bluuebunny/crossref_metadata_2025 huggingface dataset:
Viṣṇu the Saviour: On the Festival of the Romantic Quarrel (praṇayakalahotsava) in the Pāñcarātra saṃhitās
Authors: Dębicka-Borek Ewa
Published: August 2022

Built on the theme of the lovers’ quarrel that eventually ends in reconciliation, the Festival of the Romantic Quarrel (praṇayakalahotsava) displays a wide scope of meanings, so far discussed primarily in regard to its current reenactment in the South Indian Vaiṣṇava temples dedicated to Viṣṇu and his wife, Lakṣmī/Śrī. The paper explores the rare treatments of the festival found in the Pāñcarātra saṃhitās, namely the texts which serve as a prescriptive base for the ritual order in many of these temples. The analysis aims to demonstrate how the account of this particular festival might have served to channel ideas connected to a soteriological doctrine of self-surrender to Viṣṇu (prapatti), perhaps as a result of reinterpreting the teachings of the Pāñcarātra under the influence of the Śrīvaiṣṇava tradition.
Infrastructure-Aided Localization and State Estimation for Autonomous Mobile Robots
Authors: Flögel Daniel , Bhatt Neel Pratik , Hashemi Ehsan
Published: August 2022

A slip-aware localization framework is proposed for mobile robots experiencing wheel slip in dynamic environments. The framework fuses infrastructure-aided visual tracking data (via fisheye lenses) and proprioceptive sensory data from a skid-steer mobile robot to enhance accuracy and reduce variance of the estimated states. The slip-aware localization framework includes: the visual thread to detect and track the robot in the stereo image through computationally efficient 3D point cloud generation using a region of interest; and the ego motion thread which uses a slip-aware odometry mechanism to estimate the robot pose utilizing a motion model considering wheel slip. Covariance intersection is used to fuse the pose prediction (using proprioceptive data) and the visual thread, such that the updated estimate remains consistent. As confirmed by experiments on a skid-steer mobile robot, the designed localization framework addresses state estimation challenges for indoor/outdoor autonomous mobile robots which experience high-slip, uneven torque distribution at each wheel (by the motion planner), or occlusion when observed by an infrastructure-mounted camera. The proposed system is real-time capable and scalable to multiple robots and multiple environmental cameras.
Exploring the Potential of SCOPE Model for Detection of Leaf Area Index and Sun-Induced Fluorescence of Peatland Canopy
Authors: Rastogi Anshu , Antala Michal , Prikaziuk Egor , Yang Peiqi , van der Tol Christiaan , Juszczak Radoslaw
Published: August 2022

The study of peatland is challenging due to the water saturation and evergreen mixed vegetation that ranges from simple forms of plants such as mosses to higher forms of plants such as cranberries, grasses, etc. The changing water level through the growing season makes the peatland vegetation very dynamic. In this work, we have used ground-level remote-sensing signals to understand the dynamic nature of peatland vegetation. We have also estimated the leaf area index (LAI) and Sun-Induced fluorescence (SIF) through the Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model. The estimated LAI and SIF were compared with the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Near-Infrared Reflectance of vegetation (NIRv), and measured SIF. The modeled LAI was observed to be significantly correlated with NDVI, EVI, and NIRv, whereas a good correlation was observed between measured and modeled SIF. Along with showing the dynamic behavior of peatland vegetation, the study indicates that SCOPE in its inverted form can be used to estimate reflectance-based LAI for peatland, which can be more reliable to present biomass and productivity of peatland ecosystem in comparison to transmittance-based LAI measurement for such ecosystem. The good correlation between measured and modeled SIF at 760 nm indicates that a reliable SIF value can be estimated through the SCOPE model for a complex ecosystem such as peatland, which can be very helpful in the absence of high-resolution hyperspectral data (usually used for SIF measurements).
Quantifying Spatiotemporal Heterogeneities in PM2.5-Related Health and Associated Determinants Using Geospatial Big Data: A Case Study in Beijing
Authors: Zhu Yanrong , Wang Juan , Meng Bin , Ji Huimin , Wang Shaohua , Zhi Guoqing , Liu Jian , Shi Changsheng
Published: August 2022

