bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioprintability: Physiomechanical and Biological Requirements of Materials for 3D Bioprinting Processes
Authors: Theus Andrea S. , Ning Liqun , Hwang Boeun , Gil Carmen , Chen Shuai , Wombwell Allison , Mehta Riya , Serpooshan Vahid
Published: October 2020

Three-dimensional (3D) bioprinting is an additive manufacturing process that utilizes various biomaterials that either contain or interact with living cells and biological systems with the goal of fabricating functional tissue or organ mimics, which will be referred to as bioinks. These bioinks are typically hydrogel-based hybrid systems with many specific features and requirements. The characterizing and fine tuning of bioink properties before, during, and after printing are therefore essential in developing reproducible and stable bioprinted constructs. To date, myriad computational methods, mechanical testing, and rheological evaluations have been used to predict, measure, and optimize bioinks properties and their printability, but none are properly standardized. There is a lack of robust universal guidelines in the field for the evaluation and quantification of bioprintability. In this review, we introduced the concept of bioprintability and discussed the significant roles of various physiomechanical and biological processes in bioprinting fidelity. Furthermore, different quantitative and qualitative methodologies used to assess bioprintability will be reviewed, with a focus on the processes related to pre, during, and post printing. Establishing fully characterized, functional bioink solutions would be a big step towards the effective clinical applications of bioprinted products.
Effect of Carbon Fillers on the Wear Resistance of PA6 Thermoplastic Composites
Authors: Myalski Jerzy , Godzierz Marcin , Olesik Piotr
Published: October 2020

In this study, the influence of different carbon fillers on the tribological and manufacturing properties of the thermoplastic polyamide PA6 is presented. The following materials were used as carbon additives: glassy carbon (GC), carbon obtained from the pyrolysis of polymer wastes (BC), and graphene oxide (GO). Fillers were introduced into the PA6 matrix by mechanical stirring in alcohol to settle carbon particles onto the granule surface. Samples were made by injection molding from the produced granules. The microstructure, hardness, and melt flow index (MFI) of the prepared materials were determined. Also, the degree of crystallinity of the samples was examined by Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). The melting point (Tm) was examined using DSC, the results from which allowed the correct heat treatment of PA6 to increase the crystallinity of the obtained material to be selected. The dry sliding tribological behavior of the composites was evaluated via pin-on-block tests against cast iron counterparts. The tests were performed at room temperature, with a sliding speed 0.1 m/s, a sliding distance of 250 m, and a normal force of 40 N. The obtained results revealed that the introduction of GO into the PA6 matrix provides favorable wear behavior, such as the formation of debris that acts as rollers that give a decrease in wear and a lower coefficient of friction. The coefficient of friction in samples with graphene oxide was nearly two times lower than with other samples. However, the ease of manufacture of this material was drastically reduced compared to GC or BC fillers. Microstructural investigations of wear tracks revealed poor adhesion between the polymer matrix and micrograins of carbon fillers (GC and BC), and therefore their influence on tribological properties was less compared to graphene oxide.
Comparing Low-Temperature Hydrothermal Pretreatments through Convective Heating versus Microwave Heating for Napier Grass Digestion
Authors: Saritpongteeraka Kanyarat , Kaewsung Jutawan , Charnnok Boonya , Chaiprapat Sumate
Published: October 2020

This study investigates the effects of convective hydrothermal pretreatment (CHTP) compared to microwave pretreatment (MWP) on the anaerobic digestion of hybrid Napier grass for biomethane production. For rapid estimation of methane yield (YCH4), enzymatic hydrolyzability (EH), whose test lasts only 2 days was used as a surrogate parameter instead of the biochemical methane potential (BMP) assay that normally takes 45–60 days. The relationship between EH and BMP was successfully modeled with satisfactory accuracy (R2 = 0.9810). From CHTP results, quadratic regression characterised by p < 0.0001 and R2 = 0.8364 shows that YCH4 increase was clearly sensitive to detention time at all CHTP temperatures. The maximal YCH4 achieved of 301.5 ± 3.0 mL CH4/gVSadd was 53.2% higher than the control. Then, MWP was employed at various power levels and microwave exposure times. Changes in lignocellulosic structure by Fourier-transform infrared spectroscopy (FTIR) and energy balance demonstrate that MWP caused more damage to plant cells, which proved more effective than CHTP. In the best conditions, approximately 50% of energy was needed for MWP to achieve the equivalent improvement in YCH4. However, CHTP is a more suitable option since waste heat, i.e., from a biogas CHP (combined heat and power) unit, could be used, as opposed to the electricity required for MWP.
Classification, Force Deformation Characteristics and Cooking Kinetics of Common Beans
Authors: Kwofie Ebenezer M. , Mba Ogan I. , Ngadi Michael
Published: October 2020

