bluuebunny/crossref_metadata_2025_split huggingface dataset:
European governments’ electromobility plans: an assessment with a focus on infrastructure targets and vehicle estimates until 2030
Authors: Marotta Alessandro , Lodi Chiara , Julea Andreea , Gómez Vilchez Jonatan J. 
Published: November 2023

AbstractElectromobility offers great potentials to the decarbonisation of the transport sector. The purpose of this study is to analyse the development of electromobility in the European Union (EU) and in the United Kingdom (UK) by 2030. The study is based on the objectives provided by the EU Member States and UK in their national implementation reports, as foreseen by the Directive 2014/94/EU on the deployment of alternative fuels infrastructure. As the initial data coverage was not full, in order to produce a complete data set on registered electric vehicles and public recharging points, we estimated missing values with different statistical techniques and critical analysis of the initial data. A set of proposed indicators, namely the share of electric vehicles, the density of publicly accessible recharging points, the electric vehicles and recharging points annual growth rates and the sufficiency index, were averaged at EU27+UK level to depict the envisaged evolution of electromobility in the present decade. The results show that the objectives of the countries’ governments are overall less ambitious than the goals defined in the EU Green Deal for 2025 and in the Sustainable and Smart Mobility Strategy for 2030. Most of the indicators vary significantly in the 2016–2030 period, often revealing an increased divergence between the development of electric vehicles and public recharging points. Two policy implications are derived: (i) the use of a combined set of indicators to assess the governments’ electromobility plans could be pursued, while the ratio of ten electric vehicles per recharging point may no longer be a useful benchmark; and (ii) measures supporting the uptake of recharging infrastructure are still needed to mitigate the divergence with electric vehicles and to meet the ambitious objectives of the EU Green Deal and Sustainable and Smart Mobility Strategy.
Modelling the “transactive memory system” in multimodal multiparty interactions
Authors: Biancardi Beatrice , Mancini Maurizio , Ravenet Brian , Varni Giovanna 
Published: November 2023

AbstractTransactive memory system (TMS) is a team emergent state representing the knowledge of each member about “who knows what” in a team performing a joint task. We present a study to show how the three TMS dimensions Credibility, Specialisation, Coordination, can be modelled as a linear combination of the nonverbal multimodal features displayed by the team performing the joint task. Results indicate that, to some extent, the three dimensions of TMS can be expressed as a linear combination of nonverbal multimodal features. Moreover, the higher the number of modalities (audio, movement, spatial), the better the modelling. Results could be used in future work to design human-centered computing applications able to automatically estimate TMS from teams’ behavioural patterns, to provide feedback and help teams’ interactions.
Personality-Based Adaptation of Robot Behaviour: Acceptability Results on Individuals with Cognitive Impairments
Authors: Rossi Silvia , Di Napoli Claudia , Garramone Federica , Salvatore Elena , Santangelo Gabriella 
Published: November 2023

AbstractWe performed a study to evaluate if the acceptance of a social humanoid robot used for monitoring the activities of elderly users with cognitive deficits increased after interacting with the robot. In addition, we evaluated if the robot’s acceptance is improved when the interaction with the robot occurred in different modalities modulated according to each user’s cognitive and personality profile. A group of 7 participants underwent assessment tools for cognitive and personality traits and for the level of acceptability of the robot. They interacted with the robot at their private home for a minimum of two weeks. The interaction with the robot occurred under two different modalities: standard modality where the robot performed tasks by approaching the subject at a fixed pre-defined frequency of interactions, and at fixed pre-defined times; modulated modality where the robot performed tasks by approaching the subject at different frequencies set according to some personality traits and cognitive profile of the user. The results showed no change in the acceptability level of the robot after direct interaction. Still, personality traits such as Neuroticism and Openness influenced the acceptability of the robot in the elderly only before an interaction. At the same time, these personality traits did not seem to influence the acceptability of the new technology after a direct interaction. Different is the case of cognitive profiles and demographic characteristics. Finally, the score on the pleasantness scale was higher when the interaction with the robot was set in modulated modality rather than standard modality. In conclusion, the identification of the personality traits and the cognitive status in the elderly with cognitive deficits seems to be useful to modulate the type and frequency of interaction of the robot with the user to increase the acceptability of the instrument and pleasures in every daily life.
Association between psychological need satisfaction and online self-regulated learning
Authors: Hidayatullah Achmad , Csíkos Csaba 
Published: November 2023

