bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating Forest Soil Properties for Humus Assessment—Is Vis-NIR the Way to Go?
Authors: Thomas Felix , Petzold Rainer , Landmark Solveig , Mollenhauer Hannes , Becker Carina , Werban Ulrike
Published: March 2022

Recently, forest management faces new challenges resulting from increasing temperatures and drought occurrences. For sustainable, site-specific management strategies, the availability of up to date soil information is crucial. Proximal soil sensing techniques are a promising approach for rapid and inexpensive collection of data, and could facilitate the provision of the necessary information. This study evaluates the potential of visual and near-infrared spectroscopy (vis-NIRS) for estimating soil parameters relevant for humus mapping in Saxon forests. Therefore, soil samples from the organic layer are included. So far there is little knowledge about the applicability of vis-NIRS in the humus layer of forests. We investigate the spectral behaviour of samples from organic (Oh) and mineral (0–5 cm, Ah) horizons, pointing out differences in the occurring absorption features. Further, we identify and assess the accuracy of selected soil properties based on vis-NIRS for forest sites, compare the outcome of different regression methods, investigate the implications for forest soils due to the presence and different composition of the humus layer and organic horizons and interpret the results regarding their usefulness for soil mapping and monitoring purposes. For this, we used retained humus soil samples of forests from Saxony. Regression models were built with Partial Least Squares Regression, Support Vector Machine and Cubist. Investigated properties were carbon (C) and nitrogen (N) content, C/N ratio, pH value, cation exchange capacity (CEC) and base saturation (BS) due to their importance for assessing humus conditions in forests. In organic Oh horizons, prediction results for C and N content achieved R2 values between 0.44 and 0.58, with corresponding RPIQ ranging from 1.58 to 2.06 depending on the used algorithm. Estimations of C/N ratio were more precise with R2 = 0.65 and RMSE = 2.16. Best results were reported for pH value, with R2 = 0.90 and RMSE = 0.20. Regarding BS, the best model accuracy was R2 = 0.71, with RMSE = 13.97. In mineral topsoil, C and N content models achieved higher values of R2 = 0.59 to 0.72, with RPIQ values between 2.22 and 2.54. However, prediction accuracy was lower for C/N ratio (R2 = 0.50, RMSE = 3.52) and pH values (R2 = 0.62, RMSE = 0.29). Models for CEC achieved R2 = 0.65, with RPIQ = 2.81. In general, prediction precision varied dependent on the used algorithm, without showing clear tendencies. Classification into pH classes was exemplified since this offers a new perspective for humus mapping on forest soils. Balanced accuracy for the defined classes ranged from 0.50 to 0.87. We show that vis-NIR spectroscopy is suitable for assessing humus conditions in Saxon forests (Germany), in particular not only for mineral horizons but also for organic Oh horizons.
Natural- and Human-Induced Influences on Terrestrial Water Storage Change in Sichuan, Southwest China from 2003 to 2020
Authors: Cui Lilu , Zhu Chengkang , Wu Yunlong , Yao Chaolong , Wang Xiaolong , An Jiachun , Wei Pengzhi
Published: March 2022

A quantitative understanding of changes in water resources is crucial for local governments to enable timely decision-making to maintain water security. Here, we quantified natural-and human-induced influences on the terrestrial water storage change (TWSC) in Sichuan, Southwest China, with intensive water consumption and climate variability, based on the data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-on (GRACE-FO) during 2003–2020. We combined the TWSC estimates derived from six GRACE/GRACE-FO solutions based on the uncertainties of each solution estimated from the generalized three-cornered hat method. Metrics of correlation coefficient and contribution rate (CR) were used to evaluate the influence of precipitation, evapotranspiration, runoff, reservoir storage, and total water consumption on TWSC in the entire region and its five economic regions. The results showed that a significant improvement in the fused TWSC was found compared to those derived from a single model. The increase in regional water storage with a rate of 3.83 ± 0.54 mm/a was more influenced by natural factors (CR was 53.17%) compared to human influence (CR was 46.83%). Among the factors, the contribution of reservoir storage was the largest (CR was 42.32%) due to the rapid increase in hydropower stations, followed by precipitation (CR was 35.16%), evapotranspiration (CR was 15.86%), total water consumption (CR was 4.51%), and runoff (CR was 2.15%). Among the five economic regions, natural influence on Chengdu Plain was the highest (CR was 48.21%), while human influence in Northwest Sichuan was the largest (CR was 61.37%). The highest CR of reservoir storage to TWSC was in Northwest Sichuan (61.11%), while the highest CRs of precipitation (35.16%) and evapotranspiration (15.86%) were both in PanXi region. The results suggest that TWSC in Sichuan is affected by natural factors and intense human activities, in particular, the effect of reservoir storage on TWSC is very significant. Our study results can provide beneficial help for the management and assessment of regional water resources.
Early Detection of Dendroctonus valens Infestation with Machine Learning Algorithms Based on Hyperspectral Reflectance
Authors: Gao Bingtao , Yu Linfeng , Ren Lili , Zhan Zhongyi , Luo Youqing
Published: March 2022

