bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Multitemporal Changes with Artificial Neural Network-Based Change Detection Algorithm Using Hyperspectral Dataset
Authors: Dahiya Neelam , Singh Sartajvir , Gupta Sheifali , Rajab Adel , Hamdi Mohammed , Elmagzoub M. , Sulaiman Adel , Shaikh Asadullah
Published: March 2023

Monitoring the Earth’s surface and objects is important for many applications, such as managing natural resources, crop yield predictions, and natural hazard analysis. Remote sensing is one of the most efficient and cost-effective solutions for analyzing land-use and land-cover (LULC) changes over the Earth’s surface through advanced computer algorithms, such as classification and change detection. In the past literature, various developments were made to change detection algorithms to detect LULC multitemporal changes using optical or microwave imagery. The optical-based hyperspectral highlights the critical information, but sometimes it is difficult to analyze the dataset due to the presence of atmospheric distortion, radiometric errors, and misregistration. In this work, an artificial neural network-based post-classification comparison (ANPC) as change detection has been utilized to detect the muti-temporal LULC changes over a part of Uttar Pradesh, India, using the Hyperion EO-1 dataset. The experimental outcomes confirmed the effectiveness of ANPC (92.6%) as compared to the existing models, such as a spectral angle mapper (SAM) based post-classification comparison (SAMPC) (89.7%) and k-nearest neighbor (KNN) based post-classification comparison (KNNPC) (91.2%). The study will be beneficial in extracting critical information about the Earth’s surface, analysis of crop diseases, crop diversity, agriculture, weather forecasting, and forest monitoring.
A Novel Bistatic SAR Maritime Ship Target Imaging Algorithm Based on Cubic Phase Time-Scaled Transformation
Authors: Yang Qing , Li Zhongyu , Li Junao , An Hongyang , Wu Junjie , Pi Yiming , Yang Jianyu
Published: March 2023

Due to the advantages of flexible configuration, bistatic synthetic aperture radar (BiSAR) has the ability to effectively observe from various visual angles, such as forward view area and squint area, and has good anti-jamming characteristics. It can be applied to the surveillance of ship targets on the sea and is gradually gaining an increasing amount of attention. However, for ship targets with complex motions on the sea surface, such as maneuvering targets or ship targets under high sea conditions, the high-order Doppler frequency of the scattering points is always spatial variation (related to the spatial position of scattering points), which poses a considerable challenge for the imaging of maritime ship targets in BiSAR. To resolve this problem, a BiSAR maritime ship target imaging algorithm based on cubic phase time-scaled transformation is proposed in this paper. First, through pre-processing of echo such as Doppler prefiltering and keystone transform, the translation compensation of the BiSAR maritime ship target is completed, and the scattering point energy is corrected to within one range unit. Then, the azimuth signal is modeled as a multi-component cubic phase signal. Based on the proposed cubic phase time-scaled transformation, the Doppler centroid, frequency rate, and third-order frequency of scattering points are estimated. Eventually, the BiSAR imaging of maritime ship targets is realized. This algorithm has excellent noise immunity and low cross-terms. The simulation leads to the verification of the validity of the proposed algorithm.
Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models
Authors: Alexiou Simoni , Efthimiou Nikolaos , Karamesouti Mina , Papanikolaou Ioannis , Psomiadis Emmanouil , Charizopoulos Nikos
Published: March 2023

Model-based soil erosion studies have increased in number, given the availability of geodata and the recent technological advances. However, their accuracy remains rather questionable since the scarcity of field records hinders the validation of simulated values. In this context, this study aims to present a method for measuring sediment deposition at a typical Mediterranean catchment (870 ha) in Greece through high spatial resolution field measurements acquired by an Unmanned Aerial Vehicle (UAV) survey. Three-dimensional modeling is considered to be an emerging technique for surface change detection. The UAV-derived point cloud comparison, applying the Structure-from-Motion (SfM) technique at the Platana sediment retention dam test site, quantified annual topsoil change in cm-scale accuracy (0.02–0.03 m), delivering mean sediment yield of 1620 m3 ± 180 m3 or 6.05 t ha−1yr−1 and 3500 m3 ± 194 m3 or 13 t ha−1yr−1 for the 2020–2021 and 2021–2022 estimation. Moreover, the widely applied PESERA and RUSLE models estimated the 2020–2021 mean sediment yield at 1.12 t ha−1yr−1 and 3.51 t ha−1yr−1, respectively, while an increase was evident during the 2021–2022 simulation (2.49 t ha−1yr−1 and 3.56 t ha−1yr−1, respectively). Both applications appear to underestimate the net soil loss rate, with RUSLE being closer to the measured results. The difference is mostly attributed to the model’s limitation to simulate gully erosion or to a C-factor misinterpretation. To the authors’ better knowledge, this study is among the few UAV applications employed to acquire high-accuracy soil loss measurements. The results proved extremely useful in our attempt to measure sediment yield at the cm scale through UAV-SfM and decipher the regional soil erosion and sediment transport pattern, also offering a direct assessment of the retention dams’ life expectancy.
Bio-Geophysical Suitability Mapping for Chinese Cabbage of East Asia from 2001 to 2020
Authors: Shao Shuai , Takeuchi Wataru
Published: March 2023

