bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Wintertime Cloud Microphysical Properties and Their Relationship to Air Mass Advection at Ny-Ålesund, Svalbard Using the Synergy of a Cloud Radar–Ceilometer–Microwave Radiometer
Authors: Cho Yeonsoo , Park Sang-Jong , Kim Joo-Hong , Yeo Huidong , Nam Jihyun , Jun Sang-Yoon , Kim Baek-Min , Kim Sang-Woo
Published: June 2021

This study investigates the relationship of cloud properties and radiative effects with air mass origin during the winter (November–February, 2016–2020) at Ny-Ålesund, Svalbard, through a combination of cloud radar, ceilometer, and microwave radiometer measurements. The liquid cloud fraction (CF) was less than 2%, whereas the ice CF predominantly exceeded 10% below 6 km. The liquid water content (LWC) of mixed-phase clouds (LWCmix), which predominantly exist in the boundary layer (CFmix: 10–30%), was approximately four times higher than that of liquid clouds (LWCliq). Warm air mass advection (warmadv) cases were closely linked with strong southerly/southwesterly winds, whereas northerly winds brought cold and dry air masses (coldadv) to the study area. Elevated values of LWC and ice water content (IWC) during warmadv cases can be explained by the presence of mixed-phase clouds in the boundary layer and ice clouds in the middle troposphere. Consistently, the re of ice particles in warmadv cases was approximately 5–10 μm larger than that in coldadv cases at all altitudes. A high CF and cloud water content in warmadv cases contributed to a 33% (69 W m−2) increase in downward longwave (LW) fluxes compared to cloud-free conditions.
Satellite Investigation of Semidiurnal Internal Tides in the Sulu-Sulawesi Seas
Authors: Zhao Xiaoyu , Xu Zhenhua , Feng Ming , Li Qun , Zhang Peiwen , You Jia , Gao Song , Yin Baoshu
Published: June 2021

The mode-1 semidiurnal internal tides that emanate from multiple sources in the Sulu-Sulawesi Seas are investigated using multi-satellite altimeter data from 1993–2020. A practical plane-wave analysis method is used to separately extract multiple coherent internal tides, with the nontidal noise in the internal tide field further removed by a two-dimensional (2-D) spatial band-pass filter. The complex radiation pathways and interference patterns of the internal tides are revealed, showing a spatial contrast between the Sulu Sea and the Sulawesi Sea. The mode-1 semidiurnal internal tides in the Sulawesi Sea are effectively generated from both the Sulu and Sangihe Island chains, forming a spatially inhomogeneous interference pattern in the deep basin. A cylindrical internal tidal wave pattern from the Sibutu passage is confirmed for the first time, which modulates the interference pattern. The interference field can be reproduced by a line source model. A weak reflected internal tidal beam off the Sulawesi slope is revealed. In contrast, the Sulu Island chain is the sole energetic internal tide source in the Sulu Sea, thus featuring a relatively consistent wave and energy flux field in the basin. These energetic semidiurnal internal tidal beams contribute to the frequent occurrence of internal solitary waves (ISWs) in the study area. On the basis of the 28-year consistent satellite measurements, the northward semidiurnal tidal energy flux from the Sulu Island chain is 0.46 GW, about 25% of the southward energy flux. For M2, the altimetric estimated energy fluxes from the Sulu Island chain are about 80% of those from numerical simulations. The total semidiurnal tidal energy flux from the Sulu and Sangihe Island chains into the Sulawesi Sea is about 2.7 GW.
SAFFNet: Self-Attention-Based Feature Fusion Network for Remote Sensing Few-Shot Scene Classification
Authors: Kim Joseph , Chi Mingmin
Published: June 2021

In real applications, it is necessary to classify new unseen classes that cannot be acquired in training datasets. To solve this problem, few-shot learning methods are usually adopted to recognize new categories with only a few (out-of-bag) labeled samples together with the known classes available in the (large-scale) training dataset. Unlike common scene classification images obtained by CCD (Charge-Coupled Device) cameras, remote sensing scene classification datasets tend to have plentiful texture features rather than shape features. Therefore, it is important to extract more valuable texture semantic features from a limited number of labeled input images. In this paper, a multi-scale feature fusion network for few-shot remote sensing scene classification is proposed by integrating a novel self-attention feature selection module, denoted as SAFFNet. Unlike a pyramidal feature hierarchy for object detection, the informative representations of the images with different receptive fields are automatically selected and re-weighted for feature fusion after refining network and global pooling operation for a few-shot remote sensing classification task. Here, the feature weighting value can be fine-tuned by the support set in the few-shot learning task. The proposed model is evaluated on three publicly available datasets for few shot remote sensing scene classification. Experimental results demonstrate the effectiveness of the proposed SAFFNet to improve the few-shot classification accuracy significantly compared to other few-shot methods and the typical multi-scale feature fusion network.
Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance
Authors: Tun Nyi Nyi , Sanuki Fumiya , Iramina Keiji
Published: June 2021

