bluuebunny/crossref_metadata_2025 huggingface dataset:
PALANTIR: An NFV-Based Security-as-a-Service Approach for Automating Threat Mitigation
Authors: Compastié Maxime , López Martínez Antonio , Fernández Carolina , Gil Pérez Manuel , Tsarsitalidis Stylianos , Xylouris George , Mlakar Izidor , Kourtis Michail Alexandros , Šafran Valentino
Published: February 2023

Small and medium enterprises are significantly hampered by cyber-threats as they have inherently limited skills and financial capacities to anticipate, prevent, and handle security incidents. The EU-funded PALANTIR project aims at facilitating the outsourcing of the security supervision to external providers to relieve SMEs/MEs from this burden. However, good practices for the operation of SME/ME assets involve avoiding their exposure to external parties, which requires a tightly defined and timely enforced security policy when resources span across the cloud continuum and need interactions. This paper proposes an innovative architecture extending Network Function Virtualisation to externalise and automate threat mitigation and remediation in cloud, edge, and on-premises environments. Our contributions include an ontology for the decision-making process, a Fault-and-Breach-Management-based remediation policy model, a framework conducting remediation actions, and a set of deployment models adapted to the constraints of cloud, edge, and on-premises environment(s). Finally, we also detail an implementation prototype of the framework serving as evaluation material.
Infrared Small Target Detection Based on Multiscale Kurtosis Map Fusion and Optical Flow Method
Authors: Xin Jinglin , Cao Xinxin , Xiao Hu , Liu Teng , Liu Rong , Xin Yunhong
Published: February 2023

The uncertainty of target sizes and the complexity of backgrounds are the main reasons for the poor detection performance of small infrared targets. Focusing on this issue, this paper presents a robust and accurate algorithm that combines multiscale kurtosis map fusion and the optical flow method for the detection of small infrared targets in complex natural scenes. The paper has made three main contributions: First, it proposes a structure for infrared small target detection technology based on multiscale kurtosis maps and optical flow fields, which can well represent the shape, size and motion information of the target and is advantageous to the enhancement of the target and the suppression of the background. Second, a strategy of multi-scale kurtosis map fusion is presented to match the shape and the size of the small target, which can effectively enhance small targets with different sizes as well as suppress the highlighted noise points and the residual background edges. During the fusion process, a novel weighting mechanism is proposed to fuse different scale kurtosis maps, by means of which the scale that matches the true target is effectively enhanced. Third, an improved optical flow method is utilized to further suppress the nontarget residual clutter that cannot be completely removed by multiscale kurtosis map fusion. By means of the scale confidence parameter obtained during the multiscale kurtosis map fusion step, the optical flow method can select the optimal neighborhood that matches best to the target size and shape, which can effectively improve the integrity of the detection target and the ability to suppress residual clutter. As a result, the proposed method achieves a superior performance. Experimental results on eleven typical complex infrared natural scenes show that, compared with seven state-of-the-art methods, the presented method outperforms in terms of subjective visual effect, as well as some main objective evaluation indicators such as BSF, SCRG and ROC, etc.
Spectral Analysis Methods for Improved Resolution and Sensitivity: Enhancing SPR and LSPR Optical Fiber Sensing
Authors: Dos Santos Paulo S. S. , Mendes João P. , Dias Bernardo , Pérez-Juste Jorge , De Almeida José M. M. M. , Pastoriza-Santos Isabel , Coelho Luis C. C.
Published: February 2023

Biochemical–chemical sensing with plasmonic sensors is widely performed by tracking the responses of surface plasmonic resonance peaks to changes in the medium. Interestingly, consistent sensitivity and resolution improvements have been demonstrated for gold nanoparticles by analyzing other spectral features, such as spectral inflection points or peak curvatures. Nevertheless, such studies were only conducted on planar platforms and were restricted to gold nanoparticles. In this work, such methodologies are explored and expanded to plasmonic optical fibers. Thus, we study—experimentally and theoretically—the optical responses of optical fiber-doped gold or silver nanospheres and optical fibers coated with continuous gold or silver thin films. Both experimental and numerical results are analyzed with differentiation methods, using total variation regularization to effectively minimize noise amplification propagation. Consistent resolution improvements of up to 2.2× for both types of plasmonic fibers are found, demonstrating that deploying such analysis with any plasmonic optical fiber sensors can lead to sensing resolution improvements.
Buried RF Sensors for Smart Road Infrastructure: Empirical Communication Range Testing, Propagation by Line of Sight, Diffraction and Reflection Model and Technology Comparison for 868 MHz–2.4 GHz
Authors: Marsic Vlad , Faramehr Soroush , Fleming Joe , Ball Peter , Ou Shumao , Igic Petar
Published: February 2023

