bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effective Convergence Trading of Sparse, Mean Reverting Portfolios
Authors: Rácz Attila , Fogarasi Norbert 
Published: November 2024

AbstractThis paper introduces an effective convergence trading algorithm for mean reverting portfolios using Long Short Term Memory (LSTM) neural networks. Utilizing known techniques for selection of sparse, mean reverting portfolios from asset dynamics following the VAR(1) model, we introduce a 2-step technique to effectively trade the optimal portfolio. Sequence-to-sequence (Seq2Seq) LSTM architecture is implemented to make longer term prediction of future portfolio values and establish a trading range. In addition, a simple LSTM network is applied to predict very precisely one time step ahead. Combining these two constructions, a sophisticated convergence trading algorithm is implemented which produced Sharpe ratios around 1.0 on optimal portfolios selected from historical $$ S[NONSPACE] \& P500$$

S
[
N
O
N
S
P
A
C
E
]
&
P
500

stocks during $$2015-2022$$

2015
-
2022

. This represents a very significant improvement compared to the previous convergence trading algorithms on the same set of portfolios by around $$141\%$$

141
%

on average.
Measuring transformation concerning climate change and extreme events at the regional level: actor needs and spatial assessment in the Cologne district, Germany
Authors: Fekete Alexander , Frick Claudia , Beckers Daniel , Hetkämper Chris , Holtmann Friederike , Laux Julia , Nehren Udo , Ribbe Lars , Becker Klaus 
Published: November 2024

AbstractThe article focuses explicitly on transformation and analyzes how it can be measured both quantitatively and qualitatively in a case study region in western Germany. It addresses blue, critical, and green infrastructures in a region that was affected by the 2021 floods in Europe. Together with regional actors, co-creative solutions for developing adaptation strategies and infrastructure planning will be developed. Using and combining different conceptual models and applying them to the project region as well as to human infrastructure highlights the different types of change and transformation. This also shows the complexity of such an overall assessment, which needs to include a lot of diverse actors and disciplines. The project's first results are overviews of national and cross-regional changes to infrastructures and administrative structures after the 2021 floods in Germany and at the district level. The interim results reveal that more needs and plans exist than real, measurable transformations and that certain transformations stem from planning long before the floods in 2021. Maps and land use potentials are presented that provide overviews of regional differences in flood, drought, and wildfire exposure and capacities for nature-based solutions. Both the conceptual models developed in this study as well as the application examples could be useful for other researchers and administrative bodies to measure transformation to climate change and other stimuli.
A Composite Microwave Cavity for Liquid Volume Fraction and Simultaneous Phase Permittivity Measurements
Authors: Tenardi Liam D. , Hopkins Matthew G. , Richter Markus , May Eric F. , Stanwix Paul L. 
Published: November 2024

AbstractMicrowave resonators are a technology with the potential to automate the rapid acquisition of vapour-liquid equilibrium data in multicomponent mixtures. However, the re-entrant resonators commonly used for fluid characterization have limited ability to mix or drain adequately due to the bulbs and narrow gaps used within the sample volume to spatially distribute the sensing regions with intense electric fields. This work describes a novel composite cavity combining two toroidal split-ring resonators and a cylindrical resonator, each sealed and partially filled with the polymer PEEK, to spatially separate sensing regions whilst maintaining an unobstructed sample volume. This unique design also allows for the total sample volume to be an order-of-magnitude smaller than conventional microwave cavities, without significantly increasing the resonant frequencies. Mass transfer between phases is facilitated by mechanical agitation, reducing equilibration time. Finite element analysis (FEA) is used to model how the dielectric interfaces within the cavity perturb electric field distributions. This model is used to interpret measurements of two-phase propane to quantify liquid volume fraction and phase dielectric permittivities.
Review on machine learning application in tissue engineering: What has been done so far? Application areas, challenges, and perspectives
Authors: Jeznach Oliwia , Tabakoglu Sahranur , Zaszczyńska Angelika , Sajkiewicz Paweł 
Published: November 2024

AbstractArtificial intelligence and machine learning (ML) approaches have recently been getting much of researchers’ attention. The growing interest in these methods results from the fast development of machine learning algorithms in the last few years, especially artificial neural networks. In this review, we pay attention to the need and benefits that ML approaches can bring to tissue engineering (TE). We critically evaluate the possibilities of using the ML approaches in the tissue engineering field. We consider various paths of its utility in the TE, such as scaffold design, predicting the biological response to the scaffold, optimizing drug delivery approaches, supporting image analysis, and modeling scaffold in vivo performance. The current status of ML implementation is presented and supported by many study examples. On the other hand, we analyze the present difficulties and challenges in implementing ML approaches to tissue engineering, including the quality of published data, databases and repositories availability, the need for experiment and results publishing standardization, and ethical issues. Additionally, we assess the available natural language processing tools that could support TE research.
Graphical abstract
Physicochemical and spatial distribution patterns of radon and its parent radionuclides in the uranium-mineralized Singhbhum Region, India
Authors: Molla Samim , Kumar Ranjit , Singhal P. , Srivastava V. S. , Jha S. K. 
Published: November 2024

