bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Research on CEO power and corporate performance model based on data analysis
Authors: Liu Liangcan , Guo Wenming , Li Ruowei 
Published: June 2021

AbstractCompany performance can directly reflect the operation’s status, which has always been one of the central topics. Starting from the CEO power, this paper introduced the corporate innovation strategy and ownership concentration, established the corresponding research model, and studied the relationship between them. In the model design, the company performance was taken as the dependent variable, CEO power and corporate innovation strategy and ownership concentration was taken as independent variables, then the data processing software was used to establish a regression model. Through the model test, it is found that there is a positive correlation between CEO power and corporate performance, and the corporate innovation strategy can play an intermediary role in this relationship while ownership concentration can play a moderating role. This paper further improved the relevant research of corporate performance, and had certain reference significance for the operation.
An improved moving object tracking algorithm based on CAMSHIFT
Authors: Yang Xiaoyan , Yang Jinyu 
Published: June 2021

Abstract
There is a problem that Camshift algorithm relies too much on color as a criterion, in order to solve it, this paper presented an improved moving object tracking algorithm which combined Kalman filter predictor with Camshift algorithm. Firstly, the object model was built by Camshift Algorithm, and the centroid coordinates of the moving objectwere extracted, then the position of the object in the next frame was predicted by using Kalman filter, and finally, the value was used as the centroid coordinates of the object searched by Camshift algorithm in the next frame, proceeding with target match. The simulation results showed that this method can effectively solve the problem of target loss caused by the similar color between the target and the back. The new algorithm can effectively reduce the tracking error accumulation in the tracking process, greatly reduce the template drift, shorten the tracking time, and can have a better practicability and real-time performance.
Research on self-adaptive clustering algorithms for large data sparse networks based on information entropy
Authors: Ma Tingting , Zhang Guanhong 
Published: June 2021

Abstract
With the advent of the era of artificial intelligence and information technology, a large number of data and information pour into all walks of life. These data packages include many online and offline data such as text files, audio and video. However, so many data are unnecessary in real life. The application of data clustering algorithm based on artificial intelligence technology can solve such problems very well. However, the traditional clustering algorithm relies too much on manual operation when choosing clustering centers, which greatly reduces the efficiency of the whole algorithm. At the same time, the traditional clustering algorithm based on sparse network has too many coefficients in its coefficient matrix design, so it can not aggregate the relevant data well. This paper will measure the correlation of related data based on information entropy, and innovatively improve the existing sparse data network model. A model training algorithm based on multi-strategy pattern optimization is proposed to realize the automatic selection of clustering centers and reduce the training time of the algorithm. In terms of data clustering correlation, this paper proposes an optimized adaptive clustering algorithm based on the joint model of sparse subspace clustering algorithm model and the norm of adaptive subspace segmentation. In the experimental part, this paper compares the proposed algorithm with the traditional density peak clustering algorithm. The experimental results show that the proposed algorithm has obvious advantages in text data collection and classification, image data collection and filtering.
Application of Hybrid Moran’s I Index and SE Model on the spatial Impact and time dradient changes of regional development
Authors: Yu Linhui , Chang Jing 
Published: June 2021

Abstract
Spatial econometrics includes space, which has long been neglected in econometrics, into the model. To explore the two themes of spatial dependence and spatial heterogeneity is a branch of econometrics dealing with the spatial relationship of geographical units. Moran's I index test is a method to test the correlation of development in a spatial region, and the combination of spatial econometric model and Moran's I index test can add spatial effect to Moran's I index test and make a series of regression to get the regional correlation. According to the spatial econometric model, this paper collects the changes of per capita GDP scale level and real per capita GDP growth rate from 1980 to 2015, and applies Moran's model to the central, Western and eastern parts of China The results show that the spatial correlation of the development and growth of the eastern region is increasing year by year, the central region shows a fluctuating trend, and the spatial correlation of the western region shows a downward trend The change trend of I value predicts that the imbalance of regional development in China is gradually changing to the national development balance, which is consistent with the actual situation in China. It proves that the model combined with Moran's I index test is accurate and the prediction results are reliable.
Research and simulation of network security situation prediction algorithm
Authors: Li Zhengmao , Ma Tingting , Zhou Yanling , Wang Xianhui 
Published: June 2021