Post-harvest characteristics of common beans influences its classification, which significantly affects processing time and energy requirements. In this work, ten bean cultivars were classified as either easy-to-cook (ETC) or hard-to-cook (HTC) based on a traditional subjective finger pressing test and a scientific objective hardness test. The hardness study used seed coat rigidity to explain the structural deformation observed during cooking. The result shows that the average hardness of raw dry ETC and HTC beans was 102.4 and 170.8 N, respectively. The maximum seed coat resistance is observed within the first 30 min of cooking regardless of the classification. The results show that a modified three-parameter non-linear regression model could accurately predict the rate of bean softening (R2 = 0.994–0.999 and RMSE = 3.3–14.7%). The influence of bean softeners such as potassium carbonate (K2CO3) and sodium chloride (NaCl) to reduce cooking time was also investigated. The results showed that the addition of K2CO3 to the cooking water significantly reduced the cooking time by up to 50% for ETC and 57% for HTC.
Mutational Analysis of the Binding of Alternative Substrates and Inhibitors to the Active Site of Human Glutathione Transferase P1–1
Authors: Shokeer Abeer , Ismail Aram , Hegazy Usama , Kolm Rüdiger , Mannervik Bengt
Published: October 2020

Glutathione transferases (GSTs) are enzymes that play a critical role in cellular detoxication by catalyzing the nucleophilic attack of glutathione on the electrophilic center of a number of xenobiotic compounds, including many therapeutic drugs. Mutations of amino acid residues in the glutathione-binding site of human glutathione transferase P1–1, namely W39C, K45A, Q52A, Q52K, and Q52E, have been engineered. The recombinant mutant proteins were expressed in Escherichia coli, but only mutants K45A, Q52A, and Q52K showed measurable activity. Steady-state kinetics comparing glutathione with the alternative thiol substrate γ-glutamylcysteine demonstrated the importance of the glycine residue in glutathione for high catalytic efficiency. Inhibition experiments with a set of glutathione analogs structurally related to the therapeutic drugs Telintra and Telcyta enabled determination of binding energies that were contributed by different substituents. The effects of substituting amino acid side chains in the glutathione-binding site of the enzyme on binding the glutathione derivatives and catalysis were evaluated.
Continuous Fixed Bed CO2 Adsorption: Breakthrough, Column Efficiency, Mass Transfer Zone
Authors: Mesfer Mohammed K. Al , Danish Mohd , Khan Mohammed Ilyas , Ali Ismat Hassan , Hasan Mudassir , Jery Atef El
Published: October 2020

The increased levels of carbon dioxide in the environment have incited the search for breakthrough technologies to lessen its impact on climate. The CO2 capture from a mixture of CO2/N2 was studied using a molecular sieve (MS) and silica gel type-III. The breakthrough behavior was predicted as a function of temperature, superficial velocity, and CO2 partial pressure. The breakpoint time reduced significantly with increased temperature and increased superficial velocity. The CO2 adsorption capacity increased appreciably with decreased temperature and increased CO2 pressure. The saturation CO2 adsorption capacity from the CO2/N2 mixture reduced appreciably with increased temperature. The molecular sieve contributed to higher adsorption capacity, and the highest CO2 uptake of 0.665 mmol/g was realized for MS. The smaller width of the mass transfer zone and higher column efficiency of 87.5% for MS signify the efficient use of the adsorbent; this lowers the regeneration cost. The findings suggest that a molecular sieve is suitable for CO2 capture due to high adsorption performance owing to better adsorption characteristic parameters.
Theology of Revolution: In Ali Shari’ati and Walter Benjamin’s Political Thought
Authors: Khanlarzadeh Mina
Published: October 2020

In this paper, I offer a comparative analysis of the political thoughts of twentieth century Iranian revolutionary thinker and sociologist Ali Shari’ati (1933–1977) and German-Jewish philosopher Walter Benjamin (1892–1940). Despite their conspicuously independent historical-theoretical trajectories, both Shari’ati and Benjamin engaged with theology and Marxism to create theological–political conceptions of the revolution of the oppressed. Shari’ati re-interpreted and re-animated Shia history from the angle of contemporary concerns to theorize a revolution against all forms of domination. In comparison, Benjamin fused Marxism with Jewish theology in his call to seize the possibilities of past failed revolutions in the present. Both Shari’ati and Benjamin conceptualized an active messianism led by each generation, eliminating the wait for the return of a messiah. As a result, each present moment takes on a messianic potential; the present plays an essential role to both thinkers. Past was also essential to both, because theology (through remembrance) had made the past sufferings incomplete to them. Both thinkers viewed past sufferings as an integral part of present struggles for justice in the form of remembrance (or yād or zekr for Shari’ati, and Zekher for Benjamin). I explore the ways Shari’ati and Benjamin theorized the role of the past in the present, remembrance, and messianism to create a dialectical relation between theology and Marxism to reciprocally transform and compliment both of them.
Advances in Finger and Partial Hand Prosthetic Mechanisms
Authors: Difonzo Erasmo , Zappatore Giovanni , Mantriota Giacomo , Reina Giulio
Published: October 2020

