bluuebunny/crossref_metadata_2025 huggingface dataset:
Does Reference Dependence Impact Intervention Mechanisms in Vaccine Markets?
Authors: Guo Feiyu , Cao Erbao
Published: August 2020

Prior research suggests that, to maintain sustainable health, inefficient vaccine markets need to be intervened by government subsidy. However, the effectiveness of these intervention mechanisms is often reduced by the absence of reference dependence preference. Our paper introduces this preference as the psychological disutility of overproduction and underproduction, and then uses game-theoretic way to find that reference dependence has implications on one-sided (pure demand or supply side) and two-sided intervention mechanisms. (i) The positive impact is that this preference helps both pure demand-sided and specific two-sided intervention mechanisms not only to maximize social welfare, but also to achieve diverse targets: pure demand-sided one reduces government interventions while specific two-sided ones achieves budget neutrality. (ii) The negative impact is that, although maximizing social welfare, reference dependence makes general two-sided intervention mechanisms complex. This complexity is reflected in differences in intervention’s extent (i.e., a change in payment extent used to address inefficient vaccine markets) and structure (i.e., an adjustment from subsidy alone to subsidy/tax/zero schemes). These finds guide governments with diverse targets to design the corresponding intervention mechanisms to maintain sustainable health.
Investigation of Sustainable Geopolymer Composite Using Automatic Identification Technology
Authors: Behun Marcel , Kascak Patrik , Hrabcak Matej , Behunova Annamaria , Knapcikova Lucia , Sofranko Marian
Published: August 2020

Geopolymers are materials prepared from alkaline-activated cement without a calcium constituent. They are synthetic materials based on aluminosilicates. The main advantage of these environmentally friendly materials is that they save mineral resources and due to being free of calcium constituents, and only a small amount of CO2 emissions are released into the environment. The circular economy model of sustainable development of new composite materials will ensure the competitiveness of industries, their stable economic growth, and a healthy environment. This paper aims to investigate geopolymer composite materials that were reinforced with a mixture of glass powder from recycled windscreens. The glass 100% circulates in the closed material cycle and can be used again in the manufacturing process without any loss of quality. We are focused on verification of readability of selected automatic identification technology and their usability directly in the manufacturing process of geopolymer composite materials.
Development of Sustainability Indicators for Employee-Activity Based Production Process Using Fuzzy Delphi Method
Authors: Lin Chiuhsiang Joe , Belis Tariku Tamiru , Caesaron Dino , Jiang Bernard C. , Kuo Tsai Chi
Published: August 2020

Production process sustainability refers to a manufacturing system in which manufacturing industries produce products in a sustainable way. In recent years, sustainability has become a major concern and challenge for manufacturing systems because of growing consciousness of the effects of their activities on the environment, society, and economy. Different organizational reports and the academic literature have proposed indicators of sustainable manufacturing that help to measure product and process sustainability. However, little of the previous research is related to employee-activity based indicators for production process sustainability. To bridge the gap, this study identified a set of indicators of production process sustainability based on direct and indirect impacts of manufacturing activities on employees, who are key resources in the entire production process, for efficiently applying a sustainability perspective. In addition, the paper provides an evaluation model for selecting relatively important indicators based on expert opinions. A fuzzy Delphi method was applied for the screening process of the decision makers (experts). A Delphi questionnaire prepared with a nine-point linguistic scale corresponding to respective linguistic variables was utilized to assess expert opinions on the importance of each indicator. These expert opinions were aggregated for each indicator by using an adopted algorithm that considers the degree of importance allocated to the decision makers, and the similarity and distance among decision maker opinions. Lastly, the key employee-activity based indicators were chosen based on the threshold value set.
Segmenting Olive Oil Consumers Based on Consumption and Preferences toward Extrinsic, Intrinsic and Sensorial Attributes of Olive Oil
Authors: Ilak Peršurić Anita Silvana
Published: August 2020

The aim of this paper was to identify and describe segments of a study population that consumes olive oil. Therefore, a survey was conducted in 2019 on a sample of 705 German and 175 UK consumers. In both samples, three consumer segments were identified. These three segments differed significantly with regard to purchase and consumption patterns, as well as attitudes toward the extrinsic, intrinsic, sensorial, and health attributes of olive oil. Their main preferences related to health properties of olive oil, followed by hedonic attributes; therefore, these aspects should be marketed in German markets. For UK consumers, validation of extrinsic attributes, such as region, micro-location, and protected designation of geographical origin (PDO), should be used in marketing campaigns in light of economic sustainability on local family farms and small and medium-sized enterprises (SMEs). Since UK consumers rely heavily on vendors’ recommendations, more effort should be made in the UK market to establish habits of consumption and an olive oil culture that would be sustainable in long-term time frames.
Circular Economy. A Review and Bibliometric Analysis
Authors: Camón Luis Enric , Celma Dolors
Published: August 2020

