bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Apple Orchard Planting Year Based on Spatiotemporally Fused Satellite Images and Clustering Analysis of Foliage Phenophase
Authors: Zhu Yaohui , Yang Guijun , Yang Hao , Wu Jintao , Lei Lei , Zhao Fa , Fan Lingling , Zhao Chunjiang
Published: April 2020

The planting year of apple orchard not only determines the fruit output but also provides information for the governmental management of the fruit industry. However, considering that different orchards use different management and cultivation methods, this may result in some trees having similar outlines but different planting years, and it is, therefore, difficult to effectively determine the actual planting year based on textural or structural characteristics. Therefore, the monitoring method provided in this paper is not to monitor the growing year positively from the planting of orchard seedlings but to use time series remote sensing data to reverse determine the continuous growth age of each existing orchard. The city of Qixia, Shandong Province, China, was used as a case study. Firstly, the spatial distribution of apple orchards was accurately extracted using the Sentinel-2 normalized difference vegetation index (NDVI) spatiotemporally fused images and phenological vegetation information. Secondly, using region of interest (ROI) data for different vegetation types obtained from a field survey, NDVI time series were extracted from the Sentinel-2 NDVI spatiotemporally fused image. Among them, three characteristic phenological periods were selected, and the NDVI time series for apple orchards was used as a template to extract the apple orchard distribution area from 2000 to 2017. Then, the distribution area of apple orchards was defined as the area of interest in the planting year, combined with the Landsat NDVI time series image composed of three characteristic phenological periods each year from 2000 to 2017, and the apple orchard phenological curve. Subsequently, a Euclidean distance (ED) method was used to calculate the distribution area of apple orchards for each year between 2000 and 2017. Finally, a pixel-by-pixel inverse time series calculation method was used to obtain the planting year of apple orchards in the study area. This study provides a new way to accurately identify the planting year of apple orchards using satellite remote sensing images.
A Random Forest Modelling Procedure for a Multi-Sensor Assessment of Tree Species Diversity
Authors: Mallinis Giorgos , Chrysafis Irene , Korakis Georgios , Pana Eleanna , Kyriazopoulos Apostolos P.
Published: April 2020

Earth observation data can provide important information for tree species diversity mapping and monitoring. The relatively recent advances in remote sensing data characteristics and processing systems elevate the potential of satellite imagery for providing accurate, timely, consistent, and robust spatially explicit estimates of tree species diversity over forest ecosystems. This study was conducted in Northern Pindos National Park, the largest terrestrial park in Greece and aimed to assess the potential of four satellite sensors with different instrumental characteristics, for the estimation of tree diversity. Through field measurements, we originally quantified two diversity indices, namely the Shannon diversity index (H’) and Simpson’s diversity (D1). Random forest regression models were developed for associating remotely sensed spectral signal with tree species diversity within the area. The models generated from the use of the WorldView-2 image were the most accurate with a coefficient of determination of up to 0.44 for H’ and 0.37 for D1. The Sentinel-2 -based models of tree species diversity performed slightly worse, but were better than the Landsat-8 and RapidEye models. The coefficient of variation quantifying internal variability of spectral values within each plot provided little or no usage for improving the modelling accuracy. Our results suggest that very-high-spatial-resolution imagery provides the most important information for the assessment of tree species diversity in heterogeneous Mediterranean ecosystems.
Drill-Core Mineral Abundance Estimation Using Hyperspectral and High-Resolution Mineralogical Data
Authors: Tuşa Laura , Khodadadzadeh Mahdi , Contreras Cecilia , Rafiezadeh Shahi Kasra , Fuchs Margret , Gloaguen Richard , Gutzmer Jens
Published: April 2020

Due to the extensive drilling performed every year in exploration campaigns for the discovery and evaluation of ore deposits, drill-core mapping is becoming an essential step. While valuable mineralogical information is extracted during core logging by on-site geologists, the process is time consuming and dependent on the observer and individual background. Hyperspectral short-wave infrared (SWIR) data is used in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. Additionally, Scanning Electron Microscopy-based image analyses using a Mineral Liberation Analyser (SEM-MLA) provide exhaustive high-resolution mineralogical maps, but can only be performed on small areas of the drill-cores. We propose to use machine learning algorithms to combine the two data types and upscale the quantitative SEM-MLA mineralogical data to drill-core scale. This way, quasi-quantitative maps over entire drill-core samples are obtained. Our upscaling approach increases result transparency and reproducibility by employing physical-based data acquisition (hyperspectral imaging) combined with mathematical models (machine learning). The procedure is tested on 5 drill-core samples with varying training data using random forests, support vector machines and neural network regression models. The obtained mineral abundance maps are further used for the extraction of mineralogical parameters such as mineral association.
Cloud Detection: An Assessment Study from the ESA Round Robin Exercise for PROBA-V
Authors: Amato Umberto , Antoniadis Anestis , Carfora Maria Francesca
Published: April 2020