Synchronous correlation brain and muscle oscillations during motor task execution is termed as functional coupling. Functional coupling between two signals appears with a delay time which can be used to infer the directionality of information flow. Functional coupling of brain and muscle depends on the type of muscle contraction and motor task performance. Although there have been many studies of functional coupling with types of muscle contraction and force level, there has been a lack of investigation with various motor task performances. Motor task types play an essential role that can reflect the amount of functional interaction. Thus, we examined functional coupling under four different motor tasks: real movement, intention, motor imagery and movement observation tasks. We explored interaction of two signals with linear and nonlinear information flow. The aim of this study is to investigate the synchronization between brain and muscle signals in terms of functional coupling and delay time. The results proved that brain–muscle functional coupling and delay time change according to motor tasks. Quick synchronization of localized cortical activity and motor unit firing causes good functional coupling and this can lead to short delay time to oscillate between signals. Signals can flow with bidirectionality between efferent and afferent pathways.
Energy Optimization in Dual-RIS UAV-Aided MEC-Enabled Internet of Vehicles
Authors: Michailidis Emmanouel T. , Miridakis Nikolaos I. , Michalas Angelos , Skondras Emmanouil , Vergados Dimitrios J.
Published: June 2021

Mobile edge computing (MEC) represents an enabling technology for prospective Internet of Vehicles (IoV) networks. However, the complex vehicular propagation environment may hinder computation offloading. To this end, this paper proposes a novel computation offloading framework for IoV and presents an unmanned aerial vehicle (UAV)-aided network architecture. It is considered that the connected vehicles in a IoV ecosystem should fully offload latency-critical computation-intensive tasks to road side units (RSUs) that integrate MEC functionalities. In this regard, a UAV is deployed to serve as an aerial RSU (ARSU) and also operate as an aerial relay to offload part of the tasks to a ground RSU (GRSU). In order to further enhance the end-to-end communication during data offloading, the proposed architecture relies on reconfigurable intelligent surface (RIS) units consisting of arrays of reflecting elements. In particular, a dual-RIS configuration is presented, where each RIS unit serves its nearby network nodes. Since perfect phase estimation or high-precision configuration of the reflection phases is impractical in highly mobile IoV environments, data offloading via RIS units with phase errors is considered. As the efficient energy management of resource-constrained electric vehicles and battery-enabled RSUs is of outmost importance, this paper proposes an optimization approach that intends to minimize the weighted total energy consumption (WTEC) of the vehicles and ARSU subject to transmit power constraints, timeslot scheduling, and task allocation. Extensive numerical calculations are carried out to verify the efficacy of the optimized dual-RIS-assisted wireless transmission.
Transmission Sensitivities of Contact Ultrasonic Transducers and Their Applications
Authors: Ono Kanji , Cho Hideo , Vallen Hartmut , M’Closkey Robert T.
Published: June 2021

In all ultrasonic material evaluation methods, transducers and sensors play a key role of mechanoelectrical conversion. Their transduction characteristics must be known quantitatively in designing and implementing successful structural health monitoring (SHM) systems. Yet, their calibration and verification have lagged behind most other aspects of SHM system development. This study aims to extend recent advances in quantifying the transmission and receiving sensitivities to normally incident longitudinal waves of ultrasonic transducers and acoustic emission sensors. This paper covers extending the range of detection to lower frequencies, expanding to areal and multiple sensing methods and examining transducer loading effects. Using the refined transmission characteristics, the receiving sensitivities of transducers and sensors were reexamined under the conditions representing their actual usage. Results confirm that the interfacial wave transmission is governed by wave propagation theory and that the receiving sensitivity of resonant acoustic emission sensors peaks at antiresonance.
Development of a Light-Weight Unmanned Aerial Vehicle for Precision Agriculture
Authors: Ukaegbu Uchechi F. , Tartibu Lagouge K. , Okwu Modestus O. , Olayode Isaac O.
Published: June 2021

