bluuebunny/crossref_metadata_2025 huggingface dataset:
Radar High-Resolution Range Profile Ship Recognition Using Two-Channel Convolutional Neural Networks Concatenated with Bidirectional Long Short-Term Memory
Authors: Lin Chih-Lung , Chen Tsung-Pin , Fan Kuo-Chin , Cheng Hsu-Yung , Chuang Chi-Hung
Published: March 2021

Radar automatic target recognition is a critical research topic in radar signal processing. Radar high-resolution range profiles (HRRPs) describe the radar characteristics of a target, that is, the characteristics of the target that is reflected by the microwave emitted by the radar are implicit in it. In conventional radar HRRP target recognition methods, prior knowledge of the radar is necessary for target recognition. The application of deep-learning methods in HRRPs began in recent years, and most of them are convolutional neural network (CNN) and its variants, and recurrent neural network (RNN) and the combination of RNN and CNN are relatively rarely used. The continuous pulses emitted by the radar hit the ship target, and the received HRRPs of the reflected wave seem to provide the geometric characteristics of the ship target structure. When the radar pulses are transmitted to the ship, different positions on the ship have different structures, so each range cell of the echo reflected in the HRRP will be different, and adjacent structures should also have continuous relational characteristics. This inspired the authors to propose a model to concatenate the features extracted by the two-channel CNN with bidirectional long short-term memory (BiLSTM). Various filters are used in two-channel CNN to extract deep features and fed into the following BiLSTM. The BiLSTM model can effectively capture long-distance dependence, because BiLSTM can be trained to retain critical information and achieve two-way timing dependence. Therefore, the two-way spatial relationship between adjacent range cells can be used to obtain excellent recognition performance. The experimental results revealed that the proposed method is robust and effective for ship recognition.
Influence of Impervious Surface Area and Fractional Vegetation Cover on Seasonal Urban Surface Heating/Cooling Rates
Authors: Zhang Youshui , Balzter Heiko , Li Yu
Published: March 2021

The urban thermal environment is impacted by changes in urban landscape patterns resulting from urban expansion and seasonal variation. In order to cope effectively with urban heat island (UHI) effects and improve the urban living environment and microclimate, an analysis of the heating effect of impervious surface areas (ISA) and the cooling effects of vegetation is needed. In this study, Landsat 8 data in four seasons were used to derive the percent ISA and fractional vegetation cover (FVC) by spectral unmixing and to retrieve the land surface temperature (LST) from the radiative transfer equation (RTE). The percent ISA and FVC were divided into four different categories based on ranges 0–25%, 25–50%, 50–75%, and 75–100%. The LST with percent ISA and FVC were used to calculate the surface heating rate (SHR) and surface cooling rate (SCR). Finally, in order to analyze the heating effect of ISA and the cooling effect of vegetation, the variations of LST with SHR and SCR were compared between different percent ISA and FVC categories in the four seasons. The results showed the following: (1) In summer, SHR decreases as percent ISA increases and SCR increases as FVC increases in the study area. (2) Unlike the dependence of LST on percent ISA and FVC, the trends of SHR/SCR as a function of percent ISA/FVC are more complex for different value ranges, especially in spring and autumn. (3) The SHR (heating capacity) decreases with increasing percent ISA in autumn. However, the SCR (cooling capacity) decreases with increasing FVC, except in summer. This study shows that our methodology to analyze the variation and change trends of SHR, SCR, and LST based on different ISA and FVC categories in different seasons can be used to interpret urban ISA and vegetation cover, as well as their heating and cooling effects on the urban thermal environment. This analytical method provides an important insight into analyzing the urban landscape patterns and thermal environment. It is also helpful for urban planning and mitigating UHI.
An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier
Authors: Hussein Ahmed Faeq , Hashim Shaiful Jahari , Rokhani Fakhrul Zaman , Wan Adnan Wan Azizun
Published: March 2021

Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.
Haptic Glove TV Device for People with Visual Impairment
Authors: Villamarín Diego , Menéndez José Manuel
Published: March 2021

Immersive video is changing the way we enjoy TV. It is no longer just about receiving sequential images with audio, but also playing with other human senses through smells, vibrations of movement, 3D audio, feeling water, wind, heat, and other emotions that can be experienced through all human senses. This work aims to validate the usefulness of an immersive and interactive solution for people with severe visual impairment by developing a haptic glove that allows receiving signals and generating vibrations in hand, informing about what happens in a scene. The study case presented here shows how the haptic device can take the information about the ball’s location in the playing field, synchronized with the video reception, and deliver it to the user in the form of vibrations during the re-transmission of a soccer match. In this way, we take visually impaired people to live a new sensory experience, allowing digital and social inclusion and accessibility to audiovisual technologies that they could not enjoy before. This work shows the methodology used for the design, implementation, and results evaluation. Usability tests were carried out with fifteen visually impaired people who used the haptic device to attend a soccer match synchronized with the glove’s vibrations.
Standing by or Standing Up?—How Philosophy Can (In)form Our Understanding of Bystander Behaviours in Workplace Bullying Dynamics
Authors: Fahie Declan , Dunne Gerry
Published: March 2021