A Round Robin exercise was implemented by ESA to compare different classification methods in detecting clouds from images taken by the PROBA-V sensor. A high-quality dataset of 1350 reflectances and Clear/Cloudy corresponding labels had been prepared by ESA in the framework of the exercise. Motivated by both the experience acquired by one of the authors in this exercise and the availability of such a reliable annotated dataset, we present a full assessment of the methodology proposed therein. Our objective is also to investigate specific issues related to cloud detection when remotely sensed images comprise only a few spectral bands in the visible and near-infrared. For this purpose, we consider a bunch of well-known classification methods. First, we demonstrate the feasibility of using a training dataset semi-automatically obtained from other accurate algorithms. In addition, we investigate the effect of ancillary information, e.g., surface type or climate, on accuracy. Then we compare the different classification methods using the same training dataset under different configurations. We also perform a consensus analysis aimed at estimating the degree of mutual agreement among classification methods in detecting Clear or Cloudy sky conditions.
Rapid Yeast Cell Viability Analysis by Using a Portable Microscope Based on the Fiber Optic Array and Simple Image Processing
Authors: Wang Weiming , Liu Hang , Yu Yan , Cong Fengyu , Yu Jun
Published: April 2020

A fiber optic array (FOA) can be used as an alternative or a supplement to the lens in a microscope due to its large magnification, high coupling efficiency and extremely low distortion. Based on our previous research, this paper first demonstrated the resolution and field-of-view (FOV) of the microscope based on the FOA. To further validate the FOA microscope’s imaging capability, yeast activity and concentration were investigated by simple image processing. The results showed that the percentages of live and dead yeast cells correctly identified were 92.1% and 84.8%, except for the clusters, which agreed well with the manual counting methods. Then, the performances of the portable microscopes based on the FOA and lens were compared and the factors that affect the FOA microscope imaging performance were analyzed.
Wireless Sensor Networks for Noise Measurement and Acoustic Event Recognitions in Urban Environments
Authors: Luo Liyan , Qin Hongming , Song Xiyu , Wang Mei , Qiu Hongbing , Zhou Zou
Published: April 2020

Nowadays, urban noise emerges as a distinct threat to people’s physiological and psychological health. Previous works mainly focus on the measurement and mapping of the noise by using Wireless Acoustic Sensor Networks (WASNs) and further propose some methods that can effectively reduce the noise pollution in urban environments. In addition, the research on the combination of environmental noise measurement and acoustic events recognition are rapidly progressing. In a real-life application, there still exists the challenges on the hardware design with enough computational capacity, the reduction of data amount with a reasonable method, the acoustic recognition with CNNs, and the deployment for the long-term outdoor monitoring. In this paper, we develop a novel system that utilizes the WASNs to monitor the urban noise and recognize acoustic events with a high performance. Specifically, the proposed system mainly includes the following three stages: (1) We used multiple sensor nodes that are equipped with various hardware devices and performed with assorted signal processing methods to capture noise levels and audio data; (2) the Convolutional Neural Networks (CNNs) take such captured data as inputs and classify them into different labels such as car horn, shout, crash, explosion; (3) we design a monitoring platform to visualize noise maps, acoustic event information, and noise statistics. Most importantly, we consider how to design effective sensor nodes in terms of cost, data transmission, and outdoor deployment. Experimental results demonstrate that the proposed system can measure the urban noise and recognize acoustic events with a high performance in real-life scenarios.
Influence of Rotor Dynamic Scattering on Helicopter Radar Cross-Section
Authors: Zhou Zeyang , Huang Jun
Published: April 2020

With the continuous improvement and development of armed helicopters, the research on their stealth characteristics has become more and more in depth. In order to obtain the complex effect of stealth characteristics caused by the high-speed rotation of rotor-like components, a dynamic scattering method (DSM) is presented. Rotation speed, azimuth, elevation angle, pitching angle, and rolling angle are studied and discussed in detail. The results show that the electromagnetic scattering characteristics of the main rotor and tail rotor are dynamic and periodic. This period characteristic is related to the rotation speed and attitude angle of the rotor. The radar cross-section (RCS) of the helicopter varies greatly at different observation angles and attitude angles, but the dynamic electromagnetic scattering effect caused by the main rotor and tail rotor cannot be ignored. The presented DSM is effective and efficient for studying the dynamic RCS of the rotor-type parts of a helicopter or the whole machine.
Temperature and Emissivity Inversion Accuracy of Spectral Parameter Changes and Noise of Hyperspectral Thermal Infrared Imaging Spectrometers
Authors: Shao Honglan , Liu Chengyu , Li Chunlai , Wang Jianyu , Xie Feng
Published: April 2020

