bluuebunny/crossref_metadata_2025 huggingface dataset:
Illustration Design Model with Clustering Optimization Genetic Algorithm
Authors: Liu Jing , Chen Qixing , Tian Xiaoying
Published: January 2021

For the application of the standard genetic algorithm in illustration art design, there are still problems such as low search efficiency and high complexity. This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, then the k‐medoids algorithm is introduced to optimize the clustering of the genetic algorithm, and a cost function is used to carry out and evaluate the quality of clustering to optimize the complexity of the original algorithm. In addition, a multiobjective optimization genetic algorithm with complex constraints based on group classification is proposed. This algorithm focuses on the problem of group diversity and uses k‐means cluster analysis operation to solve the problem of group diversity. The algorithm divides the entire group into four subgroups and assigns appropriate fitness values to reflect the optimal preservation strategy. A large number of computer simulation calculations show that the algorithm can obtain a widely distributed and uniform Pareto optimal solution, the evolution speed is fast, usually only a few iterations can achieve a good optimization effect, and finally the improved genetic algorithm is used to design the random illustration art. The example simulation shows that the improved algorithm proposed in this paper can achieve higher artistic and innovative illustration art design.
Development of an Electroactive Hydrogel as a Scaffold for Excitable Tissues
Authors: Gupta Kriti , Patel Ruchi , Dias Madara , Ishaque Hina , White Kristopher , Olabisi Ronke
Published: January 2021

For many cells used in tissue engineering applications, the scaffolds upon which they are seeded do not entirely mimic their native environment, particularly in the case of excitable tissues. For instance, muscle cells experience contraction and relaxation driven by the electrical input of an action potential. Electroactive materials can also deform in response to electrical input; however, few such materials are currently suitable as cell scaffolds. We previously described the development of poly(ethyelene glycol) diacrylate-poly(acrylic acid) as an electroactive scaffold. Although the scaffold itself supported cell growth and attachment, the voltage (20 V) required to actuate these scaffolds was cytotoxic. Here, we describe the further development of our hydrogels into scaffolds capable of actuation at voltages (5 V) that were not cytotoxic to seeded cells. This study describes the critical next steps towards the first functional electroactive tissue engineering scaffold.
Multiple Controls on the Accumulation of Organic-Rich Sediments in the Besa River Formation of Liard Basin, British Columbia, Canada
Authors: Choi Jiyoung , Lee Hyun Suk , Kim Yuri , Ardakani Omid H. , Hong Sung Kyung
Published: January 2021

The Late Devonian Besa River Formation is an organic-rich shale sequence in Liard Basin, northeastern British Columbia, Canada, with significant natural gas reserves. High-resolution elemental geochemistry of three long continuous cored intervals of the Besa River Formation was used to better understand the paleodepositional environment of organic-rich intervals in this thick marine shale. The studied core intervals were divided into five chemostratigraphic units based on organic and inorganic geochemical proxies. The highest total organic carbon (TOC) content (up to 13 wt.%) was identified in the upper part of the Patry member (Unit III) within the Liard Basin. During the deposition of Unit III, low clastic influx and euxinic bottom conditions mostly contributed to the high accumulation of organic carbon. Moreover, a high productivity and organic influx may have increased organic-rich basinal sediments, which further depleted the seawater column oxygen content in the presence of a large amount of organic matter. This took place within the oxygen-deficient bottom water from the Patry–Exshaw stratigraphic units. This high TOC interval was most likely deposited through abundant biogenic silica production by radiolarians, thereby utilizing the supply of nutrients from the upwelling. Sea level change was also an important factor that controlled organic matter accumulation in the Besa River Formation. The transgression in sea level changed the residence time of the organic matter in oxic zones within the water column, which limited its supply in deeper water; this decreased the TOC content in Unit IV. Before the deposition, silica production collapsed and was replaced by terrestrial sedimentation of clay minerals in the upper part of the Exshaw member, which caused organic matter dilutions in Unit V (under 5 wt.%). These results provide new insights into the effects of relative sea level changes on redox conditions, productivity, and detrital flux, which are related to organic matter enrichment patterns and their geographic variations. Unit III is characterized by an organic-rich interval as well as an abundance of biogenic silica that is closely related to fracturing. Thus, Unit III is expected to have the highest shale gas potential in the Devonian Besa River Formation. The high-resolution geochemical data integrated with well log and/or seismic data can be used to determine the distribution of the perspective interval for shale gas production in the Liard Basin.
On the Global Asymptotic Stability of Solutions of Some Difference Equations with Intrinsic Initial Conditions
Authors: Berinde Vasile
Published: January 2021

Our aim in this paper is to study the asymptotic global stability of the positive solutions for a class of first-order nonlinear difference equations with a remarkable feature: the initial conditions are intrinsic and not explicitly given. Global stability results are obtained in a particular case and then for a general class of first-order difference equations. We also provide the results of some numerical experiments obtained by the mini software package FIXPOINT to illustrate asymptotic global stability as well as the rate of convergence. To the best of our knowledge, our approach is the first one in the literature on the stability of difference equations without explicit initial conditions and might generate an interesting new direction of further studies.
Effects of Li2O on Structure and Viscosity of CaO-Al2O3-Based Mold Fluxes
Authors: Chen Lifeng , Liu Kun , Han Peng , Yang Bin , Feng Lianghua
Published: January 2021