The red turpentine beetle (Dendroctonus valens LeConte) has caused severe ecological and economic losses since its invasion into China. It gradually spreads northeast, resulting in many Chinese pine (Pinus tabuliformis Carr.) deaths. Early detection of D. valens infestation (i.e., at the green attack stage) is the basis of control measures to prevent its outbreak and spread. This study examined the changes in spectral reflectance after initial attacking of D. valens. We also explored the possibility of detecting early D. valens infestation based on spectral vegetation indices and machine learning algorithms. The spectral reflectance of infested trees was significantly different from healthy trees (p < 0.05), and there was an obvious decrease in the near-infrared region (760–1386 nm; p < 0.01). Spectral vegetation indices were input into three machine learning classifiers; the classification accuracy was 72.5–80%, while the sensitivity was 65–85%. Several spectral vegetation indices (DID, CUR, TBSI, DDn2, D735, SR1, NSMI, RNIR•CRI550 and RVSI) were sensitive indicators for the early detection of D. valens damage. Our results demonstrate that remote sensing technology could be successfully applied to early detect D. valens infestation and clarify the sensitive spectral regions and vegetation indices, which has important implications for early detection based on unmanned airborne vehicle and satellite data.
Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy
Authors: Zhang Xiaoning , Jiao Ziti , Zhao Changsen , Qu Ying , Liu Qiang , Zhang Hu , Tong Yidong , Wang Chenxia , Li Sijie , Guo Jing , Zhu Zidong , Yin Siyang , Cui Lei
Published: March 2022

Surface albedo plays a controlling role in the surface energy budget, and albedo-induced radiative forcing has a significant impact on climate and environmental change (e.g., global warming, snow and ice melt, soil and vegetation degradation, and urban heat islands (UHIs)). Several existing review papers have summarized the algorithms and products of surface albedo as well as climate feedback at certain surfaces, while an overall understanding of various land types remains insufficient, especially with increasing studies on albedo management methods regarding mitigating global warming in recent years. In this paper, we present a comprehensive literature review on the variance pattern of surface albedo, the subsequent climate impact, and albedo management strategies. The results show that using the more specific term “surface albedo” is recommended instead of “albedo” to avoid confusion with similar terms (e.g., planetary albedo), and spatiotemporal changes in surface albedo can indicate subtle changes in the energy budget, land cover, and even the specific surface structure. In addition, the close relationships between surface albedo change and climate feedback emphasize the important role of albedo in climate simulation and forecasting, and many albedo management strategies (e.g., the use of retroreflective materials (RRMs)) have been demonstrated to be effective for climate mitigation by offsetting CO2 emissions. In future work, climate effects and management strategies regarding surface albedo at a multitude of spatiotemporal resolutions need to be systematically evaluated to promote its application in climate mitigation, where a life cycle assessment (LCA) method considering both climate benefits and side effects (e.g., thermal comfort) should be followed.
Remote Sensing Based Conservation Effectiveness Evaluation of Mangrove Reserves in China
Authors: Liu Xiaoliang , Yang Xiaomei , Zhang Tao , Wang Zhihua , Zhang Junyao , Liu Yueming , Liu Bin
Published: March 2022

In recent decades, the mangrove area in China has changed dramatically, and governments have established multiple mangrove protected areas at various levels. However, we know little about the effectiveness of conservation on mangroves on a national scale. In this study, we constructed an evaluation index system for landscape health and proposed a landscape health composite index (LHCI) to characterize the landscape health status of mangroves. Based on the distribution dataset of mangrove forests mangrove in the recent 40 years, we evaluated the conservation effectiveness of mangrove reserves in China from a perspective of landscape health. The dynamics of mangrove areas show that the mangrove area in 83% of the reserves increased after the establishment of reserves. Additionally, the increase in mangrove area in provincial-level, municipal-level, and county-level reserves was higher than that in national-level reserves, and the most significant increase in mangrove area was in Guangxi, followed by Fujian and Hong Kong. The evaluation results show that mangrove reserves have achieved outstanding conservation effectiveness in China, with 43% of the reserves significantly improving the landscape health status of mangroves and 35% of the reserves maintaining good condition. The reserves in Guangxi, Guangdong, and Fujian Provinces showed more significant protective effects. Specifically, the most effective reserves protecting mangroves were the Qi’ao Island reserve, Maowei Gulf reserve, and Enping reserve. This study may provide references for formulating a rapid evaluation method of conservation effectiveness based on remote sensing and promote the scientific management of protected areas and the ecological restoration of mangroves in China.
AutoRet: A Self-Supervised Spatial Recurrent Network for Content-Based Image Retrieval
Authors: Monowar Muhammad Mostafa , Hamid Md. Abdul , Ohi Abu Quwsar , Alassafi Madini O. , Mridha M. F.
Published: March 2022