The emergence of hyperspectral thermal infrared imaging spectrometers makes it possible to retrieve both the land surface temperature (LST) and the land surface emissivity (LSE) simultaneously. However, few articles focus on the problem of how the instrument’s spectral parameters and instrument noise level affect the LST and LSE inversion errors. In terms of instrument development, this article simulated three groups of hyperspectral thermal infrared data with three common spectral parameters and each group of data includes tens of millions of simulated radiances of 1525 emissivity curves with 17 center wavelength shift ratios, 6 full width at half maximum (FWHM) change ratios and 6 noise equivalent differential temperatures (NEDTs) under 15 atmospheric conditions with 6 object temperatures, inverted them by two temperature and emissivity separation methods (ISSTES and ARTEMISS), and analyzed quantitatively the effects of the spectral parameters change and noise of an instrument on the LST and LSE inversion errors. The results show that: (1) center wavelength shifts and noise affect the inversion errors strongly, while FWHM changes affect them weakly; (2) the LST and LSE inversion errors increase with the center wavelength shift ratio in a quadratic function and increase with FWHM change ratio slowly and linearly for both the inversion methods, however they increase with NEDT in an S-curve for ISSTES while they increase with NEDT slightly and linearly for ARTEMISS. During the design and development of a hyperspectral thermal infrared instrument, it is highly recommended to keep the potential center wavelength shift within 1 band and keep NEDT within 0.1K (corresponding LST error < 1K and LSE error < 0.015) for normal applications and within 0.03K (corresponding LST error < 0.5K and LSE error < 0.01) for better application effect and level.
Experimental Investigation and CFD Modeling of Slush Cryogen Flow Measurement Using Circular Shape Capacitors
Authors: Monea Bogdan Florian , Ionete Eusebiu Ilarian , Spiridon Stefan Ionut
Published: April 2020

The measurement of two-phase cryogenic fluid mixtures flow, also known as slush cryogen flow, with its most attractive form (liquid and solid) is of great interest for various applications, due to its thermodynamic advantages. This paper presents a newly developed device, under the form of a circular capacitor prototype, together with an experimental stand for slush formation. Slush nitrogen was used as testing fluid during the experimental work. Then, the experimental data for slush cryogen flow measurement using the proposed circular shape capacitor were compared with theoretical results obtained by simulation. A three-dimensional flow field model was built and solved for the innovative design slush flowmeter using a computational fluid dynamic (CFD) model. Nitrogen slush density of 874 kg/m3, representing approximately 30% solid fraction, was reported for both the modeling and experimental testing, although the numerical investigation is not limited to these values. By comparing experimental vs. simulation results, a deeper view on the designed configuration can be achieved, thus improving the progress in producing high-performance next generation devices for two-phase flow measurement in terms of physical dimensions, length and space between armatures. Even so, the mathematical model has limitations when mixtures with higher percentages of solid phase and particle sizes are encountered.
Prediction of I–V Characteristic Curve for Photovoltaic Modules Based on Convolutional Neural Network
Authors: Li Jie , Li Runran , Jia Yuanjie , Zhang Zhixin
Published: April 2020

Photovoltaic (PV) modules are exposed to the outside, which is affected by radiation, the temperature of the PV module back-surface, relative humidity, atmospheric pressure and other factors, which makes it difficult to test and analyze the performance of photovoltaic modules. Traditionally, the equivalent circuit method is used to analyze the performance of PV modules, but there are large errors. In this paper—based on machine learning methods and large amounts of photovoltaic test data—convolutional neural network (CNN) and multilayer perceptron (MLP) neural network models are established to predict the I–V curve of photovoltaic modules. Furthermore, the accuracy and the fitting degree of these methods for current–voltage (I–V) curve prediction are compared in detail. The results show that the prediction accuracy of the CNN and MLP neural network model is significantly better than that of the traditional equivalent circuit models. Compared with MLP models, the CNN model has better accuracy and fitting degree. In addition, the error distribution concentration of CNN has better robustness and the pre-test curve is smoother and has better nonlinear segment fitting effects. Thus, the CNN is superior to MLP model and the traditional equivalent circuit model in complex climate conditions. CNN is a high-confidence method to predict the performance of PV modules.
Spectrum Analysis of Gravity Waves Based on Sensors Mounted on a New Round-Trip Airborne Flat-Floating Sounding System
Authors: He Yang , Sheng Zheng , Zhang Jie , He Mingyuan , Zhou Shudao
Published: April 2020

