bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Rough with the Smooth of the Light Cone String
Authors: Dragon Norbert , Oppermann Florian 
Published: December 2023

AbstractThe polynomials in the generators of a unitary representation of the Poincaré group constitute an algebra which maps the dense subspace $$\mathcal D$$
D
of smooth, rapidly decreasing wavefunctions to itself. This mathematical result is highly welcome to physicists, who previously just assumed their algebraic treatment of unbounded operators be justified. The smoothness, however, has the side effect that a rough operator R, which does not map a dense subspace of $$\mathcal D$$
D
to itself, has to be shown to allow for some other dense domain which is mapped to itself both by R and all generators. Otherwise their algebraic product, their concatenation, is not defined. Canonical quantization of the light cone string postulates operators $$-\textrm{i}X^1$$

-
i

X
1

and $$P^-=(P^0 - P^z)/2$$

P
-

=

(

P
0

-

P
z

)

/
2

and as their commutator the multiplicative operator $$R=P^1/(P^0 + P^z)$$

R
=

P
1

/

(

P
0

+

P
z

)

. This is not smooth but rough on the negative $$z-$$

z
-

axis of massless momentum. Using only the commutation relations of $$P^m$$

P
m

with the generators $$-\textrm{i}M_{iz}$$

-
i

M

iz

of rotations in the $$P^i$$

P
i

-$$P^{z}$$

P
z

-plane we show that on massless states the operator R is inconsistent with a unitary representation of SO$$(D-1)$$

(
D
-
1
)

. This makes the algebraic determination of the critical dimension, $$D=26$$

D
=
26

, of the bosonic string meaningless: if the massless states of the light cone string admit R then they do not admit a unitary representation of the subgroup SO$$(D-1)$$

(
D
-
1
)

of the Poincaré group. With analogous arguments we show: Massless multiplets are inconsistent with a translation group of the spatial momentum which is generated by a self-adjoint spatial position operator $$\textbf{X}$$
X
.
Personality Traits Characterizing a New Type of Depression Lead to Stress Generation in Japanese University Students
Authors: Fujiwara Rika , Hasegawa Akira , Oura Shin-ichi , Matsuda Yuko 
Published: December 2023

AbstractJapanese psychiatrists have proposed a new type of depression characterized by passing blame and irritability, which worsens on working days. This new type of depression is assumed to be closely associated with two personality traits: Interpersonal sensitivity, which reflects the tendency to be excessively concerned about or overreact to others’ negative evaluations, and privileged self, which reflects the tendency to pursue own pleasures at the expense of maintaining harmony with others. Although a previous longitudinal study showed that these traits can lead to interpersonal stress generation among university students, it did not control for the influence of baseline negative events, nor use a scale that separately assessed negative dependent events caused by the participants’ behaviors and negative independent events occurring outside the participants’ control. The current study addressed these limitations and investigated whether interpersonal sensitivity and privileged self led to stress generation and increased depressive symptoms. Undergraduate and graduate students in Japan (N = 265) responded to self-report measures twice at an interval of four weeks. The results indicated that privileged self was related to an increase in subsequent experiences of negative dependent and independent events after controlling for either category of events experienced at the baseline. These findings suggest that privileged self can lead to stress generation or the perception that surrounding circumstances are worse than they are. Furthermore, privileged self was associated with an increase in subsequent depressive symptoms via experiences of negative interpersonal dependent events.
Active learning algorithm through the lens of rejection arguments
Authors: Denis Christophe , Hebiri Mohamed , Ndjia Njike Boris , Siebert Xavier 
Published: December 2023

AbstractActive learning is a paradigm of machine learning which aims at reducing the amount of labeled data needed to train a classifier. Its overall principle is to sequentially select the most informative data points, which amounts to determining the uncertainty of regions of the input space. The main challenge lies in building a procedure that is computationally efficient and that offers appealing theoretical properties; most of the current methods satisfy only one or the other. In this paper, we use the classification with rejection in a novel way to estimate the uncertain regions. We provide an active learning algorithm and prove its theoretical benefits under classical assumptions. In addition to the theoretical results, numerical experiments are carried out on synthetic and non-synthetic datasets. These experiments provide empirical evidence that the use of rejection arguments in our active learning algorithm is beneficial and allows good performance in various statistical situations.
Spatial distribution, temporal trends and impact of landslides on São Miguel Island from 1900 to 2020 based on an analysis of the Azores historical natural hazards database
Authors: Silva Rui Fagundes , Marques Rui , Zêzere José Luís 
Published: December 2023