The cultivation of Chinese cabbage is a crucial source of daily vegetable supply for both human consumption and livestock feed, particularly in East Asian countries. However, changes in global climate and land usage have resulted in significant shifts in the ecological conditions suitable for Chinese cabbage production, thereby threatening its productivity. To address this issue, this study was conducted to map the bio-geophysical suitability of Chinese cabbage in East Asia (Japan, Northeast China, South Korea, and North Korea) from 2001 to 2020. This study integrated six key factors—temperature, rainfall, photosynthetically active radiation (PAR), soil nitrogen, soil pH, and soil texture—into a seasonal and monthly bio-geophysical suitability assessment using a GIS-based Analytic Hierarchy Process–Multiple-Criteria Decision-Making Analysis (AHP-MCDA). The levels of bio-geophysical suitability were categorized into four levels: optimal, suitable, marginal, and unsuitable. The findings of the study firstly indicate that summer is the optimal season for Chinese cabbage cultivation, as it was found to have the highest level of optimal suitability among the four seasons in East Asia. South Korea has the largest percentage of optimal and suitable areas compared to the other three countries. Secondly, this study also conducted a comparison analysis between bio-geophysical suitability and Normalized Difference Vegetation Index (NDVI) over 20 years, and the results show good consistency between the two indicators, with the highest R2 value being 0.61. Thirdly, the comparison between bio-geophysical suitability and production data in two villages in Japan demonstrates that an increase in suitability from 0.28 to 0.32 indicates a significant increase in production. Production would stay stable even with further increases in suitability. Finally, two case studies with monthly comparisons of bio-geophysical suitability across Japan and East Asia in 2020 provide an effective benchmark for determining optimal sowing and harvest times. This study’s results can provide important insights into the trade of Chinese cabbage and support the development of agricultural insurance programs both for farmers and insurance companies. Furthermore, this approach may also be applicable for the assessment of the suitability of other crops.
Unmanned Aerial Vehicle (UAV) for Detection and Prediction of Damage Caused by Potato Cyst Nematode G. pallida on Selected Potato Cultivars
Authors: Jindo Keiji , Teklu Misghina Goitom , van Boheeman Koen , Njehia Njane Stephen , Narabu Takashi , Kempenaar Corne , Molendijk Leendert P. G. , Schepel Egbert , Been Thomas H.
Published: March 2023

High population densities of the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis cause substantial yield losses to potato production (Solanum tuberosum) due to the delay caused to tuber formation by the retardation of plant growth. It requires meticulous estimation of the population densities by using soil sampling and applying the right combination of nematode management to deal with the PCN problem. This study aims to assess the use of an unmanned vehicle (UAV) in detecting and estimating the effect of ranges of densities of a PCN, G. pallida, on four cultivated potato cultivars with resistance to PCN in a naturally infested potato field in The Netherlands. First, the initial population density (Pi) of G. pallida was estimated by using an intensive sampling method of collecting about 1.5 kg of soil per m2 from the center of each 3 × 5 m plot. At harvest, the fresh tuber yield of the potato cultivars (Avarna, Fontane, Sarion, and Serresta) were assessed. The Seinhorst yield loss model was used to investigate the relationship between Pi and fresh tuber yield. Secondly, the spatial data of UAV with optical and thermal sensors were analyzed to find any relationship between Pi and UAV indices. By using the classical yield loss model, all four cultivars were found to be affected by Pi with a relative minimum fresh tuber yield m, which ranged from 0.26 to 0.40. The maximum fresh tuber yield varied from 49.48 to 80.36 tons (ha)−1. The density at which the fresh tuber yield started to deteriorate was in the range of 0.62–2.16 eggs (g dry soil)−1. A regression was observed between Pi, and all UAV indices in a similar pattern to that of the fresh tuber yield by using the Seinhorst yield loss model, except for the cultivar Avarna for the two UAV indices (NDRE and NDVI). Unlike the tolerance limit, the relative minimum values of the UAV indices—except the chlorophyll index—differ when compared among each other and when compared with that of the fresh tuber yield within the same cultivar. This indicates that all indices can be useful for detection and decision making for statutory purposes but not for estimating damage (except the chlorophyll index).
Mapping Maize Tillage Practices over the Songnen Plain in Northeast China Using GEE Cloud Platform
Authors: Li Jian , Yu Weilin , Du Jia , Song Kaishan , Xiang Xiaoyun , Liu Hua , Zhang Yiwei , Zhang Weijian , Zheng Zhi , Wang Yan , Sun Yue
Published: March 2023

