bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of rheumatoid arthritis factors, adenosine deaminases and uric acid in arthritis and non-arthritis patients: A protocol
Authors: Makhe Priyanka A. , Vagga Anjali , Dhok Archana 
Published: September 2023

Rheumatic disorders are viewed as a public health issue because they affect thousands of individuals around the world and increase health care expenses. Numerous biochemical markers may play a role in the pathophysiology and etiology of rheumatoid arthritis (RA) due to its local as well as systemic inflammatory effects. Rheumatoid factors (RF) can be found in a variety of people, including young, healthy people, the elderly, and people with RA. In this study we will assess and compare the occurrence, clinical presentation, effects and possible risk of biochemical parameters such as uric acid, adenosine deaminase (ADA,), RA factor between arthritis patients and non - arthritis patients. A total of 82 participants — 41 RA patients and 41 healthy controls (non-arthritis patients) —will be included in the study. The levels of serum ADA, uric acid, and rheumatoid factor will be examined, and independent tests will be used for the statistical analysis. Serum ADA rheumatoid factors levels in RA patients is higher in healthy control. When comparing the uric acid levels of RA patients with healthy controls, there is no significant change in the uric acid level. The degree underlying ADA activity between RA patients and healthy individuals should differ noticeably, confirming the test’s value in the diagnosis of the condition.
Scalable and versatile container-based pipelines for de novo genome assembly and bacterial annotation.
Authors: Almeida Felipe Marques de , Campos Tatiana Amabile de , Pappas Jr Georgios Joannis 
Published: September 2023

Background: Advancements in DNA sequencing technology have transformed the field of bacterial genomics, allowing for faster and more cost effective chromosome level assemblies compared to a decade ago. However, transforming raw reads into a complete genome model is a significant computational challenge due to the varying quality and quantity of data obtained from different sequencing instruments, as well as intrinsic characteristics of the genome and desired analyses. To address this issue, we have developed a set of container-based pipelines using Nextflow, offering both common workflows for inexperienced users and high levels of customization for experienced ones. Their processing strategies are adaptable based on the sequencing data type, and their modularity enables the incorporation of new components to address the community’s evolving needs. Methods: These pipelines consist of three parts: quality control, de novo genome assembly, and bacterial genome annotation. In particular, the genome annotation pipeline provides a comprehensive overview of the genome, including standard gene prediction and functional inference, as well as predictions relevant to clinical applications such as virulence and resistance gene annotation, secondary metabolite detection, prophage and plasmid prediction, and more. Results: The annotation results are presented in reports, genome browsers, and a web-based application that enables users to explore and interact with the genome annotation results. Conclusions: Overall, our user-friendly pipelines offer a seamless integration of computational tools to facilitate routine bacterial genomics research. The effectiveness of these is illustrated by examining the sequencing data of a clinical sample of Klebsiella pneumoniae.
COVID-19 Vaccine: Predicting Vaccine Types and Assessing Mortality Risk Through Ensemble Learning Agorithms
Authors: Monadhel Hind , Abbas Ayad R. , Mohammed Athraa Jasim 
Published: September 2023

Background: There is no doubt that vaccination is crucial for preventing the spread of diseases; however, not every vaccine is perfect or will work for everyone. The main objective of this work is to predict which vaccine will be most effective for a candidate without causing severe adverse reactions and to categorize a patient as potentially at high risk of death from the COVID-19 vaccine. Methods: A comprehensive analysis was conducted using a dataset on COVID-19 vaccine adverse reactions, exploring binary and multiclass classification scenarios. Ensemble models, including Random Forest, Decision Tree, Light Gradient Boosting, and extreme gradient boosting algorithm, were utilized to achieve accurate predictions. Class balancing techniques like SMOTE, TOMEK_LINK, and SMOTETOMEK were incorporated to enhance model performance. Results: The study revealed that pre-existing conditions such as diabetes, hypertension, heart disease, history of allergies, prior vaccinations, other medications, age, and gender were crucial factors associated with poor outcomes. Moreover, using medical history, the ensemble learning classifiers achieved accuracy scores ranging from 75% to 87% in predicting the vaccine type and mortality possibility. The Random Forest model emerged as the best prediction model, while the implementation of the SMOTE and SMOTETOMEK methods generally improved model performance. Conclusion: The random forest model emerges as the top recommendation for machine learning tasks that require high accuracy and resilience. Moreover, the findings highlight the critical role of medical history in optimizing vaccine outcomes and minimizing adverse reactions.
Rehabilitation needs of people with brain tumours in Ireland: Protocol for a prospective, mixed methods action research study (“Brain-RESTORE”)
Authors: Malone Ailish , O'Donovan Bernadine , Carroll Paul , Donnelly Sarah , Cowie Eloise , Grogan Liam , MacNally Stephen , O'Sullivan Mary , Sorenson Jan , Tiernan Eoin J. , O'Connor Rory J. , MacFarlane John , O'Keeffe Sorcha , Murphy Andrew W. , Keegan Fiona , Horgan Frances , Bennett Kathleen 
Published: September 2023