Image retrieval techniques are becoming famous due to the vast availability of multimedia data. The present image retrieval system performs excellently on labeled data. However, often, data labeling becomes costly and sometimes impossible. Therefore, self-supervised and unsupervised learning strategies are currently becoming illustrious. Most of the self/unsupervised strategies are sensitive to the number of classes and can not mix labeled data on availability. In this paper, we introduce AutoRet, a deep convolutional neural network (DCNN) based self-supervised image retrieval system. The system is trained on pairwise constraints. Therefore, it can work in self-supervision and can also be trained on a partially labeled dataset. The overall strategy includes a DCNN that extracts embeddings from multiple patches of images. Further, the embeddings are fused for quality information used for the image retrieval process. The method is benchmarked with three different datasets. From the overall benchmark, it is evident that the proposed method works better in a self-supervised manner. In addition, the evaluation exhibits the proposed method’s performance to be highly convincing while a small portion of labeled data are mixed on availability.
Force Sensing on Cells and Tissues by Atomic Force Microscopy
Authors: Holuigue Hatice , Lorenc Ewelina , Chighizola Matteo , Schulte Carsten , Varinelli Luca , Deraco Marcello , Guaglio Marcello , Gariboldi Manuela , Podestà Alessandro
Published: March 2022

Biosensors are aimed at detecting tiny physical and chemical stimuli in biological systems. Physical forces are ubiquitous, being implied in all cellular processes, including cell adhesion, migration, and differentiation. Given the strong interplay between cells and their microenvironment, the extracellular matrix (ECM) and the structural and mechanical properties of the ECM play an important role in the transmission of external stimuli to single cells within the tissue. Vice versa, cells themselves also use self-generated forces to probe the biophysical properties of the ECM. ECM mechanics influence cell fate, regulate tissue development, and show peculiar features in health and disease conditions of living organisms. Force sensing in biological systems is therefore crucial to dissecting and understanding complex biological processes, such as mechanotransduction. Atomic Force Microscopy (AFM), which can both sense and apply forces at the nanoscale, with sub-nanonewton sensitivity, represents an enabling technology and a crucial experimental tool in biophysics and mechanobiology. In this work, we report on the application of AFM to the study of biomechanical fingerprints of different components of biological systems, such as the ECM, the whole cell, and cellular components, such as the nucleus, lamellipodia and the glycocalyx. We show that physical observables such as the (spatially resolved) Young’s Modulus (YM) of elasticity of ECMs or cells, and the effective thickness and stiffness of the glycocalyx, can be quantitatively characterized by AFM. Their modification can be correlated to changes in the microenvironment, physio-pathological conditions, or gene regulation.
Recreating the Motion Trajectory of a System of Articulated Rigid Bodies on the Basis of Incomplete Measurement Information and Unsupervised Learning
Authors: Nalepa Bartłomiej , Pawlyta Magdalena , Janiak Mateusz , Szczęsna Agnieszka , Gwiazda Aleksander , Wojciechowski Konrad
Published: March 2022

Re-creating the movement of an object consisting of articulated rigid bodies is an issue that concerns both mechanical and biomechanical systems. In the case of biomechanical systems, movement re-storation allows, among other things, introducing changes in training or rehabilitation exercises. Motion recording, both in the case of mechanical and biomechanical systems, can be carried out with the use of sensors recording motion parameters or vision systems and with hybrid solutions. This article presents a method of measuring motion parameters with IMU (Inertial Measurement Unit) sensors. The main assumption of the article is to present the method of data estimation from the IMU sensors for the given time moment on the basis of data from the previous time moment. The tested system was an industrial robot, because such a system allows identifying the measurement errors from IMU sensors and estimating errors basing on the reference measurements from encoders. The aim of the research is to be able to re-create the movement parameters of an object consisting of articulated rigid bodies on the basis of incomplete measurement information from sensors. The developed algorithms can be used in the diagnostics of mechanical systems as well as in sport or rehabilitation. Limiting sensors will allow, for example, athletes defining mistakes made during training only on the basis of measurements from one IMU sensor, e.g., installed in a smartphone. Both in the case of rehabilitation and sports, minimizing the number of sensors allows increasing the comfort of the person performing a given movement as part of the measurement.
Image Denoising Using a Compressive Sensing Approach Based on Regularization Constraints
Authors: Mahdaoui Assia El , Ouahabi Abdeldjalil , Moulay Mohamed Said
Published: March 2022

