bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of a Highly Efficient Wideband Multi-Frequency Ambient RF Energy Harvester
Authors: Roy Sunanda , Tiang Jun-Jiat , Roslee Mardeni Bin , Ahmed Md. Tanvir , Kouzani Abbas Z. , Mahmud M. A. Parvez
Published: January 2022

For low input radio frequency (RF) power from −35 to 5 dBm, a novel quad-band RF energy harvester (RFEH) with an improved impedance matching network (IMN) is proposed to overcome the poor conversion efficiency and limited RF power range of the ambient environment. In this research, an RF spectral survey was performed in the semi-urban region of Malaysia, and using these results, a multi-frequency highly sensitive RF energy harvester was designed to harvest energy from available frequency bands within the 0.8 GHz to 2.6 GHz frequency range. Firstly, a new IMN is implemented to improve the rectifying circuit’s efficiency in ambient conditions. Secondly, a self-complementary log-periodic higher bandwidth antenna is proposed. Finally, the design and manufacture of the proposed RF harvester’s prototype are carried out and tested to realize its output in the desired frequency bands. For an accumulative −15 dBm input RF power that is uniformly universal across the four radio frequency bands, the harvester’s calculated dc rectification efficiency is about 35 percent and reaches 52 percent at −20 dBm. Measurement in an ambient RF setting shows that the proposed harvester is able to harvest dc energy at −20 dBm up to 0.678 V.
Commercial and Scientific Solutions for Blood Glucose Monitoring—A Review
Authors: Xue Yirui , Thalmayer Angelika S. , Zeising Samuel , Fischer Georg , Lübke Maximilian
Published: January 2022

Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.
Automated Aircraft Dent Inspection via a Modified Fourier Transform Profilometry Algorithm
Authors: Lafiosca Pasquale , Fan Ip-Shing , Avdelidis Nicolas P.
Published: January 2022

The search for dents is a consistent part of the aircraft inspection workload. The engineer is required to find, measure, and report each dent over the aircraft skin. This process is not only hazardous, but also extremely subject to human factors and environmental conditions. This study discusses the feasibility of automated dent scanning via a single-shot triangular stereo Fourier transform algorithm, designed to be compatible with the use of an unmanned aerial vehicle. The original algorithm is modified introducing two main contributions. First, the automatic estimation of the pass-band filter removes the user interaction in the phase filtering process. Secondly, the employment of a virtual reference plane reduces unwrapping errors, leading to improved accuracy independently of the chosen unwrapping algorithm. Static experiments reached a mean absolute error of ∼0.1 mm at a distance of 60 cm, while dynamic experiments showed ∼0.3 mm at a distance of 120 cm. On average, the mean absolute error decreased by ∼34%, proving the validity of the proposed single-shot 3D reconstruction algorithm and suggesting its applicability for future automated dent inspections.
Payload Identification and Gravity/Inertial Compensation for Six-Dimensional Force/Torque Sensor with a Fast and Robust Trajectory Design Approach
Authors: Duan Jinjun , Liu Zhouchi , Bin Yiming , Cui Kunkun , Dai Zhendong
Published: January 2022

In the robot contact operation, the robot relies on the multi-dimensional force/torque sensor installed at the end to sense the external contact force. When the effective load and speed of the robot are large, the gravity/inertial force generated by it will have a non-negligible impact on the output of the force sensor, which will seriously affect the accuracy and effect of the force control. The existing identification algorithm time is often longer, which also affects the efficiency of force control operations. In this paper, a self-developed multi-dimensional force sensor with integrated gravity/inertial force sensing function is used to directly measure the resultant force. Further, a method for the rapid identification of payload based on excitation trajectory is proposed. Firstly, both a gravity compensation algorithm and an inertial force compensation algorithm are introduced. Secondly, the optimal spatial recognition pose based on the excitation trajectory was designed, and the excitation trajectory of each joint is represented by a finite Fourier series. The least square method is used to calculate the identification parameters of the load, the gravity, and inertial force. Finally, the experiment was verified on the robot. The experimental results show that the algorithm can quickly identify the payload, and it is faster and more accurate than other algorithms.
Fuzzy Risk-Based Maintenance Strategy with Safety Considerations for the Mining Industry
Authors: Tubis Agnieszka , Werbińska-Wojciechowska Sylwia , Sliwinski Pawel , Zimroz Radoslaw
Published: January 2022

