bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating Player Positions from Padel High-Angle Videos: Accuracy Comparison of Recent Computer Vision Methods
Authors: Javadiha Mohammadreza , Andujar Carlos , Lacasa Enrique , Ric Angel , Susin Antonio
Published: May 2021

The estimation of player positions is key for performance analysis in sport. In this paper, we focus on image-based, single-angle, player position estimation in padel. Unlike tennis, the primary camera view in professional padel videos follows a de facto standard, consisting of a high-angle shot at about 7.6 m above the court floor. This camera angle reduces the occlusion impact of the mesh that stands over the glass walls, and offers a convenient view for judging the depth of the ball and the player positions and poses. We evaluate and compare the accuracy of state-of-the-art computer vision methods on a large set of images from both amateur videos and publicly available videos from the major international padel circuit. The methods we analyze include object detection, image segmentation and pose estimation techniques, all of them based on deep convolutional neural networks. We report accuracy and average precision with respect to manually-annotated video frames. The best results are obtained by top-down pose estimation methods, which offer a detection rate of 99.8% and a RMSE below 5 and 12 cm for horizontal/vertical court-space coordinates (deviations from predicted and ground-truth player positions). These results demonstrate the suitability of pose estimation methods based on deep convolutional neural networks for estimating player positions from single-angle padel videos. Immediate applications of this work include the player and team analysis of the large collection of publicly available videos from international circuits, as well as an inexpensive method to get player positional data in amateur padel clubs.
Can Machine Learning and PS-InSAR Reliably Stand in for Road Profilometric Surveys?
Authors: Fiorentini Nicholas , Maboudi Mehdi , Leandri Pietro , Losa Massimo
Published: May 2021

This paper proposes a methodology for correlating products derived by Synthetic Aperture Radar (SAR) measurements and laser profilometric road roughness surveys. The procedure stems from two previous studies, in which several Machine Learning Algorithms (MLAs) have been calibrated for predicting the average vertical displacement (in terms of mm/year) of road pavements as a result of exogenous phenomena occurrence, such as subsidence. Such algorithms are based on surveys performed with Persistent Scatterer Interferometric SAR (PS-InSAR) over an area of 964 km2 in the Tuscany Region, Central Italy. Starting from this basis, in this paper, we propose to integrate the information provided by these MLAs with 10 km of in situ profilometric measurements of the pavement surface roughness and relative calculation of the International Roughness Index (IRI). Accordingly, the aim is to appreciate whether and to what extent there is an association between displacements estimated by MLAs and IRI values. If a dependence exists, we may argue that road regularity is driven by exogenous phenomena and MLAs allow for the replacement of in situ surveys, saving considerable time and money. In this research framework, results reveal that there are several road sections that manifest a clear association among these two methods, while others denote that the relationship is weaker, and in situ activities cannot be bypassed to evaluate the real pavement conditions. We could wrap up that, in these stretches, the road regularity is driven by endogenous factors which MLAs did not integrate during their training. Once additional MLAs conditioned by endogenous factors have been developed (such as traffic flow, the structure of the pavement layers, and material characteristics), practitioners should be able to estimate the quality of pavement over extensive and complex road networks quickly, automatically, and with relatively low costs.
Automatic Detection of Chewing and Swallowing
Authors: Nakamura Akihiro , Saito Takato , Ikeda Daizo , Ohta Ken , Mineno Hiroshi , Nishimura Masafumi
Published: May 2021

A series of eating behaviors, including chewing and swallowing, is considered to be crucial to the maintenance of good health. However, most such behaviors occur within the human body, and highly invasive methods such as X-rays and fiberscopes must be utilized to collect accurate behavioral data. A simpler method of measurement is needed in healthcare and medical fields; hence, the present study concerns the development of a method to automatically recognize a series of eating behaviors from the sounds produced during eating. The automatic detection of left chewing, right chewing, front biting, and swallowing was tested through the deployment of the hybrid CTC/attention model, which uses sound recorded through 2ch microphones under the ear and weak labeled data as training data to detect the balance of chewing and swallowing. N-gram based data augmentation was first performed using weak labeled data to generate many weak labeled eating sounds to augment the training data. The detection performance was improved through the use of the hybrid CTC/attention model, which can learn the context. In addition, the study confirmed a similar detection performance for open and closed foods.
A Novel Domain Adaptation-Based Intelligent Fault Diagnosis Model to Handle Sample Class Imbalanced Problem
Authors: Zhang Zhongwei , Shao Mingyu , Wang Liping , Shao Sujuan , Ma Chicheng
Published: May 2021