Air pollution has brought about serious challenges to public health. With the limitations of available data, previous studies overlooked spatiotemporal heterogeneities in PM2.5-related health (PM2.5-RH) and multiple associated factors at the subdistrict scale. In this research, social media Weibo data was employed to extract PM2.5-RH based on the Bidirectional Encoder Representations from Transformers (BERT) model, in Beijing, China. Then, the relationship between PM2.5-RH and eight associated factors was qualified based on multi-source geospatial big data using Geographically Weighted Regression (GWR) models. The results indicate that the PM2.5-RH in the study area showed a spatial pattern of agglomeration to the city center and seasonal variation in the spatially non-stationary effects. The impacts of varied factors on PM2.5-RH were also spatiotemporally heterogeneous. Specifically, nighttime light (NTL), population density (PD) and the normalized difference built-up index (NDBI) had outstanding effects on PM2.5-RH in the four seasons, but with spatial disparities. The impact of the normalized difference vegetation index (NDVI) on PM2.5-RH was significant in summer, especially in the central urban areas, while in winter, the contribution of the air quality index (AQI) was increased. This research further demonstrates the feasibility of using social media data to indicate the effect of air pollution on public health and provides new insights into the seasonal impacts of associated driving factors on the health effects of air pollution.
Temperature Contributes More than Precipitation to Runoff in the High Mountains of Northwest China
Authors: Fan Mengtian , Xu Jianhua , Chen Yaning , Fan Meihui , Yu Wenzheng , Li Weihong
Published: August 2022

In alpine areas in Northwest China, such as the Tianshan Mountains, the lack of climate data (because of scarce meteorological stations) makes it difficult to assess the impact of climate change on runoff. The main contribution of this study was to develop an integrated method to assess the impact of climate change on runoff in data-scarce high mountains. Based on reanalysis products, this study firstly downscaled climate data using machine learning algorithms, then developed a Batch Gradient Descent Linear Regression to calculate the contributions of temperature and precipitation to runoff. Applying this method to six mountainous basins originating from the Tianshan Mountains, we found that climate changes in high mountains are more significant than in lowlands. In high mountains, the runoff changes are mainly affected by temperature, whereas in lowlands, precipitation contributes more than temperature to runoff. The contributions of precipitation and temperature to runoff changes were 20% and 80%, respectively, in the Kumarik River. The insights gained in this study can guide other studies on climate and hydrology in high mountain basins.
Monitoring Lake Volume Variation from Space Using Satellite Observations—A Case Study in Thac Mo Reservoir (Vietnam)
Authors: Pham-Duc Binh , Frappart Frederic , Tran-Anh Quan , Si Son Tong , Phan Hien , Quoc Son Nguyen , Le Anh Pham , Viet Bach Do
Published: August 2022

This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016–2021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50–100 km2, while its water level varies in the range 202–217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between −0.3 and 0.4 km3 month−1, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 month−1). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes’ water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.
Global Multi-Scale Information Fusion for Multi-Class Object Counting in Remote Sensing Images
Authors: Gao Junyu , Gong Maoguo , Li Xuelong
Published: August 2022

In recent years, object counting has been investigated and has made significant progress under a surveillance-view. However, there exists only a few works focusing on the remote sensing object density estimation, and the performance of existing methods is not promising. On the one hand, due to the imbalance distribution of targets in remote sensing images, the model might collapse, leading a severe degradation. On the other hand, the scale of targets in remote sensing images actually varies in real scenarios, which remains a challenge for counting objects accurately. To remedy the above problems, we propose an approach named “SwinCounter” for object counting in remote sensing. Moreover, we introduce a Balanced MSE Loss to pay more attention to the fewer samples, which alleviates the problem of imbalanced object labels. In addition, the attention mechanism in our SwinCounter can precisely capture multi-scale information. Thus, the model is aware of different scales of objects, which capture small and dense targetes more precisely. We build experiments on the RSOC dataset, achieving MAEs of 7.2, 151.5, 14.38, and 52.88 and MSEs of 10.1, 436.0, 22.7, and 74.82 on the Building, Small-Vehicle, Large-Vehicle, and Ship sub-datasets, which demonstrates the competitiveness and superiority of the proposed method.
Hyperspectral Panoramic Image Stitching Using Robust Matching and Adaptive Bundle Adjustment
Authors: Zhang Yujie , Mei Xiaoguang , Ma Yong , Jiang Xingyu , Peng Zongyi , Huang Jun
Published: August 2022

Remote-sensing developments such as UAVs heighten the need for hyperspectral image stitching techniques that can obtain information on a large area through various parts of the same scene. State-of-the-art approaches often suffer from accumulation errors and high computational costs for large-scale hyperspectral remote-sensing images. In this study, we aim to generate high-precision hyperspectral panoramas with less spatial and spectral distortion. We introduce a new stitching strategy and apply it to hyperspectral images. The stitching framework was built as follows: First, a single band obtained by signal-to-noise ratio estimation was chosen as the reference band. Then, a feature-matching method combining the SuperPoint and LAF algorithms was adopted to strengthen the reliability of feature correspondences. Adaptive bundle adjustment was also designed to eliminate misaligned artifact areas and occasional accumulation errors. Lastly, a spectral correction method using covariance correspondences is proposed to ensure spectral consistency. Extensive feature-matching and image-stitching experiments on several hyperspectral datasets demonstrate the superiority of our approach over the state of the art.
A Deep Q-Network-Based Algorithm for Multi-Connectivity Optimization in Heterogeneous Cellular-Networks
Authors: Hernández-Carlón Juan Jesús , Pérez-Romero Jordi , Sallent Oriol , Vilà Irene , Casadevall Ferran
Published: August 2022

