bluuebunny/crossref_metadata_2025_split huggingface dataset:
Purkinje cells located in the adult zebrafish valvula cerebelli exhibit variable functional responses
Authors: Chang Weipang , Pedroni Andrea , Köster Reinhard W. , Giacomello Stefania , Ampatzis Konstantinos 
Published: September 2021

AbstractPurkinje cells are critically involved in processing the cerebellar functions by shaping and coordinating commands that they receive. Here, we demonstrate experimentally that in the adult zebrafish valvular part of the cerebellum, the Purkinje cells exhibited variable firing and functional responses and allowed the categorization into three firing classes. Compared with the Purkinje cells in the corpus cerebelli, the valvular Purkinje cells receive weak and occasional input from the inferior olive and are not active during locomotion. Together, our findings expand further the regional functional differences of the Purkinje cell population and expose their non-locomotor functionality.
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
Authors: Radha Mustafa , Fonseca Pedro , Moreau Arnaud , Ross Marco , Cerny Andreas , Anderer Peter , Long Xi , Aarts Ronald M. 
Published: September 2021

AbstractUnobtrusive home sleep monitoring using wrist-worn wearable photoplethysmography (PPG) could open the way for better sleep disorder screening and health monitoring. However, PPG is rarely included in large sleep studies with gold-standard sleep annotation from polysomnography. Therefore, training data-intensive state-of-the-art deep neural networks is challenging. In this work a deep recurrent neural network is first trained using a large sleep data set with electrocardiogram (ECG) data (292 participants, 584 recordings) to perform 4-class sleep stage classification (wake, rapid-eye-movement, N1/N2, and N3). A small part of its weights is adapted to a smaller, newer PPG data set (60 healthy participants, 101 recordings) through three variations of transfer learning. Best results (Cohen’s kappa of 0.65 ± 0.11, accuracy of 76.36 ± 7.57%) were achieved with the domain and decision combined transfer learning strategy, significantly outperforming the PPG-trained and ECG-trained baselines. This performance for PPG-based 4-class sleep stage classification is unprecedented in literature, bringing home sleep stage monitoring closer to clinical use. The work demonstrates the merit of transfer learning in developing reliable methods for new sensor technologies by reusing similar, older non-wearable data sets. Further study should evaluate our approach in patients with sleep disorders such as insomnia and sleep apnoea.
Explainable artificial intelligence based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience
Authors: Andreu-Perez Javier , Emberson Lauren L. , Kiani Mehrin , Filippetti Maria Laura , Hagras Hani , Rigato Silvia 
Published: September 2021

AbstractIn the last decades, non-invasive and portable neuroimaging techniques, such as functional near infrared spectroscopy (fNIRS), have allowed researchers to study the mechanisms underlying the functional cognitive development of the human brain, thus furthering the potential of Developmental Cognitive Neuroscience (DCN). However, the traditional paradigms used for the analysis of infant fNIRS data are still quite limited. Here, we introduce a multivariate pattern analysis for fNIRS data, xMVPA, that is powered by eXplainable Artificial Intelligence (XAI). The proposed approach is exemplified in a study that investigates visual and auditory processing in six-month-old infants. xMVPA not only identified patterns of cortical interactions, which confirmed the existent literature; in the form of conceptual linguistic representations, it also provided evidence for brain networks engaged in the processing of visual and auditory stimuli that were previously overlooked by other methods, while demonstrating similar statistical performance.
Nrf2 activation does not affect adenoma development in a mouse model of colorectal cancer
Authors: Knatko Elena V. , Castro Cecilia , Higgins Maureen , Zhang Ying , Honda Tadashi , Henderson Colin J. , Wolf C. Roland , Griffin Julian L. , Dinkova-Kostova Albena T. 
Published: September 2021