AbstractLandslides are the most frequent type of natural hazard in the Azores archipelago, primarily due to the volcanic nature and geomorphologic features of the islands. The NATHA (Natural Hazards in Azores) database is a repository of documents reporting those natural disaster events that have occurred on the Azores since their settlement in the mid-fifteenth century. This work presents and explores the landslide events that have occurred on São Miguel Island in the period 1900–2020. A total of 236 landslide events were catalogued. The temporal distribution of the landslide events reveals a higher concentration of events after 1996, which is related to a change in the rainfall regime but also to the increasing dissemination of information. The influence of climate change on landslide occurrence is demonstrated for the first time in the Azores. The landslide events catalogued in the NATHA database were responsible for 82 fatalities, 41 injuries and 305 people made homeless, while 66 buildings were partially or completely destroyed. The spatial distribution of landslide events shows that Povoação is the municipality most prone to landslide occurrence as well as to landslide impact. Rainfall was the triggering factor of most landslide events (70%) on São Miguel Island, and landslide events have been most frequent during the wettest months of the year from November to March. The obtained results demonstrate the need of landslides prevention and preparedness programs in specific areas of São Miguel Island.
Coupled nonlinear Schrödinger (CNLS) equations for two interacting electrostatic wavepackets in a non-Maxwellian fluid plasma model
Authors: Lazarides N. , Kourakis Ioannis 
Published: December 2023

AbstractThe nonlinear dynamics of two co-propagating electrostatic wavepackets in a one-dimensional non-magnetized plasma fluid model is considered, from first principles. The coupled waves are characterized by different (carrier) wavenumbers and amplitudes. A plasma consisting of non-thermalized ($$\kappa $$
κ
-distributed) electrons evolving against a cold (stationary) ion background is considered. The original model is reduced, by means of a multiple-scale perturbation method, to a pair of coupled nonlinear Schrödinger (CNLS) equations for the dynamics of the wavepacket envelopes. For arbitrary wavenumbers, the resulting CNLS equations exhibit no known symmetry and thus intrinsically differ from the Manakov system, in general. Exact analytical expressions have been derived for the dispersion, self-modulation (nonlinearity) and cross-modulation (coupling) coefficients involved in the CNLS equations, as functions of the wavenumbers ($$k_1$$

k
1

, $$k_2$$

k
2

) and of the spectral index $$\kappa $$
κ
characterizing the electron profile. An analytical investigation has thus been carried out of the modulational instability (MI) properties of this pair of wavepackets, focusing on the role of the intrinsic (variable) parameters. Modulational instability is shown to occur in most parts of the parameter space. The instability window(s) and the corresponding growth rate are calculated numerically in a number of case studies. Two-wave interaction favors MI by extending its range of occurrence and by enhancing its growth rate. Growth rate patterns obtained for different $$\kappa $$
κ
index (values) suggest that deviation from thermal (Maxwellian) equilibrium, for low $$\kappa $$
κ
values, leads to enhance MI of the interacting wave pair. To the best of our knowledge, the dynamics of two co-propagating wavepackets in a plasma described by a fluid model with $$\kappa $$
κ
-distributed electrons is investigated thoroughly with respect to their MI properties as a function of $$\kappa $$
κ
for the first time, in the framework of an asymmetric CNLS system whose coefficients present no obvious symmetries for arbitrary $$k_1$$

k
1

and $$k_2$$

k
2

. Although we have focused on electrostatic wavepacket propagation in non-thermal (non-Maxwellian) plasma, the results of this study are generic and may be used as basis to model energy localization in nonlinear optics, in hydrodynamics or in dispersive media with Kerr-type nonlinearities where MI is relevant.
An In Silico Platform to Predict Cardiotoxicity Risk of Anti-tumor Drug Combination with hiPSC-CMs Based In Vitro Study
Authors: Sang Lan , Zhou Zhengying , Luo Shizheng , Zhang Yicui , Qian Hongjie , Zhou Ying , He Hua , Hao Kun 
Published: December 2023