This paper describes the development of a modular unmanned aerial vehicle for the detection and eradication of weeds on farmland. Precision agriculture entails solving the problem of poor agricultural yield due to competition for nutrients by weeds and provides a faster approach to eliminating the problematic weeds using emerging technologies. This research has addressed the aforementioned problem. A quadcopter was built, and components were assembled with light-weight materials. The system consists of the electric motor, electronic speed controller, propellers, frame, lithium polymer (li-po) battery, flight controller, a global positioning system (GPS), and receiver. A sprayer module which consists of a relay, Raspberry Pi 3, spray pump, 12 V DC source, water hose, and the tank was built. It operated in such a way that when a weed is detected based on the deep learning algorithms deployed on the Raspberry Pi, general purpose input/output (GPIO) 17 or GPIO 18 (of the Raspberry Pi) were activated to supply 3.3 V, which turned on a DC relay to spray herbicides accordingly. The sprayer module was mounted on the quadcopter and from the test-running operation conducted, broadleaf and grass weeds were accurately detected and the spraying of herbicides according to the weed type occurred in less than a second.
Spatial Scale Effect of a Typical Polarized Remote Sensor on Detecting Ground Objects
Authors: Zhang Ying , Sun Jingyi , Qiu Rudong , Liu Huilan , Zhang Xi , Xuan Jiabin
Published: June 2021

For polarized remote sensors, the polarization images of ground objects acquired at different spatial scales will be different due to the spatial heterogeneity of the ground object targets and the limitation of imaging resolution. In this paper, the quantitative inversion problem of a typical polarized remote sensor at different spatial scales was studied. Firstly, the surface roughness of coatings was inversed based on the polarized bidirectional reflectance distribution function (pBRDF) model according to their polarization images at different distances. A linear-mixed pixel model was used to make a preliminary correction of the spatial scale effect. Secondly, the super-resolution image reconstruction of the polarization imager was realized based on the projection onto convex sets (POCS) method. Then, images with different resolutions at a fixed distance were obtained by utilizing this super-resolution image reconstruction method and the optimal spatial scale under the scene can be acquired by using information entropy as an evaluation indicator. Finally, the experimental results showed that the roughness inversion of coatings has the highest accuracy in the optimal spatial scale. It has been proved that our proposed method can provide a reliable way to reduce the spatial effect of the polarized remote sensor and to improve the inversion accuracy.
The Effect of Various Parameters on a Portable Sensor for the Detection of Thin Biofilms in Water Pipes
Authors: Davis Sachin , Salowitz Nathan , Beversdorf Lucas , Silva Marcia R.
Published: June 2021

The use of high-frequency strain waves to perform examinations and note measurements is referred to as ultrasonic testing (UT). UT is commonly used for the detection or evaluation of flaws and characterization of materials, among other applications. A standard ultrasonic inspection system comprises a pulser/receiver, transducer, and display devices. The pulser/receiver produces electrical pulses of high voltage. The transducer generates high-frequency ultrasonic energy after being driven by the pulser. The reflected wave is then converted into an electrical signal by the transducer and is displayed on a screen. The reflected signal strength versus the time plot helps to glean information regarding the features of a defect. In this paper, we discuss the experiments performed in a laboratory setting to determine ultrasound-based biofilm sensor sensitivity in relation to changes in the surrounding environment of temperature, concentration, turbidity, and conductivity of the liquid passing through the system. The effect of the change in frequency of the sensors was also studied. The sensors being developed are small and compact, portable, can be placed on the outer walls of the desired surface, use digital signal processing techniques, and the biofilm presence on the inner walls of the surface can be monitored.
Modular Data Acquisition System for Recording Activity and Electrical Stimulation of Brain Tissue Using Dedicated Electronics
Authors: Jurgielewicz Paweł , Fiutowski Tomasz , Kublik Ewa , Skoczeń Andrzej , Szypulska Małgorzata , Wiącek Piotr , Hottowy Paweł , Mindur Bartosz
Published: June 2021

In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat’s brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.
Graph Model-Based Lane-Marking Feature Extraction for Lane Detection
Authors: Yoo Juhan , Kim Donghwan
Published: June 2021

This paper presents a robust, efficient lane-marking feature extraction method using a graph model-based approach. To extract the features, the proposed hat filter with adaptive sizes is first applied to each row of an input image and local maximum values are extracted from the filter response. The features with the maximum values are fed as nodes to a connected graph structure, and the edges of the graph are constructed using the proposed neighbor searching method. Nodes related to lane-markings are then selected by finding a connected subgraph in the graph. The selected nodes are fitted to line segments as the proposed features of lane-markings. The experimental results show that the proposed method not only yields at least 2.2% better performance compared to the existing methods on the KIST dataset, which includes various types of sensing noise caused by environmental changes, but also improves at least 1.4% better than the previous methods on the Caltech dataset which has been widely used for the comparison of lane marking detection. Furthermore, the proposed lane marking detection runs with an average of 3.3 ms, which is fast enough for real-time applications.
Radar Position Estimation by Sequential Irradiation of ESM Receivers
Authors: Hubáček Petr , Veselý Jiří , Olivová Jana
Published: June 2021

