bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spata7 is required for maintenance of the retinal connecting cilium
Authors: Lu Jiaxiong , Xiong Kaitlyn , Qian Xinye , Choi Jongsu , Shim Yoon-Kyung , Burnett Jacob , Mardon Graeme , Chen Rui 
Published: April 2022

AbstractSPATA7, an early onset LCA3 retinal disease gene, encodes a putative scaffold protein that is essential for the proper assembly of the connecting cilium (CC) complex in photoreceptors. Previous studies have shown that SPATA7 interacts with other photoreceptor-specific ciliary proteins, such as RPGR and RPGRIP1, and maintains the integrity of CC integrity. However, although it is known that Spata7 is required for early formation of the CC, it is unclear if Spata7 is also required for the maintenance of the CC. To investigate Spata7 function in the retina at the adult stage, loss of function was induced in the adult retina upon tamoxifen induction of an inducible Spata7 knockout allele (Spata7flox/−; UbcCreERT2/+). The phenotype of mutant retina was characterized by a combination of histology, immunobiochemistry, and electroretinography (ERG). Our results demonstrated that Spata7 is also essential for maintaining the integrity of the mature retinal CC. Loss of Spata7 in adults caused phenotypes similar to those seen in germline mutant mice, including photoreceptor cell degeneration and defective ERG responses. Close examination of the CC revealed significantly shortened NPHP1 length as a result of Spata7 deletion. Furthermore, mislocalization of rhodopsin, leading to ER stress-mediated apoptosis, was observed in the retinal layers. Our results indicate that Spata7 is required not only for the establishment but also for the maintenance of the CC of photoreceptors.
Detection of volatile organic compounds using mid-infrared silicon nitride waveguide sensors
Authors: Zhou Junchao , Al Husseini Diana , Li Junyan , Lin Zhihai , Sukhishvili Svetlana , Coté Gerard L. , Gutierrez-Osuna Ricardo , Lin Pao Tai 
Published: April 2022

AbstractMid-infrared (mid-IR) sensors consisting of silicon nitride (SiN) waveguides were designed and tested to detect volatile organic compounds (VOCs). SiN thin films, prepared by low-pressure chemical vapor deposition (LPCVD), have a broad mid-IR transparent region and a lower refractive index (nSiN = 2.0) than conventional materials such as Si (nSi = 3.4), which leads to a stronger evanescent wave and therefore higher sensitivity, as confirmed by a finite-difference eigenmode (FDE) calculation. Further, in-situ monitoring of three VOCs (acetone, ethanol, and isoprene) was experimentally demonstrated through characteristic absorption measurements at wavelengths λ = 3.0–3.6 μm. The SiN waveguide showed a five-fold sensitivity improvement over the Si waveguide due to its stronger evanescent field. To our knowledge, this is the first time SiN waveguides are used to perform on-chip mid-IR spectral measurements for VOC detection. Thus, the developed waveguide sensor has the potential to be used as a compact device module capable of monitoring multiple gaseous analytes for health, agricultural and environmental applications.
DD‐YOLO: An object detection method combining knowledge distillation and Differentiable Architecture Search
Authors: Xing Zhiqiang , Chen Xi , Pang Fengqian 
Published: April 2022

AbstractAlthough YOLOv4 has a high detection accuracy, its backbone network CSPDarknet53 requires a large number of parameters, which reduces the inference speed of the detection network to some extent. To address this drawback, a high‐efficiency detection network search strategy is proposed. First, the concept of Differentiable Architecture Search (DARTS) is used to search networks with a small number of parameters on the COCO2017 datasets; then, the backbone of YOLOv4 is redesigned by stacking cells. This strategy can reduce the number of parameters of the network. Second, the authors use ResNet101 as the teacher network and DD‐YOLO searched by DARTS as the student network to refine the knowledge model and improve the detection accuracy of the model. The proposed model is evaluated by conducting experiments on the COCO2017 test‐dev datasets. The results show that DD‐YOLO achieves 43.5% mean average precision and 2.3% model accuracy improvement. Meanwhile, the model complexity can be reduced to 61.4% of the original. Moreover, compared with YOLOv4, DD‐YOLO is more suitable for mobile deployment.
Power laws prevail in medical ultrasound
Authors: Parker K J 
Published: April 2022