In this study, sensors mounted on a new type of round-trip airborne flat-floating sounding system (RTAFSS) were used to obtain the observation data of the three stages of "rising, flat-floating and falling". This new sounding method has a good application prospect. We performed spectrum analysis on the normalized temperature fluctuation, and the vertical wavenumber spectrum from the rising and falling stages and the horizontal wavenumber spectrum from the flat-floating stage were obtained. This is the first time the complete gravity wave spectrum characteristics were obtained from three consecutive stages: rising, flat-floating and falling. The results show that the gravity wave spectrum of the three stages can be well obtained by RTAFSS. For the horizontal wavenumber spectrum, the spectral slope is basically around −2, and the difference in the spectral structure of the horizontal wave number spectrum may be due to the intermittent turbulent activity and the variable intensity of the gravitational wave during its propagation. This study aims to make experimental exploration of the spectrum characteristics of gravity waves by this new type of observation data. It is expected to reveal the spectrum characteristics of horizontal wavenumber in the stratosphere region of China, providing a theoretical basis for spectrum analysis in a wider space–time range after further network observation of RTAFSS.
A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning
Authors: Silveira Kupssinskü Lucas , Thomassim Guimarães Tainá , Menezes de Souza Eniuce , C. Zanotta Daniel , Roberto Veronez Mauricio , Gonzaga Luiz , Mauad Frederico Fábio
Published: April 2020

Total Suspended Solids (TSS) and chlorophyll-a concentration are two critical parameters to monitor water quality. Since directly collecting samples for laboratory analysis can be expensive, this paper presents a methodology to estimate this information through remote sensing and Machine Learning (ML) techniques. TSS and chlorophyll-a are optically active components, therefore enabling measurement by remote sensing. Two study cases in distinct water bodies are performed, and those cases use different spatial resolution data from Sentinel-2 spectral images and unmanned aerial vehicles together with laboratory analysis data. In consonance with the methodology, supervised ML algorithms are trained to predict the concentration of TSS and chlorophyll-a. The predictions are evaluated separately in both study areas, where both TSS and chlorophyll-a models achieved R-squared values above 0.8.
Responsible Governance and the Sustainability of Populist Public Policies. The Implications of Wage-Led Growth Strategy in Romania
Authors: Avram Alexandru , Barna Flavia Maria , Năchescu Miruna Lucia , Avram Costin Daniel , Avram Roxana Loredana
Published: April 2020

In the present paper, we focus on the macroeconomic implications of the populist public policies and in particular on the effects of wage led growth strategy, which started to be applied in Romania from January 2017. Such a study is important as a practical example of applying this particular wage related public policy and sets the premises for analyzing its sustainability and its macroeconomic implications and costs. For analyzing the implications of the wage-led growth strategy upon the sustainability of macroeconomic variables, we have used an unrestricted VAR (vector auto regressive) and compared the effect of the impulse response functions with the recent evolutions of the Romanian economy. Thus, we have observed the effect of the wage led growth strategy, by using the average wage, trade deficit, number of employees, inflation rate, labor productivity, and minimum wage as variables. Our study shows that the wage-led growth policy had a strong positive impact on the number of employees and on inflation, increasing it, but a negative impact on productivity. In addition, we have seen a strong positive impact on increasing the trade deficit. These particular evolutions have left the Romanian economy with almost no fiscal and monetary space of maneuver in the face of the exogenous shock produced by the pandemic.
Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing
Authors: Xu Dandan , Bian Yang , Shu Shinan
Published: April 2020

As a clean, sustainable transport tool, bicycles have significant advantages in short-distance travel. Despite many efforts assumed in Beijing to improve the cycling environment, the popularity of cycling remains relatively low. However, the advent of the free-floating bike-sharing (FFBS) system has engendered an unexpected cycling enthusiasm in Beijing. Therefore, it is of great importance to delve into why travelers prefer FFBS as a transportation form from a psychological perspective. In this paper, 352 valid questionnaires were collected from an online survey, and an extended theory of planned behavior (TPB) was adopted to examine the psychological determinants of intention and actual behavior to use FFBS. The results showed that men and car-owners prefer vehicles and show a lower willingness to use FFBS. In contrast, residents under the age of 60, residents with FFBS riding experience, and residents skilled in cycling are inclined to use FFBS; the economic convenience of FFBS is the most important attractant for FFBS, while bad weather is the biggest hindrance factor for residents to use FFBS; however, imperfection in infrastructure has no significant impact on reducing residents’ willingness to use FFBS. These results have important implications for planners to better understand the FFBS use behavior, and several suggestions are proposed to support the policymaking about FFBS.
Low-End Lock-In of Chinese Equipment Manufacturing Industry and the Global Value Chain
Authors: Li Yan , Sun Huiying , Huang Jincheng , Huang Qingbo
Published: April 2020