As the population grows, the development of conservation tillage offers a means of promoting the sustainability of agricultural engineering. Remote sensing images with high spatial and temporal resolutions enable the accurate monitoring of conservation tillage on a broad spatial scale, further promoting conservation tillage research. This paper describes using streamlined time series Sentinel-2 images based on the Google Earth Engine (GEE) cloud platform for mapping maize tillage practices in the Songnen Plain region of Northeast China. Based on the correlation with the normalized difference tillage index (NDTI) and maize residue coverage (MRC) data, the optimal time series and streamlining functions in the GEE cloud platform are determined. Estimates of MRC and the mapping of tillage practices in the Songnen Plain for 2019–2022 are then determined using GEE and a previous model. Geostatistical analysis using ArcGIS is applied to analyze the spatial and temporal distribution characteristics of MRC and conservation tillage over the Songnen Plain. The results show that time series images from 20–30 May achieve an r value of 0.902 and an R2 value of 0.8136 when using the median streamlining function. The mean MRC for the study area in 2022 is 2.3%, and an overall upward trend in conservation tillage is observed (from 0.08% in 2019 to 0.25% in 2022). Our analysis shows that MRC monitoring and conservation tillage mapping can be performed over a broad spatial scale using remote sensing technology based on the GEE cloud platform. Spatial and temporal information on farm practices provides a theoretical basis for agricultural development planning efforts, which can promote sustainable agricultural development.
Satellite Navigation Signal Authentication in GNSS: A Survey on Technology Evolution, Status, and Perspective for BDS
Authors: Chen Xiao , Luo Ruidan , Liu Ting , Yuan Hong , Wu Haitao
Published: March 2023

As the Global Navigation Satellite System (GNSS) is widely used in all walks of life, the signal structure of satellite navigation is open, and the vulnerability to spoofing attacks is also becoming increasingly prominent, which will seriously affect the credibility of navigation, positioning, and timing (PNT) services. Satellite navigation signal authentication technology is an emerging technical means of improving civil signal anti-spoofing on the satellite navigation system side, and it is also an important development direction and research focus of the GNSS. China plans to carry out the design and development of the next-generation Beidou navigation satellite system (BDS), and one of its core goals is to provide more secure and credible PNT services. This paper first expounds on the principles and technical architecture of satellite navigation signal authentication, then clarifies the development history of satellite navigation signal authentication, and finally proposes the BDS authentication service system architecture. It will provide technical support for the construction and development of the follow-up Beidou authentication service.
Editorial for Special Issue: “Remote Sensing of Hydrological Processes: Modelling and Applications”
Authors: García-Galiano Sandra G. , Cánovas-García Fulgencio , Giraldo-Osorio Juan Diego
Published: March 2023

Improvements in satellite remote sensing techniques have allowed the development of several platforms that are able to capture multitemporal data with a wide range of spatial and temporal resolutions [...]
Analysis of Seismic Impact on Hailuogou Glacier after the 2022 Luding Ms 6.8 Earthquake, China, Using SAR Offset Tracking Technology
Authors: Li Weile , Chen Junyi , Lu Huiyan , Yu Congwei , Shan Yunfeng , Li Zhigang , Dong Xiujun , Xu Qiang
Published: March 2023

An Ms 6.8 earthquake struck Luding County, Ganzi Prefecture, Sichuan Province on 5 September 2022, with the epicenter about 10 km away from Hailuogou Glacier. How Hailuogou Glacier was affected by the earthquake was of major concern to society. Sentinel-1 SAR satellite imaging was used to monitor the glacier surface velocity during different periods before and after the Luding earthquake based on pixel offset tracking (POT) technology, which applies a feature-tracking algorithm to overcome the phase co-registration problems commonly encountered in large displacement monitoring. The results indicated that the velocity had a positive correlation with the average daily maximum temperature and the slope gradient on the small-slope surfaces. The correlation was not apparent on the steeper surfaces, which corresponded spatially with the identified ice avalanche region in the Planet images. It was deduced that this may be because of the occurrence of ice avalanches on surfaces steeper than 25°, or that the narrower front channel impeded the glacier’s movement. The Luding earthquake did not cause a significant increase in the velocity of Hailuogou Glacier within a large range, but it disturbed the front area of the ice cascade, where the maximum velocity reached 2.5 m/d. Although the possibility of directly-induced destruction by ice avalanches after the earthquake was low, and the buffering in the downstream glacier tongue further reduced the risk of ice avalanches, the risk of some secondary hazards such as debris flow increased. The proposed method in this study might be the most efficient in monitoring and evaluating the effects of strong earthquakes on glaciers because it would not be limited by undesirable weather or traffic blockage.
Calibration Methods for Time-to-Digital Converters
Authors: Khaddour Wassim , Uhring Wilfried , Dadouche Foudil , Dumas Norbert , Madec Morgan
Published: March 2023