Updating the road infrastructure requires the potential mass adoption of the road studs currently used in car detection, speed monitoring, and path marking. Road studs commonly include RF transceivers connecting the buried sensors to an offsite base station for centralized data management. Since traffic monitoring experiments through buried sensors are resource expensive and difficult, the literature detailing it is insufficient and inaccessible due to various strategic reasons. Moreover, as the main RF frequencies adopted for stud communication are either 868/915 MHz or 2.4 GHz, the radio coverage differs, and it is not readily predictable due to the low-power communication in the near proximity of the ground. This work delivers a reference study on low-power RF communication ranging for the two above frequencies up to 60 m. The experimental setup employs successive measurements and repositioning of a base station at three different heights of 0.5, 1 and 1.5 m, and is accompanied by an extensive theoretical analysis of propagation, including line of sight, diffraction, and wall reflection. Enhancing the tutorial value of this work, a correlation analysis using Pearson’s coefficient and root mean square error is performed between the field test and simulation results.
Fusion-Based Body-Worn IoT Sensor Platform for Gesture Recognition of Autism Spectrum Disorder Children
Authors: Ullah Farman , AbuAli Najah Abed , Ullah Asad , Ullah Rehmat , Siddiqui Uzma Abid , Siddiqui Afsah Abid
Published: February 2023

The last decade’s developments in sensor technologies and artificial intelligence applications have received extensive attention for daily life activity recognition. Autism spectrum disorder (ASD) in children is a neurological development disorder that causes significant impairments in social interaction, communication, and sensory action deficiency. Children with ASD have deficits in memory, emotion, cognition, and social skills. ASD affects children’s communication skills and speaking abilities. ASD children have restricted interests and repetitive behavior. They can communicate in sign language but have difficulties communicating with others as not everyone knows sign language. This paper proposes a body-worn multi-sensor-based Internet of Things (IoT) platform using machine learning to recognize the complex sign language of speech-impaired children. Optimal sensor location is essential in extracting the features, as variations in placement result in an interpretation of recognition accuracy. We acquire the time-series data of sensors, extract various time-domain and frequency-domain features, and evaluate different classifiers for recognizing ASD children’s gestures. We compare in terms of accuracy the decision tree (DT), random forest, artificial neural network (ANN), and k-nearest neighbour (KNN) classifiers to recognize ASD children’s gestures, and the results showed more than 96% recognition accuracy.
Low-to-Mid-Frequency Monopole Source Levels of Underwater Noise from Small Recreational Vessels in the St. Lawrence Estuary Beluga Critical Habitat
Authors: Lagrois Dominic , Kowalski Camille , Sénécal Jean-François , Martins Cristiane C. A. , Chion Clément
Published: February 2023

Anthropogenic noise from navigation is a major contributor to the disturbance of the acoustic soundscape in underwater environments containing noise-sensitive life forms. While previous studies mostly developed protocols for the empirical determination of noise source levels associated with the world’s commercial fleet, this work explores the radiated noise emitted by small recreational vessels that thrive in many coastal waters, such as in the St. Lawrence Estuary beluga population’s summer habitat. Hydrophone-based measurements in the Saguenay River (QC, Canada) were carried out during the summers of 2021 and 2022. Shore-based observations identified 45 isolated transits of small, motorized vessels and were able to track their displacement during their passage near the hydrophone. Received noise levels at the hydrophone typically fell below the hearing audiogram of the endangered St. Lawrence Estuary beluga. Monopole source levels at low frequencies (0.1–≲2 kHz) held on average twice the acoustic power compared to their mid-frequency (≳2–30 kHz) counterparts. The speed over ground of recreational vessel showed a positive correlation with the back-propagated monopole source levels. Estimations of the mid-frequency noise levels based on low-frequency measurements should be used moderately.
Nonlinear Encryption for Multiple Images Based on a Joint Transform Correlator and the Gyrator Transform
Authors: Perez Ronal A. , Vilardy Juan M. , Pérez-Cabré Elisabet , Millán María S. , Torres Cesar O.
Published: February 2023

A novel nonlinear encryption–decryption system based on a joint transform correlator (JTC) and the Gyrator transform (GT) for the simultaneous encryption and decryption of multiple images in grayscale is proposed. This security system features a high level of security for the single real-valued encrypted image and a high image quality for the multiple decrypted images. The multispectral or color images are considered as a special case, taking each color component as a grayscale image. All multiple grayscale images (original images) to encrypt are encoded in phase and placed in the input plane of the JTC at the same time without overlapping. We introduce two random-phase masks (RPMs) keys for each image to encrypt at the input plane of the JTC-based encryption system. The total number of the RPM keys is given by the double of the total number of the grayscale images to be encrypted. The use of several RPMs as keys improves the security of the encrypted image. The joint Gyrator power distribution (JGPD) is the intensity of the GT of the input plane of the JTC. We obtain only a single real-valued encrypted image with a high level of security for all the multiple grayscale images to encrypt by introducing two new suitable nonlinear modifications on the JGPD. The security keys are given by the RPMs and the rotation angle of the GT. The decryption system is implemented by two successive GTs applied to the encrypted image and the security keys given by the RPMs and considering the rotation angle of the GT. We can simultaneously retrieve the various information of the original images at the output plane of the decryption system when all the security keys are correct. Another result due to the appropriate definition of the two nonlinear operations applied on the JGPD is the retrieval of the multiple decrypted images with a high image quality. The numerical simulations are computed with the purpose of demonstrating the validity and performance of the novel encryption–decryption system.
Development of Real-Time Cuffless Blood Pressure Measurement Systems with ECG Electrodes and a Microphone Using Pulse Transit Time (PTT)
Authors: Choi Jingyu , Kang Younghwan , Park Jaesoon , Joung Yeunho , Koo Chiwan
Published: February 2023