This paper focuses on the low-end lock-in problem faced by China’s equipment manufacturing industry, which is heavily involved in the global value chain (GVC). Specifically, we use the production chain length system and total trade accounting framework to measure some physical and economic location indicators. The physical location measures the forward production length, backward production length, and the location index, whereas the economic location measures various types of value-added in industry exports. The results show that China’s equipment manufacturing industry has deepened its physical and economic low-end lock-in with the gradual deepening of China’s equipment manufacturing industry’s participation in GVC. From a segmented perspective, the manufacture of fabricated metal products (except machinery and equipment) and electrical equipment has the deepest degree of low-end lock-in physical location; the manufacture of computer, electronic, and optical products has the deepest degree of economic low-end lock-in. Therefore, China should accelerate its breakthroughs in the low-end locking dilemma and climb the GVC by adopting various measures such as accelerating the implementation of the intelligent manufacturing strategy, developing service-oriented equipment manufacturing industries, cultivating the domestic market, realizing low-carbon manufacturing, and improving enterprises’ independent innovation capabilities.
Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves
Authors: Gil-González Walter , Montoya Oscar Danilo , Grisales-Noreña Luis Fernando , Perea-Moreno Alberto-Jesus , Hernandez-Escobedo Quetzalcoatl
Published: April 2020

This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model.
Chemical Denitrification with Mg0 Particles in Column Systems
Authors: Siciliano Alessio , Curcio Giulia Maria , Limonti Carlo
Published: April 2020

The removal of nitrate from aqueous environments through zero-valent metallic elements is an attractive technique that has gained increasing interest in recent years. In comparison to other metallic elements, zero-valent magnesium (ZVM) has numerous beneficial aspects. Nevertheless, the use of Mg0 particles for nitrate reduction in column systems has not been investigated yet. To overcome the lack of research, in the present study, a wide experimental activity was carried out to develop a chemical denitrification process through ZVM in batch column equipment. Several tests were executed to evaluate the effects of recirculation hydraulic velocity, pH, Mg0 amount, N-NO3− initial concentration and temperature on the process performance. The results show that the process efficiency is positively influenced by the recirculation velocity increase. In particular, the optimal condition was detected with a value of 1 m/min. The process pH was identified as the main operating parameter. At pH 3, abatements higher than 86.6% were reached for every initial nitrate concentration tested. In these conditions, nitrogen gas was detected as the main reaction product. The pH increase up to values of 5 and 7 caused a drastic denitrification decline with observed efficiencies below 26%. At pH 3, the ratio (RMN) between Mg0 and initial nitrate amount also plays a key role in the treatment performance. A characteristic value of about RMN = 0.333 gMg0/mgN-NO3− was found with which it is possible to reach the maximum reaction rate. Unexpectedly, the process was negatively affected by the increase in temperature from 20 to 40 °C. At 20 °C, the material showed satisfactory denitrification efficiencies in subsequent reuse cycles. With the optimal RMN ratio, removals up to 90% were detected by reusing the reactive material three times. By means of a kinetic analysis, a mathematical law able to describe the nitrate abatement curves was defined. Moreover, the relation between the observed kinetic constant and the operating parameters was recognized. Finally, the reaction pathways were proposed and the corrosion reaction products formed during the treatment were identified.
Can Flow Alleviate Anxiety? The Roles of Academic Self-Efficacy and Self-Esteem in Building Psychological Sustainability and Resilience
Authors: Mao Yanhui , Yang Rui , Bonaiuto Marino , Ma Jianhong , Harmat László
Published: April 2020

A growing number of studies suggest that flow experience is associated with life satisfaction, eudaimonic well-being, and the perceived strength of one’s social and place identity. However, little research has placed emphasis on flow and its relations with negative experiences such as anxiety. The current study investigated the relations between flow and anxiety by considering the roles of self-esteem and academic self-efficacy. The study sample included 590 Chinese university students, who were asked to complete a self-report questionnaire on flow, anxiety, self-esteem, and academic self-efficacy. Data were analyzed using structural equation modeling (SEM) with AMOS software, in which both factorial analysis and path analysis were performed. Results revealed that the experience of flow negatively predicted anxiety, and both self-esteem and academic self-efficacy fully mediated the path between flow and anxiety. Specifically, self-esteem played a crucial and complete mediating role in this relationship, while academic self-efficacy mediated the path between self-esteem and anxiety. Our findings enrich the literature on flow experience and help with identifying practical considerations for buffering anxiety and more broadly with fostering strategies for promoting psychological sustainability and resilience.
Research on the Barrier Analysis and Strength Measurement of a Prefabricated Building Design
Authors: Yuan Zhenmin , Ni Guodong , Wang Linxiu , Qiao Yaning , Sun Chengshuang , Xu Na , Wang Wenshun
Published: April 2020

