bluuebunny/crossref_metadata_2025 huggingface dataset:
Eco-Province Construction Performance and Its Influencing Factors of Shandong Province in China: From Regional Eco-Efficiency Perspective
Authors: Jiang Zhengju , Guo Fuyou , Cai Liping , Li Xiaoxiao
Published: November 2021

Eco-province construction (EPC) innovated by China is an important approach for regional sustainable development. The core of this paper relates to how to quantitatively evaluate EPC performance and explore its influencing factors. We propose regional total-factor eco-efficiency as a proxy of EPC performance and apply the methods of the SBM directional distance function, the Theil index, hot-spot analysis, and the Tobit model to investigate spatial-temporal evolutionary characteristics and influencing factors of Shandong’s EPC performance from 2003 to 2017. The results showed that: (1) The EPC performance of Shandong presented a fluctuating rising trend as a whole and was unbalanced among regions with gradient-descending characteristics from the eastern, central to western regions. (2) The gravity center of Shandong’s EPC performance shifted northwards, eastwards, southwards, and westwards successively; the spatial pattern of regional EPC performance evolved from characteristics of high- and low-dispersion distribution in the initial stage to a significant H-shaped spatial conglomeration with hot spots distributed in Binzhou and Yantai and cold spots in the southern region. (3) A U-shaped environmental Kuznets curve existed between economic development level and Shandong’s EPC performance. Shandong’s EPC performance was positively related to R&D intensity while negatively related to urbanization. The impact of industrial structure, openness, and environmental regulation on Shandong’s EPC performance presented spatial heterogeneity. Shandong should establish a cross-regional collaborative governance mechanism of ecological construction and implement an ecological-innovation-driven development strategy to promote EPC performance.
Influence of Socio-Cultural Attributes on Stigmatizing Public Transport in Saudi Arabia
Authors: Nahiduzzaman Kh Md , Campisi Tiziana , Shotorbani Amin Mohammadpour , Assi Khaled , Hewage Kasun , Sadiq Rehan
Published: November 2021

Several factors over the years have contributed to stigma in public transport. Many studies have highlighted the need to make the transport system more equitable both from economic and gender perspectives. This study attempts to demonstrate how the perceptions of public transport users and non-users are stigmatized from social and cultural standpoints. Thus, it identifies the social and cultural stigma-induced barriers embedded with the use and people’s general perception about the public bus service, taking SAPTCO (Saudi Public Transport Company) as a case study. The study results suggest that privacy concern is the primary cause of stigma. Most of the users are unwilling to ride with their families as SAPTCO does not account for gender needs (e.g., privacy, travel convenience, safety, comfort, etc.). Moreover, people from the high-income classes are more stigmatized against this ridership. A fuzzy inference system (FIS) model is used to analyze the survey questionnaire responses and understand what stigma means for the public bus service. Expert opinions are employed to generate “if–then” rules of the FIS models. Sensitivity of the defined fuzzy model is conducted to different aspects of the ridership. The study results further suggest that “inconvenience” poses the highest impact while “feeling safe”, “privacy”, “fare”, “timing”, and “comfort” are found to be the medium impact-making variables for stigma. The stigma-defining variables would be critical for the public bus service to improve its service quality and help (re-)design the policies that would attract a high amount of ridership. Some solutions are suggested in the end that would complement, strengthen, and promote the current SAPTCO service. The demonstrated methodology of this study would be relevant and adaptive to any relevant context to improve public transportation service and pertaining policies.
Test-Retest Reliability of Unilateral Horizontal Drop Jump in Children
Authors: Dukarić Vedran , Antekolović Ljubomir , Baković Marijo , Rupčić Tomislav , Cigrovski Vjekoslav
Published: November 2021

Jumps are an indispensable activity for the development of coordination, muscle strength and power, especially in children. Positive effects of horizontal drop jump (HDJ) proved to be very important in improving individuals performance. HDJ presents a specific movement pattern that has similarities with running gait and take-off in different horizontal jumps. Influence and effect of implementating HDJ in children is yet to be determined. The aim of this research was to determine the test–retest reliability of the unilateral horizontal drop jump (UHDJ) in children of early school age (6–7 years). Participants (n = 31; 19 girls and 12 boys) were school-age children that regularly attended Physical Education classes (Girls: mean age 7.5 ± 0.3 years, mean height 127.1 ± 6.8 cm and mean weight 25.8 ± 5.2 kg; Boys: mean age 7.5 ± 0.2 years, mean height 127.5 ± 6.9 cm and mean weight 27.6 ± 7.1 kg). UHDJ was performed from an elevation of 30 cm relative to the platform with starting position 120 cm from the middle of the platform. A jump on the platform and a unilateral take-off in the distance were performed, followed by a bilateral landing on the mat. Intraclass correlation coefficient was used to determine the reliability between the two days of measurements. Test–retest reliability was calculated for all observed variables, and a good correlation was found between the performed measurements (ICC = 0.76–0.89). The α coefficient indicates good to excellent (0.86–0.94) internal consistency. These findings suggest the usefulness of applying a UHDJ in school-age children. Moreover, it can be used to identify children talented for sports, monitor the effects of training and discover and direct individuals towards suitable sports disciplines.
Emerging Sustainable Supply Chain Models for 3D Food Printing
Authors: Rogers Helen , Srivastava Mohit
Published: November 2021

