bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation and Calibration of MODIS Near-Infrared Precipitable Water Vapor over China Using GNSS Observations and ERA-5 Reanalysis Dataset
Authors: Zhu Dantong , Zhang Kefei , Yang Liu , Wu Suqin , Li Longjiang
Published: July 2021

Water vapor is one of the most important parameters in climatic studies. MODerate-resolution Imaging Spectroradiometer (MODIS) is a key instrument and can provide spatially continuous precipitable water vapor (PWV) products. This study was focused on the performance evaluation of the MODIS near-infrared PWV product (MOD-NIR-PWV) over China. For a comprehensive assessment of the performance of MOD-NIR-PWV, PWV retrieved from the measurements at the global navigation satellite systems (GNSS) stations (i.e., GNSS-PWV) and the ERA5 reanalysis dataset (ERA-PWV) from 2013 to 2018 were used as the reference. To investigate the suitability of using ERA-PWV as the reference for the evaluation, ERA-PWV was compared to the high-accuracy GNSS-PWV at 246 GNSS stations and PWV retrieved from radiosonde observations (RS-PWV) at 78 radiosonde stations over China. The results showed that the mean bias and mean root-mean-square (RMS) of the differences between ERA-PWV and GNSS-PWV across all the stations were 0.5 and 1.7 mm, respectively, and the mean correlation coefficient of the two datasets was above 0.96. The values were 0.4 and 1.9 mm and 0.97, respectively, for the differences between ERA-PWV and RS-PWV. This suggests the suitability of ERA-PWV as the reference for the evaluation of MOD-NIR-PWV. In addition, MOD-NIR-PWV was compared with both GNSS-PWV and ERA-PWV, and their mean bias and mean RMS were 2.9 and 3.8 mm (compared to GNSS-PWV) and 2.1 and 3.0 mm (compared to ERA-PWV), respectively. The positive bias values and the non-normal distribution of the differences between MOD-NIR-PWV and both reference datasets imply that a considerable systematic overestimation of MOD-NIR-PWV over China may exist. To mitigate the systematic bias, ERA-PWV was utilized as the sample data due to its spatial continuities, and a grid-based calibration model was developed based on the annual and semiannual periodicities in the differences between MOD-NIR-PWV and ERA-PWV at each grid point. After applying the calibration model to correct MOD-NIR-PWV, the calibrated MOD-NIR-PWV was compared with ERA-PWV and GNSS-PWV for precision and accuracy analysis, respectively. The comparison showed that the model could significantly improve the precision by 94% and accuracy by 53%, which manifested the effectiveness of the calibration model in improving the performance of MOD-NIR-PWV over China.
Learning the Incremental Warp for 3D Vehicle Tracking in LiDAR Point Clouds
Authors: Tian Shengjing , Liu Xiuping , Liu Meng , Bian Yuhao , Gao Junbin , Yin Baocai
Published: July 2021

Object tracking from LiDAR point clouds, which are always incomplete, sparse, and unstructured, plays a crucial role in urban navigation. Some existing methods utilize a learned similarity network for locating the target, immensely limiting the advancements in tracking accuracy. In this study, we leveraged a powerful target discriminator and an accurate state estimator to robustly track target objects in challenging point cloud scenarios. Considering the complex nature of estimating the state, we extended the traditional Lucas and Kanade (LK) algorithm to 3D point cloud tracking. Specifically, we propose a state estimation subnetwork that aims to learn the incremental warp for updating the coarse target state. Moreover, to obtain a coarse state, we present a simple yet efficient discrimination subnetwork. It can project 3D shapes into a more discriminatory latent space by integrating the global feature into each point-wise feature. Experiments on KITTI and PandaSet datasets showed that compared with the most advanced of other methods, our proposed method can achieve significant improvements—in particular, up to 13.68% on KITTI.
OpenEDS2020 Challenge on Gaze Tracking for VR: Dataset and Results
Authors: Palmero Cristina , Sharma Abhishek , Behrendt Karsten , Krishnakumar Kapil , Komogortsev Oleg V. , Talathi Sachin S.
Published: July 2021

This paper summarizes the OpenEDS 2020 Challenge dataset, the proposed baselines, and results obtained by the top three winners of each competition: (1) Gaze prediction Challenge, with the goal of predicting the gaze vector 1 to 5 frames into the future based on a sequence of previous eye images, and (2) Sparse Temporal Semantic Segmentation Challenge, with the goal of using temporal information to propagate semantic eye labels to contiguous eye image frames. Both competitions were based on the OpenEDS2020 dataset, a novel dataset of eye-image sequences captured at a frame rate of 100 Hz under controlled illumination, using a virtual-reality head-mounted display with two synchronized eye-facing cameras. The dataset, which we make publicly available for the research community, consists of 87 subjects performing several gaze-elicited tasks, and is divided into 2 subsets, one for each competition task. The proposed baselines, based on deep learning approaches, obtained an average angular error of 5.37 degrees for gaze prediction, and a mean intersection over union score (mIoU) of 84.1% for semantic segmentation. The winning solutions were able to outperform the baselines, obtaining up to 3.17 degrees for the former task and 95.2% mIoU for the latter.
Deep ConvNet: Non-Random Weight Initialization for Repeatable Determinism, Examined with FSGM
Authors: Rudd-Orthner Richard N. M. , Mihaylova Lyudmila
Published: July 2021

