bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Geo-KOMPSAT-2A Algorithm for Sea-Ice Detection Using Himawari-8/AHI Data
Authors: Jin Donghyun , Chung Sung-Rae , Lee Kyeong-Sang , Seo Minji , Choi Sungwon , Seong Noh-Hun , Jung Daeseong , Sim Suyoung , Kim Jinsoo , Han Kyung-Soo
Published: July 2020

Sea ice is an important meteorological factor affecting the global climate system, but it is difficult to observe in sea ice ground truth data because of its location mainly at high latitudes and in polar regions. Accordingly, sea-ice detection research has been actively conducted using satellites, since the 1970s. Polar-orbiting and geostationary satellites are used for this purpose; notably, geostationary satellites are capable of real-time monitoring of specific regions. In this paper, we introduce the Geo-KOMPSAT-2A (GK-2A)/Advanced Meteorological Imager (AMI) sea-ice detection algorithm using Japan Meteorological Agency (JMA) Himawari-8/Advanced Himawari Imager (AHI) data as proxy data. The GK-2A/AMI, which is Korea Meteorological Administration (KMA)’s next-generation geostationary satellite launched in December 2018 and Himawari-8/AHI have optically similar channel data, and the observation area includes East Asia and the Western Pacific. The GK-2A/AMI sea-ice detection algorithm produces sea-ice data with a 10-min temporal resolution, a 2-km spatial resolution and sets the Okhotsk Sea and Bohai Sea, where the sea ice is distributed during the winter in the northern hemisphere. It used National Meteorological Satellite Center (NMSC) cloud mask as the preceding data and a dynamic threshold method instead of the static threshold method that is commonly performed in existing sea-ice detection studies. The dynamic threshold methods for sea-ice detection are dynamic wavelength warping (DWW) and IST0 method. The DWW is a method for determining the similarity by comparing the pattern of reflectance change according to the wavelength of two satellite data. The IST0 method detects sea ice by using the correlation between 11.2-μm brightness temperature (BT11.2) and brightness temperature difference (BTD) [BT11.2–BT12.3] according to ice surface temperature (IST). In addition, the GK-2A/AMI sea-ice detection algorithm reclassified the cloud area into sea ice using a simple test. A comparison of the sea-ice data derived the GK-2A/AMI sea-ice detection algorithm with the S-NPP/visible infrared imaging radiometer suite (VIIRS) sea ice characterization product indicates consistency of 99.0% and inconsistency of 0.9%. The overall accuracy (OA) of GK-2A/AMI sea-ice data with the sea ice region of interest (ROI) data, which is constructed by photo-interpretation method from RGB images, is 97.2%.
Implicit and Explicit Regularization for Optical Flow Estimation
Authors: Karageorgos Konstantinos , Dimou Anastasios , Alvarez Federico , Daras Petros
Published: July 2020

In this paper, two novel and practical regularizing methods are proposed to improve existing neural network architectures for monocular optical flow estimation. The proposed methods aim to alleviate deficiencies of current methods, such as flow leakage across objects and motion consistency within rigid objects, by exploiting contextual information. More specifically, the first regularization method utilizes semantic information during the training process to explicitly regularize the produced optical flow field. The novelty of this method lies in the use of semantic segmentation masks to teach the network to implicitly identify the semantic edges of an object and better reason on the local motion flow. A novel loss function is introduced that takes into account the objects’ boundaries as derived from the semantic segmentation mask to selectively penalize motion inconsistency within an object. The method is architecture agnostic and can be integrated into any neural network without modifying or adding complexity at inference. The second regularization method adds spatial awareness to the input data of the network in order to improve training stability and efficiency. The coordinates of each pixel are used as an additional feature, breaking the invariance properties of the neural network architecture. The additional features are shown to implicitly regularize the optical flow estimation enforcing a consistent flow, while improving both the performance and the convergence time. Finally, the combination of both regularization methods further improves the performance of existing cutting edge architectures in a complementary way, both quantitatively and qualitatively, on popular flow estimation benchmark datasets.
Power Control and Clustering-Based Interference Management for UAV-Assisted Networks
Authors: Zhang Jinxi , Chuai Gang , Gao Weidong
Published: July 2020

Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the huge number of LoS paths in the air-to-ground channel. In this paper, we propose an interference management framework for UAV-assisted networks, consisting of two main modules: power control and UAV clustering. The power control is executed first to adjust the power levels of UAVs. We model the problem of power control for UAV networks as a non-cooperative game which is proved to be an exact potential game and the Nash equilibrium is reached. Next, to further improve system user rate, coordinated multi-point (CoMP) technique is implemented. The cooperative UAV sets are established to serve users and thus transforming the interfering links into useful links. Affinity propagation is applied to build clusters of UAVs based on the interference strength. Simulation results show that the proposed algorithm integrating power control with CoMP can effectively reduce the interference and improve system sum-rate, compared to Non-CoMP scenario. The law of cluster formation is also obtained where the average cluster size and the number of clusters are affected by inter-UAV distance.
Underwater 3D Doppler-Angle Target Tracking with Signal Time Delay
Authors: Su Jun , Li Yaan , Ali Wasiq , Li Xiaohua , Yu Jing
Published: July 2020