The use of multi-connectivity has become a useful tool to manage the traffic in heterogeneous cellular network deployments, since it allows a device to be simultaneously connected to multiple cells. The proper exploitation of this technique requires to adequately configure the traffic sent through each cell depending on the experienced conditions. This motivates this work, which tackles the problem of how to optimally split the traffic among the cells when the multi-connectivity feature is used. To this end, the paper proposes the use of a deep reinforcement learning solution based on a Deep Q-Network (DQN) in order to determine the amount of traffic of a device that needs to be delivered through each cell, making the decision as a function of the current traffic and radio conditions. The obtained results show a near-optimal performance of the DQN-based solution with an average difference of only 3.9% in terms of reward with respect to the optimum strategy. Moreover, the solution clearly outperforms a reference scheme based on Signal to Interference Noise Ratio (SINR) with differences of up to 50% in terms of reward and up to 166% in terms of throughput for certain situations. Overall, the presented results show the promising performance of the DQN-based approach that establishes a basis for further research in the topic of multi-connectivity and for the application of this type of techniques in other problems of the radio access network.
Agreement of Sleep Measures—A Comparison between a Sleep Diary and Three Consumer Wearable Devices
Authors: Klier Kristina , Wagner Matthias
Published: August 2022

Nowadays, self-tracking and optimization are widely spread. As sleep is essential for well-being, health, and peak performance, the number of available consumer technologies to assess individual sleep behavior is increasing rapidly. However, little is known about the consumer wearables’ usability and reliability for sleep tracking. Therefore, the aim of the present study was to compare the sleep measures of wearable devices with a standardized sleep diary in young healthy adults in free-living conditions. We tracked night sleep from 30 participants (19 females, 11 males; 24.3 ± 4.2 years old). Each wore three wearables and simultaneously assessed individual sleep patterns for four consecutive nights. Wearables and diaries correlated substantially regarding time in bed (Range CCCLin: 0.74–0.84) and total sleep time (Range CCCLin: 0.76–0.85). There was no sufficient agreement regarding the measures of sleep efficiency (Range CCCLin: 0.05–0.34) and sleep interruptions (Range CCCLin: −0.02–0.10). Finally, these results show wearables to be an easy-to-handle, time- and cost-efficient alternative to tracking sleep in healthy populations. Future research should develop and empirically test the usability of such consumer sleep technologies.
Sleep Monitoring during Acute Stroke Rehabilitation: Toward Automated Measurement Using Multimodal Wireless Sensors
Authors: Chen Pin-Wei , O’Brien Megan K. , Horin Adam P. , McGee Koch Lori L. , Lee Jong Yoon , Xu Shuai , Zee Phyllis C. , Arora Vineet M. , Jayaraman Arun
Published: August 2022

Sleep plays a critical role in stroke recovery. However, there are limited practices to measure sleep for individuals with stroke, thus inhibiting our ability to identify and treat poor sleep quality. Wireless, body-worn sensors offer a solution for continuous sleep monitoring. In this study, we explored the feasibility of (1) collecting overnight biophysical data from patients with subacute stroke using a simple sensor system and (2) constructing machine-learned algorithms to detect sleep stages. Ten individuals with stroke in an inpatient rehabilitation hospital wore two wireless sensors during a single night of sleep. Polysomnography served as ground truth to classify different sleep stages. A population model, trained on data from multiple patients and tested on data from a separate patient, performed poorly for this limited sample. Personal models trained on data from one patient and tested on separate data from the same patient demonstrated markedly improved performance over population models and research-grade wearable devices to detect sleep/wake. Ultimately, the heterogeneity of biophysical signals after stroke may present a challenge in building generalizable population models. Personal models offer a provisional method to capture high-resolution sleep metrics from simple wearable sensors by leveraging a single night of polysomnography data.
Advances in Deep-Learning-Based Sensing, Imaging, and Video Processing
Authors: Zhang Yun , Kwong Sam , Xu Long , Zhao Tiesong
Published: August 2022

Deep learning techniques have shown their capabilities to discover knowledge from massive unstructured data, providing data-driven solutions for representation and decision making [...]
Improved A* Path Planning Method Based on the Grid Map
Authors: Ou Yangqi , Fan Yuexin , Zhang Xinglan , Lin Yanhua , Yang Weijing
Published: August 2022

