bluuebunny/crossref_metadata_2025 huggingface dataset:
Tamisolve® NxG as an Alternative Non-Toxic Solvent for the Preparation of Porous Poly (Vinylidene Fluoride) Membranes
Authors: Russo Francesca , Marino Tiziana , Galiano Francesco , Gzara Lassaad , Gordano Amalia , Organji Hussam , Figoli Alberto
Published: August 2021

Tamisolve® NxG, a well-known non-toxic solvent, was used for poly(vinylidene fluoride) (PVDF) membranes preparation via a non-solvent-induced phase separation (NIPS) procedure with water as a coagulation bath. Preliminary investigations, related to the study of the physical/chemical properties of the solvent, the solubility parameters, the gel transition temperature and the viscosity of the polymer–solvent system, confirmed the power of the solvent to solubilize PVDF polymer for membranes preparation. The role of polyvinylpyrrolidone (PVP) and/or poly(ethylene glycol) (PEG), as pore former agents in the dope solution, was studied along with different polymer concentrations (10 wt%, 15 wt% and 18 wt%). The produced membranes were then characterized in terms of morphology, thickness, porosity, contact angle, atomic force microscopy (AFM) and infrared spectroscopy (ATR-FTIR). Pore size measurements, pore size distribution and water permeability (PWP) tests placed the developed membranes in the ultrafiltration (UF) and microfiltration (MF) range. Finally, PVDF membrane performances were investigated in terms of rejection (%) and permeability recovery ratio (PRR) using methylene blue (MB) in water solution to assess their potential application in separation and purification processes.
Racism as Delusion: A Buddhist Perspective
Authors: Loy David R.
Published: August 2021

The powerful novel Ceremony by Leslie Marmon Silko combines several uncomfortable truths from the perspective of a young Native American who has returned home after World War II: the theft of Native American land, the manipulations that set poor whites against poor Indians (among others) and the effects of these lies on the hearts of white people, who tried and still try to fill up their hollowness with money, technology and patriotic war. However, as Silko emphasizes, the lies do not work. Not only have we white folk been fooling ourselves, but we also know that we have been fooling ourselves, and the consequences of our self-deceptions continue to haunt all of us. This essay is an attempt to say more about how that collective delusion functions—in particular, to understand the emptiness that patriotism never quite fills up, the hollowness that wealth and consumerism cannot glut. In order to do this, I will offer a (not “the”) Buddhist perspective, so we begin with some basic Buddhist teachings, which are quite different from the Abrahamic (Jewish, Christian, Muslim) traditions more familiar to most of us.
Integrative 3D Geological Modeling Derived from SWIR Hyperspectral Imaging Techniques and UAV-Based 3D Model for Carbonate Rocks
Authors: Huynh Huy Hoa , Yu Jaehung , Wang Lei , Kim Nam Hoon , Lee Bum Han , Koh Sang-Mo , Cho Sehyun , Pham Trung Hieu
Published: August 2021

This paper demonstrates an integrative 3D model of short-wave infrared (SWIR) hyperspectral mapping and unmanned aerial vehicle (UAV)-based digital elevation model (DEM) for a carbonate rock outcrop including limestone and dolostone in a field condition. The spectral characteristics in the target outcrop showed the limestone well coincided with the reference spectra, while the dolostone did not show clear absorption features compared to the reference spectra, indicating a mixture of clay minerals. The spectral indices based on SWIR hyperspectral images were derived for limestone and dolostone using aluminum hydroxide (AlOH), hydroxide (OH), iron hydroxide (FeOH), magnesium hydroxide (MgOH) and carbonate ion (CO32−) absorption features based on random forest and logistic regression models with an accuracy over 87%. Given that the indices were derived from field data with consideration of commonly occurring geological units, the indices have better applicability for real world cases. The integrative 3D geological model developed by co-registration between hyperspectral map and UAV-based DEM using best matching SIFT descriptor pairs showed the 3D rock formations between limestone and dolostone. Moreover, additional geological information of the outcrop was extracted including thickness, slope, rock classification, strike, and dip.
Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring
Authors: Wang Zhanze , Liu Feifeng , Zeng Tao , Wang Chenghao
Published: August 2021