Abstract
Monitoring and predicting the security state of network environment is the key to solve network security. On the basis of studying the principle of network security situation awareness, a network security situation prediction model based on artificial immunity and Kalman algorithm is designed according to the artificial immunity evaluation model. First, Wireshark software was used to analyse DARPA99 dataset. Then, the situation value was obtained by using the artificial immune evaluation model. In the Curver Fitting Tool, the Kalman algorithm is written to achieve the optimal prediction of the situation value. The test results show that the model has a good prediction effect.
Research on impulse response and variance decomposition analysis of co-integrated systems
Authors: Wang Yang-Chao , Tsai Jui-Jung , Dong Yueying 
Published: June 2021

Abstract
The cointegration test explores whether a relationship of long-term equilibrium exists between the multi-dimensional series. It helps to exclude the possibility of spurious regression. As for the vector auto-regressive (VAR) model, it describes the interrelationship between endogenous variables. With impulse response and variance decomposition, the VAR model can further capture the dynamic response path of the dependent variable after being impacted by other variables, and the contribution rates of different variables to the impulse response of the dependent variable. In this paper, impulse response and variance decomposition analysis of cointegrated systems are adopted based on the VAR model to evaluate measurable data of RMB internationalization. The framework consists of four steps. First, the long-term equilibrium between variables after confirming the existence of cointegration relationship is explored. Second, the VAR model is adopted to consider the endogeneity between variables. Then, through the impulse response function, the dynamic response path of the system impacted by unit impulse is observed. Finally, combined with variance decomposition, further analysis is taken to realize the contribution rates of variables to the impulse. The results show that foreign influencement has the greatest impact on RMB internationalization, followed by foreign exchange reserves. However, the corresponding paths of RMB internationalization still requires to be adjusted.
Application of Error Correction model with monetary function factors in the return of bitcoin
Authors: Liang Huan 
Published: June 2021

Abstract
Bitcoin is a kind of virtual currency based on block chain technology. In many scenarios, it shows the function of currency to a certain extent. However, many believe that the value of Bitcoin is hollow, speculative and unable to undertake monetary functions, which prevents it to circulate as a real currency. This paper assumes that Bitcoin can undertake monetary functions, which can verify the relationship between monetary functions and Bitcoin earnings. According to the availability of the data and the previous research results, the monthly value of the indexes to measure the monetary function from 2010 to 2020 are selected to form a regression equation with the monthly return data of Bitcoin in the corresponding period. ADF test shows that the explained variable is a first-order simple integer, and the explanatory variables have both first-order simple integer and stationary sequence, and there is a cointegration relationship between them. The result of error correction model shows that the relationship between Bitcoin rate of return and the relevant indicators to measure monetary function is not significant, which rejects the original assumption that Bitcoin can assume monetary function, indicating that Bitcoin does not have the ability and potential to assume monetary function. This may be due to the speculative nature of Bitcoin and the lack of powerful credit support. Therefore, investment in Bitcoin needs to be cautiously thought, but the blockchain technology used in Bitcoin needs to be vigorously developed, which could lead to a technological revolution; in addition, it is momentous for countries to develop digital currencies of central bank to meet the challenge.
Application of time series model and deep learning method in measuring the impact of COVID-19 on agriculture in Hubei, China
Authors: Zou Yonghong , Wang Jiaojiao 
Published: June 2021