3D printing technology is rapidly transforming supply chains across diverse manufacturing sectors, enabling personalisation of consumer goods ranging from car parts, medical devices, toys, houses, and even clothing. Food production is also included in the breadth of applications of this expanding technology. Increasing consumer awareness about sustainability, including the problem of food waste, as well as growing interest in customised nutrition have led to the emergence of food industry research focused on aspects, such as packaging, portion size, and healthy sustainable ingredients, to satisfy consumer demands. The growing market for personalised food options in particular, requires increased flexibility and agility to tailor ingredients to an individual’s specific requirements. Such specificity is not easily fulfilled using traditional mass production methods; however, the emerging technology of 3D food printing (3DFP) may be one solution. This paper evaluates the opportunities, risks, and challenges associated with 3DFP, with a focus on developing sustainable supply chains for future growth. Drawing on 12 semi-structured interviews with 3DFP industry managers and current literature in the domain, we propose three supply chain models for 3DFP services, as well as an overview of the key business drivers.
Global Food Loss and Waste in Primary Production: A Reassessment of Its Scale and Significance
Authors: Parfitt Julian , Croker Tim , Brockhaus Anna
Published: November 2021

Global statistics on food waste were first reported by the United Nations Food and Agriculture Organization in 2011, and since that time, more attention has been given to food waste measurements at the consumer, retail and hospitality stages, whilst efforts to quantify losses during primary production have been more limited. To provide an updated view of global losses in primary production, data for the harvest and on-farm, post-harvest stages were reassessed through a systematic review of data sources and a selection of datasets for further analysis. To qualify for selection, food-loss measurements needed to be specific to primary production and to particular food commodities and production regions. The analysis covered a split between losses at the harvest and post-harvest stages linked to activity descriptions within the primary data sources. A cross-sectional sample of ten commodity/region case studies was conducted through stakeholder interviews and literature reviews to triangulate food waste estimates and to understand issues relating to food waste definitions from a farming perspective.
Estimation of Heavy Metal(Loid) Contents in Agricultural Soil of the Suzi River Basin Using Optimal Spectral Indices
Authors: Han Cheng , Lu Jilong , Chen Shengbo , Xu Xitong , Wang Zibo , Pei Zheng , Zhang Yu , Li Fengxuan
Published: November 2021

For agricultural production and food safety, it is important to accurately and extensively estimate the heavy metal(loid) pollution contents in farmland soil. Remote sensing technology provides a feasible method for the rapid determination of heavy metal(loid) contents. In this study, the contents of Ni, Hg, Cr, Cu, and As in the agricultural soil of the Suzi River Basin in Liaoning Province were taken as an example. The spectral data, with Savitzky–Golay smoothing, were taken as the original spectra (OR), and the spectral transformation was achieved by continuum removal (CR), reciprocal (1/R), root means square (R), first-order differential (FDR), and second-order differential (SDR) methods. Then the spectral indices were calculated by the optimal band combination algorithm. The correlation between Ni, Hg, Cr, Cu, and As contents and spectral indices was analyzed, and the optimal spectral indices were selected. Then, multiple linear regression (MLR), partial least squares regression (PLSR), random forest regression (RFR), and adaptive neuro-fuzzy reasoning system (ANFIS) were used to establish the estimation model based on the combined optimal spectral indices method. The results show that the combined optimal spectral indices method improves the correlation between spectra and heavy metal(loid), the MLR model produces the best estimation effect for Ni and Cu (R2=0.713 and 0.855, RMSE = 5.053 and 8.113, RPD = 1.908 and 2.688, respectively), and the PLSR model produces the best effect for Hg, Cr, and As (R2= 0.653, 0.603, and 0.775, RMSE = 0.074, 23.777, and 1.923, RPD = 1.733, 1.621, and 2.154, respectively). Therefore, the combined optimal spectral indices method is feasible for heavy metal(loid) estimation in soils and could provide technical support for large-scale soil heavy metal(loid) content estimation and pollution assessment.
Finding the Optimal Fatty Acid Composition for Biodiesel Improving the Emissions of a One-Cylinder Diesel Generator
Authors: Maes Rafael R. , Potters Geert , Fransen Erik , Calderay Cayetano Fátima , Van Schaeren Rowan , Lenaerts Silvia
Published: November 2021

Nitrogen oxides (NOx) and particulate matter (PM) currently are the main pollutants emitted by diesel engines. While there is a start in using hybrid and electric cars, ships will still be fueled by mineral oil products. In the quest to achieve zero-pollution and carbon-free shipping, alternative forms of energy carriers must be found to replace the commonly used mineral oil products. One of the possible alternative fuels is biodiesel. This paper explores the optimization of the composition of biodiesel in order to reduce the concentration of particulate matter and NOx in exhaust gases of a one-cylinder diesel generator.
Project Management in the Biotech Context: Exploring the Interrelation between Maturity and Sustainable Project Management
Authors: Magano José , Sousa Silva Cláudia , Martins Micaela
Published: November 2021