Global navigation satellite system (GNSS)-based synthetic aperture radar interferometry (InSAR) employs GNSS satellites as transmitters of opportunity and a fixed receiver with two channels, i.e., direct wave and echo, on the ground. The repeat-pass concept is adopted in GNSS-based InSAR to retrieve the deformation of the target area, and it has inherited advantages from the GNSS system, such as a short repeat-pass period and multi-angle retrieval. However, several interferometric phase errors, such as inter-channel and atmospheric errors, are introduced into GNSS-based InSAR, which seriously decreases the accuracy of the retrieved deformation. In this paper, a deformation retrieval algorithm is presented to assess the compensation of the interferometric phase errors in GNSS-based InSAR. Firstly, the topological phase error was eliminated based on accurate digital elevation model (DEM) information from a light detection and ranging (lidar) system. Secondly, the inter-channel phase error was compensated, using direct wave in the echo channel, i.e., a back lobe signal. Finally, by modeling the atmospheric phase, the residual atmospheric phase error was compensated for. This is the first realization of the deformation detection of urban scenes using a GNSS-based system, and the results suggest the effectiveness of the phase error compensation algorithm.
Earth Rotation Parameters Estimation Using GPS and SLR Measurements to Multiple LEO Satellites
Authors: Li Xingxing , Zhang Hongmin , Zhang Keke , Yuan Yongqiang , Zhang Wei , Qin Yujie
Published: August 2021

Earth rotation parameters (ERP) are one of the key parameters in realization of the International Terrestrial Reference Frames (ITRF). At present, the International Laser Ranging Service (ILRS) generates the satellite laser ranging (SLR)-based ERP products only using SLR observations to Laser Geodynamics Satellite (LAGEOS) and Etalon satellites. Apart from these geodetic satellites, many low Earth orbit (LEO) satellites of Earth observation missions are also equipped with laser retroreflector arrays, and produce a large number of SLR observations, which are only used for orbit validation. In this study, we focus on the contribution of multiple LEO satellites to ERP estimation. The SLR and Global Positioning System (GPS) observations of the current seven LEO satellites (Swarm-A/B/C, Gravity Recovery and Climate Experiment (GRACE)-C/D, and Sentinel-3A/B) are used. Several schemes are designed to investigate the impact of LEO orbit improvement, the ERP quality of the single-LEO solutions, and the contribution of multiple LEO combinations. We find that ERP estimation using an ambiguity-fixed orbit can attain a better result than that using ambiguity-float orbit. The introduction of an ambiguity-fixed orbit contributes to an accuracy improvement of 0.5%, 1.1% and 15% for X pole, Y pole and station coordinates, respectively. In the multiple LEO satellite solutions, the quality of ERP and station coordinates can be improved gradually with the increase in the involved LEO satellites. The accuracy of X pole, Y pole and length-of-day (LOD) is improved by 57.5%, 57.6% and 43.8%, respectively, when the LEO number increases from three to seven. Moreover, the combination of multiple LEO satellites is able to weaken the orbit-related signal existing in the single-LEO solution. We also investigate the combination of LEO satellites and LAGEOS satellites in the ERP estimation. Compared to the LAGEOS solution, the combination leads to an accuracy improvement of 0.6445 ms, 0.6288 ms and 0.0276 ms for X pole, Y pole and LOD, respectively. In addition, we explore the feasibility of a one-step method, in which ERP and the orbit parameters are jointly determined, based on SLR and GPS observations, and present a detailed comparison between the one-step solution and two-step solution.
Comparisons of Satellite and Modeled Surface Temperature and Chlorophyll Concentrations in the Baltic Sea with In Situ Data
Authors: Stramska Malgorzata , Konik Marta , Aniskiewicz Paulina , Jakacki Jaromir , Darecki Miroslaw
Published: August 2021

Among the most frequently used satellite data are surface chlorophyll concentration (Chl) and temperature (SST). These data can be degraded in some coastal areas, for example, in the Baltic Sea. Other popular sources of data are reanalysis models. Before satellite or model data can be used effectively, they should be extensively compared with in situ measurements. Herein, we present results of such comparisons. We used SST and Chl from model reanalysis and satellites, and in situ data measured at eight open Baltic Sea stations. The data cover time interval from 1 January 1998 to 31 December 2019, but some satellite data were not always available. Both the model and the satellite SST data had good agreement with in situ measurements. In contrast, satellite and model estimates of Chl concentrations presented large errors. Modeled Chl presented the lowest bias and the best correlation with in situ data from all Chl data sets evaluated. Chl estimates from a regionally tuned algorithm (SatBaltic) had smaller errors in comparison with other satellite data sets and good agreement with in situ data in summer. Statistics were not as good for the full data set. High uncertainties found in chlorophyll satellite algorithms for the Baltic Sea highlight the importance of continuous regional validation of such algorithms with in situ data.
Passive Measurement of Three Optical Beacon Coordinates Using a Simultaneous Method
Authors: Nemecek Jiri , Polasek Martin
Published: August 2021

Among other things, passive methods based on the processing of images of feature points or beacons captured by an image sensor are used to measure the relative position of objects. At least two cameras usually have to be used to obtain the required information, or the cameras are combined with other sensors working on different physical principles. This paper describes the principle of passively measuring three position coordinates of an optical beacon using a simultaneous method and presents the results of corresponding experimental tests. The beacon is represented by an artificial geometric structure, consisting of several semiconductor light sources. The sources are suitably arranged to allow, all from one camera, passive measurement of the distance, two position angles, the azimuth, and the beacon elevation. The mathematical model of this method consists of working equations containing measured coordinates, geometric parameters of the beacon, and geometric parameters of the beacon image captured by the camera. All the results of these experimental tests are presented.
Wearable Feet Pressure Sensor for Human Gait and Falling Diagnosis
Authors: Bucinskas Vytautas , Dzedzickis Andrius , Rozene Juste , Subaciute-Zemaitiene Jurga , Satkauskas Igoris , Uvarovas Valentinas , Bobina Rokas , Morkvenaite-Vilkonciene Inga
Published: August 2021