In this paper, two of the most common calibration methods of synchronous TDCs, which are the bin-by-bin calibration and the average-bin-width calibration, are first presented and compared. Then, an innovative new robust calibration method for asynchronous TDCs is proposed and evaluated. Simulation results showed that: (i) For a synchronous TDC, the bin-by-bin calibration, applied to a histogram, does not improve the TDC’s differential non-linearity (DNL); nevertheless, it improves its Integral Non-Linearity (INL), whereas the average-bin-width calibration significantly improves both the DNL and the INL. (ii) For an asynchronous TDC, the DNL can be improved up to 10 times by applying the bin–by-bin calibration, whereas the proposed method is almost independent of the non-linearity of the TDC and can improve the DNL up to 100 times. The simulation results were confirmed by experiments carried out using real TDCs implemented on a Cyclone V SoC-FPGA. For an asynchronous TDC, the proposed calibration method is 10 times better than the bin-by-bin method in terms of the DNL improvement.
Wound Healing Activity of the Flavonoid-Enriched Fraction of Selaginella bryopteris Linn. against Streptozocin-Induced Diabetes in Rats
Authors: Gautam Arti , Kumar Vikas , Azmi Lubna , Rao Ch. V. , Khan Mohammed Moizuddin , Mukhtar Beenish , Kamal Mehnaz , Arif Muhammad , Mehdi Seema , Alsanad Saud M. , Al-Khamees Osama A. , Jawaid Talha , Alam Aftab
Published: March 2023

Diabetes and its complications, such as delayed wound healing, are increasing at an alarming rate in India, putting an enormous strain on the country’s limited healthcare resources. Hence, the present study proposes to screen/identify the possible mechanisms and to study the effect of the flavonoid-enriched fraction of Selaginella bryopteris extract against human keratinocyte cell lines (HaCaT) and streptozocin (STZ)-induced diabetic wounds in a male Wistar rat model. Chemical profiling was performed by an MTT assay. The obtained GC–MS analysis results showed the presence of amentoflavone, gallic acid, imidazole, palmitic acid, catechine, L-fucitol, lupeol, and myo-inositol as the major bioactive phytoconstituents. S. bryopteris induces the generation of ROS, the condensation of chromatin in the nucleus, and changes in the membrane potential of mitochondria in HaCaT cell lines. An S. bryopteris-dependent induction of apoptosis-mediated cell death in HaCaT cell lines was confirmed by an AO/PI analysis. Mitochondrial depolarization was reflected in JC-1 staining of cells. The wound size was reduced and epithelialization was enhanced. Keratinocyte migration decreased interleukins, TNF-α, IL-2, and IL-6 and the expression of pro-apoptotic (p53, caspase-3, caspase-9, and Bax) and anti-apoptotic (Bcl-2) genes in a dose-dependent manner. Keratinocyte migration increased antioxidant enzyme levels (CAT, SOD, MDA, and GSH). Wound healing is facilitated through the mitochondria-mediated apoptosis pathway, revealing a new area of diabetic wound therapy.
Populism on the Web: Presidential Elections in Bolivia, Ecuador, Peru, and Colombia (2020–2022)
Authors: Quevedo-Stuva Maria-Ines , Tovar-Gil Gloria , Mila-Maldonado Andrea
Published: March 2023

Populism has become one of the main features of political action worldwide. This research aims to characterize the populist discourse in the tweets of presidential candidates in the Andean Community in recent elections (2020–2022). Accordingly, we analyze the characteristics of their social network profiles, as well as the content and latent discourse of their tweets. We demonstrate that the differences and similarities of their discourse go beyond their right and left association. The differences result from how they construct their identity and establish their relationship with their electorate. Our analysis reveals that this type of discourse is ideological as well as performative. It is ideological because, in the candidates’ discourse, they recontextualize the actual meanings of “us” and “them”. It is performative because it is carried out by a charismatic leader who acts in a specific way to define himself or herself as the embodiment of “the people” and “the good”.
Does Frequency or Amount Matter? An Exploratory Analysis the Perceptions of Four Universal Basic Income Proposals
Authors: Hamilton Leah , Despard Mathieu , Roll Stephen , Bellisle Dylan , Hall Christian , Wright Allison
Published: March 2023

Advocates for a Universal Basic Income (UBI) argue that it would provide citizens with a basic foundation for financial security, boost the economy, alleviate poverty, encourage entrepreneurship, reduce crime, and insulate the employment sector against job losses due to automation. Still, the idea lags in popularity in the United States compared to existing cash policies such as the annual Earned Income Tax Credit and one-time COVID-19 relief packages. We hypothesize that this disparity is related to predicted uses of a UBI in comparison to annual or lump sum cash programs. In this survey of 836 Americans, we explore whether predicted behavioral responses to four randomly assigned hypothetical cash transfer scenarios vary across the domains of amount and frequency. Respondents are more likely to associate monthly payments with work disincentives and lump-sum transfers with debt repayment. Implications for UBI advocates include the need to continue educating the public on the empirical associations between UBI, employment, and expenditures.
Toward New Value-Added Products Made from Anaerobic Digestate: Part 1—Study on the Effect of Moisture Content on the Densification of Solid Digestate
Authors: Łysiak Grzegorz , Kulig Ryszard , Al Aridhee Jawad Kadhim
Published: March 2023