In this article, a new technique for determination of 2D signal source (target) position is proposed. This novel approach, called the Inscribed Angle (InA), is based on measuring the time difference of sequential irradiation by the main beam of the target antenna’s radiation pattern, using Electronic Support Measures (ESM) receivers, assuming that the target antenna is rotating and that its angular velocity is constant. In addition, it is also assumed that the localization system operates in a LOS (Line of Sight) situation and that three time-synchronized sensors are placed arbitrarily across the area. The main contribution of the article is a complete description of the proposed localization method. That is, this paper demonstrates a geometric representation and an InA localization technique model. Analysis of the method’s accuracy is also demonstrated. The time of irradiation of the receiving station corresponds to the direction in which the maximum received signal strength (RSS) was measured. In order to achieve a certain degree of accuracy of the proposed positioning technique, a method was derived to increase the accuracy of the irradiation time estimation. Finally, extensive simulation was conducted to demonstrate the performance and accuracy of our positioning method.
Improved Support Vector Machine Enabled Radial Basis Function and Linear Variants for Remote Sensing Image Classification
Authors: Razaque Abdul , Ben Haj Frej Mohamed , Almi’ani Muder , Alotaibi Munif , Alotaibi Bandar
Published: June 2021

Remote sensing technologies have been widely used in the contexts of land cover and land use. The image classification algorithms used in remote sensing are of paramount importance since the reliability of the result from remote sensing depends heavily on the classification accuracy. Parametric classifiers based on traditional statistics have successfully been used in remote sensing classification, but the accuracy is greatly impacted and rather constrained by the statistical distribution of the sensing data. To eliminate those constraints, new variants of support vector machine (SVM) are introduced. In this paper, we propose and implement land use classification based on improved SVM-enabled radial basis function (RBF) and SVM-Linear for image sensing. The proposed variants are applied for the cross-validation to determine how the optimization of parameters can affect the accuracy. The accuracy assessment includes both training and test sets, addressing the problems of overfitting and underfitting. Furthermore, it is not trivial to determine the generalization problem merely based on a training dataset. Thus, the improved SVM-RBF and SVM-Linear also demonstrate the outstanding generalization performance. The proposed SVM-RBF and SVM-Linear variants have been compared with the traditional algorithms (Maximum Likelihood Classifier (MLC) and Minimum Distance Classifier (MDC)), which are highly compatible with remote sensing images. Furthermore, the MLC and MDC are mathematically modeled and characterized with new features. Also, we compared the proposed improved SVM-RBF and SVM-Linear with the current state-of-the-art algorithms. Based on the results, it is confirmed that proposed variants have higher overall accuracy, reliability, and fault-tolerance than traditional as well as latest state-of-the-art algorithms.
Shades of Belonging: The Intersection of Race and Religion in Utah Immigrants’ Social Integration
Authors: Lopez Jane Lilly , Munoa Genevra , Valdez Catalina , Terron Ayala Nadia
Published: June 2021

Utah, USA, a state with a unique history of immigration and a distinctive religious context, provides a useful setting in which to study the intersection of racism and religious participation with immigrant integration. Utah is one of the Whitest states in the United States, with 4 of every 5 residents identifying as non-Hispanic White. It is also home to the headquarters of the Church of Jesus Christ of Latter-day Saints (LDS Church) which, until 1978, explicitly imposed race-based exclusions that prohibited or strictly limited Black members’ participation in church leadership, rituals, and ordinances. The state’s cultural, social, and religious history has contributed to widespread beliefs among modern Utah residents of Whites’ racial supremacy in contexts both mundane and divine. Much of Utah’s population growth since 1960, especially among non-White racial and ethnic groups, can be attributed to immigrants, who today compose nearly 10 percent of the state’s population. Given Utah’s religious, social, and cultural relationship to race, it is an ideal case to study the following question: how do race, religion, and culture shape integration among immigrants? Utilizing interviews with 70 immigrants who have lived in Utah for an average of 13 years, we find that both race and LDS Church membership influence immigrants’ social integration, creating a hierarchy of belonging among immigrants in Utah––with White LDS immigrants reporting the highest levels of integration and non-White, non-LDS immigrants reporting the lowest levels of integration. These findings suggest the power of cultural narratives––beyond explicit institutional policy and practice––in perpetuating racial inequality in society. Thus, efforts to increase integration and belonging among immigrants must not only include work to dismantle legal and structural inequalities but also efforts to actively change the cultural narratives associated with them.
A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment
Authors: Iqbal Sana , Sarfraz Mohammad , Ayyub Mohammad , Tariq Mohd , Chakrabortty Ripon K. , Ryan Michael J. , Alamri Basem
Published: June 2021

