bluuebunny/crossref_metadata_2025 huggingface dataset:
A multi-stem cell basis for craniosynostosis and calvarial mineralization
Authors: Greenblatt Matthew , Bok Seoyeon , Yallowitz Alisha , McCormick Jason , Cung Michelle , Sun Jun , Lalani Sarfaraz , Li Zan , Baumgartner Tomas , Byrne Paul , Sosa Branden , Zhang Tuo , Mohamed Fatma , Ge Chunxi , Franceschi Renny , Cowling Randy , Greenberg Barry , Pisapia David , Imahiyerobo Thomas , Lakhani Shenela , Ross Margaret , Hoffman Caitlin , Debnath Shawon
Published: December 2021

Craniosynostosis is a group of disorders of premature calvarial sutural fusion. An incomplete understanding of the calvarial stem cells (CSCs) that produce fusion-driving osteoblasts has limited the development of non-surgical therapeutic approaches for craniosynostosis. Here we show that both physiologic calvarial mineralization and pathologic calvarial fusion in craniosynostosis reflect the interaction of two separate stem cell lineages; a recently reported CathepsinK (CTSK) lineage CSC (CTSK+ CSC)1 and a separate Discoidin domain-containing receptor 2 (DDR2) lineage stem cell (DDR2+ CSC) identified in this study. Deletion of Twist1, a gene associated with human craniosynostosis2,3, solely in CTSK+ CSCs is sufficient to drive craniosynostosis, however the sites destined to fuse surprisingly display a marked depletion of CTSK+ CSCs and a corresponding expansion of DDR2+ CSCs. This DDR2+ CSC expansion is a direct maladaptive response to CTSK+ CSC depletion, as partial suture fusion occurred after genetic ablation of CTSK+ CSCs. This DDR2+ CSC is a specific fraction of DDR2+ lineage cells that displayed full stemness features, establishing the presence of two distinct stem cell lineages in the sutures, with each population contributing to physiologic calvarial mineralization. DDR2+ CSCs mediate a distinct form of endochondral ossification where an initial cartilage template is formed but the recruitment of hematopoietic marrow is absent. Direct implantation of DDR2+ CSCs into suture sites was sufficient to induce fusion, and this phenotype was prevented by co-transplantation of CTSK+ CSCs. Lastly, the human counterparts of DDR2+ CSCs and CTSK+ CSCs are present in calvarial surgical specimens and display conserved functional properties in xenograft assays. The interaction between these two stem cell populations provides a new biologic interface to modulate calvarial mineralization and suture patency.
Assessing Cellulose Micro/Nanofibre Morphology Using a High Throughput Fibre Analysis Device to Predict Nanopaper Performance
Authors: Pennells Jordan , Heuberger Bérénice , Chaléat Céline , Martin Darren J.
Published: December 2021

Characterising cellulose nanofibre (CNF) morphology has been identified as a grand challenge for the nanocellulose research field. Direct techniques for CNF morphology characterisation exhibit various difficulties related to the material network structure and equipment cost, while indirect techniques that investigate fibre-light interaction, fibre-solvent interaction, fibre-fibre interaction, or specific fibre surface area involve relatively facile methods but may be more unreliable. Nanopaper mechanical testing is a prevalent metric for assessing fibre-fibre interaction, but is an off-line, time-consuming, and destructive methodology. In this study, an optical fibre morphology analyser (MorFi, TechPap) was employed as an on-line, high throughput, fast turnaround tool to assess micro/nanofibre pulp morphology and predict the properties of nanopaper material. Correlation analysis identified fibre content and fibre kink properties as most correlated with nanopaper strength and toughness, while fibre width and coarseness were most inversely correlated with nanopaper performance. Principal component analysis (PCA) was employed to visualise interdependent morphological and mechanical data. Subsequently, two data driven statistical models - multiple linear regression (MLR) and machine learning based support vector regression (SVR) - were established to predict nanopaper properties from fibre morphology data, with SVR generating a more accurate prediction across all nanopaper properties (NRMSE = 0.13-0.33) compared to the MLR model (NRMSE = 0.33-0.51). This study highlights that statistical methods are useful to disentangle and visualise interdependent morphological data from an on-line fibre analysis device, while regression models are also capable of predicting paper mechanical properties from CNF samples even though these devices do not operate at nanoscale resolution.
A Marker-Less Monocular Vision Point Positioning Method for Industrial Manual Operation Environments
Authors: Geng Junhao , Zhao Xinyang , Guo Zhenxin , Zhang Shangan , Tang Jianjun , Rong Yiming , Ma Yongsheng
Published: December 2021