Human falls pose a serious threat to the person’s health, especially for the elderly and disease-impacted people. Early detection of involuntary human gait change can indicate a forthcoming fall. Therefore, human body fall warning can help avoid falls and their caused injuries for the skeleton and joints. A simple and easy-to-use fall detection system based on gait analysis can be very helpful, especially if sensors of this system are implemented inside the shoes without causing a sensible discomfort for the user. We created a methodology for the fall prediction using three specially designed Velostat®-based wearable feet sensors installed in the shoe lining. Measured pressure distribution of the feet allows the analysis of the gait by evaluating the main parameters: stepping rhythm, size of the step, weight distribution between heel and foot, and timing of the gait phases. The proposed method was evaluated by recording normal gait and simulated abnormal gait of subjects. The obtained results show the efficiency of the proposed method: the accuracy of abnormal gait detection reached up to 94%. In this way, it becomes possible to predict the fall in the early stage or avoid gait discoordination and warn the subject or helping companion person.
Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter
Authors: Rodríguez Antonio J. , Sanjurjo Emilio , Pastorino Roland , Naya Miguel Á.
Published: August 2021

The aim of this work is to explore the suitability of adaptive methods for state estimators based on multibody dynamics, which present severe non-linearities. The performance of a Kalman filter relies on the knowledge of the noise covariance matrices, which are difficult to obtain. This challenge can be overcome by the use of adaptive techniques. Based on an error-extended Kalman filter with force estimation (errorEKF-FE), the adaptive method known as maximum likelihood is adjusted to fulfill the multibody requirements. This new filter is called adaptive error-extended Kalman filter (AerrorEKF-FE). In order to present a general approach, the method is tested on two different mechanisms in a simulation environment. In addition, different sensor configurations are also studied. Results show that, in spite of the maneuver conditions and initial statistics, the AerrorEKF-FE provides estimations with accuracy and robustness. The AerrorEKF-FE proves that adaptive techniques can be applied to multibody-based state estimators, increasing, therefore, their fields of application.
The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning
Authors: Miler Ryszard K. , Kuriata Andrzej , Brzozowska Anna , Akoel Akram , Kalinichenko Antonina
Published: August 2021

Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential equations, and set-theoretic notation, have been used as the main tools. The outcome is a model of a game-based optimization process in a two-element logistics system and an algorithm applied to find optimal steering strategies. The algorithm has been initially verified with the use of simulation based on a Bayesian network (BN) and a structured set of possible strategies (OP/TO) calculated with the use of QGeNie Modeller, finally prepared for Python. It has been proved the algorithm at this stage has no deadlocks and unforeseen loops and is ready to be challenged with the original big set of learning data from a drone-operating company (as the next stage of the planned research).
RETRACTED: A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources
Authors: Syah Rahmad , Khorshidian Mianaei Peyman , Elveny Marischa , Ahmadian Naeim , Ramdan Dadan , Habibifar Reza , Davarpanah Afshin
Published: August 2021

The power system planning problem considering system loss function, voltage profile function, the cost function of FACTS (flexible alternating current transmission system) devices, and stability function are investigated in this paper. With the growth of electronic technologies, FACTS devices have improved stability and more reliable planning in reactive power (RP) planning. In addition, in modern power systems, renewable resources have an inevitable effect on power system planning. Therefore, wind resources make a complicated problem of planning due to conflicting functions and non-linear constraints. This confliction is the stochastic nature of the cost, loss, and voltage functions that cannot be summarized in function. A multi-objective hybrid algorithm is proposed to solve this problem by considering the linear and non-linear constraints that combine particle swarm optimization (PSO) and the virus colony search (VCS). VCS is a new optimization method based on viruses’ search function to destroy host cells and cause the penetration of the best virus into a cell for reproduction. In the proposed model, the PSO is used to enhance local and global search. In addition, the non-dominated sort of the Pareto criterion is used to sort the data. The optimization results on different scenarios reveal that the combined method of the proposed hybrid algorithm can improve the parameters such as convergence time, index of voltage stability, and absolute magnitude of voltage deviation, and this method can reduce the total transmission line losses. In addition, the presence of wind resources has a positive effect on the mentioned issue.
A Systematic Review of Recommender Systems and Their Applications in Cybersecurity
Authors: Pawlicka Aleksandra , Pawlicki Marek , Kozik Rafał , Choraś Ryszard S.
Published: August 2021