Background: Approximately 480 people annually in Ireland are diagnosed with a primary brain tumour. Brain tumours are a heterogeneous group of conditions, varying in histopathology, location, and progression. A consistent feature is neurological impairment, which can lead to profound effects on physical and cognitive function. There is evidence that people with brain tumours can benefit from rehabilitation, but pathways are poorly described, and no best practice is defined. This leads to significant unmet need. The aim of this study is to understand the rehabilitation needs of people diagnosed with a brain tumour in Ireland, and gain insight to inform policy and practice. Methods: A prospective, mixed methods study with embedded action research will be conducted. Patients (n=122) with a new diagnosis of primary brain tumour, and optionally, a nominated carer or family member, will be recruited through a national neuro-oncology service. Rehabilitation need (Mayo-Portland Adaptability Inventory), quality of life (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Brain Cancer Module, EuroQol-5D-5L), healthcare utilisation and, optionally, carer needs (Carer Support Needs Assessment Tool) will be assessed at four, eight and 12 months post diagnosis. An embedded qualitative study will invite 30 patients and carers to a semi-structured interview to explore their lived experience of rehabilitation needs and services following brain tumour diagnosis. Finally, using an Action Research approach, healthcare professionals involved in caring for people with brain tumours will be invited to participate in co-operative inquiry groups, to reflect on emerging aggregate findings and identify actions that could be undertaken while the study is underway. Conclusions: By understanding rehabilitation need, the findings will help healthcare professionals and health service providers understand how to prioritise the supports required and encourage policy makers to adequately resource neurorehabilitation to meet the needs of people with a brain tumour diagnosis.
Nonlinear optics properties of Ni-Sb2Se3 nanofilms in the near-infrared region
Authors: Zhang Lu , Ding Chang , Wang Hecong , Sun Wenjun , Zhao Li 
Published: September 2023

Sb2Se3 is an emerging material in recent years, and past studies have shown that it has good optoelectronic properties when doped with metals. In this paper, pure Sb2Se3 films and Ni-Sb2Se3 films with different doping contents (1, 2, 3 W) were prepared by magnetron sputtering technology. The nonlinear optics properties of the sample films were investigated using femtosecond (fs) Z-scan technology under 800 nm. The results showed that both pure Sb2Se3 and doped films exhibited reverse saturated absorption (RSA), and the occurrence of the reverse saturated absorption behavior of the doped films was mainly due to two-photon absorption (TPA), free carrier absorption (FCA), and the presence of defective energy levels. Compared with pure Sb2Se3 films, Ni-Sb2Se3 films exhibit significantly enhanced nonlinear absorption properties and nonlinear refractive properties. By increasing Ni sputtering power and incident laser energy, the nonlinear optic properties of Ni-Sb2Se3 films are enhanced. By testing the sample films using SEM, XRD, and UV-Vis techniques, we found that Ni metal doping greatly improved and optimized the crystallinity of the films and adjusted the optical band gap.
Ganzheitliche Wandlungsfähigkeit von Produktionssystemen – der Schlüssel zur Ressourcenwende?
Authors: Bielitz Pia , Jäpel Nicole , Heik David , Reichelt Dirk 
Published: September 2023