Anaerobic digestion (AD) is widely used for the sustainable treatment of biological wastes and the production of biogas. Its byproduct, digestate, is a valuable organic waste and needs appropriate management, which is one of the major concerns with a negative impact on the efficiency of biogas installations. One approach to extend the utilization of digestate as well as improve its handling and storage characteristics is compaction into pellets. This study aimed to evaluate the behavior of digestate during cyclic loading and unloading in a closed matrix. The findings presented here may provide insights into the mechanisms of pellet formation for optimizing the production of pellets and improving their sustainable management. The study can be considered novel as it applied cyclic loading, for the first time, in view of densification modeling and pelleting prediction. A Zwick universal machine was used in the experiments. The moisture content of digestate was found to be 10–22%. Samples were loaded with a constant amplitude of 20 kN for 10 cycles. The distribution of energy inputs, including the total energy, energy of permanent deformations, and energy lost to elastic ones, was thoroughly evaluated. A decrease in the total loading energy was observed in the first cycle, in cycles 2–10, and after all 10 applied cycles due to the rise in the moisture content of digestate. Similar relations were also found for the nonrecoverable energy part. In subsequent cycles of loading/unloading, the values of total energy and permanent deformation energy fell asymptotically. One of the most noteworthy findings of the study was that the absolute values of elastic deformation energy were consistent across all the cycles and moisture levels. However, it was noted that the percentage of energy dissipated to elastic deformation in all cycles significantly increased as the moisture content increased. Loading, which contributed to elastic deformations, was identified as the key factor causing an increase in cumulative energy inputs, and the majority of the energy expended was dissipated. Dissipated energy was the only component that permanently altered the total energy required for compaction. Another important finding, which resulted from the analysis of successive courses of loading and unloading curves, was that the shape of the areas enclosed between the loading/unloading curves was significantly influenced by the moisture content of the digestate.
Effects of Pre-Turbocharger Turbine Water Injection on the Sustainable Performance of Spark Ignition Engine
Authors: Veza Ibham , Huat Ling Chee , Abas Mohd Azman , Idris Muhammad , Spraggon Martin , Herawan Safarudin G.
Published: March 2023

Water injection strategy is considered a promising technique to improve the performance of boosted engine and reduce the NOx emission via the latent heat of water vaporization. Numerous research on water injection has been conducted on in-cylinder and intake port water injection. However, the water injection focusing on the spark ignition (SI) engine exhaust system is still lacking. This study proposed a pre-turbocharger turbine water injection (PTWI) concept to reduce the turbine inlet temperature. This was done so that the stoichiometric engine operation could be achieved at a medium–high load and engine speed without resorting to a fuel enrichment strategy to reduce the exhaust gas temperature. This study aims to investigate the effect of injecting water into the exhaust gas at the pre-turbine of a turbocharged spark ignition engine. This study experimented on a 1.3-L 4-cylinder turbocharged engine to collect engine data for computational fluid dynamics (CFD) baseline model validation. A one-dimensional engine model was then developed based on the 1.6-L 4-cylinder turbocharged engine experiment using AVL BOOST software. The CFD model was used to investigate the effects of water injection pressure, pipe diameter, and water injector location. The CFD results showed that a 50 mm connecting pipe with 4 bar of injection pressure gives the largest reduction in exhaust temperature. The CFD results were then applied to the one-dimensional engine model. The engine model simulation results showed that the fuel consumption could be reduced up to 13% at 4000 rpm during wide-open throttle and 75% engine load. The PTWI is a new approach, but this study has proved the potential of using water injection at the pre-turbine turbocharger to reduce the fuel consumption of a turbocharged SI engine.
Steering Smart Mobility Services: Lessons from Seattle, Greater Manchester and Stockholm
Authors: Moscholidou Ioanna , Marsden Greg , Pangbourne Kate
Published: March 2023

This paper explores how three cities (Seattle, Greater Manchester and Stockholm) have approached the governance of smart mobility services in the early stages of their introduction. The research finds that cities have limited steering capacity, and when they do steer services this is done on the assumption that smart mobility will deliver wider social, environmental and economic good. While broad-ranging benefits are yet to materialise to any identifiable degree, the potential for smart mobility to tackle some of the challenges of automobility undoubtedly remains, and the new services are acting to change mobility patterns in cities, at least for some people. We focus on the need to develop clear accountability arrangements between the public and the private sector, which we see as a necessary element of a collaborative governance approach that allows both sides to identify shared goals and maximise their achievement. However, we stress that developing a collaborative approach requires cities to govern with intent, which means that services need to be deployed or permitted with clear objectives and an understanding of their anticipated impacts.
Citizen Science: Is It Good Science?
Authors: Davis Lloyd S. , Zhu Lei , Finkler Wiebke
Published: March 2023