As a sustainable and cleaner type of facility, prefabricated buildings face more design barriers than traditional non-prefabricated buildings. Identifying and managing these barriers is key to improving the success rate of prefabricated building design. However, direct studies on these design barriers are extremely rare. The present study solved this problem by combining multiple methods, including grounded theory (GT), structured self-intersection matrix (SSIM), analytic network process (ANP), and the linear weighted sum method (LWSM). GT was adopted to identify the barriers to prefabricated building design and then SSIM was used to analyze the interactions among them. The eight design barriers were finally identified and classified into three clusters: technical barriers, economic barriers, and management barriers. A further analysis found that there is dependence and feedback among these clusters. The technical barrier cluster and management barrier cluster experience self-feedback. A network model based on ANP was next established to calculate the weights of the barrier elements and then this model was combined with LWSM to evaluate the overall design barrier strength of a project case. The results showed that architectural individualization has the greatest impact on prefabricated building design, followed by the collaborative issues among multiple units and professional designer issues. The overall design barrier strength of the project case was larger. Therefore, the first suggestion provided to the facility management sector is to establish a library for standard house types to achieve architectural design through multihouse combinations.
Comparative Analysis of Indoor Environmental Quality of Architectural Campus Buildings’ Lecture Halls and its’ Perception by Building Users, in Karachi, Pakistan
Authors: Bughio Mushk , Schuetze Thorsten , Mahar Waqas Ahmed
Published: April 2020

Poor Indoor Environmental Quality (IEQ) adversely affects the performance and health of building users. Building users are an important source of information regarding IEQ and its influence on users’ wellbeing and productivity. This paper discusses the analysis and evaluation of IEQ in lecture halls of two public Architectural Campus Buildings (ACB) in Karachi, Pakistan. The method of this research is divided into three parts: (i) An analysis of local climate conditions, (ii) An on-site survey of two existing ACBs to analyze indoor environmental conditions. and (iii) The analysis of users’ satisfaction using a questionnaire survey. The research results showed that users are dissatisfied with existing hot and humid indoor environment conditions caused by interactions of local outdoor climate conditions, the building’s architecture, and inadequate ventilation within the building. The findings revealed that Karachi has 41.3% comfort hours with the warm sub-humid season to be the most comfortable season having 80.56% comfort hours. IEQ analysis unveiled that airflow in ACB1 is low, whereas, high airflow is observed in ACB2. The findings of this research unveiled that cross-ventilation by the adapted placement of openings, improved external shading devices, and provision of increased vegetation are required in both ACBs to achieve a more comfortable IEQ.
Post-M&A Performance and Failure: Implications of Time until Deal Completion
Authors: Thompson Ephraim Kwashie , Kim Changki
Published: April 2020

Firm values change substantially between deal announcement and closing, risking renegotiation or termination. For deals that eventually close, does waiting longer to close benefit the acquirer post-M&A? We investigate whether the time that elapses until deal completion is an indicator of post-M&A performance and failure. We find that deals taking an optimum time to implement perform better, supporting the due diligence hypothesis, while taking too long to close is an indication of poor post-M&A performance and subsequent failure, supporting the overdue hypothesis.
Measurement of the Valuation of Knowledge in Organizations: A Review Analysis
Authors: Mudrychová Kristýna , Houšková Beránková Martina , Houška Milan , Horáková Tereza
Published: April 2020

The purpose of this paper is to address the question of how to measure the value of knowledge in an organization. The study shows how to identify the attributes used to measure this value and identify the relationships between these attributes. As a first step, researchers chose selected 203 studies for review. Then those studies were analyzed through content and contextual analysis. It has been shown that it is possible to identify identical attributes across theoretical works and case studies that are aimed to assess the value of an investment in knowledge. The attributes can be defined and hierarchically structured. The paper provides the basis for establishing a broadly applicable methodology for assessing the value of the investment in knowledge and, consequently, improving the possibilities to determine its effectiveness.
Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model
Authors: Xu Kai , Loh Lawrence , Chen Qiang
Published: April 2020

As China is undergoing economic transformation and facing increasing energy and environmental problems, it is essential to pay special attention to sustainable innovation governance. This research took industrial waste and total energy consumption into consideration and uses a super efficiency slack-based measure (SBM) model to empirically evaluate the regional innovation efficiency of Chinese provinces. The results showed that the efficiency of China’s regional sustainable innovation has not changed significantly over recent years. In addition, the results also showed large and varying degrees of innovation efficiency across different provinces. Eastern China, in comparison to central and western China, showed higher innovation efficiency. In addition, we found a slightly increasing trend in terms of innovation efficiency disparities between the three areas. On the basis of these findings, the reasons for the innovation efficiency gap between different regions were analyzed. The impacts of influential factors on sustainable innovation efficiency were further explored. We found that technology market maturity affected sustainable innovation efficiency positively, while government funding had a negative impact on sustainable innovation efficiency. Industrial structure and environmental regulations had no significant effect on sustainable innovation efficiency. Finally, some implications for improving governance performance in terms of sustainable innovation were provided.
The Cross-Border Mergers and Acquisitions of Local State-Owned Enterprises: The Role of Home Country Government Involvement
Authors: Gu Qiuyang , Ju Chunhua , Bao Fuguang
Published: April 2020