There is increasing awareness of the value of interdisciplinary collaboration within academia. Scholars argue that by drawing upon the conceptual, methodological, and interrogative paradigms of at least two disparate disciplines, researchers are challenged to re-evaluate and reconsider their own discipline-centric assumptions. A consequence of such purposeful boundary-blurring is an increased rigour and richness in the analysis of raw data, as well as the development of revealing insights through the novel application of discrete conceptual perspectives and theories. In such a way, dominant, taken-for-granted methodological and analytical assumptions are destabilised, as researchers are obliged to embrace contrasting perspectives while reassessing the epistemological foundations of their work. This paper focuses on the phenomenon of bystander responses to workplace bullying dynamics. While traditional scholarship into workplace bullying emanates from disciplines such as business, psychology, law, medicine and sociology, for example, this paper argues that philosophy, as a subject/field, may provide the researcher with a fresh interrogative lens through which to (re)view the phenomenon of workplace bullying, along with the consequential response of bystanders to such noxious behaviours. It suggests that, by drawing upon the philosophical concept of virtue ethics—which posits the question “What would a good or virtuous person do?”—we are afforded a robust theoretical framework to support a thoughtful and reasoned destabilization of contemporary perspectives on bystander behaviours and motivations.
The Acute Effects of a Relative Dose of Pre-Sleep Protein on Recovery Following Evening Resistance Exercise in Active Young Men
Authors: Costa Juliana V. , Michel J. Max , Madzima Takudzwa A.
Published: March 2021

The purpose of the present study was to assess the acute effects of pre-sleep consumption of isocaloric casein protein (CP), CP and whey protein (BLEND), or non-caloric control (CTRL) at a dose relative to lean body mass (LBM) on recovery following an evening lower-body resistance exercise (RE) bout. Fifteen active and previously resistance-trained males (age: 21 ± 1 years, body fat: 14.2 ± 2.7%) participated in this randomized, single-blind, crossover study. Participants performed an evening lower-body RE bout and were provided with 0.4 g/kg/LBM of whey protein (WP) supplement post-RE. A single dose of 0.6 g/kg/LBM of CP, 0.4 g/kg/LBM of CP and 0.2 g/kg/LBM WP (BLEND), or CTRL was consumed 30 min prior to sleep. Measurements of perceived recovery (visual analogue scales (VAS) for recovery, soreness, and fatigue), appetite (VAS for hunger, satiety, and desire to eat), as well as pressure-pain threshold (dolorimeter), average power, and peak torque (isokinetic dynamometry) of the right thigh muscles were assessed the following morning. Main effects of time were seen for all recovery variables (perceived recovery: F2,28 = 96.753, p < 0.001, hp2 = 0.874; perceived fatigue: F2,28 = 76.775, p < 0.001; hp2 = 0.846; perceived soreness: F2,28 = 111.967, p < 0.001; hp2 = 0.889). A main effect of supplement was only seen for perceived recovery (F2,28 = 4.869; p = 0.015; hp2 = 0.258), with recovery being 6.10 ± 2.58 mm greater in CP vs. BLEND (p = 0.033) and 7.51 ± 2.28 mm greater in CP than CTRL (p = 0.005). No main effects of supplement were seen in measures of perceived soreness, or fatigue (F2,28 ≤ 2.291; p > 0.120; hp2 ≤ 0.141). No differences between supplements were found in perceived next-morning hunger (p = 0.06), satiety (p ≥ 0.227), or desire to eat (p = 0.528). Main effects of supplement were seen between BLEND and CP vs. CTRL for measures of pain-pressure threshold at the rectus femoris (F2,28 = 9.377; p = 0.001; hp2 = 0.401), the vastus lateralis (F2,28 = 10.887; p < 0.001; hp2 = 0.437), and the vastus medialis (F2,28 = 12.113, p < 0.001; hp2 = 0.464). Values of peak torque and average power were similar between all supplement groups at 60°/sec (F1.309,18.327 ≤ 1.994; p ≥ 0.173; hp2 ≤ 0.125), 180°/s (F2,28 ≤ 1.221; p ≥ 0.310; hp2 ≤ 0.080), and 300°/sec (F2,28 ≤ 2.854; p ≥ 0.074; hp2 ≤ 0.169). Pre-sleep consumption of CP and BLEND at a dose relative to LBM may enhance perceived overnight recovery to a greater extent than CTRL as a result of less muscle soreness the following morning after an acute evening RE bout.
Decisions in Risk and Reliability: An Explanatory Perspective
Authors: Pievatolo Antonio , Ruggeri Fabrizio , Soyer Refik , Wilson Simon
Published: March 2021