Enterprises today are increasingly seeking maintenance management strategies to ensure that their machines run faultlessly. This problem is particularly relevant in the mining sector, due to the demanding working conditions of underground mines and machines and equipment-operating regimes. Therefore, in this article, the authors proposed a new approach to mining machinery maintenance management, based on the concept of risk-based maintenance (RBM) and taking into account safety issues. The proposed method includes five levels of analysis, of which the first level focuses on hazard analysis, while the next three are connected with a risk evaluation. The final level relates to determining the RBM recommendations. The recommendations are defined in relation to the three main improvement areas: maintenance, safety, and resource availability/allocation. The proposed approach is based on the use of fuzzy logic. To present the possibilities of implementing our method, a case study covering the operation of selected mining machinery in a selected Polish underground mine is presented. In the case of mining machinery, fourteen adverse-event scenarios were identified and investigated; general recommendations were also given. The authors have also indicated further directions of research work to optimize system maintenance strategies, based on the concept of risk-based maintenance. Additionally, the discussion about the implementation possibilities of the approach developed herein is provided.
Pressure Sensor Placement for Leak Localization in Water Distribution Networks Using Information Theory
Authors: Santos-Ruiz Ildeberto , López-Estrada Francisco-Ronay , Puig Vicenç , Valencia-Palomo Guillermo , Hernández Héctor-Ricardo
Published: January 2022

This paper presents a method for optimal pressure sensor placement in water distribution networks using information theory. The criterion for selecting the network nodes where to place the pressure sensors was that they provide the most useful information for locating leaks in the network. Considering that the node pressures measured by the sensors can be correlated (mutual information), a subset of sensor nodes in the network was chosen. The relevance of information was maximized, and information redundancy was minimized simultaneously. The selection of the nodes where to place the sensors was performed on datasets of pressure changes caused by multiple leak scenarios, which were synthetically generated by simulation using the EPANET software application. In order to select the optimal subset of nodes, the candidate nodes were ranked using a heuristic algorithm with quadratic computational cost, which made it time-efficient compared to other sensor placement algorithms. The sensor placement algorithm was implemented in MATLAB and tested on the Hanoi network. It was verified by exhaustive analysis that the selected nodes were the best combination to place the sensors and detect leaks.
A Simple Method for the Detection of Biofilms Using a Heatable Capacitive Sensor Structure (CSS): Description, Proof of Concept, and Some Technical Improvements
Authors: Zirk Kai-Uwe , Olze Manuel , Pötzschke Harald
Published: January 2022

This article presents a novel method for the detection of biofilms based on a heatable, capacitive sensor structure (CSS). Biofilms are capable of strongly binding large amounts of water to their extracellular biopolymer matrix, which is detectable via its dielectric properties. A main challenge is to determine the difference between the inherent occurring presence of moisture in the ecosystem, which is necessary to form a biofilm and an actual formed biofilm. Therefore, the CSS is carefully heated to evaporate unbound surface moisture and determine whether there is a remaining residual alternation of the capacitance in comparison to the dry state. As a reproduceable substitute for complex, real biofilms, a hygroscopic, medical hydrogel-based on polysaccharides was used and applied by spray coating. Printed circuit boards (PCB) in different geometries and materials were used as CSS and compared in terms of their performance. A layer-thickness of 20 µm for the hydrogel coating to be sufficiently detected was defined as a realistic condition based on known values for real biofilms cited in literature. For this thickness a double-meander structure proves to be preferable over interdigitating and spiral geometries. It does offer a 30% lower, yet sufficient sensitivity, but shows advantages in manufacturing (one layer instead of two) and conductive heating capability. In the experiments, free water showed virtually no residual change, while the hydrogel-coated CSS still shows an approx. 300% higher value compared to a dry capacity. Yet, the overall small capacities of about 6–30 pF in dry state are difficult to measure and therefore sensitive to interferences and noise, which results in a high deviation. The principle of measurement can be evaluated as proofed by the carried out experiments, though offering room for improvement in the design of the study. The new method might be especially useful for pipes (e.g., hydrodynamically ineffective sensors installed in a pipe wall) if they at least are not permanently flooded with an aqueous medium, but can occasionally dry. If the internal surface is still only moist, it can be dried by initial heating.
Light Scattering by a Subwavelength Plasmonic Array: Anisotropic Model
Authors: Nemykin Anton , Frumin Leonid , Shapiro David
Published: January 2022

We calculate the light transmission by a subwavelength plasmonic array using the boundary element method for parallel cylinders with different cross-sections: circular or elliptic with axis ratio 4:1. We demonstrate that plasmonic resonance is sharper for the case of horizontal ellipses. This structure is susceptible to refractive index variations in the media since the high derivatives of reflection and transmission coefficients are near the angle of total internal reflection. To obtain an approximate analytical expression, we used the model of a metallic layer. We explore the “sandwich” structure with an anisotropic film between two dielectrics and demonstrate its quantitative agreement with numerical results.
Federated Learning in Edge Computing: A Systematic Survey
Authors: Abreha Haftay Gebreslasie , Hayajneh Mohammad , Serhani Mohamed Adel
Published: January 2022

Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services closer to data sources. EC combined with Deep Learning (DL) is a promising technology and is widely used in several applications. However, in conventional DL architectures with EC enabled, data producers must frequently send and share data with third parties, edge or cloud servers, to train their models. This architecture is often impractical due to the high bandwidth requirements, legalization, and privacy vulnerabilities. The Federated Learning (FL) concept has recently emerged as a promising solution for mitigating the problems of unwanted bandwidth loss, data privacy, and legalization. FL can co-train models across distributed clients, such as mobile phones, automobiles, hospitals, and more, through a centralized server, while maintaining data localization. FL can therefore be viewed as a stimulating factor in the EC paradigm as it enables collaborative learning and model optimization. Although the existing surveys have taken into account applications of FL in EC environments, there has not been any systematic survey discussing FL implementation and challenges in the EC paradigm. This paper aims to provide a systematic survey of the literature on the implementation of FL in EC environments with a taxonomy to identify advanced solutions and other open problems. In this survey, we review the fundamentals of EC and FL, then we review the existing related works in FL in EC. Furthermore, we describe the protocols, architecture, framework, and hardware requirements for FL implementation in the EC environment. Moreover, we discuss the applications, challenges, and related existing solutions in the edge FL. Finally, we detail two relevant case studies of applying FL in EC, and we identify open issues and potential directions for future research. We believe this survey will help researchers better understand the connection between FL and EC enabling technologies and concepts.
Learning Damage Representations with Sequence-to-Sequence Models
Authors: Yang Qun , Shen Dejian
Published: January 2022

Natural hazards have caused damages to structures and economic losses worldwide. Post-hazard responses require accurate and fast damage detection and assessment. In many studies, the development of data-driven damage detection within the research community of structural health monitoring has emerged due to the advances in deep learning models. Most data-driven models for damage detection focus on classifying different damage states and hence damage states cannot be effectively quantified. To address such a deficiency in data-driven damage detection, we propose a sequence-to-sequence (Seq2Seq) model to quantify a probability of damage. The model was trained to learn damage representations with only undamaged signals and then quantify the probability of damage by feeding damaged signals into models. We tested the validity of our proposed Seq2Seq model with a signal dataset which was collected from a two-story timber building subjected to shake table tests. Our results show that our Seq2Seq model has a strong capability of distinguishing damage representations and quantifying the probability of damage in terms of highlighting the regions of interest.
A Deep Learning Framework for Automatic Meal Detection and Estimation in Artificial Pancreas Systems
Authors: Daniels John , Herrero Pau , Georgiou Pantelis
Published: January 2022

Current artificial pancreas (AP) systems are hybrid closed-loop systems that require manual meal announcements to manage postprandial glucose control effectively. This poses a cognitive burden and challenge to users with T1D since this relies on frequent user engagement to maintain tight glucose control. In order to move towards fully automated closed-loop glucose control, we propose an algorithm based on a deep learning framework that performs multitask quantile regression, for both meal detection and carbohydrate estimation. Our proposed method is evaluated in silico on 10 adult subjects from the UVa/Padova simulator with a Bio-inspired Artificial Pancreas (BiAP) control algorithm over a 2 month period. Three different configurations of the AP are evaluated -BiAP without meal announcement (BiAP-NMA), BiAP with meal announcement (BiAP-MA), and BiAP with meal detection (BiAP-MD). We present results showing an improvement of BiAP-MD over BiAP-NMA, demonstrating 144.5 ± 6.8 mg/dL mean blood glucose level (−4.4 mg/dL, p< 0.01) and 77.8 ± 6.3% mean time between 70 and 180 mg/dL (+3.9%, p< 0.001). This improvement in control is realised without a significant increase in mean in hypoglycaemia (+0.1%, p= 0.4). In terms of detection of meals and snacks, the proposed method on average achieves 93% precision and 76% recall with a detection delay time of 38 ± 15 min (92% precision, 92% recall, and 37 min detection time for meals only). Furthermore, BiAP-MD handles hypoglycaemia better than BiAP-MA based on CVGA assessment with fewer control errors (10% vs. 20%). This study suggests that multitask quantile regression can improve the capability of AP systems for postprandial glucose control without increasing hypoglycaemia.
Event Visualization and Trajectory Tracking of the Load Carried by Rotary Crane
Authors: Cekus Dawid , Depta Filip , Kubanek Mariusz , Kuczyński Łukasz , Kwiatoń Paweł
Published: January 2022