In remote sensing applications and medical imaging, one of the key points is the acquisition, real-time preprocessing and storage of information. Due to the large amount of information present in the form of images or videos, compression of these data is necessary. Compressed sensing is an efficient technique to meet this challenge. It consists in acquiring a signal, assuming that it can have a sparse representation, by using a minimum number of nonadaptive linear measurements. After this compressed sensing process, a reconstruction of the original signal must be performed at the receiver. Reconstruction techniques are often unable to preserve the texture of the image and tend to smooth out its details. To overcome this problem, we propose, in this work, a compressed sensing reconstruction method that combines the total variation regularization and the non-local self-similarity constraint. The optimization of this method is performed by using an augmented Lagrangian that avoids the difficult problem of nonlinearity and nondifferentiability of the regularization terms. The proposed algorithm, called denoising-compressed sensing by regularization (DCSR) terms, will not only perform image reconstruction but also denoising. To evaluate the performance of the proposed algorithm, we compare its performance with state-of-the-art methods, such as Nesterov’s algorithm, group-based sparse representation and wavelet-based methods, in terms of denoising and preservation of edges, texture and image details, as well as from the point of view of computational complexity. Our approach permits a gain up to 25% in terms of denoising efficiency and visual quality using two metrics: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).
Initial Study Using Electrocardiogram for Authentication and Identification
Authors: Pereira Teresa M. C. , Conceição Raquel C. , Sebastião Raquel
Published: March 2022

Recently, several studies have demonstrated the potential of electrocardiogram (ECG) to be used as a physiological signature for biometric systems (BS). We investigated the potential of ECG as a biometric trait for the identification and authentication of individuals. We used data from a public database, CYBHi, containing two off-the-person records from 63 subjects, separated by 3 months. For the BS, two templates were generated: (1) cardiac cycles (CC) and (2) scalograms. The identification with CC was performed with LDA, kNN, DT, and SVM, whereas a convolutional neural network (CNN) and a distance-based algorithm were used for scalograms. The authentication was performed with a distance-based algorithm, with a leave-one-out cross validation, for impostors evaluation. The identification system yielded accuracies of 79.37% and 69.84% for CC with LDA and scalograms with CNN, respectively. The authentication yielded an accuracy of 90.48% and an impostor score of 13.06% for CC, and it had an accuracy of 98.42% and an impostor score of 14.34% for scalograms. The obtained results support the claim that ECG can be successfully used for personal recognition. To the best of our knowledge, our study is the first to thoroughly compare templates and methodologies to optimize the performance of an ECG-based biometric system.
Utility of the Novel MediPost Mobile Posturography Device in the Assessment of Patients with a Unilateral Vestibular Disorder
Authors: Rosiak Oskar , Gawronska Anna , Janc Magdalena , Marciniak Pawel , Kotas Rafal , Zamyslowska-Szmytke Ewa , Jozefowicz-Korczynska Magdalena
Published: March 2022

Balance disorders are a growing problem worldwide. Thus, there is an increasing need to provide an inexpensive and feasible alternative to standard posturographic platforms (SP) used for the assessment of balance and to provide a possible solution for telemonitoring of patients. A novel mobile posturography (MP) MediPost device was developed to address these issues. This prospective study used a Modified Clinical Test of Sensory Interaction on Balance to evaluate healthy individuals and patients with a unilateral vestibular disorder through SP and MP simultaneously. The control group included 65 healthy volunteers, while the study group included 38 patients diagnosed with a unilateral vestibular deficit. The angular velocity values obtained from both methods were compared by intraclass correlation coefficients (ICC) and Bland–Altman plot analysis. Diagnostic capabilities were measured in terms of sensitivity and specificity. The ICC between the two methods for conditions 2–4 was indicative of excellent reliability, with the ICC > 0.9 (p < 0.001), except for Condition 1 (standing stance, eyes open) ICC = 0.685, p < 0.001, which is indicative of moderate reliability. ROC curve analysis of angular velocity for condition 4 represents the most accurate differentiating factor with AUC values of 0.939 for SP and 0.953 for MP. This condition also reported the highest sensitivity, specificity, PPV, and NPV values with 86.4%, 87.7%, 80%, and 90.5% for SP, and 92.1%, 84.6%, 77.8%, and 94.8% for MP, respectively. The newly developed MediPost device has high sensitivity and specificity in distinguishing between healthy individuals and patients with a unilateral vestibular deficit.
A High Accuracy AC+DC Current Transducer for Calibration
Authors: Xiao Xia , Song Hongtian , Li Hongbin
Published: March 2022

Facing a lack of high accuracy current standards in the calibration of AC (Alternating Current) + DC (Direct Current) measurement devices that function to measure DC and AC simultaneously, a measurement method with high accuracy is proposed based on zero-flux self-oscillating fluxgate. An iron core and two windings are added onto the single-iron-core double-winding structure of the traditional self-oscillating fluxgate. The added iron core and its upper winding are used to weaken the influence of ripple on the sensor’s accuracy. The other one of the added windings is used for the feedback from the AC+DC magnetic potential, allowing the sensor to work in a zero-flux state and to measure AC+DC simultaneously. An AC+DC transducer prototype with an AC ranging from 0–500 A and DC 0–300 A is developed by selecting the core parameters and an optimized design of the circuit. The test results of the prototype show that the prototype can measure the AC and DC simultaneously, and the measurement accuracy reaches class 0.05 level in the nominal current range. This transducer can be used as a calibration standard of measurement devices for AC only, DC only, or AC and DC simultaneously. Compared with the AC+DC current transducer with the same accuracy level, the proposed transducer has fewer cores and simpler measuring circuit.
Product Quality Assessment in the Internet of Things: A Consumer-Oriented Approach
Authors: Naem Mohammed Sharief Abdelrahman , Koudil Mouloud , Ouldimam Zineeddine
Published: March 2022

