bluuebunny/crossref_metadata_2025 huggingface dataset:
Shifting Epistemologies, Shifting Our Stories—Where Might We Find Hope for a World on the Brink of Climate Catastrophe?
Authors: Hess Mary E.
Published: July 2022

In the early 1990s, David Orr wrote about the epistemological myths of North American culture, and offered ecological literacy as a form of resistance. In the same decade, Parker Palmer confronted dominant epistemologies in religious institutions, and retrieved early Christian frames by way of resistance. One was writing through the lens of environmental science, and one through the lens of the desert mothers and fathers of Christian history. Neither acknowledged the First Nations, Metis and Inuit epistemologies which offered similarly contesting frames. It may be too late, yet even in a moment of climate catastrophe there is hope that shifting our forms of knowing can invite pedagogical practices that transform our communities. This essay will articulate the congruence between these disparate and diverse stances as sacred ground within which to root embodied, theologically astute pedagogies for the 21st century. Several pragmatic exercises that have emerged as fruitful for learners seeking to embody compelling counter narratives are also offered.
Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method
Authors: Sigurdsson Jakob , Armannsson Sveinn E. , Ulfarsson Magnus O. , Sveinsson Johannes R.
Published: July 2022

The Copernicus Sentinel-2 (S2) constellation comprises of two satellites in a sun-synchronous orbit. The S2 sensors have three spatial resolutions: 10, 20, and 60 m. The Landsat 8 (L8) satellite has sensors that provide seasonal coverage at spatial resolutions of 15, 30, and 60 m. Many remote sensing applications require the spatial resolutions of all data to be at the highest resolution possible, i.e., 10 m for S2. To address this demand, researchers have proposed various methods that exploit the spectral and spatial correlations within multispectral data to sharpen the S2 bands to 10 m. In this study, we combined S2 and L8 data. An S2 sharpening method called Sentinel-2 Sharpening (S2Sharp) was modified to include the 30 m and 15 m spectral bands from L8 and to sharpen all bands (S2 and L8) to the highest resolution of the data, which was 10 m. The method was evaluated using both real and simulated data.
Data Reliability Enhancement for Wind-Turbine-Mounted Lidars
Authors: Angelou Nikolas , Sjöholm Mikael
Published: July 2022

Wind lidars can be used on wind turbines to monitor the inflow for power curve verification and for control purposes. In these applications, the lidar is most often placed on the nacelle behind the rotating blades, which occasionally intercept the line-of-sight measurements, resulting in decreased data availability or biased wind measurements. Distinguishing the wind from the blade signals is challenging for continuous-wave Doppler lidar observations. Here, we present a method that provides a more effective filtering than a typical filter relying on the strength of the backscattered signal. The method proposed is based on modelling the radial speed contribution generated by the wind turbine blades, and we present the results of a case study using a scanning wind lidar installed on the nacelle of an 850 kW wind turbine. We show that using the methodology proposed, we can optimize the identification of wind measurements, and thus, the data reliability of wind-turbine-mounted continuous-wave Doppler lidars is enhanced. Furthermore, the method is useful also for assessing the location and the alignment of a nacelle wind lidar in relation to a wind turbine’s rotor, which improves the accuracy of the inflow data and allows for a more efficient monitoring of the performance of a wind turbine.
Contrasting Forest Loss and Gain Patterns in Subtropical China Detected Using an Integrated LandTrendr and Machine-Learning Method
Authors: Shen Jianing , Chen Guangsheng , Hua Jianwen , Huang Sha , Ma Jiangming
Published: July 2022

China has implemented a series of forestry law, policies, regulations, and afforestation projects since the 1970s. However, their impacts on the spatial and temporal patterns of forests have not been fully assessed yet. The lack of an accurate, high-resolution, and long-term forest disturbance and recovery dataset has impeded this assessment. Here we improved the forest loss and gain detections by integrating the LandTrendr change detection algorithm with the Random Forest (RF) machine-learning method and applied it to assess forest loss and gain patterns in the Zhejiang, Jiangxi, and Guangxi Provinces of the subtropical vegetation in China. The accuracy evaluation indicated that our approach can adequately detect the spatial and temporal distribution patterns in forest gain and loss, with an overall accuracy of 93% and the Kappa coefficient of 0.89. The forest loss area was 8.30 × 104 km2 in the Zhejiang, Jiangxi, and Guangxi Provinces during 1986–2019, accounting for 43.52% of total forest area in 1986, while the forest gain area was 20.25 × 104 km2, accounting for 106.19% of total forest area in 1986. Although the interannual variation patterns were similar among three provinces, the forest loss and gain area and the magnitude of change trends were significantly different. Guangxi has the largest forest loss and gain area and increasing trends, followed by Jiangxi, and the least in Zhejiang. The variations in annual forest loss and gain area can be mostly explained by the timelines of major forestry policies and regulations. Our study would provide an applicable method and data for assessing the impacts of forest disturbance events and forestry policies and regulations on the spatial and temporal patterns of forest loss and gain in China, and further contributing to regional and national forest carbon and greenhouse gases budget estimations.
A Geomatic Approach to the Preservation and 3D Communication of Urban Cultural Heritage for the History of the City: The Journey of Napoleon in Venice
Authors: Fiorini Giulia , Friso Isabella , Balletti Caterina
Published: July 2022

