bluuebunny/crossref_metadata_2025 huggingface dataset:
Macrocharcoal Signals in Histosols Reveal Wildfire History of Vast Western Siberian Forest-Peatland Complexes
Authors: Startsev Viktor , Gorbach Nikolay , Mazur Anton , Prokushkin Anatoly , Karpenko Lyudmila , Dymov Alexey
Published: December 2022

Fires are a naturally cyclical factor regulating ecosystems’ function and forming new postfire ecosystems. Peat soils are unique archives that store information about ecological and climatic changes and the history of past fires during the Holocene. The paper presents a reconstruction of the dynamics of fires in the subzone of the middle taiga of Western Siberia in the Holocene. Data on fires were obtained based on the results of a study of the content of macroscopic coal particles and radiocarbon dating. The effect of fires on soil organic matter (SOM) was estimated using 13C NMR spectroscopy and the content of polyaromatic hydrocarbons (PAHs). It is shown that throughout the Holocene, the peatlands studied were prone to fires. The conducted analyses show that the maximum content of charcoal particles is observed in the Atlantic (~9100–5800 cal. B.P.) and Subatlantic (~3100 cal. B.P. to the present) periods. The high correlation dependence of the content of coals with the content of PAHs (r = 0.56, p < 0.05) and aromatic structures of SOM (r = 0.61, p < 0.05) in peat horizons is shown, which can characterize these parameters as a reliable marker of pyrogenesis.
Extraction of Essential Oils from Lavandula × intermedia ‘Margaret Roberts’ Using Steam Distillation, Hydrodistillation, and Cellulase-Assisted Hydrodistillation: Experimentation and Cost Analysis
Authors: Wainer Jessie , Thomas Adrianne , Chimhau Tania , Harding Kevin G.
Published: December 2022

Lavender oil is an important essential oil with many applications. The purpose of this study was to compare different methods of essential oil extraction to determine which method would be the most effective and profitable for commercial-scale production from Lavandula × intermedia (‘Margret Roberts’) flowers and leaves. The lavender from this variety flowers year-round, providing an extended production season compared to some other lavender varieties. Steam distillation, hydrodistillation, and cellulase-assisted hydrodistillation were used to extract oil. The average extraction times for steam distillation, hydrodistillation, and cellulase-assisted hydrodistillation were 57-, 51-, and 49 min, respectively, and the average energy consumption was 15.0-, 13.4-, and 30.8 kJ/g, respectively. Cellulase-assisted hydrodistillation produced the best quality oils, with a lower camphor content and a sweeter, more pleasant smell, while steam-distilled oils had the highest camphor content, as well as a more plant-like smell. Factors affecting scale-up (surface area of cut plants, equipment loading times, energy efficiencies, safety, mixing) have been discussed, while a basic cost analysis of theoretical large-scale processes showed that hydrodistillation and cellulase-assisted hydrodistillation would be the most and least profitable methods, respectively. Overall, hydrodistillation is recommended as the best method for commercial lavender oil production.
Analysis of Genetic Diversity and Population Structure of Cowpea (Vigna unguiculata (L.) Walp) Genotypes Using Single Nucleotide Polymorphism Markers
Authors: Gumede Mbali Thembi , Gerrano Abe Shegro , Amelework Assefa Beyene , Modi Albert Thembinkosi
Published: December 2022

Cowpea (Vigna unguiculata (L.) Walp) is an important legume crop with immense potential for nutritional and food security, income generation, and livestock feed in Sub-Saharan Africa. The crop is highly tolerant to heat and drought stresses which makes it an extremely important crop for improving resilience in crop production in the face of climate change. This study was carried out to assess the genetic diversity and population structure of 90 cowpea accessions using single nucleotide polymorphism (SNP) markers. Out of 11,940 SNPs used, 5864 SNPs were polymorphic and maintained for genome diversity analysis. Polymorphic information content (PIC) values ranged from 0.22 to 0.32 with a mean value of 0.27. The model-based Bayesian STRUCTURE analysis classified 90 cowpea accessions into four subpopulations at K = 4, while the distance-based cluster analysis grouped the accessions into three distinct clusters. The analysis of molecular variance (AMOVA) revealed that 59% and 69% of the total molecular variation was attributed to among individual variation for model-based and distance-based populations, respectively, and 18% was attributed to within individual variations. Furthermore, the low heterozygosity among cowpea accessions and the high inbreeding coefficient observed in this study suggests that the accessions reached an acceptable level of homozygosity. This study would serve as a reference for future selection and breeding programs of cowpea with desirable traits and systematic conservation of these plant genetic resources.
Assessment of Wild Rocket (Diplotaxis tenuifolia (L.) DC.) Germplasm Accessions by NGS Identified SSR and SNP Markers
Authors: Reis João M. , Pereira Ricardo J. , Coelho Paula S. , Leitão José M.
Published: December 2022

