bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cracking Chicken-Egg Conundrums: Juxtaposing Contemporaneous and Lagged Reciprocal Effects Models of Academic Self-Concept and Achievement’s Directional Ordering
Authors: Marsh Herbert W. , Guo Jiesi , Pekrun Reinhard , Lüdtke Oliver , Núñez-Regueiro Fernando 
Published: May 2024

AbstractMulti-wave-cross-lagged-panel models (CLPMs) of directional ordering are a focus of much controversy in educational psychology and more generally. Extending traditional analyses, methodologists have recently argued for including random intercepts and lag2 effects between non-adjacent waves and giving more attention to controlling covariates. However, the related issues of appropriate time intervals between waves (lag1 intervals across waves) and the possibility of contemporaneous (lag0) effects within each wave are largely unresolved. Although philosophers, theologians, and scientists widely debate sequential (lagged) and simultaneous (lag0) theories of causality, CLPM researchers have mostly ignored contemporaneous effects, arguing causes must precede effects. In a substantive-methodological synergy, we integrated these issues and designed new structural equation models to reanalyze one of the strongest CLPM studies of academic self-concept (ASC) and achievement (five annuals of mathematics data; 3527 secondary school students). A taxonomy of models incorporating various combinations of lag0, lag1, and lag2 effects, random intercepts, and covariates consistently supported a priori reciprocal effect model (REM) predictions—medium or large reciprocal effects of ASC and achievement on each other. Consistent with self-concept theory, effects of ASC on achievement evolved over time (lag1, not lag0 effects), whereas effects of achievement on ASC effects were more contemporaneous (lag0, not lag1 effects). We argue that lag0 effects reflect proximal events occurring subsequent to the previous data wave, suggesting the need for shorter intervals but also leaving open the possibility of contemporaneous effects that are truly instantaneous. We discuss limitations and future directions but also note the broad applicability of our statistical models.
Language Affects Climate
Authors: Pałasz Michał , Pieniążek Maria , Wydra Jakub 
Published: May 2024

AbstractLanguage not only reflects and cocreates social universes but can also be and is performative regarding the planetary common good, e.g., through international treaties and agreements. This paper investigates the rationale and feasibility of altering the language used by Glasgow Climate Pact to a posthuman mode that addresses the issue of more-than-human inequality by becoming inclusive toward nonhuman actors, and presents a selection of edited excerpts. The main findings state that (1) the language of the Glasgow Climate Pact is inadequate concerning its expected agency, (2) the reasons for this include its anthropocentrism, capitalocentrism and technocentrism, and (3) it is possible to rephrase the Glasgow Climate Pact and similar documents to address the diagnosed problems in a radically inclusive way. This paper represents a starting point for a discussion on the interrelations between climate and language and on the importance of language used by policy documents in the optics of climate action.
Genetic assessment of diverse rice germplasm for yield-related and stress tolerance traits
Authors: Shanmugam Sudha , Samonte Stanley Omar P. B. , Sanchez Darlene L. , Yabes Jonalyn C. 
Published: May 2024

Abstract
The development of stress-resistant crops without compromising their yield and nutritional quality is one of the major challenges in plant biology. Plant breeders have made considerable effort in developing cultivars with high yield and tolerance to biotic and abiotic stresses. This research aimed to evaluate pre-breeding resources for favorable genes conferring good yield and resistance to biotic and abiotic stresses for rice varietal improvement. Two hundred forty diverse rice cultivars from top countries with which the United States imports and exports rice were selected from the Germplasm Resource Information Network (GRIN) collection, and these were characterized using molecular markers for various desirable traits. Among the cultivars, 16 were used as checks. The genes of various traits evaluated were grain number (Gn1a), panicle weight (WFP), cold stress tolerance (qSCT-11 and qCTS-12), anaerobic germination (AG1 and AG2), rice blast disease resistance (PiB, Pi-ta, Ptr, and Piz), wide compatibility (S5-n), and restoring ability (Rf4). Out of these 240 accessions, 192 have the Gn1a gene, 168 possess the qSCT-11 cold tolerance gene, 139 carry the Rf4 gene, 152 have the qCTS12 cold tolerance gene, 87 have blast resistance genes, and 44 possess the WC gene. None of the 240 accessions possess the WFP (Wealthy Farmer’s Panicle) gene. The selections with favorable genes can be used by breeders as potential donor parents for varietal improvement programs to produce new and promising cultivars with desired specific traits that may contribute towards alleviating global issues related to food security.
Legal Dilemmas of Drone Development in Poland
Authors: Jasiuk Ewa , Chochowska Anna , Chochowski Krzysztof 
Published: May 2024