Biotechnology is an emerging and increasingly important sector in the current context. As the number of biotech projects grows, so does the need to establish processes to improve project management effectiveness and project success, including assessing their impacts (positive and negative) on the Sustainable Development Goal (SDGs). This broader approach opens the door to developing a new project management (PM) paradigm designated by sustainable project management (SPM). However, there is a need for more empirical studies to understand how sustainability can be integrated into project management. This research is based on the proposition that PM maturity could lead to incorporating sustainability in PM. No research studies are reported in the literature exploring this interrelationship between maturity and sustainable project management; such is this study’s purpose and originality. The study applies Kerzner’s Level 3 PM maturity model on a sample of 96 biotech companies in Portugal through a questionnaire that addressed project managers and team members. The findings suggest that the process of integrating sustainability into PM should follow these steps: (1) perform an early PM maturity diagnosis to identify the company’s most and least dominated areas; (2) identify the strengths and weaknesses that impact the integration of sustainability into project management practices; (3) develop a customized and adjusted action plan to integrate sustainability in PM. The study’s main contribution relies on understanding how sustainability can be integrated into project management, explaining the role of maturity assessment in this process. In addition, it characterizes the biotech industry projects concerning the linkage between PM maturity and sustainability and provides recommendations that may contribute to the companies’ development towards sustainable project management.
Experimental Study on Crack Propagation of Rock by Blasting under Bidirectional Equal Confining Pressure Load
Authors: Ge Jinjin , Xu Ying , Huang Wei , Wang Haibo , Yang Rongzhou , Zhang Zhongyi
Published: November 2021

Rock blasting during tunneling has shown that the rock failure in high in situ stress environments is different from that in low in situ stress conditions or with a shallow rock mass. In particular, the propagation direction of the main crack induced by blasting is greatly affected by the in situ stresses. In order to study the law of crack propagation in rock during blasting under the conditions of an initial in situ stress, a transparent material that conformed to the mechanical properties of hard rock was used to carry out a similar model rock blasting test, under a unidirectional load. The results show that initial stress has a great influence on the propagation number, length, and direction of the main radial cracks. The specific performances were as follows: under the action of an equal confining pressure load, the longest main radial crack in the model specimen propagated along the diagonal direction, and the number and length of the main radial cracks propagated decreased with the gradual increase of confining pressure stress; in addition, the diameter of the circumferential cracks also decreased with the increase of stress, and there was a negative correlation between them. In view of the phenomenon where the longest main radial crack propagated along the diagonal direction in the model test, a mechanical model was established in this study to explain this process. This is of practical significance for understanding the mechanism of rock fracture when blasting with high in situ stresses.
A New Sustainable and Novel Hybrid Solar Chimney Power Plant Design for Power Generation and Seawater Desalination
Authors: Abdelsalam Emad , Almomani Fares , Kafiah Feras , Almaitta Eyad , Tawalbeh Muhammad , Khasawneh Asma , Habash Dareen , Omar Abdullah , Alkasrawi Malek
Published: November 2021

This study presents a case study of a novel hybrid solar chimney power plant (HSCPP) design’s performance in the city of Doha, Qatar. The HSCPP construction is similar to the traditional solar chimney power plant (SCPP) but with the addition of water sprinklers installed at the top of the chimney. This allowed the solar chimney (SC) to operate as a cooling tower (CT) during the nighttime and operate as an SC during the daytime, hence providing a continuous 24-h operation. The results showed that the HSCPP produced ~633 MWh of electrical energy per year, compared to ~380 MWh of energy produced by the traditional SCPP. The results also showed that the HSCPP was able to produce 139,000 tons/year of freshwater, compared to 90,000 tons/year produced by the traditional SCPP. The estimated CO2 emission reduction (~600 tons/year) from the HSCPP is twice that of the traditional SCPP (~300 tons/year). The results clearly show that the HSCPP outperformed the traditional SCPP.
Transition Pathways for the Farmed Salmon Value Chain: Industry Perspectives and Sustainability Implications
Authors: Gudbrandsdottir Ingunn Y. , Saviolidis Nína M. , Olafsdottir Gudrun , Oddsson Gudmundur V. , Stefansson Hlynur , Bogason Sigurdur G.
Published: November 2021

