bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neurotoxicological profile of the hallucinogenic compound 25I-NBOMe
Authors: Herian Monika , Wojtas Adam , Maćkowiak Marzena , Wawrzczak-Bargiela Agnieszka , Solarz Anna , Bysiek Agnieszka , Madej Katarzyna , Gołembiowska Krystyna 
Published: February 2022

Abstract4-Iodo-2,5-dimethoxy-N-(2-methoxybenzyl)phenethylamine (25I-NBOMe) is a new psychoactive substance with strong hallucinogenic properties. Our previous data reported increased release of dopamine, serotonin, and glutamate after acute injections and a tolerance development in the neurotransmitters release and rats’ behavior after chronic treatment with 25I-NBOMe. The recreational use of 25I-NBOMe is associated with severe intoxication and deaths in humans. There is no data about 25I-NBOMe in vivo toxicity towards the brain tissue. In this article 25I-NBOMe-crossing through the blood–brain barrier (BBB), the impact on DNA damage, apoptosis induction, and changes in the number of cortical and hippocampal cells were studied. The presence of 25I-NBOMe in several brain regions shortly after the drug administration and its accumulation after multiple injections was found. The DNA damage was detected 72 h after the chronic treatment. On the contrary, at the same time point apoptotic signal was not identified. A decrease in the number of glial but not in neural cells in the frontal (FC) and medial prefrontal cortex (mPFC) was observed. The obtained data indicate that 25I-NBOMe passes easily across the BBB and accumulates in the brain tissue. Observed oxidative DNA damage may lead to the glial cells’ death.
Intersectional, anterograde transsynaptic targeting of neurons receiving monosynaptic inputs from two upstream regions
Authors: Kitanishi Takuma , Tashiro Mariko , Kitanishi Naomi , Mizuseki Kenji 
Published: February 2022

AbstractA brain region typically receives inputs from multiple upstream areas. However, currently, no method is available to selectively dissect neurons that receive monosynaptic inputs from two upstream regions. Here, we developed a method to genetically label such neurons with a single gene of interest in mice by combining the anterograde transsynaptic spread of adeno-associated virus serotype 1 (AAV1) with intersectional gene expression. Injections of AAV1 expressing either Cre or Flpo recombinases and the Cre/Flpo double-dependent AAV into two upstream regions and the downstream region, respectively, were used to label postsynaptic neurons receiving inputs from the two upstream regions. We demonstrated this labelling in two distinct circuits: the retina/primary visual cortex to the superior colliculus and the bilateral motor cortex to the dorsal striatum. Systemic delivery of the intersectional AAV allowed the unbiased detection of the labelled neurons throughout the brain. This strategy may help analyse the interregional integration of information in the brain.
Short‐term electricity price forecasting based on graph convolution network and attention mechanism
Authors: Yang Yuyun , Tan Zhenfei , Yang Haitao , Ruan Guangchun , Zhong Haiwang , Liu Fengkui 
Published: February 2022

AbstractIn electricity markets, locational marginal price (LMP) forecasting is particularly important for market participants in making reasonable bidding strategies, managing potential trading risks, and supporting efficient system planning and operation. Unlike existing methods that only consider LMPs' temporal features, this paper tailors a spectral graph convolutional network (GCN) to greatly improve the accuracy of short‐term LMP forecasting. A three‐branch network structure is then designed to match the structure of LMPs' compositions. Such kind of network can extract the spatial‐temporal features of LMPs, and provide fast and high‐quality predictions for all nodes simultaneously. The attention mechanism is also implemented to assign varying importance weights between different nodes and time slots. Case studies based on the IEEE‐118 test system and real‐world data from the PJM validate that the proposed model outperforms existing forecasting models in accuracy, and maintains a robust performance by avoiding extreme errors.
Performance comparison of single and ensemble CNN, LSTM and traditional ANN models for short‐term electricity load forecasting
Authors: Kathirgamanathan Arurun , Patel Afzal , Khwaja Ahmed S. , Venkatesh Bala , Anpalagan Alagan 
Published: February 2022