AbstractThis paper aims to discuss in detail the legal aspects of drone use in Poland and demonstrate the need to establish a legal act (Drone Code) that would comprehensively regulate the principles of safe drone use, whether aerial, land or sea, as well as to show the importance of creating a public administration body competent for drone-related issues, or perhaps even an entirely new international organization to safeguard the legal and ethical use of drones.
On the Performance of the Model-Free Adaptive Control For A Novel Moving-Mass Controlled Flying Robot
Authors: Heydari Mohsen , Darvishpoor Shahin , Novinzadeh Alireza Basohbat , Roshanian Jafar 
Published: May 2024

AbstractIn this paper, the performance of Model-Free Adaptive Control (MFAC) has been investigated on a novel and specific moving-mass controlled (MMC) flying robot system. The novel one-degree-of-freedom (1 DOF) MMC flying robot test bed presented in this paper has highly nonlinear and slow dynamics with a variable center of gravity (CoG) and moment of inertia. This makes the control of this system a challenging problem. One of the solutions to this challenge is the use of data-driven control methods, in particular, MFAC. This controller uses a data-driven model to control the system using only input and output (I/O) data. This paper compares this data-driven controller with proportional-integral-derivative (PID) control, and Linear Quadratic Regulator (LQR) as two model-free and model-based controllers which are widely used controllers in industry. The results of the comparison show that in the various scenarios applied, MFAC has a clear superiority over the PID and LQR, and its adaptive structure gives more freedom of action in the implementation of different scenarios and the presented noise. The results are obtained using the Integral Time Absolute Error (ITAE) criteria and the mean maximum error has also been compared in a Monte Carlo analysis. For a more detailed study, the amount of control energy consumption was also compared, which showed a clear superiority of the MFAC. Also, the robustness of the controller was demonstrated by introducing uncertainty in the plant parameters and by running 100 Monte Carlo simulations with random initial conditions. Finally, despite the PID controller, the MFAC followed the desired scenarios well and compared to LQR consumed less energy. The results demonstrate that the MFAC outperformed the PID and LQR controllers in the presence of random initial conditions and noise in terms of mean maximum error $$(70.4\%)$$

(
70.4
%
)

, mean ITAE $$(91\%)$$

(
91
%
)

, and energy consumption $$(46\%)$$

(
46
%
)

.
Impact of positive end-expiratory pressure on renal resistive index in mechanical ventilated patients
Authors: Fogagnolo Alberto , Grasso Salvatore , Morelli Elena , Murgolo Francesco , Di Mussi Rosa , Vetrugno Luigi , La Rosa Riccardo , Volta Carlo Alberto , Spadaro Savino 
Published: May 2024