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.
Complex Environment Path Planning for Unmanned Aerial Vehicles
Authors: Zhang Jing , Li Jiwu , Yang Hongwei , Feng Xin , Sun Geng
Published: August 2021

Flying safely in complex urban environments is a challenge for unmanned aerial vehicles because path planning in urban environments with many narrow passages and few dynamic flight obstacles is difficult. The path planning problem is decomposed into global path planning and local path adjustment in this paper. First, a branch-selected rapidly-exploring random tree (BS-RRT) algorithm is proposed to solve the global path planning problem in environments with narrow passages. A cyclic pruning algorithm is proposed to shorten the length of the planned path. Second, the GM(1,1) model is improved with optimized background value named RMGM(1,1) to predict the flight path of dynamic obstacles. Herein, the local path adjustment is made by analyzing the prediction results. BS-RRT demonstrated a faster convergence speed and higher stability in narrow passage environments when compared with RRT, RRT-Connect, P-RRT, 1-0 Bg-RRT, and RRT*. In addition, the path planned by BS-RRT through the use of the cyclic pruning algorithm was the shortest. The prediction error of RMGM(1,1) was compared with those of ECGM(1,1), PCGM(1,1), GM(1,1), MGM(1,1), and GDF. The trajectory predicted by RMGM(1,1) was closer to the actual trajectory. Finally, we use the two methods to realize path planning in urban environments.
Intention Prediction and Human Health Condition Detection in Reaching Tasks with Machine Learning Techniques
Authors: Ragni Federica , Archetti Leonardo , Roby-Brami Agnès , Amici Cinzia , Saint-Bauzel Ludovic
Published: August 2021

Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human–robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. Machine learning techniques (MLT) can face the limit of small data amounts, typical of this kind of applications. This paper studies the illustrative case of the reaching movement in 10 healthy subjects and 21 post-stroke patients, comparing the performance of linear discriminant analysis (LDA) and random forest (RF) in: (i) predicting the subject’s intention of moving towards a specific direction among a set of possible choices, (ii) detecting if the subject is moving according to a healthy or pathological pattern, and in the case of discriminating the damage location (left or right hemisphere). Data were captured with wearable electromagnetic sensors, and a sub-section of the acquired signals was required for the analyses. The possibility of detecting with which arm (left or right hand) the motion was performed, and the sensitivity of the MLT to variations in the length of the signal sub-section were also evaluated. LDA and RF prediction accuracies were compared: Accuracy improves when only healthy subjects or longer signals portions are considered up to 11% and at least 10%, respectively. RF reveals better estimation performance both as intention predictor (on average 59.91% versus the 62.19% of LDA), and health condition detector (over 90% in all the tests).
The Effects of Knee Flexion on Tennis Serve Performance of Intermediate Level Tennis Players
Authors: Hornestam Joana Ferreira , Souza Thales Rezende , Magalhães Fabrício Anício , Begon Mickäel , Santos Thiago Ribeiro Teles , Fonseca Sérgio Teixeixa
Published: August 2021

This study aimed to investigate the effects of knee flexion during the preparation phase of a serve on the tennis serve performance, using inertial sensors. Thirty-two junior tennis players were divided into two groups based on their maximum knee flexion during the preparation phase of serve: Smaller (SKF) and Greater (GKF) Knee Flexion. Their racket velocity, racket height, and knee extension velocity were compared during the tennis serve. Inertial sensors tracked participants’ shank, thigh, and racket motions while performing five first, flat, and valid serves. Knee flexion was analysed during the preparation phase of serve, knee extension velocity after this phase, racket velocity just before ball impact, and racket height at impact. Pre-impact racket velocity (mean difference [MD] = 3.33 km/h, p = 0.004) and the knee extension velocity (MD = 130.30 °/s, p = 0.012) were higher in the GKF than SKF; however, racket impact height was not different between groups (p = 0.236). This study’s findings support the importance of larger knee flexion during the preparation phase of serve-to-serve performance. This motion should be seen as a contributor to racket velocity.
Seasonal Snowpack Classification Based on Physical Properties Using Near-Infrared Proximal Hyperspectral Data
Authors: El Oufir Mohamed Karim , Chokmani Karem , El Alem Anas , Agili Hachem , Bernier Monique
Published: August 2021