AbstractThe role that psychological need satisfaction and self-regulated learning play in academic online learning has been extensively researched. However, the impact of the three psychological needs, perceived autonomy, competence, and relatedness, on online self-regulated learning remains unclear. This investigated the association between the satisfaction of psychological needs and the six dimensions of online self-regulated learning. This cross-sectional study adopted a quantitative approach. In all, 315 students from four higher education institutions participated in the present study. Students were asked to complete the online questionnaire of psychological need satisfaction and an online self-regulated learning questionnaire. Structural equation modeling was performed to examine the structural relationships between the two. Our study showed that perceived autonomy predicted goal setting, environment structuring, time management, and self-evaluation but did not predict help-seeking and task strategies. Perceived competence did not predict environment structuring. Perceived relatedness predicted environment structuring, help-seeking, and self-evaluation. This study appears to be the first to examine the predictions of need satisfaction to increase students’ capability in regulating their learning.
Establishment and functional testing of a novel ex vivo extraskeletal osteosarcoma cell model (USZ20-ESOS1)
Authors: Harnisch Kim , Steiner Sabrina , Pliego-Mendieta Alicia , Chen Yanjiang , Planas-Paz Lara , Pauli Chantal 
Published: November 2023

AbstractExtraskeletal osteosarcoma (ESOS) is a rare malignant mesenchymal tumor that originates in the soft tissue. ESOS accounts for less than 1% of all soft tissue sarcomas and exhibits an aggressive behavior with a high propensity for local recurrence and distant metastasis. Despite advances in treatment, the prognosis for ESOS remains poor, with a five-year survival rate of less than 50% and 27% for metastatic patients. Ex vivo models derived from patient samples are critical tools for studying rare diseases with poor prognoses, such as ESOS, and identifying potential new treatment strategies. In this work, we established a novel ESOS ex vivo sarco-sphere model from a metastatic lesion to the dermis for research and functional testing purposes. The ex vivo cell model accurately recapitulated the native tumor, as evidenced by histomorphology and molecular profiles. Through a functional screening approach, we were able to identify novel individual anti-cancer drug sensitivities for different drugs such as romidepsin, miverbresib and to multiple kinase inhibitors. Overall, our new ESOS ex vivo cell model represents a valuable tool for investigating disease mechanisms and answering basic and translational research questions.
Minimun overlap problem on finite groups
Authors: Martos Carlos A. , Huicochea Mario , Daza David F. , Trujillo Carlos A. 
Published: November 2023

AbstractLet A, B be disjoint sets such that $$A\cup B= [1,2n]\subset {\mathbb {Z}}$$

A
∪
B
=
[
1
,
2
n
]
⊂
Z

and $$\vert A\vert = \vert B\vert = n$$

|
A
|
=
|
B
|
=
n

. Let us call $$m (A, B)=\max _{t \in {\mathbb {Z}}}\vert (t+B)\cap A \vert $$

m

(
A
,
B
)

=

max

t
∈
Z

|

(
t
+
B
)

∩
A
|

and consider $$M(n):=\min \limits _{(A,B)} m(A,B)$$

M

(
n
)

:
=

min

(
A
,
B
)

m

(
A
,
B
)

(over all partitions with $$A \cup B=\left[ 1,2n\right] $$

A
∪
B
=

1
,
2
n

). There are well-known upper and lower bounds of M(n). In this paper we studied a variation of this problem, i.e. we considered a finite abelian group G with $$\vert G \vert =k$$

|
G
|
=
k

, we define M(G) which is analogous to M(n) and we obtained upper and lower bounds for M(G).
Impact of uncertainty on inflation forecast errors in Central and Eastern European countries
Authors: Kliber Agata , Szyszko Magdalena , Próchniak Mariusz , Rutkowska Aleksandra 
Published: November 2023