In obstacle spatial path planning, the traditional A* algorithm has the problem of too many turning points and slow search speed. With this in mind, a path planning method that improves the A* (A-Star) algorithm is proposed. The mobile robot platform was equipped with a lidar and inertial measurement unit (IMU). The Hdl_graph_slam mapping algorithm was used to construct a two-dimensional grid map, and the improved A* algorithm was used for path planning of the mobile robot. The algorithm introduced the path smoothing strategy and safety protection mechanism, and it eliminated redundant points and minimal corner points by judging whether there were obstacles in the connection of two path nodes. The algorithm effectively improved the smoothness of the path and facilitated the robot to move in the actual operation. It could avoid the wear of the robot by expanding obstacles and improving the safety performance of the robot. Subsequently, the algorithm introduced the steering cost model and the adaptive cost function to improve the search efficiency, making the search purposeful and effective. Lastly, the effectiveness of the proposed algorithm was verified by experiments. The average path search time was reduced by 13%. The average search extension node was reduced by 11%. The problems of too many turning points and slow search speed of traditional A* algorithm in path planning were improved.
Glucometer Usability for 65+ Type 2 Diabetes Patients: Insights on Physical and Cognitive Issues
Authors: Pinelli Maria , Lettieri Emanuele , Boaretto Andrea , Casile Carlo , Citro Giuseppe , Zazzaro Bernardino , Ravazzoni Adriana
Published: August 2022

Background: Self-monitoring of blood glucose (SMBG) is of paramount relevance for type 2 diabetes mellitus (T2DM) patients. However, past evidence shows that there are physical and cognitive issues that might limit the usage of glucometers by T2DM patients aged 65 years and over. Objective: Our aim was to investigate the physical and cognitive issues related to the usage of glucometers by T2DM patients aged 65 years and over. Materials and Methods: The extant literature was analysed to define an original framework showing the logical nexus between physical and cognitive issues and quality of life. Then we collected evidence addressing the specific case of the Accu-Chek® Instant glucometer produced by Roche Diabetes Care GmbH, which implements new features claiming to improve usability. We conducted 30 interviews with T2DM patients aged 65 years and over, three interviews with senior nurses, and a focus group with three senior physicians and three senior nurses. Results: From the interviews, both patients and nurses declared that they were generally satisfied with the Accu-Chek® Instant glucometer’s characteristics. In the focus group, the results were commented on and, in the light of some diverging answers, improvements have been set up for future implementation. Conclusions: Our study produces evidence and future suggestions about the usage of glucometers by type 2 diabetes patients aged 65 years and over.
Design of a Reconfigurable Crop Scouting Vehicle for Row Crop Navigation: A Proof-of-Concept Study
Authors: Schmitz Austin , Badgujar Chetan , Mansur Hasib , Flippo Daniel , McCornack Brian , Sharda Ajay
Published: August 2022

Pest infestation causes significant crop damage during crop production, which reduces the crop yield in terms of quality and quantity. Accurate, precise, and timely information on pest infestation is a crucial aspect of integrated pest management practices. The current manual scouting methods are time-consuming and laborious, particularly for large fields. Therefore, a fleet of scouting vehicles is proposed to monitor and collect crop information at the sub-canopy level. These vehicles would traverse large fields and collect real-time information on pest type, concentration, and infestation level. In addition to this, the developed vehicle platform would assist in collecting information on soil moisture, nutrient deficiency, and disease severity during crop growth stages. This study established a proof-of-concept of a crop scouting vehicle that can navigate through the row crops. A reconfigurable ground vehicle (RGV) was designed and fabricated. The developed prototype was tested in the laboratory and an actual field environment. Moreover, the concept of corn row detection was established by utilizing an array of low-cost ultrasonic sensors. The RGV was successful in navigating through the corn field. The RGV’s reconfigurable characteristic provides the ability to move anywhere in the field without damaging the crops. This research shows the promise of using reconfigurable robots for row crop navigation for crop scouting and monitoring which could be modular and scalable, and can be mass-produced in quick time. A fleet of these RGVs would empower the farmers to make meaningful and timely decisions for their cropping system.
Facile Conversion of the Quinone-Semicarbazone Chromophore of Naftazone into a Fluorescent Quinol-Semicarbazide: Kinetic Study and Analysis of Naftazone in Pharmaceuticals and Human Serum
Authors: Gamal Mohammed , Ali Hazim M. , El-Shaheny Rania , Naguib Ibrahim A. , Alsalahat Izzeddin , El-Maghrabey Mahmoud
Published: August 2022