The paper discusses issues that surround decisions in risk and reliability, with a major emphasis on quantitative methods. We start with a brief history of quantitative methods in risk and reliability from the 17th century onwards. Then, we look at the principal concepts and methods in decision theory. Finally, we give several examples of their application to a wide variety of risk and reliability problems: software testing, preventive maintenance, portfolio selection, adversarial testing, and the defend-attack problem. These illustrate how the general framework of game and decision theory plays a relevant part in risk and reliability.
The Renewable Energy Production Capability of Settlements to Meet Local Electricity and Transport Energy Demands
Authors: Kulcsár Balázs , Mankovits Tamás , Ailer Piroska Gyöngyi
Published: March 2021

In addition to the examination of electric power from local renewables, this study has sought the answer to the question of what proportion of vehicles are fueled by environmentally friendly energy saving technologies in the vehicle fleets of Hungarian settlements. Further, the study attempts to shed light on the self-sufficiency of Hungarian settlements with respect to the electricity and transport segments. In our assessments, the performance of small-scale household power plants (SSHPPs) utilizing local renewable energy sources, and small-scale power plants with installed capacities under 0.5 MW, was taken into account, as were the proportions of vehicles operating with partly or completely clean energy sources in the vehicle fleets of the individual settlements. Finally, the composition of the vehicle fleet has been examined in the light of the quantities of renewable electricity generated in the individual settlements, in order to consider whether these settlements are capable of covering the energy needs of their vehicle stocks from local sources. In the light of the results, the changes generated by the incentives and investments introduced over the past ten years can be established and subsequently, the energy policy needs in the future can be assessed. Our study has incorporated energy geography and settlement geography aspects.
Getting Municipal Energy Management Systems ISO 50001 Certified: A Study with 28 European Municipalities
Authors: Kaselofsky Jan , Rošā Marika , Jekabsone Anda , Favre Solenne , Loustalot Gabriel , Toma Michaël , Delgado Marín Jose Pablo , Moreno Nicolás Manuel , Cosenza Emanuele
Published: March 2021

Managing energy use by municipalities should be an important part of local energy and climate policy. The ISO 50001 standard constitutes an internationally recognized catalogue of requirements for systematic energy management. Currently, this standard is mostly implemented by companies. Our study presents an approach where consultants supported 28 European municipalities in establishing energy management systems. A majority (71%) of these municipalities had achieved ISO 50001 certification by the end of our study. We also conducted two surveys to learn more about motivations and challenges when it comes to establishing municipal energy management systems. We found that organizational challenges and resource constraints were the most important topics in this regard. Based on the experiences in our study we present lessons learned regarding supporting municipalities in establishing energy management systems.
Understanding and Strengthening the Emergency Management and Comprehensive Disaster Reduction in China’s Rural Areas: Lessons from Coping with the COVID-19 Epidemic
Authors: Kong Feng , Sun Shao
Published: March 2021

Community based bottom-up design is the foundation of national emergency management system. The outbreak of COVID-19 epidemic in early 2020 is a major test of emergency management capability in rural China. This paper first describes the necessity of strengthening the emergency management design in rural areas of China. Then this paper introduces the fundamental role of emergency management design based on bottom-up for the security of rural areas in China, especially in improving the level of comprehensive disaster reduction at the grassroots level, which plays an important role in improving the emergency management ability of China’s rural areas. Based on the above analysis, this paper takes the COVID-19 epidemic prevention and control of epidemic in rural areas of China as an example, and find out many problems in China’s rural emergency management system, such as the grass-roots government’s emergency needs cannot be met, the existing mode of systematic lack, the lack of psychological intervention and so on. Finally, this paper proposes to strengthen the emergency management design in China’s rural areas from expanding the scope of emergency management subjects, strengthening the systematic design of rural emergency management system and strengthening the psychological intervention in rural areas.
A Multilevel Simulation Method for Time-Variant Reliability Analysis
Authors: Wang Jian , Gao Xiang , Sun Zhili
Published: March 2021