AbstractTranscription factor nuclear factor erythroid 2 p45-related factor 2 (Nrf2) and its main negative regulator, Kelch-like ECH associated protein 1 (Keap1), are at the interface between redox and intermediary metabolism. Nrf2 activation is protective in models of human disease and has benefits in clinical trials. Consequently, the Keap1/Nrf2 protein complex is a drug target. However, in cancer Nrf2 plays a dual role, raising concerns that Nrf2 activators may promote growth of early neoplasms. To address this concern, we examined the role of Nrf2 in development of colorectal adenomas by employing genetic, pharmacological, and metabolomic approaches. We found that colorectal adenomas that form in Gstp−/−: ApcMin/+ mice are characterized by altered one-carbon metabolism and that genetic activation, but not disruption of Nrf2, enhances these metabolic alterations. However, this enhancement is modest compared to the magnitude of metabolic differences between tumor and peri-tumoral tissues, suggesting that the metabolic changes conferred by Nrf2 activation may have little contribution to the early stages of carcinogenesis. Indeed, neither genetic (by Keap1 knockdown) nor pharmacological Nrf2 activation, nor its disruption, affected colorectal adenoma formation in this model. We conclude that pharmacological Nrf2 activation is unlikely to impact the early stages of development of colorectal cancer.
Electrochemical topological transformation of polysiloxanes
Authors: Oka Minami , Honda Satoshi 
Published: September 2021

AbstractCoupling reactions between polymers are an important class of chemical modifications for changing, enhancing, and tuning the properties of polymeric materials. In particular, transformation of polymer topologies based on efficient, facile and less wasted coupling reactions remains a significant challenge. Here, we report coupling reactions based on electrochemical oxidation of 2,4,5-triphenylimidazole into a 2,4,5-triphenylimidazolyl radical and its spontaneous dimerization into hexaarylbiimidazole. Based on this chemistry, electrochemical topological transformation (ETT) and electrochemical chain extension have been realized with siloxane-based oligomers and polymers. Moreover, this approach enables one step ETT of star-shaped poly(dimethyl siloxane)s (PDMSs) into network PDMSs, running in an ionic liquid solvent and requiring no purification steps.
Modulation of ocean acidification by decadal climate variability in the Gulf of Alaska
Authors: Hauri Claudine , Pagès Rémi , McDonnell Andrew M. P. , Stuecker Malte F. , Danielson Seth L. , Hedstrom Katherine , Irving Brita , Schultz Cristina , Doney Scott C. 
Published: September 2021

AbstractUptake of anthropogenic carbon dioxide from the atmosphere by the surface ocean is leading to global ocean acidification, but regional variations in ocean circulation and mixing can dampen or accelerate apparent acidification rates. Here we use a regional ocean model simulation for the years 1980 to 2013 and observational data to investigate how ocean fluctuations impact acidification rates in surface waters of the Gulf of Alaska. We find that large-scale atmospheric forcing influenced local winds and upwelling strength, which in turn affected ocean acidification rate. Specifically, variability in local wind stress curl depressed sea surface height in the subpolar gyre over decade-long intervals, which increased upwelling of nitrate- and dissolved inorganic carbon-rich waters and enhanced apparent ocean acidification rates. We define this sea surface height variability as the Northern Gulf of Alaska Oscillation and suggest that it can cause extreme acidification events that are detrimental to ecosystem health and fisheries.
A novel battery separator coated by a europium oxide/carbon nanocomposite enhances the performance of lithium sulfur batteries
Authors: Peng Lin , Yu Zhanjiang , Zhang Mingkun , Zhen Shunying , Shen Junhao , Chang Yu , Wang Yi , Deng Yuanfu , Li Aiju 
Published: September 2021

Eu2O3 with oxygen-vacancy defects and porous carbon skeleton could provide active sites for catalyzing polysulfide conversion and polysulfide trapping.
Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
Authors: Zhang Zhenkai , Lin Yunhang , Jin Biao 
Published: September 2021

AbstractIn order to achieve precise localization in the underwater environment, an underwater localization method based on hybrid invasive weed algorithm is proposed. First, considering the insufficient local search capability of the invasive weed algorithm, the salp swarm algorithm is used to pre‐process the initial population, the position and velocity update formulas are employed to further improve the search depth, and the hybrid invasive weed algorithm is obtained. Then, the localization error is designed as the objective function to obtain the initial value of the source, and a new localization model is built using the initial values and interference parameters. Finally, an improved two‐step weighted least square method is used to obtain the precise location of the source. The performance of the algorithm is also verified by comparisons with Cramer‐Rao Lower Bound. Simulation experiments show that the proposed algorithm has better localization accuracy than other classic methods.
Symmetric mean and directional contour pattern for texture classification
Authors: Dong Yongsheng , Zheng Boshi , Liu Hong , Zhang Zhiyong , Fu Zhumu 
Published: September 2021