The use of historical maps in a digital environment can give considerable support to the study of the history of cities. It allows you to combine information from different sources, processed according to different geomatic techniques, to provide a reconstruction of urban configurations of the past and their comparison with iconographic and textual documentation of the same period. The aim of the research is to try to make the knowledge of a historical event easily accessible by converging within a simple model the various sources on which the reconstruction itself is based. This paper deals with the reconstruction of the ephemeral architecture created for Napoleon’s visit to Venice through the generation of 3D virtual models. The reconstruction was approached through a rigorous method, inserting these models into the context for which they were conceived. The generation of the historical city model, taking advantage of the algorithms of structure from motion applied to photogrammetry, made it possible to compare it with what was shown by the old paintings depicting the event. Virtual models processed within the GIS environment have been uploaded online thanks to the use of WebGIS. We chose to share the research results on the internet to allow users to avail themselves of a space that no longer exists from within it, going beyond the pictorial images of the past, overcoming communication through rendering and videos. The simultaneous application of methods and techniques related to the various components of geomatics within the digital environment has enabled the operation of a faithful reconstruction of reality, bringing to light past urban scenarios that no longer exist and are only known through paintings.
How to Include Crowd-Sourced Photogrammetry in a Geohazard Observatory—Case Study of the Giant’s Causeway Coastal Cliffs
Authors: Jaud Marion , Le Dantec Nicolas , Parker Kieran , Lemon Kirstin , Lendre Sylvain , Delacourt Christophe , Gomes Rui C.
Published: July 2022

The Causeway Coast World Heritage Site (Northern Ireland) is subject to rockfalls occurring on the coastal cliffs, thus raising major safety concerns given the number of tourists visiting the site. However, such high tourist frequentation makes this site favorable to implement citizen science monitoring programs. Besides allowing for the collection of a larger volume of data, better distributed spatially and temporally, citizen science also increases citizens’ awareness—in this case, about risks. Among citizen science approaches, Structure-from-Motion photogrammetry based on crowd-sourced photographs has the advantage of not requiring any particular expertise on the part of the operator who takes photos. Using a mock citizen survey for testing purposes, this study evaluated different methods relying on crowd-sourced photogrammetry to integrate surveys performed by citizens into a landslide monitoring program in Port Ganny (part of the touristic site of the Giant’s Causeway). Among the processing scenarios that were tested, the Time-SIFT method allows the use of crowd-sourced data in a very satisfactory way in terms of reconstruction quality, with a standard deviation of 8.6 cm.
Calibration and Validation of CYGNSS Reflectivity through Wetlands’ and Deserts’ Dielectric Permittivity
Authors: Molina Iñigo , Calabia Andrés , Jin Shuanggen , Edokossi Komi , Wu Xuerui
Published: July 2022

The reflection of Global Navigation Satellite Systems (GNSS) signals, namely GNSS-Reflectometry (GNSS-R), has recently proven to be able to monitor land surface properties in the microwave spectrum, at a global scale, and with very low revisiting time. Moreover, this new technique has numerous additional advantages, including low cost, low power consumption, lightweight and small payloads, and near real-time massive data availability, as compared to conventional monostatic microwave remote sensing. However, the GNSS-R surface reflectivity values estimated through the bistatic radar equation, and the Fresnel coefficients have shown a lack of coincidence with real surface reflectivity data, mostly due to calibration issues. Previous studies have attempted to avoid this matter with direct regression methods between uncalibrated GNSS-R reflectivity data and external soil moisture content (SMC) products. However, calibration of GNSS-R reflectivity used in traditional inversion models is still a challenge, such as those to estimate SMC, freeze/thaw, or biomass. In this paper, a successful procedure for GNSS-R reflectivity calibration is established using data from the CYGNSS (Cyclone GNSS) constellation. The scale and bias parameters are estimated from the theoretical dielectric properties of water and dry sand, which are well-known and empirically validated values. We employ four calibration areas that provide maximum range limits of reflectivity, such as deserts and wetlands. The CYGNSS scale factor and the bias parameter resulted in a = 3.77 and b = 0.018, respectively. The derived scale and bias parameters are applied to the CYGNSS dataset, and the retrieved SMC values through the Fresnel reflection coefficients are in excellent agreement with the Soil Moisture Active Passive (SMAP) SMC product. Then, the SMAP SMC is used as a reference true value, and provides a standard linear regression with an R-square coefficient of 0.803, a root mean square error (RMSE) of 0.084, and a Pearson’s correlation coefficient of 0.896.
A Compact Dual Band MIMO Dielectric Resonator Antenna with Improved Performance for mm-Wave Applications
Authors: Alanazi Meshari D. , Khamas Salam K.
Published: July 2022