As the key component to transmit power and torque, the fault diagnosis of rotating machinery is crucial to guarantee the reliable operation of mechanical equipment. Regrettably, sample class imbalance is a common phenomenon in industrial applications, which causes large cross-domain distribution discrepancies for domain adaptation (DA) and results in performance degradation for most of the existing mechanical fault diagnosis approaches. To address this issue, a novel DA approach that simultaneously reduces the cross-domain distribution difference and the geometric difference is proposed, which is defined as MRMI. This work contains three parts to improve the sample class imbalance issue: (1) A novel distance metric method (MVD) is proposed and applied to improve the performance of marginal distribution adaptation. (2) Manifold regularization is combined with instance reweighting to simultaneously explore the intrinsic manifold structure and remove irrelevant source-domain samples adaptively. (3) The ℓ2-norm regularization is applied as the data preprocessing tool to improve the model generalization performance. The gear and rolling bearing datasets with class imbalanced samples are applied to validate the reliability of MRMI. According to the fault diagnosis results, MRMI can significantly outperform competitive approaches under the condition of sample class imbalance.
Electrotactile Feedback for the Discrimination of Different Surface Textures Using a Microphone
Authors: Svensson Pamela , Antfolk Christian , Björkman Anders , Malešević Nebojša
Published: May 2021

Most commercial prosthetic hands lack closed-loop feedback, thus, a lot of research has been focusing on implementing sensory feedback systems to provide the user with sensory information during activities of daily living. This study evaluates the possibilities of using a microphone and electrotactile feedback to identify different textures. A condenser microphone was used as a sensor to detect the friction sound generated from the contact between different textures and the microphone. The generated signal was processed to provide a characteristic electrical stimulation presented to the participants. The main goal of the processing was to derive a continuous and intuitive transfer function between the microphone signal and stimulation frequency. Twelve able-bodied volunteers participated in the study, in which they were asked to identify the stroked texture (among four used in this study: Felt, sponge, silicone rubber, and string mesh) using only electrotactile feedback. The experiments were done in three phases: (1) Training, (2) with-feedback, (3) without-feedback. Each texture was stroked 20 times each during all three phases. The results show that the participants were able to differentiate between different textures, with a median accuracy of 85%, by using only electrotactile feedback with the stimulation frequency being the only variable parameter.
Complex Permittivity Characterization of Liquid Samples Based on a Split Ring Resonator (SRR)
Authors: Ma Jialu , Tang Jingchao , Wang Kaicheng , Guo Lianghao , Gong Yubin , Wang Shaomeng
Published: May 2021

A complex permittivity characterization method for liquid samples has been proposed. The measurement is carried out based on a self-designed microwave sensor with a split ring resonator (SRR), the unload resonant frequency of which is 5.05 GHz. The liquid samples in capillary are placed in the resonant zone of the fabricated senor for high sensitivity measurement. The frequency shift of 58.7 MHz is achieved when the capillary is filled with ethanol, corresponding a sensitivity of 97.46 MHz/μL. The complex permittivity of methanol, ethanol, isopropanol (IPA) and deionized water at the resonant frequency are measured and calibrated by the first order Debye model. Then, the complex permittivity of different concentrations of aqueous solutions of these materials are measured by using the calibrated sensor system. The results show that the proposed sensor has high sensitivity and accuracy in measuring the complex permittivity of liquid samples with volumes as small as 0.13 μL. It provides a useful reference for the complex permittivity characterization of small amount of liquid chemical samples. In addition, the characterization of an important biological sample (inositol) is carried out by using the proposed sensor.
A Monocular Visual Odometry Method Based on Virtual-Real Hybrid Map in Low-Texture Outdoor Environment
Authors: Xie Xiuchuan , Yang Tao , Ning Yajia , Zhang Fangbing , Zhang Yanning
Published: May 2021

With the extensive application of robots, such as unmanned aerial vehicle (UAV) in exploring unknown environments, visual odometry (VO) algorithms have played an increasingly important role. The environments are diverse, not always textured, or low-textured with insufficient features, making them challenging for mainstream VO. However, for low-texture environment, due to the structural characteristics of man-made scene, the lines are usually abundant. In this paper, we propose a virtual-real hybrid map based monocular visual odometry algorithm. The core idea is that we reprocess line segment features to generate the virtual intersection matching points, which can be used to build the virtual map. Introducing virtual map can improve the stability of the visual odometry algorithm in low-texture environment. Specifically, we first combine unparallel matched line segments to generate virtual intersection matching points, then, based on the virtual intersection matching points, we triangulate to get a virtual map, combined with the real map built upon the ordinary point features to form a virtual-real hybrid 3D map. Finally, using the hybrid map, the continuous camera pose estimation can be solved. Extensive experimental results have demonstrated the robustness and effectiveness of the proposed method in various low-texture scenes.
A Novel Accelerometry-Based Metric to Improve Estimation of Whole-Body Mechanical Load
Authors: Hollville Enzo , Couturier Antoine , Guilhem Gaël , Rabita Giuseppe
Published: May 2021