Salmon is the most consumed farmed seafood in the EU and there is no indication that demand will abate. Yet salmon aquaculture’s environmental impacts are significant, and its future is likely to be shaped by demands of increased but at the same time more sustainable production. This study developed an integrated theoretical framework based on the multi-level perspective (MLP) and a global value chain (GVC) governance framework and applied it to the global farmed salmon value chain. The objective was to provide insights on the most likely transition pathway towards sustainability based on industry and expert perspectives. The perceptions on challenges and drivers of change, were gathered through focus groups and in-depth interviews, and fitted to the integrated framework to facilitate the transition pathway analysis. Viewing the qualitative findings in the context of the MLP framework provided information about the current workings of the system, the drivers of change in the socio-technical landscape and niche-innovations and their potential to challenge or enhance the current system and thus indicated possible system transitions. To emphasize the role of industry actors in shaping the future of the salmon value chain, the analysis was strengthened using the GVC model which added information about power relations, signaling the ability of system actors to motivate or resist change. The findings indicate that, due to resistance in the regime and the fact that niche-innovations are not yet sufficiently developed, the farmed salmon value chain will continue to be predominated by traditional sea-based aquaculture but that there will be a gradual shift towards more diversity in terms of production methods in response to landscape pressures. The discussion addresses sustainability challenges and policy implications for the farmed salmon value chain and highlights the need for a food system perspective.
A Predictive Approach to Optimize a HHO Generator Coupled with Solar PV as a Standalone System
Authors: Butt Osama Majeed , Saeed Tareq , Elahi Hassan , Masud Usman , Ghafoor Usman , Che Hang Seng , Rahim Nasrudin Abd , Ahmad Muhammad Shakeel
Published: November 2021

Production of hydrogen by means of renewable energy sources is a way to eliminate dependency of the system on the electric grid. This study is based on a technique involving coupling of an oxyhydrogen (HHO) electrolyzer with solar PV to produce clean HHO gas as a fuel. One of objectives of this study was to develop a strategy to make the electrolyzer independent of other energy sources and work as a standalone system based on solar PV only. A DC-DC buck convertor is used with an algorithm that can track the maximum power and can be fed to the electrolyzer by PV while addressing its intermittency. The electrolyzer is considered to be an electrical load that is connected to solar PV by means of a DC-DC convertor. An algorithm is designed for this DC-DC convertor that allows maximization and control of power transferred from solar PV to the electrolyzer to produce the maximum HHO gas. This convertor is also responsible for operating the electrolyzer in its optimum operating region to avoid overheating. The DC-DC converter has been tested under simulated indoor conditions and uncontrolled outdoor conditions. Analysis of this DC-DC convertor based on maximum power tracking algorithm showed 94% efficiency.
Multi-Level Toolset for Steering Urban Green Infrastructure to Support the Development of Climate-Proofed Cities
Authors: Reinwald Florian , Brandenburg Christiane , Gabor Anna , Hinterkörner Peter , Kainz Astrid , Kraus Florian , Ring Zita , Scharf Bernhard , Tötzer Tanja , Damyanovic Doris
Published: November 2021

Adapting spatial development to the challenges of climate change is a major task facing cities. In particular, urban heat islands caused by increasing average temperatures and urban growth are a challenge for cities. The use of climate simulations to assess current and future urban heat stress is a helpful approach for supporting this transition. In particular, green and blue infrastructure helps to reduce the urban heat island effect. These cooling effects can be analysed using simulations. However, a central challenge is that urban adaptation to heat needs to be implemented consistently at different planning levels. A second major challenge in adaption is identifying the amount of urban green infrastructure required in order to achieve a specific cooling benefit and establishing this by means of planning instruments. This article presents two case studies in the city of Vienna to demonstrate how climate simulation tools can be used across different planning levels if they are standardized. When combined with a green and open space factor as a steering instrument, the necessary amount of greening for subsequent planning processes can be secured. The result is a multi-scale toolset consisting of three climate simulation models and a green and open space factor, coordinated, and standardised for use at different levels of planning.
CO2 Emissions Embodied in International Trade and Economic Growth: Empirical Evidence for OECD and Non-OECD Countries
Authors: Kang Hyunsoo
Published: November 2021

This study examined the relationship between CO2 emissions embodied in international trade and economic growth for OECD and non-OECD countries between 2005 and 2015. Unlike the traditional environmental Kuznets curve (EKC) hypothesis, which does not account for trade patterns, CO2 emissions embodied in trade balances were adopted in several models. To analyze the panel series, this study utilized econometric procedures: panel regression, the panel unit root test, the panel cointegration test, and panel Granger causality. To investigate evidence supporting the pollution haven hypothesis (PHH), this study constructed an equation including CO2 emissions embodied in net exports as a proportion of consumption. The results from the panel regression model validated the EKC hypothesis, even considering the CO2 emissions embodied in trade. Results of the panel unit root, panel cointegration, and Granger causality tests showed that CO2 emissions embodied in trade and economic growth have bi-directional Granger causality. This study provided evidence for the PHH, although some upper countries of net exporters or net importers for CO2 emissions can be observed. This study highlighted the need to intensify international cooperation to decrease environmental pollutants in both developed and developing countries, and considered the importance of CO2 emissions embodied in trade by expanding globalization.
An Index for the Sustainability of Integrated Urban Transport and Logistics: The Case Study of São Paulo
Authors: Senne Clara Moreira , Lima Josiane Palma , Favaretto Fábio
Published: November 2021