The aim of the study is mapping the thematic structure of the circular economy research by mapping research outputs related to it. The methodology consists of developing a bibliometric study based on data obtained from the Web of Science and the Scimago Journal & Country Rank from 2016 to 2019. Some descriptive and bibliographic maps and strategic diagrams are shown; they are generated by SciMAT and VOSViewer. In addition, there is also a bibliometric analysis using alternative metrics. The analysis highlights a new perspective on the subject, analysing the concept from the business administration perspective and not only from the traditional viewpoint of the environmental sciences and industrial production. Finally, the analysis identifies future implications of the circular economy linked to the field of business management.
Forecasting Wastewater Temperature Based on Artificial Neural Network (ANN) Technique and Monte Carlo Sensitivity Analysis
Authors: Golzar Farzin , Nilsson David , Martin Viktoria
Published: August 2020

Wastewater contains considerable amounts of thermal energy. Heat recovery from wastewater in buildings could supply cities with an additional source of renewable energy. However, variations in wastewater temperature influence the performance of the wastewater treatment plant. Thus, the treatment is negatively affected by heat recovery upstream of the plant. Therefore, it is necessary to develop more accurate models of the wastewater temperature variations. In this work, a computational model based on artificial neural network (ANN) is proposed to calculate wastewater treatment plant influent temperature concerning ambient temperature, building effluent temperature and flowrate, stormwater flowrate, infiltration flowrate, the hour of day, and the day of year. Historical data related to the Stockholm wastewater system are implemented in MATLAB software to drive the model. The comparison of calculated and observed data indicated a negligible error. The main advantage of this ANN model is that it only uses historical data commonly recorded, without any requirements of field measurements for intricate heat transfer models. Moreover, Monte Carlo sensitivity analysis determined the most influential parameters during different seasons of the year. Finally, it was shown that installing heat exchangers in 40% of buildings would reduce 203 GWh year−1 heat loss in the sewage network. However, heat demand in WWTP would be increased by 0.71 GWh year−1, and the district heating company would recover 176 GWh year−1 less heat from treated water.
Sustainable Innovations in Small Enterprises for the Transformation of the Primary Healthcare Sector
Authors: Emilsson Maria , Ernstson Ulf , Gustavsson Linn , Svensson Ann
Published: August 2020

Small enterprises face multiple and complex challenges when developing digital technologies. The aim of this article is to explore the role of sustainable innovation in small enterprises in relation to the ongoing transformation of the primary healthcare sector. The purpose is to gain understanding of innovation processes within the framework of sustainable development, applied to a local primary healthcare center. Data were collected through seven semi-structured interviews. A qualitative thematic analysis was conducted. Five themes appeared in relation to the ongoing transformation of the primary healthcare sector: (1) The process of sustainable innovation in a long-term perspective; (2) the companies’ views on innovations in healthcare; (3) effects of innovations in healthcare; (4) sustainable product or service development, and (5) the role of collaboration in the innovation process. The companies expressed a positive attitude to new innovations, as a natural part of developing the companies. The article concludes that incremental development of tools in small businesses supports the transformation of processes and services in the primary healthcare sector. Cross-disciplinary teams in collaboration facilitates the necessary learning and the required creation and sharing of knowledge.
Foresights from the Swedish Kitchen: Four Circular Value Opportunities for the Built Environment
Authors: Ollár Anita , Femenías Paula , Rahe Ulrike , Granath Kaj
Published: August 2020

This paper examines the kitchen as one relevant part of the home that is highly affected by frequent replacements, renovations, and a short service life. The aim is to discern circular value opportunities for the built environment by examining stakeholder activities and the value proposition associated with Swedish kitchens. The paper answers the research question ‘Which aspects in stakeholders’ value proposition of kitchens might contribute to future circular housing design?’. The empirical material was collected through a workshop, interviews, and a focus group session. The data were analysed using qualitative content analysis while applying value mapping as an analytical framework. Four opportunities for circularity were identified: (1) aligning spatial and product design for a circular economy, (2) considering end-user perspectives and demands, (3) formulating regulations informed by research, and (4) developing circular products and services through collaboration. While some of these opportunities have already been emphasised in previous literature, the most distinct contribution of this paper is that it reveals the importance of spatial parameters when transitioning towards a circular housing design. The methods and results of this paper may be adapted to various building components to create a system-level circular economy in the built environment.
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China
Authors: Shen Neng , Wang Yifan , Peng Hui , Hou Zhiping
Published: August 2020