A repeatable and deterministic non-random weight initialization method in convolutional layers of neural networks examined with the Fast Gradient Sign Method (FSGM). Using the FSGM approach as a technique to measure the initialization effect with controlled distortions in transferred learning, varying the dataset numerical similarity. The focus is on convolutional layers with induced earlier learning through the use of striped forms for image classification. Which provided a higher performing accuracy in the first epoch, with improvements of between 3–5% in a well known benchmark model, and also ~10% in a color image dataset (MTARSI2), using a dissimilar model architecture. The proposed method is robust to limit optimization approaches like Glorot/Xavier and He initialization. Arguably the approach is within a new category of weight initialization methods, as a number sequence substitution of random numbers, without a tether to the dataset. When examined under the FGSM approach with transferred learning, the proposed method when used with higher distortions (numerically dissimilar datasets), is less compromised against the original cross-validation dataset, at ~31% accuracy instead of ~9%. This is an indication of higher retention of the original fitting in transferred learning.
Multi-Beam Steering for 6G Communications Based on Graphene Metasurfaces
Authors: Ai Huifang , Kang Qianlong , Wang Wei , Guo Kai , Guo Zhongyi
Published: July 2021

As communication technology is entering the 6G era, a great demand for high-performance devices operating in the terahertz (THz) band has emerged. As an important part of 6G technology, indoor communication requires multi-beam steering and tracking to serve multi-users. In this paper, we have designed a graphene metasurface that can realize multi-beam steering for directional radiations. The designed metasurface consists of graphene ribbons, dielectric spacer, and metal substrate. By designing the graphene ribbons and controlling the applied voltage on them, we have obtained single-, double-, and triple-beam steering. In addition, we have also numerically calculated the far-field distributions of the steered multi-beam with a diffraction distance of 2 m. Our design has potential applications in future indoor directional 6G communications.
Validity Analysis of WalkerViewTM Instrumented Treadmill for Measuring Spatiotemporal and Kinematic Gait Parameters
Authors: Bravi Marco , Massaroni Carlo , Santacaterina Fabio , Di Tocco Joshua , Schena Emiliano , Sterzi Silvia , Bressi Federica , Miccinilli Sandra
Published: July 2021

The detection of gait abnormalities is essential for professionals involved in the rehabilitation of walking disorders. Instrumented treadmills are spreading as an alternative to overground gait analysis. To date, the use of these instruments for recording kinematic gait parameters is still limited in clinical practice due to the lack of validation studies. This study aims to investigate the performance of a multi-sensor instrumented treadmill (i.e., WalkerViewTM, WV) for performing gait analysis. Seventeen participants performed a single gait test on the WV at three different speeds (i.e., 3 km/h, 5 km/h, and 6.6 km/h). In each trial, spatiotemporal and kinematic parameters were recorded simultaneously by the WV and by a motion capture system used as the reference. Intraclass correlation coefficient (ICC) of spatiotemporal parameters showed fair to excellent agreement at the three walking speeds for steps time, cadence, and step length (range 0.502–0.996); weaker levels of agreement were found for stance and swing time at all the tested walking speeds. Bland–Altman analysis of spatiotemporal parameters showed a mean of difference (MOD) maximum value of 0.04 s for swing/stance time and WV underestimation of 2.16 cm for step length. As for kinematic variables, ICC showed fair to excellent agreement (ICC > 0.5) for total range of motion (ROM) of hip at 3 km/h (range 0.579–0.735); weaker levels of ICC were found at 5 km/h and 6.6 km/h (range 0.219–0.447). ICC values of total knee ROM showed poor levels of agreement at all the tested walking speeds. Bland–Altman analysis of hip ROM revealed a higher MOD value at higher speeds up to 3.91°; the MOD values of the knee ROM were always higher than 7.67° with a 60° mean value of ROM. We demonstrated that the WV is a valid tool for analyzing the spatiotemporal parameters of walking and assessing the hip’s total ROM. Knee total ROM and all kinematic peak values should be carefully evaluated, having shown lower levels of agreement.
OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection
Authors: Abbasi Saad , Famouri Mahmoud , Shafiee Mohammad Javad , Wong Alexander
Published: July 2021

