bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Intelligent Following Motion Control System of Rehabilitation Robot
Authors: Miao Mingda , Gao Xueshan , Zhao Jun , Zhao Peng 
Published: December 2021

Abstract
Background: In response to the current problem of low intelligence of mobile lower limb motor rehabilitation aids, this article proposes an intelligent control scheme based on human movement behavior in order to control the rehabilitation robot to follow the patient's movement. Methods: Firstly, a multi-sensor data acquisition system is designed according to the motion characteristics of human body. By analyzing and processing the motion data, the change law of human center of gravity and behavior intention are obtained, and the behavior intention of human is used as the control command of the robot following motion. In order to achieve the goal of the rehabilitation robot following human motion, an adaptive radial basis function neural network (ARBFNN) sliding mode controller is designed based on the robot dynamic model. The controller can reduce the impact of fluctuations in the human center of gravity on changes in the parameters of the robot control system, and enhance the adaptability of the system to other disturbance factors, and improve the accuracy of following human motion. Finally, the motion following experiment of the rehabilitation robot is carried out. Results: The experimental results show that the robot can recognize the motion intention of human body, and achieve the training goal of following different subjects to complete straight lines and curves. Conclusions: According to the experimental results, the accuracy of the multi-sensor data acquisition system and control algorithm design is verified, which demonstrates the feasibility of the proposed intelligent control scheme.
Gentiopicroside Ameliorates Glucose and Lipid Metabolism in T2DM by Activating PI3K/AKT Pathway Via FGFR1
Authors: Xu Zhanchi , Lin Zeyuan , Zeng Jingran , Chen Rui , Li Chuting , Xiao Haiming , Huang Heqing , Xu Shiyue , Lan Tian 
Published: December 2021

Abstract
Background: Abnormalities in lipid and glucose metabolism are are constantly occured in type 2 diabetes (T2DM). However, it can be ameliorated by gentiopicroside (GPS). Considering the key role of fibroblast growth factor receptor 1/phosphatidylinositol 3-kinase/protein kinase B (FGFR1/PI3K/AKT) pathway in T2DM, we explore the possible mechanism of GPS on lipid and glucose metabolism through its effects on FGFR1/PI3K/AKT pathway.Methods: Palmitic acid (PA)-induced HepG2 cells and a db/db mice were used to clarify the role and mechanism of polydatin on lipid and glucose metabolism.Results: GPS ameliorated glucose and lipid metabolism disorders in db/db mice and PA-induced HepG2 cells. Furthermore, GPS activated FGFR1/PI3K/AKT pathway including increased the protein expression of FGFR1 and promoted the phosphorylation of PI3K, AKT and FoxO1. Additionally, knockdown of FGFR1 reversed the activation of PI3K/AKT pathway by GPS.Conclusions: The present study demontrates that GPS ameliorates glucose and lipid metabolism disorders via activation of FGFR1/PI3K/AKT pathway.
Deconvolution of Ferromagnetic Resonance Spectrum of Magnetic Nanoparticle Assembly Using Genetic Algorithm
Authors: Usov N. A. , Serebryakova O. N. 
Published: December 2021