This paper proposes an innovative method for classifying the physical properties of the seasonal snowpack using near-infrared (NIR) hyperspectral imagery to discriminate the optical classes of snow at different degrees of metamorphosis. This imaging system leads to fast and non-invasive assessment of snow properties. Indeed, the spectral similarity of two samples indicates the similarity of their chemical composition and physical characteristics. This can be used to distinguish, without a priori recognition, between different classes of snow solely based on spectral information. A multivariate data analysis approach was used to validate this hypothesis. A principal component analysis (PCA) was first applied to the NIR spectral data to analyze field data distribution and to select the spectral range to be exploited in the classification. Next, an unsupervised classification was performed on the NIR spectral data to select the number of classes. Finally, a confusion matrix was calculated to evaluate the accuracy of the classification. The results allowed us to distinguish three snow classes of typical shape and size (weakly, moderately, and strongly metamorphosed snow). The evaluation of the proposed approach showed that it is possible to classify snow with a success rate of 85% and a kappa index of 0.75. This illustrates the potential of NIR hyperspectral imagery to distinguish between three snow classes with satisfactory success rates. This work will open new perspectives for the modelling of physical parameters of snow using spectral data.
Surface Plasmonic Sensors: Sensing Mechanism and Recent Applications
Authors: Duan Qilin , Liu Yineng , Chang Shanshan , Chen Huanyang , Chen Jin-hui
Published: August 2021

Surface plasmonic sensors have been widely used in biology, chemistry, and environment monitoring. These sensors exhibit extraordinary sensitivity based on surface plasmon resonance (SPR) or localized surface plasmon resonance (LSPR) effects, and they have found commercial applications. In this review, we present recent progress in the field of surface plasmonic sensors, mainly in the configurations of planar metastructures and optical-fiber waveguides. In the metastructure platform, the optical sensors based on LSPR, hyperbolic dispersion, Fano resonance, and two-dimensional (2D) materials integration are introduced. The optical-fiber sensors integrated with LSPR/SPR structures and 2D materials are summarized. We also introduce the recent advances in quantum plasmonic sensing beyond the classical shot noise limit. The challenges and opportunities in this field are discussed.
Entitlement-Based Access Control for Smart Cities Using Blockchain
Authors: Sabrina Fariza , Jang-Jaccard Julian
Published: August 2021

Smart cities use the Internet of Things (IoT) devices such as connected sensors, lights, and meters to collect and analyze data to improve infrastructure, public utilities, and services. However, the true potential of smart cities cannot be leveraged without addressing many security concerns. In particular, there is a significant challenge for provisioning a reliable access control solution to share IoT data among various users across organizations. We present a novel entitlement-based blockchain-enabled access control architecture that can be used for smart cities (and for any ap-plication domains that require large-scale IoT deployments). Our proposed entitlement-based access control model is flexible as it facilitates a resource owner to safely delegate access rights to any entities beyond the trust boundary of an organization. The detailed design and implementation on Ethereum blockchain along with a qualitative evaluation of the security and access control aspects of the proposed scheme are presented in the paper. The experimental results from private Ethereum test networks demonstrate that our proposal can be easily implemented with low latency. This validates that our proposal is applicable to use in the real world IoT environments.
Mucoadhesion and Mucopenetration of Cannabidiol (CBD)-Loaded Mesoporous Carrier Systems for Buccal Drug Delivery
Authors: Söpper Ulrike , Hoffmann Anja , Daniels Rolf
Published: August 2021

Transmucosal drug delivery represents a promising noninvasive option when drugs are employed which have a low oral bioavailability like CBD. However, this concept can only be successful as long as the formulation provides sufficient buccal retention and mucosal penetration. In this study, mucoadhesive carrier systems were evaluated consisting of CBD-loaded silica (Aeroperl 300) carriers, mucoadhesive polymers (Hypromellose (HPMC), chitosan and carbomer) and propylene glycol as a penetration enhancer. Mucoadhesive effect, drug release and penetration ability were evaluated for each carrier system. The results show that the addition of HPMC and carbomer substantially improve mucoadhesion compared to pure CBD, with an increase of 16-fold and 20-fold, respectively. However, due to their strong swelling, HPMC and carbomer hinder the penetration of CBD and rely on co-administration of propylene glycol as an enhancer to achieve sufficient mucosal absorption. Chitosan, on the other hand, achieves an 8-fold increase in mucoadhesion and enhances the amount of CBD absorbed by three times compared to pure CBD. Thus, chitosan represents a promising polymer to combine both effects. Considering the results, the development of silica-based buccal drug delivery systems is a promising approach for the effective delivery of CBD.
Durability Performance of SCC and SCGC Containing Recycled Concrete Aggregates: A Comparative Study
Authors: Ayub Tehmina , Mahmood Wajeeha , Khan Asad-ur-Rehman
Published: August 2021