Excessive consumption of traditional fossil energy has led to more serious global air pollution. This article incorporates renewable energy green innovation (REGI), fossil energy consumption (FEC), and air pollution into a unified analysis framework. Using China’s provincial panel data, a spatial measurement model was used to investigate the spatial effects of renewable energy green innovation and fossil energy consumption on air pollution in China from 2011 to 2017. The global Moran index shows that over time, the spatial correlation of air pollution has gradually weakened, while the global correlation of renewable energy green innovation and fossil energy consumption is increasing year by year. ArcGIS visualization and partial Moran index show that air pollution, renewable energy green innovation, and fossil energy consumption are extremely uneven in geographic space. The spatial distribution of air pollution, renewable energy green innovations, and fossil energy consumption are all characterized by high in the east and low in the west and they all show a strong spatial aggregation. Applying the spatial adjacency matrix to the spatial Durbin model gave the results that China’s air pollution has a significant spatial spillover effect. Replacing fossil fuels with clean renewable energy will reduce air pollutant emissions. The Environment Kuznets Curve (EKC) hypothesis has not been supported and verified in China. The partial differential method test found that the spatial spillover benefits can be decomposed into direct effects and indirect effects. The direct and indirect effects of renewable energy green innovation on air pollution are both significantly negative, indicating that green innovation of renewable energy not only inhibits local air pollution, but also inhibits air pollution in nearby areas. The consumption of fossil energy will significantly increase the local air pollution, while the impact of sulfur dioxide (SO2) and soot (DS) pollution in nearby areas is not obvious. It is recommended to increase investment in renewable energy green innovation, reduce the proportion of traditional fossil energy consumption, and pay attention to the spatial connection and overflow of renewable energy green innovation and air pollution.
Decision-Making Framework for Evaluating Physicians’ Preference Items Using Multi-Objective Decision Analysis Principles
Authors: Shbool Mohammad A. , Rossetti Manuel D.
Published: August 2020

Physician preference items or PPIs are medical items recommended by physicians for use in medical procedures and other treatments. The recommendation of PPIs by individual physicians can cause the variety of item types that need to be managed within a health care supply chain to increase over time. To better manage the PPI selection process, healthcare organizations often select items through value analysis and discussion teams, which are highly subjective. To better control PPIs, this work uses multiple-objective decision analysis (MODA) to develop a structured quantitative framework for the PPI selection process. The established decision-making framework is based on the theory of multi-objective value analysis. It offers a structured and educated guide to decision-makers for improving value analysis outcomes, advocating sustainable healthcare management strategies. The model was tested and validated through two case studies on two different items in two hospitals in Jordan.
Integrated Assessment of Climate Change Impacts and Urban Resilience: From Climate and Hydrological Hazards to Risk Analysis and Measures
Authors: Velasco Marc , Russo Beniamino , Martínez-Gomariz Eduardo
Published: August 2020

This Special Issue brings together recent research findings related to urban resilience, in particular taking into account climate change impacts and hydrological hazards. Taking advantage of the work done in the H2020 RESCCUE project, 12 different papers dealing with several issues related to the resilience of urban areas have been published. Due to the complexity of cities, urban resilience management is one of the key challenges that our societies have to deal with in the near future. In addition, urban resilience is a transversal and multi-sectorial issue, affecting different urban services, several hazards, and all the steps of the risk management cycle. This is precisely why the papers contained in this Special Issue focus on varied subjects, such as impact assessments, urban resilience assessments, adaptation strategies, flood risk and urban services, always focusing on at least two of these topics.
Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances
Authors: Grimaldi Michele , Sebillo Monica , Vitiello Giuliana , Pellecchia Vincenzo
Published: August 2020

The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account that human beings need water to survive, as well as all the systems on which they rely, namely sanitation, health, education, business, and industry. While human behavior is influenced by the growing awareness on this topic promoted by organizations specifically targeting this mission, the need to protect water resources in operational terms has led mainly to the need for smart urban infrastructure planning, consistent with the objective of promoting sustainable development. To this aim, the authorities in charge of monitoring the implementation of the investment plans by operators need to perform accurate evaluations of the technical quality of the services provided. The present paper introduces a framework to design a Multi-criteria Spatial Decision Support System, conceived to help decision-makers define and analyze the investment priorities of the individual service operators. By building a knowledge model of the network under investigation, decision-makers are aware of physical components of the whole system and are provided with an intervention priority index related to the network objects that could be affected by the planning action to be implemented.
Driving Municipal Recycling by Connecting Digital Value Endpoints in Smart Cities
Authors: Herraiz-Faixó Ferran , Arroyo-Cañada Francisco-Javier
Published: August 2020

Uncontrolled global economic growth at any cost is having palpable and general consequences for SC (smart cities) environments and sustainability worldwide. The current economic growth model is, according to experts, decidedly unsustainable, and if urgent measures are not taken, the quality of life for future citizens will decline. In the search for solutions that would make cities sustainable, the deployment of the ICT factor is playing a decisive role. However, in its role as a driver, the ICT factor needs to increase the numbers of value endpoint connectors by incorporating citizens, corporations and institutions into city decision-making, thereby becoming a real integrative tool that achieves sustainability and is more than merely a tech flag. In this sense, the present paper proposes that the digital and programmable economy as an ecosystem should become a sustainability city driver because it facilitates the integration of different value endpoints in order to work in the same purpose, allowing, for example, increased sustainability levels in cities such as improving municipal recycling. This paper will apply ICT and digital concepts, the environment-social-economy model and fuzzy logic methodology.
Robustness Evaluations of Sustainable Machine Learning Models against Data Poisoning Attacks in the Internet of Things
Authors: Dunn Corey , Moustafa Nour , Turnbull Benjamin
Published: August 2020