The ever increasing demand for electricity and the rapid increase in the number of automatic electrical appliances have posed a critical energy management challenge for both utilities and consumers. Substantial work has been reported on the Home Energy Management System (HEMS) but to the best of our knowledge, there is no single review highlighting all recent and past developments on Demand Side Management (DSM) and HEMS altogether. The purpose of each study is to raise user comfort, load scheduling, energy minimization, or economic dispatch problem. Researchers have proposed different soft computing and optimization techniques to address the challenge, but still it seems to be a pressing issue. This paper presents a comprehensive review of research on DSM strategies to identify the challenging perspectives for future study. We have described DSM strategies, their deployment and communication technologies. The application of soft computing techniques such as Fuzzy Logic (FL), Artificial Neural Network (ANN), and Evolutionary Computation (EC) is discussed to deal with energy consumption minimization and scheduling problems. Different optimization-based DSM approaches are also reviewed. We have also reviewed the practical aspects of DSM implementation for smart energy management.
Online Synchronous Model of Interpretive Sustainable Guiding in Heritage Sites: The Avatar Tourist Visit
Authors: Viñals María José , Gilabert-Sansalvador Laura , Sanasaryan Anna , Teruel-Serrano Maria-Dolores , Darés Marino
Published: June 2021

The health crisis caused by the coronavirus (COVID-19) pandemic created an unprecedented social situation. In the most critical moments, tourism activities were cancelled or reduced to their minimum operation, creating an extreme situation of separation of a country’s heritage from residents and tourists. The objective of this work is to propose new options and strategies to reconnect the public with heritage under any circumstance and, at the same time, offer tourism services in healthy, secure conditions. Thus, live-streaming experiences of online interpretative tourist guidance were developed in heritage spaces; those visits were led by real guide-interpreters in a real environment and transmitted for remote visitors. We have called this visiting model the “Avatar Tourist Visit”. It is based on tools associated with Heritage Interpretation, Interpersonal Communication, Filmmaking and Audio-Visual Language, and Information and Communication Technologies. The methodological development of this tool was based on Design Sciences Research as the creation of a new procedure was pursued. The result is a sustainable, immersive, interactive, inclusive, unique, and resilient tourism product designed not only for times of crisis but also to connect the public with heritage at all times and ensure universal access to it. In addition, this activity constitutes a marketable experience as a specialized and customizable tourist product.
Reshaping the Gdańsk Shipyard—The Birthplace of the Solidarity Movement. The Complexity of Adaptive Reuse in the Heritage Context
Authors: Lorens Piotr , Bugalski Łukasz
Published: June 2021

The Gdańsk Shipyard—the birthplace of the Solidarity movement—is host to a unique example of a multi-layered brownfield redevelopment project, an area that is burdened by a complex history, overlapping heritage, and multiple memories. These circumstances require an integrated yet differentiated approach to the site’s heritage and make the creation of one homogeneous narration of its future impossible. At the same time, the size of the area, as well as its location within Gdańsk city centre, has meant that its future has been the subject of numerous discussions and speculations conducted over the last 20 years—starting from the creation of a large-scale open-air museum and continuing to the localization of the new Central Business District of the city. Consequently, that broad discussion carried out regarding the scope of redevelopment projects has been rooted in the possible introduction of diverse models of adaptive reuse. This variety of possible approaches also includes discussion on the mode of integrating heritage in the redevelopment processes. The goal of this paper—written just before the initiation of the final stage of the conceptual part of the project—is to present the complexity of approaches to issues related to redevelopment and heritage preservation.
Monitoring the Impact of COVID-19 Lockdown on the Production of Nitrogen Dioxide (NO2) Pollutants Using Satellite Imagery: A Case Study of South Asia
Authors: Hassan Farhad , Chaudhry Muhammad Umar , Yasir Muhammad , Asghar Muhammad Nabeel , Sarkodie Samuel Asumadu
Published: June 2021

Among the numerous anthropogenic pollutants, nitrogen dioxide (NO2) is one of the leading contaminants mainly released by burning fossil fuels in industrial and transport sectors. This study evaluates the impact of COVID-19 lockdown on the growing trend of NO2 emissions in South Asia. Satellite imagery data of Sentinel-5 Precursor with Tropomi instrument was employed in this study. The analysis was performed using time series data from February–May 2019 and February–May 2020. The time frame from February–May 2020 was further divided into two sub-time-frames, i.e., from 1 February–20 March (pre-lockdown) and from 21 March–May 2020 (lockdown). Results show the concentration of NO2 pollutants over the region declined by 6.41% from February–May 2019 to February–May 2020. Interestingly, an increasing trend of NO2 concentration by 6.58% occurred during the pre-lockdown phase in 2020 (1 February–20 March) compared to 2019 (February–May). However, the concentration of NO2 pollutants reduced considerably by 21.10% during the lockdown phase (21 March–10 May) compared to the pre-lockdown phase in 2020. Furthermore, the country-specific detailed analysis demonstrates the significant impact of COVID-19-attributed lockdown on NO2 concentration in South Asia.
Quality of Life in Poor Neighborhoods through the Lenses of the Capability Approach—A Case Study of a Deprived Area of Łódź City Centre
Authors: Grabowska Izabela
Published: June 2021