This study assesses the behaviour of self-compacting geopolymer concrete (SCGC) with and without recycled concrete aggregates (RCA) by studying the rheological, mechanical and durability properties and comparison with self-compacting concrete (SCC). The idea of using RCA in geopolymer is to attain sustainable development goals, i.e., with less carbon footprint and the use of waste materials such as fly ash and RCA. Two types of concretes were prepared, namely “self-compacting concrete (SCC)” and “self-compacting geopolymer concrete (SCGC)”. Using each concrete type, two design mixes were prepared. The first mix contained 100% natural coarse aggregates (NCA), whereas, in the second mix, 30% NCA were replaced with RCA. The result of rheological properties indicated that the viscosity, passing ability, and segregation results of SCC and SCGC mixes were higher when NCA was partially replaced with RCA. Results of mechanical properties indicated that the increase in the compressive strength of the control mix of SCC (denoted as SCC-0) and SCGC mix (denoted as SCGC-0) at 28 days was 38.3% and 33.1% higher than those containing 30% RCA (denoted as SCC-30 and SCGC-30), respectively. The percentage increase in the compressive strength of SCC-0 and SCC-30 mixes was 20.24% and 13.45% higher compared to SCGC-0 and SCGC-30 mixes. The increase in the split tensile strength of SCC-0 and SCC-30 mixes was 9% and 21.74% higher than SCGC-0 and SCGC-30 mixes. The split tensile strength of control mixes SCC-0 and SCGC-0 is 47.73% and 55% higher than SCC-30 and SCGC-30 at 28 days, respectively. Durability performance of SCC and SCGC mixes was investigated by performing hydraulic permeability, accelerated carbonation, half-cell potential and pull-out tests at 28, 90, 180, 365, and 720 days, and were found inferior for SCGC mixes. The water penetration depth of SCGC-0 and SCGC-30 mixes was 5.71% to 16.1% and 10% to 18.6% higher than SCC-0 and SCC-30 mixes at 28 to 720 days. The carbonation depth in SCGC-0 and SCGC-30 mixes was 8.11% to 20.83% and 7.89% to 13.73% higher than SCC-0 and SCC-30 mixes at 28 to 720 days. The half-cell potential difference results for SCGC-0 and SCGC-30 mixes were 27.5% to 50% and 8.3% to 16.41% higher than SCC-0 and SCC-30 mixes at 28 to 720 days. The pull-out strength of SCC-0 and SCC-30 mixes was 11.36% to 29.5% and 8.3% to 38.97% higher than SCGC-0 and SCGC-30 mixes at 28 to 720 days, respectively. Overall, the mechanical and durability properties of SCC mixes were better than SCGC at the same exposure period.
Evaluating the Effects of the A-Double Vehicle Combinations If Introduced to a Line-Haul Freight Transport Network
Authors: Karam Ahmed , Reinau Kristian Hegner
Published: August 2021

One of the solutions to improve the eco-efficiency of road freight transport is to combine existing transport modules into Longer and/or Heavier Vehicles (LHVs). The scientific and industrial communities have paid increasing attention to an LHV, known as the A-double combination, consisting of a tractor, two 13.5-m semitrailers, and a dolly converter. The present research contributes to the existing literature by developing a methodology based on a cost-benefit approach to quantify the effects of the A-double combinations if introduced to a line-haul transport system. Four implementation scenarios and sensitivity analyses of main variables were evaluated within a case study of 48,472 line-haul trips in Denmark. The results indicate that in the least beneficial scenario, the A-double combinations reduce transport cost by 9.65% while reducing trips, CO2 emissions, and road wear by 17.91%, 5.34%, and 9.55%, respectively. Besides, the use of A-double combinations can significantly reduce empty tractor-semitrailer trips. However, the benefits are relatively less in the case of just-in-time deliveries and cargo constrained by vehicle weight. Also, cost saving is highly sensitive to driver salaries, fuel prices, and driving speeds. This research provides valuable insights into the potentials of A-double combinations under different regulations and freight characteristics from a micro perspective.
From Stakeholder Communication to Engagement for the Sustainable Development Goals (SDGs): A Case Study of LG Electronics
Authors: Jun Hannah , Kim Minseok
Published: August 2021

While multi-stakeholder engagement is critical to achieving the Sustainable Development Goals (SDGs), there is less understanding in the literature about how the private sector can enhance such engagement at an institutional level. In this study, we examine the case of LG Electronics (LGE), one of South Korea’s most sustainable firms. This case study highlights the key strategies that LGE employed in engaging stakeholders for the SDGs, with a focus on stakeholder scope and engagement over three phases: (1) stakeholder communication; (2) stakeholder involvement; and (3) stakeholder engagement. In addition, this paper emphasizes governance mechanisms that facilitated more effective stakeholder engagement, including the company’s Corporate Sustainability Management (CSM) strategies, CSR Committee and Sustainability Management Council. These findings also highlight the usefulness of the common language provided by the SDGs in stakeholder engagement and provide practical implications for the private sector in contributing to the shared global agenda.
Human–Elephant Conflict in Sri Lanka: A Critical Review of Causal Explanations
Authors: Köpke Sören , Withanachchi Sisira S. , Pathiranage Ruwan , Withanachchi Chandana R. , Gamage Deepika U. , Nissanka Thushantha S. , Warapitiya Chinthana C. , Nissanka Banu M. , Ranasinghe Nirangani N. , Senarathna Chathurika D. , Schleyer Christian , Thiel Andreas
Published: August 2021