Abstract
Major topics in medical ultrasound rest on the physics of wave propagation through tissue. These include fundamental treatments of backscatter, speed of sound, attenuation, and speckle formation. Each topic has developed its own rich history, lexicography, and particular treatments. However, there is ample evidence to suggest that power law relations are operating at a fundamental level in all the basic phenomena related to medical ultrasound. This review paper develops, from literature over the past 60 years, the accumulating theoretical basis and experimental evidence that point to power law behaviors underlying the most important tissue-wave interactions in ultrasound and in shear waves which are now employed in elastography. The common framework of power laws can be useful as a coherent overview of topics, and as a means for improved tissue characterization.
Evolution of the bulk electric field in capacitively coupled argon plasmas at intermediate pressures
Authors: Vass Máté , Wilczek Sebastian , Derzsi Aranka , Horváth Benedek , Hartmann Peter , Donkó Zoltán 
Published: April 2022

Abstract
The physical characteristics of an argon discharge excited by a single-frequency harmonic waveform in the low-intermediate pressure regime (5–250 Pa) are investigated using particle-in-cell/Monte Carlo collisions simulations. It is found that, when the pressure is increased, a non-negligible bulk electric field develops due to the presence of a ‘passive bulk’, where a plateau of constant electron density forms. As the pressure is increased, the ionization in the bulk region decreases (due to the shrinking of the energy relaxation length of electrons accelerated within the sheaths and at the sheath edges), while the excitation rate increases (due to the increase of the bulk electric field). Using the Fourier spectrum of the discharge current, the phase shift between the current and the driving voltage waveform is calculated, which shows that the plasma gets more resistive in this regime. The phase shift and the (wavelength-integrated) intensity of the optical emission from the plasma are also obtained experimentally. The good qualitative agreement of these data with the computed characteristics verifies the simulation model. Using the Boltzmann term analysis method, we find that the bulk electric field is an Ohmic field and that the peculiar shape of the plasma density profile is partially a consequence of the spatio-temporal distribution of the ambipolar electric field.
Retracted: Titanium doping effect on the sensing performance of ZnO nanosheets toward phosgene gas
Authors: Menazea A A , Awwad Nasser S , Ibrahium Hala A , Alharbi Khadijah H , Alqahtani Mohammed S 
Published: April 2022

Abstract
The density functional B3LYP was utilized for scrutinizing the effect of Ti-doping on the sensing performance of a ZnO nano-sheet (ZnONS) in detecting phosgene. Pure ZnONS had a weak interaction with phosgene, and the sensing response (SR) was approximately 9.4. There was an increase in the energy of adsorption (Ead) for phosgene from −5.5 to −22.8 kcal mol−1 after the doping of a Ti atom onto the surface of ZnONS. Following the doping of Ti, there was also a dramatic increase in the SR to 84.2. The recovery time (RT) for the desorption of phosgene from the ZnONS that was doped with Ti was 16.4 s. This suggested that Ti-doped ZnONS might be used as a phosgene sensor with a high sensitivity and a shorter RT.
Beyond-mean-field study of

Ar based on the Skyrme-Hartree-Fock model *
Authors: Cui Ji-Wei , Wang Ruizhe , Zhou Xian-Rong 
Published: April 2022

Abstract
We present the hypernuclear states of

Ar obtained using the Skyrme-Hartree-Fock (SHF) model and a beyond-mean-field approach, including angular momentum projection (AMP) and the generator coordinate method (GCM). A comprehensive energy spectrum is given, which includes normally deformed (ND) and super deformed (SD) hypernuclear states with positive or negative parities. Energy levels corresponding to the configurations in which a

hyperon occupies the s-, p-, or sd-shell orbitals are discussed. For the s-shell

, we pay special attention to the ND and SD states corresponding to the configurations