While the Player Load is a widely-used parameter for physical demand quantification using wearable accelerometers, its calculation is subjected to potential errors related to rotational changes of the reference frame. The aims of this study were (i) to assess the concurrent validity of accelerometry-based Player Load against force plates; (ii) to validate a novel metric, the Accel’Rate overcoming this theoretical issue. Twenty-one recreational athlete males instrumented with two triaxial accelerometers positioned at the upper and lower back performed running-based locomotor movements at low and high intensity over six in-series force plates. We examined the validity of the Player Load and the Accel’Rate by using force plates. Standard error of the estimate was small to moderate for all tested conditions (Player Load: 0.45 to 0.87; Accel’Rate: 0.25 to 0.95). Accel’Rate displayed trivial to small mean biases (−1.0 to 6.1 a.u.) while the Player Load displayed systematic very large to extremely large mean biases (17.1 to 226.0 a.u.). These findings demonstrate a better concurrent validity of the Accel’Rate compared to the Player Load. This metric could be used to improve the estimation of whole-body mechanical load, easily accessible in sport training and competition settings.
Malicious Activity Detection in Lightweight Wearable and IoT Devices Using Signal Stitching
Authors: Karabacak Fatih , Ogras Umit , Ozev Sule
Published: May 2021

The integrated circuit (IC) manufacturing process involves many players, from chip/board design and fabrication to firmware design and installation. In today’s global supply chain, any of these steps are prone to interference from rogue players, creating a security risk. Therefore, manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities. This paper presents a detection technique for malicious activity that can stem from hardware or firmware Trojans. The proposed technique relies on (i) repetitious side-channel sample collection of the active device, (ii) time-domain stitching, and (iii) frequency domain analysis. Since finding a trusted sample is generally impractical, the proposed technique is based on self-referencing to remove the effects of environmental or device-to-device variation in the frequency domain. We first observe that the power spectrum of the Trojan activity is confined to a low-frequency band. Then, we exploit this fact to achieve self-referencing using signal detection theory. The proposed technique’s effectiveness is demonstrated through experiments on a wearable electronics prototype and system-on-chip (SoC) under a variety of practical scenarios. Experimental results show the proposed detection technique enables a high overall detection coverage for malicious activities of varying types with 0.8 s monitoring time overhead, which is negligible.
Transport Infrastructure and Political Factors as Determinants of Tourism Development in the Cross-Border Region of Bihor and Maramureş. A Comparative Analysis
Authors: Wendt Jan A. , Grama Vasile , Ilieş Gabriela , Mikhaylov Andrey S. , Borza Sorin G. , Herman Grigore Vasile , Bógdał-Brzezińska Agnieszka
Published: May 2021

This article follows two important interconnected aspects. On one hand, it investigates whether the political factors represented by the presence of ethnic minorities can be a catalyst for tourism development in cross-border regions, in addition to the development of transport infrastructure. On the other hand, it offers a comparative analysis and territorial diagnosis of the Bihor-Hajdú–Bihar and Maramureş–Zakarpattya cross border regions, analyzing the main tourist indicators and the advances made in the development of the transport infrastructure with a role in the development of tourism. The paper is based on desk and quantitative research involving national and regional statistic data. Research on the literature regarding Hungarian–Romanian and Romanian–Ukrainian borderland was also realized, in order to conduct comparative analysis useful to identify and evaluate the factors linked with tourism development. Using a multiscale approach, the objective is to determine if there is a correlation between the development of the transport network and the increase in tourist traffic. The results show that transport infrastructure plays a critical role in ensuring the connections of border regions. Although the two regions are contiguous, there is an obvious difference in cross-border traffic due to the presence of two different types of border. The transport network and tourism situation in Bihor has improved in the last years, especially under the impact of cross-border cooperation, but the accessibility remains relatively low. In Maramureş, the development of cross-border connections is based on cultural exchange, and less on economic relations. Transport accessibility is a strong point of the Hungarian–Romanian borderland and represents an obstacle for the development of tourism in the Romanian–Ukrainian borderland.
Economic Emission Dispatch Considering Renewable Energy Resources—A Multi-Objective Cross Entropy Optimization Approach
Authors: Niu Qun , You Ming , Yang Zhile , Zhang Yang
Published: May 2021

The conventional electrical power system economic dispatch (ED) often only pursues immediate economic benefits but neglects the harmful environment impacts of gas emissions from thermal power plants. To address this shortfall, economic emission dispatch (EED) has drawn a lot of attention in recent years. With the increasing penetration of renewable generation, the intermittence and uncertainty of renewable energy such as solar power and wind power increase the difficulties of power system scheduling. To enhance the dispatch performance with significant penetration of renewable energy, a modified multi-objective cross entropy algorithm (MMOCE) is proposed in this paper. To solve multi-objective optimization problems, a crowding–distance calculation technique and a novel external archive mechanism are introduced into the conventional cross entropy method. Additionally, the population updating process is simplified by introducing a self-adaptive parameter operator that substitutes the smoothing parameters, while the solution diversity and the adaptability in large scale systems are improved by introducing the crossover operator. Finally, a two-stage evolutionary mechanism further enhances the diversity and the rate of convergence. To verify the efficacy of the proposed MMOCE, eight benchmark functions and three different test systems considering different mixes of renewable energy sources are employed. The dispatch results by the proposed MMOCE are compared with other multi-objective cross entropy algorithms and published heuristic methods, confirming the superiority of the proposed MMOCE over other methods in all test systems.
Analysis of Circular Thinking in Consumer Purchase Intention to Buy Sustainable Waste-To-Value (WTV) Foods
Authors: Ali Shahjahan , Akter Shahnaj , Fogarassy Csaba
Published: May 2021