Rocket is the common designation for two baby-leaf salad crops of the Brassicaceae family: Eruca sativa (L.) Cav., usually referred to as annual garden rocket, and Diplotaxis tenuifolia (L.) DC. commonly named to as perennial wild rocket. E. sativa is used for human consumption since antiquity. However, the growing consumer preference for D. tenuifolia is being accompanied by the fast increase in its production area and commercialization of new cultivars. Nevertheless, the worldwide number of wild rocket accessions maintained in germplasm collections is very reduced, the solution for which situation the project “REMIRucula” intends to contribute, establishing a germplasm collection at the INIAV, Oeiras, Portugal. Herein, we report on the establishment via next generation sequencing (NGS) of the first genome assembly of D. tenuifolia and the identification of specific single sequence repeat (SSR) and single nucleotide polymorphisms (SNP) loci for the establishment of specific DNA-markers for this species. A representative set of 87 D. tenuifolia and 3 E. sativa accessions were assessed by 5 SSR and 9 SNP-CAPS markers, allowing a drastic discrimination between both species and the establishment of unequivocal molecular fingerprints for the analyzed accessions. The non-discrimination within six pairs and one trio of D. tenuifolia accessions is discussed.
Are Foliar Nutrition Status and Indicators of Oxidative Stress Associated with Tree Defoliation of Four Mediterranean Forest Species?
Authors: Lovreškov Lucija , Radojčić Redovniković Ivana , Limić Ivan , Potočić Nenad , Seletković Ivan , Marušić Mia , Jurinjak Tušek Ana , Jakovljević Tamara , Butorac Lukrecija
Published: December 2022

Mediterranean forest ecosystems in Croatia are of very high significance because of the ecological functions they provide. This region is highly sensitive to abiotic stresses such as air pollution, high sunlight, and high temperatures alongside dry periods; therefore, it is important to monitor the state of these forest ecosystems and how they respond to these stresses. This study was conducted on trees in situ and focused on the four most important forest species in the Mediterranean region in Croatia: pubescent oak (Quercus pubescens Willd.), holm oak (Quercus ilex L.), Aleppo pine (Pinus halepensis Mill.) and black pine (Pinus nigra J. F. Arnold.). Trees were selected and divided into two groups: trees with defoliation of >25% (defoliated) and trees with defoliation of ≤25% (undefoliated). Leaves and needles were collected from selected trees. Differences in chlorophyll content, hydrogen peroxide content, lipid peroxidation and enzyme activity (superoxide dismutase, catalase, ascorbate peroxidase, non-specific peroxidase), and nutrient content between the defoliated and undefoliated trees of the examined species were determined. The results showed that there were significant differences for all species between the defoliated and undefoliated trees for at least one of the examined parameters. A principal component analysis showed that the enzyme ascorbate peroxidase can be an indicator of oxidative stress caused by ozone. By using oxidative stress indicators, it is possible to determine whether the trees are under stress even before visual damage occurs.
Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning
Authors: Yang Qiqin , Nan Fangru , Liu Xudong , Liu Qi , Lv Junping , Feng Jia , Wang Fei , Xie Shulian
Published: December 2022