Abstract
Objective
Antineoplastic agent-induced systolic dysfunction is a major reason for interruption of anticancer treatment. Although targeted anticancer agents infrequently cause systolic dysfunction, their combinations with chemotherapies remarkably increase the incidence. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a potent in vitro model to assess cardiovascular safety. However, quantitatively predicting the reduction of ejection fraction based on hiPSC-CMs is challenging due to the absence of the body's regulatory response to cardiomyocyte injury.

Methods
Here, we developed and validated an in vitro-in vivo translational platform to assess the reduction of ejection fraction induced by antineoplastic drugs based on hiPSC-CMs. The translational platform integrates drug exposure, drug-cardiomyocyte interaction, and systemic response. The drug-cardiomyocyte interaction was implemented as a mechanism-based toxicodynamic (TD) model, which was then integrated into a quantitative system pharmacology-physiological-based pharmacokinetics (QSP-PBPK) model to form a complete translational platform. The platform was validated by comparing the model-predicted and clinically observed incidence of doxorubicin and trastuzumab-induced systolic dysfunction.

Results
A total of 33,418 virtual patients were incorporated to receive doxorubicin and trastuzumab alone or in combination. For doxorubicin, the QSP-PBPK-TD model successfully captured the overall trend of systolic dysfunction incidences against the cumulative doses. For trastuzumab, the predicted incidence interval was 0.31–2.7% for single-agent treatment and 0.15–10% for trastuzumab-doxorubicin sequential treatment, covering the observations in clinical reports (0.50–1.0% and 1.5–8.3%, respectively).

Conclusions
In conclusion, the in vitro-in vivo translational platform is capable of predicting systolic dysfunction incidence almost merely depend on hiPSC-CMs, which could facilitate optimizing the treatment protocol of antineoplastic agents.
Going complex or going easy? The impact of research questions on citations
Authors: Solarino Angelo M. , Rose Elizabeth L. , Luise Cristian 
Published: December 2023

AbstractThe growing need for academic impact requires researchers to develop and address important ideas. In this paper, we analyze how theory has been framed and operationalized within international business scholarship, which has a long tradition of producing research that accounts jointly for multiple research contexts and levels of analysis. We focus on two key aspects of published articles: the complexity of their research questions and how the research questions are translated into testable hypotheses. We further assess how the complexity and operationalization of research questions have been received by business/management, interdisciplinary, and practice-oriented research audiences. To achieve this, we examine a sample of 423 quantitative articles published in the Journal of International Business Studies between 2005 and 2015, and consider the articles’ citations during 2010–2020. Our paper provides suggestions about how authors might better frame research questions that are both important and impactful.
Enhancing bitcoin transaction confirmation prediction: a hybrid model combining neural networks and XGBoost
Authors: Zhang Limeng , Zhou Rui , Liu Qing , Xu Jiajie , Liu Chengfei , Babar Muhammad Ali 
Published: December 2023

AbstractWith Bitcoin being universally recognized as the most popular cryptocurrency, more Bitcoin transactions are expected to be populated to the Bitcoin blockchain system. As a result, many transactions can encounter different confirmation delays. Concerned about this, it becomes vital to help a user understand (if possible) how long it may take for a transaction to be confirmed in the Bitcoin blockchain. In this work, we address the issue of predicting confirmation time within a block interval rather than pinpointing a specific timestamp. After dividing the future into a set of block intervals (i.e., classes), the prediction of a transaction’s confirmation is treated as a classification problem. To solve it, we propose a framework, Hybrid Confirmation Time Estimation Network (Hybrid-CTEN), based on neural networks and XGBoost to predict transaction confirmation time in the Bitcoin blockchain system using three different sources of information: historical transactions in the blockchain, unconfirmed transactions in the mempool, as well as the estimated transaction itself. Finally, experiments on real-world blockchain data demonstrate that, other than XGBoost excelling in the binary classification case (to predict whether a transaction will be confirmed in the next generated block), our proposed framework Hybrid-CTEN outperforms state-of-the-art methods on precision, recall and f1-score on all the multiclass classification cases (4-class, 6-class and 8-class) to predict in which future block interval a transaction will be confirmed.
Implication of noise exposure on hearing with emphasis to hOGG1 and GPx-1 polymorphisms and HO-1 protein among textile workers
Authors: Taha Mona Mohamed , Samir Ellaithy Lamia , Abd El-Aziz Nermeeen Said , Mahdy-Abdallah Heba , Adel Helmy Mona 
Published: December 2023