Vision-assisted technologies in industry such as Augmented Reality (AR) are increasingly popular. They require high positioning accuracy and robustness in industrial manual operation environments. However the narrow space and moving hands or tools may occlude or obscure local visual features of operation environments, affect the positioning accuracy and robustness of operating position. It may even cause misoperation of operators because of misguidance. This paper proposes a marker-less monocular vision point positioning method for vision-assisted manual operation in industrial environments. The proposed method can accurately and robustly locate the target point of operation using constraint minimization method even the target area has no corresponding visual features in the case of occlusion and improper illumination. The proposed method has three phases: intersection generation, intersection optimization and target point solving. In the intersection generation stage, a certain number intersections of epipolar lines are generated as candidate target points using fundamental matrices. Here the solving constraint is converted from point-to-line to point-to-points. In the intersection optimization stage, the intersections are optimized to two different sets through the iterative linear fitting and geometric mean absolute error methods. Here the solving constraint is converted from point-to-points to point-to-point sets. In the target point solving stage, the target point is solved as a constrained minimization problem based on the distribution constraint of the two intersection sets. Here the solving constraint is converted from point-to-point sets to point-to-point and the unique optimal solution is obtained as the target point. The experimental results show that this method has a better accuracy and robustness than the traditional homography matrix method for the practical industrial operation scenes.
Clinical Efficacy Analysis and Long-Term Follow-Up Outcomes of Robotic Versus Laparoscopic Sphincter-Preserving Surgery in Total Mesorectal Excision for Low Rectal Cancer: A Retrospective Cohort Study
Authors: Yang Bo , Zhang Shangxin , Yang Xiaodong , wang Yigao , Li Deguan , Zhao Jian , Li Yongxiang
Published: December 2021

Objective: The aim of this study is to compare short-term clinical efficacy and long-term follow-up outcomes of robotic-assisted sphincter-preserving surgery (RAS) with laparoscopic-assisted sphincter-preserving surgery (LAS) for low rectal cancer.Method: This was a single-center retrospective cohort study of consecutive patients diagnosed with low rectal cancer who underwent laparoscopic or robotic sphincter-preserving surgery (RAS 200, LAS 486) between January 1, 2015 and July 1, 2018. Results: Mean operation time was 249±64 min for RAS group and 249±64 min for LAS group (P＜0.001). the rate of temporary ileostomy was 64.5% for RAS and 51.6% for LAS (P=0.002). Time to liquid diet, firstly leaving bed time, removing catheter time and length of stay showed significant difference (all P＜0.001). The distance of distal resection margin in RAS group was closer than LAS group (P=0.004). The recovery from decreased urinary and female sexual function took more than 6 months after surgery in LAS group (P＜0.0001) but 3 months in RAS group (P＜0.0001). Male sexual function 6 months postoperatively was better in RAS group than LAS group (P＜0.001). The Wexner score showed similar results at 6 months after surgery (P＜0.001). And no significantly group difference were observed for OS or DFS at 3 and 5 years after surgery.Conclusion: Both robotic and laparoscopic sphincter-preserving surgery for low rectal cancer are safe and effective in clinical efficacy and long-term outcomes. The robotic approach showed some advantages in short-term recovery of urogenital and anorectal function.
BMP1 is Not Required for Lung Fibrosis in Mice
Authors: Ma Hsiao-Yen , N’Diaye Elsa-Noah , Caplazi Patrick , Huang Zhiyu , Arlantico Alexander , Jeet Surinder , Wong Aaron , Brightbill Hans , Li Qingling , Wong Weng Ruh , Sandoval Wendy , Tam Lucinda , Newman Robert , Roose-Girma Merone , Ding Ning
Published: December 2021

Bone morphogenetic protein 1 (BMP1) belongs to the astacin/BMP1/tolloid-like family of zinc metalloproteinases, which play a fundamental role in the development and formation of extracellular matrix (ECM). BMP1 mediates the cleavage of carboxyl terminal (C-term) propeptides from procollagens, a crucial step in fibrillar collagen fiber formation. Blocking BMP1 by small molecule or antibody inhibitors has been linked to anti-fibrotic activity in the preclinical models of skin, kidney and liver fibrosis. Therefore, we reason that BMP1 may be important for the pathogenesis of lung fibrosis and BMP1 could be a potential therapeutic target for progressive fibrotic disease such as idiopathic pulmonary fibrosis (IPF). Here, we observed the increased expression of BMP1 in both human IPF lungs and mouse fibrotic lungs induced by bleomycin. Furthermore, we developed an inducible Bmp1 conditional knockout (cKO) mouse strain. We found that Bmp1 deletion does not protect mice from lung fibrosis triggered by bleomycin. Moreover, we found no significant impact of BMP1 deficiency upon C-term propeptide of type I procollagen (CICP) production in the fibrotic mouse lungs. Based on these results, we propose that BMP1 is not required for lung fibrosis in mice and BMP1 may not be considered a candidate therapeutic target for IPF.
An Intelligent System for Prediction of Severity of SARS-Cov-2 Infection and Progression to Critical Illness: Using Machine Learning Models
Authors: afrash mohammad reza , Yaghoubi Maryam , Rahimi Fatemeh , Shanbehzadeh Mostafa , Bahadori Mohammadkarim
Published: December 2021