Since CaO-Al2O3-based mold fluxes are one of the most important mold flux systems in metallurgic processes, it is important to explore their structure characteristics and viscosity. Molecular dynamics simulation is performed to study the effect of w(CaO)/w(Al2O3) ratio on both the structural and viscosity properties of CaO-Al2O3-based mold fluxes. A systematic analysis of the structure and thermodynamics on CaO-Al2O3-based mold fluxes is carried out, and it is well known that the viscosity of mold fluxes is related to the structure. The results show that the formation of stable structures of Si-O in the mold fluxes was beneficial to reduce the probability of structural interconnection, degree of polymerization, and viscosity of the molten slag. In the cationic structure, the contents of Ca-O-Al and Ca-O-Si are more stable, the interconnection of the Ca-O-Al and Ca-O-Si network weakens, and the viscosity decreases. The tetrahedra [AlO4] and [SiO4] have similar structures, but they exhibit different thermodynamic and physical properties. Viscosity test shows that CaO/Al2O3 = 0.88–2 continuously increased, when the cosolvent content Li2O = 1%–4%, CaO-Al2O3-based mold flux viscosity decreased, the degree of network structure polymerization decreased, and the complex structure depolymerized. Increasing the water content in the cosolvent is beneficial to reduce the viscosity of the crystallizer.
MAGAN: Mask Attention Generative Adversarial Network for Liver Tumor CT Image Synthesis
Authors: Liu Yang , Meng Lu , Zhong Jianping
Published: January 2021

For deep learning, the size of the dataset greatly affects the final training effect. However, in the field of computer-aided diagnosis, medical image datasets are often limited and even scarce. We aim to synthesize medical images and enlarge the size of the medical image dataset. In the present study, we synthesized the liver CT images with a tumor based on the mask attention generative adversarial network (MAGAN). We masked the pixels of the liver tumor in the image as the attention map. And both the original image and attention map were loaded into the generator network to obtain the synthesized images. Then, the original images, the attention map, and the synthesized images were all loaded into the discriminator network to determine if the synthesized images were real or fake. Finally, we can use the generator network to synthesize liver CT images with a tumor. The experiments showed that our method outperformed the other state-of-the-art methods and can achieve a mean peak signal-to-noise ratio (PSNR) of 64.72 dB. All these results indicated that our method can synthesize liver CT images with a tumor and build a large medical image dataset, which may facilitate the progress of medical image analysis and computer-aided diagnosis. An earlier version of our study has been presented as a preprint in the following link: https://www.researchsquare.com/article/rs-41685/v1.
Sports Big Data: Management, Analysis, Applications, and Challenges
Authors: Bai Zhongbo , Bai Xiaomei
Published: January 2021

With the rapid growth of information technology and sports, analyzing sports information has become an increasingly challenging issue. Sports big data come from the Internet and show a rapid growth trend. Sports big data contain rich information such as athletes, coaches, athletics, and swimming. Nowadays, various sports data can be easily accessed, and amazing data analysis technologies have been developed, which enable us to further explore the value behind these data. In this paper, we first introduce the background of sports big data. Secondly, we review sports big data management such as sports big data acquisition, sports big data labeling, and improvement of existing data. Thirdly, we show sports data analysis methods, including statistical analysis, sports social network analysis, and sports big data analysis service platform. Furthermore, we describe the sports big data applications such as evaluation and prediction. Finally, we investigate representative research issues in sports big data areas, including predicting the athletes’ performance in the knowledge graph, finding a rising star of sports, unified sports big data platform, open sports big data, and privacy protections. This paper should help the researchers obtaining a broader understanding of sports big data and provide some potential research directions.
Improvement of the Nonparametric Estimation of Functional Stationary Time Series Using Yeo-Johnson Transformation with Application to Temperature Curves
Authors: Othman Sameera Abdulsalam , Ali Haithem Taha Mohammed
Published: January 2021

In this article, Box-Cox and Yeo-Johnson transformation models are applied to two time series datasets of monthly temperature averages to improve the forecast ability. An application algorithm was proposed to transform the positive original responses using the first model and the stationary responses using the second model to improve the nonparametric estimation of the functional time series. The Box-Cox model contributed to improving the results of the nonparametric estimation of the original data, but the results become somewhat confusing after attempting to make the transformed response variable stationary in the mean, while the functional time series predictions were more accurate using the transformed stationary datasets using the Yeo-Johnson model.
Research on Optimization of Aircraft Climb Trajectory considering Environmental Impact
Authors: Liu Fangzi , Hu Minghua , Lv Wenying , Zhang Honghai
Published: January 2021

Trajectory-based operation is a new technology that will be developed in the next generation of air traffic management. In order to clarify the optimization space of fuel consumption and emission impact on the environment under the specific operation limitation of air traffic management in the process of aircraft climb, an aircraft climb performance parameter optimization model considering the environmental impact is established. First, the horizontal and vertical climb models are established for the aircraft climb process, and then the optimization objectives are constructed by considering the impact of fuel consumption, exhaust emissions on air temperature, and the convenience of the flight process. Finally, the multiobjective model is solved by genetic algorithm. The B737-800 civil aviation aircraft is selected for simulation experiment to analyze the impact of speed change on the optimization target. The results show that with the change of speed, the fuel consumption and temperature rise are different, and the climb performance parameters of the aircraft are affected by the maximum RTA. By optimizing the flight parameters of the aircraft, it can effectively reduce the impact of flight on the environment and provide theoretical support for the sustainable development of civil aviation.
Penetration Form of Inter‐Hole Cracks under Double‐Hole Blasting Conditions with Inclined Fissures
Authors: Shen Shiwei , Zhao Yue , Liu Chang , Dai Shulin , Wu Fei , Jiang Man
Published: January 2021