AbstractNoise exposure is a health hazard in the textile industry. In cochlear hair cells, DNA damage caused by 8-oxoguanine (8-oxo G) can result in noise-induced hearing loss. Human 8-hydroxyguanine glycosylase (hOGG1) is a DNA repair enzyme that excises (8-oxo G) in the DNA and repairs DNA damage. Glutathione peroxidase-1 (GPx) is a crucial antioxidant enzyme that aids in limiting cochlear damages. Heme oxygenase-1 (HO-1) is a stress-inducible protein with a high fold change in the hair cells of the cochlea. The study aimed to investigate the association of either hOGG1 and GPx-1 polymorphisms with audiometric notches and HO-1 protein among textile workers. hOGG1 and GPx genotypes were analyzed by PCR–RFLP, and HO-1 levels were measured by ELISA in 115 male textile workers. Blood pressure and audiogram were performed. Results recorded the relation between audiometric notches and ear complaints among workers. Older age workers showed audiometric notches at > 25 dB with a significant decrease in HO-1 levels and higher levels in workers with normal audiogram. Ser/Cys genotype of hOGG1 gene was associated with age and work duration while CC genotype of GPx is associated with HO-1 levels and diastolic pressure. Ser/Cys genotype of hOGG1 gene was associated with age while Cys/Cys genotype was associated with work duration among workers. CC genotype of GPx gene was associated with higher HO-1 levels and TT genotype was associated with high diastolic pressure. Finally, hearing impairment was dependent on the duration of exposure to noise, older age, and the presence of heterozygote TC genotype of GPx gene among textile workers.
Selenium Nanoparticles Ameliorate Adverse Impacts of Aflatoxin in Nile Tilapia with Special Reference to Streptococcus agalactiae Infection
Authors: Sherif Ahmed H. , Zommara Mohsen A. 
Published: December 2023

AbstractAflatoxin B1 (AFB1) is a plant-origin toxin that could induce oxidative stress in fish. The micromineral selenium (Se) possesses well-documented antioxidant properties. To assess the ameliorative effects of SeNPs (1 mg/kg fish feed) on oxidative stress induced by AFB1 (500 μg/kg fish feed), Nile tilapia (32.2±1.7 g body weight) were distributed randomly and even in six groups for 8-week feeding trial. Live enzymes, AST, ALT, and ALP levels were increased in the serum of fish fed AFB1-contaminated diet, and the addition of SeNPs could restore normal values compared to the control. The gene expression of antioxidant enzymes, superoxide dismutase (SOD) enzyme and catalase (CAT) enzyme, and DNA fragmentation were significantly increased in response to aflatoxin exposure, while dietary SeNPs could mitigate the generated oxidative stress. The innate immunity, serum antibacterial activity (SAA), oxidative burst activity (OBA), phagocytic activities (PA and PI), and gene expression of cytokines (interleukin (IL)-1β, heat shock protein70 (Hsp), and tumor necrosis factor (TNF)-α) revealed a status of immunosuppression in Nile tilapia fed on AFB1-contaminated diet. These findings showed that fish became more vulnerable to Streptococcus agalactiae infection with a high mortality rate while dietary SeNPs provided a high relative protection level (RPL). From the obtained findings, SeNPs could mitigate the oxidative stress induced by feeding the AFB1 diet and could boost the immunity of stressed Nile tilapia.
Assessing emotion beliefs with the Polish version of the Emotion Beliefs Questionnaire (EBQ): psychometric properties, norms, and links with emotional reactivity and psychopathology
Authors: Larionow Paweł , Preece David A. , Mudło-Głagolska Karolina 
Published: December 2023

