bluuebunny/crossref_metadata_2025_split huggingface dataset:
Greenspace’s value orientations of ecosystem service and socioeconomic service in China
Authors: Yao Xia , Lin Tao , Sun Shoukai , Zhang Guoqin , Zhou Hao , Jones Laurence , Liu Wenhui , Huang Yiyi , Lin Meixia , Zhang Junmao , Chen Yuan , Ye Hong 
Published: May 2022

ABSTRACT
Background: Natural ecosystems provide necessary services for human beings, including ecosystem service values (ESVs) and socioeconomic service values (SSVs). The value orientations of ESVs and SSVs are mainly related to people’s interaction with nature. This study reclassified greenspace from a perspective of exposed and non-exposed greenspace based on the level of interaction by people and greenspace. We applied an expert questionnaire to survey the SSVs value orientations of forestland, grassland, wetland, and water bodies, and quantitatively compared the value orientations between the ESVs and SSVs of greenspace in China. Result: (1) The values of exposed greenspace were relatively far higher than non-exposed greenspace, as it had both ESVs and SSVs. (2) The forestland and grassland had relatively high ESVs and SSVs, and are the priority for both the exposed and non-exposed greenspace. (3) Wetland had relatively high ESVs but low SSVs, which was unpopular for exposed greenspace. (4) The ESVs and SSVs of water body were relatively balanced. Conclusion: Greenspace had both ESVs and SSVs when they are exposed to human. Our study provided an innovative perspective to explore the value orientations of greenspace, which provides an actionable scientific basis for greenspace planning, design and construction in human habitat.
Parameterizations of black-hole spacetimes beyond circularity
Authors: Delaporte Héloïse , Eichhorn Astrid , Held Aaron 
Published: May 2022

Abstract
We discuss parameterizations of black-hole spacetimes in and beyond general relativity in view of their symmetry constraints: within the class of axisymmetric, stationary spacetimes, we propose a parameterization that includes non-circular spacetimes, both in Boyer–Lindquist as well as in horizon-penetrating coordinates. We show how existing parameterizations, which make additional symmetry assumptions (first, circularity; second, a hidden constant of motion), are included in the new parameterization. Further, we explain why horizon-penetrating coordinates may be more suitable to parameterize non-circular deviations from the Kerr geometry. Our investigation is motivated by our result that the regular, spinning black-hole spacetimes proposed in Eichhorn and Held (2021 Eur. Phys. J. C
81 933); Eichhorn and Held (2021 J. Cosmol. Astropart. Phys.
5 73) are non-circular. This particular deviation from circularity can result in cusps, a dent and an asymmetry in the photon rings surrounding the black-hole shadow. Finally, we explore a new class of non-circular deviations from Kerr black holes, which promote the spin parameter to a function, and find indications that regularity cannot be achieved in this setting. This result strengthens the case for regular black holes based on a promotion of the mass parameter to a function.
Functional composite microbeads for cell-based meat culture: effect of animal gelatin coating on cell proliferation and differentiation
Authors: Kong Yan , Ong Shujian , Liu Mei Hui , Yu Hanry , Huang Dejian 
Published: May 2022

Abstract
Hydrogel microbeads are promising matrices for cell-based meat culture because they can be conveniently fabricated from food-grade materials. In this study, food-grade sodium alginate was successfully applied to fabricate edible microbeads with the desired diameters (∼200 µm) using electrospray technology. Pure alginate microbeads have poor cytoaffinity. To enhance the cytoaffinity of alginate microbeads for meat culture, we applied different gelatin coatings, namely porcine gelatin, bovine gelatin, and fish gelatin, onto alginate beads. The modification is non-toxic and environmentally friendly with the use of plant-derived crosslinkers and under mild reaction conditions. As all ingredients are food grade, the modified microbeads are edible and biodegradable, with the mean diameters of 142.96 ± 35.49 μm (porcine gelatin-coated beads), 105.12 ± 80.46 μm (bovine gelatin-coated beads), and 94.81 ± 67.38 μm (bovine gelatin-coated beads). These modified microbeads have self-fluorescence and can be easily distinguished under a fluorescent microscope. The hydrogel core enables the microbeads to have a density of 1.04 g cm−3 for suspension culture. Bovine gelatin-coated microbeads have the best primary porcine myoblast and C2C12 cell adhesion, and can achieve between 16- to 18-fold proliferation of different muscle cells. With the successful differentiation of C2C12 and proliferation of 3T3-L1 adipocytes on bovine gelatin-coated microbeads, cells and microbeads can form clusters, illustrating that our edible microbeads are promising microcarriers for mammalian cell culture for cell-based meat production.
Plasma-based experimental investigation of double compression ramp shock wave/boundary layer interaction control
Authors: Zhang Chuan-Biao , Yang He-Sen , Liang Hua , Guo Shan-Guang 
Published: May 2022