This paper proposes a consumer-oriented approach to IoT product recommendations. It is designed to help new consumers choose high-quality IoT products that best meet their needs. We used hybrid techniques to implement the proposed approach. Experiments were also conducted to implement an intelligent IoT marketing system at the Rehab marketplace. The system has shown good results in its performance, usability, and user satisfaction. These results confirm the applicability and effectiveness of the approach in assessing and recommending IoT products.
Fabrication of Glass Diaphragm Based Fiber-Optic Microphone for Sensitive Detection of Airborne and Waterborne Sounds
Authors: Wu Gaomi , Hu Xinyu , Liu Xin , Dong Zhifei , Yue Yan , Cai Chen , Qi Zhi-mei
Published: March 2022

A glass-diaphragm microphone was developed based on fiber-optic Fabry-Perot (FP) interferometry. The glass diaphragm was shaped into a wheel-like structure on a 150-μm-thick glass sheet by laser cutting, which consists of a glass disc connected to an outer glass ring by four identical glass beams. Such a structural diaphragm offers the microphone an open air chamber that reduces air damping and increases sensitivity and results in a cardioid direction pattern for the microphone response. The prepared microphone operates at 1550 nm wavelength, showing high stability in a range of temperature from 10 to 40 °C. The microphone has a resonance peak at 1152 Hz with a quality factor of 21, and its 3-dB cut-off frequency is 32 Hz. At normal incidence of 500 Hz sound, the pressure sensitivity of the microphone is 755 mV/Pa and the corresponding minimum detectable pressure is 251 μPa/Hz1/2. In addition to the above characteristics of the microphone in air, a preliminary investigation reveals that the microphone can also work stably under water for a long time due to the combination of the open-chamber and fiber-optic structures, and it has a large signal-to-noise ratio in response to waterborne sounds. The microphone prepared in this work is simple, inexpensive, and electromagnetically robust, showing great potential for low-frequency acoustic detection in air and under water.
Imbalanced Seismic Event Discrimination Using Supervised Machine Learning
Authors: Ahn Hyeongki , Kim Sangkyeum , Lee Kyunghyun , Choi Ahyeong , You Kwanho
Published: March 2022

The discrimination between earthquakes and artificial explosions is a significant issue in seismic analysis to efficiently prevent and respond to seismic events. However, the discrimination of seismic events is challenging due to the low incidence rate. Moreover, the similarity between earthquakes and artificial explosions with a local magnitude derives a nonlinear data distribution. To improve the discrimination accuracy, this paper proposes machine-learning-based seismic discrimination methods—support vector machine, naive Bayes, and logistic regression. Furthermore, to overcome the nonlinear separation problem, the kernel functions and regularized logistic regression are applied to design seismic classifiers. To efficiently design the classifier, P- and S-wave amplitude ratios on the time domain and spectral ratios on the frequency domain, which is converted by fast Fourier transform and short-time Fourier transform are selected as feature vectors. Furthermore, an adaptive synthetic sampling algorithm is adopted to enhance the classifier performance against the seismic data imbalance issue caused by the non-equivalent number of occurrences. The comparisons among classifiers are evaluated by the binary classification performance analysis methods.
A Decentralized Blockchain-Based Trust Management Framework for Vehicular Ad Hoc Networks
Authors: Gazdar Tahani , Alboqomi Ohoud , Munshi Asmaa
Published: March 2022

Vehicular Ad hoc Networks (VANETs) are one of the pillars of the Internet of Vehicles, they provide plenty of applications ranging from safety to entertainment. Safety applications largely depend on reliable and authentic traffic-related data. However, ensuring the data reliability and authenticity is facing many challenges due mainly to the scalability of VANETs such as the high speed, the long roads, and the open nature of VANETs. This paper addresses these challenges by proposing a decentralized Blockchain-based trust management framework (BC-TMF) aiming to compute trust metrics for vehicles. These trust metrics rely on the authenticity of the messages. Each vehicle assesses the authenticity of the received messages in real-time, calculates a local trust metric for the originator of such messages, then shares it with a miner. Periodically each miner aggregates the received trust metrics into global trust metrics, then packs them in a block. To investigate the efficiency and consistency of the proposed framework, extensive simulations are conducted. The obtained results show that the proposed BC-TMF has an excellent capability in computing accurate trust metrics for vehicles. Besides, it outperforms the existing ones in terms of the accuracy of computed trust metrics, particularly for malicious vehicles.
The Mediating Role of Firm Strategy in the Relationship between Green Entrepreneurship, Green Innovation, and Competitive Advantage: The Case of Medium and Large-Sized Firms in Greece
Authors: Skordoulis Michalis , Kyriakopoulos Grigorios , Ntanos Stamatiοs , Galatsidas Spyros , Arabatzis Garyfallos , Chalikias Miltiadis , Kalantonis Petros
Published: March 2022