Batrachospermaceae is the largest family of freshwater red algae, widely distributed around the world, and plays an important role in maintaining the balance of spring and creek ecosystems. The deterioration of the current global ecological environment has also destroyed the habitat of Batrachospermaceae. The research on the environmental factors of Batrachospermaceae and the accurate classification of the genus is necessary for the protection, restoration, excavation, and utilization of Batrachospermaceae resources. In this paper, the database of geographical distribution and environmental factors of Batrachospermaceae was sorted out, and the relationship between the classification of genus and environmental factors in Batrachospermaceae was analyzed based on two machine learning methods, random forest and XGBoost. The result shows: (1) The models constructed by the two machine learning methods can effectively distinguish the genus of Batrachospermaceae based on environmental factors; (2) The overall AUC score of the random forest model for the classification and prediction of the genus of Batrachospermaceae reached 90.41%, and the overall AUC score of the taxonomic prediction of each genus of Batrachospermaceae reached 85.85%; (3) Combining the two methods, it is believed that the environmental factors that affect the distinction of the genus of Batrachospermaceae are mainly altitude, average relative humidity, average temperature, and minimum temperature, among which altitude has the greatest influence. The results can further clarify the taxonomy of the genus in Batrachospermaceae and enrich the research on the differences in environmental factors of Batrachospermaceae.
Transcriptomics Analysis Reveals a Putative Role for Hormone Signaling and MADS-Box Genes in Mature Chestnut Shoots Rooting Recalcitrance
Authors: Vielba Jesús Mª , Rico Saleta , Sevgin Nevzat , Castro-Camba Ricardo , Covelo Purificación , Vidal Nieves , Sánchez Conchi
Published: December 2022

Maturation imposes several changes in plants, which are particularly drastic in the case of trees. In recalcitrant woody species, such as chestnut (Castanea sativa Mill.), one of the major maturation-related shifts is the loss of the ability to form adventitious roots in response to auxin treatment as the plant ages. To analyze the molecular mechanisms underlying this phenomenon, an in vitro model system of two different lines of microshoots derived from the same field-grown tree was established. While juvenile-like shoots root readily when treated with exogenous auxin, microshoots established from the crown of the tree rarely form roots. In the present study, a transcriptomic analysis was developed to compare the gene expression patterns in both types of shoots 24 h after hormone and wounding treatment, matching the induction phase of the process. Our results support the hypothesis that the inability of adult chestnut tissues to respond to the inductive treatment relies in a deep change of gene expression imposed by maturation that results in a significant transcriptome modification. Differences in phytohormone signaling seem to be the main cause for the recalcitrant behavior of mature shoots, with abscisic acid and ethylene negatively influencing the rooting ability of the chestnut plants. We have identified a set of related MADS-box genes whose expression is modified but not suppressed by the inductive treatment in mature shoots, suggesting a putative link of their activity with the rooting-recalcitrant behavior of this material. Overall, distinct maturation-derived auxin sensibility and homeostasis, and the related modifications in the balance with other phytohormones, seem to govern the outcome of the process in each type of shoots.
Genomic Characterization of Aureimonas altamirensis C2P003—A Specific Member of the Microbiome of Fraxinus excelsior Trees Tolerant to Ash Dieback
Authors: Becker Regina , Ulrich Kristina , Behrendt Undine , Schneck Volker , Ulrich Andreas
Published: December 2022

Some European ash trees show tolerance towards dieback caused by the invasive pathogen Hymenoscyphus fraxineus. The microbiome of these trees harbours a range of specific bacterial groups. One of these groups belonging to the species Aureimonas altamirensis was studied in detail by genome analysis and a plant inoculation trial. The strain group was shown to be phylogenetically distinct from clinical isolates by 16S rRNA analysis and phylogenomics. Genome analysis of a representative strain C2P003 resulted in a large number of unique gene sequences in comparison to other well-studied strains of the species. A functional analysis of the genome revealed features associated with the synthesis of exopolysaccharides, protein secretion and biofilm production as well as genes for stress adaptation, suggesting the ability of C2P003 to effectively colonize ash leaves. The inoculation of ash seedlings with C2P003 showed a significant positive effect on the plant health of the seedlings that were exposed to H. fraxineus infection. This effect was maintained over a period of three years and was accompanied by a significant shift in the bacterial microbiome composition one year after inoculation. Overall, the results indicate that C2P003 may suppress H. fraxineus in or on ash leaves via colonization resistance or indirectly by affecting the microbiome.
Grassland Degradation Has Stronger Effects on Soil Fungal Community Than Bacterial Community across the Semi-Arid Region of Northern China
Authors: Wang Congwen , Liu Zhangkai , Yu Wanying , Ye Xuehua , Ma Linna , Wang Renzhong , Huang Zhenying , Liu Guofang
Published: December 2022