Naftazone is a quinone-semi carbazone drug that possesses a strong orange color, and hence it was usually analyzed colorimetrically or by HPLC-UV. However, these methods are not sensitive enough to determine naftazone in biological samples. Naftazone lacks intrinsic fluorescence and does not possess easily derivatizable functional groups. In this contribution, we introduced the first spectrofluorimetric method for naftazone assay through reduction-elicited fluorogenic derivatization through the reduction of its quinone-semicarbazone moiety to the corresponding quinol-semicarbazide derivative by potassium borohydride as a reduction probe. The solvent-dependent fluorescence of the reaction product was studied in various protic and aprotic solvents. Eventually, the fluorescence of the reduced naftazone was measured in 2-propanol at λemission of 350 nm after excitation at λecxitation of 295 nm. The relative fluorescence intensity was linearly correlated to the drug concentration (r = 0.9995) from 10.0 to 500 ng/mL with high sensitivity, where the lower detection limit was 2.9 ng/mL. Hence, the method was effectively applied for naftazone tablets quality control with a mean %recovery of 100.3 ± 1.5, and the results agreed with those of the comparison HPLC-UV method. Furthermore, a new salting-out assisted liquid-liquid extraction (SALLE) method was established for naftazone extraction from human serum, followed by its determination using the developed reduction-based fluorogenic method. The developed SALLE method showed excellent recovery for naftazone from human serum (92.3–106.5%) with good precision (RSD ≤ 6.8%). Additionally, the reaction of naftazone with potassium borohydride was kinetically monitored, and it was found to follow pseudo-first-order kinetics with an activation energy of 43.8 kcal/mol. The developed method’s greenness was approved using three green analytical chemistry metrics.
Hyper-Parameter Optimization of Stacked Asymmetric Auto-Encoders for Automatic Personality Traits Perception
Authors: Jalaeian Zaferani Effat , Teshnehlab Mohammad , Khodadadian Amirreza , Heitzinger Clemens , Vali Mansour , Noii Nima , Wick Thomas
Published: August 2022

In this work, a method for automatic hyper-parameter tuning of the stacked asymmetric auto-encoder is proposed. In previous work, the deep learning ability to extract personality perception from speech was shown, but hyper-parameter tuning was attained by trial-and-error, which is time-consuming and requires machine learning knowledge. Therefore, obtaining hyper-parameter values is challenging and places limits on deep learning usage. To address this challenge, researchers have applied optimization methods. Although there were successes, the search space is very large due to the large number of deep learning hyper-parameters, which increases the probability of getting stuck in local optima. Researchers have also focused on improving global optimization methods. In this regard, we suggest a novel global optimization method based on the cultural algorithm, multi-island and the concept of parallelism to search this large space smartly. At first, we evaluated our method on three well-known optimization benchmarks and compared the results with recently published papers. Results indicate that the convergence of the proposed method speeds up due to the ability to escape from local optima, and the precision of the results improves dramatically. Afterward, we applied our method to optimize five hyper-parameters of an asymmetric auto-encoder for automatic personality perception. Since inappropriate hyper-parameters lead the network to over-fitting and under-fitting, we used a novel cost function to prevent over-fitting and under-fitting. As observed, the unweighted average recall (accuracy) was improved by 6.52% (9.54%) compared to our previous work and had remarkable outcomes compared to other published personality perception works.
Effect of Visually Induced Motion Sickness from Head-Mounted Display on Cardiac Activity
Authors: Park Sangin , Ha Jihyeon , Kim Laehyun
Published: August 2022

Head-mounted display (HMD) virtual reality devices can facilitate positive experiences such as co-presence and deep immersion; however, motion sickness (MS) due to these experiences hinders the development of the VR industry. This paper proposes a method for assessing MS caused by watching VR content on an HMD using cardiac features. Twenty-eight undergraduate volunteers participated in the experiment by watching VR content on a 2D screen and HMD for 12 min each, and their electrocardiogram signals were measured. Cardiac features were statistically analyzed using analysis of covariance (ANCOVA). The proposed model for classifying MS was implemented in various classifiers using significant cardiac features. The results of ANCOVA reveal a significant difference between 2D and VR viewing conditions, and the correlation coefficients between the subjective ratings and cardiac features have significant results in the range of −0.377 to −0.711 (for SDNN, pNN50, and ln HF) and 0.653 to 0.677 (for ln VLF and ln VLF/ln HF ratio). Among the MS classification models, the linear support vector machine achieves the highest average accuracy of 91.1% (10-fold cross validation) and has a significant permutation test outcome. The proposed method can contribute to quantifying MS and establishing viewer-friendly VR by determining its qualities.
Wide-Sense Nonblocking Converting-Converting Networks with Multirate Connections
Authors: Kabaciński Wojciech , Rajewski Remigiusz
Published: August 2022

In this paper, we consider a two-stage converting-converting (CC) switching network. This structure can be used, for instance, in switches of elastic optical networks (EONs) or in time-division switches. We propose a new routing algorithm based on fixed slot assignment in interstage links. This algorithm, called Fixed Input–interstage Slot Assignment (FISA), reduces the switching network complexity compared to the rearrangeable (RNB) switching networks of the same structure. We derive the wide-sense nonblocking (WNB) conditions for the switching network controlled by this algorithm. The obtained WNB conditions are the same as those of the RNB, but the switching network does not need troublesome and time-consuming rearrangements. When implementing the proposed switching network structure, we can also reduce the number of tunable full-range spectrum converters and replace part of them with fixed spectrum converters, or even use space switches in the first stage. This is especially important when this architecture is applied in EONs.
SDGs as One of the Drivers of Smart City Development: The Indicator Selection Process
Authors: Parra-Domínguez Javier , Gil-Egido Andrea , Rodríguez-González Sara
Published: August 2022