AbstractThe question underlying the research problem addressed by this study concerns various factors, including uncertainty, that could affect forecast errors. Previous works, focusing mainly on world-leading economies, are inconclusive on how economic agents form inflation forecasts or why forecast errors occur. There is a gap in the empirical literature that needs to be filled. The analysis covers the 2016–2020 period and seven economies: Albania, Czechia, Hungary, Poland, Romania, Serbia, and Turkey. We verify whether forecast errors are driven by production, inflation, exchange rates, interest rates, oil prices, changes in the tone of the central bank’s releases and their uncertainty. We assess whether economic agents can process available information to present accurate inflation forecasts. The results suggest that neither consumers nor professionals do—they present inaccurate forecasts regularly. The results suggest that exchange rate volatility is the most important variable that positively affects forecast errors, followed by inflation and its volatility. This confirms (in most cases) a theoretical assumption that a stable environment is better for long-term development as lower inflation forecast errors allow for the optimization of economic decisions. The study implies that mechanisms supporting forecasting during turbulent times must be strengthened. It presents the set of variables that should be analyzed more carefully by consumers and professionals. In addition, central banks could provide more precise communication regarding the evolution of error drivers. Our results build on existing literature by explicitly linking macroeconomic uncertainty with forecast errors including for small open economies from Eurasia.
Approximation Properties of Extended Beta-Type Szász–Mirakjan Operators
Authors: Rao Nadeem , Raiz Mohd , Ayman-Mursaleen Mohammad , Mishra Vishnu Narayan 
Published: November 2023

AbstractIn this article, we introduce generalized beta extension of Sz$$\acute{a}$$a´sz-integral type operators and study their approximation properties. First, we calculate the some estimates for these operators. Further, we study the uniform convergence and order of approximation in terms of Korovkin-type theorem and modulus of continuity for the space of univariate continuous functions and bivariate continuous functions in their sections.. Moreover, numerical estimates and graphical representations for convergence of one- and two-dimensional sequences of operators are studied. In continuation, local and global approximation properties are studied in terms of the first- and second-order modulus of smoothness, Peetre’s K-functional and weight functions in various functional spaces.
Self-help: a Systematic Review of the Efficacy of Mental Health Apps for Low- and Middle-Income Communities
Authors: Gama B. , Laher S. 
Published: November 2023

AbstractLow- and middle-income countries (LMICs) are tasked with providing adequate and accessible mental health care. However, this has been a slow process due to the lack of resources. With the recent advances in technology, mental health apps offer the opportunity to provide mental health care that is accessible and affordable. This study explored the efficacy of mental health apps in LMICs using the AAAQ framework. A systematic review following PRISMA guidelines explored studies published from 2015 to 2021. Seven studies met the inclusion criteria and were analysed using content analysis and thematic synthesis. Themes centred around the availability of mental health care systems in LMICs, some of the barriers to accessing mental health care, the need for mental health apps to be congruent with the communities that they are used in and quality criteria for apps. The study offers valuable insight towards mediating some of the struggles faced in the implementation of appropriate mental health care in LMICs using mental health apps.
Soil improvement to enhance resistance parameters using bacterial precipitation and nanosilica
Authors: Sangdeh Moein Khoshdel , Negahdar Alireza , Tabandeh Fatemeh 
Published: November 2023

AbstractSoil has an important role in the structure of every building. Although there are different methods available to improve the mechanical properties of soil (adhesion, friction, and rigidity), some, such as chemical methods, despite their limited advantages, will harm the environment. The present study examined the use of microbiologically induced calcite precipitation, which is good for the environment and is a stable improvement method. An experimental study was conducted to study the influence of different factors on the resistance parameters of improved sandy soil. These parameters were the concentration of reactive materials (0.25, 0.5, 0.75 M), curing time (3, 7, 14 days), and compatibility of the bacteria with the nanoparticle. The results showed that the shear strength parameters improved and the soil adhesion rate increased from 0.1 to 186. The soil friction angle reached 35.6°, indicating a 12% increase compared to that of unimproved sand.
Analysis of torque controlling strategies of interior permanent magnet synchronous machine in hybrid electric vehicle
Authors: Usha S. , Geetha P. , Palanisamy R. , Kitmo  , Jember Yosef Berhan 
Published: November 2023