Abstract
The ferromagnetic resonance (FMR) spectra of dilute random assemblies of magnetite nanoparticles with cubic magnetic anisotropy and various aspect ratios are calculated using the stochastic Landau-Lifshitz equation at a finite temperature, T = 300 K, taking into account the thermal fluctuations of the particle magnetic moments. Particles of non-spherical shape in the first approximation are described as elongated spheroids with a given semiaxes ratio a/b, where a and b are the long and transverse semiaxes of a spheroid, respectively. A representative database of FMR spectra is created for assemblies of randomly oriented spheroidal magnetite nanoparticles with various transverse diameters D = 5 - 25 nm, moderate aspect ratios a/b = 1.0 - 1.8, and magnetic damping constants k = 0.1, 0.2. The basic FMR spectra of assemblies with D = 25 nm at different aspect ratios can be considered as representatives of assemblies of single-domain magnetite nanoparticles with transverse diameters D > 25 nm. The database is calculated at exciting frequency f = 4.9 GHz (S-band) to clarify clearly the details of the FMR spectrum that depend on the nature of the particle magnetic anisotropy. The data obtained make it possible to analyze arbitrary combined FMR spectra constructed as weighted linear combinations of FMR spectra of the base assemblies. In addition, using a genetic algorithm, the corresponding inverse problem is solved. The latter consists in determining the volume fractions of the base assemblies in some arbitrary nanoparticle assembly, which is represented by its FMR spectrum.PACS: 75.20.-g; 75.50.Tt; 75.40.Mg
High Expression of LGR6 is A Poor Prognostic Factor In Esophageal Carcinoma
Authors: Ehara Takehito , Uehara Takeshi , Yoshizawa Takahiro , Nakajima Tomoyuki , Kinugawa Yasuhiro , Kobayashi Shota , Asaka Shiho , Iwaya Mai , Nagaya Tadanobu , Miyagawa Yusuke , Ota Hiroyoshi , Soejima Yuji 
Published: December 2021

Abstract
Background: Leucine-rich repeat-containing G-protein-coupled receptor 6 (LGR6) promotes carcinogenesis and progression in some cancer types. However, there are few reports of LGR6 expression in esophageal squamous cell carcinoma (ESCC). LGR6 expression and clinicopathological features in ESCC were investigated by RNAscope, a high-sensitivity RNA in situ hybridization method.Methods: Appropriate tumors were selected from 41 cases of ESCC from which tissue microarrays were generated, and LGR6 expression was identified by RNAscope. Results: Thirty-seven patients had LGR6 expression. High LGR6 expression was observed in 17 cases and low LGR6 expression in 24 cases. LGR6 expression was significantly higher in high histological grade ESCC than in low histological grade ESCC (P=0.0023). ESCC patients who received neoadjuvant chemotherapy had significantly higher LGR6 expression than those without neoadjuvant chemotherapy (P=0.0109). Furthermore, high LGR6 expression showed a poorer prognosis than low LGR6 expression (log-rank test, P=0.0365).Conclusions: LGR6 may be a prognostic factor and a potential new therapeutic target in ESCC.
Evaluation of Diagnostic Strategies for Fetal Skeletal Dysplasia Using Ultrasound Scan and Gene Testing: A Preliminary Study in Wu Han, China
Authors: Liu Wanlu , Cao Jing , Shi Xinwei , Li Yuqi , Qiao Fuyuan , Wu Yuanyuan 
Published: December 2021

Abstract
Objective: The aim of this study was to deliver prenatal diagnosis through sonographic examination and gene variation testing, and to evaluate the outcome of applied strategies in prenatal diagnosisMethods: From September 2015 to April 2021, the study investigated 24 cases with suspected short long bones, which were obtained from the prenatal diagnosis center of Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology. The likely pathogenic gene variants were analyzed by multiple approaches (including karyotype analysis, copy number variations and whole exome sequencing) and further determined with the accuracy of the prenatal diagnosis for fetal skeletal dysplasia through one year follow-up survey. Results: ① We found fetal skeletal dysplasia or malformation in 8 cases (account for 33.3%) before 24 weeks of gestation and in the rest cases after 30 weeks of gestation. ② Out of 24 cases, likely pathogenic gene variants in FGFR3, FBN2, COL1A2, CUL7 and DYNC2H1 were detected for 6 cases; genetic variants in FGFR3, IMPAD1 and GORAB as possibly lethal mutations were identified in other 6 cases; and gene variants in WNT1, FBN1, OBSL1, COL1A1, DYNC2H1 and NEK1, known as Variant of Undetermined Significance (VUS), were found in 4 cases. The rest 8 cases showed undetectable mutation in the whole exome sequencing (WES) analysis.③ A genetic diagnosis determined 12 different skeletal dysplasia genotypes in 14/24 (58.3%) cases. The other 10 cases with wild type gene (41.7%) were normal and well developed in one-year follow-up survey after study.Conclusion: Features of fatal skeletal dysplasia can be identified in utero using fetal ultrasound and gene testing. Sonographic examination combining with genetic diagnosis showed advance in prenatal diagnosis in the preliminary study and the applied strategy could be used to help with improving the accuracy of prenatal diagnosis for fetal skeletal dysplasia.
Assessing The Impact Path of Air Quality On Enterprise R&amp;D Investment: Empirical Evidences From Dual Perspectives of Investor Sentiment And Government Concern
Authors: Yang Jialiang , He Dan 
Published: December 2021