AbstractPurpose: Growing evidence shows the complex interaction between lung and kidney in critically ill patients. The renal resistive index (RRI) is a bedside measurement of the resistance of the renal blood flow and it is correlated with kidney injury. The positive end-expiratory pressure (PEEP) level could affect the resistance of renal blood flow, so we assumed that RRI could help to monitoring the changes in renal hemodynamics at different PEEP levels. Our hypothesis was that the RRI at ICU admission could predict the risk of acute kidney injury in mechanical ventilated critically ill patients. Methods: We performed a prospective study including 92 patients requiring mechanical ventilation for ≥ 48 h. A RRI ≥ 0.70, was deemed as pathological. RRI was measured within 24 h from ICU admission while applying 5,10 and 15 cmH2O of PEEP in random order (PEEP trial). Results: Overall, RRI increased from 0.62 ± 0.09 at PEEP 5 to 0.66 ± 0.09 at PEEP 15 (p < 0.001). The mean RRI value during the PEEP trial was able to predict the occurrence of AKI with AUROC = 0.834 [95%CI 0.742–0.927]. Patients exhibiting a RRI ≥ 0.70 were 17/92(18%) at PEEP 5, 28/92(30%) at PEEP 10, 38/92(41%) at PEEP 15, respectively. Thirty-eight patients (41%) exhibited RRI ≥ 0.70 at least once during the PEEP trial. In these patients, AKI occurred in 55% of the cases, versus 13% remaining patients, p < 0.001. Conclusions: RRI seems able to predict the risk of AKI in mechanical ventilated patients; further, RRI values are influenced by the PEEP level applied.Trial registration: Clinical gov NCT03969914 Registered 31 May 2019.
Machine Learning Based Compton Suppression for Nuclear Fusion Plasma Diagnostics
Authors: Lennon Kimberley , Shand Chantal , Smith Robin 
Published: May 2024

AbstractDiagnostics are critical on the path to commercial fusion reactors, since measurements and characterisation of the plasma is important for sustaining fusion reactions. Gamma spectroscopy is commonly used to provide information about the neutron energy spectrum from activation analysis, which can be used to calculate the neutron flux and fusion power. The detection limits for measuring nuclear dosimetry reactions used in such diagnostics are fundamentally related to Compton scattering events making up a background continuum in measured spectra. This background lies in the same energy region as peaks from low-energy gamma rays, leading to detection and characterisation limitations. This paper presents a digital machine learning Compton suppression algorithm (MLCSA), that uses state-of-the-art machine learning techniques to perform pulse shape discrimination for high purity germanium (HPGe) detectors. The MLCSA identifies key features of individual pulses to differentiate between those that are generated from photopeaks and Compton scatter events. Compton events are then rejected, reducing the low energy background. This novel suppression algorithm improves gamma spectroscopy results by lowering minimum detectable activity (MDA) limits and thus reducing the measurement time required to reach the desired detection limit. In this paper, the performance of the MLCSA is demonstrated using an HPGe detector, with a gamma spectrum containing americium-241 (Am-241) and cobalt-60 (Co-60). The MDA of Am-241 improved by 51% and the signal to background ratio improved by 49%, while the Co-60 peaks were partially preserved (reduced by 78%). The MLCSA requires no modelling of the specific detector and so has the potential to be detector agnostic, meaning the technique could be applied to a variety of detector types and applications.
Efficient WENO Schemes for Nonuniform Grids
Authors: Martí M. Carmen , Mulet Pep , Yáñez Dionisio F. , Zorío David 
Published: May 2024

AbstractA set of arbitrarily high-order WENO schemes for reconstructions on nonuniform grids is presented. These non-linear interpolation methods use simple smoothness indicators with a linear cost with respect to the order, making them easy to implement and computationally efficient. The theoretical analysis to verify the accuracy and the essentially non-oscillatory properties are presented together with some numerical experiments involving algebraic problems in order to validate them. Also, these general schemes are applied for the solution of conservation laws and hyperbolic systems in the context of finite volume methods.
The current status of natural and artificial radiation in İstanbul 36 years after chernobyl, preceding a potential nuclear threat
Authors: Günay Osman , Özden Selin , Aközcan Pehlivanoğlu Serpil 
Published: May 2024