Human operators often diagnose industrial machinery via anomalous sounds. Given the new advances in the field of machine learning, automated acoustic anomaly detection can lead to reliable maintenance of machinery. However, deep learning-driven anomaly detection methods often require an extensive amount of computational resources prohibiting their deployment in factories. Here we explore a machine-driven design exploration strategy to create OutlierNets, a family of highly compact deep convolutional autoencoder network architectures featuring as few as 686 parameters, model sizes as small as 2.7 KB, and as low as 2.8 million FLOPs, with a detection accuracy matching or exceeding published architectures with as many as 4 million parameters. The architectures are deployed on an Intel Core i5 as well as a ARM Cortex A72 to assess performance on hardware that is likely to be used in industry. Experimental results on the model’s latency show that the OutlierNet architectures can achieve as much as 30× lower latency than published networks.
The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review
Authors: Jourdan Théo , Debs Noëlie , Frindel Carole
Published: July 2021

Gait, balance, and coordination are important in the development of chronic disease, but the ability to accurately assess these in the daily lives of patients may be limited by traditional biased assessment tools. Wearable sensors offer the possibility of minimizing the main limitations of traditional assessment tools by generating quantitative data on a regular basis, which can greatly improve the home monitoring of patients. However, these commercial sensors must be validated in this context with rigorous validation methods. This scoping review summarizes the state-of-the-art between 2010 and 2020 in terms of the use of commercial wearable devices for gait monitoring in patients. For this specific period, 10 databases were searched and 564 records were retrieved from the associated search. This scoping review included 70 studies investigating one or more wearable sensors used to automatically track patient gait in the field. The majority of studies (95%) utilized accelerometers either by itself (N = 17 of 70) or embedded into a device (N = 57 of 70) and/or gyroscopes (51%) to automatically monitor gait via wearable sensors. All of the studies (N = 70) used one or more validation methods in which “ground truth” data were reported. Regarding the validation of wearable sensors, studies using machine learning have become more numerous since 2010, at 17% of included studies. This scoping review highlights the current state of the ability of commercial sensors to enhance traditional methods of gait assessment by passively monitoring gait in daily life, over long periods of time, and with minimal user interaction. Considering our review of the last 10 years in this field, machine learning approaches are algorithms to be considered for the future. These are in fact data-based approaches which, as long as the data collected are numerous, annotated, and representative, allow for the training of an effective model. In this context, commercial wearable sensors allowing for increased data collection and good patient adherence through efforts of miniaturization, energy consumption, and comfort will contribute to its future success.
Business Simulation Games Analysis Supported by Human-Computer Interfaces: A Systematic Review
Authors: Ferreira Cleiton Pons , González-González Carina Soledad , Adamatti Diana Francisca
Published: July 2021

This article performs a Systematic Review of studies to answer the question: What are the researches related to the learning process with (Serious) Business Games using data collection techniques with Electroencephalogram or Eye tracking signals? The PRISMA declaration method was used to guide the search and inclusion of works related to the elaboration of this study. The 19 references resulting from the critical evaluation initially point to a gap in investigations into using these devices to monitor serious games for learning in organizational environments. An approximation with equivalent sensing studies in serious games for the contribution of skills and competencies indicates that continuous monitoring measures, such as mental state and eye fixation, proved to identify the players’ attention levels effectively. Also, these studies showed effectiveness in the flow at different moments of the task, motivating and justifying the replication of these studies as a source of insights for the optimized design of business learning tools. This study is the first systematic review and consolidates the existing literature on user experience analysis of business simulation games supported by human-computer interfaces.
An Automated Pipeline for Dynamic Detection of Sub-Surface Metal Loss Defects across Cold Thermography Images
Authors: Doshvarpassand Siavash , Wang Xiangyu
Published: July 2021