One of the new fronts in food research is related to waste reuse and the impact of by-products on food nutrition intensity. These foods are Waste-to-Value (WTV) products that are suitable for demonstrating the processes of the circular economy (CE), in which another excess material is converted into a new food, generating higher nutritional properties. The manifestation of customer reaction is very strong when buying these products. Consumer findings can strongly support or hinder the development of circular systems through our purchasing decisions. In this way, it is essential to evaluate consumer WTV foods to learn about related consumer habits. Consumers can support or hinder the circular economy with their purchasing intentions. This analysis’s primary objective is to evaluate what different factors can be applied to consumers’ perception in purchasing sustainable WTV foods towards CE. In this study, a well-constructed questionnaire was prepared. Five hundred and forty-four (544) people participated in the survey, of which, 499 samples were analyzed. The primary research question was, “Would the consumer buy a sustainable Waste-to-Value (WTV) food product that affects the environment when it is produced? That is, it does not come from a circular system?” The other question is, how do the origin of products, information on production/nutritional value, consumer education, and certain socio-demographic characteristics affect the value of waste value for sustainable food consumption? According to the research results, in the case of the surveyed consumers, the younger age group (18–35 years old) shows a greater preference for buying sustainable products. It is also a surprising and new result that gender characteristics in this age group do not influence consumption patterns. Women and men showed the same preferences. Our second hypothesis is that education positively affects consumer intentions for sustainable WTV foods and especially organic products. The questionnaire did not confirm this.
Minimizing Shadow Area in Mountain Roads for Improving the Sustainability of Infrastructures
Authors: Aranda José Ángel , Santonja María Moncho , Saurí MÁ Gil , Peris-Fajarnés Guillermo
Published: May 2021

The lack of sunlight on mountain roads in the wintertime leads to an increase in accidents. In this paper, a methodology is presented for the use of sunny and shady areas to be included as a parameter in road design. The inclusion of this parameter allows for the design of an iterative method for the projected infrastructures. The parameterization of the road layout facilitates the possibility of applying an iterative process of modifying the geometric elements that constitute it, examining different layout alternatives until a layout is achieved in which the surface area in the shady area is minimized, increasing the road safety and minimizing environmental impact. The methodology has been defined, generating and analyzing the results of the solar lighting study using a file in IFC format capable of integrating with the rest of the design elements (platform, signaling, structures, etc.) and thus obtaining a BIM format which allows the model to be viewed in three dimensions and moves towards 4D and 5D. The model used for the study was a high mountain road located in the province of Teruel (Spain). It is a road section characterized by successive curves in which several traffic accidents have occurred due to running off the road, partly because of the presence of ice on the platform.
Production, Purification, and Characterization of Bacillibactin Siderophore of Bacillus subtilis and Its Application for Improvement in Plant Growth and Oil Content in Sesame
Authors: Nithyapriya S. , Lalitha Sundaram , Sayyed R. Z. , Reddy M. S. , Dailin Daniel Joe , El Enshasy Hesham A. , Luh Suriani Ni , Herlambang Susila
Published: May 2021

Siderophores are low molecular weight secondary metabolites produced by microorganisms under low iron stress as a specific iron chelator. In the present study, a rhizospheric bacterium was isolated from the rhizosphere of sesame plants from Salem district, Tamil Nadu, India and later identified as Bacillus subtilis LSBS2. It exhibited multiple plant-growth-promoting (PGP) traits such as hydrogen cyanide (HCN), ammonia, and indole acetic acid (IAA), and solubilized phosphate. The chrome azurol sulphonate (CAS) agar plate assay was used to screen the siderophore production of LSBS2 and quantitatively the isolate produced 296 mg/L of siderophores in succinic acid medium. Further characterization of the siderophore revealed that the isolate produced catecholate siderophore bacillibactin. A pot culture experiment was used to explore the effect of LSBS2 and its siderophore in promoting iron absorption and plant growth of Sesamum indicum L. Data from the present study revealed that the multifarious Bacillus sp. LSBS2 could be exploited as a potential bioinoculant for growth and yield improvement in S. indicum.
Sustainable Meat: Looking through the Eyes of Australian Consumers
Authors: Garcez de Oliveira Padilha Lívia , Malek Lenka , Umberger Wendy J.
Published: May 2021

