional role of the family in younger generation upbringing. The research demonstrates, that means оf the described microfield representation, refer to the idea of blood relatives relations, inherent in this ethnical culture, which contains both archaic and modern beliefs of Kuban dialect carriers.
Adjustable intragastric balloon leads to significant improvement in obesity-related lipidome and fecal microbiome profiles: a proof of concept study
Authors: Hussan Hisham , Abu Dayyeh Barham K. , Chen Jun , Johnson Stephen , Riedl Ken , Grainger Elizabeth M. , Brooks Jeffrey , Hinton Alice , Simpson Christina , Kashyap Purna C. 
Published: June 2022

BACKGROUND:
Intragastric balloons (IGB) are a safe and effective treatment for obesity. However, limited knowledge exists on the underlying biological changes with IGB placement.

METHODS:
This single-institution study was part of an adjustable IGB randomized controlled trial. Subjects with obesity were randomized in a 2 to 1 ratio to 32 weeks of IGB with diet/exercise counseling (n=8) versus counseling alone (controls, n=4). Diet/exercise counseling was continued for 24 weeks post-IGB removal to assess weight maintenance. We used mass spectrometry for non-targeted plasma lipidomics analysis and 16S rRNA sequencing to profile the fecal microbiome.

RESULTS:
IGB subjects lost 15.5% of their body weight at 32 weeks versus 2.59% for controls (P<0.05). Maintenance of a 10.5% weight loss occurred post-IGB explant. IGB placement followed by weight maintenance led to a -378.9 uM/L reduction in serum free fatty acids compared to pre-IGB (95% CI: -612.9, -145.0). This reduction was mainly in saturated, mono, and omega-6 fatty acids when compared to pre-IGB. Polyunsaturated phosphatidylcholines also increased after IGB (difference of 27 uM/L; 95% CI: 1.1, 52.8). Compared to controls, saturated and omega-6 free fatty acids (linoleic and arachidonic acids) were reduced after IGB. The fecal microbiota changed post-IGB placement and weight maintenance versus pre-IGB (P<0.05). Further analysis showed a possible trend toward reduced Firmicutes and increased Bacteroidetes post-IGB and counseling, a change that was not conclusively different from counseling alone.
IGB treatment is associated with an altered fecal microbiome profile and may have a better effect on the obesity-related lipidome than counseling alone.
epistemología como disciplina científica para el desarrollo de la investigación en los estudios de postgrado
Authors: Marquez-Fernandes Alvaro , Mendez Evaristo 
Published: June 2022

Resumen: En este artículo expondremos, a rasgos generales, la politica modernizadora de los Estudios de Postgrado en la Universidad del Zulia (Maracaibo-Venezuela). Estos Estudios requieren, al menos, de cuatro variables de integración curricular que favorezcan la interacción con los Centros e Institutos de Investigación. Para un óptimo desarrollo de los mismos, consideramos que la epistemología debe tener una importancia de disciplina científica. Ésta, además de fundar los criterios de racionalidad de los modelos científicos, enriquece el nivel metodológico de los postgraduandos en cuanto futuros investigadores.
Palabras clave: Epistemologia; Estudios de Postgrado; Investigación; Venezuela.

Resumé: Dans cet article nous exposons la politique de modernisation des estudes de postgrade à l'Université du Zulia (Maracaibo-Vénézuéla). Ces Etudes requièrent au moins, de quatre variables d'intégration curriculaire Qui favorisent l'echange avec les Centres et Institutes consacrés à la Recherche. Pour un developpement optime de ces Etudes, nous considerons qu'on dit reconnaître l' épistémologie comme une discipline cientifique Celle-ci non seulemente fonde les critères de rationalité des modéles scientifiques, mais en plus elle enrichit le niveau methodologique des posgradués en tant que chercheurs.
Mots Clef: Epistémologie; Etudes de Postgrade; Recherche; Vénézuéla.
The evolution of time-dependent Λ and G in multi-fluid Bianchi type-I cosmological models
Authors: Alfedeel Alnadhief H. A. , Abebe Amare 
Published: June 2022

Abstract
In this work, cosmological solutions based on the time-dependent cosmological (

Λ

\Lambda

) and Newtonian (

G

G

) running “constants” in the Bianchi type-I spacetime are investigated vis-à-vis known cosmological data. The observationally known values of

Ω

m

,

Ω

r

{\Omega }_{{\rm{m}}},{\Omega }_{{\rm{r}}}

and

Ω

Λ

{\Omega }_{\Lambda }

have been used to solve the Einstein field equations for the model and the resulting behaviours of the physical and dynamical quantities, with particular emphasis on late-time cosmology, are discussed. Our analysis indicates that certain choices of the defining model parameters give results consistent with the observed behaviour of the universe, such as accelerated expansion and an early anisotropy that vanishes at late times.
An ontology for remanufacturing systems
Authors: Pfrommer Julius , Klein Jan-Felix , Wurster Marco , Rapp Simon , Grauberger Patric , Lanza Gisela , Albers Albert , Matthiesen Sven , Beyerer Jürgen 
Published: June 2022

Abstract
A fully automated remanufacturing system needs to be very adaptive in order to adjust to different product variants and the condition of received products. To allow for such adaptive behavior across different subsystems and levels from the classical automation hierarchy, a common and uniform understanding regarding the core concepts that constitute a remanufacturing system is required. This article presents an ontology for the core concepts in an automated remanufacturing system.
Agiles Produktionssystem mittels lernender Roboter bei ungewissen Produktzuständen am Beispiel der Anlasser-Demontage
Authors: Lanza Gisela , Asfour Tamim , Beyerer Jürgen , Deml Barbara , Fleischer Jürgen , Heizmann Michael , Furmans Kai , Hofmann Constantin , Cebulla Alexander , Dreher Christian , Kaiser Jan-Philipp , Klein Jan-Felix , Leven Fabian , Mangold Simon , Mitschke Norbert , Stricker Nicole , Pfrommer Julius , Wu Chengzhi , Wurster Marco , Zaremski Manuel 
Published: June 2022