Crude Monte Carlo simulation (MCS) is the most robust and easily implemented method for performing time-variant reliability analysis (TRA). However, it is inefficient, especially for high reliability problems. This paper aims to present a random simulation method called the multilevel Monte Carlo (MLMC) method for TRA to enhance the computational efficiency of crude MCS while maintaining its accuracy and robustness. The proposed method first discretizes the time interval of interest using a geometric sequence of different timesteps. The cumulative probability of failure associated with the finest level can then be estimated by computing corrections using all levels. To assess the cumulative probability of failure in a way that minimizes the overall computational complexity, the number of random samples at each level is optimized. Moreover, the correction associated with each level is independently computed using crude MCS. Thereby, the proposed method can achieve the accuracy associated with the finest level at a much lower computational cost than that of crude MCS, and retains the robustness of crude MCS with respect to nonlinearity and dimensions. The effectiveness of the proposed method is validated by numerical examples.
Constructability Analyses of Vertical Extension Methods for Existing Underground Spaces
Authors: Seo Soo-Yeon , Lee Byunghee , Won Jongsung
Published: March 2021

Remodeling underground structures requires careful construction planning, including consideration of costs and scheduling. Therefore, this study aims to analyze and compare the effects of four methods for vertically extending the underground spaces of an existing building under scheduling and cost constraints. The study considers the following extension methods: (1) bottom-up method, (2) normal top-down method after demolition, (3) normal top-down method in parallel with demolition, and (4) top-down method using double beams in parallel with demolition. Twelve illustrative examples are presented to investigate the constructability of these methods in terms of construction scheduling and costs. The construction durations and costs of each example is calculated and compared. We also analyze the structural stability of the examples using MIDAS Gen 2017. We conclude that the top-down method using double beams is the most efficient method in terms of costs and scheduling. The results and analysis process can help practitioners to select appropriate methods to expand underground spaces without demolishing entire existing buildings and efficiently manage costs and schedules. In future studies, these extension methods should be applied to real-world projects in various countries to validate and verify their actual effects on construction costs and scheduling.
Spatiotemporal Characteristics and Influencing Factors of Tourism Revenue in the Yangtze River Delta Urban Agglomeration Region during 2001–2019
Authors: Jiao Gengying , Lu Lin , Chen Guangsheng , Huang Zhiqiang , Cirella Giuseppe T. , Yang Xiaozhong
Published: March 2021

Green development is a solution to achieve sustainable development, while tourism development is one of the best approaches to realize a green economy. As the most rapid economic development region in China, the Yangtze River Delta Urban Agglomeration (YRDUA) has also witnessed rapid changes in its tourism economy during 2001–2019. Here, we analyzed the spatiotemporal patterns of its tourism revenue, and further identified contributions from multiple socio-economic factors using spatial analysis tools and regression models. The total tourism revenue increased 14.35 fold, with an annual increase rate of 79.73% during 2001–2019. The proportion of tourism revenue to the GDP continuously increased from 11.57% in 2001 to 18.89% in 2019. Tourism revenue increased for all cities, with the least increasing rates in the metropolitan cities including Shanghai, Nanjing, Suzhou and Hangzhou, and the largest increase rates in Ma’anshan, Hefei, Huzhou and Zhoushan. A regression and causality test indicated that different socioeconomic factors controlled the spatiotemporal variation patterns in different cities. The economic structure in the YRDUA has undergone significant shifts, with an increasing importance of tourism revenue in the GDP for most cities and a reducing discrepancy of tourism revenue among cities. Our study can enable the policy makers to be aware of the magnitude, temporal variation patterns, differences among cities and controlling factors for tourism development, and thus take suitable measures to further promote green tourism development in the YRDUA region.
Progressing towards Environmental Health Targets in China: An Integrative Review of Achievements in Air and Water Pollution under the “Ecological Civilisation and the Beautiful China” Dream
Authors: Antwi Henry Asante , Zhou Lulin , Xu Xinglong , Mustafa Tehzeeb
Published: March 2021

Despite the positive effect of industrialisation on health and quality of life indicators across the globe, it is also responsible for the release of chemical toxins into the environment. Thus, the pursuit of economic development through industrialisation has equally nurtured numerous environmental disasters with accompanying catastrophic health effects. China is one of the countries with high carbon emissions, but new policy changes have resulted in massive gains in controlling environmental damage while enhancing the environment-related quality of life. This paper combines the six-step integrative review strategy with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) strategy to determine appropriate exclusion and inclusion criteria to explore the available stock of literature. We note that overall pollution in China fell by 10% between 2014 and 2019 whereas the average fine particulate matter (PM2.5) concentration of 93 micrograms per cubic meter reduced by 47% by 2019. Beijing exhibited the top 200 most polluted cities in 2019 after recording the lowest PM2.5 ever. All cities that implemented the 2012 Environmental Air Quality Standards reduced the average concentration of PM2.5 and sulfur dioxide by 42–68% by the end of 2018. Improvements in freshwater quality and a decline in water pollution levels were recorded despite increases in economic growth, urbanisation, energy use, trade openness, and agriculture, all of which are major stimulants of pollution. Deterring environmental tariff, tight ecological inspections, closing down of non-compliant producers, heavy investment in environmental control, and the ambitious five year-plan to revitalise renewable energy goals emanating from China’s ecological civilisation masterplan are responsible for these improvements in air and water pollution. China needs to work more aggressively to consolidate the gains already made in order to quicken the actualisation of the ecological civilisation and beautiful China dream.
Understanding Transmedia Music on YouTube through Disney Storytelling
Authors: Vizcaíno-Verdú Arantxa , Aguaded Ignacio , Contreras-Pulido Paloma
Published: March 2021