Approximately 70% of the upper extremity amputations refers to partial hand loss with the involvement of one or more fingers. Historically, this type of limb amputation has been addressed adopting simple opposition designs that use the movement of the residual digit for grasping against a fixed device. Nevertheless, in the last few years, technological advances, and the introduction of modern computer-aided tools for the synthesis and functional design of mechanisms have led to the development of smaller, more robust systems that are constantly improving body-powered and electrically-powered prototypes. This paper surveys cutting-edge solutions proposed in research or available on the market for single finger or partial hand prostheses. First, the main design requirements are outlined. Then, a wide number of prototypes are detailed underlying advantages and drawbacks. The overall goal is to create a solid starting point for the study and development of the next generation of prostheses that can be developed to advance the current state-of-the-art.
Estimation of Winter Wheat Grain Protein Content Based on Multisource Data Assimilation
Authors: Chen Pengfei
Published: October 2020

Data assimilation is a robust method to predict crop biophysical and biochemical parameters. However, no previous study has attempted to predict grain protein content (GPC) at a regional scale using this method. This study explored the feasibility of designing an assimilation model for wheat GPC estimation using remote sensing, a crop growth model, and a priori knowledge. The data included a field experiment and regional sampling data, and Landsat Operational Land Imager images were employed, with the CERES (Crop Environment REsource Synthesis)-Wheat model used as simulation model. To select an optimal method for data assimilation in GPC prediction, different state variable scenarios and cost function solving algorithm scenarios were compared. Additionally, to determine whether a priori information could improve GPC prediction, the collected leaf area index (LAI) and leaf N content sampling data and the range of GPC in the study region were used to constrain the data assimilation process. Furthermore, the data assimilation method was compared to the use of only the CERES-Wheat model. The results showed that GPC could be predicted by remote sensing observation, a crop growth model, and a priori knowledge at regional scale, where the use of data assimilation improved the GPC prediction compared to using only the CERES-Wheat model.
Improving the Classification Accuracy of Annual Crops Using Time Series of Temperature and Vegetation Indices
Authors: Chen Xinran , Zhan Yulin , Liu Yan , Gu Xingfa , Yu Tao , Wang Dakang , Liu Qixin , Zhang Yin , Zhang Yunzhou
Published: October 2020

Accurate cropland classification is important for agricultural monitoring and related decision-making. The commonly used input spectral features for classification cannot be employed to effectively distinguish crops that have similar spectro-temporal features. This study attempted to improve the classification accuracy of crops using both the thermal feature, i.e., the land surface temperature (LST), and the spectral feature, i.e., the normalized difference vegetation index (NDVI), for classification. To amplify the temperature differences between the crops, a temperature index, namely, the modified land surface temperature index (mLSTI) was built using the LST. The mLSTI was calculated by subtracting the average LST of an image from the LST of each pixel. To study the adaptability of the proposed method to different areas, three study areas were selected. A comparison of the classification results obtained using the NDVI time series and NDVI + mLSTI time series showed that for long time series from June to November, the classification accuracy when using the mLSTI and NDVI time series was higher (85.6% for study area 1 in California, 96.3% for area 2 in Kansas, and 91.2% for area 3 in Texas) than that when using the NDVI time series alone (82.0% for area 1, 94.7% for area 2, and 90.9% for area 3); the same was true in most of the cases when using the shorter time series. With the addition of the mLSTI time series, the shorter time series achieved higher classification accuracy, which is beneficial for timely crop identification. The sorghum and soybean crops, which exhibit similar NDVI feature curves in this study, could be better distinguished by adding the mLSTI time series. The results demonstrated that the classification accuracy of crops can be improved by adding mLSTI long time series, particularly for distinguishing crops with similar NDVI characteristics in a given study area.
Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
Authors: Glukhovets Dmitry , Kopelevich Oleg , Yushmanova Anna , Vazyulya Svetlana , Sheberstov Sergey , Karalli Polina , Sahling Inna
Published: October 2020

Our work’s primary goal is to reveal the problematic issues related to estimates of the colored organic matter absorption coefficient in the northern seas from data of the Ocean and Land Color Instrument (OLCI) installed on the Sentinel-3 satellites, e.g., a comparison of the OLCI standard error assessment ADG443_NN_err relating to the measurement and the retrieval of the geophysical products and the uncertainties in the northern seas’ real situation. The natural conditions are incredibly unfavorable there, mainly due to frequent cloudiness and low sun heights. We conducted a comprehensive multi-sensor study of the uncertainties using various approaches. We directly compared the data from satellites (OLCI Sentinel-3 and four other ocean color sensors) and field measurements in five sea expeditions (2016–2019) using the different processing algorithms. Our analysis has shown that the final product’s real uncertainties are significantly (≥100%) higher than the calculated errors of the ADG443_NN_err (~10%). The main reason is the unsatisfactory atmospheric correction. We present the analysis of the various influential factors (satellite sensors, processing algorithms, and other parameters) and formulate future work goals.
RDCPF: A Redundancy-Based Duty-Cycling Pipelined-Forwarding MAC for Linear Sensor Networks
Authors: Zhang Quanwei , Li Dazhong , Fei Yue , Zhang Jiakang , Chen Yu , Tong Fei
Published: October 2020