The traditional target tracking is a process of estimating the state of a moving target using measurement information obtained by sensors. However, underwater passive acoustic target tracking will confront further challenges, among which the system incomplete observability and time delay caused by the signal propagation create a great impact on tracking performance. Passive acoustic sensors cannot accurately obtain the target range information. The introduction of Doppler frequency measurement can improve the system observability performance; signal time delay cannot be ignored in underwater environments. It varies with time, which has a continuous negative impact on the tracking accuracy. In this paper, the Gauss–Helmert model is introduced to solve this problem by expanding the unknown signal emission time as an unknown variable to the state. This model allows the existence of the previous state and current state at the same time, while handling the implicit equations. To improve the algorithm accuracy, this paper further takes advantage of the estimated state and covariance for the second stage iteration and propose the Gauss–Helmert iterated Unscented Kalman filter under a three-dimensional environment. The simulation shows that the proposed method in this paper shows superior estimation accuracy and more stable performance compared with other filtering algorithms in underwater environments.
A Novel Statistical Method for Scene Classification Based on Multi-Object Categorization and Logistic Regression
Authors: Ahmed Abrar , Jalal Ahmad , Kim Kibum
Published: July 2020

In recent years, interest in scene classification of different indoor-outdoor scene images has increased due to major developments in visual sensor techniques. Scene classification has been demonstrated to be an efficient method for environmental observations but it is a challenging task considering the complexity of multiple objects in scenery images. These images include a combination of different properties and objects i.e., (color, text, and regions) and they are classified on the basis of optimal features. In this paper, an efficient multiclass objects categorization method is proposed for the indoor-outdoor scene classification of scenery images using benchmark datasets. We illustrate two improved methods, fuzzy c-mean and mean shift algorithms, which infer multiple object segmentation in complex images. Multiple object categorization is achieved through multiple kernel learning (MKL), which considers local descriptors and signatures of regions. The relations between multiple objects are then examined by intersection over union algorithm. Finally, scene classification is achieved by using Multi-class Logistic Regression (McLR). Experimental evaluation demonstrated that our scene classification method is superior compared to other conventional methods, especially when dealing with complex images. Our system should be applicable in various domains such as drone targeting, autonomous driving, Global positioning systems, robotics and tourist guide applications.
Towards Breathing as a Sensing Modality in Depth-Based Activity Recognition
Authors: Kempfle Jochen , Van Laerhoven Kristof
Published: July 2020

Depth imaging has, through recent technological advances, become ubiquitous as products become smaller, more affordable, and more precise. Depth cameras have also emerged as a promising modality for activity recognition as they allow detection of users’ body joints and postures. Increased resolutions have now enabled a novel use of depth cameras that facilitate more fine-grained activity descriptors: The remote detection of a person’s breathing by picking up the small distance changes from the user’s chest over time. We propose in this work a novel method to model chest elevation to robustly monitor a user’s respiration, whenever users are sitting or standing, and facing the camera. The method is robust to users occasionally blocking their torso region and is able to provide meaningful breathing features to allow classification in activity recognition tasks. We illustrate that with this method, with specific activities such as paced-breathing meditating, performing breathing exercises, or post-exercise recovery, our model delivers a breathing accuracy that matches that of a commercial respiration chest monitor belt. Results show that the breathing rate can be detected with our method at an accuracy of 92 to 97% from a distance of two metres, outperforming state-of-the-art depth imagining methods especially for non-sedentary persons, and allowing separation of activities in respiration-derived features space.
Enhanced Action Recognition Using Multiple Stream Deep Learning with Optical Flow and Weighted Sum
Authors: Kim Hyunwoo , Park Seokmok , Park Hyeokjin , Paik Joonki
Published: July 2020

Various action recognition approaches have recently been proposed with the aid of three-dimensional (3D) convolution and a multiple stream structure. However, existing methods are sensitive to background and optical flow noise, which prevents from learning the main object in a video frame. Furthermore, they cannot reflect the accuracy of each stream in the process of combining multiple streams. In this paper, we present a novel action recognition method that improves the existing method using optical flow and a multi-stream structure. The proposed method consists of two parts: (i) optical flow enhancement process using image segmentation and (ii) score fusion process by applying weighted sum of the accuracy. The enhancement process can help the network to efficiently analyze the flow information of the main object in the optical flow frame, thereby improving accuracy. A different accuracy of each stream can be reflected to the fused score while using the proposed score fusion method. We achieved an accuracy of 98.2% on UCF-101 and 82.4% on HMDB-51. The proposed method outperformed many state-of-the-art methods without changing the network structure and it is expected to be easily applied to other networks.
Robust Control for the Detection Threshold of CFAR Process in Cluttered Environments
Authors: Shin Jeong Hoon , Choi Youngjin
Published: July 2020