AbstractIn this letter, we propose a simple yet effective texture descriptor, symmetric mean and directional contour pattern (SMDCP), for texture classification. In particular, first the robust symmetric mean pattern (RSMP) that extracts the sign and amplitude information of the local difference through the neighbourhood average in a new scheme of encoding to further enhance the robustness to noise is constructed. Then a local directional and contour pattern (LDCP) to represent the contour information and direction information of adjacent sampling points is extracted. By concatenating the RSMP and LDCP, a robust and effective texture descriptor (SMDCP) for classification is built. Experimental results reveal that the proposed method obtains significant performance and high discrimination in comparison with 10 representative approaches.
A novel DOA estimation method for uncorrelated and coherent signals via compressed sensing in sparse arrays
Authors: Han Peng , Xu Haiyun , Cui Weijia , Zhang Yankui , Ba Bin 
Published: September 2021

AbstractWhen there is the coexistence of uncorrelated and coherent signals in sparse arrays, the conventional algorithms using coarray are fail. In order to solve this problem, the letter proposes a novel method based on compressed sensing. Firstly, the authors vectorize the covariance matrix and establish a sparse representation model through constructing a two‐dimensional redundant dictionary. Then, the authors use an improved orthogonal matching pursuit algorithm for off‐grid sources to recover the sparse vector. Through analysing location of non‐zero elements in sparse vector, the direction‐of‐arrivals of both uncorrelated and coherent signals can be obtained. The proposed method has no strict limitation by the structure of the existing sparse arrays. Moreover, it makes full use of vectorized data and can estimate more number of signals than that of sensors. Numerical experiments prove the effectiveness and favourable performance of the proposed method.
One‐step synthesis of Cu/N co‐doped TiO2 nanocomposites with enhanced photocatalytic activities under visible‐light irradiation
Authors: Li Dayu , Liang Zhongyang , Zhang Wentao , Zhang Chao 
Published: September 2021

AbstractIn this research, a one‐step hydrothermal method is used to prepare Cu‐doped, N‐doped and Cu/N co‐doped titanium dioxide (TiO2) composites, and the doping effects on the structures, absorption and photocatalytic performance are investigated. All the products are in anatase structure. The substitution of Cu atoms in TiO2 and distribution of N in the crystal lattice have been identified by X‐ray diffraction, which lead to the decrease of grain size. Hollow micro‐nanospheres of Cu‐TiO2 samples, which make them have strong dark adsorption properties, can be observed. Cu/N co‐doped samples exhibit the maximum light absorption in the visible light region, and a red‐shift which is responsible for narrow band gap energy owing to the presence of N‐atoms and Cu‐atoms in the TiO2 lattice. The synergistic effect of Cu and N results in the enhanced photocatalytic activity for degradation of methyl orange under visible light irradiation.
A passive compensator for imbalances in current sharing of parallel‐siC MOSFETs based on planar transformer
Authors: Delzendeh Sarfejo Mahdi , Allahyari Hesamodin , Bahrami Hamid , Afifi Ahmad , Latif Zadeh Mohammad Ali , Yavari Ehya , Ghavidel Jalise Mahdi 
Published: September 2021

AbstractSiCMOSFETs are widely employed in power converters due to their high switching speed and low switching loss. However, their low current rating due to the limited active area restricts their high power applications. To apply SiC MOSFETs in high power applications, providing parallel connection is an inevitable choice. To tackle the challenge of imbalanced current sharing problem between parallel SiC MOSFETs, a new passive compensator based on planar transformer (PT) is proposed here. Compared with the conventional transformer compensators, parasitic elements are adjustable and predictable in PT compensators, which is especially important for mass production aims. After explaining the concept of the physical operation of the PT compensator, the whole parasitic elements of the PT compensator are formulated. Based on estimated parasitic elements and using the finite element method (FEM), an optimum PT structure is extracted for imbalances in current sharing of parallel SiC MOSFETs. Afterward, the PT design is discussed in detail and then, a boost converter is constructed. Finally, the experimental results are presented to verify the reliability, accuracy, and effectiveness of the theoretical results.
Radiopraxis
Authors: Forsting Michael 
Published: September 2021