With the increasing popularity of the Internet of Things (IoT) platforms, the cyber security of these platforms is a highly active area of research. One key technology underpinning smart IoT systems is machine learning, which classifies and predicts events from large-scale data in IoT networks. Machine learning is susceptible to cyber attacks, particularly data poisoning attacks that inject false data when training machine learning models. Data poisoning attacks degrade the performances of machine learning models. It is an ongoing research challenge to develop trustworthy machine learning models resilient and sustainable against data poisoning attacks in IoT networks. We studied the effects of data poisoning attacks on machine learning models, including the gradient boosting machine, random forest, naive Bayes, and feed-forward deep learning, to determine the levels to which the models should be trusted and said to be reliable in real-world IoT settings. In the training phase, a label modification function is developed to manipulate legitimate input classes. The function is employed at data poisoning rates of 5%, 10%, 20%, and 30% that allow the comparison of the poisoned models and display their performance degradations. The machine learning models have been evaluated using the ToN_IoT and UNSW NB-15 datasets, as they include a wide variety of recent legitimate and attack vectors. The experimental results revealed that the models’ performances will be degraded, in terms of accuracy and detection rates, if the number of the trained normal observations is not significantly larger than the poisoned data. At the rate of data poisoning of 30% or greater on input data, machine learning performances are significantly degraded.
Research on the Sustainability of the Enterprise Business Ecosystem from the Perspective of Boundary: The China Case
Authors: He Li , Cheng Yang , Su Xuejie
Published: August 2020

In the context of the Internet, the business environment shows great uncertainty. This kind of uncertainty has not only changed the original competitive boundary of enterprise completely, but also the competition rules of enterprise. The cooperation of enterprises with suppliers, producers, sellers, customers, other organizations and stakeholders is getting closer and closer. The competition among enterprises is no longer the competition between individual enterprises, but based on the co-evolution under the business ecosystem. Therefore, how to create a good business ecosystem and sustainable development is the main problem faced by enterprises. This paper conducts an exploratory case study on the sustainability of the business ecosystem of enterprises from the perspective of boundary, to provide a new theoretical basis for the sustainable development of enterprises. This study investigates the specific impact of various system elements on the sustainable development of enterprises, summarizes the theoretical model, and finally provides feasible suggestions on promoting the sustainable development of the business ecosystem from the perspective of boundary.
Environmental Health Diagnosis in a Park as a Sustainability Initiative in Cities
Authors: Orozco-Medina Martha Georgina , Martínez-Abarca Javier Omar , Figueroa-Montaño Arturo , Davydova-Belitskaya Valentina
Published: August 2020

Environmental health diagnosis was made in a sport and recreational park in the city of Guadalajara, Jalisco, Mexico. The objective of this research was to perform an environmental diagnosis in Tucson Park; it concentrated on air quality (fine and coarse particulate matter, carbon dioxide), environmental noise, water quality of springs and a pond according to national standards, and macroinvertebrates as biological indicators of water condition, as well as phytosanitary state of wooded area. Additionally, a survey was conducted to study environmental perception. Results of the study highlighted significant statistical differences concerning the amount and size of particles for the winter and spring seasons. Noise levels within the park premises exceeded the Mexican standard. Water quality measured through general criteria of integrated water quality index (WQI) qualified the park´s analyzed springs as acceptable but to abstain its use and human consumption. Finally, the perception survey identified insecurity as the major problem, followed by the lack of lighting and effective communication of courses and workshops for the community to attend. It is one of the first environmental diagnoses in sport parks in Mexico´s Metropolitan Areas as an integrated approach of ecosystem health and wellbeing of city inhabitants.
‘Plural Reciprocity’ vs. ‘Acquaintance Society’: Place Attachment and Residential Satisfaction under Development-Induced Resettlement Differences in Guangzhou, China
Authors: Qiu Jianjian , Liu Yihua , Xian Shi , Song Longjian , Ru Xiaolin
Published: August 2020

In the context of urban expansion and regeneration, development-induced resettlement has had inevitable impacts on place attachment and residential satisfaction of residents. However, insufficient attention has been paid to the social-psychological performances of both attachment and satisfaction, and the possible influences of the former on the latter. Such deficiency also emerges when considering different resettlement patterns in peripheral urban China. This study conducted a semi-structural survey on two neighborhoods affected by the construction of Higher Mega Education Center (HEMC) in Guangzhou with different resettlement patterns. Based on multidimensional measurement, residents in relocated subsidized housing expressed higher attachment and satisfaction through the remaining social bonding as ‘acquaintance society’ than those in in-situ urban villages relying on self-identified clan-kinship and stable reciprocity. Hukou status is found to be fundamental in building attachment and life fulfillment, especially for the urban villages with plural population structure. Significances are found in the impacts of place dependence, social bonding and place identification on residential satisfaction in in-situ neighborhoods while only social bonding was found to be significant in the relocated ‘enclave’ one. However, deeper integration with affective connections are insufficient for both. The findings generally indicate that positive outcomes are also achieved for self-regeneration after resettlement.
Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation
Authors: Haq Mohammad Asif ul , Islam Aminul , Shihavuddin ASM , Maruf Md Hasan , Al Mansur Ahmed , Hassan Mohammad Yusri
Published: August 2020