The aim of the paper is to identify the mechanisms shaping the quality of life of the residents of poor neighborhoods based on the example of a deprived area of Łódź city center. To analyze this multidimensional phenomenon, the capability approach is used with a special focus on conversion factors that limit the pursuit of preferred lifestyles. Based on 80 in–depth interviews with residents and register data from public authorities (at the building level, which enables presenting the detailed spatial distribution of the analyzed issues), individual trajectories in the form of individual mechanisms have been established and then aggregated. The aggregation is presented as a web of social exclusion. The collected information has allowed the author to create a categorization of conversion factors in degraded areas that take into account their interrelationships and complex cause–effect mechanisms. The classification is constructed using the following categories: housing conditions, economic wealth, knowledge and skills, norms, attitudes and social capital, work environment, and life conditions (defined mainly as access to public services and space). Combining quantitative data (at the building level) with qualitative data provided the author with crucial input for the identification of specific public policy actions that can affect conversion factors.
A Hybrid Multi-Criteria Decision Making Model for Defect-Based Condition Assessment of Railway Infrastructure
Authors: El-khateeb Laith , Mohammed Abdelkader Eslam , Al-Sakkaf Abobakr , Zayed Tarek
Published: June 2021

The condition of railway infrastructure, such as rails, ballasts and sleepers, should always be monitored and analyzed to ensure ride safety and quality for both passengers and freight. It is hard to assess the condition of railway infrastructure due to the existence of various components. The existing condition assessment models are mostly limited to only assess track geometry conditions and structural condition of the railway infrastructure. Therefore, the present research develops a defect-based structural and geometrical condition model of railway infrastructure. The defects of each component are identified and examined through literature and experts in the field. Two main inputs are used to develop the model: (1) the relative weight of importance for components, defects and their categories and (2) defects severities. To obtain the relative weights, the analytic network process (ANP) technique is adopted. Fuzzy logic is used to unify all the different defect criteria and to interpret the linguistic condition assessment grading scale to a numerical score. Hence, the technique for order preference by similarity to ideal Solution (TOPSIS) is used to integrate both weights and severities to determine the railway infrastructure condition. The developed model gives a detailed condition of the railway infrastructure by representing a three-level condition state, for defect categories, components and an overall railway infrastructure. The developed model is implemented to five case studies from Ontario, Canada. The developed model is validated by comparing its results with the real case studies results, which shows similar results, indicating the robustness of the developed model. This model helps in minimizing the inaccuracy of railway condition assessment through the application of severity, uncertainty mitigation and robust aggregation
Is It All about Efficiency? Exploring Students’ Conceptualizations of Sustainability in an Introductory Energy Course
Authors: Gelles Laura A. , Mejia Joel Alejandro , Lord Susan M. , Hoople Gordon D. , Chen Diana A.
Published: June 2021

Engineers are increasingly called on to develop sustainable solutions to complex problems. Within engineering, however, economic and environmental aspects of sustainability are often prioritized over social ones. This paper describes how efficiency and sustainability were conceptualized and interrelated by students in a newly developed second-year undergraduate engineering course, An Integrated Approach to Energy. This course took a sociotechnical approach and emphasized modern energy concepts (e.g., renewable energy), current issues (e.g., climate change), and local and personal contexts (e.g., connecting to students’ lived experiences). Analyses of student work and semi-structured interview data were used to explore how students conceptualized sustainability and efficiency. We found that in this cohort (n = 17) students often approached sustainability through a lens of efficiency, believing that if economic and environmental resources were prioritized and optimized, sustainability would be achieved. By exploring sustainability and efficiency together, we examined how dominant discourses that privilege technical over social aspects in engineering can be replicated within an energy context.
Numerical Analysis and Parametric Study of a 7 kW Tubular Permanent Magnet Linear Alternator
Authors: Cheng Chin-Hsiang , Dhanasekaran Surender
Published: June 2021