Zusammenfassung
Agile Produktionssysteme vereinen ein hohes Maß an Flexibilität und Wandlungsfähigkeit. Diese Qualitäten sind insbesondere in einer Umgebung mit hoher Unsicherheit entscheidend, beispielsweise im Kontext von Remanufacturing. Remanufacturing beschreibt den industriellen Prozess der Aufbereitung von Gebrauchtteilen, sodass diese vergleichbare technische Eigenschaften wie Neuteile zurückerlangen. Aufgrund der Ressourcenknappheit und regulatorischer Vorgaben nimmt die Bedeutung von Remanufacturing zu. Bedingt durch die unvorhersehbaren Bauteileigenschaften spielt Automatisierung im Remanufacturing eine untergeordnete Rolle. Die Autoren präsentieren ein Konzept, wie eine automatisiere Demontage auch bei Bauteilen ungewisser Spezifikationen durch den Einsatz von künstlicher Intelligenz erreicht werden kann. Zum autonomen Aufbau der Demontagefähigkeiten werden zum einen gezielt digitale Zwillinge als Lernumgebungen eingesetzt. Zum anderen werden aus der Beobachtung des Menschen Fähigkeiten und Problemlösungsstrategien identifiziert und abstrahiert. Um ein effizientes, vernetztes Demontagesystem zu erreichen, findet ein modulares Stationskonzept Anwendung, sowohl auf technischer als auch auf informationstechnischer Ebene.
Lernende Roboter für die spanende Bearbeitung leicht zerspanbarer Materialien
Authors: Gollee Christian , Selch Maximilian , Schenke Christer-Clifford , Hellmich Arvid , Ihlenfeldt Steffen 
Published: June 2022

Zusammenfassung
Wandlungsfähige Produktionssysteme werden oft im Kontext von Effizienzsteigerungen trotz sinkender Losgrößen und steigender Produktvariationen diskutiert. Aber auch derzeit noch manuell ausgeführte Prozesse können durch automatisierte Produktionssysteme realisiert werden, sofern sie sich an veränderliche Aufgaben und Randbedingungen autonom anpassen können. Nachgelagerte Prozesse bei der additiven Fertigung, wie das Reinigen der Bauteile, das Entfernen von Stützstrukturen und das Bearbeiten von Funktionsflächen sind hierfür Beispiele. Der vorliegende Artikel stellt ein Konzept der autonomen Nachbearbeitung additiv gefertigter Bauteile vor. Es werden die Integration von Lernverfahren in die Steuerung einer modularen, NC-roboterbasierten Fertigungszelle vorgestellt und zwei Aspekte des Lernens adressiert: Zum einen das initiale Training eines künstlichen neuronalen Netzes anhand von Simulationsdaten und zum anderen die Modifikation der Lernstrategie für das fortgesetzte, kontinuierliche Lernen im Betrieb des Roboters. Das Ziel des Lernens ist die Steigerung der Robotergenauigkeit. Hierzu wird eine, in die Roboterzelle integrierte, 3D-Laserlinienscanstation eingesetzt. Durch Analyse der erfassten Bauteilgeometrie werden unsichere Modellparameter des Roboters geschätzt und der Robotersteuerung mit dem Ziel einer genaueren Fertigung zugänglich gemacht.
Erfassung und Interpretation menschlicher Handlungen für die Programmierung von Robotern in der Produktion
Authors: Dreher Christian R. G. , Zaremski Manuel , Leven Fabian , Schneider David , Roitberg Alina , Stiefelhagen Rainer , Heizmann Michael , Deml Barbara , Asfour Tamim 
Published: June 2022

Zusammenfassung
Der Mensch ist die flexibelste, aber auch eine teure Ressource in einem Produktionssystem. Im Kontext des Remanufacturings sind Roboter eine kostengünstige Alternative, jedoch ist deren Programmierung oft nicht rentabel. Das Programmieren durch Vormachen verspricht eine flexible und intuitive Alternative, die selbst von Laien durchführbar wäre, doch hierfür ist zunächst eine Erfassung und Interpretation von Handlungen des Menschen nötig. Diese Arbeit stellt eine multisensorielle, robotergestützte Plattform vor, welche die Erfassung zweihändiger Manipulationsaktionen sowie menschlicher Posen, Hand- und Blickbewegungen während der Demontage ermöglicht. Im Rahmen einer Studie wurden an dieser Plattform Versuchspersonen bei der Demontage von Elektromotoren aufgezeichnet, um adäquate Datensätze für die Erkennung und Klassifikationen von menschlichen Aktionen zu erhalten.
Operation Warp Speed: A Legal Analysis of the Vaccine Development Process and How We Got Here
Authors: Ascencio Kenia 
Published: June 2022

Abstract
The COVID-19 Pandemic created a need for a vaccine that would need to be rapidly created, tested and approved in order to reduce the pandemic’s tremendous impact on human life and the economy. This article discusses the vaccine development process as well as Operation Warp Speed, the United States plan for emergency vaccine development in a pandemic situation. Written before the approval of the currently available COVID-19 vaccines, this article also discusses the implications of a speedier vaccine development process as well as recommendations to the standard process.