The objective of this paper is to understand the interactions and functioning of the transportation of people and goods in the urban environment, and to propose an evaluation model in terms of sustainability and integrated transportation. Firstly, an in-depth literature review allowed us to understand the interactions and functioning of transport of people and goods in the urban environment, verifying the main initiatives to promote sustainability. The model was developed through a multi-criteria decision analysis methodology consisting of the application of Analytic Hierarchy Process (AHP) in a system specially developed for remote evaluation of the hierarchical model. The index was then applied to São Paulo, where two distinct periods were considered, and the results provided an assessment of the evolution of the city regarding the sustainability and integration of the passenger and freight systems. The conclusions indicate improve in the sustainability of the urban transport and logistics in the city, highlighting the importance of incentives to the use of active modes of transport and the communication channel with population.
Indicators of the Public Participation Exercise for Designing Public Parks in Malaysia: A Systematic Review
Authors: Sonet Ungku Norani , Klufallah Mustafa , Peters Michael D. , Dixon Timothy J.
Published: November 2021

In an attempt to enhance democratic governance, sustainable development goals (SDG), and Local Agenda 21 (LA21), the notion of public participation exercise (PPE) presents a range of possibilities. The PPE is observed as a method of solving the constraints faced by public parks in Malaysia, which in general suffer from two main challenges, namely (i) the underutilisation issue of public parks and (ii) the weakness of the present top-down development policy. Consequently, the objective of this study is to develop indicators for PPE in designing public parks in Malaysia. The method implemented in this study is an assessment of the construct, variable, and indicator adapted from Lazarsfeld’s scheme by conducting a document review of the Public Consultation Index (PCI), six sustainability assessment tools, namely LEED-ND, BREEAM, IDP, SITES V2, Green Mark-NRB, and GTI, and literature references. The variables and indicators were tabulated into the respective operational definition of the construct table and variables and measurement table. The findings include the identification of two main constructs, including public participation and public parks. Multiple variables were derived from each construct, including attributes of PPE in designing public parks in Malaysia, development stage, method of approach, type of public, and public parks design criteria. Subsequently, this study developed the fundamental basis for the PPE framework in designing public parks in Malaysia, which benefits the local development approach for public parks towards an integrated design framework.
Establishing Operational Norms for Labor Rights Standards Implementation in Low-Cost Apparel Production
Authors: Hasan Rejaul , Moore Marguerite , Handfield Robert
Published: November 2021

Low-cost production has driven many global apparel brands and retailers to source apparel from less developed countries. However, low-cost apparel production is often accompanied by labor rights violations. A persistent pattern of labor rights violations exists in the global apparel supply chains, including minimum wage violations, unpaid overtime, forced overtime, worker abuse, restricting workers’ unions, and many other violations. Research suggests that low-cost pressures restrict factory level resources, which often leads to labor rights violations in global apparel supply chains. To date, academics and practitioners remain unaware of the actual cost of implementing labor rights standards in factories. We sought to establish a baseline taxonomy of the fundamental cost-bearing activities required to provide a safe and ethical factory workplace. A Delphi survey was adopted to capture data from an expert group of experienced factory compliance auditors in Asian apparel production. The research provides practical insights for factory adoption of actions that can improve enforcement of multiple labor standards, as well as specific actions required to enforce unique requirements that arose in our analysis.
Small-Angle Scattering from Fractional Brownian Surfaces
Authors: Anitas Eugen Mircea
Published: November 2021

Recent developments in nanotechnology have allowed the fabrication of a new generation of advanced materials with various fractal-like geometries. Fractional Brownian surfaces (fBs) are often used as models to simulate and characterize these complex geometries, such as the surface of particles in dilute particulate systems (e.g., colloids) or the interfaces in non-particulate two-phase systems (e.g., semicrystalline polymers with crystalline and amorphous phases). However, for such systems, a realistic simulation involves parameters averaged over a macroscopic volume. Here, a method based on small-angle scattering technique is proposed to extract the main structural parameters of surfaces/interfaces from experimental data. It involves the analysis of scattering intensities and the corresponding pair distance distribution functions. This allows the extraction of information with respect to the overall size, fractal dimension, Hurst and spectral exponents. The method is applied to several classes of fBs, and it is shown that the obtained numerical values of the structural parameters are in very good agreement with theoretical ones.
Reductions of Invariant bi-Poisson Structures and Locally Free Actions
Authors: Mykytyuk Ihor
Published: November 2021