ZusammenfassungWandlungsfähigkeit von Unternehmen ist der Schlüssel, um gegenüber Multikrisen wie in den letzten Jahren bestehen zu können und langfristig handlungsfähig zu bleiben. Gleichzeitig fordert die globale Situation aber auch dringend einen Wandel hin zu einem drastisch reduzierten Ressourcenverbrauch. Im vorliegenden Beitrag wird daher untersucht, wie sich die Wandlungsfähigkeit eines Produktionssystems steigern und gleichzeitig der Ressourceneinsatz im Unternehmen senken lässt. Durch die Zusammenführung der vier grundlegenden Ressourcenschonungsstrategien (repair, reuse, recycle und reduce) mit den fünf etablierten Wandlungsbefähigern (Kompatibilität, Mobilität, Modularität, Skalierbarkeit, Universalität) können die Interdependenzen zwischen diesen evaluiert werden. Die Anwendung dieser auf ein sozio-technisches System fördert dabei außerdem einen gesamtheitlichen und stärker menschzentrierten Ansatz. Anhand des entwickelten Use-Cases „flexible Qualitätssicherung zur Ressourcenschonung“ wird darüber hinaus ein konkretes Anwendungsbeispiel zur parallelen Implementierung eines wandlungsfähigen, menschzentrierten und ressourcenschonenden Prozesses im Unternehmensumfeld erläutert. Damit unterstützt der Beitrag die konsequente Auslegung von Produktionssystemen auf Resilienz, Menschzentrierung und Nachhaltigkeit, welche als die drei wesentlichen Schlüsseltreiber der Industrie 5.0 gelten.
Characteristics and outcomes of patients with severe COVID-19 in Indonesia: Lessons from the first wave
Authors: Burhan Erlina , Liu Keibun , Marwali Eva M. , Huth Samuel , Wulung Navy G. H. M. L. , Juzar Dafsah A. , Taufik Muhammad A. , Wijaya Surya O. , Wati Dyah K. , Kusumastuti Neurinda P. , Yuliarto Saptadi , Pratomo Bhirowo Y. , Pradian Erwin , Somasetia Dadang H. , Rusmawatiningtyas Desy , Fatoni Arie Z. , Mandei Jose M. , Lantang Eka Y. , Perdhana Fajar , Semedi Bambang P. , Rayhan Muhammad , Tarigan Tiffany R. S. , White Nicole , Bassi Gianluigi L. , Suen Jacky Y. , Fraser John F. 
Published: September 2023

Background
Indonesia’s national response to COVID-19 evolved rapidly throughout 2020. Understanding pandemic response and outcomes is crucial for better mitigation strategies ahead. This study describes the characteristics and outcomes of patients admitted to ICU during the early stages of the pandemic.

Methods
This is a multi-centre prospective observational study including patients from twelve collaborating hospitals in Indonesia. All patients were clinically suspected or laboratory-confirmed COVID-19 cases admitted to ICU between January 2020 and March 2021. The primary outcome was monthly ICU mortality. Descriptive statistics of patient characteristics and treatment were generated as secondary outcomes.

Results
From 559 subjects, the overall mortality was 68% and decreased over the study period, while the mortality of patients that received mechanical ventilation was 92%, consistently high over the study period. Fatal cases showed 2- and 4-day delays from symptoms onset to hospital admissions and ICU admissions, respectively. Evidence-backed approaches which could influence patient outcome, such as extracorporeal membrane oxygenation, prone positioning, renal replacement therapy, and neuromuscular blockade were scarcely administered.

Conclusions
The mortality rate of COVID-19 patients in Indonesia was extremely high during the first major outbreak of disease, particularly in those mechanically ventilated. Delayed admission and unavailability of evidence-based approaches due to high burden on health facility during COVID-19 crisis could be addressed by efficient public health measures and enhancing health infrastructure to improve the future pandemic response.
Protocolo de convivencia en los centros escolares
Authors: Torre Rodríguez Alejandra , Delgado Abad María , Hurtado Velasco Irene 
Published: September 2023