The constant false alarm rate (CFAR) process is essential for target detection in radar systems. Although the detection performance of the CFAR process is normally guaranteed in noise-limited environments, it may be dramatically degraded in clutter-limited environments since the probabilistic characteristics for clutter are unknown. Therefore, sophisticated CFAR processes that suppress the effect of clutter can be used in actual applications. However, these methods have the fundamental limitation of detection performance because there is no feedback structure in terms of the probability of false alarm for determining the detection threshold. This paper presents a robust control scheme for adjusting the detection threshold of the CFAR process while estimating the clutter measurement density (CMD) that uses only the measurement sets over a finite time interval in order to adapt to time-varying cluttered environments, and the probability of target existence with finite measurement sets required for estimating CMD is derived. The improved performance of the proposed method was verified by simulation experiments for heterogeneous situations.
Validation of a Wireless Bluetooth Photoplethysmography Sensor Used on the Earlobe for Monitoring Heart Rate Variability Features during a Stress-Inducing Mental Task in Healthy Individuals
Authors: Correia Bruno , Dias Nuno , Costa Patrício , Pêgo José Miguel
Published: July 2020

Heart rate variability (HRV), using electrocardiography (ECG), has gained popularity as a biomarker of the stress response. Alternatives to HRV monitoring, like photoplethysmography (PPG), are being explored as cheaper and unobtrusive non-invasive technologies. We report a new wireless PPG sensor that was tested in detecting changes in HRV, elicited by a mentally stressful task, and to determine if its signal can be used as a surrogate of ECG for HRV analysis. Data were collected simultaneously from volunteers using a PPG and ECG sensor, during a resting and a mentally stressful task. HRV metrics were extracted from these signals and compared to determine the agreement between them and to determine if any changes occurred in the metrics due to the stressful task. For both tasks, a moderate/good agreement was found in the mean interbeat intervals, SDNN, LF, and SD2, and a poor agreement for the pNN50, RMSSD|SD1, and HF metrics. The majority of the tested HRV metrics obtained from the PPG signal showed a significant decrease caused by the mental task. The disagreement found between specific HRV features imposes caution when comparing metrics from different technologies. Nevertheless, the tested sensor was successful at detecting changes in the HRV caused by a mental stressor.
Coronavirus Disease (COVID-19): Handling Challenges in Kuwait
Authors: Gasana Janvier , Shehab Maryam
Published: July 2020

The world is currently facing a serious pandemic of coronavirus disease 2019 (COVID-19) which started in Wuhan, China, and was then transmitted rapidly to other countries. Countries applied different methods and procedures in an attempt to prevent or reduce and/or control the incidence of cases and manage existing ones. This paper discusses the methods and procedures applied by Kuwait to control this epidemic, and how effective they have been. The State of Kuwait followed WHO, European CDC, US CDC, and/or other countries’ institutional guidelines, and is still working on containing the disease, given the rising number of cases among Kuwaitis returning from affected areas such as the UK and USA, and migrant workers who bear the highest burden, given their cramped living conditions.
Animals as Something More Than Mere Property: Interweaving Green Criminology and Law
Authors: Gacek James , Jochelson Richard
Published: July 2020

Our article argues that non-human animals deserve to be treated as something more than property to be abused, exploited, or expended. Such an examination lies at the heart of green criminology and law—an intersection of which we consider more thoroughly. Drawing upon our respective and collective works, we endeavor to engage in a discussion that highlights the significance of green criminology for law and suggests how law can provide opportunities to further green criminological inquiry. How the law is acutely relevant for constituting the animal goes hand in glove with how humanness and animality are embedded deeply in the construction of law and society. We contend that, when paired together, green criminology and law have the potential to reconstitute the animal as something more than mere property within law, shed light on the anthropocentric logics at play within the criminal justice system, and promote positive changes to animal cruelty legislation. Scholarship could benefit greatly from moving into new lines of inquiry that emphasize “more-than-human legalities”. Such inquiry has the power to promote the advocacy-oriented scholarship of animal rights and species justice.
Vector Maps Mobile Application for Sustainable Eco-Driving Transportation Route Selection
Authors: Balali Vahid , Fathi Soheil , Aliasgari Mehrdad
Published: July 2020