Tracking the trajectory of the load carried by the rotary crane is an important problem that allows reducing the possibility of its damage by hitting an obstacle in its working area. On the basis of the trajectory, it is also possible to determine an appropriate control system that would allow for the safe transport of the load. This work concerns research on the load motion carried by a rotary crane. For this purpose, the laboratory crane model was designed in Solidworks software, and numerical simulations were made using the Motion module. The developed laboratory model is a scaled equivalent of the real Liebherr LTM 1020 object. The crane control included two movements: changing the inclination angle of the crane’s boom and rotation of the jib with the platform. On the basis of the developed model, a test stand was built, which allowed for the verification of numerical results. Event visualization and trajectory tracking were made using a dynamic vision sensor (DVS) and the Tracker program. Based on the obtained experimental results, the developed numerical model was verified. The proposed trajectory tracking method can be used to develop a control system to prevent collisions during the crane’s duty cycle.
Acoustic Forward Model for Guided Wave Propagation and Scattering in a Pipe Bend
Authors: Rasgado-Moreno Carlos-Omar , Rist Marek , Land Raul , Ratassepp Madis
Published: January 2022

The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive method that enables the monitoring of a whole bend area by processing the waves excited and received by transducer arrays. The main challenge associated with the tomography of the bend is the development of an appropriate forward model, which should simply and efficiently handle the wave propagation in a complex bend model. In this study, we developed a two-dimensional (2D) acoustic forward model to replace the complex three-dimensional (3D) bend domain with a rectangular domain that is made artificially anisotropic by using Thomsen parameters. Thomsen parameters allow the consideration of the directional dependence of the velocity of the wave in the model. Good agreement was found between predictions and experiments performed on a 220 mm diameter (d) pipe with 1.5d bend radius, including the wave-field focusing effect and the steering effect of scattered wave-fields from defects.
Multi-Criteria Evaluation of Site Selection for Smart Community Demonstration Projects
Authors: Sung Ming-Shiu , Shih Shen-Guan , Perng Yeng-Horng
Published: January 2022

Definition and imagination of an ideal city can be traced back to the origin of garden city in UK about 100 years ago. Since then, many different names and topics have been proposed and smart city is the one most recently proposed. Starting from 2000, more and more countries have developed various demonstration projects for the promotion of smart city in order to provide total solution for the promotion of sustainable development and social welfare. In fact, some of them have been successfully carried out. Some researchers in Taiwan argue that the current mechanism by which government subsidies are allocated for smart city demonstration projects warrants improvement. A comprehensive literature review determined that the development potential of smart cities should be prioritized in site selection for such demonstration projects. This study developed an evaluation framework on the basis of multi-criteria evaluation methods to enable the identification of suitable smart city demonstration sites. Evaluation criteria were first identified through the Delphi method. Next, the weights of each criterion were derived through the analytic hierarchy process. Furthermore, the capability of the proposed evaluation model was determined through simulation testing. Four demonstration sites are simulated, they are: Taipower Smart Community, Yinlin Technology University campus, Taichung Creative Cultural Park, and Asian New Bay Area in Kaohsiung, It is expected that the research findings in this thesis can be helpful to the future decision for the demo site selection of smart city.
Changes in Body Composition and Strength after 12 Weeks of High-Intensity Functional Training with Two Different Loads in Physically Active Men and Women: A Randomized Controlled Study
Authors: Kapsis Daniel P. , Tsoukos Athanasios , Psarraki Maria P. , Douda Helen T. , Smilios Ilias , Bogdanis Gregory C.
Published: January 2022

This study examined the effects of two different resistance loads during high-intensity Functional Training (HIFT) on body composition and maximal strength. Thirty-one healthy young individuals were randomly assigned into three groups: moderate load (ML: 70% 1-RM), low load-(LL: 30% 1-RM), and control (CON). Each experimental group performed HIFT three times per week for 12 weeks with a similar total volume load. Body fat decreased equally in both experimental groups after 6 weeks of training (p < 0.001), but at the end of training it further decreased only in LL compared to ML (−3.19 ± 1.59 vs. −1.64 ± 1.44 kg, p < 0.001), with no change in CON (0.29 ± 1.08 kg, p = 0.998). Lean body mass (LBM) increased after 6 weeks of training (p = 0.019) in ML only, while after 12 weeks a similar increase was observed in LL and ML (1.11 ± 0.65 vs. ML: 1.25 ± 1.59 kg, p = 0.034 and 0.013, respectively), with no change in CON (0.34 ± 0.67 kg, p = 0.991). Maximal strength increased similarly in four out of five exercises for both experimental groups by between 9.5% and 16.9% (p < 0.01) at the end of training, with no change in CON (−0.6 to 4.9%, p > 0.465). In conclusion, twelve weeks of HIFT training with either low or moderate resistance and equal volume load resulted in an equal increase in LBM and maximal strength, but different fat loss.
Can Popular High-Intensity Interval Training (HIIT) Models Lead to Impossible Training Sessions?
Authors: Briand Jérémy , Tremblay Jonathan , Thibault Guy
Published: January 2022

