bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thin-film electronics on active substrates: review of materials, technologies and applications
Authors: Catania Federica , de Souza Oliveira Hugo , Lugoda Pasindu , Cantarella Giuseppe , Münzenrieder Niko 
Published: April 2022

Abstract
In the last years, the development of new materials as well as advanced fabrication techniques have enabled the transformation of electronics from bulky rigid structures into unobtrusive soft systems. This gave rise to new thin-film devices realized on previously incompatible and unconventional substrates, such as temperature-sensitive polymers, rough organic materials or fabrics. Consequently, it is now possible to realize thin-film structures on active substrates which provide additional functionality. Examples include stiffness gradients to match mechanical properties, mechanical actuation to realize smart grippers and soft robots, or microfluidic channels for lab-on-chip applications. Composite or microstructured substrates can be designed to have bespoke electrical, mechanical, biological and chemical features making the substrate an active part of a system. Here, the latest developments of smart structures carrying thin-film electronics are reviewed. Whereby the focus lies on soft and flexible systems, designed to fulfill tasks, not achievable by electronics or the substrate alone. After a brief introduction and definition of the requirements and topic areas, the materials for substrates and thin-film devices are covered with an emphasis on their intrinsic properties. Next, the technologies for electronics and substrates fabrication are summarized. Then, the desired properties and design strategies of various active substrate are discussed and benchmarked against the current state-of-the-art. Finally, available demonstrations, and use cases are presented. The review concludes by mapping the available technologies to innovative applications, identifying promising underdeveloped fields of research and potential future progress.
Implicit neural representation for radiation therapy dose distribution
Authors: Vasudevan Varun , Shen Liyue , Huang Charles , Chuang Cynthia , Islam Md Tauhidul , Ren Hongyi , Yang Yong , Dong Peng , Xing Lei 
Published: April 2022

Abstract

Objective. Dose distribution data plays a pivotal role in radiotherapy treatment planning. The data is typically represented using voxel grids, and its size ranges from 106 to 108. A concise representation of the treatment plan is of great value in facilitating treatment planning and downstream applications. This work aims to develop an implicit neural representation of 3D dose distribution data. Approach. Instead of storing the dose values at each voxel, in the proposed approach, the weights of a multilayer perceptron (MLP) are employed to characterize the dosimetric data for plan representation and subsequent applications. We train a coordinate-based MLP with sinusoidal activations to map the voxel spatial coordinates to the corresponding dose values. We identify the best architecture for a given parameter budget and use that to train a model for each patient. The trained MLP is evaluated at each voxel location to reconstruct the dose distribution. We perform extensive experiments on dose distributions of prostate, spine, and head and neck tumor cases to evaluate the quality of the proposed representation. We also study the change in representation quality by varying model size and activation function. Main results. Using coordinate-based MLPs with sinusoidal activations, we can learn implicit representations that achieve a mean-squared error of 10−6 and peak signal-to-noise ratio greater than 50 dB at a target bitrate of ∼1 across all the datasets, with a compression ratio of ∼32. Our results also show that model sizes with a bitrate of 1–2 achieve optimal accuracy. For smaller bitrates, performance starts to drop significantly. Significance. The proposed model provides a low-dimensional, implicit, and continuous representation of 3D dose data. In summary, given a dose distribution, we systematically show how to find a compact model to fit the data accurately. This study lays the groundwork for future applications of neural representations of dose data in radiation oncology.
Analog synaptic devices applied to spiking neural networks for reinforcement learning applications
Authors: Kim Jangsaeng , Lee Soochang , Kim Chul-Heung , Park Byung-Gook , Lee Jong-Ho 
Published: April 2022

Abstract
In this work, we implement hardware-based spiking neural network (SNN) using the thin-film transistor (TFT)-type flash synaptic devices. A hardware-based SNN architecture with synapse arrays and integrate-and-fire (I&F) neuron circuits is presented for executing reinforcement learning (RL). Two problems were used to evaluate the applicability of the proposed hardware-based SNNs to off-chip RL: the Cart Pole balancing problem and the Rush Hour problem. The neural network was trained using a deep Q-learning algorithm. The proposed hardware-based SNNs using the synapse model with measured characteristics successfully solve the two problems and show high performance, implying that the networks are suitable for executing RL. Furthermore, the effect of variations in non-ideal synaptic devices and neurons on the performance was investigated.
Facile fabrication and enhanced photoresponse of CuO/β-Ga2O3 nanostructure photodetector
Authors: Du Shiyu , Yu Naisen , Wu Yunfeng , Lin Xiang , Liu Benkang , Li Haiou 
Published: April 2022