AbstractThe authors propose bagged and boosted convolutional neural networks (CNNs) and long short‐term memory (LSTM) networks, and compare their performance with the bagged and boosted traditional shallow artificial neural networks (ANNs) for short‐term electricity load forecasting. Unlike existing references that mainly compare the performance of ensemble deep learning with single deep learning and machine learning techniques, three further performance comparisons are carried out: (1) bagged CNNs and bagged LSTMs, (2) boosted CNNs and LSTMs, and (3) bagged CNNs and bagged LSTMs, and boosted CNNs and LSTMs. This allows an insight into the individual effects of ensemble learning on CNNs and LSTMs. The proposed models' inputs consist of weather and time‐related features in addition to the past load. The use of these features allows CNNs and LSTMs to estimate further complex relationship between them and the load. We implement all these methods and compare their performance on the same New England electricity load forecasting data set via statistical analysis. Effects on the forecasting performance with reduced training data are further shown. The LSTM models have the largest performance variation and are also more sensitive to a reduction in training data. In these models, boosting can improve both prediction accuracy and consistency.
Heating of the solar chromosphere through current dissipation
Authors: da Silva Santos J. M. , Danilovic S. , Leenaarts J. , de la Cruz Rodríguez J. , Zhu X. , White S. M. , Vissers G. J. M. , Rempel M. 
Published: February 2022

Context.The solar chromosphere is heated to temperatures higher than predicted by radiative equilibrium. This excess heating is greater in active regions where the magnetic field is stronger.Aims.We aim to investigate the magnetic topology associated with an area of enhanced millimeter (mm) brightness temperatures in a solar active region mapped by the Atacama Large Millimeter/submillimeter Array (ALMA) using spectropolarimetric co-observations with the 1-m Swedish Solar Telescope (SST).Methods.We used Milne–Eddington inversions, nonlocal thermodynamic equilibrium (non-LTE) inversions, and a magnetohydrostatic extrapolation to obtain constraints on the three-dimensional (3D) stratification of temperature, magnetic field, and radiative energy losses. We compared the observations to a snapshot of a magnetohydrodynamics simulation and investigate the formation of the thermal continuum at 3 mm using contribution functions.Results.We find enhanced heating rates in the upper chromosphere of up to ∼5 kW m−2, where small-scale emerging loops interact with the overlying magnetic canopy leading to current sheets as shown by the magnetic field extrapolation. Our estimates are about a factor of two higher than canonical values, but they are limited by the ALMA spatial resolution (∼1.2″). Band 3 brightness temperatures reach about ∼104K in the region, and the transverse magnetic field strength inferred from the non-LTE inversions is on the order of ∼500 G in the chromosphere.Conclusions.We are able to quantitatively reproduce many of the observed features including the integrated radiative losses in our numerical simulation. We conclude that the heating is caused by dissipation in current sheets. However, the simulation shows a complex stratification in the flux emergence region where distinct layers may contribute significantly to the emission in the mm continuum.
Die Bedeutung der Verhaltens- und
Verhältnisprävention in der Metallindustrie: Empirische
Untersuchungen am Beispiel der Berufsgruppe Schweißer
Authors: Weyh Christopher , Pilat Christian , Krüger Karsten , Frech Torsten , Schubert Emil , Mooren Frank-Christoph 
Published: February 2022