High-Intensity Interval Training (HIIT) is a time-efficient training method suggested to improve health and fitness for the clinical population, healthy subjects, and athletes. Many parameters can impact the difficulty of HIIT sessions. This study aims to highlight and explain, through logical deductions, some limitations of the Skiba and Coggan models, widely used to prescribe HIIT sessions in cycling. We simulated 6198 different HIIT training sessions leading to exhaustion, according to the Skiba and Coggan-Modified (modification of the Coggan model with the introduction of an exhaustion criterion) models, for three fictitious athlete profiles (Time-Trialist, All-Rounder, Sprinter). The simulation revealed impossible sessions (i.e., requiring athletes to surpass their maximal power output over the exercise interval duration), characterized by a few short exercise intervals, performed in the severe and extreme intensity domains, alternating with long recovery bouts. The fraction of impossible sessions depends on the athlete profile and ranges between 4.4 and 22.9% for the Skiba model and 0.6 and 3.2% for the Coggan-Modified model. For practitioners using these HIIT models, this study highlights the importance of understanding these models’ inherent limitations and mathematical assumptions to draw adequate conclusions from their use to prescribe HIIT sessions.
Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making
Authors: Xiong Luchang , Zhang Zhaoyang , Wan Zhijun , Zhang Yuan , Wang Ziqi , Lv Jiakun
Published: January 2022

As a solid waste produced by coal combustion, fly ash will cause serious environmental pollution. However, it can be considered as a sustainable and renewable resource to replace partial cement in grouting materials. Fly ash grouting materials re-cement the broken rock mass and improve the mechanical properties of the original structure. It can reinforce the broken surrounding rock of mine roadway. The utilization of fly ash also reduces environmental pollution. Therefore, this paper establishes a new material mixture ratio optimization model to meet the requirement of material property through combining the methods of experimental design and numerical analysis. Based on the Box–Behnken design with 3 factors and 3 levels, a mathematical model is constructed to fit the nonlinear multiple regression functions between material properties and raw materials ratios. The influence of raw materials is analyzed on material properties (the material’s 7-day uniaxial compressive strength, initial setting time, and slurry viscosity). Then, 80 Pareto solutions are obtained through NASG-II algorithm which takes the regression functions as the objective functions for multi-objective optimization of the grouting material ratio. Finally, the best ratio solution of water-cement ratio—0.71, silica fume content—1.73%, and sodium silicate content—2.61% is obtained through the NNRP-TOPSIS method.
How to Develop Moral Skills in Sport by Using the Corruption Heritage?
Authors: Constantin Pompiliu-Nicolae , Stanescu Rares , Pelin Florin , Stoicescu Marius , Stanescu Monica , Barkoukis Vassilis , Naidenova Kornelia , Yordanova Vania , Gomez Carole , Vershuuren Pim
Published: January 2022

This paper examines how the corruption heritage of South-Eastern European sport can be used as content for educational strategies designed to improve the ethics and integrity in today’s sport. Hidden or dark history is useful when considering an education for a sustainable development approach to improving athletes’ moral skills. In education, examining mistakes can be a useful tool for preventing their recurrence as they provide examples for study and content for evidence-based learning. At the same time, it is a useful process, aiming to develop critical thinking and the decision-making skills in the area of sports. This paper provides examples on how narratives can be used in the field of sport moral education and what patterns reflecting the lack of integrity in sport can be identified. Because it has perpetuated and altered the image and principles of sports competition, diminishing trust in sport sustainability, it is important to identify how this effect can be approached from the perspective of the education for sustainable development (ESD), as applied to the area of sports. However, it is essential that sports integrity be valued by society and that all sports actors (athletes, coaches, officials) promote ethics and fair play.
Improving Operational and Sustainability Performance in a Retail Fresh Food Market Using Lean: A Portuguese Case Study
Authors: Marques Pedro Alexandre , Carvalho André M. , Santos José Oliveira
Published: January 2022

