bluuebunny/crossref_metadata_2025_split huggingface dataset:
CXCL10 as a shared specific marker in rheumatoid arthritis and inflammatory bowel disease and a clue involved in the mechanism of intestinal flora in rheumatoid arthritis
Authors: Guan Yin , Zhang Yue , Zhu Yifan , Wang Yue 
Published: June 2023

AbstractThis study aimed to identify shared specific genes associated with rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) through bioinformatic analysis and to examine the role of the gut microbiome in RA. The data were extracted from the 3 RA and 1 IBD gene expression datasets and 1 RA gut microbiome metagenomic dataset. Weighted correlation network analysis (WGCNA) and machine learnings was performed to identify candidate genes associated with RA and IBD. Differential analysis and two different machine learning algorithms were used to investigate RA’s gut microbiome characteristics. Subsequently, the shared specific genes related to the gut microbiome in RA were identified, and an interaction network was constructed utilizing the gutMGene, STITCH, and STRING databases. We identified 15 candidates shared genes through a joint analysis of the WGCNA for RA and IBD. The candidate geneCXCL10was identified as the shared hub gene by the interaction network analysis of the corresponding WGCNA module gene to each disease, andCXCL10was further identified as the shared specific gene by two machine learning algorithms. Additionally, we identified 3 RA-associated characteristic intestinal flora (Prevotella,Ruminococcus, andRuminococcus bromii) and built a network of interactions between the microbiomes, genes, and pathways. Finally, it was discovered that the geneCXCL10shared between IBD and RA was associated with the three gut microbiomes mentioned above. This study demonstrates the relationship between RA and IBD and provides a reference for research into the role of the gut microbiome in RA.
Lead induces mouse skin fibroblast apoptosis by disrupting intracellular homeostasis
Authors: Wang Hui , Wang Huinuan , Guan Jiawen , Guan Weijun , Liu Zheng 
Published: June 2023

AbstractLead (Pb) is a critical industrial and environmental contaminant that can cause pathophysiological changes in several cellular and organ systems and their processes, including cell proliferation, differentiation, apoptosis, and survival. The skin is readily exposed to and damaged by Pb, but the mechanisms through which Pb damages cells are not fully understood. We examined the apoptotic properties of Pb in mouse skin fibroblast (MSF) in vitro. Treatment of fibroblasts with 40, 80, and 160 μM Pb for 24 h revealed morphological alterations, DNA damage, enhanced caspase-3, -8, and -9 activities, and apoptotic cell population. Furthermore, apoptosis was dosage (0–160 μM) and time (12–48 h) dependent. Concentrations of intracellular calcium (Ca2+) and reactive oxygen species were increased, and the mitochondrial membrane potential was decreased in exposed cells. Cell cycle arrest was evident at the G0/G1 phase. The Bax, Fas, caspase-3 and -8, and p53 transcript levels were increased, whereas Bcl-2 gene expression was decreased. Based on our analysis, Pb triggers MSF apoptosis bydisrupting intracellular homeostasis. Our findings enrich the knowledge about the mechanistic function of Pb-induced cytotoxicity on human skin fibroblasts and could potentially guide future Pb health risk assessments.
Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry
Authors: Nizioł Joanna , Ossoliński Krzysztof , Płaza-Altamer Aneta , Kołodziej Artur , Ossolińska Anna , Ossoliński Tadeusz , Nieczaj Anna , Ruman Tomasz 
Published: June 2023

AbstractBladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.
Sex-dependent performance differences in curvilinear aiming arm movements in octogenarians
Authors: Kutz Dieter F. , Fröhlich Stephanie , Rudisch Julian , Müller Katrin , Voelcker-Rehage Claudia 
Published: June 2023