Let (X,G,ω1,ω2,{ηt}) be a manifold with a bi-Poisson structure {ηt} generated by a pair of G-invariant symplectic structures ω1 and ω2, where a Lie group G acts properly on X. We prove that there exists two canonically defined manifolds (RLi,Gi,ω1i,ω2i,{ηit}), i=1,2 such that (1) RLi is a submanifold of an open dense subset X(H)⊂X; (2) symplectic structures ω1i and ω2i, generating a bi-Poisson structure {ηit}, are Gi- invariant and coincide with restrictions ω1|RLi and ω2|RLi; (3) the canonically defined group Gi acts properly and locally freely on RLi; (4) orbit spaces X(H)/G and RLi/Gi are canonically diffeomorphic smooth manifolds; (5) spaces of G-invariant functions on X(H) and Gi-invariant functions on RLi are isomorphic as Poisson algebras with the bi-Poisson structures {ηt} and {ηit} respectively. The second Poisson algebra of functions can be treated as the reduction of the first one with respect to a locally free action of a symmetry group.
Design of Broadband and Wide-Angle Hexagonal Metamaterial Absorber Based on Optimal Tiling of Rhombus Carbon Pixels and Implantation of Copper Cylinders
Authors: Kim Yongjune , Lee Jeong-Hae
Published: November 2021

A design method for a broadband and wide-angle metamaterial absorber is proposed based on optimal tiling of rhombus carbon pixels on and implantation of metal cylinders inside an acrylic substrate for which the backside is blocked by the perfect conductor. First, an intermediate carbon metapattern is achieved via optimal tiling of rhombus carbon pixels based on the genetic algorithm (GA), which can minimize the reflectances of both of the transverse electric (TE) and transverse magnetic (TM) polarized electromagnetic (EM) waves for the incident angles 0∘ and 60∘ simultaneously. Then, copper cylinders are implanted inside the substrate to boost the absorptions of both of the TE and TM polarizations for the 60∘ oblique incidences. To extend the absorption bandwidth, the design is finalized by evolving the intermediate metapattern using the GA. Based on the finalized carbon metapattern, the 90% absorption bandwidth is confirmed in the frequency range 8.8 to 11.6 GHz, for which the fractional bandwidth is 27.5% for both of the two polarizations with the incident angles from 0∘ to 60∘. The proposed method could open a way to design a broadband and wide-angle EM metamaterial absorber that can be applied to the edges of three-dimensional structures such as a regular tetrahedron or square pyramid that have interior angles of 60∘ that cannot be covered by conventional square or rectangular metamaterial absorbers.
An Anti-Counterfeit and Traceable Management System for Brand Clothing with Hyperledger Fabric Framework
Authors: Chen Chin-Ling , Shang Xin , Tsaur Woei-Jiunn , Weng Wei , Deng Yong-Yuan , Wu Chih-Ming , Cui Jianfeng
Published: November 2021

Counterfeit products are internationally regarded as “the world’s second greatest public health hazards after drugs”. Counterfeiters produce counterfeit brand clothing and then sell them to consumers through unofficial channels; thus, consumers spend a lot of money without getting the value they deserve. With the rise of e-shopping, the safety and security of branded clothing supply chains are also under threat. Counterfeit branded apparel manufacturers generate profits while genuine manufacturers suffer, which ultimately violates the interests of the public. This study proposes a traceable anti-counterfeit management system for branded clothing based on Hyperledger Fabric technology. This system can achieve full traceability of the production information of branded clothing. It uses the unique characteristics of blockchain, such as being unforgeable, traceable, open, and transparent, and collectively ‘maintaining’, to record the specific production processes of the brand clothing, and ensure the authenticity and legitimacy of the production information of brand clothing. The end-user can self-verify the product’s authenticity by sharing the product’s details on the immutable framework. It solves problems surrounding information asymmetry, opaque supply chain data, and easy falsification in the production process of branded clothing in traditional branded clothing supply chains.
New Fractional Dynamic Inequalities via Conformable Delta Derivative on Arbitrary Time Scales
Authors: El-Deeb Ahmed A. , Ahmad Hijaz , Awrejcewicz Jan
Published: November 2021

Building on the work of Josip Pečarić in 2013 and 1982 and on the work of Srivastava in 2017. We prove some new α-conformable dynamic inequalities of Steffensen-type on time scales. In the case when α=1, we obtain some well-known time scale inequalities due to Steffensen inequalities. For some specific time scales, we further show some relevant inequalities as special cases: α-conformable integral inequalities and α-conformable discrete inequalities. Symmetry plays an essential role in determining the correct methods to solve dynamic inequalities.
New Non-Toxic N-alkyl Cholinium-Based Ionic Liquids as Excipients to Improve the Solubility of Poorly Water-Soluble Drugs
Authors: Jesus Ana R. , Raposo Luís R. , Soromenho Mário R. C. , Agostinho Daniela A. S. , Esperança José M. S. S. , Baptista Pedro V. , Fernandes Alexandra R. , Reis Patrícia M.
Published: November 2021