The present research examines both the relationship between green innovation and green entrepreneurship and the mediating role of firm strategies in the relationship between green entrepreneurship, green innovation, and competitive advantage. A total of 225 managers responsible for the environmental strategy of medium and large-sized firms operating in Greece were used as a sample for the study. To measure the research variables, a structured questionnaire was used. The collected data were analyzed using descriptive and inductive statistics, including principal components analysis, correlation analysis, a multivariate generalized linear model, and a structural equations model. The empirical results indicate a positive influence of green entrepreneurship in green product innovation and green process innovation. Furthermore, the mediating role of firm strategies in the relationship between green entrepreneurship, green innovation, and competitive advantage is confirmed.
Assessing the Role of the Young Farmer Scheme in the Export Orientation of Greek Agriculture
Authors: Staboulis Christos , Natos Dimitrios , Gkatsikos Alexandros , Tsakiridou Efthimia , Mattas Konstadinos , Bojar Waldemar , Baranowski Piotr , Krzyszczak Jaromir , Rivero Obdulia Parra , Roldán Álvaro Ojeda
Published: March 2022

The present paper attempts to investigate whether the Sub-Measure 6.1 “Start-Up Aid for Young Farmers” payments of the 2014–2020 Rural Development Programme have a role to play in explaining Greek farms’ export orientation and export performance through a statistical analysis of farm-level data. The results demonstrate considerable differences in farm structures between beneficiaries and non-beneficiaries and provide support for the contention that beneficiaries are more likely to operate more productive and economically efficient farms. However, the results also provide a sobering assessment of the role of the young-farmer-related subsidies in stimulating export orientation and export performance.
The Measurable Predominance of Weekend Trips in Established Tourism Regions—The Case of Visitors from Budapest at Waterside Destinations
Authors: Kádár Bálint , Gede Mátyás
Published: March 2022

Short trips to weekend destinations are less researched than more conventional forms of tourism involving longer trips and overnight stays, because quantitative data are hard to procure on the behavior of such weekend tourists. As a result, the effects of these day trips on secondary destinations cannot be measured, yet weekend tourism does contribute to the economic sustainability of many tourism regions. In this study, we analyzed geotagged photography uploaded to Flickr.com in the Budapest metropolitan area, the Danube Bend north of the Hungarian capital, and the Northern Balaton Region. Analysis of the spatio-temporal activity of photographers revealed Flickr users who live in the analyzed regions or in foreign countries, identifying the locals, weekend visitors from Budapest, those from other Hungarian regions, and foreign tourists. The predominance of visitors from Budapest was measured in both of the water-side destinations, and the spatial patterns of such visitors were more dispersed than the more concentrated spatial patterns of foreign tourists. These results show how day-trippers spread out the economic effects of tourism to much wider geographic areas than conventional tourists. Therefore, more focus should be directed toward these previously invisible forms of visits among the scientific community, policy makers, and the tourism industry.
Menu Choice and Meat-Eating Habits: Results of a Field Experiment in Two University Canteens
Authors: Egeler Gian-Andrea , Baur Priska
Published: March 2022

In a transdisciplinary field experiment in two Swiss university canteens over 12 weeks, how customers respond to a revised menu choice of meat dishes and ovo-lacto-vegetarian or vegan dishes was investigated. Several interventions were implemented: the vegetarian menu line was abolished, the meat and veg-dishes were randomly distributed across the three menu lines, vegetarian and vegan dishes (veg-dishes) were not labelled or marketed as such, and in the 6 ‘intervention weeks’ the share of veg-dishes was increased compared to the 6 ‘base weeks’. Based on the lunchtime eating habits in the canteen, regular canteen visitors were categorised into either seven or five different ‘lunch types’. During the intervention weeks, the share of meat dishes decreased for every lunch type, although with different response patterns. It is particularly noteworthy that customers with meat-oriented lunchtime eating habits ate in the canteen more frequently. This indicates that the usual choices in the two canteens are more appealing for meat-eaters. Overall, the data show a clear potential to reduce meat consumption in canteens by increasing the range of attractive veg-dishes without explicitly marketing them as vegetarian or vegan. We conclude this also to be an economically profitable strategy, as it provides a chance to attract customers with veg-oriented lunchtime eating habits without either losing meat eaters or meat lovers.
Systematic Review of Intervention Studies to Foster Sustainable Employability Core Components: Implications for Workplace Promotion
Authors: Picco Eleonora , Gragnano Andrea , Daghini Arianna , Miglioretti Massimo
Published: March 2022