AbstractSignificance of this research is based on torque controlling strategies in hybrid electric vehicle. The traction motor of a hybrid electric commercial vehicle must have a high power density-to-weight ratio and excellent torque at extremely low speeds. A proportional-integral controller estimates the high-resolution rotor position based on the difference between actual as well as reference output power. This technique can correct for hall position sensor installation error and also accurately estimate rotor position. In this study, a current proportional integral controller is also used to determine the permanent magnetic flux linkage. Experiments are used to test other key metrics such as d-axis and q-axis inductances, stator resistance, and energy loss. The measured parameters are kept in lookup tables that span the whole operating range at various current levels. A maximum torque per ampere control methodology, paired with the feed forward parameter iteration method, may be used to produce accurate and efficient torque control based on these precise parameters. The standard driving cycle performance requirements of the modelled Federal Test Procedure vehicle is analysed in the article for understanding the real model requirements of the vehicle. The efficacy of the proposed methodology using Matlab/Simulink environment is analysed. Both modelling and experimental findings validate the efficacy, torque ripple, stator and rotor flux, sensitivity of the vehicle parameter as well as the computational complexity of the proposed methodology.
Analysis of Collision Avoidance Manoeuvres Using Aerodynamic Drag for the Flying Laptop Satellite
Authors: Turco Fabrizio , Traub Constantin , Gaißer Steffen , Burgdorf Jonas , Klinkner Sabine , Fasoulas Stefanos 
Published: November 2023

AbstractCollision avoidance is a topic of growing importance for any satellite orbiting Earth. Especially those satellites without thrusting capabilities face the problem of not being able to perform impulsive collision avoidance manoeuvres. For satellites in low Earth orbits, though, perturbing accelerations due to aerodynamic drag may be used to influence their trajectories, thus offering a possibility to avoid collisions without consuming propellant. Here, this manoeuvring option is investigated for the satellite Flying Laptop of the University of Stuttgart, which orbits the Earth at approximately $${600}\,{\textrm{km}}$$

600

km

. In a first step, the satellite is aerodynamically analysed making use of the tool ADBSat. By employing an analytic equation from the literature, in-track separation distances can then be derived following a variation of the ballistic coefficient through a change in attitude. A further examination of the achievable separation distances proves the feasibility of aerodynamic collision avoidance manoeuvres for the Flying Laptop for moderate and high solar and geomagnetic activity. The predicted separation distances are further compared to flight data, where the principle effect of the manoeuvre on the satellite trajectory becomes visible. The results suggest an applicability of collision avoidance manoeuvres for all satellites in comparable and especially in lower orbits than the Flying Laptop, which are able to vary their ballistic coefficient.
2D/2D composites based on graphitic carbon nitride and MXenes for photocatalytic reactions: a critical review
Authors: Praus Petr 
Published: November 2023

AbstractThe combination of the two-dimensional (2D) materials g-C3N4 and MXenes in photocatalysis offers several advantages. The g-C3N4 can serve as a visible light-absorbing material, while MXenes can enhance the charge separation and transfer processes leading to improved photocatalytic efficiency. A critical review of 77 already published articles in the field of photocatalytic reactions using g-C3N4 and MXenes, such as hydrogen evolution, the reduction of carbon dioxide, the degradation of organic compounds, the redox reactions of nitrogen, was conducted. For the purpose of greater objectivity, the published results were analysed by non-parametric Mann–Whitney, Kolmogorov–Smirnov, and Mood´s median tests and visualised by box and whisker plots. It was found that MXenes can significantly improve the photocatalytic activity of g-C3N4. Adding other co-catalysts to the MXene/g-C3N4 composites does not bring a significant improvement in the photocatalytic performance. Promising results were obtained especially in the fields of hydrogen evolution and the reduction of carbon dioxide. Since the MXenes are relatively a new class of materials, there is still a big challenge for finding new photocatalytic applications and for the enhancement of existing photocatalytic systems based on g-C3N4, especially in terms of the MXenes and g-C3N4 surface and in the heterojunction engineering.
RETRACTED ARTICLE: Determination of Power Transformer Fault’s Severity Based on Fuzzy Logic Model with GR, Level and DGA Interpretation
Authors: Gopakumar S. , Sree Renga Raja T. 
Published: November 2023