Abstract
CuO/β-Ga2O3 hybrid structures with β-Ga2O3 nanorods coated with CuO nanoparticle layers were successfully synthesized by a multi-cycle dipping and annealing process method. Compared with bare β-Ga2O3 nanorods, the CuO/β-Ga2O3 hybrid structures had greatly enhanced and dramatically broadened responses to light in the range from the near-ultraviolet to visible light. This novel synthetic pathway will provide new possibilities to prepare nanomaterials that integrate oxide heterojunctions for photodetection applications.
A nonlinear optimization method for large shape morphing in 3D printed pneumatic lattice structures
Authors: du Pasquier Cosima , Shea Kristina 
Published: April 2022

Abstract
Shape morphing has been increasingly investigated as a solution to increase the functionality and efficiency of structures. The main criteria to assess the quality of a shape morphing structure in this paper are: accuracy of deformation and range and number of achievable target shapes. The lightweight lattice structures used in this work inherently address the first criteria. The focus of this work is to address accuracy and range by developing a nonlinear optimization method that can handle large shape changes and a variety of target shapes for 2D and 3D overdeterminate lattice structures. The accuracy and deformation range of the method are verified numerically using finite element analysis and experimentally through a modular, 3D printed pneumatic lattice toolkit. The method is shown to replicate desired target shapes with a minimum accuracy of 80.4% for case studies in 2D and 69.1% in 3D. The simulation and the experimental results replicate results from the actuator placement optimization with a minimum accuracy of 92.3% and 76.2% respectively in 2D, and 88.2% and 69.6% in 3D. The impact of varying the size and degree of static overdeterminacy of a structure on its deformation range is evaluated. The proposed optimization method provides designers with more design freedom in terms of the structure type, target shape, and deformation range than shown in similar publications.
Spectral interaction between universes
Authors: Bochniak A. , Sitarz A. 
Published: April 2022

Abstract
We derive a perturbative formula for the direct interaction between two four-dimensional geometries. Based on the spectral action principle we give an explicit potential up to the third order perturbation around the flat vacua. We
present the leading terms of the interaction as polynomials of the invariants of the two metrics and compare the expansion
to the models of bimetric gravity.
Alfvén waves in reversed-field pinch and tokamak ohmic plasmas: nonlinear 3D MHD modeling and comparison with RFX-mod
Authors: Kryzhanovskyy A. , Bonfiglio D. , Cappello S. , Veranda M. , Zuin M. 
Published: April 2022

Abstract
The properties and possible triggering mechanisms of Alfvén waves in the reversed-field pinch (RFP) and circular tokamak configurations are discussed in the framework of nonlinear 3D magnetohydrodynamics (MHD) modeling. Numerical simulations are performed with the SpeCyl code (Cappello and Biskamp 1996 Nucl. Fusion) that solves the equations of the viscoresistive MHD model in cylindrical geometry. Configurations with increasing levels of complexity are analyzed. First, single-wave numerical solutions are compared with analytical ones in the simplest case of a uniform axial magnetic field: an excellent agreement is obtained for both the shear Alfvén wave (SAW) and the compressional Alfvén eigenmodes (CAEs). Then, tokamak and RFP configurations are studied. Phenomena such as phase mixing of SAW, resonant absorption of CAEs and the appearance of the global Alfvén eigenmode are described. Finally, the fully 3D RFP case with typical sawtoothing activity is investigated, showing for the first time in nonlinear RFP simulations the excitation of Alfvén waves by magnetic reconnection events. The modeling results appear to be consistent with the experimental characterization of Alfvénic activity observed in RFX-mod.
Preparation and properties of room-temperature-vulcanized silicone rubber using modified dopamine as a crosslinking agent
Authors: Wang Xiangyu , Zhou Jing , Meng Rui , Zhao Yu , Guo Weihong 
Published: April 2022