Human–elephant conflict (HEC) is a severe and much-debated issue in Sri Lanka. An average of two hundred animals are intentionally killed, and seventy to eighty human casualties are counted each year. The Sri Lankan elephant (Elephas maximus maximus) is an endangered subspecies. The reported elephant mortality rates are high. On the other hand, human–elephant conflict also leads to hardship and trauma among rural populations. This research paper reviews causal explanations for HEC in Sri Lanka, tracing underlying narratives and connecting broader conservation theory and practical approaches. The paper discusses potential causes and contexts of HEC in Sri Lanka, including historical factors (i.e., colonial hunting and land-use changes), poaching, habitat loss due to population growth, crop-raiding behaviour, problem animals, and changes in agricultural production systems. The review concludes that socio-economic and cultural factors in HEC in Sri Lanka are poorly explained, and more research should focus on the underlying conditions of rural populations’ vulnerability.
The Structural Relationship among Perceived Service Quality, Perceived Value, and Customer Satisfaction-Focused on Starbucks Reserve Coffee Shops in Shanghai, China
Authors: Ge Yuhan , Yuan Qing , Wang Yaxi , Park Keunsoo
Published: August 2021

In today’s increasingly competitive coffee industry, the point of running a good coffee shop is no longer to run a coffee and beverage shop simply, but to focus on the quality of service and the value that customers feel as a result. Previous studies have mainly discussed the customer satisfaction and behavioral intention of restaurants, while few studies have explored the influencing factors of customer satisfaction and behavioral intention of chain coffee shops. Given that the perceived service quality theory and DINESERV model can effectively predict customer satisfaction and behavioral intention, this study took 385 consumers in the first Starbucks Reserve flagship store in China as survey objects. SmartPLS 3.0 software was used to explore the relationship among respondents’ perceived service quality, customer perceived value, satisfaction, and behavioral intention. The results show that service quality has a partially significant positive effect on perceived value. Perceived service quality and customers’ perceived value both have significant positive effects on satisfaction. Customers’ satisfaction has a significant positive effect on their behavioral intention. These results indicate that enterprises should strengthen the emotional bond between consumers and enterprises and improve the reliability, assurance, and empathy of perceived service quality to create a better emotional resonance between consumers and the Starbucks brand to improve customer satisfaction. At the same time, it should also promote the symbolic perceived value of Chinese consumers to Starbucks to realize the sustainable development of coffee-shop operation and consumer repurchase. This study expands the research on the service quality, perceived value, and behavioral intention of coffee chain enterprises in the context of non-habitual coffee-drinking countries. Moreover, it provides case support for the operation and research of regional cultural consumption habits of international catering chain enterprises.
Sustainable Usage of Freight Drones in City Centers, Proposition of Regulations for Safe Usage of Drones
Authors: Lewandowski Krzysztof
Published: August 2021

This article concentrates on the regulations for the sustainable usage of drones in the central area of cities. This paper does not present the development of freight drones. Here, we do not concentrate on the construction, maneuvering, and steering of one drone or groups of drones, although these aspects are very important for the development of drones. However, the most important usage aspect of drones is the safety conditions. Here, we present a review of the current regulations and also propose beginning a discussion about the technical regulations of the usage of freight drones in this time and after the end of this pandemic for the sustainable usage of them in cities. The regulations are very scattered in the area of the usage of drones. This paper proposes a uniform base of regulations for the usage of drones in city centers.
Sustainable Weed Control in the Agro-Ecosystems
Authors: Radicetti Emanuele , Mancinelli Roberto
Published: August 2021

Worldwide weeds are the cause of the highest potential crop losses (representing on average −34%), even if they are frequently underestimated since more attention is generally paid to dangerous insects (representing on average 18% of yield loss) or pathogens (representing on average 16% of yield loss) [...]
Trends in Corporate Social Responsibility Reporting. The Case of Chinese Listed Companies
Authors: Wu Xiaojuan , Hąbek Patrycja
Published: August 2021

Compared with Western developed countries, corporate social responsibility (CSR) implementation in China started relatively late, but so far, its development has been going on for more than ten years. Therefore, the development process of CSR reporting as a vital tool to reflect the CSR related information of Chinese listed companies is worth studying. It has been asserted in a large amount of literature that the government of a country has an important influence on the development of CSR reporting. Thus, in this paper, we aim to study the trends in CSR reporting practices of Chinese listed companies through statistical analysis methods and then consider the role of the government in it. The results show that the number of CSR reports issued by Chinese listed companies has increased year by year; notably, the number of voluntary CSR disclosure and environmental information disclosure has increased significantly. However, the overall disclosure rate of CSR reports is low and shows no upward trend, the published CSR reports lack third-party certification, and the information disclosure level of most CSR reports is concentrated at a relatively low level. The findings provide some useful references for the future development of Chinese CSR related laws, regulations, and guidelines.
Influence of Thermal Enclosures on Energy Saving Simulations of Residential Building Typologies in European Climatic Zones
Authors: Márquez-Martinón José Miguel , Martín-Dorta Norena , González-Díaz Eduardo , González-Díaz Benjamín
Published: August 2021