A compact multiple-input-multiple-output (MIMO) dielectric resonator antenna (DRA) that is suitable for internet of things (IoT) sensor networks is proposed with reduced coupling between elements. Two rectangular-shaped DRAs have been placed on the opposite sides of a Rogers substrate and each is fed using a coplanar waveguide (CPW) feed with slots etched in a dedicated metal ground plane that is located under the DRA. Moreover, locating the elements at the opposite sides of the substrate has improved the isolation by 27 dB without the need to incorporate additional complex structures, which has reduced the overall antenna size. Furthermore, a dual band operation is achieved since each antenna resonates at two frequencies: 28 GHz and 38 GHz with respective impedance matching bandwidths of 18% and 13%. As a result, the corresponding data rates are also increased independently. In addition to the advantages of improved isolation, compact size and dual band operation, the proposed configuration offers a diversity gain (DG), envelope correlation coefficient (ECC) and channel capacity loss (CCL) of 9.98 dB, 0.007, 0.06 bits/s/Hz over the desired bands, respectively. A prototype has been built with good agreement between simulated and measured results.
RESEKRA: Remote Enrollment Using SEaled Keys for Remote Attestation
Authors: Gómez-Marín Ernesto , Parrilla Luis , Mauro Gianfranco , Escobar-Molero Antonio , Morales Diego P. , Castillo Encarnación
Published: July 2022

This paper presents and implements a novel remote attestation method to ensure the integrity of a device applicable to decentralized infrastructures, such as those found in common edge computing scenarios. Edge computing can be considered as a framework where multiple unsupervised devices communicate with each other with lack of hierarchy, requesting and offering services without a central server to orchestrate them. Because of these characteristics, there are many security threats, and detecting attacks is essential. Many remote attestation systems have been developed to alleviate this problem, but none of them can satisfy the requirements of edge computing: accepting dynamic enrollment and removal of devices to the system, respecting the interrupted activity of devices, and last but not least, providing a decentralized architecture for not trusting in just one Verifier. This security flaw has a negative impact on the development and implementation of edge computing-based technologies because of the impossibility of secure implementation. In this work, we propose a remote attestation system that, through using a Trusted Platform Module (TPM), enables the dynamic enrollment and an efficient and decentralized attestation. We demonstrate and evaluate our work in two use cases, attaining acceptance of intermittent activity by IoT devices, deletion of the dependency of centralized verifiers, and the probation of continuous integrity between unknown devices just by one signature verification.
Integrated Navigation Algorithm Based on Multiple Fading Factors Kalman Filter
Authors: Sun Bo , Zhang Zhenwei , Liu Shicai , Yan Xiaobing , Yang Chengxu
Published: July 2022

An integrated navigation algorithm based on a multiple fading factors Kalman filter (MFKF) is proposed to solve the problems that the Kalman filtering (KF) algorithm easily brings about diffusion when the model becomes a mismatched or noisy, and the MFKF accuracy is reduced when the fading factor is overused. Based on the innovation covariance theory, the algorithm designs an improved basis for judging filtering anomalies and makes the timing of the introduction of the fading factor more reasonable by switching the filtering state. Different from the traditional basis of filter abnormality judgment, the improved judgment basis adopts a recursive way to continuously update the estimated value of the innovation covariance to improve the estimation accuracy of the innovation covariance, and an empirical reserve factor for the judgment basis is introduced to adapt to practical engineering applications. By establishing an inertial navigation system (INS)/global navigation satellite system (GNSS) integrated navigation model, the results show that the average positioning accuracy of the proposed algorithm is improved by 26.52% and 7.48%, respectively, compared with the KF and MFKF, and shows better robustness and self-adaptability.
A Two-Stage Feature Point Detection and Marking Approach Based on the Labeled Multi-Bernoulli Filter
Authors: Yang Jiahui , Liu Weifeng
Published: July 2022

In recent years, various algorithms using random finite sets (RFS) to solve the issue of simultaneous localization and mapping (SLAM) have been proposed. Compared with the traditional method, the advantage of the RFS method is that it can avoid data association, landmark appearance and disappearance, missed detections, and false alarms in Bayesian recursion. There are many problems in the existing robot SLAM methods, such as low estimation accuracy, poor back-end optimization, etc. On the basis of previous studies, this paper presents a labeled random finite set (L-RFS) SLAM method. We describe a scene where the sensor moves along a given path and avoids obstacles based on the L-RFS framework. Then, we use the labeled multi-Bernoulli filter (LMB) to estimate the state of the sensor and feature points. At the same time, the B-spline curve is used to smooth the obstacle avoidance path of the sensor. The effectiveness of the algorithm is verified in the final simulation.
Underwater Acoustic Signal Detection Using Calibrated Hidden Markov Model with Multiple Measurements
Authors: You Heewon , Byun Sung-Hoon , Choo Youngmin
Published: July 2022