This review aims to outline the effectiveness of employer-initiated workplace interventions in promoting sustainable employability (SE), which means developing workers’ capabilities to foster productivity, health, and valuable work in the long term. A systematic search of the literature is performed in three databases covering the period from January 1999 to February 2022. Fourteen studies are included. Considering SE core components, all interventions cover the valuable work component in terms of content, and the majority also cover the health component. Interventions addressing at least three SE components have more positive effects on SE outcomes. More positive effects are found for valuable work outcomes. Overall, the findings highlight the importance of developing workplace interventions considering a comprehensive model of SE and promoting an organizational culture for SE. Future directions and limits are discussed.
Current Status and Potential of Biofortification to Enhance Crop Nutritional Quality: An Overview
Authors: Sheoran Seema , Kumar Sandeep , Ramtekey Vinita , Kar Priyajoy , Meena Ram Swaroop , Jangir Chetan Kumar
Published: March 2022

Around 2 billion people are suffering from chronic malnutrition or “hidden hunger”, which is the result of many diseases and disorders, including cognitive degeneration, stunting growth, and mortality. Thus, biofortification of staple food crops enriched with micronutrients is a more sustainable option for providing nutritional supplements and managing malnutrition in a society. Since 2001, when the concept of biofortification came to light, different research activities have been carried out, like the development of target populations, breeding or genetic engineering, and the release of biofortified cultivars, in addition to conducting nutritional efficacy trials and delivery plan development. Although, being a cost-effective intervention, it still faces many challenges, like easy accessibility of biofortified cultivars, stakeholders’ acceptance, and the availability of biofortified germplasm in the public domain, which varies from region to region. Hence, this review is focused on the recent potential, efforts made to crop biofortification, impacts analysis on human health, cost-effectiveness, and future perspectives to further strengthen biofortification programs. Through regular interventions of sustainable techniques and methodologies, biofortification holds huge potential to solve the malnutrition problem through regular interventions of nutrient-enriched staple food options for billions of people globally.
Optimal Location and Sizing of Distributed Generators in Power System Network with Power Quality Enhancement Using Fuzzy Logic Controlled D-STATCOM
Authors: Prashant  , Siddiqui Anwar Shahzad , Sarwar Md , Althobaiti Ahmed , Ghoneim Sherif S. M.
Published: March 2022

This article presents the selection of location and sizing of multiple distributed generators (DGs) for boosting performance of the radial distribution system in the case of constant power load flow and constant impedance load flow. The consideration of placing and sizing of DGs is to meet the load demand. This article tries to overcome the limitations of existing techniques for determining the appropriate location and size of DGs. The selection of DG location is decided in terms of real power losses, accuracy, and sensitivity. The size of DG is measured in terms of real and reactive power. Both positioning and sizing of DG are analyzed with the genetic algorithm and the heuristic probability distribution method. The results are compared with other existing methods such as ant-lion optimization algorithm, coyote optimizer, modified sine-cosine algorithm, and particle swarm optimization. Further, the power quality improvement of the network is assessed by positioning D-STATCOM, and its location is decided on the basis of the nearby bus having poor voltage profile and high total harmonic distortion (THD). The switching and controlling of D-STATCOM are assessed with fuzzy logic controller (FLC) for improving the performance parameters such as voltage profile and THD at that particular bus. The proposed analytical approach for the system is tested on the IEEE 33 bus system. It is observed that the performance of the system with the genetic algorithm gives a better solution in comparison to heuristic PDF and other existing methods for determining the optimal location and size of DG. The introduction of D-STATCOM into the system with FLC shows better performance in terms of improved voltage profile and THD in comparison to existing techniques.
New Energy Vehicle Consumer Demand Mining Research Based on Fusion Topic Model: A Case in China
Authors: Wang Xiaoguang , Lv Tao , Fan Lei
Published: March 2022

This study extracted the demand preference topic words of new energy vehicle consumers with the help of the topic model, calculated the similarity between the word vectors and the topic keywords and expanded the topic keywords, analyzed and compared the demand topics and feature expansion words of different car models, and summarized the demand differences of other consumer groups. The analysis results show that consumers’ demands of different groups have the exact demand dimensions such as new energy features and brand features, and different demand dimensions such as application, services, and professional performance. The research findings help consumers filter valuable information from online review data and help car companies objectively and accurately obtain consumer demands, develop more reasonable marketing strategies, and achieve healthy and sustainable corporate development.
Peanut Drought Risk Zoning in Shandong Province, China
Authors: Jiang Meiyi , Xue Xiaoping , Zhang Lijuan , Chen Yuying , Zhao Cheng , Song Haiyan , Wang Nan
Published: March 2022