Existing literature tends to treat enterprises as a whole when measuring government intervention. However, in Chinese region-specific institutional development, ultimate control (i.e., local government) tends to control multiple enterprises. This paper considers the enterprises controlled by the same ultimate controller as a portfolio, which is used to measure government intervention by comparing the differences of the enterprises in the portfolio. This paper uses the data of Chinese listed local state-owned enterprises (LSOEs). and we assess whether local state ownership benefits or offsets LSOEs’ cross-border mergers and acquisitions (CBM & A) activities. We propose a new measurement of government intervention to explain the mechanisms through which government influences the cross-border mergers and acquisitions of local SOEs. The experimental results show that government intervention and region-specific marketization institutional development negatively moderate the effect of government internationalization subsidies and government intervention on CBM & A separately. However, government internationalization subsidies, government intervention, and region-specific marketization enhance the CBM & A effect of state ownership separately. This study explores the benefits of government involvement in local SOEs. The value of this paper is to provide a novel perspective, including the intermediary effect of government intervention and the market environment.
Mediating Effects of Cohesion Policy and Institutional Quality on Convergence between EU Regions: An Examination Based on a Conditional Beta-Convergence Model with a 3-Way Multiplicative Term
Authors: Butkus Mindaugas , Mačiulytė-Šniukienė Alma , Matuzevičiūtė Kristina
Published: April 2020

The paper contributes to the existing literature on the EU’s Cohesion Policy outcomes by extending the conditional beta-convergence model with a 3-way multiplicative term to examine the mediating effects of the Cohesion Policy, institutional quality, and their interaction on regional convergence. The empirical analysis based on conditional slope coefficients and conditional standard errors provides evidence that both the mediating factors under consideration contribute positively to boosting regional convergence in the EU at the NUTS 2 and 3 disaggregation level, but with much bigger success over the 2007–2013 programming period compared to the previous one. Moreover, Cohesion Policy and institutional quality act as substituting rather than complementary mediating factors.
Energy Justice in Slum Rehabilitation Housing: An Empirical Exploration of Built Environment Effects on Socio-Cultural Energy Demand
Authors: Debnath Ramit , Simoes Gianna Monteiro Farias , Bardhan Ronita , Leder Solange Maria , Lamberts Roberto , Sunikka-Blank Minna
Published: April 2020

The interaction of energy and buildings institutes a complex socio-technical system that influences the eudemonic well-being of the occupants. Understanding these drivers become even more necessary in impoverished areas where occupants struggle to avail essential energy services. The literature indicates that energy injustice can be addressed through provisioning of comfort, cleanliness, and convenience (3Cs) as critical cultural energy services in low-income areas. This study investigates the socio-architectural influence for slum rehabilitation housing (SRH) on cultural energy services that can promote distributive justice. The methodology adopts an empirical route using data from 200 household surveys from SRH in Mumbai, India, and João Pessoa, Brazil. A model between the 3Cs and socio-architectural elements was established using Firth’s binary logistic regression. The survey results showed that the SRH in Brazil had twice the appliance ownership as compared to the Mumbai SRH. There were distinct energy service preferences in the study areas, despite common poverty burdens. The empirical results showed that the lack of socio-architectural design elements like open spaces, privacy, and walkability in the study areas demanded specific comfort and convenience appliances as a counter-response. A critical policy implication drawn was on the need for socio-architectural inclusive energy planning for distributive justice in poverty. Mitigating rising energy demand through appropriate built environment design of slum rehabilitation housing can contribute to fulfilling the UN’s SDG 7 (clean and affordable energy) and 11 (sustainable cities and communities) goals.
Taxonomy of Three-Qubit Mermin Pentagrams
Authors: Saniga Metod , Holweck Frédéric , Jaffali Hamza
Published: April 2020

Given the fact that the three-qubit symplectic polar space features three different kinds of observables and each of its labeled Fano planes acquires a definite sign, we found that there are 45 distinct types of Mermin pentagrams in this space. A key element of our classification is the fact that any context of such pentagram is associated with a unique (positive or negative) Fano plane. Several intriguing relations between the character of pentagrams’ three-qubit observables and ‘valuedness’ of associated Fano planes are pointed out. In particular, we find two distinct kinds of negative contexts and as many as four positive ones.
Optimal Denoising and Feature Extraction Methods Using Modified CEEMD Combined with Duffing System and Their Applications in Fault Line Selection of Non-Solid-Earthed Network
Authors: Hou Sizu , Guo Wei
Published: April 2020