The decisions managing all modes of transportation are currently based on the traffic rate and travel time. However, other factors such as Green House Gas (GHG) emissions, the sustainability index, fuel consumption, and travel costs are not considered. Therefore, more comprehensive methods need to be implemented to improve transportation systems and support users’ decision making in their daily commute. This paper addresses current challenges by utilizing data analytics derived from our proposed mobile application. The proposed application quantifies various factors of each transportation mode including but not limited to the cost, trip duration, fuel consumption, and Carbon Dioxide (CO2) emissions. All calculated travel costs are based on the real-time gas prices and toll fees. The users are also able to navigate to their destination and update the total travel costs in real-time. The emissions data per trip basis are aggregated to provide analytics of emissions usage. The traffic data is collected for the Southern California region and the effectiveness of the application is evaluated by twenty participants from California State University, Long Beach. The results demonstrate the application’s impacts on users’ decision-making and the propriety of the factors used in route selection. The proposed application can foster urban planning and operations vis-à-vis daily commutes, and as a result improve the citizens’ quality of life in various aspects.
Archetypes of Goal and Scope Definitions for Consistent Allocation in LCA
Authors: Schrijvers Dieuwertje , Loubet Philippe , Sonnemann Guido
Published: July 2020

The selection of an appropriate allocation procedure for co-production and recycling in Life Cycle Assessment (LCA) depends on the goal and scope of the analysis. However, it is not always clear when partitioning or system expansion can be applied, or when to conduct an attributional or a consequential LCA, both for LCA practitioners and users of LCA results. In this paper, the influence of the goal and scope on the selected modeling approaches is clarified. The distinction between process-oriented and product-oriented LCAs, between system expansion and substitution, and between the cut-off approach and other allocation procedures are highlighted. Archetypes of goal and scope definitions are developed. These archetypes reflect the minimum amount of information required to select an allocation procedure. It is demonstrated via an illustrative example that the question “what is the environmental impact of a product” can result in at least 15 different research questions requiring at least five different modeling methods. Finally, perspectives are provided on the use of attributional and consequential approaches to evaluate the environmental, social, and economic sustainability of products and processes.
Design of Flexible Vehicle Scheduling Systems for Sustainable Paratransit Services
Authors: Mo Daniel Y. , Lam H. Y. , Xu Weikun , Ho G. T. S.
Published: July 2020

The aging population has led to an increase in the variety and volume of transportation demands by people facing travel difficulties. Hence, transportation organisations need to provide flexible and sustainable paratransit services to meet these increasing demands. In this study, we investigate the design of flexible vehicle scheduling systems in order for a community organisation to serve more people and achieve higher operational efficiency. We analyse and propose a system design based on user requirements for different types of paratransit types. Further, we identify an integrated service option and process flow for dial-a-ride passengers to ride on a vehicle with schedule route passengers. Because this option involves a complex decision, we formulate the problem as a two-stage decision model. To verify the effectiveness of our proposed design, we perform numerical simulations and conduct a case study by collaborating with a transportation organisation. We found that the proposed system would enable the organisation to serve more people with fewer vehicles but without an increase in the travelling time. These results demonstrate the importance of a flexible vehicle scheduling system for accessible transportation organisations to sustain their service operations.
Exploring the Spatial-Temporal Relationship between Rainfall and Traffic Flow: A Case Study of Brisbane, Australia
Authors: Qi Yanmin , Zheng Zuduo , Jia Dongyao
Published: July 2020

The impact of inclement weather on traffic flow has been extensively studied in the literature. However, little research has unveiled how local weather conditions affect real-time traffic flows both spatially and temporally. By analysing the real-time traffic flow data of Traffic Signal Controllers (TSCs) and weather information in Brisbane, Australia, this paper aims to explore weather’s impact on traffic flow, more specifically, rainfall’s impact on traffic flow. A suite of analytic methods has been applied, including the space-time cube, time-series clustering, and regression models at three different levels (i.e., comprehensive, location-specific, and aggregate). Our results reveal that rainfall would induce a change of the traffic flow temporally (on weekdays, Saturday, and Sunday and at various periods on each day) and spatially (in the transportation network). Particularly, our results consistently show that the traffic flow would increase on wet days, especially on weekdays, and that the urban inner space, such as the central business district (CBD), is more likely to be impacted by inclement weather compared with other suburbs. Such results could be used by traffic operators to better manage traffic in response to rainfall. The findings could also help transport planners and policy analysts to identify the key transport corridors that are most susceptible to traffic shifts in different weather conditions and establish more weather-resilient transport infrastructures accordingly.
Regional View on Housing of the Marginalized Roma Population in the Slovak Republic
Authors: Sika Peter , Vidová Jarmila , Rievajová Eva
Published: July 2020