Peanut growth in Shandong Province, a major peanut-producing area in China, is greatly affected by drought. The present study uses hierarchical analysis, weighted comprehensive evaluation, and ArcGIS spatial analysis to conduct spatial zoning of peanut drought risk in Shandong Province based on daily precipitation data for the province acquired from 1991 to 2020, the per capita GDP, and the peanut planting area of Shandong Province, so as to quantify the disaster risk of peanut drought and formulate disaster prevention and resilience planning accordingly. The results show the high-drought-risk zone was mainly distributed in the northwestern part of Shandong Province and on the Jiaodong Peninsula, covering 32.4% of the province. Drought risk was concentrated on the Jiaodong Peninsula, covering 20.7% of the province. The high-vulnerability zone was mainly distributed in the cities of Yantai, Weihai, Linyi, and Rizhao, accounting for 26.8% of the total area. The low-disaster-prevention and low-mitigation-capacity zone was mainly distributed in the western part of Shandong Province, covering 38.7% of the province. Medium- and high-risk areas for drought affecting peanuts were widely distributed, while the overall comprehensive risk index was high, covering 76.2% of the province. Spatial analysis to conduct risk zoning and assessment of peanut drought in Shandong Province, so as to provide a basis for peanut drought disaster prevention and safe peanut production in Shandong Province.
Participatory Guarantee Systems: When People Want to Take Part
Authors: Cuéllar-Padilla Mamen , Haro-Pérez Isabel , Begiristain-Zubillaga Mirene
Published: March 2022

Participatory guarantee systems (PGSs) have emerged as a response to exclusion and intermediation processes involving third-party certification, which is currently the only guarantee system recognised by the European Union for organic food. Despite their unofficial recognition, PGSs are developing and generating shared frameworks of action. In this research, through three certification bodies (two public and one private) and eight PGSs in Spain, we investigate the similarities and differences between the procedures and tasks that both systems develop in order to generate trust in the decision-making structures involved and the responsibilities on which they are based. While the overall organisation of the systems is very similar, there are profound differences in their decision-making: their procedures and who participates in them. The differences we highlight lead us to argue that PGSs effectively solve the exclusion problems that third-party certification generates. Specifically, they offer lower costs and more accessible bureaucracy. They also generate and strengthen, through trust-building, the links and processes of local self-management and empowerment. However, developing PGSs demands much time and dedication, and their official regulation is complex, so it is difficult to predict that they will be widely adopted.
The Impact of Economic Sustainability in the Transport Sector on GDP of Neighbouring Countries: Following the Example of the Baltic States
Authors: Ševčenko-Kozlovska Galina , Čižiūnienė Kristina
Published: March 2022

Transport is very important for the economy and the society because good transport infrastructure helps to improve the mobility of citizens and the traffic of goods, thus ensuring economic sustainability. Background: The European Union (hereinafter—EU) plans to maintain support for the development of transport infrastructure in individual member states. Lithuania’s role as a transit country in the EU’s transport network is of great importance; therefore, efficient transport services and appropriate infrastructure can not only support the domestic market and economic and social growth of the country, but also promote positive economic, social, and political processes in other countries and ensure EU’s strategic defence movement channels. Methods: The study was conducted using econometric methods, including correlation analysis and a regression model, to assess the selected parameters of the transport sector of Lithuania as a transit country and their impact on the real gross domestic product (hereinafter—RGDP) of the selected Baltic states (Latvia and Estonia). Results: The study identified a combination of key factors in the Lithuanian transport sector that affect differences in the level of real GDP per capita. Conclusions: The findings revealed differences in the context of relation between RGDP per capita in the three Baltic states and indicators of the Lithuanian transport sector.
Safety Measures and Risk Analysis for Outdoor Recreation Technicians and Practitioners: A Systematic Review
Authors: Mata Carlos , Pereira Catarina , Carvalhinho Luís
Published: March 2022

There is no expectation to suppress all accidents in the outdoor recreation sector; nevertheless, it is expected that all possible safety measures are taken in order to minimize the risk of accidents. The objective of this study was to systematize the knowledge regarding recommended and used safety measures and risk assessments for technicians and outdoor recreation practitioners. We conducted a systematic review on PubMed, BVS, SciELO, Science Direct, ABI/INFORM, Spinger, Web of Knowledge, and Esmerald full text databases, up to February 2021. The eligible criteria followed the PICOS strategy; the included risk assessment studies on outdoor recreation (according to its definition) had methodological quality, were indexed, and peer reviewed. Ten studies, from ten countries, fulfilled these specifications, which focused on different approaches. Five studies focused on risk perception, four studies focused on safety practices, injuries, and risk assessment; three studies addressed safe behaviors; two studies addressed equipment- and risk matrix-related themes. We concluded that there was a concern for this topic, and the 28 mentioned measures could provide important information regarding health and prevention. These measures could be used to develop safety strategies and risk reduction, aimed at reducing accidents in outdoor recreation activities. In order to evaluate the pertinence and importance of the mentioned measures, namely risk perception, safe practices, sport injuries, risk analysis, safe behaviors, as well as equipment and risk assessment matrices, further investigation is needed using experimental or observational designs. These strategies and procedures can contribute to enhanced interventions by technicians with higher security and quality, and therefore, improved well-being and satisfaction of practitioners.