It is important to find signals of interest (SOIs) when operating sonar systems. A threshold-based method is generally used for SOI detection. However, it induces a high false alarm rate at a low signal-to-noise ratio. On the other side, machine-learning-based detection is performed to obtain more reliable detection results using abundant training data, costing intensive time and labor. We propose a method with favorable detection performance by using a hidden Markov model (HMM) for sequential acoustic data, which requires no separate training data. Since the detection results from HMM are significantly affected by the random initial parameters of HMM, the genetic algorithm (GA) is adopted to reduce the sensitivity of the initial parameters. The tuned initial parameters from GA are used as a start point for the subsequent Baum–Welch algorithm updating the HMM parameters. Furthermore, multiple measurements from arrays are exploited both in determining the proper initial parameters with GA and updating the parameters with the Baum–Welch algorithm. In contrast to the standard random selection of the initial point with single measurement, a stable initial point setting by the GA ensures improved SOI detections with the Baum–Welch algorithm using the multiple measurements, which are demonstrated in passive and active acoustic data. Particularly, the proposed method shows the most confidential detection in finding weak elastic surface waves from target, compared to existing methods such as conventional HMM.
Introducing the CYSAS-S3 Dataset for Operationalizing a Mission-Oriented Cyber Situational Awareness
Authors: Medenou Choumanof Roumen Daton , Llopis Sanchez Salvador , Calzado Mayo Victor Manuel , Garcia Balufo Miriam , Páramo Castrillo Miguel , González Garrido Francisco José , Luis Martinez Alvaro , Nevado Catalán David , Hu Ao , Rodríguez-Bermejo David Sandoval , Pasqual de Riquelme Gerardo Ramis , Sotelo Monge Marco Antonio , Berardi Antonio , De Santis Paolo , Torelli Francesco , Maestre Vidal Jorge
Published: July 2022

The digital transformation of the defence sector is not exempt from innovative requirements and challenges, with the lack of availability of reliable, unbiased and consistent data for training automatisms (machine learning algorithms, decision-making, what-if recreation of operational conditions, support the human understanding of the hybrid operational picture, personnel training/education, etc.) being one of the most relevant gaps. In the context of cyber defence, the state-of-the-art provides a plethora of data network collections that tend to lack presenting the information of all communication layers (physical to application). They are synthetically generated in scenarios far from the singularities of cyber defence operations. None of these data network collections took into consideration usage profiles and specific environments directly related to acquiring a cyber situational awareness, typically missing the relationship between incidents registered at the hardware/software level and their impact on the military mission assets and objectives, which consequently bypasses the entire chain of dependencies between strategic, operational, tactical and technical domains. In order to contribute to the mitigation of these gaps, this paper introduces CYSAS-S3, a novel dataset designed and created as a result of a joint research action that explores the principal needs for datasets by cyber defence centres, resulting in the generation of a collection of samples that correlate the impact of selected Advanced Persistent Threats (APT) with each phase of their cyber kill chain, regarding mission-level operations and goals.
Responsivity and NEP Improvement of Terahertz Microbolometer by High-Impedance Antenna
Authors: Aji Arie Pangesti , Satoh Hiroaki , Apriono Catur , Rahardjo Eko Tjipto , Inokawa Hiroshi
Published: July 2022

The antenna-coupled microbolometer with suspended titanium heater and thermistor was attractive as a terahertz (THz) detector due to its structural simplicity and low noise levels. In this study, we attempted to improve the responsivity and noise-equivalent power (NEP) of the THz detector by using high-resistance heater stacked on the meander thermistor. A wide range of heater resistances were prepared by changing the heater width and thickness. It was revealed that the electrical responsivity and NEP could be improved by increasing the heater’s resistance. To make the best use of this improvement, a high-impedance folded dipole antenna was introduced, and the optical performance at 1 THz was found to be better than that of the conventional halfwave dipole antenna combined with a low-resistance heater. Both the electrical and optical measurement results indicated that the increase in heater resistance could reduce the thermal conductance in the detector, thus improved the responsivity and NEP even if the thermistor resistance was kept the same.
A Standardized Morpho-Functional Classification of the Planet’s Humipedons
Authors: Zanella Augusto , Ponge Jean-François , Jabiol Bernard , Van Delft Bas , De Waal Rein , Katzensteiner Klaus , Kolb Eckart , Bernier Nicolas , Mei Giacomo , Blouin Manuel , Juilleret Jérôme , Pousse Noémie , Stanchi Silvia , Cesario Fernando , Le Bayon Renée-Claire , Tatti Dylan , Chersich Silvia , Carollo Luca , Englisch Michael , Schrötter Anna , Schaufler Judith , Bonifacio Eleonora , Fritz Ines , Sofo Adriano , Bazot Stéphane , Lata Jean-Christophe , Iffly Jean-Francois , Wetzel Carlos E. , Hissler Christophe , Fabiani Ginevra , Aubert Michael , Vacca Andrea , Serra Gianluca , Menta Cristina , Visentin Francesca , Cools Nathalie , Bolzonella Cristian , Frizzera Lorenzo , Zampedri Roberto , Tomasi Mauro , Galvan Paola , Charzynski Przemyslaw , Zakharchenko Elina , Waez-Mousavi Seyed Mohammad , Brun Jean-Jacques , Menardi Roberto , Fontanella Fausto , Zaminato Nicola , Carollo Silvio , Brandolese Alessio , Bertelle Michele , Zanella Gaétan , Bronner Thomas , Graefe Ulfert , Hager Herbert
Published: July 2022