Ar

s

and

Ar

s

, where

Ar

and

Ar

denote the ND and SD nuclear cores, respectively. The disagreements between different models over the

separation energy of the SD state in previous studies are revisited. For the p-shell

, four rotational bands are predicted, and the impurity effects are shown. Furthermore, two energy levels corresponding to the configurations

Ar

[101]

and

Ar

[101]

are obtained below the separation threshold of

Ar+

within 0.5 MeV. For the sd-shell

, three bound states are found near the separation threshold, and the mechanism behind these states are discussed.
Estimating muscle activation from EMG using deep learning-based dynamical systems models
Authors: Wimalasena Lahiru N , Braun Jonas F , Keshtkaran Mohammad Reza , Hofmann David , Gallego Juan Álvaro , Alessandro Cristiano , Tresch Matthew C , Miller Lee E , Pandarinath Chethan 
Published: April 2022

Abstract

Objective. To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One approach is to try extracting the underlying neural command signal to muscles by applying latent variable modeling methods to electromyographic (EMG) recordings. However, estimating the latent command signal that underlies muscle activation is challenging due to its complex relation with recorded EMG signals. Common approaches estimate each muscle’s activation independently or require manual tuning of model hyperparameters to preserve behaviorally-relevant features. Approach. Here, we adapted AutoLFADS, a large-scale, unsupervised deep learning approach originally designed to de-noise cortical spiking data, to estimate muscle activation from multi-muscle EMG signals. AutoLFADS uses recurrent neural networks to model the spatial and temporal regularities that underlie multi-muscle activation. Main results. We first tested AutoLFADS on muscle activity from the rat hindlimb during locomotion and found that it dynamically adjusts its frequency response characteristics across different phases of behavior. The model produced single-trial estimates of muscle activation that improved prediction of joint kinematics as compared to low-pass or Bayesian filtering. We also applied AutoLFADS to monkey forearm muscle activity recorded during an isometric wrist force task. AutoLFADS uncovered previously uncharacterized high-frequency oscillations in the EMG that enhanced the correlation with measured force. The AutoLFADS-inferred estimates of muscle activation were also more closely correlated with simultaneously-recorded motor cortical activity than were other tested approaches. Significance. This method leverages dynamical systems modeling and artificial neural networks to provide estimates of muscle activation for multiple muscles. Ultimately, the approach can be used for further studies of multi-muscle coordination and its control by upstream brain areas, and for improving brain-machine interfaces that rely on myoelectric control signals.
An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions
Authors: Bigoni Claudia , Cadic-Melchior Andéol , Vassiliadis Pierre , Morishita Takuya , Hummel Friedhelm C 
Published: April 2022

AbstractBackground.Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection are still missing.Objective.We present a novel open-source algorithm suitable for MEP onset/latency detection during resting state that only requires the post-stimulus electromyography signal and exploits the approximation of the first derivative of this signal to find the time point of initial deflection of the MEP.Approach.The algorithm has been benchmarked, using intra-class coefficient (ICC) and effect sizes, to manual detection of latencies done by three researchers independently on a dataset comprising almost 6500 MEP trials from healthy participants (n= 18) and stroke patients (n= 31) acquired during rest. The performance was further compared to currently available automatized methods, some of which created for active contraction protocols. Mainresults.The unstandardized effect size between the human raters and the present method is smaller than the sampling period for both healthy and pathological MEPs. Moreover, the ICC increases when the algorithm is added as a rater.Significance.The present algorithm is comparable to human expert decision and outperforms currently available methods. It provides a promising method for automated MEP latency detection under physiological and pathophysiological conditions.
Force scaling and efficiency of elongated median fin propulsion
Authors: Uddin Mohammad I , Garcia Gonzalo A , Curet Oscar M 
Published: April 2022