Abstract
An experimental investigation on the control effects of the high-frequency streamwise pulsed arc discharge array (HS-PADA) on the double compression ramp shock wave/boundary layer interaction (DCR-SWBLI) was carried out at Mach 2.0. Firstly, two types of ramp configurations were designed. The base flow field and actuation flow field were investigated. The actuation frequencies were 10 kHz and 20 kHz. Fast Fourier transform and root-mean-square methods were applied based on schlieren images. The base flow field indicated that the compression effect of ramps decreased with the lengthen of the first ramp. The results of actuation flow field showed that the 20 kHz actuation was superior to the 10 kHz actuation in weakening the shock wave intensity. The HS-PADA exhibited two types of control effects: modifying the shock structure, which was closely related to the separation zone, and modifying the low-frequency unsteadiness of the shock wave, which might not be related to the separation zone. The first separation shock wave, of which the high-frequency motion was more intense under actuation, may be more sensitive to HS-PADA than the second. Finally, the control mechanism of the HS-PADA on DCR-SWBLI was extracted.
Dual-emission fluorescent nanoprobe based on Ag nanoclusters for sensitive detection of Cu(II)
Authors: Chen Ming , Ao Wei , Bai Jinna , Li Pengjun , Wei Wei , Pang Shujie , Yang Xudong 
Published: May 2022

Abstract
Noble metal nanoclusters have attracted much attention because of their excellent fluorescence properties. In this work, we demonstrated a dual-emission fluorescent nanocomposite based on silver nanoclusters. First, we synthesized positively charged His-AgNCs, which emits intense blue light, and then Ag nanoclusters with stable red emission were synthesized using DHLA as the ligand. Thus a dual-emission fluorescent nanoprobe was successfully obtained through electrostatic self-assembly, with the advantages of good water solubility and excellent stability. Based on the intensity ratio of the two emission peaks, the nanoprobe can be used for selective and sensitive detection of copper ions, and presents a good linear relationship within a certain concentration range. In addition, we also designed a polymer film, and our dual-emission nanoprobe was successfully loaded onto it, which means that the visual detection of copper ions is possible. This indicates that our dual-emission fluorescent nanoprobe has potential application prospects in environmental analysis, medical diagnosis, biological detection, etc.
Triple-band electromagnetically induced transparency effects enabled by two sets of arc-ring-type resonators at terahertz frequency
Authors: Xu Wei , Yang Zhuchuang , Zhou Haiquan , Wu Yangkuan , Zhu Huaxin , Zhang Xiangyang , Wang Ben-Xin 
Published: May 2022