Sustainability is a complex and multifaceted concept that comprises environmental, economic, social, and cultural dimensions. Growing consumer concerns over the impacts of global meat production and consumption have led to increasing interest in sustainability initiatives and the use of sustainability labels. Yet, an understanding of what sustainability means to consumers in the context of meat and how consumers relate production-related credence attributes of chicken meat to sustainability remains limited. Between September 2019 and January 2020, an exploratory research study was conducted using a multi-method approach. Participants completed an online survey before participating in a series of eye-tracking choice tasks followed by in-depth interviews. The study revealed that the environmental dimension of sustainability is most important to consumers’ definition of a “sustainable food system”. Likewise, the sustainability of chicken meat products was most commonly associated with the perceived environmental impact of chicken meat production, followed by animal welfare aspects. Consumers made incorrect inferences about some sustainability labels and these inferences sometimes contributed to positive associations with sustainability. Consumers frequently associated a higher price with higher sustainability, indicating a belief that “doing the right thing” might cost more. This study provides new insights regarding consumers’ perceptions of production-related credence attributes and sustainability labels.
Impact of Entrepreneurial Orientation on Innovation Capability: The Mediating Role of Absorptive Capability and Organizational Learning Capabilities
Authors: Makhloufi Lahcene , Laghouag Abderrazak Ahmed , Ali Sahli Alhussain , Belaid Fateh
Published: May 2021

Learning and knowledge creation are acknowledged as crucial drivers associated with entrepreneurial orientation (EO) and innovation capability (IC). Absorptive capacity (AC) harmonizes internal innovation-building activities with external opportunities, while organizational learning capabilities (OLC) foster entrepreneurial cognitive skills and innovation capabilities. This study aims to (1) predict the impact of absorptive capacity and organizational learning on IC and (2) to estimate the mediation effect of OLC and AC on the relationship between entrepreneurial orientation and innovation capabilities. Drawing upon the dynamic capability theory, the study had applied a cross-sectional survey targeting Algerian firms to test the hypotheses. The study findings indicate that EO is positively associated with innovation capability. Besides, even though both OLC and AC partially increase EO’s interaction impact on innovation capability as a mediation role, suggesting that the more a firm is entrepreneurially oriented, the more learning and knowledge creation processes are involved in the interaction relationship. This study’s core focus is to overcome the substantial role of learning and knowledge creation processes as an intangible proactive resource that fosters the EO mindset to get involved in innovation activities. It has been discovered that AC and OLC as a connectedness mechanism links external knowledge and internal learning processes to accompany EO readiness during innovation development.
Modeling the Influence of Roundabout Deflection on Its Efficiency as a Noise Abatement Measure
Authors: Ahac Saša , Ahac Maja , Domitrović Josipa , Dragčević Vesna
Published: May 2021

Challenges that emerge in roundabout design are mostly related to space constrictions and provision of appropriate deflection around the central island. This can result in speed profiles on roundabouts that might reduce their potential as a noise abatement measure. Because of this, the impact of a roundabout on noise levels and its applicability as a traffic calming device and a noise abatement measure should be investigated in the early design stage, by modeling noise levels. In this paper, the following hypothesis is tested: vehicle movement trajectories, defined during the fastest path performance check in roundabout early design phase, can be used as the road traffic noise sources when modeling noise at roundabouts using static noise model. This procedure (1) simplifies the preparation of the noise model, (2) results in a model that is closer to the real-world in terms of traffic flow conditions, (3) allows the noise calculations in the early stages of roundabout design, and (4) includes the influence of roundabout deflection on calculated noise levels. The abovementioned simplifications of the road traffic noise modeling process should encourage the optimization of roundabout geometry in terms of its noise reduction capabilities in the preliminary design phase of these intersections.
Effect of Visible Light on Surface-Attached and Suspended Heterotrophic Bacteria in a Typical Household Rainwater Harvesting Tank
Authors: Andriamanantena R. Vonihanitriniaina , Kim Mikyeong , Han Mooyoung
Published: May 2021

Rainwater harvesting (RWH) systems can be used to mitigate global water crises; however, they have been poorly received by communities because of the sub-standard quality of harvested water. Heterotrophic bacteria present in the water can degrade the water’s microbiological quality and create health issues. Moreover, exposure to visible light can affect both suspended and surface-attached heterotrophic bacteria, a phenomenon that is poorly investigated. This study explored the effect of visible light on surface-attached heterotrophs (SAB) and suspended heterotrophs (SB) in an RWH tank for a period of three months. The SAB plate counts were observed to be significantly higher in the tank exposed to sun (TES) than in the tank not exposed to sun (TNES). Furthermore, the SB plate counts in the TNES reduced 10 folds faster than in the TES, especially at the top and middle levels. When exposed to visible light, the phototrophs present in the water sustained the heterotrophs by producing nutrients via photosynthesis. Based on the findings of this research, this paper recommends providing shade to the tanks that are exposed to sunlight. Additionally, it suggests not to disinfect the tank because it leads to a decrease in the self-purification effect of microbes.
The Impact of EA-Driven Dynamic Capabilities, Innovativeness, and Structure on Organizational Benefits: A Variance and fsQCA Perspective
Authors: van de Wetering Rogier , Hendrickx Tom , Brinkkemper Sjaak , Kurnia Sherah
Published: May 2021