Introduction: The rapid worldwide outbreak of coronavirus disease 2019 (COVID-19) has posed serious and extraordinary challenges to healthcare industries in predicting disease behavior, and outcomes. Aim: This study aimed to develop a Clinical Decision Support System (CDSS) for predicting the severity of SARS-CoV-2 infection and progression to critical illness in a patient with COVID-19 using several machine learning algorithms. Material and Methods: Using a two-center registry, the data of 2482 COVID-19 patients from February 9, 2020, to December 20, 2020, were reviewed. The Relief Feature Selection (RFS) algorithm was used for optimizing the input variables. Then, selected variables feed into ML models including XGBoost, HistGradient Boosting (HGB), Random Forest (RF), and Naïve Bayesian (NB) to construct prediction models. Afterwards, the performance of each combination was compared using some evaluation metrics. Eventually using the best ML model performance, a Clinical Decision Support System (CDSS) was implemented with C# programming language.Results: of the 63 included variables, 15 features were identified as the most important predictors. The experimental results indicated that the HGB classifier with an average classification accuracy of 94.2%, mean specificity of 92.4%, mean sensitivity of 91%, mean F-score of 87.2 %, and finally mean AUC of 87.3 % was selected as the most appropriate machine learning model for predicting the Severity of SARS-CoV-2.Conclusion: The results of this study showed that the hybrid ML algorithms and in particular the RFS-HGB (by optimizing input variables and customizing the structure of the algorithms (can help the frontline clinicians to predict the severity of COVID-19 progression.
Research on Intelligent Following Motion Control System of Rehabilitation Robot
Authors: Miao Mingda , Gao Xueshan , Zhao Jun , Zhao Peng
Published: December 2021

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

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

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

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

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&D Investment: Empirical Evidences From Dual Perspectives of Investor Sentiment And Government Concern
Authors: Yang Jialiang , He Dan
Published: December 2021

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

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

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

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

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

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

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

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.
Inter-row Vegetation Increases Abundances of Ground- and Canopy-dwelling Arthropods in Mediterranean Vineyards
Authors: Blaise Chloé , Mazzia Christophe , Bischoff Armin , Millon Alexandre , Ponel Philippe , Blight Olivier
Published: December 2021

The decline of arthropod populations observed in many parts of the world is a major component of the sixth mass extinction with intensive agriculture being one of its main drivers. Biodiversity-friendly farming practices are taking centre stage in the recovery process. In vineyards, vegetation cover is commonly used for production purposes, to reduce soil compaction by machinery use and soil erosion. Here we examined the effects of vegetation cover and soil management on the abundance of ground- (spiders, beetles, Hemiptera and harvestmen) and canopy-dwelling (wild bees, green lacewings, beetles and Hemiptera) arthropods in three categories of vineyards: (i) vineyards with no vegetation, (ii) partially vegetated (every second inter-row is vegetated) and (iii) all inter-rows are vegetated. We recorded a general positive effect of a decrease in soil perturbation intensity and corresponding higher vegetation cover on arthropod abundance. Plant species richness was the most important vegetation parameter, with a positive effect on spiders, harvestmen, hemipterans and beetles (ground and canopy) abundances. Using a path analysis, we also highlighted the central role of inter-row vegetation management in trophic and non-trophic relationships between vegetation and arthropods, and between arthropod groups. Our results demonstrate the benefits of a softer soil management preserving a diverse vegetation cover for the conservation of arthropods in Mediterranean vineyards.
Increased Flooded Area and Exposure in the White Volta River Basin in Western Africa, Identified From Multi-source Remote Sensing Data
Authors: Li Chengxiu , Dash Jadunandan , Asamoah Moses , Sheffield Justin , Dzodzomenyo Mawuli , Gebrechorkos Solomon Hailu , Anghileri Daniela , Wright Jim
Published: December 2021