Abstract
This paper investigates the modification of dopamine (IDA) and uses it as a crosslinking agent to enhance the mechanical strength and hydrophobicity of room-temperature-vulcanized (RTV) silicone rubber. IDA was successfully synthesized with dopamine and 3-isocyanatopropyltriethoxysilane. The structure of IDA was verified by Fourier transform infrared spectroscopy and 1H nuclear magnetic resonance spectroscopy. IDA was introduced into the hydroxyl-terminated polydimethylsiloxane (PDMS) system to prepare RTV silicone rubber, and dibutyltin dilaurate (DBTDL) was used as the catalyst. A combination of the scanning electron microscope, thermal gravimetric analysis, universal testing machine, and contact angle was used to analyze the morphology and properties of RTV silicone rubber. The results demonstrated that the addition of IDA significantly enhanced the thermal stability and mechanical strength of RTV silicone rubber. The mechanical strength of the novel RTV silicone rubber increased by 221%. Moreover, the IDA modified RTV silicone rubber had better hydrophobicity as compared to the PDMS polymer prepared with the traditional crosslinking agent.
Study on static softening behavior and hot working performance of Fe-0.2C-7Mn steel
Authors: Wang Yang , Wang Weijun , Cen Qiongying , Zhang Mei 
Published: April 2022

Abstract
Static softening behavior and hot working performance of medium Mn steel (Fe-0.2C-7Mn) are studied by 2-step and interrupt hot compression test with a Gleeble-3500 thermal-mechanical simulator. The results show that static softening behavior of the steel exhibits obvious sensitivity to the deformation temperature, inter-pass time and strain rate. But deformation temperature has a more significant effect on the static recrystallization (SRX) grain size than strain rate. 3D hot working processing maps are established, that low temperature and medium strain rate (850 °C ∼ 925 °C and 0.02 s−1 ∼ 0.3 s−1) are the preferred thermal deformation conditions for the test steel. Microstructure observations indicate that both static recovery (SRV) and SRX occur within inter-pass time, and SRV is the predominant mechanism in determining softening fraction. The microstructure is composed of film-like α at room temperature, and most of the nucleation of SRX preferably take place at triple junctions of grains or prior grain boundaries. Besides, high-angle grain boundaries (HAGBs) migration produce twin boundaries during grain growth and the main nucleation mechanism of the SRX is strain-induced boundary migration. The kinetics model of static softening is established and the experimental values are consistent with predicted ones, which proves the reliability of the model.
Spin pumping from antiferromagnetic insulator spin-orbit-proximitized by adjacent heavy metal: a first-principles Floquet-nonequilibrium Green function study
Authors: Dolui Kapildeb , Suresh Abhin , Nikolić Branislav K 
Published: April 2022

Abstract
Motivated by the recent experiment (Vaidya et al 2020 Science
368 160) on spin pumping from sub-THz radiation-driven uniaxial antiferromagnetic insulator (AFI) MnF2 into heavy metal (HM) Pt hosting strong spin-orbit (SO) coupling, we compute and compare pumped spin currents in Cu/MnF2/Cu and Pt/MnF2/Cu heterostructures. Recent theories of spin pumping by AFI have relied on simplistic Hamiltonians (such as tight-binding) and the scattering approach to quantum transport yielding the so-called interfacial spin mixing conductance (SMC), but the concept of SMC ceases to be applicable when SO coupling is present directly at the interface. In contrast, we use a more general first-principles quantum transport approach which combines noncollinear density functional theory with Floquet-nonequilibrium Green’s functions in order to take into account: SO-proximitized AFI as a new type of quantum material, different from isolated AFI and brought about by AFI hybridization with adjacent HM layer; strong SO coupling at the interface; and evanescent wavefunctions penetrating from Pt or Cu into AFI layer to make its interfacial region conducting rather than insulating as in the isolated AFI. The DC component of pumped spin current

I

D
C

S
z

vs. precession cone angle

θ

l

of the Néel vector
l
of AFI does not follow putative

I

DC

S
z

∝

sin

2

θ

l

, except for very small angles

θ

l

≲

10

°

for which we define an effective SMC from the prefactor and find that it doubles from MnF2/Cu to MnF2/Pt interface. In addition, the angular dependence