AbstractThis study examined the distributions of radon and its parent radionuclides 226Ra and 238U in groundwater samples from the Singhbhum region, Jharkhand, India. Radon showed a heterogeneous spatial distribution pattern, with a lognormal distribution. A good correlation between radon bubbler-Lucas cells and liquid scintillation counting techniques was observed for radon monitoring. 222Rn and 226Ra were negatively correlated with pH, suggesting the mobilization of radionuclides at low pH. Uranium was positively correlated with common ions (e.g., Ca, Mg, and SO42−). The activity ratios among the radionuclides indicated disequilibrium, with 222Rn origin controlled by parent radionuclide activity in bedrock. The 226Ra and 238U concentrations in groundwater were lower than the limits recommended by the WHO.
Phase transitions in medium-Mn alloy: thermodynamic simulation and experimental verification
Authors: Skowronek Adam , Kozłowska Aleksandra 
Published: November 2024

AbstractThe present work explores a design process of new medium-Mn alloy for forgings and its heat treatment optimization by thermodynamic simulations and experimental approach. The selection of specific chemical composition was performed on the basis of thermodynamic simulation for alloys with different additions of Mn and Al. The aim was to design an alloy allowing for production of at least 25% retained austenite in an intercritical annealing process, without deteriorating technological properties and economic indicators. Next simulations of intercritical annealing in a temperature range between 600 and 1000 °C, and their experimental verification were performed. For the thermodynamical simulations of different chemical compositions of steel and its intercritical annealing in a wide temperature range the JMatPro software was used. To verify the characteristic temperatures of steel such as Ac1, Ac3 and Ms, and for experimental investigation of intercritical annealing in a temperature range from 660 to 740 °C dilatometry was used. Obtained microstructures were characterized by means of X-ray diffraction and scanning electron microscopy. It was observed that with an initial increase in soaking temperature a fraction of retained austenite increases; however, its stability decreases, which leads to formation of large martensite fraction during cooling after soaking at high temperatures. The results of thermodynamic simulations and experimental tests showed the moderate agreement. Large differences were revealed for Ac1, Ms temperatures and the amount of retained austenite obtained at a given annealing temperature. The results clearly indicate that at the moment of software development and available databases for novel medium-Mn steels, simulations of their heat treatment can only be used to estimate results and be a guide for experimental research. However, they cannot be used to optimize heat treatment.
A systematic review on WebRTC for potential applications and challenges beyond audio video streaming
Authors: Mahmoud Haitham , Abozariba Raouf 
Published: November 2024

Abstract
Video conferencing and live streaming are being used in various industries, such as healthcare, gaming, telecommunication, manufacturing and others. As technology progresses, the need for real-time data transmission with minimal latency has increased. Web Real-Time Communication () addresses this need effectively. WebRTC is a technology designed to provide real-time communication through web and mobile browsers. Its low latency and P2P communication capabilities make it a convenient technology for secure, efficient communication in real-time applications. This paper reviews the key features of WebRTC, discusses its strengths and weaknesses and investigates a detailed analysis of 83 existing studies. Moreover, It evaluates all use cases that can be adopted by WebRTC by examining their descriptions, problem statements, and research gaps based on literature to date. Finally, It highlights the open research directions for the emerging technologies and enhancements of WebRTC. to identify their potential applications.
Patient-derived glioma organoids real time identification of IDH mutation, 1p/19q-codeletion and CDKN2A/B homozygous deletion with differential ion mobility spectrometry
Authors: Hermelo Ismaïl , Haapala Ilkka , Mäkelä Meri , Jacome Sanz Dafne , Kontunen Anton , Karjalainen Markus , Müller Philipp , Lehtimäki Kai , Nykter Matti , Frösén Juhana , Haapasalo Hannu , Roine Antti , Oksala Niku , Nordfors Kristiina , Vehkaoja Antti , Haapasalo Joonas 
Published: November 2024

Abstract

Purpose
Extent of brain tumor resection continues to be one of the central decisions taken during standard of care in glioma patients. Here, we aimed to evaluate the most essential molecular factors, such as IDH (isocitrate dehydrogenase) mutation in gliomas classification with patient-derived glioma organoids (PGOs) using differential mobility spectrometry (DMS).

Methods
we prospectively recruited 12 glioma patients, 6 IDH-mutated and 6 IDH wild-type tumors, from which PGOs were generated ex-vivo. Altogether, 320 PGOs DMS spectra were analyzed with a classifier algorithm based on linear discriminant analysis (LDA).