Liebe Leserinnen und Leservor Ihnen liegt die dritte Ausgabe von Radiopraxis für das Jahr 2021. Sie
bekommen das Heft im September, ich schreibe das Editorial aber schon im Juli.
Gerade steigt die Zahl der Corona-Infektionen in Deutschland wieder an und ich
drücke uns allen die Daumen, dass die Impfungen verhindern
können, dass wieder viele Patientinnen und Patienten auf unseren
Intensivstationen versorgt werden müssen. Wenn meine Hoffnungen sich
erfüllen, können Sie dieses Heft wahrscheinlich in einer wieder
fast normalisierten Welt lesen.
A study of the effects of a thermally evaporated nanoscale CsBr layer on the optoelectronic properties and stability of formamidinium-rich perovskite solar cells
Authors: Koech Richard K. , Ichwani Reisya , Martin Julia L. , Oyewole Deborah O. , Oyelade Omolara V. , Olanrewaju Yusuf A. , Sanni Dahiru M. , Adeniji Sharafadeen A. , Grimm Ronald L. , Bello Abdulhakeem , Oyewole Oluwaseun K. , Ntsoenzok Esidor , Soboyejo Winston O. 
Published: September 2021

Incorporation of cesium (Cs) into the perovskite layer has become a good strategy to boost the stability and power conversion efficiency (PCE) of perovskite solar cells (PSCs). However, a suitable and scalable method of Cs incorporation in a perovskite film that does not cause a significant increase in the optical bandgap is needed. In this paper, we introduce a thin layer of CsBr into a formamidinium (FA)-rich mixed halide perovskite film using the thermal evaporation technique. The effects of the thickness of the CsBr layer on the microstructural, structural, and optoelectronic properties and surface chemical states of the perovskite film are then studied. The results indicate that the CsBr layer thickness is able to tune the microstructural and optoelectronic properties of the perovskite film. Planar PSCs fabricated with different thicknesses of CsBr layers in the perovskite absorber exhibited different photovoltaic performance characteristics. The CsBr-modified PSC device with a 50 nm layer of CsBr in the perovskite layer showed a better PCE of 16.19% ± 0.17%, which was about 15% higher than that of the control device, and was able to retain nearly 70% of its initial PCE value after 120 days of storage in an unencapsulated state.
Teaching English pronunciation in Croatian elementary
schools
Authors: Vančura Alma , Molnar Draženka 
Published: September 2021

Abstract
This chapter explores learners’ and teachers’
attitudes towards English pronunciation in elementary schools in
Croatia, as well as the relationship between pre-service education
and pronunciation teaching methods and techniques. The participants
included 152 learners and 31 teachers. The results show that
teachers feel inadequately trained, and that both teachers and
learners have positive attitudes towards pronunciation and believe
that language exposure greatly contributes to improving
pronunciation. Classroom practices include teaching word and
sentence stress, use of listen-and-repeat activities and teacher-led
corrective feedback. Some learners are motivated to improve their
pronunciation, while others wish to express their Croatian identity.
We consider the pedagogical implications of these findings and
propose recommendations that can make pronunciation teaching more
effective in this context.
Nonlinear power dependence of ferromagnetic resonance in NiFe/Pt/CoFeB trilayer
Authors: Yafuso Minoru , Miyazaki Keishi , Takayama Yusei , Obinata Sora , Kimura Takashi 
Published: September 2021

Abstract
The static and dynamic magnetization properties for a NiFe/Pt/CoFeB tri-layered film have been investigated. We find that the two ferromagnetic layers separated by a Pt spacer are ferromagnetically coupled even at room temperature. Moreover, the damping constant for the NiFe layer is found to show the significant enhancement with non-linear power dependence. These unique magnetic features observed in the NiFe layer can be understood by the weak ferromagnetism induced in the Pt spacer between two ferromagnetic layers.
Heat-content and diffusive leakage from material sets in the low-diffusivity limit
*
Authors: Schilling Nathanael , Karrasch Daniel , Junge Oliver 
Published: September 2021

Abstract
We generalize leading-order asymptotics of a form of the heat content of a submanifold (van den Berg & Gilkey 2015) to the setting of time-dependent diffusion processes in the limit of vanishing diffusivity. Such diffusion processes arise naturally when advection–diffusion processes are viewed in Lagrangian coordinates. We prove that as diffusivity ɛ goes to zero, the diffusive transport out of a material set S under the time-dependent, mass-preserving advection–diffusion equation with initial condition given by the characteristic function

1

S

, is

ε
/
π

d

A

¯

(

∂
S

)

+
o

(

ε

)