Utilising cooling stimulation as a thermal excitation means has demonstrated profound capabilities of detecting sub-surface metal loss using thermography. Previously, a prototype mechanism was introduced which accommodates a thermal camera and cooling source and operates in a reciprocating motion scanning the test piece while cold stimulation is in operation. Immediately after that, the camera registers the thermal evolution. However, thermal reflections, non-uniform stimulation and lateral heat diffusions will remain as undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no prior knowledge of the non-defective area in order to effectively distinguish between defective and non-defective areas. In this work, the previously automated acquisition and processing pipeline is re-designed and optimised for two purposes: 1—Through the previous work, the mentioned pipeline was used to analyse a specific area of the test piece surface in order to reconstruct the reference area and identify defects. In order to expand the application of this device over the entire test area, regardless of its extension, the pipeline is improved in which the final surface image is reconstructed by taking into account multiple segments of the test surface. The previously introduced pre-processing method of Dynamic Reference Reconstruction (DRR) is enhanced by using a more rigorous thresholding procedure. Principal Component Analysis (PCA) is then used in order for feature (DRR images) reduction. 2—The results of PCA on multiple segment images of the test surface revealed different ranges of intensities across each segment image. This potentially could cause mistaken interpretation of the defective and non-defective areas. An automated segmentation method based on Gaussian Mixture Model (GMM) is used to assist the expert user in more effective detection of the defective areas when the non-defective areas are uniformly characterised as background. The final results of GMM have shown not only the capability of accurately detecting subsurface metal loss as low as 37.5% but also the successful detection of defects that were either unidentifiable or invisible in either the original thermal images or their PCA transformed results.
Impact of Youth-in-Agribusiness Program on Employment Creation in Nigeria
Authors: Bello Lateef Olalekan , Baiyegunhi Lloyd James Segun , Mignouna Djana , Adeoti Razack , Dontsop-Nguezet Paul Matin , Abdoulaye Tahirou , Manyong Victor , Bamba Zoumana , Awotide Bola Amoke
Published: July 2021

The increasing rate of youth unemployment in Africa, particularly in Nigeria, remains among the challenges to social and economic stability. Accordingly, the Nigerian government implemented several interventions, including the Youth-in-Agribusiness (YIA) program to reduce youth unemployment. However, the effect of these programs on gainful employment creation is yet to be documented. Therefore, this study examined the impact of the YIA program on creating gainful employment among the youth. Multistage random sampling was used to obtain cross-sectional data from 668 youth in Southwestern Nigeria. Propensity score matching and endogenous switching probit techniques were used for the estimations. Results indicated that variables such as educational attainment, access to training, non-agricultural activity, membership in a youth organization, access to credit, productive resources, and youth location were significant and positively influenced youth decision to participate in the YIA program. Furthermore, participation in the YIA program has a significant positive impact on gainful employment among the youth. Therefore, the study recommends that strengthening social capital such as youth organization, credit scheme (financed by private and government), vocational training, and educational system is vital in enhancing participation in the YIA program and eventually gainful employment of youth.
Effect of Space Configurational Attributes on Social Interactions in Urban Parks
Authors: Sheng Qiang , Wan Dongyang , Yu Boya
Published: July 2021

Urban parks are one of the most common spaces for social interactions in modern cities. The design of park spaces, especially space configuration, has significant influences on people’s social behaviors in parks. In this study, the associations between space configurational attributes and social interactions were investigated using space syntax theory. An observation analysis of social behaviors was carried out in two urban parks in Beijing, China. Nine space configurational attributes, including depth to the gate, depth to the main road, connectivity, normalized angular integration (NAIN), and normalized angular choice (NACH) with three radii, were calculated using a segment model. The variance analysis and regression analysis reveal the strong joint effect of space type, space scale factors, and space configurational attributes on social interaction behaviors in parks. The personal interaction group contained 23% of the total observed people involved in social interactions. Pathway length, zone area, and NACH-10K (NACH with a radius of 10,000 m) are positively associated with the number of people involved in personal interactions. For the social interaction group (77% of the total observed people), the space scale and depth to main city road were found to have a positive and negative influence on social interaction intensity.
Differences on Habitual Physical Activity Index in Primary Schoolchildren according to Age and Gender
Authors: Navarro-Patón Rubén , Arufe-Giráldez Víctor , Sanmiguel-Rodríguez Alberto , Ramos-Álvarez Oliver
Published: July 2021

The World Health Organization (WHO) has warned that a large majority of children do not reach its recommendations on physical activity for health, i.e., 60 min a day of moderate to vigorous physical activity. The objective of this study was to know the index of habitual physical activity in different contexts where the child interacts: school index (SCHOOL-I), extracurricular/sports activity index (SPORT-I), free time index (LEISURE-I) and the total habitual physical activity index (GLOBAL-I) based on age and gender. 900 Primary Education schoolchildren from Galicia (Spain) aged 10–12 years (M = 10.84; SD = 0.67) participated, of which 454 (50.40%) were boys and 446 (49.6%) girls. For data collection, the validated Inventory of Habitual Physical Activity in Schoolchildren (IAFHE) questionnaire was used. The results show a significant main effect on the age factor in SCHOOL-I (p < 0.001), and in GLOBAL-I (p = 0.034), the rates being higher in 10-year-old children compared to 11 and 12. A significant main effect has also been found in the gender factor in SCHOOL-I (p < 0.001), SPORT-I (p < 0.001) and in GLOBAL-I (p < 0.001), being greater in boys than in girls. It is concluded that, as school age increases, a lower index of physical activity is registered, this being higher in boys compared to girls. It is necessary to establish strategies to promote the practice of physical activity from different agents and in different contexts.
Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators
Authors: Razmjoo Armin , Nezhad Meysam Majidi , Kaigutha Lisa Gakenia , Marzband Mousa , Mirjalili Seyedali , Pazhoohesh Mehdi , Memon Saim , Ehyaei Mehdi A. , Piras Giuseppe
Published: July 2021