Results
LDA model classification accuracy (CA) obtained between IDH-mutant and IDH wild-type PGOs was 90% (91% sensitivity and 89% specificity). Furthermore, 1p/19q codeletion classification within IDH mutant PGOs reached 98% CA (93% sensitivity and 99% specificity), while CDKN2A/B homozygous loss status had 86% CA (63% sensitivity 93% specificity).

Conclusion
DMS suitability to differentiate IDH-mutated PGOs was thus validated in ex vivo cultured samples, PGOs. Preliminary results regarding 1p/19q codeleted PGOs and CDKN2A/B loss PGOs identification endorse testing in a prospective intraoperative glioma patient cohort. Our results reveal a sample classification set-up that is compatible with real-time intraoperative surgery guidance.
Uncertainty quantification in real-time parameter updating for digital twins using Bayesian inverse mapping models
Authors: Kessels Bas M. , Fey Rob H. B. , van de Wouw Nathan 
Published: November 2024

AbstractTo achieve its full predictive potential, a digital twin must consistently and accurately reflect its physical counterpart throughout its operational lifetime.To this end, the inverse mapping parameter updating method enables physically interpretable parameter values to be updated, in real-time, for a wide range of (nonlinear) dynamical models using features extracted from measured response data. This paper proposes to extend this method by employing a probabilistic Bayesian neural network, which is trained offline using simulated data, to infer, again in real-time, probability distributions for the updating parameter values instead of (traditionally obtained) point estimates. As a result, the user obtains a quantification of the (un)certainty, providing insight into the degree of trust to be placed in the updated parameter values, which supports the decision-making process for which the digital twin is used. Additionally, it is proposed to include so-called ‘input parameters’ (that characterize the specific settings on the physical setup) as inputs to the neural network to allow for a broader applicability of the updating method. To validate the proposed methodology, it is applied, using both simulated and real-world measurements, to a medical mechanical ventilation system, in which information about uncertainty in the inferred parameter values is important. Parameter values of this system and their uncertainties are shown to be inferred with sufficient accuracy.
Structural nonlinear boundary condition identification using a hybrid physics data-driven approach
Authors: Luo Lanxin , Sun Limin , Li Yixian , Xia Yong 
Published: November 2024

AbstractAs civil infrastructures often exhibit nonlinearities, the identification of nonlinear behaviors is crucial to assess the structural safety state. However, existing physics-driven methods can only estimate the nonlinear parameters given a known nonlinear behavior pattern. By contrast, the data-driven methods can merely map the load-response relationship at the structural level, rather than identify an accurate nonlinear mapping relationship at the component level. To address these issues, a hybrid physics-data-driven strategy is developed in this study to identify the blind nonlinearity. The nonlinear structural components are surrogated by a data-driven multilayer perceptron, and the linear ones are simulated by using the finite element method. Subsequently, the global stiffness matrix and restoring force vector are assembled according to the elemental topology relationship to obtain the hybrid model. The discrepancy between the measured and hybrid model-predicted responses is formulated as the loss function, by minimizing which of the MLPs are indirectly trained and the nonlinearities can be identified without knowing the nonlinearity type. Three numerical cases are used to verify the proposed method in identifying the elastic, hysteretic, and multiple nonlinear boundary conditions. Results show that the proposed method is robust given different noise levels, sensor placements, and nonlinear types. Moreover, the trained hybrid model possesses a strong generalization ability to accurately predict full-field structural responses.
A qualitative systematic review of the impact of hearing on quality of life
Authors: Henderson Nadine , Hodgson Sian , Mulhern Brendan , Page Katie , Sampson Chris 
Published: November 2024

Abstract
Purpose
Hearing loss, deafness, and other hearing-related conditions can significantly impact quality of life; numerous qualitative studies have sought to describe these impacts. Synthesis of these findings may provide additional or more robust insights.

Methods
A qualitative systematic review of studies reporting qualitative data relating to the impact of hearing problems on adults’ health-related quality of life. A subset of studies was included in the review and subsequently analysed using a thematic approach.

Results
The literature search yielded 129 studies, of which 22 met our inclusion criteria and were included for analysis. The included studies, primarily from Australia, the UK, and the USA, involved approximately 450 participants with various hearing conditions. Semi-structured interviews and focus groups were the most common data collection methods, with thematic analysis being the predominant analytical approach. Three overarching categories of descriptive themes were identified: Physical, Mental, and Social. Physical encompassed sound localization, sound clarity, speech, and physical fatigue. Social included relationships, isolation, communication, independence, work function, social stigma, and confidence. Mental encompassed depression, anxiety, listening effort, mental fatigue, fear, and identity. The identified themes shed light on the diverse domains of health-related quality of life affected by hearing conditions.