During blasting construction in tunnel engineering, an inclined fissure near the blast hole produces the “Z” type of over‐excavation and subsequently affects the overall blasting effect and stability of the tunnel. In this work, dynamic caustics testing was used to study the burst propagation mode and penetration form of explosive cracks at different positions between holes under double‐hole blasting conditions. Results showed that the existence of gently inclined cracks changed the propagation law of explosive stress wave. The dominant fracture surface was formed in the vertical direction between the borehole and the fracture. Finally, the crack penetrates to form “Z”‐type over‐excavation, which was analyzed by the dynamic caustics test. The expansion velocity of the burst crack reached the maximum under the reflection of the explosion stress wave and then decreased with the attenuation of the stress wave intensity. The peak propagation velocity decreased with the increasing vertical distance between the prefabricated fracture and the borehole, and the stress intensity factor at the crack tip immediately reached its peak value after detonation, and the oscillation then decreased. These research results can serve a basis for reducing tunnel blasting over‐excavation under this condition and optimizing blasting parameters.
An Interpolation Theorem for Quasimartingales in Noncommutative Symmetric Spaces
Authors: MA Congbian , Zhao Guoxi
Published: January 2021

Let

E

be a separable symmetric space on

0
,
∞

and

E

M

the corresponding noncommutative space. In this paper, we introduce a kind of quasimartingale spaces which is like but bigger than

E

M

and obtain the following interpolation result: let

E
^

M

be the space of all bounded

E

M

-quasimartingales and

1
<
p
<

p

E

<

q

E

<
q
<
∞

. Then, there exists a symmetric space

F

on

0
,
∞

with nontrivial Boyd indices such that

E
^

M

=

L
^

p

M

,

L
^

q

M

F
,
K

.
Heat Shock Proteins in Oxidative Stress and Ischemia/Reperfusion Injury and Benefits from Physical Exercises: A Review to the Current Knowledge
Authors: Szyller Jakub , Bil-Lula Iwona
Published: January 2021

Heat shock proteins (HSPs) are molecular chaperones produced in response to oxidative stress (OS). These proteins are involved in the folding of newly synthesized proteins and refolding of damaged or misfolded proteins. Recent studies have been focused on the regulatory role of HSPs in OS and ischemia/reperfusion injury (I/R) where reactive oxygen species (ROS) play a major role. ROS perform many functions, including cell signaling. Unfortunately, they are also the cause of pathological processes leading to various diseases. Biological pathways such as p38 MAPK, HSP70 and Akt/GSK‐3β/eNOS, HSP70, JAK2/STAT3 or PI3K/Akt/HSP70, and HSF1/Nrf2‐Keap1 are considered in the relationship between HSP and OS. New pathophysiological mechanisms involving ROS are being discovered and described the protein network of HSP interactions. Understanding of the mechanisms involved, e.g., in I/R, is important to the development of treatment methods. HSPs are multifunctional proteins because they closely interact with the antioxidant and the nitric oxide generation systems, such as HSP70/HSP90/NOS. A deficiency or excess of antioxidants modulates the activation of HSF and subsequent HSP biosynthesis. It is well known that HSPs are involved in the regulation of several redox processes and play an important role in protein‐protein interactions. The latest research focuses on determining the role of HSPs in OS, their antioxidant activity, and the possibility of using HSPs in the treatment of I/R consequences. Physical exercises are important in patients with cardiovascular diseases, as they affect the expression of HSPs and the development of OS.
Research and Development Investment Combination Forecasting Model of High-Tech Enterprises Based on Uncertain Information
Authors: Wei Qi , Chen Min , Ruan Chuan-yang
Published: January 2021

The high demand of the competitive market for innovation has brought the increase of research and development (R&D) investment. High-tech enterprises can reasonably control R&D cost and effectively manage R&D activities by accurately predicting R&D investment. Given the characteristics that high-tech enterprises have high uncertainty and frequently changing information in R&D investment, this paper uses the grey metabolic GM (1, 1) model and the exponential smoothing method in time series to establish a single prediction model of R&D investment in high-tech enterprises. With the analysis of the advantages and disadvantages of each single model, a combined forecast model of R&D investment in high-tech enterprises is thus established. The model was applied to the forecast of R&D investment of a high-tech enterprise in China from 2019 to 2023, and the results verified the higher accuracy and practicability of this model. The establishment of this model can provide effective support for high-tech enterprises in R&D cost management.
A Novel Robust Fuzzy Rough Set Model for Feature Selection
Authors: Li Yuwen , Wei Shoushui , Liu Xing , Zhang Zhimin
Published: January 2021