This paper presents a real application of a lean–green improvement initiative conducted at a large Portuguese hypermarket store. It explores how lean tools and techniques may be used to not only improve the operational performance, but also sustainability. A case study was carried out in one store of a multinational retail enterprise, with the aim of enhancing both the operational and sustainability performance in the cold meat section, one of the most relevant areas of the fresh food markets. The Gemba Kaizen event approach, which comprises three main stages, was adopted. During the workshop stage, the structured problem-solving methodology was followed, and was recorded in an A3 format. As a consequence of this project, food waste in the cold meat market was reduced by half, whereas the out-of-stock index decreased by a third. In addition, the pilot store hit top performance within all stores of the company in Portugal, ranking first in all key indicators for the cold meat market. The lean–green scope and performance improvement procedures developed and implemented in the pilot store were later deployed to other stores of the company. This is one of the first publications regarding the application of lean management in the food retail sector for improving both the operational and sustainability performance.
The Mercury Content in the Upper Layers of Soils in the Selected Area of the Masovian Landscape Park
Authors: Małuszyński Marcin J. , Małuszyńska Ilona
Published: January 2022

Due to the high toxicity of the element itself and its compounds, mercury poses a significant threat to the human natural environment, in particular to the soil and water environment. An additional risk is the possibility of mercury accumulation in various elements of the environment. Soil is one of the most important elements of the natural environment and is the main link in the mercury cycle. The cycle of this element is related to both the natural processes taking place in the environment and human activity. The presence of mercury in the natural environment poses a particularly high risk of its re-accumulation as a result of its re-emission. The aim of the research was to determine the mercury content in the upper layers of soils collected from the area and buffer zone of the Mazowiecki Landscape Park as a potential source of this element’s re-emission to the environment. The paper presents the results of research on mercury content in the upper soil layer from the areas adjacent to the communication routes running through the area of the Mazowiecki Landscape Park and its buffer zone. The mercury content in the analyzed soil samples collected from the area of the Mazowiecki Landscape Park ranged from 0.082 mgHg·kg−1 dm to 0.183 mgHg·kg−1 dm, and in the soils from the cover, these values were slightly higher and ranged from 0.125 mgHg·kg−1 dm up to 0.362 mgHg·kg−1 dm. In order to avoid uncontrolled re-emission and, consequently, possible accumulation of this element in the environment, it is necessary to continue monitoring the level of mercury contamination, among others, in soil.
A Framework for Archive Demand Management Strategies: A Pilot Study on Water Use in a Low-Income Brazilian Area
Authors: Botelho Gabriella , Mello Mariza , Kiperstok Asher , Oliveira-Esquerre Karla
Published: January 2022

This study presents a pilot study in suburban households in Salvador, Brazil, inserted in the context of a framework developed to aid water demand management strategies. The framework aims to understand the barrier of subjectivity while identifying consumption habit patterns in households. Six key sets of components create the framework architecture: (1) characterization of the area based on: context, climate, population/area, population growth rate, and water management challenges; (2) a survey to obtain socio-demographic and physical property data of the sample; (3) smart metering and data processing systems to monitor sample water end use; (4) determining daily consumption patterns; (5) analyzing qualitative data through theoretical consumption models to identify relevant variables for the next step; and (6) construction of representative mathematical models of consumption for each daily practice (this item was not included on pilot). It provides a starting point to understand how water demand management strategies can be supported at the user and decision-making level. As a result, improvements to the interview guides used in the pilot were suggested. Furthermore, customized measures to promote rational water consumption were identified in the study area, and policies could be proposed.
Product Returns: An Opportunity to Shift towards an Access-Based Economy?
Authors: Baden Denise , Frei Regina
Published: January 2022

With the rise in online purchases, returns polices have become more lenient to maximise sales, leading to increased product returns. This results in considerable costs to businesses due to complex returns systems, and environmental costs due to unnecessary transportation and waste. Unsustainable consumption poses a threat to our environment, and access-based business models whereby products are borrowed/rented rather than purchased have been proposed as a way to align customer needs, business success, and sustainability. Product returns often constitute a form of informal or illegitimate borrowing, as goods are bought with the intention of being returned. In this discussion paper we propose that, instead of being viewed as a threat to business, issues with high product returns could be seen as an opportunity to switch to an access-based model. As product returns escalate, businesses will need to invest substantially in their reverse supply chains. We propose that a more strategic approach might be to leapfrog the costly stage of developing more efficient returns systems, and move straight to formalising product returns as the new normal for those goods that would best suit an access-based model, so that processes are streamlined around borrowing and returning rather than around sales.
Examining Farmers’ Adoption Decisions towards Precision-Agricultural Practices in Greek Dairy Cattle Farms
Authors: Kleftodimos Georgios , Kyrgiakos Leonidas Sotirios , Kleisiari Christina , Tagarakis Aristotelis C. , Bochtis Dionysis
Published: January 2022