Abstract
A new type of terahertz metamaterial resonance device with triple-band electromagnetically induced transparent (EIT) is introduced in this paper. Its unit cell consists of two sets of arc-ring-type resonators placed on a dielectric sheet, which can generate three EIT transparency peaks at terahertz region. The generation of these transparent peaks is mainly attributed to the coupling effect between the resonant modes of the arc-ring-type resonators. Influence of the arc length and radius of the arc-ring-type resonators and the width of the air layer between the inner arc-ring-type resonators and outer arc-ring-type resonators on the transmission spectrum is studied. Furthermore, active tunability of the transparent peaks is achieved by incorporating photosensitive silicon with tunable conductivity in the metamaterial structure. The results show that depending on the change of conductivity as well as the position of photosensitive silicon, the EIT effect can be shown as an adjustable switch from triple-band to dual-band or from triple-band to single-band. In addition, the refractive index sensing performance of the metamaterial device is discussed. The metamaterial device has the excellent characteristics of simple structure design and active modulation, which are important and useful for the development of photoelectric switches, sensors and filter devices.
Expansion history-dependent oscillations in the scalar-induced gravitational wave background
Authors: Witkowski Lukas T. , Domènech Guillem , Fumagalli Jacopo , Renaux-Petel Sébastien 
Published: May 2022

Abstract
Oscillations in the frequency profile of the scalar-induced contribution to the stochastic gravitational wave background are a characteristic signal for small-scale features during inflation. We investigate how this oscillatory frequency profile is affected by the expansion history of the post-inflationary universe. Our results are applicable as long as the equation of state of the universe can be taken as constant during the period in which the gravitational waves are produced, and we compute the spectrum of gravitational waves induced by both sharp and resonant features, associated with oscillations in k and log(k), respectively. For resonant features, the frequencies of the oscillatory contributions to the gravitational wave spectrum are unaffected by the equation of state, but not their relative amplitudes, allowing one to extract information about both inflationary physics and the post-inflationary expansion history from the oscillatory pattern. For sharp features we find that the gravitational wave spectrum only exhibits prominent modulations as long as the propagation speed of density fluctuations is cs
< 1, with a frequency larger by a factor cs

-1 than that of the scalar power spectrum. We find that the stiffer the equation of state, the larger the relative amplitude of the oscillations. In particular, a relative amplitude significantly higher than 20 % is not achievable for the `standard' case of radiation domination, and would be a smoking-gun signal of both nontrivial inflationary dynamics on small scales, and a post-inflationary universe not dominated by radiation.
Geometric structure of multi-form-field isotropic inflation and primordial fluctuations
Authors: Chen Chong-Bin , Soda Jiro 
Published: May 2022

Abstract
An inflationary scenario is expected to be embedded into an ultraviolet (UV)
complete theory such as string theory. The effect of UV complete theories may appear as nontrivial kinetic terms in the low energy effective field theory, which provides a nontrivial
geometry in field space. In this paper, we study the effect of the geometry
of multi-form-field space on an inflationary scenario.
In particular, we focus on the geometric destabilization mechanism
which induces the phase transition from the conventional slow-roll inflation
to a novel inflationary scenario. Anisotropic inflation is a typical example of the new phase. To conform to observations, we restrict us to isotropic configuration of form fields.
We clarify the conditions for the onset of the destabilization and
reveal the geometric structure of attractors after the destabilization.
We classify the viable models from the observational point of view.
We also investigate the features of the primordial fluctuations and
find the similarity to hyperbolic inflation.
By calculating the power spectrum, we make several
phenomenological predictions which are useful to discriminate our models from others inflation models. We found the scalar-to-tensor r will be suppressed by large one-form gauge fields, while it has the same order as the slow roll parameter r ∼ 𝒪(1)ϵ for large two-from gauge fields.
Noninvasively recorded high-gamma signals improve synchrony of force feedback in a novel neurorehabilitation brain–machine interface for brain injury
Authors: Flint Robert D , Li Yongcheng , Wang Po T , Vaidya Mukta , Barry Alex , Ghassemi Mohammad , Tomic Goran , Brkic Nenad , Ripley David , Liu Charles , Kamper Derek , Do An H , Slutzky Marc W 
Published: May 2022