AbstractIn an aging society, it is necessary to detect the cognitive decline of individuals at an early stage using simple measurement methods. This makes early health care possible for those affected. The aim of the study was to develop a classifier for cognitive state in older adults with and without mild cognitive impairment (MCI) based on kinematic parameters of linear and curvilinear aiming arm movements. In a group of 224 older adults over 80 years of age (cognitively healthy and MCI), the movement duration and intersegment intervals of linear and curvilinear arm movements of 20 cm were recorded. Movement duration was significantly longer in the curvilinear condition than in the straight movement, and MCI participants required significantly more time than cognitively healthy participants. Post-hoc analysis on the fluidity of movement in the curvilinear condition showed that MCI men had significantly longer inter-segmental intervals than non-MCI men. No difference was found in women. Based on the inter-segmental intervals, a simple classifier could be developed that correctly classified 63% of the men. In summary, aiming arm movements are only conditionally suitable as a classifier for cognitive states. For the construction of an ideal classifier, age-related degeneration of cortical and subcortical motor areas should be considered.
Investigation of the potential role of fusicoccin, a fungal phytotoxin, in mitigating salt stress in onion roots
Authors: Çavuşoğlu Kürşat , Çavuşoğlu Dilek 
Published: June 2023

AbstractFusicoccin is a diterpene glycoside that plays an important role in the regulation of plant growth and development. Fusicoccin produced by Fusicoccum amydali fungus is known to affect plant growth positively with external applications due to its potential to stimulate the tolerance system of plants under stress conditions. In this study, it was aimed to reduce the negative effects of salt (0.15 M NaCl) stress on the germination and growth of onion (Allium cepa L.) bulbs by external fusicoccin (3 µM) application. For this purpose, the germination percentage, root length, root number, fresh weight, mitotic activity, micronucleus frequency, chromosomal abnormality, antioxidant enzyme activity, osmolyte accumulation, cell membrane damage and root anatomical structure were investigated in the current study. Salt stress caused a statistically significant difference (p < 0.05) in all examined parameters. External application of fusicoccin to onion bulbs germinated under salt stress conditions was found to be promising as a plant growth promoter and mitosis stimulator. In addition, fusicoccin application alleviated the harmful effects of salt stress on the chromosome structure and root anatomical structure and protected the cells from the cytotoxic and genotoxic effects of salt. Moreover, this application contributed to the fight against reactive oxygen species of onion plant and increased salt tolerance by regulating the accumulation of osmolyte substances such as proline and antioxidant enzymes such as superoxide dismutase and catalase, and by minimizing cell membrane damage in root cells. In conclusion, this study showed that exogenous application of 3 µM fusicoccin reduced the damage caused by oxidative stress in onion bulbs and served for healthy germination and growth.
Photocarboxylation of remote C–H bonds through nitrogen-centred radical 1,5-hydrogen atom transfer
Authors: Li Wenke , Sun Beiqi , Zhang Lei , Mo Fanyang 
Published: June 2023

We have pioneered a methodology for the visible-light-driven carboxylation of remote C−H bonds, employing a nitrogen-centered 1,5-hydrogen atom transfer (1,5-HAT) mechanism, with CO2 serving as the carbon source.
Deep learning in crowd counting: A survey
Authors: Deng Lijia , Zhou Qinghua , Wang Shuihua , Górriz Juan Manuel , Zhang Yudong 
Published: June 2023