Citizen science projects, which entail scientific work undertaken by members of the public, have increased substantially over the last three decades. However, the credibility of such science has been questioned, especially with respect to its prospects for producing peer-reviewed publications, the principal means by which science is communicated and validated. We conducted a meta-analysis of 895 citizen science projects launched between 1890 and 2018. Three-quarters (674) did not produce a single peer-reviewed paper. The remaining 221 projects produced 2075 publications, although just five projects accounted for nearly half the publications. The average time from project launch to first publication was 9.15 years. Projects in health and medicine and astronomy were most likely to produce publications. Projects in biology (65.8% of all projects), computer science, and social sciences were least likely to publish their results. In conclusion, the “science” element of most citizen science projects is largely irrelevant as it is never validated or communicated. We propose reclassifying citizen science projects into two types: (i) Citizen Science, where the focus is on science, and participants essentially function as sampling devices; and (ii) Citizen Engagement, where the value lies more in citizen engagement than it does in citizen science.
Novel Isolated Multiple-Input, Multiple-Output Multidirectional Converter for Modern Low-Voltage DC Power Distribution Architectures
Authors: Carrijo de Oliveira Raphael , Tofoli Fernando Lessa , Silva de Morais Aniel
Published: March 2023

This work introduces a multiple-input, multiple-output (MIMO) isolated converter for low-power applications involving residential DC nanogrids and nanogrids. The topology has a multiport characteristic that allows for the integration of loads and sources with distinct ratings, e.g., photovoltaic (PV) modules, battery banks, DC loads, and the AC grid. The structure relies on a DC-DC multi-winding multidirectional flyback converter that operates as power interface and can minimize the number of power conversion stages while enabling flexible power flow control. Owing to its multidirectional characteristic, a port can be responsible for supplying or absorbing energy using duty cycle control or phase-shift control, respectively. Since the operating modes of the converter are decoupled, a predictive controller is capable of managing the power flow among the ports independently. Simulation results are presented and discussed to evaluate the control system robustness and its performance in power flow management.
The Trees of the Pisa Botanic Garden under Climate Change Scenarios: What Are We Walking into?
Authors: D’Antraccoli Marco , Weiger Nóra , Cocchi Leonardo , Peruzzi Lorenzo
Published: March 2023

Botanical gardens are dynamic systems of high scientific, ecological, cultural, and historical value. They are irreplaceable places to cultivate, manage, study, and preserve tree diversity. One of the ongoing biggest challenges worldwide in managing and preserving trees is climate change, which exposes specimens to more stressful and severe environmental conditions, causing an increase in mortality. In our research, we aimed to assess the future climate change impact on the tree collection of Botanic Garden of Pisa in order to outline the expected consequences about tree cultivation and management. Under the most pessimistic scenario, in 2090 more than 60% of the tree species cultivated in the Botanic Garden of Pisa are expected to fall outside of their climatic niche. Future chances and pitfalls in managing urban green areas, focusing on the botanical garden community, are also explored.
Financing Sustainable Agriculture in Sub-Saharan Africa: A Review of the Role of Financial Technologies
Authors: Mapanje Olga , Karuaihe Selma , Machethe Charles , Amis Mao
Published: March 2023

African agriculture needs to adapt to climate change and shift from unsustainable production practices to sustainable ones. This requires innovative, substantial, and long-term agricultural investments that can allow all agricultural actors to adopt sustainable agricultural practices. Better and more inclusive options to leapfrog Africa’s sustainable agricultural development lie in financial technologies (FinTech). FinTech uses digital technology innovations to ease the provision of financial services to users and thus enhance financial inclusion. The aim of this study is to clarify the important role that FinTech can play in financing sustainability in agriculture in sub-Saharan Africa (SSA). To examine this role, the study shortlisted 17 SSA countries. The literature on FinTech-enhanced agricultural initiatives in these countries was reviewed. The results confirm that FinTech has the opportunity to become the much needed ‘support system’ for sustainable agriculture in SSA. Most of the financial products accessed by smallholder farmers in the selected countries helped the farmers in addressing production and marketing challenges in agriculture. The technologies can also help to improve efficiency in financing smallholder agriculture, enabling wider adoption of sustainable agricultural practices. To promote the financing of sustainable agriculture at scale, there is a need to train the farmers about the functionality of digital platforms, and policymakers need to address challenges such as gaps in infrastructure between the urban and rural areas.
Climate-Smart Pest Management in Sustainable Agriculture: Promises and Challenges
Authors: Bouri Meriam , Arslan Kadir Sinan , Şahin Fikrettin
Published: March 2023