Research has shown that pulse transit time (PTT), which is the time delay between the electrocardiogram (ECG) signal and the signal from a photoplethysmogram (PPG) sensor, can be used to estimate systolic blood pressure (SBP) and diastolic blood pressure (DBP) without the need for a cuff. However, the LED of the PPG sensor requires the precise adjustment of both light intensity and light absorption rates according to the contact status of the light-receiving element. This results in the need for regular calibration. In this study, we propose a cuffless blood pressure monitor that measures real-time blood pressure using a microphone instead of a PPG sensor. The blood pulse wave is measured in the radial artery of the wrist using a microphone that can directly measure the sound generated by a body rather than sending energy inside the body and receiving a returning signal. Our blood pressure monitor uses the PTT between the R-peak of the ECG signal and two feature points of the blood pulse wave in the radial artery of the wrist. ECG electrodes and circuits were fabricated, and a commercial microelectromechanical system (MEMS) microphone was used as the microphone to measure blood pulses. The peak points of the blood pulse from the microphone were clear, so the estimated SBP and DBP could be obtained from each ECG pulse in real time, and the resulting estimations were similar to those made by a commercial cuff blood pressure monitor. Since neither the ECG electrodes nor the microphone requires calibration over time, the real-time cuffless blood pressure monitor does not require calibration. Using the developed device, blood pressure was measured three times daily for five days, and the mean absolute error (MAE) and standard deviation (SD) of the SBP and DBP were found to be 2.72 ± 3.42 mmHg and 2.29 ± 3.53 mmHg, respectively. As a preliminary study for proof-of-concept, these results were obtained from one subject. The next step will be a pilot study on a large number of subjects.
Ultraprecise Controller for Piezoelectric Actuators Based on Deep Learning and Model Predictive Control
Authors: Uralde Jokin , Artetxe Eneko , Barambones Oscar , Calvo Isidro , Fernández-Bustamante Pablo , Martin Imanol
Published: February 2023

Piezoelectric actuators (PEA) are high-precision devices used in applications requiring micrometric displacements. However, PEAs present non-linearity phenomena that introduce drawbacks at high precision applications. One of these phenomena is hysteresis, which considerably reduces their performance. The introduction of appropriate control strategies may improve the accuracy of the PEAs. This paper presents a high precision control scheme to be used at PEAs based on the model-based predictive control (MPC) scheme. In this work, the model used to feed the MPC controller has been achieved by means of artificial neural networks (ANN). This approach simplifies the obtaining of the model, since the achievement of a precise mathematical model that reproduces the dynamics of the PEA is a complex task. The presented approach has been embedded over the dSPACE control platform and has been tested over a commercial PEA, supplied by Thorlabs, conducting experiments to demonstrate improvements of the MPC. In addition, the results of the MPC controller have been compared with a proportional-integral-derivative (PID) controller. The experimental results show that the MPC control strategy achieves higher accuracy at high precision PEA applications such as tracking periodic reference signals and sudden reference change.
HRTFs Measurement Based on Periodic Sequences Robust towards Nonlinearities in Automotive Audio
Authors: Cecchi Stefania , Bruschi Valeria , Nobili Stefano , Terenzi Alessandro , Carini Alberto
Published: February 2023

The head related transfer functions (HRTFs) represent the acoustic path transfer functions between sound sources in 3D space and the listener’s ear. They are used to create immersive audio scenarios or to subjectively evaluate sound systems according to a human-centric point of view. Cars are nowadays the most popular audio listening environment and the use of HRTFs in automotive audio has recently attracted the attention of researchers. In this context, the paper proposes a measurement method for HRTFs based on perfect or orthogonal periodic sequences. The proposed measurement method ensures robustness towards the nonlinearities that may affect the measurement system. The experimental results considering both an emulated scenario and real measurements in a controlled environment illustrate the effectiveness of the approach and compare the proposed method with other popular approaches.
Convolution Neural Networks and Self-Attention Learners for Alzheimer Dementia Diagnosis from Brain MRI
Authors: Carcagnì Pierluigi , Leo Marco , Del Coco Marco , Distante Cosimo , De Salve Andrea
Published: February 2023