As the non-solid-earthed network fails, the zero-sequence current of each line is highly non-stationary, and the noise component is serious. This paper proposes a fault line selection method based on modified complementary ensemble empirical mode decomposition (MCEEMD) and the Duffing system. Here, based on generalized composite multiscale permutation entropy (GCMPE) and support vector machine (SVM) for signal randomness detection, the complementary ensemble empirical mode decomposition is modified. The MCEEMD algorithm has good adaptability, and it can restrain the modal aliasing of empirical mode decomposition (EMD) at a certain level. The Duffing system is highly sensitive when the frequency of the external force signal is the same as that of the internal force signal. For automatically identifying chaotic characteristics, by using the texture features of the phase diagram, the method can quickly obtain the numerical criterion of the chaotic nature. Firstly, the zero-sequence current is decomposed into a series of intrinsic mode functions (IMF) to complete the first noise-reduction. Then an optimized smooth denoising model is established to select optimal IMF for signal reconstruction, which can complete the second noise-reduction. Finally, the reconstructed signal is put into the Duffing system. The trisection symmetry phase estimation is used to determine the relative phase of the detection signal. The faulty line in the non-solid-earthed network is selected with the diagram outputted by the Duffing system.
Improved ‘Infotaxis’ Algorithm-Based Cooperative Multi-USV Pollution Source Search Approach in Lake Water Environment
Authors: Huang Xiaoci
Published: April 2020

This paper studies the cooperation method of multi-cooperative Unmanned Surface Vehicles (USVs) for chemical pollution source monitoring in a dynamic water environment. Multiple USVs formed a mobile sensor network in a symmetrical or asymmetrical formation. Based on ‘Infotaxis’ algorithms for multi-USV, an improved shared probability is proposed for solving the problems of low success rate and low efficiency resulting from the cognitive differences of multi-USV in cooperative exploration. By introducing the confidence factor, the cognitive differences between USVs are coordinated. The success rate and the efficiency of exploration are improved. To further optimize the exploration strategy, the particle swarm optimization (PSO) algorithm is introduced into the ‘Infotaxis’ algorithm to plan the USVs’ exploration path. This method is called the ‘PSO-Infotaxis’ algorithm. The effectiveness of the proposed method is verified by simulation and laboratory experiments. A comparison of the test results shows that the ‘PSO-Infotaxis’ algorithm is superior with respect to exploring efficiency. It can reduce the uncertainty of the estimation for source location faster and has lower exploration time, which is most important for the exploration of a large range of water areas.
Noether Symmetries of a Generalized Coupled Lane-Emden-Klein-Gordon-Fock System with Central Symmetry
Authors: Muatjetjeja B. , Mbusi S. O. , Adem A. R.
Published: April 2020

In this paper we carry out a complete Noether symmetry analysis of a generalized coupled Lane-Emden-Klein-Gordon-Fock system with central symmetry. It is shown that several cases transpire for which the Noether symmetries exist. Moreover, we derive conservation laws connected with the admitted Noether symmetries. Furthermore, we fleetingly discuss the physical interpretation of the these conserved vectors.
Well-Posedness for a Class of Degenerate Itô Stochastic Differential Equations with Fully Discontinuous Coefficients
Authors: Lee Haesung , Trutnau Gerald
Published: April 2020

We show uniqueness in law for a general class of stochastic differential equations in R d , d ≥ 2 , with possibly degenerate and/or fully discontinuous locally bounded coefficients among all weak solutions that spend zero time at the points of degeneracy of the dispersion matrix. Points of degeneracy have a d-dimensional Lebesgue–Borel measure zero. Weak existence is obtained for a more general, but not necessarily locally bounded drift coefficient.
Unsubstituted Oximes as Potential Therapeutic Agents
Authors: Surowiak Alicja K. , Lochyński Stanisław , Strub Daniel J.
Published: April 2020

Oximes, which are highly bioactive molecules, have versatile uses in the medical sector and have been indicated to possess biological activity. Certain oximes exist in nature in plants and animals, but they are also obtained by chemical synthesis. Oximes are known for their anti-inflammatory, antimicrobial, antioxidant and anticancer activities. Moreover, they are therapeutic agents against organophosphate (OP) poisoning. Two oximes are already commonly used in therapy. Due to these abilities, new oxime compounds have been synthesized, and their biological activity has been verified. Often, modification of carbonyl compounds into oximes leads to increased activity. Nevertheless, in some cases, oxime activity is connected to the activity of the substrate. Recent works have revealed that new oxime compounds can demonstrate such functions and thus are considered to be potential drugs for pathogenic diseases, as adjuvant therapy in various types of cancer and inflammation and as potential next-generation drugs against OP poisoning.
Existence Results for a Nonlocal Coupled System of Differential Equations Involving Mixed Right and Left Fractional Derivatives and Integrals
Authors: K. Ntouyas Sotiris , Broom Abrar , Alsaedi Ahmed , Saeed Tareq , Ahmad Bashir
Published: April 2020

In this paper, we study the existence and uniqueness of solutions for a new kind of nonlocal four-point fractional integro-differential system involving both left Caputo and right Riemann–Liouville fractional derivatives, and Riemann–Liouville type mixed integrals. The Banach and Schaefer fixed point theorems are used to obtain the desired results. An example illustrating the existence and uniqueness result is presented.