Sustainable development in global and regional contexts has become mandatory to prevent the potential adverse effects of human activities on the environment. While agricultural activities stand as the leading source of degradation and pollution in ecosystems, climate changes are among the most important challenges facing agricultural productivity. Climate-smart agriculture involves farming methods and strategies adopted for the early diagnosis and management of climate crisis drawbacks. Changing climatic conditions affect plant health either through abiotic or biotic factors that influence diverse disease scenarios on a wide range of crops. Therefore, disease management under the concerns of climate change is considered the cornerstone of sustainable agriculture. The climate-smart pest management (CSPM) concept and its role in supporting sustainable agricultural development, particularly the effect of weather changes on phytosanitary issues, are reviewed in this article. Problems in implementation and difficulties in decision-making are among the main challenges facing CSPM, which still has both technological and coordination shortcomings to overcome. Intensifying collaborative activities in scientific and technological research, risk assessment, and surveillance may enhance the current efficiency of CSPM in terms of preserving the sustainable development of agricultural systems. More efforts for capacity building are also needed in developing countries to promote the implementation and adoption of CSPM.
Exploring Factors Influencing Neuromarketing Implementation in Malaysian Universities: Barriers and Enablers
Authors: Alsharif Ahmed H. , Salleh Nor Zafir Md , Hashem E Alharthi Rami , Khraiwish Ahmad , Putit Lennora , Arif Lily Suriani Mohd
Published: March 2023

This paper aims to explore academicians’ perceptions and perspectives regarding the limitations, challenges, and potential solutions of neuromarketing implementations in the Malaysian context. A semi-structured interview with 16 academicians was conducted. The findings revealed that several issues had impeded the growth of neuromarketing, such as ethical and manipulation concerns, the high cost, the need for specialized expertise, lack of proper knowledge and understanding, the lack of financial resources, the lack of labs and facilities, and time requirements. Despite these obstacles, the academicians suggested several potential solutions to enhance the application of neuromarketing, such as establishing strong collaborative networks, providing labs and facilities, increasing financial resources, complying with laws and regulations, and reducing tools and experiment costs. This study will significantly contribute to the body of knowledge by increasing awareness of the potential difficulties in implementing neuromarketing techniques and helping to guide future research and development. This information can inform decision making by practitioners, researchers, and stakeholders, allowing them to make more informed decisions about using and implementing neuromarketing. To the best of the authors’ knowledge, no current study has identified avenues for future research in neuromarketing and the emerging challenges and limitations that researchers may face in Malaysia. The current paper aims to foster the application of neuromarketing by providing potential solutions to overcome the obstacles researchers face. Moreover, quantitative research is required to test, measure, and validate the items revealed in this study’s findings.
Analysis of Countries in Terms of Artificial Intelligence Technologies: PROMETHEE and GAIA Method Approach
Authors: Ozkaya Gokhan , Demirhan Ayse
Published: March 2023

Artificial intelligence development and research leaders in business, industry, and nations gain a major competitive edge. Additionally, it is clear that nations with a well-established national artificial intelligence policy have an edge over others, both technologically and economically. To further their artificial intelligence capability, nations also seek to develop a strategy, vision, structure, and working environment that encourages collaboration between the public sector, private industry, and educational institutions. Artificial intelligence is thought to be a tool that will help bridge the gap between powerful and developing countries growing in the future. Using data from “The Global AI Index” for 2021, this study aims to examine and analyze the present state of artificial intelligence management in 62 nations in terms of talent, infrastructure, business environment, development and research government policy, and commercial efforts. The research used PROMETHEE, which is widely used in multi-criteria decision-making evaluations, and its geometric representation, the GAIA plane. This study also found that the United States of America is the world leader in artificial intelligence (AI) research and development as well as AI investment. The United Kingdom, China, Israel, Canada, the Netherlands, South Korea, and Germany all rank well. China is rapidly catching up to the USA. At the very bottom of the list are nations such as Armenia, Kenya, Egypt, South Africa, and Pakistan. Turkey’s values are more similar to those of nations towards the bottom of the list than of those in the top half. There is a significant gap between the top three countries and the rest of the world in all parameters included in the survey. Except for the ‘State Strategy’ category, Turkey scores quite low compared to the top-performing countries. Decision makers are expected to address the identified global challenges of the study by creating a more comprehensive national AI strategy, both financially and in terms of content.
Mediated Effect of Entrepreneurial Education on Students’ Intention to Engage in Social Entrepreneurial Projects
Authors: Rakicevic Zoran , Njegic Katarina , Cogoljevic Maja , Rakicevic Jovana
Published: March 2023

Social enterprises are gaining great importance, since they can efficiently solve social problems and help reduce unemployment. Thus, it is important to discover how social entrepreneurial intention (SEI) can be enhanced. In this paper, a model of the impact of entrepreneurial education (EE) on SEI is formulated by relying on the human capital theory. It is hypothesized that EE acts on SEI directly as well as indirectly by increasing the perceived importance of social entrepreneurship (PISE). The model was evaluated on a sample of 400 students from the Republic of Serbia, and Bosnia and Herzegovina. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). In addition, a multigroup analysis was conducted in order to establish differences in the proposed relationship between countries. The obtained results indicate a positive impact of EE on SEI and a positive impact of PISE on SEI in both observed countries. The influence of EE on PISE, as well as the indirect effect of EE on SEI through PISE, was confirmed in Serbia, but not in Bosnia and Herzegovina. The results of this paper justify further government investment in the development of educational programs. This paper also gives recommendations to universities, educators, and researchers.
Identifying the PEM Fuel Cell Parameters Using Artificial Rabbits Optimization Algorithm
Authors: Riad Andrew J. , Hasanien Hany M. , Turky Rania A. , Yakout Ahmed H.
Published: March 2023