Transmedia storytelling has been integrated into contemporary society through social media, where influencers have enabled the building of worlds. Within this environment of human-interaction, fiction and converging social realities have become an essential tool to tell stories. On YouTube, storytelling has expanded to music, where cover videos take on great relevance. The aim of this study is to understand the transmedia music phenomenon due to the impact of music on the platform. To this end, we applied a methodology that stemmed from Grounded Theory principles in the analysis of 300 Disney animation song covers in three stages: (1) deductive and inductive codebook development; (2) social network analysis; and (3) statistical test. The results showed that youtubers highlight specific audiovisual codes from the film and cultural industries. Furthermore, we observed these productions often display configurations that expand the original story through performance, location, costumes, make-up, among others. We argue that, on the digital sphere, a sustainable transmedia music paradigm is developing, where performers construct more meaningful and valuable stories.
Cross-Country Potentials and Advantages in Trade in Fish and Seafood Products in the RCEP Member States
Authors: Erokhin Vasilii , Tianming Gao , Ivolga Anna
Published: March 2021

Fisheries has always played a vital role in supporting livelihoods and ensuring food security and sustainable economic and social development in Southeast Asia. Historically, rural and coastal communities across the region have heavily relied on the fish trade as an indispensable source of income and employment. With the establishment of the Regional Comprehensive Economic Partnership (RCEP) between Association of Southeast Asian Nations (ASEAN) economies and large fish traders like China, Japan, South Korea, Australia, and New Zealand, there is a threat for smaller countries to lose competitive advantages in the regional market. By studying bilateral trade flows between fifteen RCEP members in 2010–2019 and matching indicative untapped trade potentials (ITP method) with revealed comparative (RCA method), relative trade (RTA method), and competitive (Lafay index) advantages across 210 pairs of countries, the authors found substantial misbalances between potential values of country-to-country trade and actual advantages of RCEP economies. To optimize gains from intraregional trade for both smaller and larger RCEP members, this study identified advantageous and disadvantageous trading destinations and product categories for individual countries. The recommendations were then generalized along the four groups of economies based on their level of income, contribution to overall RCEP trade in fish, and the share of fishery products in the national trade turnover. From a practical side, the study adds to the knowledge about the fish trade in Asia by detailing how countries can better utilize individual combinations of advantages. From a methodological side, the approach can be employed widely outside the RCEP to establish a reliable picture of potential gains or losses of a particular country in trade with its counterparts across varied sets of competitive advantages.
Uncovering Prospective Role and Applications of Existing and New Nutraceuticals from Bacterial, Fungal, Algal and Cyanobacterial, and Plant Sources
Authors: Al-Obaidi Jameel R. , Alobaidi Khalid H. , Al-Taie Bilal Salim , Wee David Hong-Sheng , Hussain Hasnain , Jambari Nuzul Noorahya , Ahmad-Kamil E. I. , Ariffin Nur Syamimi
Published: March 2021

Nutraceuticals are a category of products more often associated with food but having pharmaceuticals property and characteristics. However, there is still no internationally accepted concept of these food-pharmaceutical properties, and their interpretation can differ from country to country. Nutraceuticals are used as part of dietary supplements in most countries. They can be phytochemicals which are biologically active and have health benefits. These can be supplied as a supplement and/or as a functional food to the customer. For human health and longevity, these materials are likely to play a vital role. Consumption of these items is typical without a therapeutic prescription and/or supervision by the vast majority of the public. The development of nutraceuticals can be achieved through many bioresources and organisms. This review article will discuss the current research on nutraceuticals from different biological sources and their potential use as an agent for improving human health and well-being, as well as the gaps and future perspective of research related to nutraceutical development.
Harmonisation and Emergence Concerning the Performance Audit of the EU Member States’ Public Sector. Romania’s Case
Authors: Drăgușin (Trincu-Drăgușin) Cristina-Petrina , Pitulice Ileana Cosmina , Ștefănescu Aurelia
Published: March 2021