ZusammenfassungMuskel-Skelett-Erkrankungen gehören zu den häufigsten
berufsbedingten Erkrankungen in der Metallindustrie. Die Berufsgruppe der
Schweißer fällt dort durch hohe Prävalenzen auf. Daher
sind Maßnahmen zur Prävention und Gesundheitsförderung
dieser Zielgruppe von großem Interesse. Die vorliegende Studienreihe
hatte zum Ziel, gesundheitliche Probleme von Schweißern zu analysieren
und Möglichkeiten der Verhaltens- und
Verhältnisprävention zu untersuchen. Eine Fragebogenuntersuchung
bei 143 Schweißern in 34 Unternehmen der deutschen Industrie ergab, dass
die 12-Monats-Prävalenz von unteren Rückenschmerzen 71%,
Nackenschmerzen 61% und Schulterschmerzen 55% betrug. Insgesamt
42% der Befragten weisen eine körperliche
Freizeitaktivität unter dem von der WHO empfohlenen Umfang auf. Eine
niedrige Freizeitaktivität sowie Nackenschmerzen konnten als
unabhängige Risikofaktoren für das Auftreten von unteren
Rückenschmerzen identifiziert werden.In einem weiteren Studienteil wurden die Auswirkungen eines individualisierten
und progressiven 24-wöchigen Ausdauer- oder Krafttrainingsprogramms bei
77 berufstätigen Schweißern untersucht. Es konnten
differenzierte Auswirkungen auf arbeitsbedingte Beanspruchungen und auf
verschiedene Dimensionen von Gesundheit und Leistung gezeigt werden. Zum
Erreichen präventiver Effekte sollten Bewegungsinterventionen mit
systematischem, langfristigem und progressivem Charakter ausgewählt
werden. Die Erfahrungen aus der Praxis zeigen allerdings auch, dass die
Barrieren zur Teilnahme an Bewegungsprogrammen hoch sind und gezielte
Maßnahmen zur Motivation und Implementierung geschaffen werden
müssen.Neben Maßnahmen der Verhaltensprävention wurden auch
verhältnispräventive Aspekte in einem ganzheitlichen Ansatz
berücksichtigt. So konnten durch Verwendung eines ergonomisch
modifizierten Schweißbrenners bei einer Schweißsimulation die
beanspruchte Muskulatur um bis zu 9% entlastet und die
Arbeitsqualität gesteigert werden.Insgesamt scheinen Maßnahmen der Verhaltensprävention wie ein
systematisches Training sowie der Verhältnisprävention im Sinne
der Arbeitsergonomie effektive Strategien in der Prävention und
Gesundheitsförderung bei Schweißern darzustellen.
Herausforderungen der stationären Versorgung von
Fragilitätsfrakturen während der Covid 19-Pandemie –
eine Übersicht
Authors: Schultz Katharina , Beyersdorf Christoph , Maus Uwe 
Published: February 2022

ZusammenfassungDie Covid-19-Pandemie hat in vielen Bereichen zwangsläufig zu einer
Veränderung der gewohnten Strukturen und Abläufe
geführt. Auch die Betreuung von Osteoporosepatienten ist davon betroffen
– von der Diagnostik bis zur Behandlung, im ambulanten und im
stationären Bereich. In einer Literaturrecherche widmeten wir uns der
Frage, inwieweit sich die stationäre Versorgung der
Osteoporose-Patienten diesbezüglich veränderte.
High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning
Authors: Quach Co D. , Gilmer Justin B. , Pert Daniel , Mason-Hogans Akanke , Iacovella Christopher R. , Cummings Peter T. , McCabe Clare 
Published: February 2022

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.
Where translation studies and the social meet
Authors: van Doorslaer Luc , McMartin Jack 
Published: February 2022

AbstractThis article outlines some main developments that have led to the recent emergence of research on the ‘sociology of translation.’ Such research adopts approaches from the broader social sciences, particularly sociology, but is also directly related to the so-called ‘cultural turn’ within translation studies. The scope of translation research has subsequently expanded to include cultural and power-related issues, creating common ground with the social sciences both in terms of how translation is conceptualized and the methods used to study it. Translation has come to be understood as a socially situated relation with difference, just as translation practitioners and researchers have been understood as complex, situated agents acting within and across the social spheres that condition cross-cultural, multilingual exchange. This orientation opens the way for new discoveries at the intersection of translation studies and the social sciences – workTranslation in Societyseeks to advance.
Marginal tubes and foliations by marginal surfaces
Authors: Le Pengyu 
Published: February 2022