The existing fuzzy rough set (FRS) models all believe that the decision attribute divides the sample set into several “clear” decision classes, and this data processing method makes the model sensitive to noise information when conducting feature selection. To solve this problem, this paper proposes a robust fuzzy rough set model (RS‐FRS) based on representative samples. Firstly, the fuzzy membership degree of the samples is defined to reflect its fuzziness and uncertainty, and RS‐FRS model is constructed to reduce the influence of the noise samples. RS‐FRS model does not need to set parameters for the model in advance and can effectively reduce the complexity of the model and human intervention. On this basis, the related properties of RS‐FRS model are studied, and the sample pair selection algorithm (SPS) based on RS‐FRS is used for feature selection. In this paper, RS‐FRS is tested and analysed on the open 12 datasets. The experimental results show that RS‐FRS model proposed can effectively select the most relevant features and has certain robustness to the noise information. The proposed model has a good applicability for data processing and can effectively improve the performance of feature selection.
Interpolative Kannan Contractions inT0-Quasi-Metric Spaces
Authors: Gaba Yaé Ulrich , Aphane Maggie , Aydi Hassen
Published: January 2021

In this paper, we update the well-known fixed point theorem of Kannan using the interpolation notion in the realm of quasi-metric spaces. We consider some asymmetric versions. We also present some illustrative examples in support of the obtained results.
High-Expressed Macrophage Scavenger Receptor 1 Predicts Severity Clinical Outcome in Transplant Patient in Idiopathic Pulmonary Fibrosis Disease
Authors: Zheng Mingfeng , Tian Tian , Liang Jialong , Ye Shugao , Chen Jingyu , Ji Yong
Published: January 2021

Background. Lung transplantation has been performed worldwide and admitted as an effective treatment for patients with various end-stage lung diseases. However, limit reliable clinical indicators exist to identify patients at high risk for allograft failure in lung transplant recipients. The recent advances in the knowledge of immunological aspects of the pulmonary diseases, for that innate macrophage activation, are induced by pathogen or pathogen-derived molecules and widely accepted as the critical evidence among the pathogenesis of lung inflammation and fibrosis. This study was aimed at evaluating the clinical significance of CD86- and macrophage scavenger receptor 1- (MSR1-) positive cells during the development of idiopathic pulmonary fibrosis (IPF) and pulmonary arterial hypertension (PAH), and their potential roles in the prediction of the outcomes after lung transplantation were examined. Methods. Tissues from lung transplantation for 37 IPF and 15 PAH patients from the Department of Cardiothoracic Surgery in Wuxi People’s Hospital from December 2015 to December 2016 were analyzed by immunohistochemistry (IHC) for detecting the expression and CD86 and MSR1 and correlated with clinical events after lung transplantation. Results. IHC results showed that the expression of MSR1, IL-13, and arginase-1 (Arg1) but not CD86 in the lung section of IPF patients was dramatically enhanced when compared with that of PAH patients. The expression of MSR1, IL-13, and Arg1 but not CD86 in the lung from IPF patients with smoking was significantly increased when compared with that from nonsmoking subjects. In addition, the expression of MSR1-positive cells in IPF subjects with Klebsiella pneumoniae infection was dramatically enhanced than that in noninfection subjects. MSR1-positive macrophages were negatively associated with FEV1 and with FVC but not associated with TLC and with TLCO. However, CD86-positive macrophages were not significantly associated with the above lung function-related factors. Furthermore, MSR1 had a higher area under the ROC curve (AUC) than CD86 for IPF diagnosis. Survival analysis indicated that high levels of MSR1-positive macrophages had a worse prognostic effect for IPF patients with lung transplantation. Conclusion. Our study indicates the clinical significance of Klebsiella pneumoniae infection-related MSR1-positive cells in IPF progression, and it could be a prognostic marker in IPF after the lung transplant; development strategies to reduce the expression of MSR1-positive macrophages in IPF may be beneficial for the lung transplant.
The Existence of Least Energy Sign-Changing Solution for Kirchhoff-Type Problem with Potential Vanishing at Infinity
Authors: Xiao Ting , Gan Canlin , Zhang Qiongfen
Published: January 2021

In this paper, we study the Kirchhoff-type equation:

−

a
+
b

∫

ℝ

3

 
 

∇
u

2

d
x

Δ
u
+
V

x

u
=
Q

x

f

u

,
in
 

ℝ

3

,

where

a

,

b
>
0

,

f
∈

C

1

ℝ

3

,
ℝ

, and

V
,
Q
∈

C

1

ℝ

3

,

ℝ

+

.

V

x

and

Q

x

are vanishing at infinity. With the aid of the quantitative deformation lemma and constraint variational method, we prove the existence of a sign-changing solution

u

to the above equation. Moreover, we obtain that the sign-changing solution

u

has exactly two nodal domains. Our results can be seen as an improvement of the previous literature.
Impact of Smart City Planning and Construction on Community Governance under Dynamic Game
Authors: Guo Jie , Ling Wenhao
Published: January 2021