With a goal of achieving net-zero emissions by developing Smart Cities (SCs) and industrial decarbonization, there is a growing desire to decarbonize the renewable energy sector by accelerating green buildings (GBs) construction, electric vehicles (EVs), and ensuring long-term stability, with the expectation that emissions will need to be reduced by at least two thirds by 2035 and by at least 90% by 2050. Implementing GBs in urban areas and encouraging the use of EVs are cornerstones of transition towards SCs, and practical actions that governments can consider to help with improving the environment and develop SCs. This paper investigates different aspects of smart cities development and introduces new feasible indicators related to GBs and EVs in designing SCs, presenting existing barriers to smart cities development, and solutions to overcome them. The results demonstrate that feasible and achievable policies such as the development of the zero-energy, attention to design parameters, implementation of effective indicators for GBs and EVs, implementing strategies to reduce the cost of production of EVs whilst maintaining good quality standards, load management, and integrating EVs successfully into the electricity system, are important in smart cities development. Therefore, strategies to governments should consider the full dynamics and potential of socio-economic and climate change by implementing new energy policies on increasing investment in EVs, and GBs development by considering energy, energy, techno-economic, and environmental benefits.
Geological Approach for Landfill Site Selection: A Case Study of Vršac Municipality, Serbia
Authors: Carević Ivana , Sibinović Mikica , Manojlović Sanja , Batoćanin Natalija , Petrović Aleksandar S. , Srejić Tanja
Published: July 2021

One of the biggest problems of environmental protection in Serbia is landfills. It is often a case that the economic interests are predominant in the landfill sitting; thus, most landfills are not located according to standards. This study shows that detailed geological data assets combined with geographical modeling represents a reliable way to define and locate the landfill site. Geological evaluation is discussed in detail with regard to bedrock lithology, quaternary geology, geological structure, hydrogeology, surface runoff patterns, and topography. An approach combining geographical modeling and geology is presented for determining the sites suitable for landfill selection with respect to their geologic favorability. As opposed to numerous research papers on this topic, in the methodological procedure, special importance is devoted to the analysis of the geological criteria. In this way, it is significantly easier to determine the landfill area with the best characteristics due to geological structure and lithology which unequivocally and precisely indicates inadequate territories for candidate sites. The multicriteria decision analysis (MCDA) is based on geological criteria upgraded with road (primary, residential, secondary, and tertiary), settlements network, railway, airport, infrastructure, land use, hypsometry aquifer, wetland, and surface water. The score values are divided into four classes, i.e., restricted areas, suitable but avoid, suitable, and most suitable. Combining geographical modeling with geology led to the recognition of two locations to be most favorable for landfill site located in the most suitable area, which represents 25.3% of the study area.
Improvement of the Outdoor Thermal Comfort by Water Spraying in a High-Density Urban Environment under the Influence of a Future (2050) Climate
Authors: Wai Ka-Ming , Xiao Lei , Tan Tanya Zheng
Published: July 2021

Adaptation to prepare for adverse climate change impacts in the context of urban heat islands and outdoor thermal comfort (OTC) is receiving growing concern. However, knowledge of quantitative microclimatic conditions within the urban boundary layer in the future is still lacking, such that the introduction of adequate adaptation measures to increase OTC is challenging. To investigate the cooling performance of a water spraying system in a sub-tropical compact and high-rise built environment in summer under the influence of future (2050) climatic conditions, results from two validated models (Weather Research and Forecast (WRF) and ENVI-met models) have been used and analyzed. Our results indicate that the spraying system provides cooling of 2–3 °C for ambient air temperature at the pedestrian-level of the urban canyons considered here, which benefits pedestrians. However, improvement of the OTC in terms of the physiological equivalent temperature (PET—a better indicator of human thermal sensation) was noticeable (e.g., <42 °C or from very hot to hot) when the urban canyon was orientated parallel to the prevailing wind direction only. This implies that in order to improve city resilience in terms of heat stress, more holistic adaptation measures in urban planning are needed. This includes the introduction of more breezeways and building disposition to facilitate the urban ventilation, as well as urban tree arrangement and sunshades to reduce direct solar radiation to plan for the impact of future climate change.
Residents’ Cognition and Behavior Related to Eco-Environmental Risks from the Development of Large Coal Power Plants: A Case Study in Xilinhot, Inner Mongolia
Authors: Ma Yan , Ma Yan , Cao Zhiguo , Li Shuyi , Lv Bowen , Ruan Ziyuan , Wang Lina , Yu Hong , Lu Zhaohua
Published: July 2021