Abstract
Based on the data of Shanghai and Shenzhen A-share listed companies from 2015 to 2019, this paper studies the influence paths of air quality on R&D investment of listed companies from the perspectives of investor sentiment and government concern. It is found that, on the whole, air quality has a significant inhibitory effect on R&D investment. Air quality has a significant promoting effect on investor sentiment, which serves as a path to further restrain the R&D investment of listed companies. Air pollution is an effective concern for the government, and serves as a veil between air quality and R&D investment. Furthermore, this paper analyzes the heterogeneity of enterprises from the aspects of regional technology complexity, property right nature, whether it is a polluting enterprise or not, and whether it is a key regulated enterprise or not, and comes to relevant conclusions. This paper expands the research on air quality and enterprise R&D investment decision-making, which helps to clarify and improve the transmission mechanism and implementation effect of environmental protection policies.
The Effect of Structural Parameters on Response Characteristics of Aeroelastic System in the Presence of Dynamic Stall
Authors: Qiu Zhan , Wang Fuxin 
Published: December 2021

Abstract
The effect of structural paramters on the response and aerodynamic stiffness characteristics of the free aeroelastic system under the influence of dynamic stall is investigated adopting CFD (Computational Fluid Dynamics) method. The equilibrium angle of the spring and the structural stiffness are taken as parameters of interest. Systems with small equilibrium angles enter the symmetric limit-cycle state more quickly after a Hopf bifurcation and experience dynamic stall in both directions, rather than slowly decreasing in minimum angle of attack and remaining in the asymmetric limit-cycle state before dynamic stall in the opposite direction, as is the case with systems with large spring equilibrium angles. Thus, aerodynamic stiffness of system with large equilibrium angles can be more significantly influenced by the change in aerodynamic moment characteristics at the minimum angle of attack. Furthermore, by increasing the initial angular velocity, we find that the system response all becomes symmetric limit cycle and therefore the aerodynamic stiffness appears to have a monotonically increasing characteristic. As to the effect of structural stiffness, it is found that the limit cycle amplitude first increases with structural stiffness after bifurcation, then the amplitude is unchanged with varying structural stiffness at higher Mach number. Energy maps show that the parametric distribution of the energy transfer contributes to this phenomenon. Moreover, when entering the symmetric limit cycle state, the structural stiffness no longer has a significant effect on the aerodynamic stiffness of the system, as the increase in the aerodynamic stiffness is determined solely by the increase in dynamic pressure without the effect of changes in moment characteristics.
Evaluation of Blood Glucose Level Control in Type 1 Diabetic Patients Using Deep Reinforcement Learning
Authors: Viroonluecha Phuwadol , Egea-Lopez Esteban , Santa Jose 
Published: December 2021

Abstract
Diabetes mellitus is a disease associated with abnormally high levels of blood glucose due to lack of insulin. Combining an insulin pump and continuous glucose monitor with a control algorithm to deliver insulin is an alternative to patient self-management of insulin doses to control blood glucose levels in diabetes mellitus patients. In this work we propose a closed-loop control for blood glucose levels based on deep reinforcement learning. We describe the initial evaluation of several alternatives conducted on a realistic simulator of the glucoregulatory system and propose a particular implementation strategy based on reducing the frequency of the observations and rewards passed to the agent, and using a simple reward function. We train agents with that strategy for three groups of patient classes, evaluate and compare it with alternative control baselines. Our results show that our method is able to outperform baselines as well as similar recent proposals, by achieving longer periods of safe glycemic state and low risk.
Development and Validation of a Wearable Device to Provide Rich Somatosensory Feedback for Rehabilitation After Sensorimotor Impairment
Authors: Buist Mirka , Mastinu Enzo , Ortiz-Catalan Max 
Published: December 2021