Daylight utilization is one of the key areas for energy savings in indoor environments. An important factor often not considered by the existing daylight utilization approaches is the segregation of the floor into task areas and non-task areas. It is also observed that the inherent asymmetry in the daylight penetration pattern in most indoor environments is not given consideration while designing artificial lighting arrangements. Moreover, daily and annual daylight availability is found to have a symmetrical variation pattern, which is a significant factor often overlooked in utilizing daylight. Thus, the energy assessment can be inaccurate, leading to an incorrect or impractical evaluation of energy savings. This research proposes a comprehensive new approach to assess the energy-saving potential of daylight utilization in indoor environments. This new method combines two approaches to overcome the aforementioned issues. (1) The considered area is segmented into task area and non-task areas (or surrounding area) and considers different levels of required illuminance for each separate area. (2) The variation of available daylight at the considered location is accounted for by dividing the daylight penetration into multiple levels. For the study, the method is first applied to a simulated office space considering real-life parameters, where the annual energy savings were estimated at 83.67%. For further validation, a comparison with a case from an existing method was also carried out, and the proposed method gave an energy saving estimation of 73.45%. This indicates a 10% higher energy saving estimation as compared to the original study, against which the proposed method was compared.
Asymmetrical Pseudo-Extinction Phenomenon in the Illusory Line Motion
Authors: Del Vicario Vidheya G. , Actis-Grosso Rossana , Bolognini Nadia , Daini Roberta
Published: August 2020

Illusory Line Motion (i.e., a static line, presented after a lateral cue, is perceived as movement in the opposite direction to the cue) has been used to study a phenomenon of perceptual asymmetry. We have demonstrated the presence of an illusion of leftward movement, even in the presence of bilateral symmetrical cues. We have classified this phenomenon as one of pseudo-extinction. The paradigm of the four experiments performed was always the same: a white line, briefly presented alone or preceded by one or two lateral cues (150 ms), was judged by a group of young participants to be moving either to one side or the other. The asymmetrical effect in the bilateral cue condition was observed with horizontal lines (Experiment 1 and 4), and not with vertical or oblique (Experiment 2 and 3). These results suggest that the effect is linked to the asymmetry of the horizontal spatial planum and the mechanisms of spatial attention. Experiment 4 verified whether the Illusory Line Motion involves the collicular pathway by using blue stimuli for the cues, which activate less the Superior Colliculus (SC), with negative results. We interpreted the asymmetrical pseudo-extinction phenomenon in terms of a right-space exogenous attention advantage.
Remaining Useful Life Prediction of an IGBT Module in Electric Vehicles Statistical Analysis
Authors: Wu Huawei , Ye Congjin , Zhang Yuanjin , Nie Jingquan , Kuang Yong , Li Zhixiong
Published: August 2020

The whole life cycle of an insulated gate bipolar transistor (IGBT) is a kind of asymmetry process, while the whole life cycles of a set of IGBTs can be regarded as a symmetry process. Modelling these symmetry characteristics of the IGBT life cycles enables the improvement of the remaining useful life (RUL) prediction performance. For this purpose, based on the key failure mechanism of IGBT in electric vehicles, a new method for estimating the RUL of an IGBT module is proposed based on the two-stress acceleration synthesis environment of junction temperature and vibration. The maximum likelihood estimation (MLE) was employed to estimate the logarithmic standard deviation and covariance matrix. The Shapiro–Wilk (S–W) test was performed to investigate the satisfaction degree of the RUL of the IGBT module to the lognormal distribution. The accelerated life test datasets of the IGBT module were analyzed using the Weibull++ software. The analysis results demonstrate that the IGBT lifetime is confirmed to lognormal distribution, and the accelerated model accords with the generalized Eyring acceleration model. The proposed method can estimate IGBT RUL in a short time, which provides a certain technical reference for the reliability analysis of the IGBT module.
A Systematic Review of Challenges and Opportunities of Blockchain for E-Voting
Authors: Taş Ruhi , Tanrıöver Ömer Özgür
Published: August 2020