Alzheimer’s disease (AD) is the most common form of dementia. Computer-aided diagnosis (CAD) can help in the early detection of associated cognitive impairment. The aim of this work is to improve the automatic detection of dementia in MRI brain data. For this purpose, we used an established pipeline that includes the registration, slicing, and classification steps. The contribution of this research was to investigate for the first time, to our knowledge, three current and promising deep convolutional models (ResNet, DenseNet, and EfficientNet) and two transformer-based architectures (MAE and DeiT) for mapping input images to clinical diagnosis. To allow a fair comparison, the experiments were performed on two publicly available datasets (ADNI and OASIS) using multiple benchmarks obtained by changing the number of slices per subject extracted from the available 3D voxels. The experiments showed that very deep ResNet and DenseNet models performed better than the shallow ResNet and VGG versions tested in the literature. It was also found that transformer architectures, and DeiT in particular, produced the best classification results and were more robust to the noise added by increasing the number of slices. A significant improvement in accuracy (up to 7%) was achieved compared to the leading state-of-the-art approaches, paving the way for the use of CAD approaches in real-world applications.
Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues
Authors: Cicek Didem , Kantarci Burak
Published: February 2023

With the increasing efforts to utilize information and communication technologies (ICT) in disaster management, the massive amount of heterogeneous data that is generated through ubiquitous sensors paves the way for fast and informed decisions in the case of disasters. Utilization of the big “sensed” data leads to an effective and efficient management of disaster situations so as to prevent human and economic losses. The advancement of built-in sensing technologies in smart mobile devices enables crowdsourcing of sensed data, which is known as mobile crowdsensing (MCS). This systematic literature review investigates the use of mobile crowdsensing in disaster management on the basis of the built-in sensor types in smart mobile devices, disaster management categories, and the disaster management cycle phases (i.e., mitigation, preparedness, response, and recovery activities). Additionally, this work seeks to unveil the frameworks or models that can potentially guide disaster management authorities towards integrating crowd-sensed data with their existing decision-support systems. The vast majority of the existing studies are conceptual as they highlight a challenge in experimental testing of the disaster management solutions in real-life settings, and there is little emphasis on the use cases of crowdsensing through smartphone sensors in disaster incidents. In light of a thorough review, we provide and discuss future directions and open issues for mobile crowdsensing-aided disaster management.
High-Resolution Magnetoelectric Sensor and Low-Frequency Measurement Using Frequency Up-Conversion Technique
Authors: Sun Kunyu , Jiang Zhihao , Wang Chengmeng , Han Dongxuan , Yao Zhao , Zong Weihua , Jin Zhejun , Li Shandong
Published: February 2023

The magnetoelectric (ME) sensor is a new type of magnetic sensor with ultrahigh sensitivity that suitable for the measurement of low-frequency weak magnetic fields. In this study, a metglas/PZT-5B ME sensor with mechanical resonance frequency fres of 60.041 kHz was prepared. It is interesting to note that its magnetic field resolution reached 0.20 nT at fres and 0.34 nT under a DC field, respectively. In order to measure ultralow-frequency AC magnetic fields, a frequency up-conversion technique was employed. Using this technique, a limit of detection (LOD) under an AC magnetic field lower than 1 nT at 8 Hz was obtained, and the minimum LOD of 0.51 nT was achieved at 20 Hz. The high-resolution ME sensor at the sub-nT level is promising in the field of low-frequency weak magnetic field measurement technology.
The Pandemic and the Creative Performance of Cities: An Empirical Study in Portugal
Authors: Rodrigues Margarida , Franco Mário , Oliveira Cidália , Borges Ana Pinto , Silva Rui
Published: February 2023

In a pandemic and post-pandemic environment, the consequences for the creative economy have been brutal and nefarious. Thus, this study aims to measure cities’ creativity performance, through a composite index, reported in the year 2021. In this sense, the results show that culture, the creative economy and enabling environment, as subdimensions of creativity, show that cities suffered a significant setback in their creative performance. However, this is currently being reversed so that creativity continues to contribute to the performance and growth of cities, whereby the formation of networks/partnerships as allies of the creative class and industries that characterise this dimension becomes even more important. This means that the creative class was one of the most affected by the pandemic, given that its activities are sustained mainly by the public, which corroborated recent studies. The study’s main contribution lies in the use of the Composite Index, in which it was concluded that creativity generates employment and wealth for a country’s economy. Finally, some limitations and avenues for future research were outlined.
Family Leisure in Rural and Urban Environments: A Question of Context
Authors: Hernández-Prados Mª Ángeles , Álvarez-Muñoz José Santiago
Published: February 2023

Family leisure increasingly plays a fundamental role as an educational resource that enhances human development and enriches intrafamily relationships. Theoretically, the conceptualization of free time and leisure, the typologies and agents of family leisure, and the benefits, difficulties, and satisfaction are discussed at home. This empirical study aims to describe the family leisure patterns shown by adolescents according to the context in which they reside, allowing a comparison of the rural leisure profile with the urban leisure profile, which are traditionally considered as differentiated contexts. The sample consisted of 1054 adolescents (51.6% boys and 48.4% girls) from Spain, stratified by place of residence (48.2% urban and 51.8% rural), who were administered the questionnaire “Evaluation of family leisure practices”. The data were processed using SPSS, and the results indicate that scarcity of time and economic resources in an urban setting and repetition and family conflicts in a rural setting are the most representative difficulties. In addition, the adolescents living in urban environments identify more benefits, have a more diversified practice, and have greater family satisfaction than the adolescents in rural areas. Both coincide with the importance of the family itself as a promoter of family leisure. In conclusion, the reconversion of social policies and the promotion of family educational procedures in rural areas to reduce the differences between the two contexts are highlighted.
Empowering Absence? Assessing the Impact of Transnational Male Out-Migration on Left behind Wives
Authors: Koirala Saroj
Published: February 2023