The 2030 Agenda is a clear development milestone for humanity in its ambition to care for our future generations. Smart Cities play an essential role in this development, the development direction of which is based, among others factors, on the fulfilment of the criteria set by the various Sustainable Development Goals (SDGs). The purpose of the current research is to verify the current state of science concerning the development of the SDGs in Smart Cities to establish a theoretical framework for the development and integration of data specific to a Smart City to participate in homogeneous monitoring of these indicators and to compare with other Smart Cities. Once a robust bibliographic study has been carried out, we proceed to establish a theoretical study, the application methodology of which follows a process developed in various phases to obtain an integrated system for monitoring and linking of the development of Smart Cities according to the criteria set out in the applicable SDGs. The clear implication is establishing an objective and efficient process that covers collection to integrate and compare the obtained data. One of the limitations of this process is overcoming the technological barrier in specific less developed environments that may not have sufficient funding. With respect to future lines of research, the current study opens the door to studying the implications of this type of process on the management and elaboration of specific public policies, for example, concerning the time taken to establish and resolve them.
Exploring the Dynamic Shock of Unconventional Monetary Policy Channels on Income Inequality: A Panel VAR Approach
Authors: Zungu Lindokuhle Talent , Greyling Lorraine
Published: August 2022

In response to the “Great Recession and Global Financial Crisis”, central banks had to deploy unconventional monetary policies (UMP) in order to fight the severe impact of the crisis. Therefore, the purpose of this study is to examine the dynamic shock of unconventional monetary policies through earning heterogeneity, income composition, and portfolio channels on income inequality in emerging economies covering the period 2000–2019, using the panel vector autoregressive (PVAR) model. A PVAR model was designed for this study because of its ability to address the dynamics of numerous entities considered in parallel. The findings suggest that the UMPs used by these countries’ central banks may have increased income inequality through all of the channels investigated in this study, as a shock to unconventional monetary policy results in a positive response in income inequality. Even when pre-tax income, held by the top 10%, is adopted to measure income inequality, the study yields similar results. It is evident that a central bank’s objective is and should be to fulfil its mandate of achieving maximum employment and price stability, thus bringing wide economic benefits. Thus, some forms of policies are more appropriate for addressing concerns about inequality (income policy or fiscal policy) than others. However, the current study alerts the central bank to the fact that monetary policies may have a wounding impact on income inequality. Therefore, the central banks should consider the cost of monetary policies on income inequality when drafting or implementing these kinds of policies.
Social Media and Cross-Border Political Participation: A Case Study of Kyrgyz Migrants’ Online Activism
Authors: Chekirova Ajar
Published: August 2022

In an attempt to address the debate among social science scholars regarding whether or not online political engagement is a legitimate form of political participation, this study investigates the conditions under which migrants engage politically with virtual communities, and when and how online participation spills over to real-world social mobilization. The case study of Kyrgyz migrants’ online activism in virtual social media groups and pages on Facebook and its Russian equivalents VKontakte and Odnoklassniki demonstrates that, although migrants are not likely to routinely participate in, initiate, or continuously engage with political conversations on these platforms, crisis conditions, such as the October revolution in 2020, the first COVID wave the summer of that same year, and the Kyrgyz–Tajik border conflict in April–May 2021, trigger bursts of political activism on social media which carry over to the real-world in the form of fundraising and protest mobilization.
Emerging Themes on Factors Influencing Career and Employment Decisions: Voices of Individuals with Disabilities from Four Gulf Countries
Authors: Al-Hendawi Maha , Thoma Colleen A. , Habeeb Hawraa , Khair Muhammad Salman
Published: August 2022

Understanding the range of factors influencing career and employment decisions of individuals with disabilities is crucial for policy makers, businesses, and other stakeholders to support and integrate individuals with disabilities in the economic and social capital of the Arab-Gulf. The purpose of this sttudy was to investigate the factors that influence individuals with disabilities in making decisions about their career and employment. We explore how Arab adults with disabilities explain their career and employment decisions experiences, challenges, and barriers. We interviewed 15 adults with disabilities from four Arab-Gulf countries: Kuwait, Oman, Qatar, and Saudi Arabia. Our findings reveal eight factors that influence individuals with disabilities in their decision-making process about work and their future goals. Two distinct emerging themes were identified as influencing career and employment decisions for individuals with disabilities: individual attributes and environmental factors. Self-determination theory guided our analysis for this research study. The study provided in-depth understanding of the factors that impact employment persistence and individuals with disabilities in the Gulf region. The findings from this base-line study has implications for transition and self-determination. Thus, the study discusses ways to improve the quality of services and supports for individuals with disabilities in the Arab-Gulf and their families.
A Sustainable Cold Mix Asphalt Mixture Comprising Paper Sludge Ash and Cement Kiln Dust
Authors: Dulaimi Anmar , Al-Busaltan Shakir , Kadhim Mustafa Amoori , Al-Khafaji Ruqayah , Sadique Monower , Al Nageim Hassan , Ibrahem Raed Khalid , Awrejcewicz Jan , Pawłowski Witold , Mahdi Jasim M.
Published: August 2022