Abstract
BACKGROUNDThis study describes the development and validation of a non-invasive wearable device to provide haptic feedback and train sensory discrimination. The ultimate aim of this device is to be used as part of a treatment for functional and/or pain rehabilitation due to sensorimotor impairment.METHODSThe development was guided by a structured design control process to ensure the verifiability and validity of the design outcomes. Two sub-systems were designed to systematically provide various types of somatosensory stimulation: 1) a tactile display for touch and vibration, and 2) a set of bands for sliding, pressure, and strain sensations. The device was designed with a versatile structure that allows for its application on different body parts. We designed an interactive computer program to command the device and enable training sessions. The validation of the device was performed with 11 able-bodied individuals whose upper arm tactile sensitivity was measured over 5 training sessions conducted daily. Tactile discrimination and perception threshold were measured using the standard 2-point discrimination and Semmes-Weinstein monofilament tests, respectively.RESULTSThe development and verification procedures ensured that the device successfully complied with the pre-established requirements, which were selected to enable the device clinical application. The results on tactile discrimination and sensitivity showed high subject-dependent variability but trended towards improvement (p=0.05). This trend was also confirmed by the scores achieved during the training sessions.CONCLUSIONSWe introduced a wearable device to deliver somatosensory stimulation and to train sensory discrimination. The design is versatile enough to allow for its application on different body parts. The device was found robust enough for clinical application, and it showed to increase tactile sensitivity on upper arms of able-bodied individuals. Further studies will be conducted to determine if our current findings transfer to individuals with sensorimotor impairment and if this approach is suitable for functional and/or pain rehabilitation after sensorimotor impairments.
Prediction of Agricultural Commodities Futures Prices: A DQN-LSTM Method
Authors: Xu Hanxiao , Liang Jie , Zang Wenchaun 
Published: December 2021

Abstract
This paper combines deep Q network (DQN) with long and short-term memory (LSTM) and proposes a novel hybrid deep learning method called DQN-LSTM framework. The proposed method aims to address the prediction of five Chinese agricultural commodities futures prices over different time duration. The DQN-LSTM applies the strategy enhancement of deep reinforcement learning to the structural parameter optimization of deep recurrent networks, and achieves the organic integration of two types of deep learning algorithms. The new framework has the capacity of self-optimization and learning of parameters, thus improving the performance of prediction by its own iteration, which shows great prospects for future application in financial prediction and other directions. The performance of the proposed method is evaluated by comparing the effectiveness of the DQN-LSTM method with that of traditional predicting methods such as auto-regressive integrated moving average (ARIMA), support vector machine (SVR) and LSTM. The results show that the DQN-LSTM method can effectively optimize the traditional LSTM structural parameters through policy iteration of the deep reinforcement learning algorithm, which contributes to a better long and short-term prediction accuracy. In particular, the longer the prediction period, the more obvious the advantage of prediction accuracy of a DQN-LSTM method.
Comparative Analysis of Spin, Paths, Temporal, and Spatial Modes
Authors: Martinez Carlos , Nieminsky Ewa 
Published: December 2021