Existing duty-cycling and pipelined-forwarding (DCPF) protocols applied in battery-powered wireless sensor networks can significantly alleviate the sleep latency issue and save the energy of networks. However, when a DCPF protocol applies to a linear sensor network (LSN), it lacks the ability to handle the bottleneck issue called the energy-hole problem, which is mainly manifested due to the excessive energy consumption of nodes near the sink node. Without overcoming this issue, the lifespan of the network could be greatly reduced. To that end, this paper proposes a method of deploying redundant nodes in LSN, and a corresponding enhanced DCPF protocol called redundancy-based DCPF (RDCPF) to support the new topology of LSN. In RDCPF, the distribution of energy consumption of the whole network becomes much more even. RDCPF also brings improvements to the network in terms of network survival time, packet delivery latency, and energy efficiency, which have been shown through the extensive simulations in comparison with existing DCPF protocols.
Dual Circularly Polarized Planar Four-Port MIMO Antenna with Wide Axial-Ratio Bandwidth
Authors: Kumar Sachin , Lee Gwan Hui , Kim Dong Hwi , Choi Hyun Chul , Kim Kang Wook
Published: October 2020

A broadband compact-sized planar four-port multiple-input–multiple-output (MIMO) antenna with polarization diversity is presented. The proposed dual circularly polarized (CP) MIMO antenna consists of four G-shaped monopole elements, two of which are left-hand CP and the other two are right-hand CP. A vertical line strip in the G-shaped radiating element acts in balancing the vertical and horizontal electric field components to obtain 90° phase difference between them for circular polarization. Also, an I-shaped strip is incorporated between the ground planes of the G-shaped antenna elements to obtain equal voltage level in the proposed MIMO configuration. The dual circular polarization mechanism of the proposed MIMO/diversity antenna is analysed from the vector current distributions. The impedance bandwidth (S11 ≤ –10 dB) of the MIMO antenna is 105.9% (4–13 GHz) and the 3 dB axial ratio bandwidth (ARBW) is 67.7% (4.2–8.5 GHz), which is suitable for C-band applications. The overall size of the MIMO antenna is 70 × 68 × 1.6 mm3, and the minimum isolation between the resonating elements is 18 dB. The envelope correlation coefficient is less than 0.25, and the peak gain within the resonating band is 6.4 dBi.
Satellite-Aided Consensus Protocol for Scalable Blockchains
Authors: Ling Xintong , Gao Zheng , Le Yuwei , You Li , Wang Jiaheng , Ding Zhi , Gao Xiqi
Published: October 2020

In this work, we propose a satellite-aided permissionless consensus protocol for scalable space–terrestrial blockchains. We design its working principle and workflow by taking full advantage of satellites for extensive coverage and ubiquitous connectivity. Based on the proposed protocol, we demonstrate how such a space–terrestrial blockchain grows and evolves through several typical cases in the presence of adversarial nodes, user misbehavior, and transmission outage. Taking proof of work (PoW) as a benchmark, we assess the system security by considering both adversarial miners and possible colluding satellites. Then, we analyze the maximum blockchain throughput under network capacity limits and evaluate the impact of information propagation delay via a Markov model. Simulation results support that the proposed satellite-aided consensus protocol achieves higher throughput and exhibits greater scalability than PoW.
PORF-DDPG: Learning Personalized Autonomous Driving Behavior with Progressively Optimized Reward Function
Authors: Chen Jie , Wu Tao , Shi Meiping , Jiang Wei
Published: October 2020

Autonomous driving with artificial intelligence technology has been viewed as promising for autonomous vehicles hitting the road in the near future. In recent years, considerable progress has been made with Deep Reinforcement Learnings (DRLs) for realizing end-to-end autonomous driving. Still, driving safely and comfortably in real dynamic scenarios with DRL is nontrivial due to the reward functions being typically pre-defined with expertise. This paper proposes a human-in-the-loop DRL algorithm for learning personalized autonomous driving behavior in a progressive learning way. Specifically, a progressively optimized reward function (PORF) learning model is built and integrated into the Deep Deterministic Policy Gradient (DDPG) framework, which is called PORF-DDPG in this paper. PORF consists of two parts: the first part of the PORF is a pre-defined typical reward function on the system state, the second part is modeled as a Deep Neural Network (DNN) for representing driving adjusting intention by the human observer, which is the main contribution of this paper. The DNN-based reward model is progressively learned using the front-view images as the input and via active human supervision and intervention. The proposed approach is potentially useful for driving in dynamic constrained scenarios when dangerous collision events might occur frequently with classic DRLs. The experimental results show that the proposed autonomous driving behavior learning method exhibits online learning capability and environmental adaptability.
Modeling Seasonal Variations in Vertical GPS Coordinate Time Series Using Independent Component Analysis and Varying Coefficient Regression
Authors: Liu Bin , Xing Xuemin , Tan Jianbo , Xia Qing
Published: October 2020