AbstractCounting high‐density objects quickly and accurately is a popular area of research. Crowd counting has significant social and economic value and is a major focus in artificial intelligence. Despite many advancements in this field, many of them are not widely known, especially in terms of research data. The authors proposed a three‐tier standardised dataset taxonomy (TSDT). The Taxonomy divides datasets into small‐scale, large‐scale and hyper‐scale, according to different application scenarios. This theory can help researchers make more efficient use of datasets and improve the performance of AI algorithms in specific fields. Additionally, the authors proposed a new evaluation index for the clarity of the dataset: average pixel occupied by each object (APO). This new evaluation index is more suitable for evaluating the clarity of the dataset in the object counting task than the image resolution. Moreover, the authors classified the crowd counting methods from a data‐driven perspective: multi‐scale networks, single‐column networks, multi‐column networks, multi‐task networks, attention networks and weak‐supervised networks and introduced the classic crowd counting methods of each class. The authors classified the existing 36 datasets according to the theory of three‐tier standardised dataset taxonomy and discussed and evaluated these datasets. The authors evaluated the performance of more than 100 methods in the past five years on different levels of popular datasets. Recently, progress in research on small‐scale datasets has slowed down. There are few new datasets and algorithms on small‐scale datasets. The studies focused on large or hyper‐scale datasets appear to be reaching a saturation point. The combined use of multiple approaches began to be a major research direction. The authors discussed the theoretical and practical challenges of crowd counting from the perspective of data, algorithms and computing resources. The field of crowd counting is moving towards combining multiple methods and requires fresh, targeted datasets. Despite advancements, the field still faces challenges such as handling real‐world scenarios and processing large crowds in real‐time. Researchers are exploring transfer learning to overcome the limitations of small datasets. The development of effective algorithms for crowd counting remains a challenging and important task in computer vision and AI, with many opportunities for future research.
Rule acquisition of three‐way semi‐concept lattices in formal decision context
Authors: Zhao Jie , Wan Renxia , Miao Duoqian , Zhang Boyang 
Published: June 2023

AbstractThree‐way concept analysis is an important tool for information processing, and rule acquisition is one of the research hotspots of three‐way concept analysis. However, compared with three‐way concept lattices, three‐way semi‐concept lattices have three‐way operators with weaker constraints, which can generate more concepts. In this article, the problem of rule acquisition for three‐way semi‐concept lattices is discussed in general. The authors construct the finer relation of three‐way semi‐concept lattices, and propose a method of rule acquisition for three‐way semi‐concept lattices. The authors also discuss the set of decision rules and the relationships of decision rules among object‐induced three‐way semi‐concept lattices, object‐induced three‐way concept lattices, classical concept lattices and semi‐concept lattices. Finally, examples are provided to illustrate the validity of our conclusions.
A dual robust control architecture with variable stiffness and damping parameters for switching task dominance in collaborative haptic systems
Authors: Motaharifar Mohammad , Sharifi Iman , Sadeghi Hamed , Taghirad Hamid D. 
Published: June 2023

AbstractIn collaborative haptic training systems, a novice operator is interfaced with an expert operator and cooperatively performs some task on a real/virtual environment. Most control architectures for collaborative haptic training systems do not consider the switching task dominance together with investigating overall stability in the presence of nonlinear dynamics and uncertainty. In this paper, a theoretical framework is presented for switching task dominance in collaborative haptic training systems based on supervision and intervention of the expert operator. To that effect, the novice operator performs the operation with as little as possible interference haptic signals in the normal operational conditions. On the other hand, the expert operator is able to intervene the operation to guide the novice operator when it is necessary. The most challenging part of controller design for such systems is to provide the mentioned supervisory framework in a way that the stability of interaction between the operators and the system is ensured with acceptable task performance in various operational conditions. This work offers a variable‐gain dual robust control scheme to address the above problem. The key idea is that the tracking gain of each controller is adjusted in real‐time to switch the task authorities. It is verified that the input‐to‐state stability property is satisfied for each subsystem. Then, the overall stability is proved by leveraging the small gain theorem. Finally, the functionality and performance of the suggested control architecture is demonstrated through simulation and experimental studies.
Multi‐stage stochastic long‐term planning of grid‐connected hydrogen‐based energy system based on improved SDDIP
Authors: Cao Binrui , Wu Xiong , Liu Bingwen , Wang Xiuli , Wang Penglei , Wu Yunyi 
Published: June 2023