Accurate information on flood extent and exposure is critical for disaster management in data-scarce, vulnerable regions, such as Sub-Saharan Africa (SSA). However, uncertainties in flood extent affect flood exposure estimates. This study developed a framework to examine the spatiotemporal pattern of floods and to assess flood exposure through utilization of satellite images, ground-based participatory mapping of flood extent, and socio-economic data. Drawing on a case study in the White Volta basin in Western Africa, our results showed that synergetic use of multi-temporal radar and optical satellite data improved flood mapping accuracy (77% overall agreement with participatory mapping outputs), in comparison with existing global flood datasets (43% overall agreement for the moderate-resolution imaging spectroradiometer (MODIS) Near Real-Time (NRT) Global Flood Product). Increases in flood extent were observed according to our classified product, as well as two existing global flood products. Flood exposure estimates remain highly uncertain and sensitive to the input dataset used, with the greatest farmland and infrastructure exposure estimated using a composite flood map derived from three products, with lower exposure estimated from each flood product individually. While population exposure varied greatly depending on the population dataset used. The study shows that there is considerable scope to develop an accurate flood mapping system in SSA and thereby improve flood exposure assessment and develop mitigation and intervention plans.
Analytic Solution for Double Optical Metasurface Beam Scanners
Authors: Wang Jingru , Ge Yuehe , Chen Zhizhang (David) , Xu Zhimeng , Zhang Hai
Published: December 2021

Optical metasurfaces are researched more and more intensively for the possible realization of lightweight and compact optical devices with novel functionalities. In this paper, a new beam-steering system based on double metasurface lenses (metalenses) is proposed and developed. The proposed system is lightweight, small volume, low cost, and easy to integrate. The exact forward and inverse solutions are derived respectively using the generalized Snell’s law of refraction. Given the orientations of the double metalenses, the pointing position can be accurately determined. If the desired pointing position is given, the required metalenses’ orientations can be obtained by applied global optimization algorithms to solve nonlinear equations related to the inverse problem. The relationships of the scan region and blind zone with the system parameters are derived. The method to eliminate the blind zone is given. Comparison with double Risley-prism systems is also conducted. This work provides a new approach to control light beams.
Investigation into the Role of Cold Atmospheric Plasma on the Precision Grinding of RB-SiC Ceramic at Room Temperature
Authors: Xu Jiabin , Rao Xiaoshuang , Xu Xiaoyu , Wang Kechong , Guo Bao , Liu Lifei , Li Yingjie , Zhang Feihu
Published: December 2021

RB-SiC ceramic is one of the most important and useful material as optical precision elements in many scientific research fields. In this paper, a novel cold atmospheric plasma (CAP), which is based on the precision grinding process in surface technology to modify at room temperature (RT) for grinding with a combination of plasma oxidation surface modification is proposed. To identify the performance of the proposed cold atmospheric plasma (CAP) method on the surface modification of RB-SiC ceramic, precision grinding test was conducted. To reveal the fundamental issue in the grinding of RB-SiC ceramic, numerical calculation and model analysis were conducted to investigate the effect of the composite process on grinding forces and the mechanism of subsurface material removal in the presence of plasma oxidation. As a result of the method included the kept constant during the precision grinding of the composite process self-adaption-grinding process to avoid the deviation caused by second grinding particle entry. As a summary, we provides a significant cold atmospheric plasma-precision grinding compound process toward the establishment of the basic theory by analyzing the mechanism of the simulated design and computation. The process and technical difficulties of RB-SiC ceramic and mechanism of subsurface material removal during precision grinding were be solved.
Mining TCGA to Reveal Immunotherapy-related Genes for Soft Tissue Sarcoma
Authors: Li Ruixin , Yao Fan , Liu Yijin , Wu Xiaodan , Su Peng , Li Tianran
Published: December 2021

Objective: By mining the TCGA database to look for immunotherapy targets of soft tissue sarcoma, and analyzed their biological behavior. Methods: The data of 265 samples were downloaded from the TCGA database to analyze the expression profile of soft tissue sarcomas. Research methods include immune and stromal scores, calculating DEGs, volcano maps and differential gene survival curves, gene enrichment analysis.Results: Kaplan-Meier survival curves showed that in the high immune score group, the total survival time was generally higher than that in the low immune score group. Analysis of the top ten terms resulted in the minimum P values for immune and inflammatory responses, plasma membrane, receptor activity, and chemokine activity. By plotting the K-M curves, we obtained 86 survivals related DEGs. Finally, the genes that can be used as independent risk factors for prognosis of soft tissue sarcoma were obtained by multivariate analysis of the DEGs. Conclusion: We believe that these genes are expected to be new targets for sarcoma immunotherapy and key genes for the analysis of prognosis of sarcoma.
Self-oscillating Chemoelectrical Interface of Solution-gated Ion-sensitive Field-effect Transistor Based on Belousov–zhabotinsky Reaction
Authors: Sakata Toshiya , Nishitani Shoichi , Yasuoka Yusuke , Himori Shogo , Homma Kenta , Masuda Tsukuru , Akimoto Aya Mizutani , Sawada Kazuaki , Yoshida Ryo
Published: December 2021