Common seasonal variations in Global Positioning System (GPS) coordinate time series always exist, and the modeling and correction of the seasonal signals are helpful for many geodetic studies using GPS observations. A spatiotemporal model was proposed to model the common seasonal variations in vertical GPS coordinate time series, based on independent component analysis and varying coefficient regression method. In the model, independent component analysis (ICA) is used to separate the common seasonal signals in the vertical GPS coordinate time series. Considering that the periodic signals in GPS coordinate time series change with time, a varying coefficient regression method is used to fit the separated independent components. The spatiotemporal model was then used to fit the vertical GPS coordinate time series of 262 global International GPS Service for Geodynamics (IGS) GPS sites. The results show that compared with least squares regression, the varying coefficient method can achieve a more reliable fitting result for the seasonal variation of the separated independent components. The proposed method can accurately model the common seasonal variations in the vertical GPS coordinate time series, with an average root mean square (RMS) reduction of 41.6% after the model correction.
LiDAR- and AR-Based Monitoring of Evolved Building Façades upon Zoning Conflicts
Authors: Shih Naai-Jung , Chen Yi
Published: October 2020

Zoning conflicts have transformed Old Street fabrics in terms of architectural style and construction material in Lukang, Taiwan. This transformation should be assessed as a contribution to digital cultural sustainability. The objective of this study was to compare the evolved façades resultant from the changes made by the development of architectural history and urban planning. A combination of 3D scan technology and a smartphone augmented reality (AR) app, Augment®, was applied to the situated comparison with direct interaction on-site. The AR application compared 20 façades in the laboratory and 18 façades in four different sites using a flexible interface. The comparisons identified the correlation of evolved façades in real sites in terms of building volumes and components, pedestrian arcades on store fronts, and previous installations. The situated comparisons were facilitated in a field study with real-time adjustments to 3D models and analyses of correlations across details and components. The application of AR was demonstrated to be effective in reinstalling scenes and differentiating diversified compositions of vocabulary in a remote site.
Distributed Dynamic Strain Sensing Based on Brillouin Scattering in Optical Fibers
Authors: Coscetta Agnese , Minardo Aldo , Zeni Luigi
Published: October 2020

Over the past three decades, extensive research activity on Brillouin scattering-based distributed optical fiber sensors has led to the availability of commercial instruments capable of measuring the static temperature/strain distribution over kilometer distances and with high spatial resolution, with applications typically covering structural and environmental monitoring. At the same time, the interest in dynamic measurements has rapidly grown due to the relevant number of applications which could benefit from this technology, including structural analysis for defect identification, vibration detection, railway traffic monitoring, shock events detection, and so on. In this paper, we present an overview of the recent advances in Brillouin-based distributed optical fiber sensors for dynamic sensing. The aspects of the Brillouin scattering process relevant in distributed dynamic measurements are analyzed, and the different techniques are compared in terms of performance and hardware complexity.
UAV Autonomous Tracking and Landing Based on Deep Reinforcement Learning Strategy
Authors: Xie Jingyi , Peng Xiaodong , Wang Haijiao , Niu Wenlong , Zheng Xiao
Published: October 2020

Unmanned aerial vehicle (UAV) autonomous tracking and landing is playing an increasingly important role in military and civil applications. In particular, machine learning has been successfully introduced to robotics-related tasks. A novel UAV autonomous tracking and landing approach based on a deep reinforcement learning strategy is presented in this paper, with the aim of dealing with the UAV motion control problem in an unpredictable and harsh environment. Instead of building a prior model and inferring the landing actions based on heuristic rules, a model-free method based on a partially observable Markov decision process (POMDP) is proposed. In the POMDP model, the UAV automatically learns the landing maneuver by an end-to-end neural network, which combines the Deep Deterministic Policy Gradients (DDPG) algorithm and heuristic rules. A Modular Open Robots Simulation Engine (MORSE)-based reinforcement learning framework is designed and validated with a continuous UAV tracking and landing task on a randomly moving platform in high sensor noise and intermittent measurements. The simulation results show that when the moving platform is moving in different trajectories, the average landing success rate of the proposed algorithm is about 10% higher than that of the Proportional-Integral-Derivative (PID) method. As an indirect result, a state-of-the-art deep reinforcement learning-based UAV control method is validated, where the UAV can learn the optimal strategy of a continuously autonomous landing and perform properly in a simulation environment.
Exclusion and Antisystem Attitudes: The Impact of Perceived Discrimination in Attitudes towards Democracy and the Willingness to Use Violence among Adolescents in Brussels
Authors: Mansoury Babhoutak Elham , Kavadias Dimokritos , Echeverria Vicente Nohemi Jocabeth
Published: October 2020