Ante la propuesta para realizar una presentación final en la asignatura de Prácticas IV sobre lo que sería para nosotras un protocolo de convivencia “ideal” en un centro educativo, escogimos la opción de presentar la información y las dinámicas de una forma práctica y aplicable a todos los colegios, donde se incluyeran no solo a los docentes, sino también a los alumnos y familias, puesto que todos formamos parte de esta comunidad.
A lo largo del artículo iremos detallando nuestra puesta en práctica con la temática del cine, seleccionando actividades y juegos que hemos ido viendo gracias a nuestras prácticas en los colegios y que hemos tenido la oportunidad de llevar a cabo con anterioridad.
Roles of Political Orientation and Social Representations of Social Order on Socio-Representational Construction Towards Universal Basic Income in France
Authors: Dupoirier Samuel , Demarque Christophe , Souville Marc , Forissier Solveig , Lampropoulos Dimitrios 
Published: September 2023

Abstract
As an object which is new, complex and potentially challenging some of the foundations of the Social Order (SO), we sought to study the influence of the Political Orientation (PO) and Social Representations (SR) of the Social Order (Staerklé et al., 2007). Qui a droit à quoi ? Représentations et légitimation de l’ordre social. PUG) on the socio-representational construction of the Universal Basic Income (UBI) and stances towards this measure (attitude and estimated fair amount). Data were collected via Facebook from 264 French general population participants (Mage = 37.8; SD = 12.7; 174 women). Our Structural Equation Model revealed that the PO would be associated with the stances towards the UBI, mediated by the different ways of representing it and the representations of the SO. Results show two differents socio-representational logics in relation to being right-wing and one in relation to being left-wing. This leads to contrasting stances towards the UBI and seems to reflect different desires to maintain or change the SO.
The Transcendental Grounds of Novalis’ Conception of Life as Poetical Work
Authors: Malimpensa Maurizio Maria 
Published: September 2023

Abstract
The aim of the present paper is to show Novalis’ complete belonging to the history of transcendental philosophy by bringing out the connection between his conception of poetry and the issue of transcendental imagination in Kant and Fichte. Given that solving this problem is the main issue around which Novalisian thought is structured, an attempt is made to consider the writing style adopted by the author as necessary to fulfill this task, and not as an arbitrary rhetorical choice. The connection between poetry and philosophy is then explored in the practical role it has to play among human beings, namely, that of revealing the meaning of the whole reality as a manifestation of the absolute. Thus, life itself is properly displayed by the singular existences as absolute creativity, such as that of poetical creations.
Use of waste activated carbon and wood ash mixture as an electrical grounding enhancement material
Authors: Wahba Mahmoud , Abdel-Salam Mazen , Nayel Mohamed , Ziedan Hamdy A. 
Published: September 2023

Abstract
The grounding scheme is one of the main elements for protection system to mitigate the effect of unwanted lightning strikes or operational failures due to faults in generation, transmission and distribution systems. Desert sand soil has a very low electric conductivity, causing weakness in grounding system. To mitigate problems, the soil is supported with a high conductivity agent to adjust the soil conductivity to acceptable levels. A high-cost and non-renewable commercial product can be added to soils to increase their conductivity. This study brings innovation to conventional soil-enhancement materials. A newly developed mixture is proposed, which is composed of waste-activated carbon received from water purification industries and wood ash from agricultural wastes. First, mixture samples with different compositions of available waste materials were prepared. Then, experimental tests were performed and optimized with a combined genetic algorithm (GA) and fuzzy ranking method to estimate the optimal percentage volume value of each material involved in the developed mixture. To validate the effectiveness of the developed mixture, the results were compared with a commercial product available in the market. Also, the obtained results using GA are compared with those obtained by particle swarm optimization (PSO) to appreciate the best GA solutions. The effectiveness of using the developed mixture and the commercial product in reducing the resistance-to-ground of a rod driven in high and low resistivity soils is evaluated. Finally, a sample of the developed mixture was checked to be non-corrosive material for copper grounding rods.
Power quality disturbances classification using autoencoder and radial basis function neural network
Authors: Veeramsetty Venkataramana , Dhanush Aitha , Nagapradyullatha Aluri , Krishna Gundapu Rama , Salkuti Surender Reddy 
Published: September 2023