Abstract
In this paper, we introduce the notion of a marginal tube, which is a hypersurface foliated by marginal surfaces. It generalises the notion of a marginally trapped tube and several notions of black hole horizons, for example trapping horizons, isolated horizons, dynamical horizons, etc. We prove that if every spacelike section of a marginal tube is a marginal surface, then the marginal tube is null. There is no assumption on the topology of the marginal tube. To prove it, we study the geometry of spacelike surfaces in a four-dimensional spacetime with the help of double null coordinate systems. The result is valid for arbitrary four-dimensional spacetimes, regardless of any energy condition.
A wearable exhaling-oxygen-sensing mask based on piezoelectric/gas-sensing coupling effect for real-time monitoring and uploading lung disease information
Authors: Lin Yuxing , Long Zhihe , Liang Shan , Zhong Tianyan , Xing Lili 
Published: February 2022

Abstract
Comprehensive analysis of respiratory gases may provide noninvasive health monitoring of lung diseases, such as corona virus 2019 pneumonia. Here, a self-powered wearable mask has been fabricated for real-time monitoring and uploading exhaling oxygen information. Tetrapod ZnO (T-ZnO) nanostructures are hybridized with polyvinylidene fluoride (PVDF) that adhere to flexible fabric substrate on a mask. The piezoelectric effect of T-ZnO/PVDF is coupled with the gas sensing properties. The sensing unit can convert breath energy into piezoelectric signal without any external power supply, and the outputting piezoelectric voltage increases with increasing oxygen concentration, acting as the sensing signal. The sensing unit integrated with data processing module and wireless Bluetooth module can transmit the exhaling oxygen information to the mobile device, realizing real-time monitoring the oxygenation capacity of the lungs. This self-powered wearable approach can promote the lung diagnosis outside of clinical settings.
Epitaxial (110)-oriented La0.7Sr0.3MnO3 film directly on flexible mica substrate
Authors: Ye Lianxu , Zhang Di , Lu Juanjuan , Xu Sicheng , Xu Ruixing , Fan Jiyu , Tang Rujun , Wang Haiyan , Guo Haizhong , Li Weiwei , Yang Hao 
Published: February 2022

Abstract
Manufacture and characterizations of perovskite-mica van der Waals epitaxy heterostructures are a critical step to realize the application of flexible devices. However, the fabrication and investigation of the van der Waals epitaxy architectures grown on mica substrates are mainly limited to (111)-oriented perovskite functional oxide thin films up to now and buffer layers are highly needed. In this work, we directly grew La0.7Sr0.3MnO3 (LSMO) thin films on mica substrates without using any buffer layer. By the characterizations of x-ray diffractometer and scanning transmission electron microscopy, we demonstrate the epitaxial growth of the (110)-oriented LSMO thin film on the mica substrate. The LSMO thin film grown on the mica substrate via van der Waals epitaxy adopts domain matching epitaxy instead of conventional lattice matching epitaxy. Two kinds of domain matching relationships between the LSMO thin film and mica substrate are sketched by Visualization for Electronic and STructural Analysis software and discussed. A decent ferromagnetism retains in the (110)-oriented LSMO thin film. Our work demonstrates a new pathway to fabricate (110)-oriented functional oxide thin films on flexible mica substrates directly.
Bearing fault diagnosis method based on a multi-head graph attention network
Authors: Jiang Li , Li Xingjie , Wu Lin , Li Yibing 
Published: February 2022