Conclusion
Differences in hearing function impact upon people’s health-related quality of life in a variety of ways relating to physical, mental, and social aspects of health, and these themes are clearly demonstrated across qualitative studies. These results will inform the development of hearing-specific questionnaire items for with the EQ-5D descriptive system, a commonly used patient-reported outcome measure.
Effect of an Instructional Program for Word Processing and efficient typing on ‘Year 4 students’ composition
Authors: Gahshan Nagham , Weintraub Naomi 
Published: November 2024

AbstractElementary-school students are increasingly required to compose texts on computers. Composing involves both higher-level (planning, translating and revising) and lower-level (i.e., transcription) skills. It is assumed that automatic lower-level skills enable students to focus their attention on the higher composition demands. However, while composing instruction is part of the language arts curriculum, computer literacy instruction (e.g., typing and word processing [WP]) receives less attention. This disparity may affect composition performance, but the evidence for this premise is limited. To address this gap, the Word Processing and Typing Instructional Program (WoTIP) was developed which is grounded in motor learning, ergonomics, and self-regulated learning principles, and incorporated within a language arts curriculum via a collaborative consultation model. The study examined: (a) if the WoTIP will improve students’ typing speed, WP, and composition performance compared to a ‘no touch-typing or WP instruction’ control group; and (b) if improvement in typing and WP will be associated with enhanced composition performance. This study included Grade 4 students (N = 51). Findings showed that the WoTIP group (n = 27) significantly improved their typing and WP performance, as well as their composition quantity and quality, compared to the control group (n = 24). Additionally, a low significant correlation was observed between WP and composition quantity and between typing, WP and composition quality. Hence, it appears that the WoTIP may be an effective program for enhancing both transcription and composing abilities of Grade 4 students.
Profiles of phonological deficits and comorbidity in Chinese developmental dyslexia
Authors: Ding Ning , Peng Peng , Li Sen , Tang Jiuqing , Zhao Jingjing 
Published: November 2024

AbstractIt has been widely accepted that phonological awareness (PA), rapid automatized naming (RAN), and verbal short-term memory (VSTM) deficits are three core facets of phonological deficits in developmental dyslexia (DD) of alphabetic orthographies. Yet, whether these three phonological facets also represent key phonological deficits of DD in Chinese, a logographic language, has never been investigated. The current study aimed to examine profiles of phonological deficits and comorbidity in Chinese DD. We tested 128 children with DD aged between 8 and 11 years and 135 age-matched controls on 9 tasks, including 2 PA tasks (phoneme deletion and onset/rime deletion), 3 RAN tasks (digit, object and color), 2 VSTM task (spoonerisms and digit span), an orthographic awareness task (orthographic judgment), and a morphological awareness task (morphological production). With the control of morphological and orthographic awareness, results from latent profile analysis revealed three latent profiles, namely the RAN deficit group, the severe PA deficit group, and the mild VSTM deficit group. Individual analysis using a Venn plot showed that 83.59% of DD exhibited phonological deficits, among whom 58.59% with RAN deficit, 49.22% with PA deficit, and 47.66% with VSTM deficit, and all three groups shared overlap. The results have important implications for the identification and remediation of Chinese DD.
Incidence of Factors in Teaching Actions to Manage Antisocial Cyberbehaviour
Authors: Guillén-Gámez Francisco David , Colomo-Magaña Ernesto , Doddanavar Indrajit , Ortiz-Padilla Myriam 
Published: November 2024

Abstract
With the proliferation of information and communication technologies (ICT), antisocial cyber-behavior has emerged, where teachers have a crucial role in the prevention and management of this behavior, focusing on developing actions that promote emotional and civic competences in students, where the skills and beliefs of the teacher are also a key piece. The purpose of this study was to develop an instrument to analyze the impact of these factors on teachers' actions to manage students' antisocial cyber-behaviors. A higher-order causal model was proposed following the partial least squares (PLS) method. The study was conducted with a sample of 835 active teachers from different educational stages from Spain, who taught in the following educational stages: Early Childhood Education, Primary Education, Secondary Education, Adult Education and Vocational Training. The main finding indicates that teachers' beliefs, coupled with their conflict resolution skills and approaches to fostering civic competencies, significantly influence (accounting for 50.30% of the real variance) their actions in managing cyber social behaviors. The study further reveals a connection between teachers' actions to enhance emotional and citizenship skills in students and their proficiency in conflict resolution. Consequently, the study underscores the importance of teachers possessing effective conflict resolution skills. These findings hold practical implications for education, as the developed causal model provides a deeper understanding of the factors influencing teachers' actions, facilitating targeted interventions in specific areas.