In this work, we prepared new biocompatible N-alkyl cholinium-based ionic liquids to be used as cosolvents to improve the solubility of poorly water-soluble drugs, namely, sodium diclofenac and paracetamol. In this set of ionic liquids, we intend to understand the effect of increasing the asymmetry of the ionic liquid cation/anion by growing the length of one of the alkyl chains attached to the nitrogen center/sulfonate center on the dissolution capacity of the ionic liquid. The addition of these new ionic liquids to water increased the dissolution capacity of the drugs up to four-times that in water, and improved the pharmacodynamic properties of these drugs, especially the case of sodium diclofenac. The intermolecular interactions between the drugs and ionic liquids were investigated by NMR. Two-dimensional 1H/1H nuclear overhauser effect spectroscopy (NOESY) revealed an interaction between sodium diclofenac and the alaninate anion from the [C2Ch]2[SucAla]. In the case of paracetamol and [C4Ch][C2SO3], it was possible to observe two intermolecular interactions between the hydroxyl group of paracetamol and two protons from the cation [C4Ch]+. Interestingly, the ionic liquid bearing a succinyl-DL-alaninate anion, [SucAla]2−, and a N-ethyl cholinium cation, [C2Ch]+, which presented the highest ability to dissolve sodium diclofenac, showed no cytotoxicity up to 500 mM. Therefore, this ionic liquid is a potential candidate for drug delivery applications.
Symmetry Solutions and Conservation Laws for the 3D Generalized Potential Yu-Toda-Sasa-Fukuyama Equation of Mathematical Physics
Authors: Khalique Chaudry Masood , Plaatjie Karabo , Diteho Oageng Lawrence
Published: November 2021

In this paper we study the fourth-order three-dimensional generalized potential Yu-Toda-Sasa-Fukuyama (gpYTSF) equation by first computing its Lie point symmetries and then performing symmetry reductions. The resulting ordinary differential equations are then solved using direct integration, and exact solutions of gpYTSF equation are obtained. The obtained group invariant solutions include the solution in terms of incomplete elliptic integral. Furthermore, conservation laws for the gpYTSF equation are derived using both the multiplier and Noether’s methods. The multiplier method provides eight conservation laws, while the Noether’s theorem supplies seven conservation laws. These conservation laws include the conservation of energy and mass.
Weighted Sobolev–Morrey Estimates for Nondivergence Degenerate Operators with Drift on Homogeneous Groups
Authors: Hou Yuexia
Published: November 2021

Let X0,X1,…,Xq(q<N) be real vector fields, which are left invariant on homogeneous group G, provided that X0 is homogeneous of degree two and X1,…,Xq are homogeneous of degree one. We consider the following nondivergence degenerate operator with drift L=∑i,j=1qaij(x)XiXj+a0(x)X0, where the coefficients aij(x), a0(x) belonging to vanishing mean oscillation space are bounded measurable functions. Furthermore, aij(x) satisfies the uniform ellipticity condition on Rq and a0(x)≠0. We obtain the local weighted Sobolev–Morrey estimates by applying the boundedness of commutators and interpolation inequalities on weighted Morrey spaces.
An Alternate Generalized Odd Generalized Exponential Family with Applications to Premium Data
Authors: Khan Sadaf , Balogun Oluwafemi Samson , Tahir Muhammad Hussain , Almutiry Waleed , Alahmadi Amani Abdullah
Published: November 2021

In this article, we use Lehmann alternative-II to extend the odd generalized exponential family. The uniqueness of this family lies in the fact that this transformation has resulted in a multitude of inverted distribution families with important applications in actuarial field. We can characterize the density of the new family as a linear combination of generalised exponential distributions, which is useful for studying some of the family’s properties. Among the structural characteristics of this family that are being identified are explicit expressions for numerous types of moments, the quantile function, stress-strength reliability, generating function, Rényi entropy, stochastic ordering, and order statistics. The maximum likelihood methodology is often used to compute the new family’s parameters. To confirm that our results are converging with reduced mean square error and biases, we perform a simulation analysis of one of the special model, namely OGE2-Fréchet. Furthermore, its application using two actuarial data sets is achieved, favoring its superiority over other competitive models, especially in risk theory.
On the Johnson–Tzitzeica Theorem, Graph Theory, and Yang–Baxter Equations
Authors: Nichita Florin F.
Published: November 2021

This paper presents several types of Johnson–Tzitzeica theorems. Graph diagrams are used in this analysis. A symmetric scheme is derived, and new results are obtained and open problems stated. We also present results relating the graphs and the Yang–Baxter equation. This equation has certain symmetries, which are used in finding solutions for it. All these constructions are related to integrable systems.
Categorizing Diseases from Leaf Images Using a Hybrid Learning Model
Authors: N. Devi , P. Leela Rani , AR. Guru Gokul , Kannadasan Raju , Alsharif Mohammed H. , Jahid Abu , Khan Muhammad Asghar
Published: November 2021