Abstract
Taking the agricultural situation of Hubei Province as the research object, this paper uses the time series ARIMA model, ARMA model and deep learning LSTM neural network model to explore the impact of COVID-19 on the agriculture of Hubei Province. Three main indicators are screened out to measure the development of agricultural economy, that is, gross regional product, gross output value of agriculture, forestry, animal husbandry and fishery, agricultural product production price index. Based on the quarterly data of indicators from 2001 to 2019 from the National Bureau of Statistics, three indicators in Hubei Province in the first quarter and the second quarter of 2020 are predicted by using the deep learning-based time series ARIMA model, ARMA model and LSTM neural network model. By comparing the predicted data with the real data, the impact of COVID-19 is measured on the agricultural situation of Hubei Province. It was found that COVID-19 had a great impact on the agricultural situation of Hubei Province in both of the first and second quarters of 2020, with the impact in the first quarter being greater than that in the second quarter. At the same time, the prediction accuracy of the two methods is compared to find that the time series model is more effective and reliable in predicting the agricultural product price index. The LSTM neural network model with a long and short term memory has a good prediction effect on the regional gross product and the total output value of agriculture, forestry, animal husbandry and fishery.
Structural design and thermal performance analysis of hybrid electric vehicle battery pack cooling system
Authors: Sun Ye , Wang Yibo 
Published: June 2021

Abstract
In this paper, the flow channel structure and battery of battery cooling system are taken as the research object, and the heat transfer simulation is carried out. In order to analyze the temperature and influencing factors of battery pack in the initial scheme of cooling system structure at high ambient temperature of 40 °C, 50 °C and 60 °C, the temperature of battery pack under many working conditions is simulated, and then the optimization scheme is put forward, and the feasibility of the two schemes is compared with that of the initial scheme.
The cosmological effect of N-entangled state in multiverse
Authors: Trenggana A , Zen F P 
Published: June 2021

Abstract
We investigate the effect of quantum entanglement betwen N-causally disconnected universes by calculated the power spectrum of quantum fluctuation. To investigate it the general from of N-quantum state and specific N-entangled state(GHZ and W state) are used. We found that the power spectrum has the maximum value when the state is near to pure one particle state. For the specific N-entangled state, the power spectrum of W state is equal to pure vacuum state when the amount of N-causally disconnected universes is near to infinite and for GHZ state the power spectrum has same value for every N-causally disconnected universes.
The Geophysics evidence for fault in Tertiary, Pre-Tertiary deposits rock of Lok Ulo central Java, revealed by Gravity data
Authors: Laesanpura A , Wahyudi E J , Parnadi W , Gunawan W 
Published: June 2021

Abstract
Lok Ulo is a mayor river extended from north to South Kebumen. Area is famous pre-tertiary basement rock exposed to the surface. The evidence of fault directly is difficult due to in part by thick weathering surface, and second it could be hidden beneath the river. The gravity instrument of micro Gal precision is running to overcome the problem across the area where anticline valley is very subtle. Geology reconstruction is doing, but the geophysics evidence is giving another solution. The anomalous of 2.5 mGal is because of 1.5 km downthrown block. The reconciliation finally deducted, hence the fault is separating two block. Therefore, the thickness of sedimentary rock is becoming into two parts, the west and east. The throw of fault shows significant separating the mélange complex from the others. The gravity data is estimating the fault take deep seated origin. The thickness claystone of tertiary sedimentary is covering the mélange (the older one) and separating each other. By consequence, the sediments formation in east part is thicker than the west.
Subsurface Structure around Mas Crater of Papandayan Volcano based on Magnetotelluric and Geomagnetic Data
Authors: Diba Dieno , Nurhasan  , Sutarno Doddy , Ogawa Yasuo 
Published: June 2021

Abstract
Papandayan is a hydrothermally active volcano in Indonesia. We revealed the subsurface structure around the Mas Crater area of Papandayan based on the magnetotelluric (MT) and geomagnetic (GM) method. For the MT method, 14 sounding stations were deployed and two of them are located close to the active fumaroles. We estimated the MT response functions using a remote reference and then modeled the data with the aid of a 1-D robust inversion. The resistivity structure can generally be divided into three layers, namely a thin resistive surface layer, a middle conductive layer, and a more resistive basement. We interpreted the middle layer to be the hydrothermal zone or clay mineral. For the GM method, we measured the total intensity at 19 data points. The IGRF and diurnal variation were subtracted from the raw data. We then obtained the 2-D magnetic susceptibility model of magnetic field anomaly using an Occam inversion. The model shows a significantly low susceptibility structure beneath the fumaroles which might correlate with thermally demagnetized rocks.
Neutronic Performances of 100 MWe MSR with Weapon Grade Plutonium Fuel
Authors: Wulandari C , Waris A , Permana S , Pramuditya S 
Published: June 2021