Abstract
The classification of power quality (PQ) disturbances is a critical task for both utilities and industry. PQ issues cause power system equipment to fail. PQ disruptions also cause significant disruption in the paper and semiconductor industries, with significant financial implications as well as technological difficulties. Deep learning based approaches are used for automatic PQ disturbance classification, which requires huge amounts of data. A PQ disturbance dataset consisting of 12 PQ disturbances is developed using wavelet transform and MATLAB software. In this paper, an autoencoder is used to reduce the dimensionality of power quality disturbances data from higher dimensionality space, which consists of 72 input features, to lower dimensionality space, which consists of 21 input features. Based on data extracted from the autoencoder, a radial basis function neural network is used to identify the type of PQ disturbances. Based on the simulation results, it is observed that radial basis function neural network is able to distinguish the type of PQ disturbance with 92 % accuracy.
Olive Oil World Price Forecasting: A Bayesian VAR Approach
Authors: Messaoudi Haïfa , Abbassi Abdessalem , Khraief Naceur 
Published: September 2023

AbstractThe Tunisian olive oil strategy is based on the development of exports. Extension and modernization measures of Tunisian olivegrove have come into effect these recent years in order to increase the exports and diversify the target markets. Like any other agricultural good, olive oil is subject to world price fluctuations. Forecasting the long-term world price of olive oil is essential both as a decision-making tool and as a strategic factor for the development of the sector. This paper attempts to forecast the long-term olive oil world price using annual time series. The data reveals that the number of observations is too restrictive for a frequentist approach. To overcome the sample shortage, we adopt a Bayesian VAR. We use the hierarchical prior selection to specify the prior parameters. The results show an increase in world price and production. However, the price grows more proportionally than the production. In such a context, the increasing production orientation seems adequate but not sufficient to enhance the Tunisian position on the international olive oil market. For the coming decade, the Tunisian olive oil policy should focus as well on deepening the dynamics of product valorization.
Efficient numerical solution of the Fokker–Planck equation using physics-conforming finite element methods
Authors: Wegener Katharina , Kuzmin Dmitri , Turek Stefan 
Published: September 2023

Abstract
We consider the Fokker–Planck equation (FPE) for the orientation probability density of fiber suspensions. Using the continuous Galerkin method, we express the numerical solution in terms of Lagrange basis functions that are associated with N nodes of a computational mesh for a domain in the 3D physical space and M nodes of a mesh for the surface of a unit sphere representing the configuration space. The NM time-dependent unknowns of our finite element approximations are probabilities corresponding to discrete space locations and orientation angles. The framework of alternating-direction methods enables us to update the numerical solution in parallel by solving N evolution equations on the sphere and M three-dimensional advection equations in each (pseudo-)time step. To ensure positivity preservation as well as the normalization property of the probability density, we perform algebraic flux correction for each equation and synchronize the correction factors corresponding to different orientation angles. The velocity field for the spatial advection step is obtained using a Schur complement method to solve a generalized system of the incompressible Navier–Stokes equations (NSE). Fiber-induced subgrid-scale effects are taken into account using an effective stress tensor that depends on the second- and fourth-order moments of the orientation density function. Numerical studies are performed for individual subproblems and for the coupled FPE-NSE system.
Efficient NOMA system: hybrid heuristic-based network parameter optimization for spectral and energy efficiency with QoS maximization
Authors: Devi R. Prameela , Prabakaran N. 
Published: September 2023

Abstract
Due to its ability to boost the spectral efficiency of wireless communications systems, non-orthogonal multiple access (NOMA) has been deemed promising. NOMA retains the necessary effectiveness to enable 5G communication. The wireless network’s spectral efficiency and energy are reduced due to the limited spectrum and rising demands of users. Because of the mutual cross-tier interference that occurs in heterogeneous networks, NOMA presents brand-new technical difficulties in resource allocation. The use of non-orthogonal resources and spectrum sharing can cause interference that lowers the performance. Therefore, incorporating quality-of-service (QoS) into the design of a new NOMA model with improved bandwidth efficiency and energy efficiency (EE) is absolutely necessary. A deep learning strategy for maximizing the efficiency of spectrum and energy with QoS in NOMA is presented in this paper. In order to increase the efficiency of spectrum and energy with QoS in the NOMA system, an adaptive artificial rabbits Harris Hawks optimization (AARHHO) algorithm is developed to optimize parameters such as the time allocation ratio and beam forming vectors presented in the full-duplex (FD) relay and base station (BS). As a result, the NOMA network efficiency of bandwidth and energy is effectively maximized with QoS using the newly developed AARHHO approach.