Experiences of left-behind family members of transnational migrant workers have been in the shadow of academic discourse on migration. To contribute to the slowly growing body of literature, this study explores the impact of male out-migration on left-behind wives. The study proposes and applies a novel framework to estimate Women Empowerment Index (WEI) for comparing the empowerment level across households with and without men in transnational labor. Cross-sectional surveys and unstructured interviews were used to collect data from 373 respondents from three selected areas in Nepal. Results indicate that left-behind wives experience a higher degree of decision-making authority, physical mobility, and involvement in socio-political spheres compared to women with husbands at home. However, left behind wives were found to experience increased unpaid workload and decreased access to information, together with emotional and psychological costs in the absence of their husbands.
Cu-Based Materials as Photocatalysts for Solar Light Artificial Photosynthesis: Aspects of Engineering Performance, Stability, Selectivity
Authors: Zindrou Areti , Belles Loukas , Deligiannakis Yiannis
Published: February 2023

Cu-oxide nanophases (CuO, Cu2O, Cu0) constitute highly potent nanoplatforms for the development of efficient Artificial Photosynthesis catalysts. The highly reducing conduction band edge of the d-electrons in Cu2O dictates its efficiency towards CO2 reduction under sunlight excitation. In the present review, we discuss aspects interlinking the stability under photocorrosion of the (CuO/Cu2O/Cu0) nanophase equilibria, and performance in H2-production/CO2-reduction. Converging literature evidence shows that, because of photocorrosion, single-phase Cu-oxides would not be favorable to be used as a standalone cathodic catalyst/electrode; however, their heterojunctions and the coupling with proper partner materials is an encouraging approach. Distinction between the role of various factors is required to protect the material from photocorrosion, e.g., use of hole scavengers/electron acceptors, band-gap engineering, nano-facet engineering, and selectivity of CO2-reduction pathways, to name a few possible solutions. In this context, herein we discuss examples and synthesis efforts that aim to clarify the role of interfaces, faces, and phase stability under photocatalytic conditions.
Second-Order Collocation-Based Mixed FEM for Flexoelectric Solids
Authors: Tannhäuser Kevin , Serrao Prince Henry , Kozinov Sergey
Published: February 2023

Flexoelectricity is an electromechanical coupling between the electric field and the mechanical strain gradient, as well as between the mechanical strains and the electric field gradient, observed in all dielectric materials, including those with centrosymmetry. Flexoelectricity demands C1-continuity for straightforward numerical implementation as the governing equations in the gradient theory are fourth-order partial differential equations. In this work, an alternative collocation-based mixed finite element method for direct flexoelectricity is used, for which a newly developed quadratic element with a high capability of capturing gradients is introduced. In the collocation method, mechanical strains and electric field through independently assumed polynomials are collocated with the mechanical strains and electric field derived from the mechanical displacements and electric potential at collocation points inside a finite element. The mechanical strain gradient and electric field are obtained by taking the directional derivative of the independent mechanical strain and electric field gradients. However, an earlier proposed linear element is unable to capture all mechanical strain gradient components and, thus, simulate flexoelectricity correctly. This problem is solved in the present work by using quadratic shape functions for the mechanical displacements and electric potential with fewer degrees of freedom than the traditional mixed finite element method. A Fortran user-element code is developed by the authors: first, for the linear and, after that, for the quadratic element. After verifying the linear element with numerical results from the literature, both linear and quadratic elements’ behaviors are tested for different problems. It is shown that the proposed second-order collocation-based mixed FEM can capture the flexoelectric behavior better compared to the existing linear formulations.
A Comparison of Contributing Factors between Young and Old Riders of Motorcycle Crash Severity on Local Roads
Authors: Champahom Thanapong , Se Chamroeun , Jomnonkwao Sajjakaj , Boonyoo Tassana , Ratanavaraha Vatanavongs
Published: February 2023