Free-Piston Stirling Engines (FPSEs) are known for their easy maintenance, longer lifetimes, high reliability, quiet operation due to no crankshafts, and having fewer seals compared to the traditional Stirling engine. Free-piston systems are popular in the conversion of thermal energy into electrical energy and are compatible with many types of heat sources. This research paper concentrates on the development of a Permanent Magnet Linear Alternator (PMLA) and parametrically analyzing it to predict its limitations and performance over variable operable conditions and material choices. Operable conditions including stroke length and frequency of the translator, and material choice for the stator and magnets, are varied in this study to analyze the machine and put it to test for its extreme limitations. Spacing between slots is introduced to reduce the overall mass of the stator and increase the power density. The load test is carried out with varied parameters. It induces a load EMF of 2.4 kV, yields a power of 7 kW, and has a power density of 314 W/kg by FEM analysis in peak variations. This study enumerates the performance variation of a PMLA over these varied conditions and illustrates the limitations of such power-dense machines.
Susceptibility Analysis of Glacier Debris Flow by Investigating the Changes in Glaciers Based on Remote Sensing: A Case Study
Authors: Lin Ruoshen , Mei Gang , Liu Ziyang , Xi Ning , Zhang Xiaona
Published: June 2021

Glacier debris flow is one of the most critical categories of geological hazards in high-mountain regions. To reduce its potential negative effects, it needs to investigate the susceptibility of glacier debris flow. However, when evaluating the susceptibility of glacier debris flow, most research work considered the impact of existing glacier area, while ignoring the impact of changes in glacier ablation volume. In this paper, we considered the impact of the changes in the glacier ablation volume to investigate the susceptibility of glacier debris flow. We proposed to evaluate the susceptibility analysis in G217 gullies with frequent glacial debris flow on the Duku highway, Xinjiang Province. Specifically, by using the simple band ratio method with the manual correction to identify glacier outlines, we identified the ablation zone by comparing the glacier boundary in 2000 with that in 2015. We then calculated ablation volume by changes in glacier elevation and ablation area from 2000 to 2015. Finally, we used the volume of glacier melting in different watersheds as the main factor to evaluate the susceptibility based on the improved geomorphic information entropy (GIE) method. We found that, overall, the improved GIE method with a correction coefficient based on the glacier ablation volume is better than the previous method. Deglaciation can be adapted to analyze glacier debris flow susceptibility based on glaciology and geomorphology. Our presented work can be applied to other similar glacial debris flow events in high-mountain regions.
A Study on the Perceived Positive Coaching Leadership, Sports Enthusiasm, and Happiness of Boxing Athletes
Authors: Huang Hsing-Chieh , Lee Peng-Yeh , Lo Yu-Chih , Chen I-Shen , Hsu Chin-Hsien
Published: June 2021

In recent years, the sport of boxing has become a popular trend, and with the promotion of sport psychology, the leadership style of coaches plays an important role in influencing the mental aspect of athletes. Boxing is an exercise that combines intensity and relaxation, which not only improves the strength of the muscles and bones but also contributes to the mental health of people and brings them a sense of happiness. In this study, we investigated the correlation between boxing athletes’ perceived positive coaching leadership, sports enthusiasm, and happiness. In this study, 300 valid questionnaires were collected from boxing athletes and then analyzed by statistical software. The results showed that positive leadership had a significant positive effect on sports enthusiasm; sports enthusiasm had a significant positive effect on happiness, and positive leadership had a significant positive effect on happiness.In conclusion, the study has discussed the significance of sport psychology and well-being. The study is expected to contribute to the related literature and offer suggestions for future studies in sports science and management.
Understanding Economic, Social, and Environmental Sustainability Challenges in the Global South
Authors: Sierra Javier , Suárez-Collado Ángela
Published: June 2021

In an increasingly complex world, students of economics, business, and management must learn how to combine financial objectives with social and environmental aims. To that end, institutions, teachers, and curricula have a growing need for multidisciplinary approaches to reinforce education for sustainable development. This study presents a pilot project consisting of an innovative online simulation designed to help students understand the challenges that countries and companies from the Global South are facing to balance economic, social, and environmental objectives under sustainability criteria. This research uses quantitative and qualitative data provided by the students to assess the effectiveness of the methodology. The results indicate the usefulness of the methodology in helping students comprehend economic complexities in the Global South, as well as to assist them in acquiring key cognitive, skill-based, and affective educational outcomes. The combination of three active-learning methodologies (role-play, collaborative-learning, and inquiry-based learning) proved to be of high value to address sustainability-related issues in higher education and help students develop 21st-century skills.
Optimization of the Biomethane Production Process by Anaerobic Digestion of Wheat Straw Using Chemical Pretreatments Coupled with Ultrasonic Disintegration
Authors: Ouahabi Yasmine Ryma , Bensadok Kenza , Ouahabi Abdeldjalil
Published: June 2021