Abstract

Objective. Brain injury is the leading cause of long-term disability worldwide, often resulting in impaired hand function. Brain–machine interfaces (BMIs) offer a potential way to improve hand function. BMIs often target replacing lost function, but may also be employed in neurorehabilitation (nrBMI) by facilitating neural plasticity and functional recovery. Here, we report a novel nrBMI capable of acquiring high-γ (70–115 Hz) information through a unique post-traumatic brain injury (TBI) hemicraniectomy window model, and delivering sensory feedback that is synchronized with, and proportional to, intended grasp force. Approach. We developed the nrBMI to use electroencephalogram recorded over a hemicraniectomy (hEEG) in individuals with TBI. The nrBMI empowered users to exert continuous, proportional control of applied force, and provided continuous force feedback. We report the results of an initial testing group of three human participants with TBI, along with a control group of three skull- and motor-intact volunteers. Main results. All participants controlled the nrBMI successfully, with high initial success rates (2 of 6 participants) or performance that improved over time (4 of 6 participants). We observed high-γ modulation with force intent in hEEG but not skull-intact EEG. Most significantly, we found that high-γ control significantly improved the timing synchronization between neural modulation onset and nrBMI output/haptic feedback (compared to low-frequency nrBMI control). Significance. These proof-of-concept results show that high-γ nrBMIs can be used by individuals with impaired ability to control force (without immediately resorting to invasive signals like electrocorticography). Of note, the nrBMI includes a parameter to change the fraction of control shared between decoded intent and volitional force, to adjust for recovery progress. The improved synchrony between neural modulations and force control for high-γ signals is potentially important for maximizing the ability of nrBMIs to induce plasticity in neural circuits. Inducing plasticity is critical to functional recovery after brain injury.
Designing and validating a robust adaptive neuromodulation algorithm for closed-loop control of brain states
Authors: Fang Hao , Yang Yuxiao 
Published: May 2022

Abstract

Objective. Neuromodulation systems that use closed-loop brain stimulation to control brain states can provide new therapies for brain disorders. To date, closed-loop brain stimulation has largely used linear time-invariant controllers. However, nonlinear time-varying brain network dynamics and external disturbances can appear during real-time stimulation, collectively leading to real-time model uncertainty. Real-time model uncertainty can degrade the performance or even cause instability of time-invariant controllers. Three problems need to be resolved to enable accurate and stable control under model uncertainty. First, an adaptive controller is needed to track the model uncertainty. Second, the adaptive controller additionally needs to be robust to noise and disturbances. Third, theoretical analyses of stability and robustness are needed as prerequisites for stable operation of the controller in practical applications. Approach. We develop a robust adaptive neuromodulation algorithm that solves the above three problems. First, we develop a state-space brain network model that explicitly includes nonlinear terms of real-time model uncertainty and design an adaptive controller to track and cancel the model uncertainty. Second, to improve the robustness of the adaptive controller, we design two linear filters to increase steady-state control accuracy and reduce sensitivity to high-frequency noise and disturbances. Third, we conduct theoretical analyses to prove the stability of the neuromodulation algorithm and establish a trade-off between stability and robustness, which we further use to optimize the algorithm design. Finally, we validate the algorithm using comprehensive Monte Carlo simulations that span a broad range of model nonlinearity, uncertainty, and complexity. Main results. The robust adaptive neuromodulation algorithm accurately tracks various types of target brain state trajectories, enables stable and robust control, and significantly outperforms state-of-the-art neuromodulation algorithms. Significance. Our algorithm has implications for future designs of precise, stable, and robust closed-loop brain stimulation systems to treat brain disorders and facilitate brain functions.
Research on online monitoring and fault diagnosis system based on multivariate empirical mode decomposition
Authors: Li Linfeng , Lv Yong , Yuan Rui , Dang Zhang , Wu Lifeng 
Published: May 2022

Abstract
Mechanical equipment is crucial to industrial production, so the monitoring and fault diagnosis of its vibration signals is important to ensure production safety. And this paper mainly researches on an online monitoring and fault diagnosis system. The system makes use of multiple sensors to collect vibration signals from different positions of machines for multivariate signals so that condition of the machines can be monitored and information of local faults can avoid loss. Besides, this paper applies a method for fault feature extraction of mechanical equipment based on multivariate empirical mode decomposition (MEMD), which can accurately extract frequency of fault features to realize fault diagnosis when the features are weak in the early period. And this paper puts forward a design to the overall framework of the system based on technical requirements of the system, then introduces the multi-sensor mechanical fault diagnosis method based on MEMD. On such basis, this paper employs LabVIEW and Python to develop the upper computer software of the system, and experiments are carried out to testify whether this system is viable or not. The research results show that the system developed by this paper has practical application value in condition monitoring and fault diagnosis of mechanical equipment.
Mass estimation method of loose parts based on function model
Authors: Sheng Lin , Xu Zhongfeng , Tan Yi , Ma Bo 
Published: May 2022