Concerns about the environment, the cost of energy, and safety mean that low-energy cold-mix asphalt materials are very interesting as a potential replacement for present-day hot mix asphalt. The main disadvantage of cold bituminous emulsion mixtures is their poor early life strength, meaning they require a long time to achieve mature strength. This research work aims to study the protentional utilization of waste and by-product materials as a filler in cold emulsion mixtures with mechanical properties comparable to those of traditional hot mix asphalt. Accordingly, cold mix asphalt was prepared to utilize paper sludge ash (PSA) and cement kiln dust (CKD) as a substitution for conventional mineral filler with percentages ranging from 0–6% and 0–4%, respectively. Test results have shown that the incorporation of such waste materials reflected a significant improvement in the mixture’s stiffness and strength evolution. The cementitious reactivity of PSA produces bonding inside the mixtures, while CKD is used as an additive to activate the hydration process of PSA. Therefore, based on the results, it will be easier to build cold mixtures by shortening the amount of time needed to reach full curing conditions.
Venture Capital and Chinese Firms’ Technological Innovation Capability: Effective Evaluation and Mechanism Verification
Authors: Song Yuegang , Jin Songlin , Li Zhenhui
Published: August 2022

Making the financial industry a solider mainstay of the real economy is of great concern for China in the midst of economic reform. For China, leveraging venture capital (VC) to enhance a firm’s technological innovation capability (TIC) is an important means of actualising its innovation and development strategy, as well as a must-do to realise sustainable development. In this study, firms that went public from 2010 to 2020 on the A-stock market were used as samples to study the effects of VC on TIC and the relevant mechanism based on the difference-in-differences (DID) method. As research findings show, VC can improve TIC through the medium of the internal incentive and external constraint easing effects. The contributory role of VC in TIC varies with firm size, ownership, and industry type. A range of robustness tests, including the PSM, variable substitution, and instrumental variable methods, further strengthened the reliability of the conclusions. This study can enlighten policymakers on how to implement comprehensive resource factor market reform to build a favourable innovation environment that materialises the role of marketisation.
Evaluation of Interaction between Bridge Infrastructure Resilience Factors against Seismic Hazard
Authors: Román Ángel Francisco Galaviz , Khan Md Saiful Arif , Kabir Golam , Billah Muntasir , Dutta Subhrajit
Published: August 2022

Infrastructure systems, such as bridges, are perpetually vulnerable to natural hazards such as seismic events, flooding, and landslides. This study aims to determine the relevant parameters required to increase the seismic resilience of bridge infrastructure based on the decisions of experts and prior research. To this end, the crisp DEMATEL (decision-making and trial evaluation laboratory) and rough DEMATEL methods are employed. Rough DEMATEL is a supplement to crisp DEMATEL that incorporates rough theory to handle ambiguity. The efficacies of the rough and crisp DEMATEL methods are then compared between the two approaches. This study found the most crucial seismic-resilience variables for bridges. The outcomes of this study reveal the significant order and cause-and-effect relationships. This research can assist transportation engineers and executive agencies in enhancing the seismic resilience of roadway bridges and bridge networks.
The Impacts of Social Media on Accounting and Auditing: Evidence from Greek Listed Firms
Authors: Beka Erietta , Pavlatos Odysseas
Published: August 2022

Companies are increasingly using social media to communicate with stakeholders. During the last decade, social media started to become part and parcel of contemporary lifestyles. Thus, the main purpose of this research was the investigation of the impacts of social media on accounting and auditing by using companies’ social media posts. We performed quantitative research on an initial population of 183 companies being traded on the Athens Stock Exchange (ATHEX) for one fiscal year. We gathered data from corporate social media accounts and social media posts for the 2018 fiscal year (Twitter, Facebook and LinkedIn). We analyzed social media posts’ strategies, and we used the Kruskal–Wallis model and OLS regression model in order to analyze the relationships between social media accounts and posts and accounting and auditing. The findings from our research show that firms with active social media accounts and active impression management techniques on Twitter, Facebook and LinkedIn tend to achieve higher profits compared to companies that have inactive social media accounts. Additionally, the firm’s total liabilities are mainly positively related to its posts on specific social media accounts. In addition, cash, total assets and earnings before taxes affect social media posts to different degrees, depending on the post’s content and the category of social media as well. Taking into account the auditing variables, it is suggested that there is no relation among the given auditor’s opinion, the going concern assumption and the reviewed posts.
Residents’ Perceptions of Tourism: A Decisive Variable in Stimulating Entrepreneurial Intentions and Activities in Tourism in the Mountainous Rural Area of the North-East Region of Romania
Authors: Saghin Despina , Lăzărescu Luminița-Mirela , Diacon Liliana Daniela , Grosu Maria
Published: August 2022