The complexity of the public sector generated by the mobilisation and use of significant financial resources, national cultural factors, the heterogeneity of the provision of public services, the numerous interested parties, the increasing demand for the quality of public services, the information asymmetry, require an actor to provide credible assurance regarding the proper management of public financial resources. In this context, performance audits are the link between public sector entities and stakeholders. The research has two components: the first component analyzes the degree of harmonization of the regulations specific to the performance audit in Romania with the International Standards of Supreme Audit Institutions (ISSAI); the second component analyses the degree of transparency of performance audit information by the SAIs of the EU Member States, through their official websites. In this regard, we have resorted to an in-depth longitudinal study, content analysis and disclosure index. The research results highlighted that the Romanian SAI has adopted in its normative framework the foremost ISSAI provisions on performance audit and the harmonization degree has systematically improved correlative with the regulatory revisions. The degree of disclosure for performance audit-specific information by the EU member state SAIs is high.
Optimizing Energy Use, Cost and Carbon Emission through Building Information Modelling and a Sustainability Approach: A Case-Study of a Hospital Building
Authors: Khahro Shabir Hussain , Kumar Danish , Siddiqui Fida Hussain , Ali Tauha Hussain , Raza Muhammad Saleem , Khoso Ali Raza
Published: March 2021

The construction industry (CI) has a significant impact on the environment and on climate change due to the emission of greenhouse gases like carbon dioxide. Globally accepted Sustainable Development Goals (SDG), specifically SDG 7 (Access to Affordable, Reliable, Sustainable and Modern Energy for All), SDG 9 (Industry, Innovation and Infrastructure), and SDG 11 (Sustainable Cities and Communities) stress the responsible utilization of energy in various industries, including construction. The CI uses almost half of the world’s produced energy. Therefore, this research presents insights into the efficient use of energy in the building sector and shows how energy efficiency can be achieved by altering different parameters and components like orientation, materials, glazing, and HVAC systems through a case study of a hospital building in Green Building Studio (GBS). This paper also aims to use the Building Information Modelling (BIM) approach to make environmentally sustainable decisions to reduce energy waste in projects. Initially, beneficial factors of BIM on green buildings were identified in the literature and later ranked, based on expert opinions collected using a set of questionnaires. Average Index was used for data analysis. The identified benefits were validated by conducting energy analyses on a hospital model through 3D BIM. It was concluded that a substantial share of energy cost, carbon dioxide (CO2), and electricity can be saved using this approach. It was determined that a quick and sustainable design process, improved energy efficiency, enhanced building performance, and provision of better design alternatives are the key benefits of the adoption of BIM by such projects. A Cronbach’s alpha value of 0.822 was obtained, which further validates the results. The proposed approach may lead future structures to be sustainable and enriches the culture of energy-efficient green buildings.
Smart Specialisation Strategies for Elevating Integration of Cultural Heritage into Circular Economy
Authors: Stanojev Jermina , Gustafsson Christer
Published: March 2021

The smart specialisation approach is becoming a strategic instrument for identifying regions’ opportunities for growth and sustainable development. It is a place-based approach and plays an important role in benchmarking regional competitiveness. To have a smart specialisation strategy has been thought of as a key factor in making a choice for investment. Smart specialisation strategies represent a policy measure to overcome disorganised and weak parallel activities in developed EU countries and offer support to those areas that have research, technological and production capacity to carry out particular activities. Smart specialisation strategies, therefore, follow the socio-economic situation in countries and their integrated technological, institutional and business processes. The EU Member States and regions recognised that supporting a limited number of well-identified priorities for knowledge-based investments and/or clusters could advance, focusing on competitive assets and realistic growth capabilities reinforced by a critical mass of action and entrepreneurial resources. However, the role of culture and cultural heritage has not been significant in these processes. As the policy review revealed that circular economy should be considered as a broader sustainable development strategy, which should also “support Member States and regions to strengthen innovation for the circular economy through smart specialisations”, the purpose of this paper is to lay a basis for a new, stronger complementarity between culture, cultural heritage and adaptive reuse practices, and circular economy concepts through smart specialisation strategies.
Survey on e-Powered Micro Personal Mobility Vehicles: Exploring Current Issues towards Future Developments
Authors: Boglietti Stefania , Barabino Benedetto , Maternini Giulio
Published: March 2021

Nowadays, the diffusion of electric-powered micro Personal Mobility Vehicles (e-PMVs) worldwide—i.e., e-bikes, e-scooters, and self-balancing vehicles—has disrupted the urban transport sector. Furthermore, this topic has captured many scholars and practitioners’ interest due to multiple issues related to their use. Over the past five years, there has been strong growth in the publication of e-PMV studies. This paper reviews the existing literature by identifying several issues on the impact that e-PMVs produce from different perspectives. More precisely, by using the PRIMA’s methodological approach and well-known scientific repositories (i.e., Scopus, Web of Science, and Google Scholar), 90 studies between 2014 and 2020 were retrieved and analyzed. An overview and classification into endogenous issues (e.g., impact on transport and urban planning) and exogenous issues (e.g., impact on safety and the environment) are provided. While several issues are deeply investigated, the findings suggest that some others need many improvements. Therefore, the status quo of these studies is being assessed to support possible future developments.
Knowledge and Feelings of Competence with Regard to ADHD Among Support Staff in All-Day Primary Schools
Authors: Domsch Holger , Ruhmland Martina , Lissmann Ilka
Published: March 2021