The Roma ethnic group represents an integral part of the Slovak population. Thanks to their specific customs and traditions, in combination with social segregation, they have kept several differences from the majority of the population. These differences have also been demonstrated in the conditions and quality of housing, which are the basic indicators of the economic and cultural maturity of an individual, as well as the nation itself. The goal of this paper is to examine the issue of the Roma population in the Slovak Republic, with a focus on the area of housing. In the historical excursion, the authors present the arrival of the Roma to Europe and subsequently the present territory of the Slovak Republic. They point out the importance of the Roma issue and what has caused the conditions and factors determining the development and position of this ethnic group at the periphery of the majority. Using the data from the Atlas of Roma Communities from 2019, they analyze the demographic behavior and reproduction of the Roma population, which differs from the reproduction behavior of the majority population, as well as the territorial displacement of the Roma. In the following sections of the paper, the authors focus on examining the housing conditions of the Roma community in individual regions of the Slovak Republic and the programmes aimed at improving the housing situation of the Slovak Roma.
Assessment of Ventilation Efficiency in School Classrooms Based on Indoor–Outdoor Particulate Matter and Carbon Dioxide Measurements
Authors: Bartyzel Jakub , Zięba Damian , Nęcki Jarosław , Zimnoch Mirosław
Published: July 2020

The concentration of indoor suspended particulate matter is considered to be one of the main factors that affect health and quality of life. In Poland, in response to the pressure of public opinion, a few thousand air purifiers have been installed in public buildings where children spend time. However, another factor that also impacts upon the quality of indoor air, namely increased CO2 mixing ratios, is frequently overlooked. The only way to remove CO2 excess from interiors is through intensive ventilation. This is often an action at odds with the need to maintain low concentrations of particulate matter in indoor air. Two methods are presented to assess the rate of air exchange using CO2 or particulate matter as a tracer. One of the methods using indoor/outdoor PM (particulate matter) concentrations is based on the use of box models for analysis. The second one uses indoor CO2 concentration change analysis. At the tested locations, they showed large deviations of the determined values of the air exchange coefficients from its limits. Both methods showed consistent ventilation parameters estimation.
An Integrated Approach of Multi-Community Monitoring and Assessment of Aquatic Ecosystems to Support Sustainable Development
Authors: Forio Marie Anne Eurie , Goethals Peter L. M.
Published: July 2020

Aquatic ecosystems are one of the most threatened ecosystems in the world resulting in the decline of aquatic biodiversity. Monitoring and the assessment of aquatic ecosystems are necessary to protect and conserve these ecosystems as monitoring provides insights into the changes in the aquatic ecosystem over a long period of time and assessment indicates the status of these ecosystems. This paper presents an overview of different methods for the hydromorphological, physical–chemical and the biological monitoring and assessment of surface waters. Furthermore, recently developed monitoring and assessment methods are discussed to support sustainable water management and contribute to the implementation of the Sustainable Development Goals 6 (SDG6 related to clean water and sanitation) and 15 (SDG15 related to terrestrial and freshwater systems) of the United Nations. However, many other SDGs are dependent on freshwater, such as food (e.g., SDG2) and climate-related SDGs. We presented an innovative concept for integrated monitoring and assessment. The main new elements are the monitoring of all communities and the use of integrated socio-environmental models to link these communities to ecosystem interactions and functions as a basis for determining their relation to the SDGs. Models can also allow to determine the effects of changes in SDGs on the different elements of the concept, and serve in this manner as tools for the selection of an optimal balance between the SDGs in the context of sustainable development.
Inter-Organisational Exercises in Dry and Wet Context—Why Do Maritime Response Organisations Gain More Knowledge from Exercises at Sea Than Those on Shore?
Authors: Carlström Eric , Magnussen Leif Inge , Kristiansen Elsa , Berlin Johan , Sørensen Jarle Løwe
Published: July 2020

This is a study of inter-organisational exercises arranged by on-shore organisations (ONSOs) and off-shore organisations (OFFSOs). The aim was to compare findings from trained emergency staffs’ perceptions of the impact of exercises. The data were retrieved from surveys conducted by the research team in conjunction with exercises. The surveys included staff from the coast guard, sea rescue, police department, fire department and ambulance services. A total of 94 professional emergency personnel participated in the ONSO exercises and 252 in the OFFSO exercises. The study was based on the suggestion that collaborative elements during an inter-organisational exercise promote learning, and learning is important to make the exercises useful. Collaboration proved to be a predictor for some of the items in learning, and learning was a predictor for some of the items in utility. There was, however, a stronger covariation between collaboration, learning and utility in the OFFSOs exercises than in the ONSOs. One reason might be the different cultures of emergency staff involved in on-shore and off-shore organisations. The OFFSOs’ qualifications may be dominated by seamanship, together with professional practice, and all parties are expected to act as first responders. ONSOs, on the other hand, practice exercises from a strict professional and legal perspective.
ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation
Authors: Hsieh Yi-Zeng , Lin Shih-Syun , Luo Yu-Cin , Jeng Yu-Lin , Tan Shih-Wei , Chen Chao-Rong , Chiang Pei-Ying
Published: July 2020