Abstract
An advanced nuclear reactor Generation IV, called Molten Salt Reactor (MSR), has been developed with Thorium utilization for a sustainable energy system. In this paper, the study is focused in the neutronic calculation of 250 MWt/100 MWe MSR with Thorium-Plutonium (Th-Pu) fuel salt for 5 years time operation. Fuel salt is composed of a eutectic FLiBe, Th, and Pu, as a coolant, fertile, and fissile nuclide, respectively. Pu loaded is a weapon-grade which consist of 238Pu, 239Pu, 240Pu, 241Pu, 242Pu, and 241Am. The reactor is operated in the thermal energy range and moderated by the graphite. The reactor design is calculated in neutronic terms with program code CITATION in SRAC 2006 with JENDL 4.0 as a nuclear data library. The result shows some neutronic parameter changes with increasing Plutonium loaded and the reactor criticality is obtained for 5 years by minimal loaded of PuF4 of 2.41%mol. The utilization of Plutonium is described as a capability of MSR in burning a high-level waste of nuclear and radioactive isotopes. This system can be dedicated to future cleaning energy production in a nuclear reactor.
Determination of Motility and Charge Type of Mencit Sperm (Mus musculus) Through Study of Exposure Electrical Fields
Authors: Trimayanti E , Khotimah S N , Wibowo I , Viridi S 
Published: June 2021

Abstract
Analysis of sperm quality is still one of the most important tools for evaluating a man’s fertility. Sperm quality includes several aspects including motility and viability. Mice (Mus musculus) are usually used as experimental animals because the reproductive system is almost the same as human. The purpose of this study is to determine the motility, viability, and type of charge of sperm mice (Mus muculus) through the study of exposure electric fields in an ex vivo condition. Observations were made in the time At for sperm without influence and influenced by an electric field. Mice sperm is diluted with a solution of Phosphate Buffered Saline (PBS). The liquid is inserted into the hemocytometer and then placed between two iron plates connected with a DC voltage source. The distance between the two plates d = 7.0 cm. The magnitude of the voltage used is Δv = 0 (control) and Δv = 12.5 V. Sperm movement was observed using a fluorescence microscope then recorded using NIS Elements software. Then the movement of sperm is analyzed using Tracker software. Sperm without an electric field (Δv = 0) has a viability of 60 minutes longer than sperm affected by an electric field (ΔV = 12.5 V) which has a viability of 30 minutes. The sperms move almost randomly in all directions without the influence of the electric field but tend to move to a positive plate when under the influence of the electric field. Based on the direction of the movement of mice sperm, the sperm is thought to be negatively charged. From the results of this study, it was found that the fast zig-zag motion had a velocity v > 37 μm/s.
Shear velocity inversion from ambient seismic noise using RR-PSO: a case study of Nusa Tenggara Island
Authors: Farduwin A , Yudistira T 
Published: June 2021

Abstract
Ridge regression particle swarm optimization (RR-PSO) is an optimization technique based on the simulation of social behavior of some animal swarm that has been successfully used in many different engineering fields. In this study, RR-PSO was used to invert Rayleigh wave phase velocity curves that extracted from ambient seismic noise records to obtain the shear velocity (Vs) profile. The optimization algorithm is relatively faster, stable and the important aspect is that can provide uncertainty information of the inversion results. In order to determine the capabilities of the RR-PSO algorithm, the synthetic simulation was carried out using both noise-free and noise-contaminated data. The validity test includes the calculation of similarity index and estimation of the model uncertainty using their standard deviation. Based on the resulted model, the convergence of RR-PSO algorithm is relatively faster, stable and adaptable to some level of noise and can provide good model estimation of the subsurface. The application of RR-PSO to the real dispersion curve data is carried out in order to determine the seismic crustal structure beneath Nusa Tenggara islands.
A Stable Photoluminescence of Waste Derived Acrylic Plastics (PMMA) and MAPbBr 3 Composite Film
Authors: Mahen E C S , Nuryadin B W , Permatasari F A , Aimon A H , Suprijadi  , Iskandar F 
Published: June 2021