Perceived discrimination, the perception of systematic exclusion due to background characteristics, has been studied extensively in general. The political consequences of this perception remain underexplored for adolescents. Discrimination may engender a rejection of common political values such as the support for democratic politics. Using the data of 1789 pupils with an average age of 16 years (grade 10) from 24 schools in Brussels, we focus on the consequences of perceived discrimination in attitudes towards violence, as well as on a rejection of representative democracy. The outcomes of a multilevel analysis suggest that high levels of self-reported perceived discrimination are significantly associated with an anti-democratic attitude (rejection of the current form of representative democracy) and the willingness to use violence. In a context in which 75% of pupils have a non-native background, these findings reveal the challenges for future forms of civic education.
Evaluation of the Professional Competence of Kitchen Staff to Avoid Food Waste Using the Modified Delphi Method
Authors: Ko Wen-Hwa , Lu Min-Yen
Published: October 2020

Avoiding food waste has become an important development trend nowadays, and the concept of sustainable cooking is becoming more and more important. How to integrate the concept of surplus food into the catering industry is, in reality, a topic of concern in all walks of life. This study discusses the indicators of professional competence that kitchen staff should have in cooking, from the perspective of surplus food. In this study, literature review, interviews, and the modified Delphi method were used to evaluate the importance of the indicators. After three rounds of the Delphi method analysis by 22 experts, the indicators of the professional culinary competence of kitchen staff, with regard to surplus food, were summarized in the results. The research results showed that there are a total of 58 indicators in professional culinary competence, which are divided into the following four dimensions: 13 items were knowledge competence indicators, 13 items were attitude competence indicators, 23 items were skills competence indicators and 9 items were problem and difficulty indicators. Among them, attitude was the most important indicator, followed by knowledge and skills.
A Quantitative Approach to Characterizing the Changes and Managing Urban Form for Sustaining the Suburb of a Mega-Urban Region: The Case of North Cianjur
Authors: Jatayu Anoraga , Rustiadi Ernan , Pribadi Didit Okta
Published: October 2020

Mega-urban development in Monsoon Asia has a relatively similar pattern, which leads to the formation of Mega-Urban Region (MUR). Such urban development potentially threatens sustainability as it vastly expands to encroaching rural areas. North Cianjur has been experiencing urban expansion from its surrounding metropolitan areas of Jakarta and Bandung that leads to the formation of urban sprawl and many other environmental problems. In this case, spatial characterization based on a quantitative and objective approach is urgently needed to provide better insight into the development of the mega-urban region’s suburb. This study proposed a quantitative and objective approach which was developed based on a quantitative zoning method. This study aims to characterize the region affected by urban expansion and urban form dynamics in North Cianjur using spatial clustering and spatial metrics approaches. The results showed that North Cianjur has four different zones consisting of two urban zones, a peri-urban zone, and a rural zone. Furthermore, the dynamics of urban forms in North Cianjur showed a trend of a more compact form in the urban zones while outside the urban zones it has become more sprawled and dispersed. This implies that spatial planning policies are incapable of containing and managing the massive expansion forces which were coming from Jakarta metropolitan, Bandung metropolitan, as well as Cianjur urban zones itself. Thus, the quantitative zoning method could enhance spatial planning, as different zones of urban–rural typology and urban from in the mega-urban suburb can be defined as a base for developing more specific effort in managing land-use changes. This approach could be adopted by other regions which have similar characteristics.
Reporting of Intellectual Capital Management Using a Scoring Model
Authors: Matos Florinda , Vairinhos Valter , Godina Radu
Published: October 2020

The global transformation of the economy, driven by digital transformation and sustainability challenges, is placing its focus on the evaluation of companies’ intangible assets. Thus, if the report of those intangible assets, namely intellectual capital (IC) management, is endowed with credible metrics, recognized, and accepted, it can work as a guarantee, ensuring the reliability and sustainability of an organization. The aim of this research is to propose a data-driven Intellectual Capital Management Scoring System to be used in the auditing of the IC management of organisations. This paper presents one of the first attempts to use Path Modelling and the Partial Least Squares (PLS) Methodology, combined with Biplots, to define and validate Intellectual Capital Scoring Systems. This system relies on a model estimated using the PLS Path Modelling methodology and uses data from two independent random samples of Portuguese small and medium-sized enterprises (SMEs), which, in turn, was used to obtain two independent model estimates. The results obtained with the mentioned methodology show a good consistency both in performance and very similar parameters estimates, suggesting the validity of the associated scoring function.
A Regional Response to a Global Problem: Single Use Plastics Regulation in the Countries of the Pacific Alliance
Authors: Abril Ortiz Adriana , Sucozhañay Dolores , Vanegas Paul , Martínez-Moscoso Andrés
Published: October 2020