Under the vigorous development of global anticipatory computing in recent years, there have been numerous applications of artificial intelligence (AI) in people’s daily lives. Learning analytics of big data can assist students, teachers, and school administrators to gain new knowledge and estimate learning information; in turn, the enhanced education contributes to the rapid development of science and technology. Education is sustainable life learning, as well as the most important promoter of science and technology worldwide. In recent years, a large number of anticipatory computing applications based on AI have promoted the training professional AI talent. As a result, this study aims to design a set of interactive robot-assisted teaching for classroom setting to help students overcoming academic difficulties. Teachers, students, and robots in the classroom can interact with each other through the ARCS motivation model in programming. The proposed method can help students to develop the motivation, relevance, and confidence in learning, thus enhancing their learning effectiveness. The robot, like a teaching assistant, can help students solving problems in the classroom by answering questions and evaluating students’ answers in natural and responsive interactions. The natural interactive responses of the robot are achieved through the use of a database of emotional big data (Google facial expression comparison dataset). The robot is loaded with an emotion recognition system to assess the moods of the students through their expressions and sounds, and then offer corresponding emotional responses. The robot is able to communicate naturally with the students, thereby attracting their attention, triggering their learning motivation, and improving their learning effectiveness.
The Impact of Political Connection and Information Asymmetry on Investment Efficiency: Evidence from China
Authors: Yu Hui-Fun , Lin Tsui-Jung , Chang Hai-Yen , Wang Yu-Huai
Published: July 2020

This study investigates the impact of political connection and information asymmetry on the investment efficiency of firms in China. This paper employs a panel data regression analysis on a dataset comprising 4307 observations for listed companies from 2008 to 2015. The results indicate that if taken alone, neither political connection nor information asymmetry affects firms’ investment efficiency. However, the interactive effect of both political connection and information asymmetry significantly reduces firms’ investment efficiency. The results of this study help investors understand the forces that lead the Chinese firms to deviate from optimal investment decisions.
Effects of Drought Stress on Some Agronomic and Morpho-Physiological Traits in Durum Wheat Genotypes
Authors: Pour-Aboughadareh Alireza , Mohammadi Reza , Etminan Alireza , Shooshtari Lia , Maleki-Tabrizi Neda , Poczai Peter
Published: July 2020

Durum wheat performance in the Mediterranean climate is limited when water scarcity occurs before and during anthesis. The present research was performed to determine the effect of drought stress on several physiological and agro-morphological traits in 17 durum wheat genotypes under two conditions (control and drought) over two years. The results of analysis of variance indicated that the various durum wheat genotypes responded differently to drought stress. Drought stress significantly reduced the grain filling period, plant height, peduncle length, number of spikes per plot, number of grains per spike, thousand grains weight, grain yield, biomass, and harvest index in all genotypes compared to the control condition. The heatmap-based correlation analysis indicated that grain yield was positively and significantly associated with phenological characters (days to heading, days to physiological maturity, and grain filling period), as well as number of spikes per plant, biomass, and harvest index under drought conditions. The yield-based drought and susceptible indices revealed that stress tolerance index (STI), geometric mean productivity (GMP), mean productivity (MP), and harmonic mean (HM) were positively and significantly correlated with grain yields in both conditions. Based on the average of the sum of ranks across all indices and a three-dimensional plot, two genotypes (G9 and G12) along with the control variety (G1) were identified as the most tolerant genotypes. Among the investigated genotypes, the new breeding genotype G12 showed a high drought tolerance and yield performance under both conditions. Hence, this genotype can be a candidate for further multi-years and locations test as recommended for cultivation under rainfed conditions in arid and semi-arid regions.
Acoustic Characteristics of Cross-Laminated Timber Systems
Authors: Di Bella Antonino , Mitrovic Milica
Published: July 2020

The growing diffusion of cross-laminated timber structures (CLT) has been accompanied by extensive research on the peculiar characteristics of this construction system, mainly concerning its economic and environmental benefits, lifecycle, structural design, resistance to seismic actions, fire protection, and energy efficiency. Nevertheless, some aspects have not yet been fully analysed. These include both the knowledge of noise protection that CLT systems are able to offer in relation to the possible applications and combinations of building elements, and the definition of calculation methods necessary to support the acoustic design. This review focuses on the main acoustic features of CLT systems and investigate on the results of the most relevant research aimed to provide key information on the application of acoustic modelling in CLT buildings. The vibro-acoustic behaviour of the basic component of this system and their interaction through the joints has been addressed, as well as the possible ways to manage acoustic information for calculation accuracy improvement by calibration with data from on-site measurements during the construction phase. This study further suggests the opportunity to improve measurement standards with specific reference curves for the bare CLT building elements, in order to compare different acoustic linings and assemblies on the same base. In addition, this study allows to identify some topics in the literature that are not yet fully clarified, providing some insights on possible future developments in research and for the optimization of these products.
Response of Soil Microbial Communities to Warming and Clipping in Alpine Meadows in Northern Tibet
Authors: Zhang Haorui , Li Shaowei , Zhang Guangyu , Fu Gang
Published: July 2020