. The surface measure

d

A

¯

is that of the so-called geometry of mixing, as introduced in (Karrasch & Keller 2020). We apply our result to the characterisation of coherent structures in time-dependent dynamical systems.
Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control
Authors: Sakata Ayaka , Obuchi Tomoyuki 
Published: September 2021

Abstract
We consider a reconstruction problem of sparse signals from a smaller number of measurements than the dimension formulated as a minimization problem of nonconvex sparse penalties: smoothly clipped absolute deviations and minimax concave penalties. The nonconvexity of these penalties is controlled by nonconvexity parameters, and the ℓ
1 penalty is contained as a limit with respect to these parameters. The analytically-derived reconstruction limit overcomes that of the ℓ
1 limit and is also expected to overcome the algorithmic limit of the Bayes-optimal setting when the nonconvexity parameters have suitable values. However, for small nonconvexity parameters, where the reconstruction of the relatively dense signals is theoretically expected, the algorithm known as approximate message passing (AMP), which is closely related to the analysis, cannot achieve perfect reconstruction leading to a gap from the analysis. Using the theory of state evolution, it is clarified that this gap can be understood on the basis of the shrinkage in the basin of attraction to the perfect reconstruction and also the divergent behavior of AMP in some regions. A part of the gap is mitigated by controlling the shapes of nonconvex penalties to guide the AMP trajectory to the basin of the attraction.
Retraction: A New Approach for Testing Engagement Characteristics of Clutch (J. Phys.: Conf. Ser.
1885 022027)
Authors: Zou Xinyu , Wang Yang 
Published: September 2021

It has come to the attention of IOP Publishing that this article should not have reached publication because the paper contains a number of fundamental errors in the initial data, calculation, and conclusion which has led to the findings being unreliable. Consequently, this paper has been retracted by IOP Publishing. The authors agree to this retraction.
Retraction published: 15 September 2021
Monte Carlo Simulations of scintillation detectors for the use as dosemeters
Authors: Alegria N. , Kessler P. , Gabay K.-L. , Legarda F. , Neumaier S. , Röttger A. 
Published: September 2021

Abstract
The energy dependent conversion factors from measured photon
pulse height spectra to ambient dose equivalent (H*(10)) of three
different detectors based on the scintillation materials CeBr_3,
LaBr3 and SrI2 were simulated with the three Monte Carlo
Codes, GEANT4, MCNP and PENELOPE, respectively. The performance of
the detection systems, using the calculated conversion factors
(fitted to response functions), is demonstrated for different
scenarios ranging from laboratory conditions (i.e. a precisely
defined radiation field in a calibration facility) to a free-field
irradiation scenario produced by the natural radioactivity at a
large lawn. With very simple geometric models of the detector
systems, the response function of scintillation based dosemeters can
be derived from the aforementioned Monte Carlo simulations with an
accuracy of the measured doses in H*(10) of ±10% in an photon
energy range from 100 keV to 3000 keV, as being typical for
natural environmental gamma radiation.
Generation of megawatt soliton at 1680 nm in very large mode area antiresonant fiber and application to three-photon microscopy
Authors: Delahaye H , Hage C-H , Bardet S M , Tiliouine I , Granger G , Gaponov D , Lavoute L , Jossent M , Aleshkina S , Bubnov M , Salganskii M , Lipatov D , Guryanov A , Likhachev M , Louradour F , Février S 
Published: September 2021

Abstract
The spectral window around 1700 nm is interesting for in-depth multiphoton microscopy of intact tissues due to reduced scattering and absorption in this wavelength range. However, wide adoption of this excitation range will rely on the availability of robust and cost-effective high peak power pulsed lasers operating at these wavelengths. Here, we report on a fiber-based femtosecond laser providing up to 95 nJ, 85 fs pulses at 1800 nm. The laser system makes use of a fiber-based chirped pulse amplifier emitting at 1560 nm followed by an in-house fabricated very large mode area antiresonant fiber for soliton self-frequency shift. Megawatt-peak power pulses at the repetition rate of 1 MHz are available directly at the output of the flexible fiber. We illustrate the potential of the source for biological microscopy by recording three-photon-excited fluorescence images of mouse nervous tissue. The flexible fiber tailored to propagate megawatt solitons in the biologically relevant window around 1700 nm opens the way to deep brain imaging of freely moving animals via miniaturized endomicroscopes.