(1) Background: Schools report a high number of schoolchildren with poor attention and hyperactive behavior, with 5% being diagnosed with attention deficit/hyperactivity disorder (ADHD). This causes specific problems during homework and classroom times, and the extension of all-day schooling in German primary schools makes this a challenge for support staff working in the after-school programs. Such staff have a very wide variety of qualifications, ranging from no formal teacher training to full teaching qualifications. (2) Methods: This study documents the knowledge of 196 support staff working in all-day primary schools about ADHD, and their subjective view of whether they feel competent with regard to homework situations in general and ADHD in particular. (3) Results: Those with an educational background have significantly more knowledge than those without such a background, staff feel less prepared to supervise children with ADHD, and there is a small but significant correlation here with knowledge about ADHD. (4) Conclusions: The importance of trained pedagogical staff in the supervision of children with concentration problems is emphasized.
Hybrid Convolutional Neural Networks Based Framework for Skimmed Milk Powder Price Forecasting
Authors: Malczewski Jarosław , Czubak Wawrzyniec
Published: March 2021

The latest studies have compellingly argued that Neural Networks (NN) classification and prediction are the right direction for forecasting. It has been proven that NN are suitable models for any continuous function. Moreover, these methods are superior to conventional methods, such a Box–Jenkins, AR, MA, ARMA, or ARIMA. The latter assume a linear relationship between inputs and outputs. This assumption is not valid for skimmed milk powder (SMP) forecasting, because of nonlinearities, which are supposed to be approximated. The traditional prediction methods need complete date. The non-AI-based techniques regularly handle univariate-like data only. This assumption is not sufficient, because many external factors might influence the time series. It should be noted that any Artificial Neural Network (ANN) approach can be strongly affected by the relevancy and “clarity” of its input training data. In the proposed Convolutional Neural Networks based methodology assumes price series data to be sparse and noisy. The presented procedure utilizes Compressed Sensing (CS) methodology, which assumes noisy trends are incomplete signals for them to be reconstructed using CS reconstruction algorithms. Denoised trends are more relevant in terms of NN-based forecasting models’ prediction performance. Empirical results reveal robustness of the proposed technique.
Harmonic Analysis of Grid-Connected Solar PV Systems with Nonlinear Household Loads in Low-Voltage Distribution Networks
Authors: Ahsan Syed Muhammad , Khan Hassan Abbas , Hussain Akhtar , Tariq Sarmad , Zaffar Nauman Ahmad
Published: March 2021

Grid-connected rooftop and ground-mounted solar photovoltaics (PV) systems have gained attraction globally in recent years due to (a) reduced PV module prices, (b) maturing inverter technology, and (c) incentives through feed-in tariff (FiT) or net metering. The large penetration of grid-connected PVs coupled with nonlinear loads and bidirectional power flows impacts grid voltage levels and total harmonic distortion (THD) at the low-voltage (LV) distribution feeder. In this study, LV power quality issues with significant nonlinear loads were evaluated at the point of common coupling (PCC). Various cases of PV penetration (0 to 100%) were evaluated for practical feeder data in a weak grid environment and tested at the radial modified IEEE-34 bus system to evaluate total harmonic distortion in the current (THDi) and voltage (THDv) at PCC along with the seasonal variations. Results showed lower active, reactive, and apparent power losses of 1.9, 2.6, and 3.3%, respectively, with 50% solar PV penetration in the LV network as the voltage profile of the LV network was significantly improved compared to the base case of no solar. Further, with 50% PV penetration, THDi and THDv at PCC were noted as 10.2 and 5.2%, respectively, which is within the IEEE benchmarks at LV.
Normalized Difference Vegetation Index and Chlorophyll Content for Precision Nitrogen Management in Durum Wheat Cultivars under Semi-Arid Conditions
Authors: Kizilgeci Ferhat , Yildirim Mehmet , Islam Mohammad Sohidul , Ratnasekera Disna , Iqbal Muhammad Aamir , Sabagh Ayman EL
Published: March 2021