I

D
C

S
z

(

θ

l

)

differs for opposite directions of precession of the Néel vector, leading to twice as large SMC for the right-handed than for the left-handed chirality of the precession mode.
Development of Partial Tolerance to the Suppressing Effect of the Positive Allosteric Modulator of the GABAB Receptor, KK-92A, on Alcohol Self-Administration in Rats
Authors: Maccioni Paola , Kaczanowska Katarzyna , McDonald Patricia , Colombo Giancarlo 
Published: April 2022

Abstract

Aims
A recent study reported how acute treatment with KK-92A, a newly synthesized positive allosteric modulator (PAMs) of the GABAB receptor (GABAB PAMs), suppressed a series of alcohol-related behaviors, including operant oral alcohol self-administration, in selectively bred Sardinian alcohol-preferring (sP) rats. These findings lead to the addition of KK-92A to the long list of GABAB PAMs capable of reducing, after acute treatment, alcohol self-administration in rats. As a further step toward a more complete characterization of the anti-addictive properties of KK-92A, the present study was designed to assess the effect of repeated treatment with the compound on alcohol self-administration.

Methods
sP rats were trained to lever-respond for oral alcohol (15%, v/v) under the fixed ratio 5 (FR5) schedule of reinforcement. Once lever-responding behavior had stabilized, KK-92A (0, 5, 10 and 20 mg/kg, i.p.) was administered 30 min prior to 10 consecutive daily self-administration sessions (likewise occurring under the FR5 schedule).

Results
The first injection of KK-92A produced a dose-related suppression in number of lever-responses for alcohol and amount of self-administered alcohol. Magnitude of the suppressing effect of KK-92A decreased over the following two self-administration sessions and then tended to stabilize on continuation of treatment. Statistical significance at post hoc analysis was maintained only by the highest dose tested (20 mg/kg).

Conclusions
These data suggest the development of partial tolerance to the reducing effect of repeatedly administered KK-92A on alcohol self-administration. The agonistic component of the ago-allosteric profile of KK-92A is discussed as the likely key element underlying the observed tolerance.
Characterization of Exposure to Cleaning Agents Among Health Workers in Two Southern African Tertiary Hospitals
Authors: Mwanga H H , Baatjies R , Jeebhay M F 
Published: April 2022

AbstractBackgroundWhilst cleaning agents are commonly used in workplaces and homes, health workers (HWs) are at increased risk of exposure to significantly higher concentrations used to prevent healthcare-associated infections. Exposure assessment has been challenging partly because many are used simultaneously resulting in complex airborne exposures with various chemicals requiring different sampling techniques. The main objective of this study was to characterize exposures of HWs to various cleaning agents in two tertiary academic hospitals in Southern Africa.MethodsA cross-sectional study of HWs was conducted in two tertiary hospitals in South Africa (SAH) and Tanzania (TAH). Exposure assessment involved systematic workplace observations, interviews with key personnel, passive personal environmental sampling for aldehydes (ortho-phthalaldehyde—OPA, glutaraldehyde and formaldehyde), and biomonitoring for chlorhexidine.ResultsOverall, 269 samples were collected from SAH, with 62 (23%) collected from HWs that used OPA on the day of monitoring. OPA was detectable in 6 (2%) of all samples analysed, all of which were collected in the gastrointestinal unit of the SAH. Overall, department, job title, individual HW use of OPA and duration of OPA use were the important predictors of OPA exposure. Formaldehyde was detectable in 103 (38%) samples (GM = 0.0025 ppm; range: &lt;0.0030 to 0.0270). Formaldehyde levels were below the ACGIH TLV-TWA (0.1 ppm). While individual HW use and duration of formaldehyde use were not associated with formaldehyde exposure, working in an ear, nose, and throat ward was positively associated with detectable exposures (P-value = 0.002). Glutaraldehyde was not detected in samples from the SAH. In the preliminary sampling conducted in the TAH, glutaraldehyde was detectable in 8 (73%) of the 11 samples collected (GM = 0.003 ppm; range: &lt;0.002 to 0.028). Glutaraldehyde levels were lower than the ACGIH’s TLV-Ceiling Limit of 0.05 ppm. p-chloroaniline was detectable in 13 (4%) of the 336 urine samples (GM = 0.02 ng/ml range: &lt;1.00 to 25.80).ConclusionThe study concluded that detectable exposures to OPA were isolated to certain departments and were dependent on the dedicated use of OPA by the HW being monitored. In contrast, low-level formaldehyde exposures were present throughout the hospital. There is a need for more sensitive exposure assessment techniques for chlorhexidine given its widespread use in the health sector.
kmtricks: efficient and flexible construction of Bloom filters for large sequencing data collections
Authors: Lemane Téo , Medvedev Paul , Chikhi Rayan , Peterlongo Pierre 
Published: April 2022