Enterprise Architecture (EA) allows firms to create value on the firm and operational levels. This paper argues that firms’ EA-driven dynamic capabilities lead to innovative value-creating actions and, ultimately, improve organizational benefits. Hence, we propose a theoretical model that explains how these dynamic capabilities enable the innovativeness of firms. Moreover, we explain the contingent role of an organic firm structure and its relation to firm innovativeness. Data within this study is collected from 299 CIOs and IT managers. This study uses a variance-based approach and a complementary fuzzy-set qualitative comparative analysis (fsQCA) to analyze the model’s hypothesized relationships. Our study outcomes demonstrate a positive relationship between EA-driven dynamic capabilities and firms’ innovativeness as well as between innovation and organizational benefits. Our post-hoc analyses using fsQCA reveal various circumstances in which organic firm structure and valuable, rare, inimitable, and non-substitutional (VRIN) firm resources are particularly relevant for firms to obtain high levels of firm innovativeness.
Evaluation of Environmental Information Disclosure of Listed Companies in China’s Heavy Pollution Industries: A Text Mining-Based Methodology
Authors: Cai Rongjiang , Lv Tao , Deng Xu
Published: May 2021

Environmental information disclosure (EID) of listed companies is a significant and essential reference for assessing their environmental protection commitment. However, the content and form of EID are complex, and previous assessment studies involved manual scoring mainly by the experts in this field. It is subjective and has low timeliness. Therefore, this paper proposes an automatic evaluation framework of EID quality based on text mining (TM), including the EID index system’s construction, automatic scoring of environmental information disclosure quality, and EID index calculation. Furthermore, based on the EID of 801 listed companies in China’s heavy pollution industry from 2013 to 2017, case studies are conducted. The case study results show that the overall quality of the EID of listed companies in China’s heavily polluting industries is low, and there is a gap differentiation between the 16 industries. Compared with the subjective manual scoring method, TM evaluation can evaluate the quality of EID more effectively and accurately. It has great potential and can become an essential tool for the sustainable development of society and listed companies.
Sustainability of Global Economic Policy and Stock Market Returns in Indonesia
Authors: Hashmi Shabir Mohsin , Gilal Muhammad Akram , Wong Wing-Keung
Published: May 2021

Interdependence in trade and financial globalization has increased the vulnerability of developed and developing countries to external shocks alike, whereas emerging markets are more vulnerable to the shocks originating from the world’s leading economies. This paper investigates the impact of the uncertainty from the global economic policy on the return of the Indonesian stock market by using the time-varying correlation based on the rolling window method and time-varying built dynamic conditional correlation method. Both the rolling window and condition correlation estimates indicate that the correlation between global policy uncertainty and Indonesian stock returns is time-varying. The results of the autoregressive distributed lag-based regression indicate that inflation, global crude oil prices, gross domestic product, and world crude oil production have significant impacts on the dynamic conditional correlation. The average negative estimate of time-varying correlation suggests that investors when faced with liquidity constraints in one country may sell off their assets in another country to raise funds in order to meet their future financial needs. This also indicates that the rise in the uncertainty of economic policy in developed markets has a negative impact on the shocks faced by the Indonesian stock market. Based on our empirical findings, it is recommended that Indonesian policymakers should place more focus on the sustainability of the economic growth, pay close attention to volatile crude oil prices, world crude oil production, and inflation so as to avoid dynamic interaction between the uncertainty of economic policy in the developed markets and the return of the Indonesian stock market.
From Waste to Product: Circular Economy Applications from Sea Urchin
Authors: Zilia Federico , Bacenetti Jacopo , Sugni Michela , Matarazzo Agata , Orsi Luigi
Published: May 2021

The classic linear economy model based on extraction, processing, production and waste no longer seems to be functional in a world where natural resources are starting to run out. For these reasons, the aim of this study is to analyse the transition from a linear system to the circular economy, providing an example of reuse of sea urchin waste for the creation of new eco-sustainable products. From a comprehensive literature review, it is provided a framework of all the properties deriving from marine collagen and other inedible parts of the sea urchin. Thanks to its characteristics, marine collagen is a valid support for production of biomedical devices, dermal implants, cosmetic and pharmaceutical products. To make their core business effective, companies should not consider only the financial perspectives but also the social and environmental aspects. Therefore, this work aims at analysing these three frameworks using the Triple-Layered Business Model Canvas, which is a useful tool to support the creative exploration of sustainable and innovative business models. The reuse of sea urchin waste is a clear example of how a circular economy model can be adopted for companies to be successful. Through this virtuous model, they can be projected towards a green economy based on a more eco-sustainable vision.
Growth and Physiological Responses of Three Landscape Plants to Calcium Chloride
Authors: Kwon Kei-Jung , Choi Jaehyuck , Kim Sang-Yong , Jeong Na-Ra , Park Bong-Ju
Published: May 2021