Abstract
The bearing is the core component of mechanical equipment, and attention has been paid to its health monitoring and fault diagnosis. Bearing fault diagnosis technology based on deep learning has been widely developed because of its powerful feature learning and fault classification ability. However, the traditional deep learning-based bearing fault diagnosis methods fail in mining the relationship between signals explicitly, which is beneficial to fault classification. Therefore, this paper proposes a new method based on a multi-head graph attention network (MHGAT) for bearing fault diagnosis. Firstly, it employs dynamic time warping to transform the original vibration signals into graph data with topological structure, so as to exploit the intrinsic structural information of the independent samples. Next, the graph data is input into the MHGAT, and the weights of neighbor nodes are learned automatically. Then, the MHGAT extracts the discriminative features from different scales and aggregates them into an enhanced, new feature representation of graph nodes through the multi-head attention mechanism. Finally, the enhanced, new features are fed into the SoftMax classifier for bearing fault diagnosis. The effectiveness of the proposed method is examined by two bearing datasets. The superiority of the proposed method is verified by comparison to traditional deep learning diagnosis models.
Dual-molecular targeted NIR II probe with enhanced response for head and neck squamous cell carcinoma imaging
Authors: Ma Yaqun , Wang Yanxing , Hui Xin , Lin Bi , Yuan Ying , Tao Xiaofeng , Lv Ruichan 
Published: February 2022

Abstract
In this research, a fluorescent probe of 7-(diethylamine) coumarin derivatives with multiple binding sites to detect biothiols in tumor cell with strong NIR II luminescence in vivo was synthesized. The biothiols include cysteine (Cys) and glutathione (GSH) in tumor cells, and the tumor-response luminescence was proved by the cell experiment. Importantly, the monolayer functional phospholipid (DSPE-PEG) coating and aggregation induced emission (AIE) dye of TPE modification made the probe have good stability and biocompatibility with little luminescence quenching in aqueous phase, which was proved by in vitro and in vivo experiments. The final aqueous NIR II probe combined with bevacizumab (for VEGF recognition in the cancer cells) and Capmatinib (for Met protein recognition in the cancer cells) has stronger targeted imaging on head and neck squamous cell carcinoma (HNSCC) cancer with intravenous injection. This GSH/Cys detection in the tumor cell and strong dual-molecular NIR II bioimaging in vivo may provide new strategy to tumor detection.
Characterization of plasma in RF jet interacting with water: Thomson scattering versus spectral line broadening
Authors: Yatom Shurik , Oldham Trey , Thimsen Elijah 
Published: February 2022

Abstract
In this work we carry out a detailed characterization of an Ar radiofrequency plasma jet interacting with liquid. The focus of the paper is measurement of the electron density by examining the Stark broadening of hydrogen Balmer α line and Thomson scattering (TS). Supporting diagnostics are done to investigate the channel evolution and movement, and gas temperature. The comparison of the two approaches shows the caveats and the advantages that should gain attention in future applications. In particular, the plasma channel dynamics have a significant impact on the TS signal and may result in physical phenomena being missed due to channel dislocations. The conclusions of the work elucidate the pitfalls for interpreting the results of TS when the discharge is a dynamic filamentary plasma. This work establishes the temporal evolution of the plasma and the gas parameters in a plasma–liquid system employed for investigation of plasma-induced electrodeless electrochemistry.
Normal zone propagation in various REBCO tape architectures
Authors: Lacroix Christian , Giguère Jaël , Bergeron Hartman Simon-Mathieu , Ben Saad Haïfa , Martin Anthony , Leduc Thomas , Gendron-Paul Maxime , Bellil Zakaria , Fournier-Lupien Jean-Hughes , Moret Lucile , Barusco Pedro , Granados Xavier , Obradors Xavier , Pekarčiková Marcela , Gömöry Fedor , Grosse Veit , Bauer Markus , Sirois Frédéric 
Published: February 2022

Abstract
The normal zone propagation velocity (NZPV) of three families of REBCO tape architectures designed for superconducting fault current limiters and to be used in high voltage direct current transmission systems has been measured experimentally in liquid nitrogen at atmospheric pressure. The measured NZPVs span more than three orders of magnitude depending on the tape architectures. Numerical simulations based on finite elements allow us to reproduce the experiments well. The dynamic current transfer length (CTL) extracted from the numerical simulations was found to be the dominating characteristic length determining the NZPV instead of the thermal diffusion length. We therefore propose a simple analytical model, whose key parameters are the dynamic CTL, the heat capacity and the resistive losses in the metallic layers, to calculate the NZPV.