Abstract
Several fishes swim by undulating a thin and elongated median fin while the body is mostly kept straight, allowing them to perform forward and directional maneuvers. We used a robotic vessel with similar fin propulsion to determine the thrust scaling and efficiency. Using precise force and swimming kinematics measurements with the robotic vessel, the thrust generated by the undulating fin was found to scale with the square of the relative velocity between the free streaming flow and the wave speed. A hydrodynamic efficiency is presented based on propulsive force measurements and modelling of the power required to oscillate the fin laterally. It was found that the propulsive efficiency has a broadly high performance versus swimming speed, with a maximum efficiency of 75%. An expression to calculate the swimming speed over wave speed was found to depend on two parameters: A
p/A
e (ratio between body frontal area to fin swept area) and C
D/C

x
(ratio of body drag to fin thrust coefficient). The models used to calculate propulsive force and free-swimming speed were compared with experimental results. The broader impacts of these results are discussed in relation to morphology and the function of undulating fin swimmers. In particular, we suggest that the ratio of fin and body height found in natural swimmers could be due to a trade-off between swimming efficiency and swimming speed.
Enhanced strength and corrosion resistance in as-cast TA10 alloys via interstitial carbon solute
Authors: Yang Yong , Wang Binbin , Li Yanjie , Su Baoxian , Luo Liangshun , Wang Liang , Huang Haiguang , Su Yanqing , Guo Jingjie 
Published: April 2022

Abstract
The addition of interstitial elements generally has a significant impact on the macroscopic performances of structural alloys. Here, we report a systematic study on the microstructure, corrosion behaviors and mechanical properties of a series of as-cast Ti-0.3Mo-0.8Ni-xC (x = 0.09, 0.12 and 0.15 wt.%) alloys. A typical basket-weave microstructure appears in all specimens, characterized by the lamellar α-phase and intergranular retained β-phase without TiC precipitates within the prior β grain boundary. Based on the electrochemical and immersion tests, doping with C element can significantly improve the corrosion resistance of TA10 alloys; with increasing the carbon content, the passivation current density decreases from 5.750 to 4.938 μA·cm−2, the breakdown potential increases from −1.115 to −1.223 V versus SCE, the corrosion rate reduces from 15 mm/a to 7.5 mm/a. Moreover, the mechanical properties of TA10 alloys, such as the strength and hardness, can also be enhanced via C alloying. Our results indicate that the addition of interstitial elements should be a potential effective mean to accommodate the comprehensive performances of TA10 alloys.
Rapid identification of volatile organic compounds and their isomers in the atmosphere
Authors: ZHANG Xinglong , GE Yifan , WAN Enlai , LIU Yuzhu , YAO Jinping 
Published: April 2022

Abstract
Isomers are widely present in volatile organic compounds (VOCs), and it is a tremendous challenge to rapidly distinguish the isomers of VOCs in the atmosphere. In this work, laser-induced breakdown spectroscopy (LIBS) technology was developed to online distinguish VOCs and their isomers in the air. First, LIBS was used to directly detect halogenated hydrocarbons (a typical class of VOCs) and the characteristic peaks of the related halogens were observed in the LIBS spectra. Then, comparing the LIBS spectra of various samples, it was found that for VOCs with different molecular formulas, although the spectra are completely the same in elemental composition, there are still significant differences in the relative intensity of the spectral lines and other information. Finally, in light of the shortcomings of traditional LIBS technology in identifying isomers, machine learning algorithms were introduced to develop the LIBS technique to identify the isomers of atmospheric VOCs, and the recognition results were very good. It is proved that LIBS combined with machine learning algorithms is promising for online traceability of VOCs in the atmospheric environment.
Optimization of energy production in two-qubit heat engines using the ecological function
Authors: Fernández J J 
Published: April 2022