Unsustainable production and consumption patterns of single use plastics are causing worldwide negative environmental and socioeconomic impacts on land-based and marine ecosystems. Nevertheless, in Latin America, plastics governance is still fragmented across borders because of dispersed normative adoption and limited regional coordination. In this context, the instrumental level of articulation between the international principles of environmental law and the formal legal arrangements from the Pacific Alliance countries is assessed to analyze how this strategic platform can contribute to offering a regional response to the global problem of single use plastics. For this purpose, an illustrative case study of the national and subnational regulation developed by the Pacific Alliance and its members was performed. To this end, a framework analysis was conducted on the official legal documents from Mexico, Colombia, Chile, Peru, and Ecuador. The results show extensive and scattered subnational regulation to control the consumption of plastic bags and single use plastics, with diverse policies on extended producer responsibility, educational and economic strategies to influence mainly the consumer’s behaviour. Recommendations are presented in order to improve plastics governance in the region through the legal component.
Characterizing Industrial-Dominated Suburban Formation Using Quantitative Zoning Method: The Case of Bekasi Regency, Indonesia
Authors: Kurnia Adib , Rustiadi Ernan , Pravitasari Andrea
Published: October 2020

Suburbanization of Bekasi Regency as a part of the Jakarta Metropolitan Area (JMA) is mainly induced by urban expansion and industrialization, in which the suburbanization process threatens food security and ultimately disrupts urban sustainability. This study aims to characterize industrial-dominated suburban formation to manage the suburbanization process using a quantitative zoning method. In assessing the characteristics of industrially dominated suburban, this research utilizes the concept of urban–rural development (URD), which consists of five aspects of development (socioeconomic, population, industrial, land-use, and environmental). Factor analysis and Rustiadi’s spatial clustering form regional clusters using all variables while referring to the URD concept. The results showed that there are three regional typologies: (i) urban, (ii) Desakota, and (iii) rural regions. Urban regions are situated in the central and western parts of Bekasi Regency, rural regions are situated in the northern part of Bekasi Regency, while the desakota region is situated between urban and rural regions. Characteristics of each typology then could be used as the basis for development policy in Bekasi Regency which is then constructed towards the protection of agricultural areas in the rural and desakota regions, serving both food security function and strengthening urban sustainability of JMA.
Identifying the Major Construction Wastes in the Building Construction Phase Based on Life Cycle Assessments
Authors: Park Won-Jun , Kim Rakhyun , Roh Seungjun , Ban Hoki
Published: October 2020

The purpose of this study was to identify the major wastes generated during the construction phase using a life cycle assessment. To accomplish this, the amount of waste generated in the construction phase was deduced using the loss rate and weight conversions. Major construction wastes were assessed using six comprehensive environmental impact categories, including global warming potential, abiotic depletion potential, acidification potential, eutrophication potential, ozone depletion potential, and photochemical ozone creation potential. According to the analysis results, five main construction wastes—concrete, rebar, cement, polystyrene panel, and concrete block—comprehensively satisfied the 95% cutoff criteria for all six environmental impact categories. The results of the environmental impact characterization assessment revealed that concrete, concrete block, and cement waste accounted for over 70% of the contribution level in all the environmental impact categories except resource depletion. Insulation materials accounted for 1% of the total waste generated but were identified by the environmental impact assessment to have the highest contribution level.
Conceptualising Design Fixation and Design Limitation and Quantifying Their Impacts on Resource Use and Carbon Emissions
Authors: Wasserbaur Raphael , Sakao Tomohiko
Published: October 2020

Design for sustainability needs to apply a societal perspective. The purpose of this paper is to combine the concept of design fixation with higher levels of analysis. Design fixation is used to describe a blind adherence to known concepts during the design process. It is used mostly at the micro level of design with the focus on the activities of an individual designer or a group of designers. In this paper, design fixation gets conceptually lifted to the levels of the organisation and the institution. We ask how the understanding of design fixation helps to achieve higher resource efficiency. Examples of organisational and institutional design fixations are presented. A System Dynamics model is used to simulate the impacts of design fixation on resource use of a sociotechnical laundry systems. Applying this lens suggests that in order to solve societal design fixations, systemic parameters like infrastructure, business models, or policies need to be considered design parameters. The simulation results show that high-level design fixations can have significant impact on resource use.
Effect of Corrosion in the Transverse Reinforcements in Concrete Beams: Sustainable Method to Generate and Measure Deterioration
Authors: Castro-Borges P. , Juárez-Alvarado C. A. , Soto-Ibarra R. I. , Briceño-Mena J. A. , Miguel G. Fajardo-San , Valdez-Tamez P.
Published: October 2020