A blockchain is a distributed, digitized and consensus-based secure information storage mechanism. The present article provides an overview of blockchain based e-voting systems. The primary purpose of this review is to study the up-to-date state of blockchain-based voting research along with associated possible challenges while aiming to forecast future directions. The methodology applied in the review is a systematic review approach. Following an introduction to the basic structure and features of the blockchain in relation to e-voting, we provide a conceptual description of the desired blockchain-based e-voting application. Symmetrical and asymmetrical cryptography improvements play a key role in developing blockchain systems. We have extracted and reviewed 63 research papers from scientific databases that have advised the adoption of the blockchain framework to voting systems. These articles indicate that blockchain-supported voting systems may provide different solutions than traditional e-voting. We classified the main prevailing issues into the five following categories: general, integrity, coin-based, privacy and consensus. As a result of this research, it was determined that blockchain systems can provide solutions to certain problems that prevail in current election systems. On the other hand, privacy protection and transaction speed are most frequently emphasized problems in blockchain applications. Security of remote participation and scalability should be improved for sustainable blockchain based e-voting. It was concluded that frameworks needed enhancements in order to be used in voting systems due to these reservations.
Convergence Analysis of Self-Adaptive Inertial Extra-Gradient Method for Solving a Family of Pseudomonotone Equilibrium Problems with Application
Authors: Bantaojai Thanatporn , Pakkaranang Nuttapol , ur Rehman Habib , Kumam Poom , Kumam Wiyada
Published: August 2020

In this article, we propose a new modified extragradient-like method to solve pseudomonotone equilibrium problems in real Hilbert space with a Lipschitz-type condition on a bifunction. This method uses a variable stepsize formula that is updated at each iteration based on the previous iterations. The advantage of the method is that it operates without prior knowledge of Lipschitz-type constants and any line search method. The weak convergence of the method is established by taking mild conditions on a bifunction. In the context of an application, fixed-point theorems involving strict pseudo-contraction and results for pseudomonotone variational inequalities are considered. Many numerical results have been reported to explain the numerical behavior of the proposed method.
A Gyrogeometric Mean in the Einstein Gyrogroup
Authors: Honma Takuro , Hatori Osamu
Published: August 2020

In this paper, we define a gyrogeometric mean on the Einstein gyrovector space. It satisfies several properties one would expect for means. For example, it is permutation-invariant and left-translation invariant. It is already known that the Einstein gyrogroup is a gyrocommutative gyrogroup. We give an alternative proof which depends only on an elementary calculation.
Investigation of the Efficacy of a Postbiotic Yeast Cell Wall-Based Blend on Newly-Weaned Pigs under a Dietary Challenge of Multiple Mycotoxins with Emphasis on Deoxynivalenol
Authors: Holanda Debora Muratori , Yiannikouris Alexandros , Kim Sung Woo
Published: August 2020

Pigs are highly susceptible to mycotoxins. This study investigated the effects of a postbiotic yeast cell wall-based blend (PYCW; Nicholasville, KY, USA) on growth and health of newly-weaned pigs under dietary challenge of multiple mycotoxins. Forty-eight newly-weaned pigs (21 d old) were individually allotted to four dietary treatments, based on a three phase-feeding, in a randomized complete block design (sex; initial BW) with two factors for 36 d. Two factors were dietary mycotoxins (deoxynivalenol: 2000 μg/kg supplemented in three phases; and aflatoxin: 200 μg/kg supplemented only in phase 3) and PYCW (0.2%). Growth performance (weekly), blood serum (d 34), and jejunal mucosa immune and oxidative stress markers (d 36) data were analyzed using MIXED procedure of SAS. Mycotoxins reduced (p < 0.05) average daily feed intake (ADFI) and average daily gain (ADG) during the entire period whereas PYCW did not affect growth performance. Mycotoxins reduced (p < 0.05) serum protein, albumin, creatinine, and alanine aminotransferase whereas PYCW decreased (p < 0.05) serum creatine phosphokinase. Neither mycotoxins nor PYCW affected pro-inflammatory cytokines and oxidative damage markers in the jejunal mucosa. No interaction was observed indicating that PYCW improved hepatic enzymes regardless of mycotoxin challenge. In conclusion, deoxynivalenol (2000 μg/kg, for 7 to 25 kg body weight) and aflatoxin B1 (200 μg/kg, for 16 to 25 kg body weight) impaired growth performance and nutrient digestibility of newly-weaned pigs, whereas PYCW could partially improve health of pigs regardless of mycotoxin challenge.
Purification and Characterization of the Pink-Floyd Drillipeptide, a Bioactive Venom Peptide from Clavus davidgilmouri (Gastropoda: Conoidea: Drilliidae)
Authors: Chua Victor M. , Gajewiak Joanna , Watkins Maren , Espino Samuel S. , Ramiro Iris Bea L. , Omaga Carla A. , Imperial Julita S. , Carpio Louie Paolo D. , Fedosov Alexander , Safavi-Hemami Helena , Salvador-Reyes Lilibeth A. , Olivera Baldomero M. , Concepcion Gisela P.
Published: August 2020