AbstractTransformer defects are defined by their severity which is the intrinsic property of the transformer. Several approaches for identifying the severity of Power Transformer (PT) problems have previously been proposed; however, most published research does not incorporate Gas Level (GL), Gas Rate (GR), and DGA interpretation into a unified strategy. A novel technique in the form of fuzzy logic (FL) has been offered as a new way to assess faults’ severity by utilizing the combination of GL, GR, and DGA interpretation from the Duval Pentagon Method (DPM) to increase the reliability of the faults’ severity evaluation of PT. Based on the local population, a four-level typical concentration and rate were created. A Deep Learning (DL) oriented Convolutional Neural Network (CNN) based DPM and Harris Hawks Optimization (HHO) method with a high agreement to that same graphical DPM has also been devised to enable the evaluation of hundreds of PT information easy. The proposed method was applied to 448 PTs, and it was then used to assess the severity of problems in PTs using historical DGA data. Due to the integration of GL, GR, and DGA interpretation results in one technique, this novel strategy yields good agreement with earlier methods, but with better sensitivity.
Crisis management experience in Hungary
Authors: Gellen Marton 
Published: November 2023

AbstractThe experience of managing the COVID-19 and the migration crises in Hungary has been highly criticized in academic literature. The article delves deeper into the matter by scrutinizing the dual challenge of managing the given crises while facing disciplinary measures from the EU. The study uses the system approach to explain and predict the interactions between the affected nation states and the EU institutions in times of turbulent crises. The article’s affirmations are inspired by the system approach and are substantiated by comparative findings of empirical studies. The article finds that disciplinary interventions are likely to increase autopoietic tendencies in the targeted member states. Disciplinary measures apparently add to the member states’ challenges inevitably increasing self-reliance and autonomous decision-making.
Microphysics of Heavy Rain Associated With the Eyewall and Inner Rainbands of Typhoon Meranti (2016)
Authors: Wang Lan , Bao Xuwei , Hu Yajun , Zhang Shuai , Lin Wen , Zhuang Yao 
Published: November 2023

AbstractHeavy rain in a tropical cyclone (TC) tends to occur in its eyewall and inner spiral rainbands. The distinct dynamical and thermodynamical structures between TC eyewall and inner rainbands were argued to be responsible for different rain microphysics by previous studies. Thus, this study investigated the microphysical characteristics of heavy rain (≥10 mm hr−1) associated with the eyewall and inner rainbands of Typhoon Meranti (2016), based on the joint observations of two disdrometers and a dual‐polarization radar (DPR) as well as automatic weather stations in Fujian province of China. The surface disdrometer observation showed that the eyewall rain has a larger mean raindrop diameter and a smaller mean concentration than the inner‐rainband rain. In general agreement with the disdrometer observation, the DPR observation confirmed larger sizes of raindrops near the ground in the eyewall. However, the vertical profiles of polarimetric variables showed larger values almost throughout the atmosphere in the eyewall, namely that more efficient ice‐ and warm‐cloud processes are evident for the production of ice and rain particles. This result looks contradictory to the lower concentration of the eyewall rain than the inner‐rainband rain as measured by surface disdrometers. This is because stronger updrafts observed in the eyewall not only facilitate the production and growth of hydrometeors, but also prevent small raindrops from falling to the ground. Consequently, the surface rain in the eyewall has larger raindrop diameter and lower concentration than that in the inner rainbands, despite a larger number of ice and rain particles in the atmosphere.