A consistent method to generate and measure deterioration by corrosion in transverse reinforcements for concrete beams is presented and discussed in this work. This approach could be applied in other circumstances, such as bending, compression or combinations of stresses, with comparable results and therefore can be used to ensure sustainability. In marine environments, macro-cells are produced primarily from a transverse reinforcement, which works as an anode and therefore becomes a critical part of the structural analysis. To evaluate the adaptation efficiency of our proposed method, the corrosion potential, mass losses and cross-section reductions of the steel were measured. The shear stress behavior of the beams was investigated, including beam responses to load deformations, failure modes and cracking. The method ensured that all the beams exhibited a shear failure from diagonal stress with almost 50% less deflection when mechanically tested. The critical cross-sectional area, calculated according to the experimental diameter with the greatest cross-sectional loss due to the corrosion of the deteriorated stirrup, proved to be a reliable value for predicting the ultimate shear strength of concrete beams deteriorated by severe corrosion. A reduction of up to 30% in the shear strength of deteriorated versus non-deteriorated beams was found. Additional results showed that there is a correlation between the experimental and theoretical results and that the method is reproducible.
Development of Concrete Mixture Design Process Using MCDM Approach for Sustainable Concrete Quality Management
Authors: Ahmed Mohd. , Mallick Javed , AlQadhi Saeed , Ben Kahla Nabil
Published: October 2020

The development of a concrete mixture design process for high-quality concrete production with sustainable values is a complex process because of the multiple required properties at the green/hardened state of concrete and the interdependency of concrete mixture parameters. A new multicriteria decision making (MCDM) technique based on Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methodology is applied to a fuzzy setting for the selection of concrete mix factors and concrete mixture design methods with the aim towards sustainable concrete quality management. Three objective properties for sustainable quality concrete are adopted as criteria in the proposed MCDM model. The seven most dominant concrete mixture parameters with consideration to sustainable concrete quality issues, i.e., environmental (density, durability) and socioeconomic criteria (cost, optimum mixture ingredients ratios), are proposed as sub-criteria. Three mixture design techniques that have potentiality to include sustainable aspects in their design procedure, two advanced and one conventional concrete mixture design method, are taken as alternatives in the MCDM model. The proposed selection support framework may be utilized in updating concrete design methods for sustainability and in deciding the most dominant concrete mix factors that can provide sustainable quality management in concrete production as well as in concrete construction. The concrete mix factors found to be most influential to produce sustainable concrete quality include the water/cement ratio and density. The outcomes of the proposed MCDM model of fuzzy TOPSIS are consistent with the published literature and theory. The DOE method was found to be more suitable in sustainable concrete quality management considering its applicable objective quality properties and concrete mix factors.
Open Innovation 4.0 as an Enhancer of Sustainable Innovation Ecosystems
Authors: Costa Joana , Matias João C.O.
Published: October 2020

Innovation matters. Business success increasingly depends upon sustainable innovation. Observing recent innovation best practices, the emergence of a new paradigm is traceable. Creating an innovative ecosystem has a multilayer effect: It contributes to regional digitalization, technological start-up emergence, open innovation promotion, and new policy enhancement retro-feeding the system. Public policy must create open innovation environments accordingly with the quintuple helix harmonizing the ecosystem to internalize emerging spillovers. The public sector should enhance the process, providing accurate legal framework, procurement of innovation, and shared risks in R&D. Opening the locks that confine the trunks of community, academic, industry, and government innovation will harness each dimension exploiting collective and collaborative potential of individuals towards a brighter sustainable future. In this sense, the aim of this study is to present how open innovation can enhance sustainable innovation ecosystems and boost the digital transition. For that, firstly, a diachronic perspective of the sustainable innovation ecosystem is traced, its connection to open innovation, and identification of the university linkages. Secondly, database exploration and econometric estimations are performed. Then, we will ascertain how far open innovation frameworks and in particular the knowledge flows unveiled by the university promote smart and responsible innovation cycles. Lastly, we will propose a policy package towards green governance, empowering the university in governance distributed ecosystem, embedded in the community, self-sustained with shared gains, and a meaningful sense of identity.
Augmented Reality as a Sustainable Technology to Improve Academic Achievement in Students with and without Special Educational Needs
Authors: Badilla-Quintana María Graciela , Sepulveda-Valenzuela Eileen , Salazar Arias Margarita
Published: October 2020

Virtual reality has impacted education, where progressively more educational institutionsconsider its inclusion. The research problem derives from the need to study the educational possibilitiesprovided by integrating augmented reality into the curriculum, and its effect on academic achievement ina diverse class, specifically in the chemistry subject. This study examines 60 school-age participants withandwithout special educational needs, and addresses three overarching questions: (a)Would integratingaugmented reality (AR) technology result in better academic achievement? (b)Would knowledge beretained longer by using AR? (c) Is there any relationship between academic achievement, acceptanceand motivation regarding the use of this technology? Embracing the socio-constructivist theory oflearning and collaborative and immersive learning as a framework, this study was carried out usinga quantitative approach and a pre-experimental design. The AR VR Molecules Editor applicationwas used in chemistry lessons. Main results showed significant immediate academic achievementand content retention. Despite classroom diversity, immersive technologies enhance students’ learningregardless of whether they have special educational needs (SEN) or not. They also acknowledge that ARis a suitable sustainable technology that may foster social and cognitive justice and inclusive education,and train students that are equally prepared for the dynamic future.