AbstractIn this study, the current status of natural and artificial radioactivity levels in soil samples from the Büyükçekmece and Silivri districts of Istanbul, as well as the Marmara Ereğlisi district in Tekirdağ, has been determined in anticipation of a potential nuclear leakage (e.g. the Zaporizhzhia Nuclear Power Plant). Twenty soil samples were collected from the study area, and the radioactivity concentrations of 226Ra, 232Th, 40K and 137Cs were measured using an HPGe detector. The average concentrations of 226Ra, 232Th, 40K and 137Cs were found to be 26 ± 2, 30 ± 2, 540 ± 29, 0.55 ± 0.07 Bq kg−1, respectively.
Investigations of the carbonization process of hybrid polymer microspheres using the TGA-EGA method: assessment of the impact of sulphanilic acid on the process
Authors: Sobiesiak Magdalena , Podkościelna Beata , Mazur Liliana 
Published: May 2024

AbstractThe TGA-EGA technique was used to study the influence of sulphanilic acid (SA) on the carbonisation process of the hybrid terpolymeric precursors composed of methacrylamide, divinylbenzene, and trimethoxyvinylsilane. The pristine polymers were impregnated with saturated solution of SA, dried, and carbonized at 600 °C under N2 atmosphere. The characteristic properties of both the pristine hybrid polymers and the resulting carbons were based on FTIR, Raman, and PXRD analyses, which revealed the materials were composed of amorphous polymeric or carbon phase interpenetrated by silica/silicate disordered network. The porosimetric analysis showed the resulted carbons possessed homogeneous supermicropores with the average pore width of 0.7 nm and reduced number of mesopores compared to pristine precursors. From the TGA results, it was followed that impregnated polymers decomposed in two stages, instead of one like pristine precursors did. Moreover, IDT of impregnated polymers was reduced by about 100 °C, and their Tmax was increased by 2–5.5 °C. Their decomposition proceeded slower by 22–37% that caused increase in efficiency of the process by 10–48%. The EGA showed the decomposition of the impregnated precursors started from the degradation of the amide groups, then SA destruction took place, followed by further decomposition of the polymer. The studies led to the conclusion that SA had the protective effect on the surface of the carbonized polymers. During impregnation and thermal treatment, SA produced a deposit in pores of the precursors. This resulted in narrowing of the pore width, delaying and slowing down the polymer thermal decomposition process, as well as increasing its efficiency.
Generating Function of q- and Elliptic Multiple Polylogarithms of Hurwitz Type
Authors: Kato Masaki 
Published: May 2024

AbstractOhno and Zagier (Indag Math 12:483–487, 2001) found that a generating function of sums of multiple polylogarithms can be written in terms of the Gauss hypergeometric function $${}_2F_1$$

2

F
1

. As a generalization of the Ohno and Zagier formula, Ihara et al. (Can J Math 76:1–17, 2022) showed that a generating function of sums of interpolated multiple polylogarithms of Hurwitz type can be expressed in terms of the generalized hypergeometric function $${}_{r+1}F_r$$

r
+
1

F
r

. In this paper, we establish q- and elliptic analogues of this result. We introduce elliptic q-multiple polylogarithms of Hurwitz type and study a generating function of sums of them. By taking the trigonometric and classical limits in the main theorem, we can obtain q- and elliptic generalizations of the Ihara, Kusunoki, Nakamura and Saeki formula.
Speeding up the Training of Neural Networks with the One-Step Procedure
Authors: Meskini Wajd , Brouste Alexandre , Dugué Nicolas 
Published: May 2024

AbstractIn the last decade, research and corporate have shown a dramatically growing interest in the field of machine learning, mostly due to the performances of deep neural networks. These increasingly complex architectures solved a wide range of problems. However, training these sophisticated architectures require many computation on advanced hardware. With this paper, we introduce a new approach based on the One-Step procedure that may fasten their training. In this procedure, an initial guess estimator is computed on a subsample that is then improved with only one step of the Newton gradient descent on the whole dataset. To show the efficiency of this framework, we consider regression and classification tasks using simulated and real datasets. We consider classic architectures, namely multi-layer perceptrons and show, on our examples, that the One-Step procedure is often halving the computation time to train the neural networks while preserving the performances.
Fractional optical normalization operator of magnetic field and electroosmotic optimistic energy
Authors: Ogrenmis Meltem 
Published: May 2024