It was time to take stock. We modified the humipedon classification key published in 2018 to make it easier and more practical. This morpho-functional taxonomy of the topsoil (humipedon) was only available in English; we also translated it into French and Italian. A standardized morpho-functional classification of humipedons (roughly the top 30–40 cm of soil: organic and organomineral surface horizons) would allow for a better understanding of the functioning of the soil ecosystem. This paper provides the founding principles of the classification of humipedon into humus systems and forms. With the recognition of a few diagnostic horizons, all humus systems can be determined. The humus forms that make up these humus systems are revealed by measuring the thicknesses of the diagnostic horizons. In the final part of the article, several figures represent the screenshots of a mobile phone or tablet application that allows for a fast recall of the diagnostic elements of the classification in the field. The article attempts to promote a standardized classification of humipedons for a global and shared management of soil at planet level.
User Interface Design Patterns for Infotainment Systems Based on Driver Distraction: A Colombian Case Study
Authors: Alarcón Juan , Balcázar Isabela , Collazos César A. , Luna Huizilopoztli , Moreira Fernando
Published: July 2022

In this paper, we present a set of nine user interface design patterns for in-vehicle infotainment systems centered on the content, interaction mode, style, shortcuts, and notifications of the system, which are built based on both theoretical support and an empirical pattern finding process. This empirical process consists in an exploratory test made with 10 users from an age range from 18 to 29 and with a minimum of 2 years of driving experience, who were asked to perform a set of 13 secondary tasks in the vehicle to identify recurrent problems, behavioral patterns, and best practices. The output of this exploratory test was used as the main data source for the design patterns consolidation. It is worth mentioning that the proposal of these patterns arose as an initiative to begin to consider factors that can affect the driver’s experience in the Latin American context. The set of design patterns has been validated via a content validation (as an exploratory study) by a panel of Latin American experts in the area of HCI and UX through the development of a prototype using the patterns as a tool for the redesign proposal of the infotainment systems tested during the empirical finding process.
Influence of a Novel Carbon-Based Nano-Material on the Thermal Conductivity of Mortar
Authors: Alexa-Stratulat Sergiu-Mihai , Covatariu Daniel , Toma Ana-Maria , Rotaru Ancuta , Covatariu Gabriela , Toma Ionut-Ovidiu
Published: July 2022

The paper presents the results of research work to assess the thermal conductivity of mortar incorporating a novel carbon-based nano-material (CBN). The data from the laboratory tests served as the starting point in training an artificial neural network (ANN) based on the Levenberg–Marquardt backpropagation algorithm that was used to predict the values of the thermal conductivity at later ages. The used CBNs were essential precursors of multi-walled carbon nano-tubes but different from their counterparts in the fact that they were capped at the ends. This configuration should result in lower surface tension and should prevent the bundling even without the use of surfactants and sonication. The obtained results show that the mortar mixes with CBN exhibit higher values for the thermal coefficient at early ages compared to the reference mix, even at very low percentages of CBN by weight of cement. The ANN is able to accurately predict the experimental results both at 28 days and at later ages. The obtained results should serve as the starting point for further investigations into the microstructure of cement-based materials enhanced with CBNs.
Spatiotemporal Variability in Water-Use Efficiency in Tianshan Mountains (Xinjiang, China) and the Influencing Factors
Authors: Chen Jun , Cao Liguo
Published: July 2022