AbstractOriginally developed in English, the Emotion Beliefs Questionnaire (EBQ) is a self-report measure of beliefs about the controllability and usefulness of negative and positive emotions. In this study, we introduce the Polish version and examine its psychometric properties and links with emotional outcomes. Our sample was 914 Polish adults aged 18–70 from the general population. Confirmatory factor analysis was applied to verify the factor structure. Convergent and divergent validity were assessed based on the relationship between the EBQ and emotional reactivity traits as well as markers of anxiety, depression, and stress. We assessed internal consistency reliability. We also examined discriminant validity by conducting exploratory factor analyses of EBQ scores and emotional reactivity traits and psychopathology symptoms. We evaluated criterion validity by conducting a set of multiple regression analyses, examining whether EBQ scores could predict significant variance in psychopathology symptoms. Our factor analyses supported the EBQ’s factorial validity, conforming to the intended 4-factor structure (subscales: negative-controllability, positive-controllability, negative-usefulness, positive-usefulness), with support also found for a higher-order general factor (e.g., CFI = 0.941, RMSEA = 0.063). This structure was invariant across gender and age categories. The EBQ subscales correlated in expected directions with emotional reactivity traits and psychopathology symptoms. The EBQ showed good internal consistency reliability (α = 0.77–0.88) and discriminant validity. Beliefs about the uncontrollability of negative emotions were the strongest unique predictor of psychopathology symptoms. We also presented percentile rank norms for Polish adults. The Polish version of the EBQ appears to have strong psychometric properties and good clinical relevance.
Knowledge and Food Sustainability: the Metaverse as a New Economic-Environmental Paradigm
Authors: Boccia Flavio , Covino Daniela 
Published: December 2023

AbstractNowadays the metaverse may represent the line between the most avant-garde innovations of the present and the possible development potential of the next years. The present article aims to show for the first time the potential that this innovative technological opportunity offers in the coming years. By looking at the current state of knowledge and, above all, with the help of empirical evidence from the metaverse’s main application business cases in the food sector, it is possible to understand how food companies can survive in the increasingly fierce world competition. The considerations that derive from the observation of these corporate excellent examples highlight that it is increasingly necessary to strategically invest in all three dimensions of sustainability, but also in novel new technological innovations. So, from the analysis of the most important available case studies, it is clear that metaverse is definitely a very particular innovation capable of opening up new and sustainable economic opportunities for companies in the food industry. At the current state of research, there are no comparable studies on this topic, especially in agri-food systems. Yet, this is only a starting point for further research in the future. Nonetheless, we can already recognize the strategic potential of virtual universes.
Image-based Appraisal of Woody Starch Reserves in Grapevine
Authors: Dinu Daniel Grigorie , Nuzzo Vitale , Gestri Giulia , Montanaro Giuseppe , Rustioni Laura 
Published: December 2023

AbstractMaintaining stable yield in a climate change scenario requires the implementation of adaptive strategies for vine and vineyard management. Knowing the level of starch stored in perennial vine organs may help to reduce the risk of environmental constraints. Therefore, the development of decision support tools is important to assist winegrowers. The aim of this work was to test the possibility of estimating the starch content in grapevine woody tissues using digital imaging analysis. A colorimetric index (CI) based on red (R), green (G), and blue (B) mean pixel values was proposed and compared with an existing spectrophotometric index (SI). Shoots of three grapevine cultivars were collected during the 2020 dormant season and forced to produce new rooted cuttings. From these cuttings, a total of 73 internodes were sampled and their woody sections stained with Lugol’s iodine solution and CI and SI determined. In the three varieties, the CI well correlated with the SI (Spearman’s test ranged from − 0.84 to − 0.93, p < 0.0001). The resulting CI-based model developed can accurately (R2 = 0.84) predict the SI confirming it is a reliable method for the digital determination of woody reserves in grapevine, supporting management decisions in viticulture.