Abstract
Research on optical modes, such as orbital, temporal, or parity, bring much attention, for these new degrees of freedom allow larger quantum communication alphabets. Each lab usually adapts the Bloch or Poincare sphere to their experiment or light mode. This takes an extra effort and time and produces a plethora of spheres and notations. Yet, we miss a common framework or convention valid among diverse physical-modes. We aim to unite in one representation the best points from many different spheres. Such common-sphere could also help to compare distant experiments, for an intuitive understanding of quantum optical states. We built a common representation by mathematically aligning the Hilbert space and a three dimensional color space. We define a unique color for each one of the three Poincare axes and positive Pauli vectors. Beyond three primary colors and states, our equations associate each Hilbert state to a specific tonality, among the infinite combinations in Color space. These maths achieve a new ability to unequivocally represent any quantum state by its precise combination of colors. Thus, with these equations, quantum states ‘yellow’ or ‘magenta’ are not mere names, rather each one denotes an exact superposition in Hilbert space. To handle disparities between SO3 vs. SU2 space operations, we propose a darkness bit and a Hermite-inspired shape. A simulation of HG modes let us align distinct shapes to quantum optical states. Three examples of applications show our color sphere in practice. First, we apply the Hilbert-Color mapping in Polarization. Then, the same color-space is shown in Orbital Angular Momentum. We also represent location paths in this color-mapping. The simulations and practical comparisons let us refine the proposed color sphere convention. For higher-order and path-to-industry, any sphere section serves as color constellation diagram. One color-space sphere served as common ground to represent coexisting concepts among diverse physical areas. The introduced change diagrams are visual tools to communicate setups and operators. The examples showed a unique notation matches many physical processes. The resulting diagram of superposition of spatially separated optical paths is coherent with a Plate on Polarization or cylinder lens on OAM Hermite Gaussian modes. A unique change diagram describes the three examples. The meaning persist despite the physical implementation. Found also how this color space let us grasp visually some meaning. Thus, the amount of blue in a state representation indicated the degree of its phase shift. Overall, we presented math and visual tools to display and compare experiments. We showed examples in different physical modes, all linked to a unique color sphere.
Distribution and Safety Assessment of Heavy Metals in Fresh Meat from Zhejiang, China
Authors: Han Jian Long , Pan Xiao Dong , Chen Qing 
Published: December 2021

Abstract
There are increasing concerns on heavy metals in animal derived foods. We analyzed the levels of As, Cd, Cr, Cu, Hg, Ni, and Pb in 1066 fresh meat samples including pork, beef, mutton, chicken and duck from Zhejiang province, southeast China. The average levels of As, Cd, Cr, Cu, Hg, Ni, and Pb were 0.018, 0.002, 0.061, 0.801, 0.0038, 0.055, and 0.029 mg/kg wet weight respectively. There are significant positive correlations among Cd, Hg and Pb (P<0.05) and negative correlations for Cu-Pb or Cu-Cd (P<0.05). The exposure assessment showed that the health risk to humans by consuming these meat products was relatively low. However, regular monitoring of heavy metals in meat products is still recommended considering their intensive industrial activities.
Theoretical and Experimental Studies of ion Transport in Mixed Polyanion Solid Electrolytes
Authors: Deng Zeyu , Mishra Tara , Mahayoni Eunike , Ma Qianli , Guillon Olivier , Chotard Jean-Noel , Seznec Vincent , Cheetham Anthony K. , Masquelier Christian , Gautam Gopalakrishnan Sai , Canepa Pieremanuele 
Published: December 2021

Abstract
Lithium and sodium (Na) mixed polyanion solid electrolytes for all-solid-state batteries display some of the highest ionic conductivities reported to date. However, the effect of polyanion mixing on ion transport properties is still debated. Here, we focus on Na1+xZr2SixP3-xO12 (0 ≤ x ≤ 3) NASICON electrolyte to elucidate the role of polyanion mixing on Na-transport properties. Although there is a large body of data available on this NASICON system, transport properties extracted from experiments or theory vary by orders of magnitude, signifying the need to bridge the gap between different studies. Here, more than 2,000 distinct ab initio-based kinetic Monte Carlo simulations have been used to map the statistically vast compositional space of NASICON over an unprecedented time range and spatial resolution and across a range of temperatures. We performed impedance spectroscopy of samples with varying Na compositions revealing that the highest ionic conductivity (~ 0.1 S cm–1) is achieved in Na3.4Zr2Si2.4P0.6O12, in line with our predictions (~0.2 S cm–1). Our predictions indicate that suitably doped NASICON compositions, especially with high silicon content, can achieve high Na+ mobilities. Our findings are relevant for the optimization of mixed polyanion solid electrolytes and electrodes, including sulfide-based polyanion frameworks, which are known for their superior ionic conductivities.