The cone snails (family Conidae) are the best known and most intensively studied venomous marine gastropods. However, of the total biodiversity of venomous marine mollusks (superfamily Conoidea, >20,000 species), cone snails comprise a minor fraction. The venoms of the family Drilliidae, a highly diversified family in Conoidea, have not previously been investigated. In this report, we provide the first biochemical characterization of a component in a Drilliidae venom and define a gene superfamily of venom peptides. A bioactive peptide, cdg14a, was purified from the venom of Clavus davidgilmouri Fedosov and Puillandre, 2020. The peptide is small (23 amino acids), disulfide-rich (4 cysteine residues) and belongs to the J-like drillipeptide gene superfamily. Other members of this superfamily share a conserved signal sequence and the same arrangement of cysteine residues in their predicted mature peptide sequences. The cdg14a peptide was chemically synthesized in its bioactive form. It elicited scratching and hyperactivity, followed by a paw-thumping phenotype in mice. Using the Constellation Pharmacology platform, the cdg14a drillipeptide was shown to cause increased excitability in a majority of non-peptidergic nociceptors, but did not affect other subclasses of dorsal root ganglion (DRG) neurons. This suggests that the cdg14a drillipeptide may be blocking a specific molecular isoform of potassium channels. The potency and selectivity of this biochemically characterized drillipeptide suggest that the venoms of the Drilliidae are a rich source of novel and selective ligands for ion channels and other important signaling molecules in the nervous system.
Survey of Tetrodotoxin in New Zealand Bivalve Molluscan Shellfish over a 16-Month Period
Authors: Boundy Michael J. , Biessy Laura , Roughan Brian , Nicolas Jeane , Harwood D. Tim
Published: August 2020

Tetrodotoxin (TTX) is a heat-stable neurotoxin typically associated with pufferfish intoxications. It has also been detected in shellfish from Japan, the United Kingdom, Greece, China, Italy, the Netherlands and New Zealand. A recent European Food Safety Authority (EFSA) scientific opinion concluded that a level of <0.044 mg TTX/kg in marine bivalves and gastropods, based on a 400 g portion size, does not result in adverse effects in humans. There have been no reports of human illness attributed to the consumption of New Zealand shellfish containing TTX. To obtain a greater understanding of its presence, a survey of non-commercial New Zealand shellfish was performed between December 2016 and March 2018. During this period, 766 samples were analysed from 8 different species. TTX levels were found to be low and similar to those observed in shellfish from other countries, except for pipi (Paphies australis), a clam species endemic to New Zealand. All pipi analysed as part of the survey were found to contain detectable levels of TTX, and pipi from a sampling site in Hokianga Harbour contained consistently elevated levels. In contrast, no TTX was observed in cockles from this same sampling site. No recreationally harvested shellfish species, including mussels, oysters, clams and tuatua, contained TTX levels above the recommended EFSA safe guidance level. The levels observed in shellfish were considerably lower than those reported in other marine organisms known to contain TTX and cause human intoxication (e.g., pufferfish). Despite significant effort, the source of TTX in shellfish, and indeed all animals, remains unresolved making it a difficult issue to understand and manage.
Nuclear Pairing Gaps and Neutron Star Cooling
Authors: Wei Jin-Biao , Burgio Fiorella , Schulze Hans-Josef
Published: August 2020

We study the cooling of isolated neutron stars with particular regard to the importance of nuclear pairing gaps. A microscopic nuclear equation of state derived in the Brueckner-Hartree-Fock approach is used together with compatible neutron and proton pairing gaps. We then study the effect of modifying the gaps on the final deduced neutron star mass distributions. We find that a consistent description of all current cooling data can be achieved and a reasonable neutron star mass distribution can be predicted employing the (slightly reduced by about 40%) proton 1S0 Bardeen-Cooper-Schrieffer (BCS) gaps and no neutron 3P2 pairing.
Chronic Hepatitis B Infection Is Associated with Increased Molecular Degree of Inflammatory Perturbation in Peripheral Blood
Authors: Vinhaes Caian L. , Cruz Luís A. B. , Menezes Rodrigo C. , Carmo Thomas A. , Arriaga María B. , Queiroz Artur T. L. , Barral-Netto Manoel , Andrade Bruno B.
Published: August 2020

Hepatitis B virus (HBV) infection remains a major public health concern. The interaction between HBV and the host inflammatory response is an important contributing factor driving liver damage and diseases outcomes. Here, we performed a retrospective analysis employing an adapted molecular degree of perturbation (MDP) score system to assess the overall inflammatory imbalance related to persistent HBV infection. Plasma levels of several cytokines, chemokines, and other inflammatory markers were measured in Brazilian individuals diagnosed with either chronic HBV or previous HBV infection, as well as in uninfected controls between 2006 and 2007. Multidimensional analyses were used to depict and compare the overall expression profile of inflammatory markers between distinct clinical groups. Chronic HBV patients exhibited a marked inflammatory imbalance, characterized by heightened MDP scores and a distinct profile of correlation networks inputting plasma concentrations of the biomarkers, compared with either individuals with previous HBV or controls. Furthermore, in participants with chronic HBV infection, the viral loads in peripheral blood were directly proportional to overall molecular perturbation as well as to specific perturbations of interleukin (IL)-4 and interferon (IFN)-γ concentrations. These findings highlight additional nuances about systemic inflammation related to persistent HBV infection.
Special Issue “Virus-Like Particle Vaccines”
Authors: Vogel Monique , Bachmann Martin F.
Published: August 2020