In order to explore responses of soil microbial communities among different alpine meadows under warming and clipping, soil microorganisms of three alpine meadow sites (low altitude: 4313 m, alpine steppe meadow, 30°30′ N, 91°04′ E; mid-altitude: 4513 m, alpine steppe meadow, 30°31′ N, 91°04′ E; and high altitude: 4693, alpine Kobresia meadow, 30°32′ N, 91°03′ E) were measured using the phospholipid fatty acid (PLFA) method. Both warming and clipping significantly reduced PLFA content and changed the community composition of soil microbial taxa, which belong to bacterial and fungal communities in the alpine Kobresia meadow. Warming significantly reduced the soil total PLFA content by 36.1% and the content of soil fungi by 37.0%; the clipping significantly reduced the soil total PLFA content by 57.4%, the content of soil fungi by 49.9%, and the content of soil bacteria by 60.5% in the alpine Kobresia meadow. Only clipping changed the total fungal community composition at a low altitude. Neither clipping nor warming changed the microbial community composition at a moderate altitude. Soil temperature, soil moisture, and pH were the main factors affecting soil microbial communities. Therefore, the effects of warming and clipping on soil microbial communities in alpine meadows were related to grassland types and soil environmental conditions.
Exploring the Relationship between Urbanization and Ecological Environment Using Remote Sensing Images and Statistical Data: A Case Study in the Yangtze River Delta, China
Authors: Shao Zhenfeng , Ding Lin , Li Deren , Altan Orhan , Huq Md. Enamul , Li Congmin
Published: July 2020

With the rapid urban development in China, urbanization has brought more and more pressure on the ecological environment. As one of the most dynamic, open, and innovative regions in China, the eco-environmental issues in the Yangtze River Delta have attracted much attention. This paper takes the central region of the Yangtze River Delta as the research object, through building the index system of urbanization and ecological environment based on statistical data and two new indicators (fraction of vegetation coverage and surface urban heat island intensity) extracted from remote sensing images, uses the Entropy-TOPSIS method to complete the comprehensive assessment, and then analyzes the coupling coordination degree between the urbanization and ecological environment and main obstacle factors. The results showed that the coupling coordination degree in the study region generally shows an upward trend from 0.604 in 2008 to 0.753 in 2017, generally changing from an imbalanced state towards a basically balanced state. However, regional imbalance of urbanization and ecological environment always exists, which is mainly affected by social urbanization, economic urbanization, landscape urbanization, pollution loading and resource consumption. Finally, on the basis of the obstacle factor analysis, some specific suggestions for promoting the coordinated development of the Yangtze River Delta are put forward.
The Price of Farmland as a Factor in the Sustainable Development of Czech Agriculture (A Case Study)
Authors: Seeman Tomáš , Šrédl Karel , Prášilová Marie , Svoboda Roman
Published: July 2020

Each year, around 2% of the four million hectares of farmland in Czechia changes owners. However, after years of significant growth in prices, a slowdown in pace and demand is expected. Rising interest rates, a strengthening of the crown and legislative changes in 2018 have influenced the price of farmland. Yet the prices of farmland in Czechia are a third of those in the countries of Western Europe, and so it still represents an interesting opportunity for investors. Currently, land is bought primarily by the farmers who work it. In Czechia, 80% of farmers farm on hired land, and rent increases are starting to be an issue for many of them. The return on the investment in agricultural land is currently around 50 years for an owner and 25 years for a farmer working the land. As research has shown, the price of farmland is an important factor in the sustainable development of agriculture in Czechia, along with the greening of production and the fight against soil erosion and the effects of climate change.
Explanatory Factors of Entrepreneurship in Food and Beverage Clusters in Spain
Authors: Claver-Cortés Enrique , Marco-Lajara Bartolomé , Seva-Larrosa Pedro , Ruiz-Fernández Lorena , Sánchez-García Eduardo
Published: July 2020

Research into entrepreneurship has gradually changed its perspective over recent decades, becoming a very relevant research topic. In the last few years, various lines of research have been developed to find new explanatory factors of entrepreneurial propensity in specific socioeconomic and institutional contexts, among which we can highlight local territorial agglomerations. The main objective of the study is to offer new knowledge about the factors that influence the entrepreneurial capacity of food and beverage clusters using different secondary sources. To reach this objective, we analyze how the degree of agglomeration, institutional thickness, and knowledge affects new companies created in the last five years within the 37 food and beverage clusters in Spain. Multiple regression results show that company agglomeration and the presence of supporting institutions positively influence entrepreneurial capacity in these clusters. However, available knowledge has a negative influence on entrepreneurial capacity in these specialized environments.
Practical Application of the Galerkin Finite Element Method with a Mass Conservation Scheme under Dirichlet Boundary Conditions to Solve Groundwater Problems
Authors: Suk Heejun , Chen Jui-Sheng , Park Eungyu , Kihm You Hong
Published: July 2020