The development of large coal power plants is often accompanied by environmental pollution, thereby influencing the lives of the surrounding residents, resulting in a “not-in-my-backyard” effect and associated social injustice. To mitigate these influences, we conducted field research and questionnaire surveys with individuals living in areas around the Xilinhot coal power plant to explore their cognitive and behavioral psychological changes in response to the environmental risks of the coal power plant and the factors influencing such changes. A “cognition-perception-behavior” model was constructed for residents coping with the ecological environment influenced by the development of the coal power plant. Cognition of eco-environmental risks had a significant effect on the perception of eco-environmental risks which, in turn, significantly promoted the adoption of adaptive behaviors. Residents had a strong cognition and perception of eco-environmental risks but an extremely low likelihood of adopting relevant adaptive behaviors. Thus, affective responses can increase the residents’ cognition and perception of eco-environmental risks, and the communication of risk information can help them evaluate eco-environmental risks rationally.
Timely Loss Recognition Helps Nothing
Authors: Lin Hung-Wen , Lin Kun-Ben , Huang Jing-Bo , Chen Shu-Heng
Published: July 2021

This paper digests the relationship between the manipulation of losses and price reversals in the Chinese stock market. Timely loss recognition is involved in detecting the manipulation of losses, while price reversals are investigated by momentum profit. In addition, two-way sorting momentum portfolios are employed to connect manipulating losses with price reversals. Companies with low timely loss recognition aggressively manipulate their losses, and our results indicate that they generate much more significantly negative momentum profits. As a consequence, they cannot build up any immunity against reversal risks and encounter much higher reversal risks than other companies. Such findings still hold after the risk adjustments using asset pricing models come into play and when controlling for the calendar effect. This research indeed suggests that investors should exercise caution when dealing with companies whose financial information is too positive. Such companies may dress up their financial reports, thereby significantly increasing the risks associated with price reversals.
Quantitative Assessment of Environmental Sensitivity to Desertification Using the Modified MEDALUS Model in a Semiarid Area
Authors: Afzali Sayed Fakhreddin , Khanamani Ali , Maskooni Ehsan Kamali , Berndtsson Ronny
Published: July 2021

Iran is mainly located in the arid and semiarid climate zone and seriously affected by desertification. This is a severe environmental problem, which results in a persistent loss of ecosystem services that are fundamental to sustaining life. Process understanding of this phenomenon through the evaluation of important drivers is, however, a challenging work. The main purpose of this study was to perform a quantitative evaluation of the current desertification status in the Segzi Plain, Isfahan Province, Iran, through the modified Mediterranean Desertification and Land Use (MEDALUS) model and GIS. In this regard, five main indicators including soil, groundwater, vegetation cover, climate, and erosion were selected for estimating the environmental sensitivity to desertification. Each of these qualitative indicators is driven by human interference and climate. After statistical analysis and a normality test for each indicator data, spatial distribution maps were established. Then, the maps were scored in the MEDALUS approach, and the current desertification status in the study area from the geometric mean of all five quality indicators was created. Based on the results of the modified MEDALUS model, about 23.5% of the total area can be classified as high risk to desertification and 76.5% classified as very high risk to desertification. The results indicate that climate, vegetation, and groundwater quality are the most important drivers for desertification in the study area. Erosion (wind and water) and soil indices have minimal importance.
Developing Farm-Level Social Indicators for Agri-Environment Schemes: A Focus on the Agents of Change
Authors: Mills Jane , Chiswell Hannah , Gaskell Peter , Courtney Paul , Brockett Beth , Cusworth George , Lobley Matt
Published: July 2021

Most monitoring and evaluation programmes for agri-environment schemes focus on understanding the environmental outcomes and the cost-effectiveness of these schemes. Evaluation of the social dimensions of agri-environment schemes, particularly the socio-cultural factors that might influence the quality of engagement with the schemes and the social wellbeing impact of scheme engagement, is limited. This is a critical gap in knowledge as there is growing recognition that without more explicit consideration of the farmers involved in land management as agents of change, the required environmental improvements will not be achieved. The aim of this paper was to undertake a systematic literature review to inform the development of a set of social indicators that can be used to measure the level of farmers’ engagement with their scheme agreement and the social sustainability outcomes from participation. Following the literature review and a short-listing ranking exercise with two sets of experts, 20 high-level (composite) social indicators and associated sub-level (component) indicators were identified. A series of scale or ranking questions that can be used to capture the indicator data were also developed and tested. This paper presents the first stage in the development of a robust set of social indicators for agri-environment schemes that will also provide a good indicator of long-term environmental outcomes.
Resilience Reporting for Sustainable Development in Cities
Authors: Bruzzone Monica , Dameri Renata Paola , Demartini Paola
Published: July 2021