Abstract
This paper reports the synthesis and characterization of a composite thin of waste-derived acrylic plastic (PMMA) and MAPbBr 3 perovskite nanocrystal that prepared by ligand assisted re-precipitation (LARP) method. The composite thin film prepared from MABr, PbBr2, oleic acid and oleyl amine, N, N-dimethylformamide (DMF) as a precursor, toluene as a solvent, and waste-derived PMMA as polymer, and then deposited on glass substrate using a spin coater with different speed. As a result, the highest transmittance value was around 90% for the sample with a high spin speed (3000 rpm). The photoluminescence of MAPbBr3 film, when illuminated by UV shows a bright green color with a peak at 536 nm wavelength and maximum luminescence found in the sample with the lower spin speed (1000 rpm). Thus, the fabricated perovskite composite thin film using recycled acrylic plastic has a good prospect to be applied in optoelectronic application.
Towards a method for quantitative evaluation of nanoparticle from suspensions via microarray printing and SEM analysis
Authors: Bennet F , Burr L , Schmid D , Hodoroaba V-D 
Published: June 2021

Abstract
As part of the development of a library of accurate and efficient methods for measurement of nanoparticle properties, we develop and optimize a method for the efficient analysis of nanoparticle size distribution from suspensions via microprinting and digital analysis of electron microscopy (SEM and TEM) images, with the ultimate aim of automated quantitative concentration analysis (calculated from drop volume). A series of different nanoparticle suspensions (gold, latex, and SiO2 in varying sizes and concentrations) were printed onto TEM grids in a 4 x 4 array in the concentration range 7×108 to 1×1011 nanoparticles/mL and imaged with SEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee-ring effect.
Safety and Efficacy of OncoTherad Nano-immunotherapy in Patients with Non-Muscle Invasive Bladder Cancer
Authors: Alonso J C C , Maciel M C , Ferrari H A , Gonçalves J M , Sasaki B R S , Cintra A A , Durán N , Billis A , Fávaro W J 
Published: June 2021

Abstract
The new modalities for treating patients with non-muscle invasive bladder cancer (NMIBC) for whom Bacillus Calmette-Guerin (BCG) has failed or is contraindicated are recently increasing due to the development of new drugs. In this scenario, a new perspective is represented by OncoTherad nano-immunotherapy. We carried out a prospective, single-center (Municipal Hospital of Paulínia, São Paulo, Brazil), single-arm phase I/II study (Clinical Trial: RBR-6swqd2) in 29 (18 male, 11 female) patients with BCG-refractory, relapsed or intolerant NMIBC (≥ 1 previous course of BCG therapy). The median age of the 29 patients and follow-up were 65 years (range 34-96) and 24 months, respectively. OncoTherad treatment showed complete response of 79.3% and recurrence-free survival of 22.2 months at 24-month follow-up. Regarding toxicity, 62.1% of adverse events were Grade 1 or 2. The most commonly reported treatment-related adverse events were dysuria, cystitis, pruritus, rash, arthralgia and fatigue. Also, this study demonstrated an important effect of activation of the Toll-like Receptor 4 (TLR4) signaling pathway triggered by OncoTherad in the formation and organization of primary lymphoid follicles in most patients at 24-months follow-up, which may be related to antitumor and immunoprotective effects from this immunotherapy in bladder tissue. In conclusion, OncoTherad nano-immunotherapy seems a safe and effective treatment option for BCG-relapsed and/or intravesical chemotherapy-relapsed NMIBC patients and may provide benefit for preventing tumor recurrence.