The Galerkin finite element method (FEM) has long been used to solve groundwater flow equations and compute the mass balance in a region. In this study, we proposed a simple, new computational FEM procedure for global mass balance computations that can simultaneously obtain boundary fluxes at Dirichlet boundary nodes and finite element hydraulic heads at all nodes in only one step, whereas previous approaches usually require two steps. In previous approaches, the first step obtains the Galerkin finite element hydraulic heads at all nodes, and then, the boundary fluxes are calculated using the obtained Galerkin finite element hydraulic heads in a second step. Comparisons between the new approach proposed in this study and previous approaches, such as Yeh’s approach and a conventional differential approach, were performed using two practical groundwater problems to illustrate the improved accuracy and efficiency of the new approach when computing the global mass balance or boundary fluxes. From the results of the numerical experiments, it can be concluded that the new approach provides a more efficient mass balance computation scheme and a much more accurate mass balance computation compared to previous approaches that have been widely used in commercial and public groundwater software.
The Revaluation of Uninhabited Popular Patrimony under Environmental and Sustainability Parameters
Authors: Blandón Begoña , Palmero Luís , di Ruocco Giacomo
Published: July 2020

Abandoning rural areas requires promoting their repopulation. In Europe, wealth and life in these enclaves are valued. However, the current state of these houses does not meet actual needs and requires interventions to actualize current standards. Therefore, decisions in the design and execution of the works will generate a volume of construction and demolition waste (CDW), which must be managed sustainably out of respect towards its origin, the architecture, and the surrounding environment. This paper examines the prevention and management of CDW, providing control strategies and actions to monitor and plan them from the rehabilitation project itself. Some of the interventions carried out in recent years on this type of housing have been analyzed and the existing management protocols within the European Union have been reviewed, specifying their application in Mediterranean popular housing. As a result, we herein show a representative case that observes the existing reality regarding the destination of generated CDW and delves into their possibilities for use. We present these findings in order to reduce the energy cost resulting from manufacturing new materials and meeting the established sustainability and energy efficiency parameters.
Factors Used to Make Appropriate Decisions in Youth Categories in Volleyball
Authors: Conejero Suárez Manuel , Serenini Antônio L. P. , González-Silva Jara , Moreno Arroyo M. Perla
Published: July 2020

The study aim was to examine the associations between the category of play and the factors athletes use to make appropriate decisions. We observed 6567 game actions performed by 144 athletes. All game actions involved appropriate decisions. The study variables were factors on which appropriate decision-making is based (for five game actions in volleyball: serve, reception, setting, attack, block) and game category (Under-14, Under-16, Under-19). Our analysis—using contingency tables, the Chi-square test, and Cramer’s V—revealed a significant association between the two variables across the five actions. In the U-14 category, and sometimes in the U-16 category, it was more frequent than the expected random frequency that appropriate decisions were of low tactical complexity, focused on the performance of the skill, with an attentional focus on close elements, of low risk, and with actions of reduced difficulty and precision. For the U-19 category, it was more frequent than the expected random frequency that decisions were of greater tactical complexity, with an attentional focus on the opposing team, considering more relevant stimuli, with greater risk, and with greater time pressure. There is, therefore, a need for coaches to understand the decision-making skills of athletes from early on, as this will allow them to develop tasks and apply cognitive strategies that are adapted to the level of the athlete and that can ultimately improve decision-making further.
The Contribution of the Fishermen’s Guilds and the Agrarian Transformation Societies to the Sustainable Development Goals: The Case of the Canary Islands
Authors: Mendoza Jiménez Javier , Guzmán Pérez Beatriz , Pérez Monteverde María Victoria , Román Cervantes Cándido
Published: July 2020

The Social Economy entities have been recognized as key agents for achieving the 17 Sustainable Development Goals (SDG) of the 2030 Agenda. To reach that, indicators are required to guide decision-making and facilitate accountability to citizens. Substantial progress has been made for the economic and environmental dimensions, but not for the social one, which is a particularly serious deficiency to support the social value that the Third Sector entities’ have for the society. The objective of this study is to advance in this line, taking two organizations of the Social Economy that operate in the rural and marine environments of an important international tourist destination in Spain, the Canary Islands. The achieve this goal, the study uses the Social Value Polyhedral Model (SPOLY) of Social Accounting in the framework of the SDG to generate a system of relevant indicators that makes possible to project the particular contribution of these social actors, guide their action towards the global objectives, and render accounts in a transparent and understandable way to their stakeholders. The results show a common ground of contribution for both organizations (goals 8 and 17), but also the influence of the sphere of activity and the connections with the community.