This study aims to identify the factors that influence the severity of motorcycle crashes on local roads, particularly given the high speeds often observed for motorcycles on these roads with low traffic volumes and numerous multi-leg intersections. Previous research has shown that a rider’s age can impact their speed behavior. To explore this issue, data on motorcycle crashes from 2015 to 2020 in Thailand—a middle-income developing country—were analyzed using a random parameter logit model with unobserved heterogeneity in means and variances, comparing young (<30-year-old) and older (>50-year-old) riders. The contributing factors were divided into four groups: driver, crash, environmental, and road factors. The transferability test yielded different results for the young rider and old rider models, indicating that it is appropriate to analyze these models separately. A constant value revealed that old riders were more likely to die in a crash than young riders. In terms of the random parameter, the local address and road surface variables were found to be significant in both models. The results of unobserved heterogeneity in means and variances identified significant variables in both models, including gender, exceeding the speed limit, lit roads, unlit roads, mobile phone use, and road surface. These findings were used to develop policy recommendations for reducing the severity of motorcycle crashes on local roads.
The Influence of Psychological Capital on Individual’s Social Responsibility through the Pivotal Role of Psychological Empowerment: A Study Towards a Sustainable Workplace Environment
Authors: Kariri Hadi Dhafer Hassan , Radwan Omaymah Abdulwahab
Published: February 2023

The study aimed to examine the influence of psychological capital on an individual’s social responsibility via the mediating function of psychological empowerment. In order to conduct this applied study, a random sample (N = 813) was chosen. Male and female employees in the Jazan region of Saudi Arabia were surveyed to collect data that was analyzed using descriptive statistics and structural equation modeling (path analysis). The study instrument was a structured questionnaire, the validity of which was evaluated by an expert panel for facial and content-based validity. In addition, Cronbach’s alpha coefficients (0.743–0.929) were utilized to confirm the instrument’s reliability. To examine the three proposed hypotheses, path analysis was applied. Favorable and statistically significant (p < 0.05) results suggested that the direct influence of psychological capital on social responsibility is positive. In addition, psychological empowerment considerably and favorably mediated the relationship between psychological capital and social responsibility. The research on indirect effects revealed that psychological capital has a substantial indirect influence on social responsibility. Finally, it should be noted that both the direct and indirect impacts of psychological capital on social responsibility are considerable and that the model’s fitness indices were satisfactory.
Evaluating the Factors of Green Finance to Achieve Carbon Peak and Carbon Neutrality Targets in China: A Delphi and Fuzzy AHP Approach
Authors: Li Chaofeng , Solangi Yasir Ahmed , Ali Sharafat
Published: February 2023

Green finance (GF) is a vital strategy implemented by China to minimize carbon emissions to achieve targets of carbon peak and carbon neutrality. Thus, the objective of this study is to reduce carbon emissions by developing green finance practices in China. This study identifies, evaluates, and ranks the factors and sub-factors of green finance because it is the core issue for sustainable development. In this regard, this study utilizes the Delphi and fuzzy Analytical Hierarchy Process (FAHP) method to analyze the main factors and sub-factors of green finance. The Delphi method finalizes the 6 factors and 26 sub-factors after a thorough investigation. The FAHP method was used to assess and rank the identified factors and sub-factors of green finance. The findings show that the political (POF) is the most crucial factor of green finance in the Chinese economy. The economic (ECF) and environmental (ENF) factors are ranked second and third important factors. The further results of the FAHP reveal that ecological and political identification (POF1), political stability (POF3), and climate commitments (POF2) are the top-ranked sub-factors of green finance. The results specify that green finance development is a very crucial strategy to minimize carbon emissions.
A Novel Design of a Hybrid Solar Double-Chimney Power Plant for Generating Electricity and Distilled Water
Authors: Abdelsalam Emad , Almomani Fares , Ibrahim Shadwa , Kafiah Feras , Jamjoum Mohammad , Alkasrawi Malek
Published: February 2023

The classical solar chimney offers passive electricity and water production at a low operating cost. However, the solar chimney suffers from high capital cost and low energy output density per construction area. The high capital investment increases the levelized cost of energy (LCOE), making the design less economically competitive versus other solar technologies. This work presents a new noteworthy solar chimney design for high energy density and maximizing water production. This was achieved by integrating a cooling tower with the solar chimney and optimizing the operating mood. The new design operated day and night as a hybrid solar double-chimney power plant (HSDCPP) for continuous electricity and water production. During the daytime, the HSDCPP operated as a cooling tower and solar chimney, while during the night, it operated as a cooling tower. The annual energy output from the cooling towers and solar chimney (i.e., the HSDCPP) totaled 1,457,423 kWh. The annual energy production from the cooling towers alone was 1,077,134 kWh, while the solar chimney produced 380,289 kWh. The annual energy production of the HSDCPP was ~3.83-fold greater than that of a traditional solar chimney (380,289 kWh). Furthermore, the HSDCPP produced 172,344 tons of fresh water per year, compared with zero tons in a traditional solar chimney. This led to lower overall capital expenditures maximizing energy production and lower LCOE.
Levels of Sustainability Awareness in Spanish University Students of Nautical Activities as Future Managers of Sports and Active Tourism Programmes
Authors: Morales-Baños Vicente , Borrego-Balsalobre Francisco José , Díaz-Suárez Arturo , López-Gullón José María
Published: February 2023