AbstractHydrogen‐based energy systems (HESs) have shown great potential to promote the process of decarbonization. Conventional studies mainly focus on the sizing and operation of HESs in a determined static situation, and the dynamic planning model of HESs considering large‐scale uncertain scenarios of future developments should be considered. This paper proposes a multi‐stage stochastic programming (MSP) long‐term planning model to find the optimal sequential planning results of the grid‐connected HES. The planning model considers the long‐term uncertainties of the investment cost decrease and the load increase. Additionally, the short‐term uncertainties of renewable energies are also considered to obtain robust results in each stage. The improved stochastic dual dynamic integer programming (SDDIP) is then employed to solve the MSP long‐term planning model with consideration of the realized uncertainties. Specifically, the sequential planning order is developed to improve the efficiency of the SDDIP. Numerical case studies are constructed to show the convergence process of the improved SDDIP and the planning results of the HES. Moreover, the improved SDDIP shows greater efficiency compared with the traditional SDDIP and the method which solves the model directly.
User trajectory prediction in mobile wireless networks using quantum reservoir computing
Authors: Mlika Zoubeir , Cherkaoui Soumaya , Laprade Jean Frédéric , Corbeil‐Letourneau Simon 
Published: June 2023

AbstractThis paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks by using an approach called quantum reservoir computing (QRC). Mobile users' trajectories prediction belongs to the task of temporal information processing, and it is a mobility management problem that is essential for self‐organising and autonomous 6G networks. Our aim is to accurately predict the future positions of mobile users in wireless networks using QRC. To do so, the authors use a real‐world time series dataset to model mobile users' trajectories. The QRC approach has two components: reservoir computing (RC) and quantum computing (QC). In RC, the training is more computational‐efficient than the training of simple recurrent neural networks since, in RC, only the weights of the output layer are trainable. The internal part of RC is what is called the reservoir. For the RC to perform well, the weights of the reservoir should be chosen carefully to create highly complex and non‐linear dynamics. The QC is used to create such dynamical reservoir that maps the input time series into higher dimensional computational space composed of dynamical states. After obtaining the high‐dimensional dynamical states, a simple linear regression is performed to train the output weights and, thus, the prediction of the mobile users' trajectories can be performed efficiently. In this study, we apply a QRC approach based on the Hamiltonian time evolution of a quantum system. The authors simulate the time evolution using IBM gate‐based quantum computers, and they show in the experimental results that the use of QRC to predict the mobile users' trajectories with only a few qubits is efficient and can outperform the classical approaches such as the long short‐term memory approach and the echo‐state networks approach.
An atypical plateau-like extreme-ultraviolet late-phase solar flare driven by the nonradial eruption of a magnetic flux rope
Authors: Chen Yuehong , Dai Yu , Ding Mingde 
Published: June 2023

Context. Recent observations in extreme-ultraviolet (EUV) wavelengths reveal an EUV late phase in some solar flares that is characterized by a second peak in the warm coronal emissions (∼3 MK) occurring several tens of minutes to a few hours after the corresponding main flare peak.
Aims. Our aim is to clarify the physical origin of an atypical plateau-like EUV late phase in an X1.8-class solar flare occurring on 2011 September 7 from active region (AR) 11283.
Methods. We mainly took advantage of observations with the three instruments on board the Solar Dynamics Observatory (SDO). We first characterized the plateau-like late phase using EUV Variability Experiment (EVE) full-disk integrated irradiance observations and Atmospheric Imaging Assembly (AIA) spatially resolved imaging observations. Then we performed a nonlinear force-free-field (NLFFF) extrapolation of the AR magnetic fields based on the photospheric vector magnetogram with the Helioseismic and Magnetic Imager (HMI), from which a filament-hosting magnetic flux rope (MFR) is revealed. The eruption of the MFR is tracked both in the plane of the sky (POS) and along the line of sight (LOS) through visual inspection and spectral fitting, respectively. Finally, we carried out differential emission measure (DEM) analysis to explore the thermodynamics of the late-phase loops.
Results. The MFR shows a nonradial eruption from a fan-spine magnetic structure. The eruption of the MFR and its interaction with overlying arcades invoke multiple magnetic reconnections that are responsible for the production of different groups of late-phase loops. Afterward, the late-phase loops enter a long-lasting cooling stage, appearing sequentially in AIA passbands of decreasing response temperatures. Due to their different lengths, the different groups of late-phase loops cool down at different rates, which makes their warm coronal emission peaks temporally separated from each other. Combining the emissions from all late-phase loops together, an elongated plateau-like late phase is formed.
TDCOSMO
Authors: Wells Patrick , Fassnacht Christopher D. , Rusu C. E. 
Published: June 2023