We present a research on smart city planning and community governance using dynamic game methods, analyze the current status and problems of the current smart community service system, and put forward countermeasures and suggestions based on the global smart community development experience. Through smart city planning and construction, the game model of government governance and information sharing between communities and decision making is obtained, and the two‐dimensional replication dynamic system equations of smart city planning and construction agencies and communities are obtained from smart city planning and construction. The evolutionary stability strategy and a united front are analyzed. The strategy achieves the ideal stable conditions. We define the relevant definition of a smart community and discuss the purpose and significance of the research, especially the importance and necessity of the construction of the smart community. Based on the current situation of the construction of smart communities, we conduct specific research, discuss the deficiencies and shortcomings in the current construction of smart communities, and find out the causes of these problems. Finally, based on learning from the relevant work experience, corresponding improvement measures are proposed for the existing problems from the united front, top‐level design, social participation, platform construction, and talent training.
Antimicrobial Activity of Thermocycled Polymethyl Methacrylate Resin Reinforced with Titanium Dioxide and Copper Oxide Nanoparticles
Authors: Giti Rashin , Zomorodian Kamiar , Firouzmandi Maryam , Zareshahrabadi Zahra , Rahmannasab Sedigheh
Published: January 2021

Aims. This study aimed to evaluate the effect of 2.5% and 7.5% copper oxide (CuO) and titanium dioxide (TiO2) nanoparticles on the antimicrobial activity of thermocycled polymethyl methacrylate (PMMA) denture base material against standard strains of yeast and bacteria species. Material and Methods. In this in vitro study, 150 disk-shaped (10 × 2 mm) specimens of heat-cured PMMA were prepared and divided into five groups (n = 30) to be reinforced with 2.5% CuO, 7.5% CuO, 2.5% TiO2, or 7.5% TiO2 nanoparticles and a control group (without nanoparticle). The specimens were thermocycled, and their antimicrobial activity was assessed against standard strains of yeast including Candida albicans and C. dubliniensis and oral bacteria species including Streptococcus mutans, S. sobrinus, S. salivarius, and S. sanguis. Data were analyzed with ANOVA and Tukey’s post hoc tests (α = 0.05). Results. Both concentrations of CuO and TiO2 nanoparticles had significant antimicrobial activity against S. salivarius, S. sanguis, and C. dubliniensis compared with the control group (

P

 < 0.05). Significant differences existed between both 2.5% (

P

 = 0.006) and 7.5% CuO (

P

 = 0.005) and the control group against S. mutans. However, TiO2 groups were not significantly different from the control group against S. mutans. Concerning C. albicans, 7.5% TiO2 was the only nanoparticle with significantly higher antimicrobial activity compared with the control group (

P

 = 0.043). Conclusions. Both concentrations of CuO and TiO2 were effective antimicrobial agents against S. salivarius, S. sanguis, and C. dubliniensis, and the concentration of CuO was effective against S. mutans. Yet, TiO2 was not much effective. Regarding C. albicans, only 7.5% TiO2 showed efficient antimicrobial activity.
A Novel Value for the Parameter in the Dai-Liao-Type Conjugate Gradient Method
Authors: Ivanov Branislav , Stanimirović Predrag S. , Shaini Bilall I. , Ahmad Hijaz , Wang Miao-Kun
Published: January 2021

A new rule for calculating the parameter

t

involved in each iteration of the MHSDL (Dai-Liao) conjugate gradient (CG) method is presented. The new value of the parameter initiates a more efficient and robust variant of the Dai-Liao algorithm. Under proper conditions, theoretical analysis reveals that the proposed method in conjunction with backtracking line search is of global convergence. Numerical experiments are also presented, which confirm the influence of the new value of the parameter

t

on the behavior of the underlying CG optimization method. Numerical comparisons and the analysis of obtained results considering Dolan and Moré’s performance profile show better performances of the novel method with respect to all three analyzed characteristics: number of iterative steps, number of function evaluations, and CPU time.
Comparative Analysis of the Kinematics Solution Based on the DH Method and Screw Theory
Authors: Li Yong-Bin , Li Tie-Jun , Zhu Hui-Fang , Yang Dong , Chen Ya-Jun , Zhang Wen-Ming , Liu Jian-Ming , Zhang Tian
Published: January 2021

The premise of analyzing and researching robot technology is to establish a proper mathematical model and then to solve it with kinematics. In this study, a self-developed humanoid hydraulically driven dual-arm robot is taken as the research object, and the DH (Denavit–Hartenberg) parameter method and the rotational exponential formula (POE) are used to solve the kinematics of the robot. The calculation results are verified by simulation. The advantages and disadvantages of the two methods are analyzed. The differences between the two methods are compared. It lays a foundation for other scholars to choose mathematical models when analyzing the mechanism in the future.
Stiff-Person Syndrome: Seeing Past Comorbidities to Reach the Correct Diagnosis
Authors: Hicken Jared , Ramirez Daniel , Rigby Mark , Minasian Aram
Published: January 2021

Stiff-person syndrome (SPS) is a rare disorder seen in approximately one in one million people. Although it is rare, the symptoms and findings of a typical case should paint a clear clinical picture for those who are familiar with the disease. The primary findings in SPS include progressive axial muscle rigidity as well as muscle spasms. These symptoms most commonly occur in the setting of antibodies against Glutamic Acid Decarboxylase (GAD), the rate-limiting enzyme in the production of Gamma-Aminobutyric Acid (GABA), which is the primary inhibitory enzyme in the central nervous system. Here, we report the case of a 65-year-old African-American female with a past medical history of hypothyroidism, anxiety, and depression with psychotic features who presented with axial muscle rigidity and lactic acidosis. She had been symptomatic for several months and reported extensive workups performed at two previous hospitals without a definitive diagnosis. A complete neurological and musculoskeletal investigation yielded no positive findings except for the presence of GAD antibodies. The patient was treated with diazepam, tizanidine, and Intravenous Immunoglobulin (IVIG) with significant improvement, thus solidifying the diagnosis of SPS, a rare autoimmune and/or paraneoplastic syndrome.
Sensors Anomaly Detection of Industrial Internet of Things Based on Isolated Forest Algorithm and Data Compression
Authors: Liu Desheng , Zhen Hang , Kong Dequan , Chen Xiaowei , Zhang Lei , Yuan Mingrun , Wang Hui
Published: January 2021