Interest in the study of rural tourism and its contribution to the development of rural mountain communities has increased in recent decades. It is recognized that many factors are involved in tourism development, and that residents play a key role in ensuring its success at a local level. This study aims to investigate the perceptions of the inhabitants of the mountainous rural area in the North-East Region of Romania (MRA) towards rural tourism, and to verify whether the development of entrepreneurship in this area is consistent with the positive/negative perceptions identified. A total of 1277 questionnaires were collected from the inhabitants of 78 sampled municipalities, and their processing using statistical methods shows that the inhabitants of two counties have positive perceptions of the living conditions in their communities, the involvement of the authorities in the development of tourism, and the exploitation of tourist attractions. On the other hand, comparing the values of entrepreneurship development indicators shows that two counties concentrate 91% of all active businesses and 94% of newly created businesses in the food and accommodation sector at the level of the study area, and the rate of creation of new businesses and their density have much higher values in these counties than in the county where the analyzed aspects are perceived negatively. The information provided by the research is particularly useful for regional and local authorities to make decisions related to more consistent funding of rural mountain tourism.
Sustainable Hunting as a Tourism Product in Dehesa Areas in Extremadura (Spain)
Authors: Martín-Delgado Luz-María , Jiménez-Barrado Víctor , Sánchez-Martín José-Manuel
Published: August 2022

The dehesa is one of the main agricultural landscapes in the Extremadura region. It is currently undergoing a production crisis caused by changes in the market, including the abandonment of uses linked to its exploitation. This situation could lead to the disappearance of this unique landscape due to its anthropogenic nature. It is therefore necessary to develop alternative activities to improve its productive profitability, which could include sustainable hunting. The hunting literature recognizes the role it plays in environmental, economic, and social sustainability, with hunting tourism being one of the productive activities that generates the most wealth within the sector, where big game hunting is of great importance. In this scenario, the regions of Villuercas-Ibores-Jara and La Siberia have an ideal landscape for the development of this modality due to their physical characteristics. For this reason, this study carried out an analysis of the situation of hunting tourism in these areas through the dissemination of a questionnaire among the managers of rural accommodation in the study area. The responses recorded were processed using statistical techniques that allowed us to extract interesting results such as the importance of hunting as a tourist resource, with a large number of big game species living in these areas, the high presence of hunters in these lodgings during the hunting season, the role that hunting plays in environmental, economic, and social sustainability, and the need to create a specific tourist product that meets the needs of the demand of hunters.
Should “Green” Be Precise? The Effect of Information Presentation on Purchasing Intention of Green Products
Authors: Liang Shichang , Zhang Min , Chu Yuxuan , He Lingling
Published: August 2022

Green product companies usually convey product performance in either ambiguous or precise ways. Many studies have been conducted on the ambiguous and precise information presentation of traditional products, but few have examined which kind of information presentation (ambiguous vs. precise) is better for presenting green products. This article conducted three experiments with 484 participants to examine the influence of information presentation (ambiguous vs. precise) of green products on consumers’ purchase intention. Results show that ambiguous information presentation can increase more consumers’ purchase intention of green products than precise information, and green trust plays a mediating effect. Furthermore, product type (durable goods vs. fast-moving consumer goods [FMCG]) moderates the influence of information presentation on consumers’ purchase intention. Specifically, for green durable goods, ambiguous information is more likely to arouse consumers’ purchase intention than precise information presentation. For green FMCG, precise information is more likely to promote consumers’ purchase intention than ambiguous information presentation.
One-Step Solution Plasma-Mediated Preparation of Se Nanoplarticles and Evaluating Their Acute Oral Toxicity in Mice
Authors: Vu Tri Thien , Nguyen Dung Thi , Nguyen Tran Hung , Le Huu Thanh , Nguyen Dinh Duc , La Duong Duc
Published: August 2022

Selenium element is considered as one of the most important micronutrients for many biological systems. It has been well demonstrated that Se nanoparticles (Se NPs) express greater bioavailability, biocompatability, and less toxicity than that of Se in ion form. In this work, the Se NPs were facilely fabricated by a one-step plasma process in the ethanol–water solution mixture. The as-prepared Se NPs were well characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), UV-vis spectroscopy, Raman spectroscopy, and energy dispersive X-ray spectroscopy (EDX). The prepared Se NPs were a light red color with a spherical shape and particle size in the range of 100–200 nm. The average diameter of the Se NPs calculated from the ImageJ software and TEM image was approximately 154 nm. The EDX results showed that the Se NPs prepared by the plasma process in the solution were highly pure and stable. The acute oral toxicity of the obtained Se NPs toward mice was also studied, which revealed that the Se NPs were safe for the human body. The mechanism for the formation of Se NPs from the Se ions under the solution plasma condition was also studied and discussed.