Biomass is an attractive energy source that can be used for production of heat, power, and transport fuels and when produced and used on a sustainable basis, can make a large contribution to reducing greenhouse gas emissions. Anaerobic digestion (AD) is a suitable technology for reducing organic matter and generating bioenergy in the form of biogas. This study investigated the factors allowing the optimization of the process of biogas production from the digestion of wheat straw (WS). The statistical analysis of the experiments carried out showed that ultrasonic processing plays a fundamental role with the sonication density and solids concentration leading to improved characteristics of WS, reducing particle size, and increasing concentration of soluble chemical oxygen demand. The higher the sonicating power used, the more the waste particles are disrupted. The optimality obtained under mesophilic conditions for WS pretreated with 4% w/w (weight by weight) H2O2 at temperature 36 °C under 10 min of ultrasonication at 24 kHz with a power of 200 W improves the methane yield by 64%.
Co-Housing Response to Social Isolation of COVID-19 Outbreak, with a Focus on Gender Implications
Authors: Giorgi Emanuele , Martín López Lucía , Garnica-Monroy Ruben , Krstikj Aleksandra , Cobreros Carlos , Montoya Miguel A.
Published: June 2021

COVID-19 forced billions of people to restructure their daily lives and social habits. Several research projects have focused on social impacts, approaching the phenomenon on the basis of different issues and scales. This work studies the changes in social relations within the well-defined urban-territorial elements of co-housing communities. The peculiarity of this research lies in the essence of these communities, which base their existence on the spirit of sharing spaces and activities. As social distancing represented the only effective way to control the outbreak, the research studied how the rules of social distancing impacted these communities. For this reason, a questionnaire was sent to 60 communities asking them to highlight the changes that the emergency imposed on the members in their daily life and in the organization of common activities and spaces. A total of 147 responses were received and some relevant design considerations emerged: (1) the importance of feeling part of a “safe” community, with members who were known and deemed reliable, when facing a health emergency; and (2) the importance of open spaces to carry out shared activities. Overall, living in co-housing communities was evaluated as an “extremely positive circumstance” despite the fact that the emergency worsened socialization.
Direct Improvement in the Combustion Chamber and the Radiant Surface to Reduce the Emission of Particles in Biomass Cooking Stoves Used in Araucanía, Chile
Authors: Betancourt Astete Robinson , Gutiérrez-Cáceres Nicolás , Muñoz-Catalán Marcela , Mora-Chandia Tomas
Published: June 2021

Solid particle emissions from burning wood in three internal combustion biomass cooking stoves commonly used in southern Chile were compared. Each stove was used to show differences in sealing systems, combustion chamber shape, and heating surfaces in order to optimize biomass combustion and the energy produced at a low manufacturing cost. The influence of cooking stove design along with particle and gas emissions that resulted from the biomass combustion within the cooking stove was investigated in this study. Levels of diverse atmospheric contaminants, such as particulate matter, emission factor, NOx, CO2, and CO, and the temperature of the flue gases were determined with the Ch-28 method and UNE-EN 12815. The average emission of particulate matter was significantly reduced by modifying the geometry of the combustion chamber and heating surface of each stove, resulting in 5 g/h particle emissions in conventional equipment and 2 g/h in the improved equipment. In relation to gas emissions, there was a 25% maximum decrease in NOx gases and 35% in CO after modifying the heating surface of each stove. This background supports the evidence of technological improvement with high environmental impact and low economic cost for local manufacturers.
Implementation of Different MPPT Techniques in Solar PV Tree under Partial Shading Conditions
Authors: Pandiyan Pitchai , Saravanan Subramani , Prabaharan Natarajan , Tiwari Ramji , Chinnadurai Thangam , Babu Neelakandan Ramesh , Hossain Eklas
Published: June 2021

This paper presents the design and analytical modeling of the proposed solar photovoltaic standalone system under varying environmental conditions. The proposed system consists of a unique structure of a solar PV-tree, maximum power point tracking (MPPT) technique, and DC–DC converter. The output voltage acquired from the solar PV tree is low. A DC–DC boost converter is utilized to step-up the required amount of voltage level. In this paper, the appropriate duty cycle is obtained for extracting the optimum power from the solar PV tree by using various MPPT mechanisms such as perturb and observe (P&O), incremental conductance (INC), and a radial basis function network (RBFN)-based neural network (NN). The proposed solar photovoltaic tree-based energy harvesting system is designed and validated by using MATLAB/SIMULINK software and real-time application. The simulation results of the above-mentioned three techniques are compared with each other in order to show the effectiveness of the proposed system with RBFN. The RBFN-MPPT provides a significant improvement in tracking efficiency of 6.0% and 5.72% as compared with the P&O method and the INC method at 1000 W/m2 irradiance condition. From the simulation and real-time results, it is concluded that the RBFN-based NN provides better tracking efficiency and less oscillation as compared with the other two algorithms.