Abstract
The nuclear main pump has a complex structure and contains a large number of components. With the continuous flow of the primary circuit coolant, there is a risk of loosening and falling off of the components in the reactor. The existence of loose parts in the reactor makes the reactor operation a safety hazard. Accurate mass estimation of the loose parts is conductive to quickly judge the degree of the failure of loose parts, provide effective suggestions for the subsequent maintenance of the reactor and ensure the safety of reactor operation. The existing mass estimation methods have problems of large errors and poor consistency. This article proposes a method for estimating the mass of loose parts by establishing a functional relationship model based on signal characteristic value. The characteristic value of the signal is constructed by extracting the Root Mean Square value and the main frequency of the shock signal, and then the functional relationship between the quality of the loose part and the characteristic value of the signal is established, which is used to estimate the mass of the loose part. The experimental results show that the method proposed in this paper has the characteristics of small estimation error and good consistency, which can meet the needs of practical engineering applications.
Feature extraction of scraping noise of the car seat electric track based on sparse representation
Authors: Hou Fatao , Chen Jin , Dong Guangming , Li Yao , Zhang Ke 
Published: May 2022

Abstract
With the development of the science and technology, the demanding of convenience and comfort when driving a car are getting higher and higher. As an important part that has a great influence on the comfort of the car driving, the car seat is also developing towards the electric direction. The electric seat is becoming the choice of more and more manufacture of automobile. However, the product quality inspection of the electric track of the car seat is still in a relatively preliminary stage. At present, the detection of the unqualified track product is mainly performed by workers listening in an anechoic room. This will lead to the high cost of construction of the anechoic chamber, low quality inspection efficiency, and instability by different quality inspection personnel. In this paper, we focus on the scraping noise detection of the electric track product, as scraping noise is the main cause of the product disqualification. Since scraping noise often features a higher energy in the high frequency band, we adopt the Short Time Fourier Transform (STFT) to acquire the total energy at different time duration. Then we model the acquired time series as summation of one sparse signal, one low-passing signal, and one noise signal. Based on the property of the three parts, the objective function is established and solved with Majorization-Minimization (MM) approach. The effectiveness of the proposed scraping detection method is verified with the real track vibration signal, and the superiority of the proposed method is verified via the comparison with other impulse detection method.
Refined time-shift multiscale diversity entropy: a novel feature extraction algorithm for fault diagnosis of planetary gearbox
Authors: Wang Shun , Li Yongbo 
Published: May 2022

Abstract
Planetary gearboxes play a critical role in aerospace and heavy industry fields, such as wind turbines, heavy vehicles and construction machines. Intelligent fault diagnosis is significant for safe operation and fault prevention of planetary gearboxes. Recently, multiscale diversity entropy and related entropy methods are proposed to extract features of time series and applied for the fault diagnosis. However, there are still some limitations in fault feature representation and stability for multiscale diversity entropy. To solve the problem, in this paper, a novel planetary gearboxes fault diagnosis method via refined time-shift multiscale diversity entropy (RTSMDE) is proposed. First, a novel entropy algorithm called RTSMDE is proposed to measure the complexity of time series and extract fault features of the vibration signals, which is robust and efficient in performance. Then, the obtained features are utilized to fulfil automatically the fault pattern identifications using support vector machine. To confirm the superiority of the RTSMDE-based fault diagnosis method, simulated signals and experimental studies are constructed and three used widely methods are employed to present a comprehensive comparison. The results indicate that RTSMDE performs best and obtains the highest accuracy.