The artificial rabbits optimization (ARO) algorithm is proposed in this article to find the optimum values for uncertain parameters for the proton exchange membrane fuel cell (PEMFC) model. The voltage–current polarization curve of the PEMFC is nonlinear, and the model used in this paper to describe it is Mann’s model, which has seven uncertain parameters. The sum of square errors (SSE) between the ARO-based estimated voltages of the model and the measured voltages of the fuel cell defines the objective function. The simulation results show that the ARO technique has the best SSE compared to other optimization techniques. The precision of the ARO model is evaluated by comparing the optimized model’s power–current and voltage–current curves with the measured curves of three stacks which are NedStack PS6, BCS stack 500 W, and Ballard Mark V. The results show that the estimated curves and measured curves are very close which, means a high accuracy is achieved. Moreover, the ARO method shows a fast convergence curve with a minimal standard deviation. Furthermore, the PEMFC-optimized model is studied at different temperature and pressure operating conditions.
Synthesis of Low Density and High Purity Silica Xerogels from South African Sugarcane Leaves without the Usage of a Surfactant
Authors: Maseko Ncamisile Nondumiso , Enke Dirk , Iwarere Samuel Ayodele , Oluwafemi Oluwatobi Samuel , Pocock Jonathan
Published: March 2023

Sugarcane leaves were used to produce high-purity and low-density silica xerogels through a sol–gel method. The biogenic silica produced through a thermochemical method was reacted with sodium hydroxide (NaOH) to form sodium silicate and the produced sodium silicate was titrated with 1 M citric acid to form silica gel. The formed silica gel was washed, subjected to a solvent exchange process and later dried at 80 °C to produce low-density and high-purity silica xerogels. The produced xerogels were characterized with energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), nitrogen physisorption, elemental analysis (CHNS), X-ray fluorescence (XRF), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The produced silica xerogels had an amorphous structure and purity of 99.9 wt%. In addition, the textural properties analysis showed that the xerogel has a BET surface area of 668 m2·g−1, an average pore diameter of 7.5 nm, a pore volume of 1.26 cm3·g−1 and a density of 0.23 g·cm−3.
Life Cycle Assessment of Greenhouse Gas Emissions from Recycled Asphalt Pavement Production
Authors: Gruber Michael R. , Hofko Bernhard
Published: March 2023

With the growing impact of climate change, there is an increasing need and obligation to reduce the responsible greenhouse gases (GHG) in road construction as well. Using life cycle assessment (LCA) methods, several studies have already separately analysed individual parameters of the asphalt production process and illustrated potential improvements in terms of GHG reduction. However, the data of most assessments originate from single sources and databases, and as such can offer little validation against unreliable assumptions. For this reason, in addition to conducting separate assessments at quarries, batch asphalt mixing plants, and construction sites in order to collect energy and material consumption data with which to calculate GHG emissions, this work relies on the results of multiple sources found in the literature. Using the structure for environmental product declarations (EPDs) in EN 15804, our results are divided into the different stages of a life cycle and the corresponding modules. This allows for systematic comparison of different products and eliminates previous uncertainties regarding the inclusion of benefits beyond the system boundary. The results show the dominance of asphalt binder in the material footprint and the corresponding advantage of substituting virgin material with recycled material, as well as the influence of material moisture on GHG emissions in the production process. In addition to the evaluating the material itself, two road sections with increasing traffic volume (and increasing share of electric mobility) were examined and compared with the traffic-related GHG emissions over a 30-year lifetime. We can confirm that traffic has a substantially higher share of the total GHG emissions (>95%); however, as its regulation is the responsibility of governments, the construction industry can only bring about improvements in its own sphere in seeking to further climate protection.
Logistics Village Location with Capacity Planning Problem, an MILP Model Approach
Authors: Baghestani Amirhossein , Abbasi Mohammadhossein , Rastegar Saeed , Mamdoohi Amir Reza , Afaghpoor Atoosa , Saffarzadeh Mahmoud
Published: March 2023

The optimal location for establishing logistics centers is of great importance in reducing logistics costs and improving supply chain efficiency. This paper aims to provide a conceptual framework for finding the optimal location and capacity for a logistics village establishment using mixed-integer linear programming (MILP). The proposed model is applied on Qazvin province, Iran, as a developing country with a strategic location in international transport corridors. Unlike previous research, the proposed approach considers various logistics operations such as warehousing, refrigeration, sorting, and packaging, along with their capacities as distinct decision variables. The study area is divided into 6972 blocks of 1.5 × 1.5 km, of which 59% are infeasible and excluded due to environmental and natural hazard constraints. The MILP model is then applied in the GAMS for each feasible block to identify the best alternatives for the logistic village establishment with maximum total profit. Based on the results, total freight imported to Qazvin province is directly transferred to their final destinations without visiting the logistics village, while around 98% of exports of Qazvin province would first enter the logistics village to get a service before delivering to customers.