To impart sustainability to modern intensive farming systems, environmental pollution caused by nitrogenous fertilizers in needs to be reduced by optimizing their doses. To estimate the grain yield and nutrtional quallity of wheat, the normalized difference vegetation index (NDVI) and chlorophyll content (SPAD) are potential screening tools to identify the N deficiency and screen out the promising cultivars. The two-year field study was comprised with five levels of nitrogen (N) (control, 50, 100, 150 and 200 kg N ha−1) and two durum wheat genotypes (Sena and Svevo). The experimental design was split-plot, in which N levels were placed in the main plots, while wheat genotypes were arranged in sub-plots. To predict the yield and quality traits, the NDVI and SPAD values recorded at heading, anthesis and milky growth stages were taken as response variables. The results revealed that N fertilization significantly influenced the SPAD and NDVI attributed traits of durum wheat, except NDVI at milky stage (NDVI-M) during the first year. The maximum value of NDVI was recorded by 150 kg N ha−1, while control treatment gave the minimum value. The grain yield was increased with the increasing dose of the N up to 100 kg N ha−1 (4121 kg ha−1), and thereafter, it was declined with further increased of N levels. However, the variation between the genotypes was not significant, except NDVI and SPAD values at the milky stage. The genotype Svevo had the highest NDVI values at all growth stages, while the genotype Sena recorded the maximum SPAD values during both years. Similarly, the N levels significantly influenced the quality traits (protein, wet gluten, starch test weight and Zeleny sedimentation) of both genotypes. The highly significant relationship of SPAD and NDVI with the grain yield and yield attributes showed their reliability as indicators for determining the N deficiency and selection of superior wheat genotypes for ensuring food security under climate change scenario.
Applying PCA to Deep Learning Forecasting Models for Predicting PM2.5
Authors: Choi Sang , Kim Brian
Published: March 2021

Fine particulate matter (PM2.5) is one of the main air pollution problems that occur in major cities around the world. A country’s PM2.5 can be affected not only by country factors but also by the neighboring country’s air quality factors. Therefore, forecasting PM2.5 requires collecting data from outside the country as well as from within which is necessary for policies and plans. The data set of many variables with a relatively small number of observations can cause a dimensionality problem and limit the performance of the deep learning model. This study used daily data for five years in predicting PM2.5 concentrations in eight Korean cities through deep learning models. PM2.5 data of China were collected and used as input variables to solve the dimensionality problem using principal components analysis (PCA). The deep learning models used were a recurrent neural network (RNN), long short-term memory (LSTM), and bidirectional LSTM (BiLSTM). The performance of the models with and without PCA was compared using root-mean-square error (RMSE) and mean absolute error (MAE). As a result, the application of PCA in LSTM and BiLSTM, excluding the RNN, showed better performance: decreases of up to 16.6% and 33.3% in RMSE and MAE values. The results indicated that applying PCA in deep learning time series prediction can contribute to practical performance improvements, even with a small number of observations. It also provides a more accurate basis for the establishment of PM2.5 reduction policy in the country.
A Circular Economy for Phosphorus in Sweden—Is it Possible?
Authors: Lorick Dag , Harder Robin , Svanström Magdalena
Published: March 2021

More sustainable management of phosphorus requires comprehensive understanding of phosphorus stocks and flows. With the purpose of shedding light on the possibilities for an increased level of recirculation of phosphorus in Sweden, phosphorus flows entering and exiting biomass production sectors were quantified along with waste flows, that is, flows that are not currently utilized in biomass production. Relevant waste flows were also characterized in terms of phosphorus concentration, plant availability, contamination and geo-spatial distribution. The theoretical recirculation potential of phosphorus in Sweden was then estimated. The results indicate that there is a large potential for making phosphorus management more circular, especially regarding the utilization of phosphorus in sewage sludge as well as wood ashes from the forestry sector. Moreover, there is a large amount of phosphorus in mining waste that could potentially be used for fertilizer production. It is concluded that the amount of phosphorus in flows fit for recirculation in forestry could more or less balance today’s output. In agriculture, however, recirculation can only sufficiently replace imported mineral phosphorus at current demand if the phosphorus in mining waste is utilized. Thus, if the goal is to replace all of the mineral phosphorus, the agricultural sector also has to become much more efficient in its phosphorus usage.
Fractional Reverse Coposn’s Inequalities via Conformable Calculus on Time Scales
Authors: Zakarya Mohammed , Altanji Mohamed , AlNemer Ghada , Abd El-Hamid Hoda A. , Cesarano Clemente , M. Rezk Haytham
Published: March 2021

This paper provides novel generalizations by considering the generalized conformable fractional integrals for reverse Copson’s type inequalities on time scales. The main results will be proved using a general algebraic inequality, chain rule, Hölder’s inequality, and integration by parts on fractional time scales. Our investigations unify and extend some continuous inequalities and their corresponding discrete analogues. In addition, when α = 1, we obtain some well-known time scale inequalities due to Hardy, Copson, Bennett, and Leindler inequalities.