Aiming at solving network delay caused by large chunks of data in industrial Internet of Things, a data compression algorithm based on edge computing is creatively put forward in this paper. The data collected by sensors need to be handled in advance and are then processed by different single packet quantity K and error threshold e for multiple groups of comparative experiments, which greatly reduces the amount of data transmission under the premise of ensuring the instantaneity and effectiveness of data. On the basis of compression processing, an outlier detection algorithm based on isolated forest is proposed, which can accurately identify the anomaly caused by gradual change and sudden change and control and adjust the action of equipment, in order to meet the control requirement. As is shown by experimental simulation, the isolated forest algorithm based on partition outperforms box graph and K-means clustering algorithm based on distance in anomaly detection, which verifies the feasibility and advantages of the former in data compression and detection accuracy.
Development of Coal Mine Filling Paste with Certain Early Strength and Its Flow Characteristics
Authors: Zhang Feng , Liu Jinxiao , Ni Haiming , Li Wenxin , Liu Yongle
Published: January 2021

In coal mine paste filling technology, geomaterials like coal gangue and fly ash are used as the main component, and cement is applied as the cementing material. In the mining production, mining-and-filling is a cyclic work, where the filling immediately after mining and mining immediately after filling. Long solidification time after filling will affect mining; consequently, the paste should have early strength. In addition, the prepared paste will be conveyed to goaf through the pipeline. The paste flow characteristics will change to some extent in the conveying process, and there is uncertainty about whether the paste can meet the requirements of pumpability and strength. Therefore, the influence of pipeline conveying on flow characteristics of paste before filling the goaf should be taken into consideration. Based on the above two points, this paper studies the paste strength, backfill strength, and pumpability parameters in coal mine paste filling and determines the early and later strength of coal mine paste, as well as the pumpability parameters such as slump degree, segregation degree, setting time, and paste gradation. With the determined mass proportion of coal gangue, fly ash, and silicate cement, the orthogonal test was carried out with three factors including gypsum content, the content of early strength agent (Na2SO4), and the mass concentration, and at three levels. The factors affecting paste flow characteristics were determined by range analysis, and the factors affecting the paste’s early strength were determined by the XRD test and SEM test on its microstructure. With paste proportioning and pipeline conveying simulation system, taking slump, segregation degree, backfill strength, and other parameters as indicators, we obtain the influence law of pipeline conveying on the flow characteristics of paste. The research has great theoretical and practical significance for developing coal paste with early strength and its flow characteristics.
Improved ACD-Based Financial Trade Durations Prediction Leveraging LSTM Networks and Attention Mechanism
Authors: Shi Yong , Dai Wei , Long Wen , Li Bo
Published: January 2021

The liquidity risk factor of security market plays an important role in the formulation of trading strategies. A more liquid stock market means that the securities can be bought or sold more easily. As a sound indicator of market liquidity, the transaction duration is the focus of this study. We concentrate on estimating the probability density function

p

Δ

t

i
+
1

|

G

i

, where

Δ

t

i
+
1

represents the duration of the (i + 1)-th transaction and

G

i

represents the historical information at the time when the (i + 1)-th transaction occurs. In this paper, we propose a new ultrahigh-frequency (UHF) duration modelling framework by utilizing long short-term memory (LSTM) networks to extend the conditional mean equation of classic autoregressive conditional duration (ACD) model while retaining the probabilistic inference ability. And then, the attention mechanism is leveraged to unveil the internal mechanism of the constructed model. In order to minimize the impact of manual parameter tuning, we adopt fixed hyperparameters during the training process. The experiments applied to a large-scale dataset prove the superiority of the proposed hybrid models. In the input sequence, the temporal positions which are more important for predicting the next duration can be efficiently highlighted via the added attention mechanism layer.
Genome-Wide Characterization and Expression Analysis of the HD-ZIP Gene Family in Response to Salt Stress in Pepper
Authors: Zhang Zhongrong , Zhu Ranran , Ji Xuehua , Li Hui Ji , Lv Hui , Zhang Hai Ying
Published: January 2021