Water-use efficiency (WUE) is a crucial physiological index in carbon–water interactions and is defined as the ratio of vegetation productivity to water loss. The variation in climatic variables and drought have the most significant effects on WUE and evapotranspiration (ET). Nevertheless, how WUE varies with climate factors and drought processes in the Tianshan Mountains (TMS) is still poorly understood. In the present work, we analyzed the spatiotemporal variations in WUE, and investigated the correlations between WUE, climate factors, and drought, in the study area. The results showed that, in the TMS during 2000–2020, annual net primary productivity (NPP) ranged from 147.9 to 189.4 gC·m−2, annual ET was in the range of 212.5–285.8 mm, and annual WUE ranged from 0.66 to 0.78 gC·kg−1·H2O. Both NPP and ET exhibited an increasing trend with some fluctuation, whereas WUE showed the opposite tendency during the study period. The obtained results demonstrated that the decrease in WUE was primarily because of the increase in ET. There were obvious differences in WUE, under different land-use types, caused by NPP and ET. However, the interannual variation in WUE showed small fluctuations and the dynamic process of WUE in each land-use type showed good consistency. Temperature and wind speed had a positive influence on WUE in the middle and eastern regions of the TMS. Precipitation also played a mainly positive role in enhancing WUE, especially on the northern slope of the TMS. There was strong spatial heterogeneity of the correlation coefficient (0.68, p < 0.05) between WUE and the temperature vegetation drought index (TVDI). Moreover, the slopes of WUE and TVDI showed good consistency in terms of spatial distribution, suggesting that drought had a significant impact on ecosystem WUE. This work will enhance the understanding of WUE variation, and provide scientific evidence for water resource management and sustainable utilization in the study area.
Demographic and Social Dimension of the COVID-19 Pandemic in Polish Cities: Excess Deaths and Residents’ Fears
Authors: Cieślińska Barbara , Janiszewska Anna
Published: July 2022

The aim of this article is to present the impact of the COVID-19 pandemic on demographic facts and social opinions regarding life in Polish cities under conditions of an epidemic threat. We point out that the way of informing the public about the threat of the disease was conducive to causing moral panic, and the imposed top-down methods of protection against infection and treatment methods, which were uniform for all, brought negative effects in the form of increased mortality and excess deaths. In this article, we present statistical data on the deaths of city dwellers with more than 100,000 inhabitants and the results of public opinion polls on changes in the perception of satisfaction with life in the city and fears related to the risk of disease. The pandemic has contributed to a deterioration in both health (excess deaths, health debt) and the broader quality of life. Previously, living in a large city in Poland provided a number of economic, social, and health benefits. The period of the pandemic and the methods used to fight this threat, have created a situation of moral panic and change unfavorable for urban residents. Based on statistical data and survey research, we attempt to verify this thesis.
Social Sustainability in Production Planning: A Systematic Literature Review
Authors: Trost Marco , Claus Thorsten , Herrmann Frank
Published: July 2022

Sustainable production includes economic, environmental, and social aspects. However, social sustainability has received less attention, especially compared to the economic aspects. Next to technical and organizational measures, social improvements within supply chains can also be achieved through suitable production planning. Within production planning, production programs are determined, and the assignment of available resources (e.g., employees) is specified. Thus, the utilization and workload of employees are defined. This systematic literature review investigates to what extent such employee-related social aspects are reflected in production planning and discusses whether economic aspects dominate them. For this, a Scopus database search was carried out and 76 identified approaches were analyzed and categorized regarding the occurring employee-related social aspects and their implementation. Thus far, the approaches mainly consider single aspects on single planning levels. A consideration of a broad set of aspects along the entire production planning has rarely been studied. In particular, health and safety aspects are considered on the levels of assembly line balancing and job rotation. However, their impact is primarily determined by the specific settings of the decision-maker. To support decision-makers, only a few studies have investigated the effects based on real application scenarios. Further potential might be an extended modeling of social and economic interdependencies and a consideration of employee-related social aspects in medium- to long-term production planning.
Post-Soviet Suburbanization as Part of Broader Metropolitan Change: A Comparative Analysis of Saint Petersburg and Riga
Authors: Sechi Guido , Zhitin Dmitrii , Krisjane Zaiga , Berzins Maris
Published: July 2022

Studies on post-socialist suburbanization, which originally focused on demand side dynamics and linear narratives of modernization, have progressively adopted more holistic approaches that consider the various dimensions and factors behind the phenomenon. However, there are still significant gaps and shortcomings affecting this research domain; studies encompassing demand side and supply side dynamics are rare, and so are comparative perspectives. The phenomenon has rarely been analyzed in the context of broader metropolitan change, together with other dynamics such as inner-city gentrification, degradation, or maintenance/regeneration of socialist era residential neighborhoods. This study addresses the mentioned gaps through a multi-dimensional comparative pilot analysis of suburban dynamics in Saint Petersburg and Riga. The analysis encompasses the spatial extent of demographic, socioeconomic, and housing market dynamics within the broader context of metropolitan change. The findings reveal a picture of a demographically and economically significant phenomenon with remarkable implications for macro- and micro-level socio-spatial segmentation; the distinctive features between the two cases are primarily due to migration dynamics and the short/medium term effects of the 2008 financial crisis on the real estate market and industry. Overall, the suburban option appears to be an attractive option for the demand side (in terms of an economic trade-off or societal aspiration) as well as a safe and profitable option for developers.
Influence of Flow Experience, Perceived Value and CSR in Craft Beer Consumer Loyalty: A Comparison between Mexico and The Netherlands
Authors: Guerra-Tamez Cristobal Rodolfo , Franco-García María-Laura
Published: July 2022