The Belousov–Zhabotinsky (BZ) self-oscillation reaction is an important chemical model to elucidate nonequilibrium chemistry in an open system. However, there are only a few studies on the electrical behavior of pH oscillation induced by the BZ reaction, although numerous studies have been carried out to investigate the mechanisms by which the BZ reaction interacts with redox reactions, which results in potential changes. Needless to say, the electrical characteristic of a self-oscillating polymer gel driven by the BZ reaction has not been clarified. On the other hand, a solution-gated ion-sensitive field-effect transistor (ISFET) has a superior ability to detect ionic charges and includes capacitive membranes on the gate electrode. In this study, we carried out the electrical monitoring of self-oscillation behaviors at the chemoelectrical interface based on the BZ reaction using ISFET sensors, focusing on the pH oscillation and the electrical dynamics of the self-oscillating polymer brush. The pH oscillation induced by the BZ reaction is not only electrically observed using the ISFET sensor, the electrical signals of which results from the interfacial potential between the solution and the gate insulator, but also visualized using a large-scale and high-density ISFET sensor. Moreover, the N-isopropylacrylamide (NIPAAm)-based self-oscillating polymer brush with Ru(bpy)3 as a catalyst clearly shows a periodic electrical response based on the swelling–deswelling behavior caused by the BZ reaction on the gate insulator of the ISFET sensor. Thus, the elucidation of the electrical self-oscillation behaviors induced by the BZ reaction using the ISFET sensor provides a solution to the problems of nonequilibrium chemistry.
The Prognostic and Predictive Value of ESR1 Fusion Gene Transcripts in Primary Breast Cancer
Authors: Vitale Silvia R. , Ruigrok-Ritstier Kirsten , Timmermans A. Mieke , Foekens Renée , Trapman-Jansen Anita M.A.C. , Beaufort Corine M. , Vigneri Paolo , Sleijfer Stefan , Martens John W.M. , Sieuwerts Anieta M. , Jansen Maurice P.H.M.
Published: December 2021

Background: In breast cancer (BC), recurrent fusion genes of estrogen receptor alpha (ESR1) and AKAP12, ARMT1 and CCDC170 have been reported. In these gene fusions the ligand binding domain of ESR1 has been replaced by the transactivation domain of the fusion partner constitutively activating the receptor. As a result, these gene fusions can drive tumor growth hormone independently as been shown in preclinical models, but the clinical value of these fusions have not been reported. Here, we studied the prognostic and predictive value of different frequently reported ESR1 fusion transcripts in primary BC. Methods: We evaluated 732 patients with primary BC (131 ESR1-negative and 601 ESR1-positive cases), including two ER-positive BC patient cohorts: one cohort of 322 patients with advanced disease who received first-line endocrine therapy (ET) (predictive cohort), and a second cohort of 279 patients with lymph node negative disease (LNN) who received no adjuvant systemic treatment (prognostic cohort). Fusion gene transcript levels were measured by reverse transcriptase quantitative PCR. The presence of the different fusion transcripts was associated, in uni- and multivariable Cox regression analysis taking along current clinic-pathological characteristics, to progression free survival (PFS) during first-line endocrine therapy in the predictive cohort, and disease- free survival (DFS) and overall survival (OS) in the prognostic cohort.Results: The ESR1-CCDC170 fusion transcript was present in 27.6% of the ESR1-positive BC subjects and in 2.3% of the ESR1-negative cases. In the predictive cohort, none of the fusion transcripts were associated with response to first-line ET. In the prognostic cohort, the median DFS and OS were respectively 37 and 93 months for patients with an ESR1-CCDC170 exon 8 gene fusion transcript and respectively 91 and 212 months for patients without this fusion transcript. In a multivariable analysis, this ESR1-CCDC170 fusion transcript was an independent prognostic factor for DFS (HR) (95% confidence interval (CI): 1.8 (1.2–2.8), P=0.005) and OS (HR (95% CI: 1.7 (1.1–2.7), P=0.023). Conclusions: Our study shows that in primary BC only ESR1-CCDC170 exon 8 gene fusion transcript carries prognostic value. None of the ESR1 fusion transcripts, which are considered to have constitutive ER activity, was predictive for outcome in BC with advanced disease treated with endocrine treatment.