Nowadays, the sustainability of Greek dairy cattle farms is questionable due to low competitiveness and high GHG emissions. In this context, the BIOCIRCULAR project, funded by the EYDE ETAK, developed a series of alternative practices focusing on precision agriculture principles. However, the adoption of any practice from farmers is not a given, and depends on several determinants. Hence, the objective of this study is to examine farmers’ adoption decisions regarding precision-agricultural practices in Greek dairy production systems, as well as the economic and environmental impacts of this adoption. In order to achieve this, a bio-economic model was developed based on mathematical programming methods. The proposed model simulates a large number of dairy cattle farms with or without crop production, including different management strategies and their relevant costs, and provides an environmental assessment of the adopted practices based on GHG emissions. Moreover, in order to analyze farmers’ adoption decisions, different policy measures, linked to various environmental outcomes, were examined. The results highlighted that the adoption of precision-agricultural practices led to significantly better economic and environmental outcomes. Furthermore, it was found that different levels of incentives can be efficiently targeted to encourage the adoption of new feeds and, more broadly, to secure the sustainability of the sector.
Comparison of Ultrasound Type and Working Parameters on the Reduction of Four Higher Alcohols and the Main Phenolic Compounds
Authors: Zhang Qingan , Zheng Hongrong , Cheng Shuang , Xu Bowen , Guo Penghui
Published: January 2022

In this paper, studies were conducted by a series of single-factor experiments to investigate the effects of ultrasound types and working parameters on the higher alcohols (HA), phenolic compounds, and color properties of red wine, so as to highlight the importance of the comprehensive consideration on its application. The results indicate that ultrasound devices and working parameters do have some definite influences on the HA of wine; moreover, the ultrasound bath (SB-500DTY) is better than the SCIENTZ-950E and the KQ-300VDE. With the SB-500DTY employed to further investigate its effects on phenols and color properties other than on HA, unexpectedly, some variations of color parameters are opposite to the results ever obtained from other ultrasound conditions. In summary, all these results suggest that both the ultrasound type and parameters should be fully considered or neutralized so as to have a comprehensive evaluation about its application, instead of some contradictory results.
Impact of Diversity Management on Employees’ Engagement: The Role of Organizational Trust and Job Insecurity
Authors: Alshaabani Ayman , Hamza Khadija Aya , Rudnák Ildikó
Published: January 2022

The frequent world changes raised by globalization, new technology development, and the increase in migration movements have generated an immensely diversified workforce. To face these challenges, managers started to seek the best strategies to effectively run this mixed environment and implement the leading diversity management policies for human resource management sustainability, which is also considered as very constructive in boosting employees’ performance, motivation, satisfaction, as well as their work engagement. Consistently, this paper examines the impact of service companies’ diversity management systems on employees’ engagement and the moderating role of organizational trust and job insecurity in that relationship. As we opted for a quantitative study, we managed a survey based on a questionnaire dedicated to 580 employees working in Hungarian companies, specializing in Marketing, Management consulting, IT, and logistics services, to effectively assess the hypothesis concluded from the literature review. With the use of structural equation modeling (SEM) as a data analysis tool, our findings reveal that diversity management has a positive significant effect on Employees’ engagement and that organizational trust and job insecurity truly and significantly mediate that association. Along with social exchange theory, our research contributes to affirming that by implementing proper diversity management practices and by ensuring a trustworthy environment and outstanding work conditions, managers are constructively able to assist their employees, raise their involvement, and minimize the level of job insecurities.
Effect of Temperature Fluctuations on the Bearing Capacity of Cold In-Depth Recycled Pavements
Authors: Loizos Andreas , Papavasiliou Vasilis
Published: January 2022

This study investigates the influence of the temperature fluctuations on the bearing capacity of cold in-depth recycled (CIR) pavements stabilized with foamed asphalt (FA). Aiming to achieve this goal, non-destructive testing was conducted during mild and high temperatures on a highway CIR pavement, utilizing mainly the FWD device. The back-calculated moduli values were utilized to estimate the strain values within the body of the pavement, while the strains induced using the FWD device were measured with a fiber optic sensors (FOS) system. Moreover, data from the fatigue behavior of the layer materials was also considered. The results of the related analysis indicate that for every 1 °C temperature increase within the body of the AC overlay, an approximately 5.7% increase of the critical tensile strain is expected. Moreover, for every 1 °C temperature increase within the body of the FA layer, an approximately 1.8% increase of the tensile strain at the bottom of the FA layer is expected. The new constructed layers, i.e., asphalt concrete (AC) and FA, sustain much more damage at high temperatures. This was more evident in the upper layer, i.e., the AC overlay.
Potential Impact of Biostimulator NeOsol and Three Different Manure Types on Physical Soil Properties and Crop Status in Heavy Soils Conditions
Authors: Novák Václav , Šařec Petr , Křížová Kateřina , Novák Petr , Látal Oldřich
Published: January 2022