Craft beer production enterprises are categorized as micro-, small- and medium-sized enterprises (MSMEs) in Mexico and the Netherlands. As MSMEs, they encounter challenges to achieving consolidation; one main challenge is linked to deficient consumer-loyalty development. This work explores and compares the effects of experience of flow, perceived value and CSR in the development of loyalty in two different population samples of craft beer consumers: Mexico and the Netherlands. In total, 452 surveys were collected during experiential events, and the data were analyzed using multivariate partial-least-square (PLS) structural equation modeling. Our model results indicate that attention, concentration and notion of time influence flow experience in the same way in both countries. Experiential factors are stronger for the Mexican population. For the case of the Netherlands, perceived value had a higher effect on loyalty development and a lower impact on experiential factors. The CSR variable was only significant for the Dutch sample.
Root Water Uptake Patterns for Nitraria during the Growth Period Differing in Time Interval from a Precipitation Event in Arid Regions
Authors: Dong Haibiao , Hao Jing , Chen Zongyu , Zhang Guanghui , Yan Mingjiang , Wang Jinzhe
Published: July 2022

Vegetation root water uptake is one of the most central water transport processes along the soil-vegetation-atmosphere interface particularly in (semi-)arid ecosystems. The identification and quantification of root activities and water uptake patterns of arid vegetation remain challenging. This paper aims at the quantitative examination of water uptake behaviors of Nitraria, a prevalent desert species in arid environments, during the growth phase via a multivariate linear mixed model based on water stable isotopes, with a main focus on the time interval from a precipitation pulse. The observations indicate that the precipitation events exert periodic significant pulse-effects on vegetation water uptake through direct absorption (contribution of almost 75%) and activation of deep root activity at a certain depth. While in most occasions without rainfall, Nitraria relies on its extremely extensive shallow roots in surface-near lateral zone (contribution of about 60%) to extract massive soil as well as the hydraulic lifting mechanism to survive drought. Achievements would be beneficial to enhancing the understanding of entangled water transport processes and eco-hydrological feedbacks along soil-vegetation interface in arid ecosystems and contribute to a scientific allocation to water resources with the consideration of ecological protection.
A Bibliometric Analysis of Blockchain Technology Research Using VOSviewer
Authors: Kuzior Aleksandra , Sira Mariya
Published: July 2022

Blockchain technology remains popular for several reasons. The main one is that it has facilitated the rise of digital currencies over the past several years and many other uses of non-crypto currency. There is a belief that the technology itself could far exceed cryptocurrencies by its impact. Thus, researchers are still discovering the real potential of blockchain. This study aims to conduct a comprehensive blockchain analysis with a bibliometric study. The data was retrieved from the Scopus database and was analyzed using the VOSviewer software, developed at Leiden University’s Centre for Science and Technology Studies (CWTS), Leiden University, the Netherlands. The study is based on the analysis of 1842 documents published in the 2007–2021 period using Scopus. From the visualization, three main groups of six clusters are generated. The red area includes topics related to blockchain technology, supply chain management, and sustainable development. The green cluster stands for such keywords as blockchains, smart contracts, electronic money, and Bitcoin and Ethereum. The blue cluster area focuses on issues related to artificial intelligence, big data, health care, and COVID-19. The analysis helps to improve the quality of the review by directing researchers to the most significant documents and mapping areas of publications.
Service Trust and Customer Loyalty in China’s Hotel Services: The Causal Role of Commitment
Authors: Xu Jialei
Published: July 2022

The hotel industry experienced substantial economic losses during the COVID-19 pandemic, and it is only recently that there has been a return to normal. In order to recover those losses, hotel managers are taking competitive actions focused on customer trust as a factor of utmost importance to guarantee customer commitment so that uncertainty and risk can be reduced. In particular, it is necessary to confirm the importance of relationship quality management for target customers in order to secure long-term profits for upscale hotels. Therefore, the purpose of this study is to confirm the antecedents of service trust, the effect of service trust on loyalty through commitment factors, and the moderating effect of length of relationship. For this purpose, a total of 303 questionnaires were collected from Chinese consumers who have experienced upscale hotel service, and empirical analysis was conducted on the data using structural equation model analysis. The results of this study confirmed the importance of trust in front-line employees to build service trust, the different influences of factors of commitment and loyalty, and the moderating effect of length of relationship. Furthermore, efficient customer relationship management can be achieved by classifying the customer’s commitment type.
Measuring the Policy Effectiveness of China’s New-Energy Vehicle Industry and Its Differential Impact on Supply and Demand Markets
Authors: Wang Di , Li Yuman
Published: July 2022