Abstract
We study the ecological regime of quantum heat engines where the heat transfer between the environment and the engine is mediated with two qubits that act as energy filters and allow the conversion of heat into work. Using quantum thermodynamics, the theory of open quantum system and the fundamentals of finite-time thermodynamics we obtain the output power, the ecological function and the entropy production of the engine. Then, we optimize the functioning to the ecological function to find the range of efficiencies for which the system works optimally under the ecological criterium. We find that (i) the maximum value of the ecological function depends on the thermal copulings and the energies of the qubits that define the engine. (ii) We can define an ecological working region where the engine works producing a power that is similar to the maximum power but where it rejects much less heat to the environment. (iii) That the range of efficiencies defining the ecological region depends on the parameters defining the engine.(iv) An optimal working region where both the power and the ecological function are big is defined for each machine.
Quantitative verification of the turbulence barrier effect during heavy haze pollution events
Authors: Ren Yan , Zhang Hongsheng , Zhang Xiaoye , Wu Bingui , Cai Xuhui , Song Yu , Zhu Tong 
Published: April 2022

Abstract
Under calm and steady weather conditions with low wind speeds, turbulent intermittency frequently occurs in the atmospheric boundary layer (ABL), which can significantly weaken the turbulent diffusion of matter and energy between the surface and atmosphere. The turbulence barrier effect is defined as the phenomenon in which turbulence may disappear at certain heights, and during periods of heavy haze, creating what can seem like a barrier layer that hinders vertical transmissions. Although the turbulence barrier effect can explain the physical mechanisms behind the rapid accumulation of PM2.5 (fine particulate matter with diameters smaller than 2.5 μm) and the influence of turbulent diffusion conditions on the vertical distribution of PM2.5, more direct perspectives such as turbulent flux is still required for quantitative verification. Due of challenges in the acquisition of PM2.5 turbulent flux, carbon dioxide (CO2), which has relatively mature flux acquisition technology, was used as a substitute means of verifying and quantifying this phenomenon. The turbulence data collected during heavy haze events, at from five levels of a 255 m meteorological tower located in Tianjin, were analyzed and used to quantitatively verify the influence of the turbulent barrier effect on PM2.5. The results also revealed that the vertical changes in the turbulent barrier effect were consistent with those of the concentrations and flux of CO2. This means that this knowledge about the turbulent barrier effect can be extended to other mass-transfer processes. The analysis also found that the proportion of counter-gradient transport increases when the occurrences of the turbulent barrier effect are frequent. This work validates the presence of the turbulent barrier effect and is an important foundation for its future parameterization, which will help to accurately identify the matter transport processes in the stable boundary layer and under extreme weather conditions, such as intense pollution events.
The Effects of Different Antihypertensive Drugs on Postmenopausal Mild-to-Moderate Hypertension: A Network Meta-analysis
Authors: Ding Hong , Zhang Xiang , Zhang Xiao-wei , Yuan Ruo-wen , Kou Chen-kun , Li Ning-yin , Yu Jing 
Published: April 2022

Abstract

Background
To compare the effects of different antihypertensive drugs on the reduction of blood pressure in postmenopausal women with hypertension.

Methods
PubMed, EMBASE, Cochrane Library, ClinicalTrails, WanFang, VIP, and CNKI databases were electronically retrieved. The retrieval time limit was from the establishment of the database to April 2020. The efficacy of 2 or more antihypertensive agents or placebos in postmenopausal hypertensive females was investigated. Mainly, the changes of systolic and diastolic blood pressure were compared. Two reviewers independently screened the literature and extracted the data. Cochrane’s “risk of bias” method was used to evaluate the methodological quality of randomized controlled trials. A network meta-analysis was performed by Stata15.0 software.

Results
Eight studies were involved in this meta-analysis. Angiotensin receptor blockers (ARBs) showed the most significant antihypertensive effects on systolic blood pressure as compared with placebo [standardized mean differences (SMDs) = −9.25, 95% credibility intervals (CIs) −12.24 to −6.26]. Surface under the cumulative ranking (SUCRA) suggested ARB (SUCRA = 76.3%) and diuretics (SUCRA = 72.4%) was the cumulative probability of the best treatment. Diuretics showed the best effect on diastolic blood pressure (SMD = −11.98, 95% CI −14.42 to −0.95) and its cumulative probability was the highest (SUCRA = 94.9%).

Conclusions
For postmenopausal females with hypertension, ARB was optimal on systolic blood pressure while diuretics was optimal on diastolic blood pressure among the different antihypertensive drugs.