HD-ZIP is a unique type of transcription factor in plants, which are closely linked to the regulation of plant growth and development, the response to abiotic stress, and disease resistance. However, there is little known about the HD-ZIP gene family of pepper. In this study, 40 HD-ZIP family members were analyzed in the pepper genome. The analysis indicated that the introns number of Ca-HD-ZIP varied from 1 to 17; the number of amino acids was between 119 and 841; the theoretical isoelectric point was between 4.54 and 9.85; the molecular weight was between 14.04 and 92.56; most of them were unstable proteins. The phylogenetic tree divided CaHD-ZIP into 4 subfamilies; 40 CaHD-ZIP genes were located on different chromosomes, and all of them contained the motif 1; two pairs of CaHD-ZIP parallel genes of six paralogism genes were fragment duplications which occurred in 58.28~88.24 million years ago. There were multiple pressure-related action elements upstream of the start codon of the HD-Z-IP family. Protein interaction network proved to be coexpression phenomenon between ATML1 (CaH-DZ22, CaHDZ32) and At4g048909 (CaHDZ12, CaHDZ31), and three regions of them were highly homology. The expression level of CaHD-ZIP gene was different with tissues and developmental stages, which suggested that CaHD-ZIP may be involved in biological functions during pepper progress. In addition, Pepper HD-ZIP I and II genes played a major role in salt stress. CaHDZ03, CaHDZ 10, CaHDZ17, CaHDZ25, CaHDZ34, and CaHDZ35 were significantly induced in response to salt stress. Notably, the expression of CaHDZ07, CaHDZ17, CaHDZ26, and CaHDZ30, homologs of Arabidopsis AtHB12 and AtHB7 genes, was significantly upregulated by salt stresses. CaHDZ03 possesses two closely linked ABA action elements, and its expression level increased significantly at 4 h under salt stress. qRT-P-CR and transcription analysis showed that the expression of CaHDZ03 and CaHDZ10 was upregulated under short-term salt stress, but CaHDZ10 was downregulated with long-term salt stress, which provided a theoretical basis for research the function of Ca-HDZIP in response to abiotic stress.
Unfermented Freeze-Dried Leaf Extract of Tongkat Ali (Eurycoma longifolia Jack.) Induced Cytotoxicity and Apoptosis in MDA-MB-231 and MCF-7 Breast Cancer Cell Lines
Authors: Moses Lusia Barek , Abu Bakar Mohd Fadzelly , Mamat Hasmadi , Aziz Zaleha Abdul
Published: January 2021

The present study was conducted to determine the cytotoxicity effect of Eurycoma longifolia (Jack.) leaf extracts and also its possible anticancer mechanism of action against breast cancer cell lines: non-hormone-dependent MDA-MB-231 and hormone-dependent MCF-7. The leaves of E. longifolia were processed into unfermented and fermented batches before drying using freeze and microwave-oven drying techniques. Obtained extracts were tested for cytotoxicity effect using MTT assay and phenolic determination using HPLC-DAD technique. The most toxic sample was analyzed for its apoptotic cell quantification, cell cycle distribution, and the expression of caspases and apoptotic protein using flow cytometry technique. Fragmentation of DNA was tested using an agarose gel electrophoresis system. The results determined that the unfermented freeze-dried leaf extract was the most toxic towards MDA-MB-231 and MCF-7 cells, in a dose-dependent manner. This extract contains the highest phenolics of gallic acid, chlorogenic acid, ECG, and EGCG. The DNA fragmentation was observed in both cell lines, where cell cycle was arrested at the G2/M phase in MCF-7 cells and S phase in MDA-MB-231 cells. The number of apoptotic cells for MDA-MB-231 was increased when the treatment was prolonged from 24 h to 48 h but slightly decreased at 72 h, whereas apoptosis in MCF-7 cells occurred in a time-dependent manner. There were significant activities of cytochrome c, caspase-3, Bax, and Bcl-2 apoptotic protein in MDA-MB-231 cells, whereas MCF-7 cells showed significant activities for caspase-8, cytochrome c, Bax, p53, and Bcl-2 apoptotic protein. These results indicate the ability of unfermented freeze-dried leaf extract of E. longifolia to induce apoptosis cell death on MDA-MB-231 and MCF-7, as well as real evidence on sample preparation effect towards its cytotoxicity level.
Geothermal Fluid Variation Recorded by Banded Ca-Carbonate Veins in a Fault-Related, Fissure Ridge-Type Travertine Depositional System (Iano, southern Tuscany, Italy)
Authors: Matera Paola Francesca , Ventruti Gennaro , Zucchi Martina , Brogi Andrea , Capezzuoli Enrico , Liotta Domenico , Yu Tsai-Luen , Shen Chuan-Chou , Huntington Katharine W. , Rinyu László , Kele Sándor
Published: January 2021

Banded Ca-carbonate veins in travertine deposits are efficient recorders of the compositional fluctuations of geothermal fluids flowing (or flowed) from deep reservoirs up to the surface, within fault zones. In this view, these veins represent key tools for decoding those factors that influenced the geochemical variations. We have analyzed veins developed in fractures channeling geothermal fluids forming travertine deposits. The studied veins cut a fossil travertine fissure ridge, near the Larderello geothermal area (Iano area, southern Tuscany) where geothermal fluid circulation is favored by NE-trending strike-to-oblique-slip faults and their intersections with NW-trending normal ones. U-Th dating indicates that fluid circulation occurred from (at least) 172 ka to 21 ka. In this time span, the geothermal fluid changed in composition, and the banded Ca-carbonate veins recorded these variations in terms of mineralogical and stable isotope composition and temperature (