This study was conducted to understand the long-term influence of biostimulator NeOsol in combination with different manure types on soil’s physical properties and crop status. NeOsol is a soil biostimulator that should stimulate the biological reactions of the soil profile and improve the soil’s physical and chemical properties. A six-year experiment was conducted with eight treatments: NPK, cattle manure, pig manure, poultry manure, and the same four treatments with the NeOsol added on top. The in situ sampling of soil properties provided data on unit draft (UD), bulk density (BD), and saturated hydraulic conductivity (SHC). Furthermore, remotely sensed data were analyzed to describe crop status via three selected vegetation indices (VI), and crop yields were assessed last. The variants treated with NeOsol demonstrated decreases in UD over time; BD, SHC, and VI did not significantly change. The impact on yield was significant and increased over time. When comparing the variants with manure application to those without one, the cattle manure led to significantly higher SHC; the pig manure led to significantly lower UD and BD but significantly higher SHC and yield; and the poultry manure led to significantly lower UD and BD but higher yield.
Wetland Change Mapping Using Machine Learning Algorithms, and Their Link with Climate Variation and Economic Growth: A Case Study of Guangling County, China
Authors: Gemechu Gadisa Fayera , Rui Xiaoping , Lu Haiyue
Published: January 2022

Wetlands are a distinctive terrestrial ecosystem that benefits living things, including people, in various ways. Sustainable wetland ecosystem resources are needed to protect the global environment. Wetlands in China have undergone positive and negative changes in response to several factors, but studies documenting their long-term dynamicity have been few, particularly in Guangling County. This study examines the change of wetlands area based on remotely sensed data while exploring trends associated with climate variations and economic growth in Guangling County, China. Analysis of remotely sensed imagery, mainly in hilly and nonhomogeneous environments is problematic, largely as a result of interference and their high spectral non-homogeneity. We conducted experiments using five classical machine learning algorithms based on the Google Earth Engine (GEE) and obtained the greatest robustness and accuracy using a Support Vector Machine (SVM)—Radial Basis Function (RBF) kernel approach, with overall accuracy and kappa statistics ranging from 86% to 98.1% and from 0.789 to 0.960, respectively. Based on the SVM-RBF model’s outperformance of four other algorithms, we identified spatial distributions of wetland in the study area and associated change trends. We found that 45.71 km2 of wetland area was lost over the past 3.7 decades (January 1984–December 2020), or 81.82% of wetland area coverage. In this paper, we explore how factors such as county economic growth (GDP), humidity, and temperature variations are tightly linked with wetland change.
Statistical Modeling of Energy Harvesting in Hybrid PLC-WLC Channels
Authors: Fernandes Victor , Nogueira Thiago F. A. , Poor H. Vincent , Ribeiro Moisés V.
Published: January 2022

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.
Impact of Granular Activated Carbon on Anaerobic Process and Microbial Community Structure during Mesophilic and Thermophilic Anaerobic Digestion of Chicken Manure
Authors: Ziganshina Elvira E. , Bulynina Svetlana S. , Ziganshin Ayrat M.
Published: January 2022

In this work, the impact of granular activated carbon (GAC) on the mesophilic and thermophilic anaerobic digestion of chicken manure and the structure of microbial communities was investigated. These results demonstrated that GAC supplementation effectively enhanced the consumption of produced organic acids in the mesophilic and thermophilic batch tests, accompanied by faster biomethane production in the presence of GAC than from reactors without GAC. However, since the free ammonia level was 3–6 times higher in the thermophilic reactors, this led to the instability of the anaerobic digestion process of the nitrogen-rich substrate at thermophilic temperatures. Bacteroidia and Clostridia were the two main bacterial classes in the mesophilic reactors, whereas the class Clostridia had a competitive advantage over other groups in the thermophilic systems. The archaeal communities in the mesophilic reactors were mainly represented by representatives of the genera Methanosarcina, Methanobacterium, and Methanotrix, whereas the archaeal communities in the thermophilic reactors were mainly represented by members of the genera Methanosarcina, Methanoculleus, and Methanothermobacter. New data obtained in this research will help control and manage biogas reactors in the presence of GAC at different temperatures.