To promote the precise governance of China’s new-energy vehicle (NEV) industry, this paper quantitatively analyzes 204 policy texts on the NEV industry in China since 2007 and constructs an evaluation system of policy effectiveness from three dimensions of policy attributes, policy objectives, and policy measures to reveal the effectiveness and evolutionary trends of China’s NEV industry policies. In addition, this paper explores the two-way effects of different types of policy measures on the NEV supply and demand markets through an econometric model to reveal the differential impact effectiveness of various policy instruments in China’s NEV industry. The results indicate that China’s NEV industry has changed from “government-driven” to “government-driven + market-driven”, and the multi-sectoral policy coordination needs to be further improved; the dynamic evolution over the years reveals a similar pattern of change in the total effectiveness of policy issuance as influenced by the number of policies; the quantity of patents in China is large but the quality of patents is insufficient, and an overall problem of low level of core technology is being faced; taxation and subsidy measure, technical innovation measures, social guidance measures, and environmental support measures all effectively promote the development of the supply-side market, while taxation and subsidy measures, social guidance measures and legal regulation measures can better promote the development of the demand-side market; the impact of financial support measures on both supply and demand-side markets is not significant.
Consumer Perceptions about the Value of Short Food Supply Chains during COVID-19: Atlantic Canada Perspective
Authors: Maas Melissa , Abebe Gumataw Kifle , Hartt Christopher M. , Yiridoe Emmanuel K.
Published: July 2022

The recent global COVID-19 pandemic has revealed weaknesses in the global food system, with short food supply chains (SFSCs) and long food supply chains (LFSC) being impacted differently. This raises the question as to whether the pandemic has contributed to a greater interest in and demand for locally produced foods. To answer this question, a study was undertaken to explore how consumers perceive SFSCs in delivering social, economic, and environmental benefits and whether these perceptions have been enhanced during the pandemic. A survey was carried out among consumers in Atlantic Canada who purchase food from SFSCs. Based on 80 valid responses, the findings revealed that consumers perceive SFSCs to deliver more social benefits post-pandemic than they thought SFSCs did before the pandemic. Supporting the local economy, food safety, freshness, and product quality are key motivators of shopping from SFSCs. Consumer perceptions about the sustainability of SFSCs did not vary much based on sociodemographic factors. Also, the COVID-19 pandemic did not significantly alter consumer spending and frequency of shopping from SFSCs. This may affect the SFSCs’ ability to expand operations beyond current levels and suggest the complementarity between SFSCs and LFSCs for more sustainable consumption patterns. The study provides valuable insights into the attractiveness of the local food businesses and the effect of unexpected events such as COVID-19 on consumer behaviors.
Technical College Students’ Practical Performance Anxiety during Online Learning: Difference in Gender and Average Time of Online Learning
Authors: Zhang Xu , Zhou Fangyi , Xu Jinlei
Published: July 2022

The person-artifact-task model provided us with a method to consider the practical performance anxiety (PPA) of technical college students who were working on a computer-related task via online learning. This study investigated 474 technical college students’ PPA in online courses without hands-on demonstration (PPAOC-without-HD) and with hands-on demonstration (PPAOC-with-HD), and it explored whether their PPA varied according to gender and average time spent on online learning. The results indicated that the students’ two types of PPA (PPAOC-without-HD and PPAOC-with-HD) varied significantly by gender and across the different online learning time groups. The average levels of participants’ two types of PPA were both high, and their PPAOC-without-HD was higher than their PPAOC-with-HD. Both types of PPA for females were significantly higher than those for males. Participants’ PPAOC-with-HD showed a significant difference for the average time of online learning. The findings of this study will be of value to educators who need to design and carry out online learning courses for technical college students.
Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers
Authors: Khudhair Mohammed , Ragab Muhammad , AboRas Kareem M. , Abbasy Nabil H.
Published: July 2022

This paper proposes a new combined controller, the proportional integral derivative-second derivative with a proportional derivative (PIDD2-PD), to improve the frequency response of a multi-area interconnected power system with multiple generating units linked to it. The optimum gains of the presented controller are well-tuned using a wild horse optimizer (WHO), a modern metaheuristic optimization approach. The main study is a two-area-linked power system with varied conventional and renewable generating units. The physical constraints of the speed turbines and governors are considered. The WHO optimization algorithm is proven to outperform various other optimization approaches, such as the whale optimization algorithms (WOA) and chimp optimization algorithms (ChOA). The efficacy of the proposed WHO-based PIDD2-PD controller is evaluated by comparing its performance to other controllers in the literature (cascaded proportional integral derivative-tilted integral derivative (PID-TID), integral derivative-tilted (ID-T) controller). Multiple and varied scenarios are applied in this work to test the proposed controller’s sturdiness to various load perturbations (step, random, and multi-step), renewable energy source penetration, and system parameter variations. The results are provided as time-domain simulations run using MATLAB/SIMULINK. The simulation results reveal that the suggested controller outperforms other structural controllers in the dynamic response of the system in terms of settling time, maximum overshoot, and undershoot values, with an improvement percentage of 70%, 73%, and 67%, respectively.