Context.Time-delay cosmography uses strong gravitational lensing of a time-variable source to infer the Hubble constant. The measurement is independent from both traditional distance ladder and CMB measurements. An accurate measurement with this technique requires considering the effects of objects along the line of sight outside the primary lens, which is quantified by the external convergence (κext). In absence of such corrections,H0will be biased towards higher values in overdense fields and lower values in underdense fields.Aims.We discuss the current state of the methods used to account for environment effects. We present a new software package built for this kind of analysis and others that can leverage large astronomical survey datasets. We apply these techniques to the SDSS J0924+0219 strong lens field.Methods.We infer the relative density of the SDSS J0924+0219 field by computing weighted number counts for all galaxies in the field, and comparing to weighted number counts computed for a large number of fields in a reference survey. We then compute weighted number counts in the Millennium Simulation and compare these results to infer the external convergence of the lens field.Results.Our results show the SDSS J0924+0219 field is a fairly typical line of sight, with medianκext = −0.012 and standard deviationσκ = 0.028.
Auswirkungen des Tragens von Gesichtsmasken zur Prävention
von Infektionskrankheiten auf das Befinden und Verhalten von Kindern und
Jugendlichen: Eine Interviewstudie
Authors: Drössler Stephanie , Horvath Kathy , Freiberg Alice , Kämpf Daniel , Spura Anke , Buhs Bernhard , Seidler Andreas 
Published: June 2023

Zusammenfassung
Ziel Auswirkungen des Maskentragens während der COVID-19 Pandemie
auf Befinden, Verhalten und die psychosoziale Entwicklung von Kindern und
Jugendlichen zu untersuchen.
Methodik Es wurden leitfadengestützte Expert:inneninterviews mit
Erzieher:innen (n=2), Lehrkräften aus dem Primar- und
Sekundarbereich (n=9), Jugendlichen aus der
Schüler:innenvertretung (n=5) und Ärztinnen aus der
Primärversorgung (n=3) und dem Öffentlichen
Gesundheitsdienst (n=1) geführt, transkribiert und mit MAXQDA
2020 einer thematischen Analyse unterzogen.
Ergebnisse Am häufigsten werden kurz- und mittelfristige direkte
Auswirkungen des Maskentragens auf eine eingeschränkte Kommunikation
durch Reduktion von Hörverstehen und Mimik berichtet. Aus diesen
Kommunikationseinschränkungen ergeben sich Folgen für die
soziale Interaktion und die Qualität des Unterrichts. Auswirkungen auf
Sprachentwicklung und sozial-emotionale Entwicklung werden eher perspektivisch
vermutet. Es wird eine Zunahme von psychosomatischen Beschwerden,
Ängsten, Depressionen und Essstörungen beschrieben, die nur sehr
eingeschränkt auf das Maskentragen als vielmehr auf das Konglomerat an
Distanzierungsmaßnahmen zurückgeführt wird. Als
vulnerable Gruppen werden Kinder mit Entwicklungsschwierigkeiten, nichtdeutscher
Muttersprache, jüngere Kinder sowie schüchterne und stille
Kinder und Jugendliche genannt.
Schlussfolgerung Während für den gesamten Bereich der
Kommunikation und Interaktion die Folgen des Maskentragens für Kinder
und Jugendliche recht gut beschrieben werden können, sind Auswirkungen
auf die anderen Bereiche der psychosozialen Entwicklung (noch) nicht eindeutig
identifizierbar. Empfehlungen für den Umgang mit den
Einschränkungen werden vor allem mit Blick auf den schulischen Bereich
gegeben.