Plant diseases pose a severe threat to crop yield. This necessitates the rapid identification of diseases affecting various crops using modern technologies. Many researchers have developed solutions to the problem of identifying plant diseases, but it is still considered a critical issue due to the lack of infrastructure in many parts of the world. This paper focuses on detecting and classifying diseases present in the leaf images by adopting a hybrid learning model. The proposed hybrid model uses k-means clustering for detecting the disease area from the leaf and a Convolutional Neural Network (CNN) for classifying the type of disease based on comparison between sampled and testing images. The images of leaves under consideration may be symmetrical or asymmetrical in shape. In the proposed methodology, the images of various leaves from diseased plants were first pre-processed to filter out the noise present to get an enhanced image. This improved image enabled detection of minute disease-affected regions. The infected areas were then segmented using k-means clustering algorithm that locates only the infected (diseased) areas by masking the leaves’ green (healthy) regions. The grey level co-occurrence matrix (GLCM) methodology was used to fetch the necessary features from the affected portions. Since the number of fetched features was insufficient, more synthesized features were included, which were then given as input to CNN for training. Finally, the proposed hybrid model was trained and tested using the leaf disease dataset available in the UCI machine learning repository to examine the characteristics between trained and tested images. The hybrid model proposed in this paper can detect and classify different types of diseases affecting different plants with a mean classification accuracy of 92.6%. To illustrate the efficiency of the proposed hybrid model, a comparison was made against the following classification approaches viz., support vector machine, extreme learning machine-based classification, and CNN. The proposed hybrid model was found to be more effective than the other three.
Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study
Authors: Martens Corentin , Lebrun Laetitia , Decaestecker Christine , Vandamme Thomas , Van Eycke Yves-Rémi , Rovai Antonin , Metens Thierry , Debeir Olivier , Goldman Serge , Salmon Isabelle , Van Simaeys Gaetan
Published: November 2021

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas. Nevertheless, these models require an initial condition: the tumor cell density distribution over the whole brain at diagnosis time. Several works have proposed to relate this distribution to abnormalities visible on magnetic resonance imaging (MRI). In this work, we verify these hypotheses by stereotactic histological analysis of a non-operated brain with glioblastoma using a 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2-FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously proposed exponential decrease of the tumor cell density with the distance to the core is reasonable but (ii) the edema outlines would not correspond to a cell density iso-contour and (iii) the suggested tumor cell density at these outlines is likely overestimated. These findings highlight the limitations of conventional MRI to derive glioma cell density maps and the need for other initialization methods for reaction-diffusion models to be used in clinical practice.
Cryoablation in Locoregional Management of Complex Unresectable Chest Neoplasms
Authors: Iezzi Roberto , Contegiacomo Andrea , Posa Alessandro , Attempati Nico , Punzi Ernesto , Tanzilli Alessandro , Margaritora Stefano , Congedo Maria Teresa , Cassano Alessandra , Bria Emilio , Tagliaferri Luca , Valentini Vincenzo , Colosimo Cesare , Manfredi Riccardo
Published: November 2021

Rationale and Objectives: The aim of our retrospective study was to assess the safety and feasibility of cryoablation in high-risk patients with complex chest neoplastic lesions. Materials and Methods: Twenty patients with complex chest malignancies, both primary and secondary, located in the mediastinum, lung, and chest wall, underwent percutaneous CT-guided cryoablation treatments. Procedural success as well as complications were evaluated. Results: A total of 24 neoplastic lesions were treated (mean diameter: 27 mm; range: 7–54 mm). Technical success was obtained in all patients, without major complications or intraprocedural death. A pneumothorax not requiring a drainage tube placement was registered in 50% of patients, while 3/24 patients had a grade 3 pneumothorax requiring a chest tube placement. Conclusion: Percutaneous CT-guided cryoablation seems a safe and feasible treatment for complex thoracic lesions.
The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
Authors: Szabó István Viktor , Simon Judit , Nardocci Chiara , Kardos Anna Sára , Nagy Norbert , Abdelrahman Renad-Heyam , Zsarnóczay Emese , Fejér Bence , Futácsi Balázs , Müller Veronika , Merkely Béla , Maurovich-Horvat Pál
Published: November 2021

We sought to analyze the prognostic value of laboratory and clinical data, and an artificial intelligence (AI)-based algorithm for Coronavirus disease 2019 (COVID-19) severity scoring, on CT-scans of patients hospitalized with COVID-19. Moreover, we aimed to determine personalized probabilities of clinical deterioration. Data of symptomatic patients with COVID-19 who underwent chest-CT-examination at the time of hospital admission between April and November 2020 were analyzed. COVID-19 severity score was automatically quantified for each pulmonary lobe as the percentage of affected lung parenchyma with the AI-based algorithm. Clinical deterioration was defined as a composite of admission to the intensive care unit, need for invasive mechanical ventilation, use of vasopressors or in-hospital mortality. In total 326 consecutive patients were included in the analysis (mean age 66.7 ± 15.3 years, 52.1% male) of whom 85 (26.1%) experienced clinical deterioration. In the multivariable regression analysis prior myocardial infarction (OR = 2.81, 95% CI = 1.12–7.04, p = 0.027), immunodeficiency (OR = 2.08, 95% CI = 1.02–4.25, p = 0.043), C-reactive protein (OR = 1.73, 95% CI = 1.32–2.33, p < 0.001) and AI-based COVID-19 severity score (OR = 1.08; 95% CI = 1.02–1.15, p = 0.013) appeared to be independent predictors of clinical deterioration. Personalized probability values were determined. AI-based COVID-19 severity score assessed at hospital admission can provide additional information about the prognosis of COVID-19, possibly serving as a useful tool for individualized risk-stratification.