Virus-like particles (VLPs) have become a key tool for vaccine developers and manufacturers [...]
Immuno-Oncotherapeutic Approaches in Advanced Hepatocellular Carcinoma
Authors: Park Robin , Eshrat Fariha , Al-Jumayli Mohammed , Saeed Azhar , Saeed Anwaar
Published: August 2020

Advanced hepatocellular carcinoma has limited treatment options, but there has been extensive growth recently with cabozantinib, regorafenib, lenvatinib, nivolumab, atezolizumab, and bevacizumab, which are some of the treatments that have received FDA approval just over the last three years. Because HCC tumor microenvironment is potentially immunogenic and typically characterized by inflammation, immunotherapy has been proposed as a potential novel therapeutic approach, which has prompted studies in advanced HCC patients investigating various immune-therapeutic strategies such as CAR-T cell therapy, checkpoint inhibitors, and onco-vaccines. The anti-PD-1 checkpoint inhibitors nivolumab and pembrolizumab have been FDA approved as a second line treatment in patients who progressed or are intolerant to Sorafenib. To build up on the success of PD-1 monotherapy, combinatorial regimens with PD-1/PD-L1 inhibitors plus VEGF targeted agents have shown positive results in various malignancies including HCC. The combination of atezolizumab plus bevacizumab is the new addition to the HCC treatment armamentarium following a pivotal study that demonstrated an improvement in OS over frontline sorafenib. Other novel immune-based approaches and oncolytic viruses are in the early phases of clinical evaluation. These innovative approaches enhance the intensity of cancer-directed immune responses and will potentially impact the outlook of this aggressive disease.
Identification of High-Risk Areas for the Spread of Highly Pathogenic Avian Influenza in Central Luzon, Philippines
Authors: Salvador Roderick , Tanquilut Neil , Na Lampang Kannika , Chaisowwong Warangkhana , Pfeiffer Dirk , Punyapornwithaya Veerasak
Published: August 2020

Highly pathogenic avian influenza virus (HPAIV) is a major problem in the poultry industry. It is highly contagious and is associated with a high mortality rate. The Philippines experienced an outbreak of avian influenza (AI) in 2017. As there is always a risk of re-emergence, efforts to manage disease outbreaks should be optimal. Linked to this is the need for an effective surveillance procedure to capture disease outbreaks at their early stage. Risk-based surveillance is the most effective and economical approach to outbreak management. This study evaluated the potential of commercial poultry farms in Central Luzon to transmit HPAI by calculating their respective reproductive ratios (R0). The reproductive number for each farm is based on the spatial kernel and the infectious period. A risk map has been created based on the calculated R0. There were 882 (76.63%) farms with R0 < 1. Farms with R0 ≥ 1 were all located in Pampanga Province. These farms were concentrated in the towns of San Luis (n = 12) and Candaba (n = 257). This study demonstrates the utility of mapping farm-level R0 estimates for informing HPAI risk management activities.
A New Set of Local Indices Applied to a Water Network through Demand and Pressure Driven Analysis (DDA and PDA)
Authors: Bonora Marco Amos , Caldarola Fabio , Maiolo Mario
Published: August 2020

In the analysis of drinking Water Distribution Networks (WDNs), performance indices are widely used tools for obtaining synthetic information about the WDN operating regime (pressures and flows). This paper presents applications of a series of local surplus indices that act in a new mathematical framework. This framework allows reworking many well-known performance and energetic indices and simultaneously allowing analysis of specific aspects of the WDN. The analyses are carried out using different resolutive hydraulic approaches: the Demand-Driven Analysis (DDA) and the Pressure-Driven Analysis (PDA), typical of software such as EPANET and WaterNetGen. The authors analyse the hypotheses necessary for the application of these models, and how these influence the results of both the hydraulic modeling and the resilience indices assessment. In particular, two resilience indices are reformulated through the new local surplus indices and all of them are then simulated in different conditions for a water network known in literature as the Kang and Lansey WDN. The solving model assumption effects are deepen, reporting graphical and numerical results for different consumption scenarios and the different hydraulic approaches used.
Application of Rehabilitation and Active Pressure Control Strategies for Leakage Reduction in a Case-Study Network
Authors: Bosco Camillo , Campisano Alberto , Modica Carlo , Pezzinga Giuseppe
Published: August 2020

The paper discusses the results of a simulation analysis to evaluate the potential of rehabilitation measures and active pressure control strategies for leakage reduction in a water distribution network (WDN) in southern Italy. The analysis was carried out by using a simulation model developed under the EPANET-MATLAB environment. The model was preliminarily calibrated based on pressure and flow measurements acquired during a field monitoring campaign in two districts of the WDN. Three different scenarios of leakage reduction including (i) pipe rehabilitation (scenario S1), (ii) implementation of pressure local control (S2), and (iii) introduction of remote real-time pressure control (RTC) (S3) were simulated and compared with the current scenario of network operation (S0). Results of the simulations revealed that a combination of the used strategies can improve network performance by a significant reduction of water leakage. Specifically, 16.7%, 35.0%, and 37.5% leakage reductions (as compared to S0) can be obtained under scenarios S1, S2, and S3, respectively.