T

) of deposition. We also documented for the first time the occurrence of Mn-rich black tree-shaped structures within the veins. Mineralogy coupled with stable and clumped isotope measurements allows the reconstruction of some features (i.e., crystal texture, temperature, and CO2 origin) and the inference of the processes (i.e., pH, T, and pCO2 variations) that have controlled the fluid evolution through time. Multiple-stage and one-stage deposition processes have played an important role in modifying the stable isotope composition of banded Ca-carbonate veins; temperature coupled with pCO2 also influenced their mineralogical composition. Interpreted in the context of the tectonic setting, the data show that the NW-trending faults have mainly controlled travertine deposition. Their intersection with NE-trending faults, interpreted as transfer faults, highlights the important role of transfer zones in channeling the geothermal fluids.
Phosphorus Sorption Characteristics of Luvisols and Nitisols in North Ethiopian Soils
Authors: Getie Ashebir , Kiflu Alemayehu , Meteke Gashaw
Published: January 2021

Crop response to phosphorus (P) application is often erratic in most acidic soil types. The main processes for P losses from agricultural fields are fixation, crop removal, erosion, surface runoff, and subsurface leaching. The purpose of this experiment was to evaluate adsorption properties of selected soils, determine the external phosphorous requirements (EPRs) of the soils, and identify factors contributing to P sorption in two soils in North Ethiopia. In this experiment, separately weighed 1 g soil samples were equilibrated with KH2PO4 at rates of 0.5, 5, 10, 20, 30, 40, and 50 mg PL−1. The P sorption data were fitted well with both Langmuir and Freundlich models with average r2 values of 0.91 and 0.88, respectively. The adsorption maximum (Xm) of the Langmuir isotherm ranged from 588.20 mg P kg−1 soil in Luvisols to 833.3 mg P kg−1 soil in Nitisols. The EPRL values ranged between 86.20 to 93.28 mg P kg−1 for soils of the study area. Among the soil properties, clay content and Ex. Al were positively correlated with Xm. The path analysis revealed that clay, pH, and Av. P had a direct effect on P sorption parameters. The EPRL of the studied soils was 3.44 to 3.6 times greater than the blanket P fertilizer rate recommendation. It is concluded that P sorption models can effectively be used to discriminate soils based on P fixation ability. The result further indicates that the current P fertilizer application rate of 50 kg P ha−1 being practiced across all soil types should be revised after validating the models and EPR values estimated in this study for each soil both under greenhouse and in-the-field conditions.
Permanent Deformation and Temperature Monitoring of Subgrades Using Fiber Bragg Grating Sensing Technology
Authors: Cheng Youkun , Shi Zhenwu
Published: January 2021

The hidden nature of subgrades makes the effective monitoring of their deformation very difficult. This paper addresses this issue by proposing the use of fiber Bragg grating (FBG) sensing technology. Here, an FBG is encapsulated within a monitoring tube formed from a polyvinyl chloride tube, and one end of the monitoring tube is fixed perpendicular to a concrete column, forming a cantilever beam monitoring system. The deformation is assessed according to the theoretical relationship between the horizontal strain on the FBG embedded in the monitoring tube and the vertical displacement of the cantilever beam. Then, the relationship between the variation in the wavelength of light reflected by the encapsulated FBG and the temperature and horizontal strain is obtained on this basis by calibration experiments. The monitoring tubes are buried at a proscribed depth below the top surface of the subgrade, which facilitates the monitoring of the deformation and temperature of the subgrade at different stages of construction through the collection of FBG wavelength data during different periods, such as after embedding the monitoring tubes, the completion of the test road surface, and during the period of operation. The proposed technology is verified by employing the system to monitor the instantaneous maximum deformation and permanent deformation of a subgrade under dynamic loads. The monitoring results demonstrate that the instantaneous maximum deformation values of the subgrade at 0.25 m and 0.5 m below the surface are 695.40 μm and 574.02 μm, respectively, and the corresponding permanent deformation values are 53.00 μm and 41.54 μm, respectively. The FBG sensor system is thereby verified to provide a reliable method for conducting long‐term continuous, accurate, and efficient subgrade deformation and temperature monitoring.
Structure Optimization of Vibrating Feeder Based on Inertia Release
Authors: Xu Ningning , Wang Xinwen , Yu Chi , Gong Sanpeng , Lin Dongdong , Su Xing
Published: January 2021

Reliability is a key factor in the design and manufacture of vibrating feeders. In this paper, a method considering materials force was proposed to optimize the structure of the vibrating feeder. Discrete Element Method (DEM) was used to couple the materials force and the excitation force based on the phase characteristics of the vibrating feeder, and Finite Element Method (FEM) was used to analyze the vibrating feeder structure based on the inertia release method. In order to reduce the stress on the beam of the vibrating feeder, three structural improvement schemes were proposed, which were constructing a statically indeterminate structure, increasing the width of the rib‐stiffened plates on the beam, and increasing the internal spacing of the beam. Then, these three schemes were compared using the FEM. Finally, the response surface method was used to optimize the width of the inner and outer rib‐stiffened plates. The research results showed that when the vibrating feeder moved close to the highest point, the materials force reached the peak. The maximum first principal stress occurred at the middle and both ends of the vibrating feeder beam under the joint action of the excitation force and the materials force. The first principal stress value of the beam was most significantly decreased by increasing the width of the rib‐stiffened plates on the beam of three optimization schemes. The optimal increment of rib‐stiffened plate width was 30 mm with the maximum first principal stress value reduced by 40.12%.