The objective of this study was to analyze the effects of calcium chloride (CaCl2) used as a de-icing agent on growth and physiological responses of three ground cover plants, Hosta longipes, Iris ensata, and Iris pseudacorus. CaCl2 concentration was set to be 0 mM (control), 9 mM (0.1%), 18 mM (0.2%), and 54 mM (0.6%). After treatment with CaCl2 for 3 months, plant heights, fresh weights of shoots and roots, photosynthetic rates, chlorophyll fluorescence, chlorophyll content (SPAD), and leaf water potential were measured. After Hosta longipes was treated with CaCl2 for 60 days, physiological damage began to occur in all treatment groups except for the control group. Those treated with 54 mM CaCl2 completely withered. At 90 days after treatment (DAT), there were significant differences for all measured parameters for Hosta longipes compared to the control (p < 0.001). The higher the treatment concentration, the lower the photosynthetic rate, the SPAD, and the leaf water potential. There was no significant difference in plant height in Iris ensata after 60 DAT (p > 0.05), but in other physiological responses, there was a significant difference by concentration (p < 0.001). Iris ensata had a visually healthier state at 90 DAT, showing the smallest reduction in photosynthetic rate at 60 DAT and 90 DAT. Its SPAD value was increased more at 90 DAT than at 60 DAT, indicating its higher resistance to CaCl2. Iris pseudacorus showed similar results as Iris ensata. Over time, the 54 mM treatment resulted in significant damage. Among these three plants, Iris ensata showed the highest tolerance to CaCl2. Therefore, they are considered to be highly beneficial ground cover plants for green infrastructure in urban areas with high CaCl2 concentrations.
The Effects of Psychological Capital and Internal Social Capital on Frontline Hotel Employees’ Adaptive Performance
Authors: Luo Cheng-Yi , Tsai Chin-Hsun (Ken) , Chen Ming-Hsiang , Gao Jun-Li
Published: May 2021

This study examines the relationship between psychological capital, social capital, and adaptive performance in China’s lodging industry. Recent research has revealed that the production attributes of internal social capital can explain adaptive performance, and that psychological capital affects the relationship attributes of social capital. This raises the question of whether social capital might mediate between psychological capital and adaptive performance. Therefore, this study examined data from a sample of 304 hotel employees in China, using internal social capital as a mediating variable. The results confirmed that psychological capital has a significant positive impact on adaptive performance. Social capital also plays a mediating role partially between psychological capital and adaptive performance. The findings of this study contribute to the theoretical framework of psychological capital and adaptive performance and provide a new approach to human resource management in the lodging industry and other dynamically competitive service industries.
Assessing the Transformability of Public Housing through BIM
Authors: Acampa Giovanna , Diana Lorenzo , Marino Giorgia , Marmo Rossella
Published: May 2021

Public residential buildings make a large portion of the European existing stock and they quite often require deep renovation interventions. A methodology for setting priorities and targeting regeneration investments should be defined relying on the increasing use of building information modelling (BIM) tools even for managing existing buildings. The aim of this paper is to integrate the evaluation process into BIM Revit software developing a specific plug-in, a Decision support system (DSS) that will help to identify the most appropriate flats to be transformed. It is based on measuring three indicators: Usability, Fragmentation, and Constructive Modifiability. Through their weighted average it is possible to obtain a final transformability score. The proposed approach has been tested on a case study chosen within the 1st P.E.E.P. (1st public plan for council and affordable housing) that has been approved in Rome in 1964. The results demonstrate that the transformability of apartments is related mainly to the Constructive Modifiability indicator and buildings with reinforced concrete frames show higher scores. A widespread application of such a methodology on large real estate portfolio may lead stakeholders involved in housing management investments in clear choices related to maintenance of buildings.
CO2 Utilization Strategy for Sustainable Cultivation of Mushrooms and Lettuces
Authors: Jung Dae-Ho , Son Jung-Eek
Published: May 2021

Mushroom cultivation generates a large amount of CO2 that can be used sustainably. The objective of this study was to use actual cultivation and simulation to find a sustainable cultivation method that uses the CO2 generated by king oyster mushrooms for the production of romaine lettuces. A closed cultivation system consisting of one mushroom chamber, three lettuce chambers, and one gas-mixing chamber was used. Two cultivation conditions, non-continuous and continuous, were analyzed. The non-continuous system cultivated 15 lettuces and 12 mushroom bottles at a time every 25 and 16 days, respectively. The continuous system cultivated three lettuces and mushroom bottles every five and four days, respectively, so that each chamber contained mushrooms or lettuces at each growth stage. The CO2 concentrations in the lettuce and mushroom chambers were stably maintained above 1000 μmol∙mol−1 and below 2000 μmol∙mol−1 in the continuous system. Mathematical models were developed to analyze the CO2 concentration in each chamber. The shoot dry weight of lettuces grown in the mixed cultivation were 48.0%, 21.9%, 19.7%, and 18.1% at 10, 15, 20, and 25 days after transplanting, respectively, higher than those in the lettuce-only cultivation. Compared to mushroom-only cultivation, mixed cultivation reduced the accumulated CO2 emissions into the air by 80.6%. Thus, using CO2 from mushrooms to cultivate lettuce in a continuous cultivation system could reduce CO2 emissions into the air and enable mixed cultivation of mushrooms and lettuces, achieving sustainable agriculture.
Self-Regulation of Motivation and Confinement by COVID-19: A Study in Spanish University Students
Authors: Santamaría-Vázquez Montserrat , Del Líbano Mario , Martínez-Lezaun Iratxe , Ortiz-Huerta Juan Hilario
Published: May 2021