Soil microbes play crucial roles in grassland ecosystem functions, such as soil carbon (C) pool and nutrient cycle. Soil microbes in grasslands are susceptible to the degradation mediated by climate change and anthropogenic disturbance. However, research on how the degradation influences the diversity and community structure of different soil microbial taxa is relatively scarce. We conducted a large-scale field survey to describe the effects of four degradation levels (PD: potential degradation, LD: light degradation, MD: moderate degradation, and SD: severe degradation) on soil bacterial and fungal community in the semi-arid grasslands of northern China. We found that soil moisture, nutrients, and clay content decreased, but soil sand content increased along the increasing degradation gradient. However, the degradation had no effects on soil pH and the C:N ratio. Grassland degradation had non-significant effect on soil bacterial diversity, but it significantly affected soil bacterial community structure. The degradation decreased soil fungal diversity and had a relatively larger influence on the community structure of soil fungi than that of bacteria. The community composition and structure of soil fungi were mainly affected by soil nutrients and texture, while those of soil bacteria were mainly affected by soil pH. These results indicate that changes in soil properties induced by grassland degradation mainly drive the variation in the soil fungal community and have less effect on the soil bacterial community. This study reveals the sensitivity of soil fungal community to grassland degradation, highlighting the priority of soil fungal community for the management and restoration of degraded grasslands.
Fluoropolymer Membranes for Membrane Distillation and Membrane Crystallization
Authors: Li Xue , Pan Jun , Macedonio Francesca , Ursino Claudia , Carraro Mauro , Bonchio Marcella , Drioli Enrico , Figoli Alberto , Wang Zhaohui , Cui Zhaoliang
Published: December 2022

Fluoropolymer membranes are applied in membrane operations such as membrane distillation and membrane crystallization where hydrophobic porous membranes act as a physical barrier separating two phases. Due to their hydrophobic nature, only gaseous molecules are allowed to pass through the membrane and are collected on the permeate side, while the aqueous solution cannot penetrate. However, these two processes suffer problems such as membrane wetting, fouling or scaling. Membrane wetting is a common and undesired phenomenon, which is caused by the loss of hydrophobicity of the porous membrane employed. This greatly affects the mass transfer efficiency and separation efficiency. Simultaneously, membrane fouling occurs, along with membrane wetting and scaling, which greatly reduces the lifespan of the membranes. Therefore, strategies to improve the hydrophobicity of membranes have been widely investigated by researchers. In this direction, hydrophobic fluoropolymer membrane materials are employed more and more for membrane distillation and membrane crystallization thanks to their high chemical and thermal resistance. This paper summarizes different preparation methods of these fluoropolymer membrane, such as non-solvent-induced phase separation (NIPS), thermally-induced phase separation (TIPS), vapor-induced phase separation (VIPS), etc. Hydrophobic modification methods, including surface coating, surface grafting and blending, etc., are also introduced. Moreover, the research advances on the application of less toxic solvents for preparing these membranes are herein reviewed. This review aims to provide guidance to researchers for their future membrane development in membrane distillation and membrane crystallization, using fluoropolymer materials.
Influence of Curing Agent Amount on Properties of Dynamic Vulcanized Phenyl Silicone Rubber-SEBS-SBS System
Authors: Zhao Chunxu , He Bobing , Chen Xian
Published: December 2022