Recently, a new paradigm has emerged—the resilient city. It is an evolutionary concept rooted in recent—but more consolidated—city visions, such as a smart city or a sustainable city, from which it inherits the interweaving of different dimensions. This paper investigates the factors behind effective resilience reporting, as well as how a city should draw up an urban resilience strategy report to be accountable to its citizens. We first highlighted the main factors to design and implement reporting for the achievement of strategic resilience goals, by combining research on a resilient city and accountability practices. These factors could be organized following two different perspectives: political and sociotechnical. Then, we applied our framework to four pioneering municipalities selected as paradigmatic case studies. A qualitative content analysis applied to the city resilience reports has provided depth to our framework. We found that the “weak factor” is the ability to embed the resilience strategy in rooted connections and transform itself into an ecosystem that crosscuts different sectoral urban processes. Our exploratory research claims could be used for future research in this field, as cities are becoming increasingly complex systems, where the quality of life and well-being of a larger population depends.
Developing an Environmental Management System for Evaluating Green Casino Hotels
Authors: Cheong Fan , Lee Young-Hee
Published: July 2021

In the field of tourism, casino hotels consume considerable energy and water resources. They differ from general hotels due to their specific features; consequently, the environmental practices of casino hotels differ from those of general hotels. Thus, the application of a general hotel’s environmental management system (EMS) to a casino hotel is not suitable. To this end, in this study we developed an EMS for green casino hotels in Macau. We selected the casino hotel EMS indicators from ISO 14000 and nine representative green hotel evaluation systems. We additionally employed the Delphi method to determine the preliminary EMS evaluation framework. Based on our findings, indicators in 10 dimensions were identified and prioritized according to their relative importance and feasibility. The EMS developed in this study provides management suggestions for governments, hoteliers, and consumers to improve environmental management.
Perspective Biomethane Potential and Its Utilization in the Transport Sector in the Current Situation of Latvia
Authors: Argalis Pauls P. , Vegere Kristine
Published: July 2021

A major problem in the modern world is the overuse of fossil resources. The use of such resources and of that amount contribute negatively to the environment we live in. Fossil resources should be replaced with renewable ones. That way, less impact would be done to the environment. Renewable resources would greatly contribute to a healthy sustainable future. Latvia currently ranks seventh on the number of biogas plants per 1 million per capita (27) and is searching for new ways and opportunities to switch from the production of electricity to biomethane. Thus, in this study, a mathematical approach for the calculations of biomethane potentials and emissions of different feedstocks under the anaerobic digestion principle was studied. Databases were searched for the factual numbers of livestock animals, as well as processed sludge, and average food waste. RED II and JEC Well-To-Wheels report v5 were analyzed for data on emission factors and future obligations. Out of combined biomethane potentials of different feedstocks, livestock manure’s potential share was 91%, of which 61% is dairy cow manure. The overall biomethane potential in Latvia is 2.21 to 4.28 PJ. Replacing fossil fuels with biomethane in the transport sector could lower the overall CO2-eq emissions by 12.47–23.86% or 0.4–0.8 million tonnes.
TSO-DSO Coordination Schemes to Facilitate Distributed Resources Integration
Authors: Najibi Fatemeh , Apostolopoulou Dimitra , Alonso Eduardo
Published: July 2021

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. In order to achieve this, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.
Soil Arthropods in the Douro Demarcated Region Vineyards: General Characteristics and Ecosystem Services Provided
Authors: Gonçalves Fátima , Carlos Cristina , Crespo Luís , Zina Vera , Oliveira Amália , Salvação Juliana , Pereira José Alberto , Torres Laura
Published: July 2021

Viticulture is one of the oldest and most profitable forms of agriculture; it is also one of the most intensive farming systems. As intensive cultivation threatens the environment, there is increasing interest in the concept of sustainability within the wine industry, as well as new business opportunities, as customers begin to pay more attention to environmental and sustainability issues. Recognizing the key role of soil quality in environmentally and economically sustainable viticulture makes it essential to understand better soil arthropod communities, given their crucial functions in maintaining soil quality and health. The ‘Douro Demarcated Region’ (DDR) in northern Portugal offers good potential, in regards to biodiversity, due to its significant areas of non-crop habitats. This work aims to compile information on soil arthropod communities (both soil surface and soil-living) collected in the DDR vineyard agroecosystems. A description of the ecosystem services provided by them, as a basis for the development and implementation of sustainable viticulture systems, is also an objective of this work. An important set of soil arthropods necessary for the delivery of vital ecosystem services for viticulture, with particular reference to supporting and regulating services, occurred in this ecosystem. Eight classes were chiefly represented in a sample of about 167,000 arthropod specimens: Arachnida, Chilopoda, Diplopoda, Entognatha, Insecta, Malacostraca, Pauropoda, and Symphyla. The most representative were Entognatha and Insecta in soil-surface arthropods, and Arachnida and Entognatha in soil-living arthropods. The presence of recognized groups as bioindicators in agroecosystems, such as soil quality indicators, is also revealed. This knowledge is expected to contribute to a more efficient and sustainable management of the viticultural ecosystem.
Safety Leadership as a Means for Safe and Sustainable Shipping
Authors: Hasanspahić Nermin , Frančić Vlado , Vujičić Srđan , Mandušić Mario
Published: July 2021