AbstractIn this manuscript, we introduce optical fractional normalization and fractional recursive operators for a particle. The significance of this research lies in obtaining optical fractional recursive operators and normalized operators of magnetic fields through the utilization of a fractional spherical frame within spherical space. Throughout the study, we employ the general form of fractional derivatives, as it enables us to derive more generalized results compared to classical derivatives. Additionally, we derive the microfluidic optical fractional electroosmotic magnetic optimistic fractional energy. We propose a design for optical recursion-based fractional electroosmotic magnetic optimistic fractional energy. This innovative study holds significant potential for applications across various fields, including fluid dynamics, optics, and energy conversion.
The Body of “the Body of Christ”: An Introduction to Hyperscanning Research and a Discussion of Its Possible Implications for Understanding Social Experiences During Religious Gatherings
Authors: Forman Robert K. C. , Wald-Fuhrmann Melanie 
Published: May 2024

AbstractNeuroscience has become a well-accepted methodological modality in the study of religion, especially of religious behavior, personal prayer, meditation, mysticism, spiritual experience, and personal religious experiences. However, such studies have been performed on individuals only; none have helped scholars understand the neuro-physiological correlates of religious communities, religious interactions, collective liturgical action, or the like. This article introduces the new field of social neuroscience, showing how its primary tool, hyperscanning, is revealing surprising levels of “brain-to-brain synchrony.” Though there are no hyperscanning studies of religious communities yet, the authors suggest that findings about shared attention, interpersonal coordination, and feelings of closeness all have clear parallels in and implications for religious communities. The authors then suggest both directions and cautions for future research.
Agree to agree: correcting acquiescence bias in the case of fully unbalanced scales with application to UK measurements of political beliefs
Authors: Swatton Phil 
Published: May 2024

AbstractA methodologically important area in political science is measuring the ideology of voters. This task can be difficult, and researchers often rely on ‘off the shelf’ datasets. Many of these datasets contain unbalanced Likert scales, which risk acquiescence bias. This paper proposes a strategy for dealing with this issue. I first demonstrate using two comparable datasets from the UK how unbalanced scales produce distorted distributions and can affect regression results. Then, building on past research that utilises factor analysis to eliminate the influence of acquiescence bias, I demonstrate how researchers can utilise a person intercept confirmatory factor analysis model to obtain factor scores corrected for acquiescence in the case of fully unbalanced scales. I conclude with practical recommendations for researchers and survey designers moving forward.
Gender differences in oral appliance treatment of obstructive sleep apnea
Authors: Fransson Anette , Nohlert Eva , Tegelberg Åke , Isacsson Göran 
Published: May 2024

Abstract
Purpose
Although overall success rates for treating obstructive sleep apnea (OSA) with an oral appliance (OA) are high, they are significantly higher among females. To verify published data, the study’s purpose was to evaluate a participant sample after one year of OA use. The primary outcome was treatment response, with responders defined as having an apnea-hypopnea index (AHI) < 10 at follow-up and/or reduced by ≥50% of baseline. Secondary measures were from standardized questionnaires.

Methods
A sample of 314 participants, predominately with moderate-to-severe OSA, were enrolled and instructed to use an OA every night. At baseline and one-year follow-up, polygraphic recordings and questionnaires, including sleepiness (measured using the Epworth sleepiness scale) and quality-of-life (measured using the Functional Outcomes of Sleep Questionnaire), were collected.

Results
Among the 314 participants, 192 completed the one-year evaluation: 51 females (27%) and 141 males (73%). Overall, OA treatment resulted in 78% and 77% responders among females and males, respectively. Neither the difference in improvement nor the absolute change in AHI differed significantly based on gender, at any OSA severity level. There were no significant gender differences in sleepiness or quality of life. Treatment-related adverse reactions were more common among females.

Conclusion
Both females and males with OSA respond well to OA therapy, with nonsignificant gender differences in outcomes. Thus, the hypothesis that females respond better to OA treatment is rejected.