(1) Background: confinement by COVID-19 in 2020 meant that face-to-face teaching changed to virtual teaching. The goal of this study was to test how confinement affected to self-regulation of motivation (SRM); (2) Methods: a longitudinal design was used to obtain information from 75 university students in three moments: before confinement, 20 days after confinement, and 40 days after confinement. The SRM Strategies Questionnaire and the Pittsburgh Sleep Index were used to evaluate the study variables; (3) Results: the SRM decreased as confinement progressed. Moreover, those students who had higher levels of SRM before confinement, showed worse sleep quality 20 days after. There was no interaction effect between moments and gender and between moments and work situation on any of the dimensions of the SRM. There were gender differences (women scored higher) in almost all of the SRM dimensions in the three moments, but there were no differences dependent on the work situation (i.e., only study or study and work); (4) Conclusions: the change from face-to-face classes to virtual learning decreased the SRM of university students and was related to worse sleep quality. Women showed higher levels of SRM than men, but these levels were reduced to the same extent in both genders.
Some Properties of the Arithmetic–Geometric Index
Authors: Molina Edil D. , Rodríguez José M. , Sánchez José L. , Sigarreta José M.
Published: May 2021

Recently, the arithmetic–geometric index (AG) was introduced, inspired by the well-known and studied geometric–arithmetic index (GA). In this work, we obtain new bounds on the arithmetic–geometric index, improving upon some already known bounds. In particular, we show families of graphs where such bounds are attained.
Estimation and Prediction for Gompertz Distribution under General Progressive Censoring
Authors: Wang Yuxuan , Gui Wenhao
Published: May 2021

In this article, we discuss the estimation of the parameters for Gompertz distribution and prediction using general progressive Type-II censoring. Based on the Expectation–Maximization algorithm, we calculate the maximum likelihood estimates. Bayesian estimates are considered under different loss functions, which are symmetrical, asymmetrical and balanced, respectively. An approximate method—Tierney and Kadane—is used to derive the estimates. Besides, the Metropolis-Hasting (MH) algorithm is applied to get the Bayesian estimates as well. According to Fisher information matrix, we acquire asymptotic confidence intervals. Bootstrap intervals are also established. Furthermore, we build the highest posterior density intervals through the sample generated by the MH algorithm. Then, Bayesian predictive intervals and estimates for future samples are provided. Finally, for evaluating the quality of the approaches, a numerical simulation study is implemented. In addition, we analyze two real datasets.
The Problem of the Non-Uniqueness of the Solution to the Inverse Problem of Recovering the Symmetric States of a Bistable Medium with Data on the Position of an Autowave Front
Authors: Levashova Natalia , Gorbachev Alexandr , Argun Raul , Lukyanenko Dmitry
Published: May 2021

The paper considers the question of the possibility of recovering symmetric stable states of a bistable medium in the inverse problem for a nonlinear singularly perturbed autowave equation by data given on the position of an autowave front propagating through it. It is shown that under certain conditions, this statement of the problem is ill-posed in the sense of the non-uniqueness of the solution. A regularizing approach to its solution was proposed.
KRRecover: An Auto-Recovery Tool for Hijacked Devices and Encrypted Files by Ransomwares on Android
Authors: Wang Senmiao , Qin Sujuan , He Nengqiang , Tu Tengfei , Hou Junjie , Zhang Hua , Shi Yijie
Published: May 2021

Ransomwares on Android have become a challenging threat, performing tasks such as hijacking screen resources, locking devices, and encrypting files. Even worse, with the evolution of ransomwares, many ransomwares can disable USB interfaces of mobile devices. It is difficult for users to recover their devices or decrypt files with the help of other equipment and gives monetary damages to victims. In this paper, we analyse the symmetry between the ransom behaviours and the source code of screen resource hijacked ransomwares, devices locked ransomwares and files encrypted ransomwares. We also propose strategies of recovering hijacked resources, recovering hijacked devices and decrypting encrypted files. To protect mobile devices and private files from ransomwares, we design and implement an automatic recovery application—KRRecover—which is used to recover the hijacked devices and decrypt encrypted files on Android.