University students will play an important role in making decisions that will affect the environment, as future leaders of our society. Their level of sensitivity and environmental knowledge will play an important role in adequately facing future challenges. This article aims to measure the sustainability awareness of a sample of future graduates in Physical Activity and Sport Sciences in Spain. The literature supports that the sensitivity of these students can be estimated by using the Spanish adaptation of the SCQ-S. This allows for establishing the level of knowledge, attitudes and behaviour pertaining to sustainability in three dimensions: environmental, social and economic. The sample consisted of 170 students (58.8% males; 41.2% females) with a mean age of 20.5 years (±4.039). The overall Cronbach’s alpha showed a fairly good value (α = 0.836). The same was true for the Kaiser–Meyer–Olkin test values (KMO = 0.816) and Bartlett’s sphericity test (p < 0.001). The knowledge construct (4.56 ± 0.53) was the highest descriptive, followed by attitude (4.12 ± 0.59). The lowest value was behaviour (3.79 ± 0.66). By gender, girls obtained the highest sensitivity indexes. In addition, the place of habitual residence and physical activity in the natural environment were related to the overall behaviour of the university students. It is concluded that being in active contact with the natural environment allows us to have a higher level of awareness.
Solar Self-Sufficient Households as a Driving Factor for Sustainability Transformation
Authors: Harke Franz , Otto Philipp
Published: February 2023

We present a model to estimate the technical requirements, including the photovoltaic area and battery capacity, along with the costs, for a four-person household to be 100% electrically self-sufficient in Germany. We model the hourly electricity consumption of private households with quasi-Fourier series and an autoregressive statistical model based on data from Berlin in 2010. Combining the consumption model and remote-sensed hourly solar irradiance data from the ERA5 data set, we find the optimal photovoltaic area and battery capacity that would have been necessary to be self-sufficient in electricity from July 2002 to June 2022. We show that it is possible to build a self-sufficient household with today’s storage technology for private households and estimate the costs expected to do so.
The Role of Powerbroking in the Mediterranean Hydrocarbon Issue and Its Impact on Environmental Crisis—A Kin-State Case Dimension on Cyprus
Authors: Jabbar Bahrooz Jaafar , Direkli Mehmet
Published: February 2023

The Mediterranean Sea is prone to pollution as it is almost entirely enclosed by land and its warm waters need more than 80–90 years to clean and revive themselves. The dynamic environment and climate variables affect this region, known as the cradle of civilization. Many studies have examined the Mediterranean hydrocarbon issue through varying approaches that explain how cooperation or conflict is promoted in the region. The regional security complex approach, securitization theory, resource regionalism, location theory, and the materialist school have been considered to analyze the Mediterranean basin’s hydrocarbon relations. These approaches have focused on the issue’s political, economic, security, and geographical aspects, while there needs to be more analysis on the role of the kin-states. However, the interests of each country and regional conflicts have marginalized environmental problems. This study suggests that studying the role of Greece and Turkey in Cyprus as kin-states contributes to the direction of stability for hydrocarbon gas exploration and highlights the environmental threats. It applies a new approach to the issue of Mediterranean hydrocarbon relations by utilizing the concept of kin-states and emphasizing the environmental hazards in the Mediterranean region. At the same time, hydrocarbon development is deemed a high priority for the world in general and specifically for Europe. This study reveals the role of kin-states as powerbrokers as a significant hindrance to the progress of the peaceful development of the hydrocarbon infrastructure, ensuring clean energy in the region and reducing the vulnerability of the entire island. It recommends a multilateral approach that puts kin-states at the center of hydrocarbon cooperation. Thus, the matter of environment is analyzed by interpreting the theoretical contribution to international relations.
An AI-Based Shortlisting Model for Sustainability of Human Resource Management
Authors: Aydın Erdinç , Turan Metin
Published: February 2023

The adoption of artificial intelligence in human resource management may help businesses and create a keen advantage in the market. With the help of artificial intelligence, most human resource duties can be completed efficiently and in a much shorter timeframe. For the sustainability of companies, it is essential to shorten the processes that are time-consuming and possible to automate. Especially in the recruitment process, artificial intelligence can ease short listings and much more. This study focuses on the adoption of artificial intelligence for recruitment and shortlisting as a human resource management operation. It is intended to remove noisy data from the resumes of applicants by using a minimum description length algorithm and to create a learning algorithm based on the support vector machine to choose the better candidates according to company culture and preferences. By creating shortlists for open positions, it is possible to improve the hiring process and cut the cost of the process. To the best of our knowledge, no studies in the research literature that focused on resume shares learning algorithms and performance evaluation results. This paper presents how the feature extraction algorithm fails while feature selection reduces successfully, and how the learning algorithm can create shortlisting.
Sustainable and Environmental Dyeing with MAUT Method Comparative Selection of the Dyeing Recipe
Authors: Özomay Meral
Published: February 2023