Safety leadership is critical in high-risk industries such as shipping since inadequate leadership can cause marine accidents, resulting in injuries, fatalities, damage to property and environmental pollution. One of the aspects of good and effective safety leadership is creating good human relations and satisfaction among crewmembers, considered a precondition for effective teamwork. Officers on board ships should establish effective teamwork and implement adequate safety leadership, positively affecting safety culture, increasing safety in general and improving marine environment protection. Safety leadership onboard ships comprises several characteristics, including maintaining safe work performance, carrying out safety training, and encouraging crewmember morale. Therefore, it is essential for all stakeholders in shipping industries that officers onboard ships can identify those characteristics, adapt, and apply them adequately. This paper presents the characteristics and skills that shipboard officers need to apply in order to be excellent leaders and serve with adequate safety leadership abilities. One tool for recognizing those characteristics and skills was a survey carried out among experienced professional seafarers. Analysis of the survey data revealed latent factors, these being transformational and transactional leadership elements affecting safety leadership onboard ships.
A Novel Single-Loop Mechanism and the Associated Cylindrical Deployable Mechanisms
Authors: Huang Long , Liu Bei , Yin Lairong , Wang Jinhang
Published: July 2021

This paper presents a new type of 2-DOF single-loop mechanism inspired by the Sarrus mechanism, and it utilizes this mechanism to construct 2-DOF cylindrical deployable mechanisms. First, the motion pattern of the single-loop mechanism is analyzed utilizing screw theory. According to the structural symmetries, the cylindrical deployable mechanisms are constructed through the linear pattern combination and circular pattern combination of the single-loop mechanisms. After the geometrical analysis and interference condition analysis, the axial, circumferential and area magnification ratios are defined and, furthermore, applied to the parameter optimization of the deployable mechanisms, forming an example surface. Finally, a simplified 1-DOF single-loop mechanism is derived from the proposed 2-DOF mechanism, which is used to construct 1-DOF cylindrical deployable mechanisms with singular free workspaces.
Control of a Symmetric Chaotic Supply Chain System Using a New Fixed-Time Super-Twisting Sliding Mode Technique Subject to Control Input Limitations
Authors: Wang Bo , Jahanshahi Hadi , Volos Christos , Bekiros Stelios , Yusuf Abdullahi , Agarwal Praveen , Aly Ayman A.
Published: July 2021

Control of supply chains with chaotic dynamics is an important, yet daunting challenge because of the limitations and constraints there are in the amplitude of control efforts. In real-world systems, applying control techniques that need a large amplitude signal is impractical. In the literature, there is no study that considers the control of supply chain systems subject to control input limitations. To this end, in the current study, a new control scheme is proposed to tackle this issue. In the designed control input, limitations in control inputs, as well as robustness against uncertainties, are taken into account. The proposed scheme is equipped with a fixed time disturbance observer to eliminate the destructive effects of uncertainties and disturbances. Additionally, the super-twisting sliding mode technique guarantees the fixed-time convergence of the closed-loop system. After that, a symmetric supply chain system is presented, and its chaotic attractors are demonstrated. Finally, the proposed controller is applied to the symmetric supply chain system. Numerical simulations exhibit the proposed scheme’s excellent performance even though the system is subjected to control input limitations and time-varying uncertainties.
The Uniform Poisson–Ailamujia Distribution: Actuarial Measures and Applications in Biological Science
Authors: Aljohani Hassan M. , Akdoğan Yunus , Cordeiro Gauss M. , Afify Ahmed Z.
Published: July 2021

We propose a new asymmetric discrete model by combining the uniform and Poisson–Ailamujia distributions using the binomial decay transformation method. The distribution, named the uniform Poisson–Ailamujia, due to its flexibility is a good alternative to the well-known Poisson and geometric distributions for real data applications in public health, biology, sociology, medicine, and agriculture. Its main statistical properties are studied, including the cumulative and hazard rate functions, moments, and entropy. The new distribution is considered to be suitable for modeling purposes; its parameter is estimated by eight classical methods. Three applications to biological data are presented herein.