Abstract

Summary
When indexing large collections of short-read sequencing data, a common operation that has now been implemented in several tools (Sequence Bloom Trees and variants, BIGSI) is to construct a collection of Bloom filters, one per sample. Each Bloom filter is used to represent a set of k-mers which approximates the desired set of all the non-erroneous k-mers present in the sample. However, this approximation is imperfect, especially in the case of metagenomics data. Erroneous but abundant k-mers are wrongly included, and non-erroneous but low-abundant ones are wrongly discarded. We propose kmtricks, a novel approach for generating Bloom filters from terabase-sized collections of sequencing data. Our main contributions are (i) an efficient method for jointly counting k-mers across multiple samples, including a streamlined Bloom filter construction by directly counting, partitioning and sorting hashes instead of k-mers, which is approximately four times faster than state-of-the-art tools; (ii) a novel technique that takes advantage of joint counting to preserve low-abundant k-mers present in several samples, improving the recovery of non-erroneous k-mers. Our experiments highlight that this technique preserves around 8× more k-mers than the usual yet crude filtering of low-abundance k-mers in a large metagenomics dataset.

Availability and implementation
https://github.com/tlemane/kmtricks.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
Brain connectivity modulation by Bayesian surprise in relation to control demand drives cognitive flexibility via control engagement
Authors: Qiao Lei , Zhang Lijie , Chen Antao 
Published: April 2022

AbstractHuman control is characterized by its flexibility and adaptability in response to the conditional probability in the environment. Previous studies have revealed that efficient conflict control could be attained by predicting and adapting to the changing control demand. However, it is unclear whether cognitive flexibility could also be gained by predicting and adapting to the changing control demand. The present study aimed to explore this issue by combining the model-based analyses of behavioral and neuroimaging data with a probabilistic cued task switching paradigm. We demonstrated that the Bayesian surprise (i.e. unsigned precision-weighted prediction error [PE]) negatively modulated the connections among stimulus processing brain regions and control regions/networks. The effect of Bayesian surprise modulation on these connections guided control engagement as reflected by the control PE effect on behavior, which in turn facilitated cognitive flexibility. These results bridge a gap in the literature by illustrating the neural and behavioral effect of control demand prediction (or PE) on cognitive flexibility and offer novel insights into the source of switch cost and the mechanism of cognitive flexibility.
Green spotted puffers detect a nontoxic TTX analog odor using crypt olfactory sensory neurons
Authors: Suzuki Takehisa , Nakahigashi Ryota , Adachi Masaatsu , Nishikawa Toshio , Abe Hideki 
Published: April 2022

Abstract
Toxic puffers accumulate their defense substance (tetrodotoxin; TTX) through the food chain. Although the previous study suggests that 5,6,11-trideoxyTTX, a nontoxic TTX analog detected simultaneously with TTX in toxic puffers or their prey, acts as an olfactory chemoattractant for grass puffers, it is unclear whether toxic puffers are commonly attracted to 5,6,11-trideoxyTTX, and which types of olfactory sensory neurons (OSNs) detect 5,6,11-trideoxyTTX. Here, we demonstrated that green spotted puffer, a phylogenetically distant species from the grass puffer, is attracted to 5,6,11-trideoxyTTX. 5,6,11-TrideoxyTTX administration made green spotted puffers stay longer at the administered site, whereas a food odor (l-Arg) made them actively swim throughout the aquarium. Attractive responses were not observed when TTX or its vehicle was administered, nor when 5,6,11-trideoxyTTX was administered to anosmic fish. Furthermore, double immunohistochemistry with activity marker and crypt OSN marker antibodies labeled oval cells with apical invagination on the olfactory epithelium surface treated with 5,6,11-trideoxyTTX. These results suggest that 5,6,11-trideoxyTTX acts as an olfactory chemoattractant detected by crypt OSNs, and attraction to 5,6,11-trideoxyTTX odor appears to be a trait shared by toxic puffers for social communication or effective toxification.