The textile industry is one of the most complex sectors, in terms of the materials and chemical processes used from petroleum and the environmental degradation during its production and disposal. It is therefore a sector looking for new possibilities and for more sustainable materials and applications. One option is to use natural dyes, as they are considered biodegradable, do not pollute the environment, and have potential use for many sectors, including the fashion industry. In this study, Alanya silk was dyed by a natural dyeing method with crocus sativus, Helichrysum arenarium, and Glycyrrhiza glabra L., plants that grow in and around the Alanya region. Quercus aegilops L. grown in the region was preferred as mordant, a natural binder, and is one of the plants with the highest tannin content, and it was used with a more environmentally friendly and sustainable approach to increase the binding in natural dyeing instead of chemical mordants. The aim is to provide an environmental and scientific contribution to the dyeing producers in this region. According to the MAUT (Multi-Attribute Utility Theory) method, the best dyes in terms of fastness and color efficiency were determined as the dyes made with the Glycyrrhiza glabra L. plant.
Sustainable International Management: Research in Global Culture and Leadership Development
Authors: Jiménez Alfredo , Yahiaoui Dorra , Zhang Chi , Jiang Cuiling
Published: February 2023

Organizations are directing increasing attention towards corporate sustainability due to the regulative requests, the expectations of stakeholders and the greater community, environmental pressure, and the benefits of maximizing the firms’ performance [...]
The Influence of Multistakeholder Value Cognition and Risk Attitudes on Sustainable Interior Landscape Design Decisions
Authors: Chen Chuhan , Haron Syarmila Hany
Published: February 2023

With the increasing demand for interior landscapes, sustainable interior landscape design (SILD) has become part of a desirable lifestyle. However, consumer attitudes and a lack of consciousness and understanding of SILD have led to potentially negative impacts on design decisions regarding the use of sustainability in SILD. This study recruited 405 stakeholders to explore the relationships among value cognition, risk attitude, and decision intention. The value–attitude–behavior (VAB) model method was adopted to evaluate stakeholders’ cognitions and attitudes toward sustainable design and factors that influence sustainable design practices. The results demonstrated a positive correlation between multistakeholders’ value cognition, risk attitude, and SILD decisions. The relationship between value cognition and SILD decision intention is mediated by risk attitude. Furthermore, the value cognition of multistakeholders impacts risk attitude on the practice of SILD, thus changing design decisions. These findings provide insights into the sustainability of interior landscapes and design, particularly in terms of addressing diverse needs within multistakeholder practices.
Impact of Social Media Influencers on Customer Engagement and Purchase Intention: A Meta-Analysis
Authors: Ao Lie , Bansal Rohit , Pruthi Nishita , Khaskheli Muhammad Bilawal
Published: February 2023

This research aims at providing a meta-analysis of empirical findings of the literature on the characteristics of social media influencers on customer engagement and purchase intention. For this purpose, researchers derived eight social media influencers’ characteristics, i.e., homophily, expertise, trustworthiness, credibility, congruence with the product, entertainment value, informative value, and attractiveness. The current study synthesizes 176 effect sizes derived from 62 individual studies, and 22,554 individuals act as an aggregate sample. Results revealed that these characteristics have a moderate to high correlation with customer engagement and purchase intention. The entertainment value of social media influencers has the strongest association with customer engagement among all the attributes studied in this analysis. It also concluded that the credibility of influencers impacts purchase intention more than any other attribute. This work provides a novel approach to reducing the heterogeneity in influencer marketing research by empirically specifying the directions of relationships and the extent of the effect of these relationships.
Rhizobiome Signature and Its Alteration Due to Watering in the Wild Plant Moringa oleifera
Authors: Refai Mohammed Y. , Abulfaraj Aala A. , Hakeem Israa J. , Shaer Nehad A. , Alqahtani Mashael D. , Alomran Maryam M. , Alotaibi Nahaa M. , Sonbol Hana S. , Alhashimi Abdulrahman M. , Al-Abbas Nouf S. , Ashy Ruba A. , Alshareef Sahar A. , Jalal Rewaa S.
Published: February 2023

Metagenomic approach was used to detect microbial gene abundance and relative abundance in the rhizosphere of Moringa oleifera and surrounding bulk soil and to detect the response of soil microbes to watering. Expectedly, the number and abundance of non-redundant genes were extremely higher in bacteria followed by archaea, eukaryota and viruses. Results demonstrated unexpected high abundance of some microbes (ex., endophyte genus Nocardioides) in the rhizosphere that are supposed to exist mainly in other rhizocompartments. We suggest this differential distribution of microbes is due to the specific pattern of host-microbe interaction. Other endosymbiont microbes, ex., fungi Mucoromycota and Ascomycota, were highly abundant in the bulk soil possibly because they are phytopathogens where plant exudates might inhibit their growth or force these fungi to approach reverse chemotaxis. Our data indicated high abundance of other symbiont microbes in the rhizosphere of M. oleifera at phylum (ex., Actinobacteria) and genus (ex., Streptomyces) levels. Watering experiment indicated that phylum Actinobacteria and the descending genus Streptomyces are among the highest. Rhizobiome of M. oleifera seems to harbor a wealth of new species of the genus Streptomyces that are required to be deciphered for function in order to be eventually utilized in pharmaceutical and agricultural applications.