Nowadays, the computational simulation of the energy consumption in buildings is a key issue to determine the most proficient configuration between the construction solutions and the necessary equipment, without compromising comfort and accomplishing the legal requirements for each country. The feasible and most profitable solutions can lead to minimizing CO2 emissions and environmental impact. In this work, the internal enclosures influencing the evaluation of energy consumption by energy simulation have been analysed in order to obtain an accurate solution when all the information regarding the internal partitions is not available. The main aim of the present research was to evaluate the role of internal distribution in the simulations of the total building energy consumption. Differences between the results of the energy simulations of buildings that are calculated considering their internal distribution, and those in which only the exterior geometry that makes up the perimeter of the envelope are being described. In this way, it is intended to establish a correction factor based on the building typology and the European climate zone that allows simulation tools to describe the energy reality of a building without knowing its internal distribution.
LED versus HPS Lighting: Effects on Water and Energy Consumption and Yield Quality in Lettuce Greenhouse Production
Authors: Dannehl Dennis , Schwend Thomas , Veit Daniel , Schmidt Uwe
Published: August 2021

High-pressure sodium (HPS) lighting is increasingly replaced by LED lighting in lettuce greenhouse cultivation. In contrast to HPS lighting, LEDs do not heat radiation. Therefore, the leaf temperature is significantly lower under LEDs. This raises the question of whether LED lighting has a positive impact on the reduction in water consumption during lettuce production. In this paper, we investigated this question and found that the water consumption of lettuce produced under LEDs was significantly lower (−15%) than under HPS without loss of yield. We also found that supplementary lighting increases the concentrations of caffeoylquinic acid, dicaffeoyltartaric acid, dicaffeoylquinic acid and that of the total phenolic compounds in lettuce leaves by 61%, 39%, 163% and 38%, respectively. Only the LED fixture was also efficient enough to increase the concentration of caffeoyltartaric acid (+24%). Most of the phenolic compounds showed a very strong positive correlation with the chlorophyll concentration in lettuce, which predominated in the leaves exposed to the LED lighting. Based on these facts, we conclude that by optimizing the light composition, more sustainable plant production, higher concentrations of chlorophyll and some phenolic compounds are possible.
Meta-Analysis and Forest Plots for Sustainability of Heavy Load Carrier Equipment Used in the Industrial Mining Environment
Authors: Chattopadhyaya Somnath , Dinkar Brajeshkumar , Mukhopadhyay Alok , Sharma Shubham , Machado José
Published: August 2021

It is a common recommendation not to attempt a reliability analysis with a small sample size. However, this is feasible after considering certain statistical methods. One such method is meta-analysis, which can be considered to assess the effectiveness of a small sample size by combining data from different studies. The method explores the presence of heterogeneity and the robustness of the fresh large sample size using sensitivity analysis. The present study describes the approach in the reliability estimation of diesel engines and the components of industrial heavy load carrier equipment used in mines for transporting ore. A meta-analysis is carried out on field-based small-sample data for the reliability of different subsystems of the engine. The level of heterogeneity is calculated for each subsystem, which is further verified by constructing a forest plot. The level of heterogeneity was 0 for four subsystems and 2.23% for the air supply subsystem, which is very low. The result of the forest plot shows that all the plotted points mostly lie either on the center line (line of no effect) or very close to it, for all five subsystems. Hence, it was found that the grouping of an extremely small number of failure data is possible. By using this grouped TBF data, reliability analysis could be very easily carried out.
Students’ Perception about Sustainability in the Engineering School of Bilbao (University of the Basque Country): Insertion Level and Importance
Authors: Aginako Zaloa , Guraya Teresa
Published: August 2021

Almost three decades have passed since the Rio declaration, and after numerous initiatives developed to include sustainability in higher education, with the support of Education for Sustainable Development, it is worth wondering at what point is the process of inserting sustainability in university degrees. To clarify this question, engineering students were inquired, at the University of the Basque Country (UPV/EHU), about their perception of the insertion-level of sustainability and the importance they give to it (in environmental, social, and economic dimensions). The novelty of this study lies in the use of a new questionnaire, based on the students’ activity. The instrument was designed ad hoc and was previously validated for this study. The results indicate a low insertion level of sustainability in its three dimensions in three engineering degrees analysed. Nevertheless, the research also shows that the students give great importance to Sustainable Development (SD), either in academic, personal, or professional spheres. The low insertion level of SD and the high interest of students should be considered by the academic institution as an opportunity to deep in its holistic approach to promote the integration of SD in university curricula, not only in engineering degrees.