In this paper, we prepared a new type of thermoplastic vulcanizate (TPV) by melt blending methyl vinyl phenyl silicone rubber (PSR), styrene butylene copolymer (SBS), and hydrogenated SBS (SEBS) and then dynamically vulcanizing it. At the same time, we studied the influence of the content of the vulcanizing agent on the properties. The corresponding backscattered electron images were obtained by a scanning electron microscope (SEM) test of each group of samples, as well as the distribution of the PSR phase and the SEBS-SBS phase, and the vulcanization process of the samples with a vulcanizing agent content of 1 phr were characterized. According to the imaging principle of the backscattered electron signal, we found that the atomic number contrast can be clearly reflected in the backscattered image. From the obtained images, we found that PSR is a dispersed phase, while SEBS and SBS are continuous phases, that is, they had a “Sea-Island” structure. In the first 30 s of the vulcanization reaction, the “Sea-Island” structure is formed, and then the vulcanization reaction rate gradually slows down. We then printed the images and analyzed them using a colorimeter and found that it was feasible to quantitatively characterize the size of the compatible layer between the continuous and dispersed phases. According to the quantitative characterization results, we found that the silane coupling agent KH-172 can increase the thickness of the compatible layer by nearly 35%. In addition, we also tested the mechanical properties and low-temperature elastic properties of the material. Finally, we found that when the content of the vulcanizing agent was 1 phr, the elastic properties and tensile properties were the best, and when the content of the vulcanizing agent was more than 1 phr, the tensile and elastic properties of the material decreased significantly. At the same time, we also found that the addition of the silane coupling agent KH-172 can also significantly improve the tensile properties and elastic properties of TPV, which we believe is related to the increase in the thickness of the compatible layer. The test results of dynamic mechanics show that PSR has good compatibility with SEBS-SBS. When the vulcanizing agent content is less than or equal to 1 phr, the material exhibits good low-temperature resistance. In addition, through the test of the melt index of each group, it was also found that the addition of the vulcanizing agent will affect the fluidity of the melt to a certain extent. When the content of the vulcanizing agent is greater than 1 phr, the melt fluidity decreases more obviously.
Polymer Nanoparticles: Synthesis and Applications
Authors: Perumal Suguna
Published: December 2022

Polymer nanoparticles (PNPs) are generally formed by the spontaneous self-assembly of polymers that vary size from 1 to 1000 nm [...]
Smart and Resilient Transformation of Manufacturing Firms
Authors: Sofic Aleksandar , Rakic Slavko , Pezzotta Giuditta , Markoski Branko , Arioli Veronica , Marjanovic Ugljesa
Published: December 2022

The smart and resilient transformation of manufacturing firms has flourished in the last decade. This paper investigates the smart and resilient transformation of manufacturing firms with the application of digital services. It uses a Serbian data set of 136 manufacturing firms from the Digital Servitization Survey from 2022 coordinated by IFIP WG5.7. The authors applied a different method approach through social network analysis, correlation analysis, and interviews with representatives from the manufacturing firms. The main results show that manufacturing firms that apply an adequate combination of services and digital technologies have the highest impact on the network of manufacturing firms. Moreover, the results show that applying digital technologies, such as additive manufacturing/3D printing, big data analytics, and digital twin, increases the gross annual turnover of manufacturing firms in the COVID-19 era. Finally, the results show that for a successful smart and resilient transformation, manufacturing firms need to develop a strategy and motivation oriented to profit to be resilient enough to withstand market change.
Determination of 7 Kinds of Alkaloids in Semen Nelumbinis and Its Products by HPLC
Authors: Zhong Feifei , Ouyang Li , Deng Nan , Yin Fangping , He Jiajie , Lei Deqing , Gao Jieying , Zeng Hui , Wang Zhaoxia , Wang Lu , Yang Lixia , Zhou Hui
Published: December 2022

Objective: To establish a method for the simultaneous determination of seven alkaloids in Semen Nelumbinis and its products, the extraction technology and HPLC method were optimized by the single factor experiment. Methods: Firstly, the samples were extracted ultrasonically with 1% formic acid ethanol and purified by PXC SPE column. Then, the extracts and the purified liquid were taken after concentration with nitrogen for quantitative analysis of seven alkaloids by HPLC method. Next, the contents of alkaloids in five samples were determined. Results: The method was fully validated and the result showed that seven kinds of alkaloids had good linear relation in the corresponding range of mass concentration, r2 > 0.999, where the detection limit was 0.5–1.5 mg/kg, the quantification limit was 1.25–4.5 mg/kg, the recovery was 83.33–116.04%, and the RSD of detection method was 1.06–5.25% (n = 7). In five samples, the contents of Lotusine and Neferine were the highest, Berberine Hydrochloride was not detected. Conclusion: This method is simple, sensitive, accurate and reproducible, and it can realize the quantitative analysis and chemical separation of seven kinds of common alkaloids in Semen Nelumbinis and its products and provide a theoretical method for the simultaneous determination of alkaloids. The extraction yields of alkaloids in Semen Nelumbinis can be increased through the extraction process, which is optimized by a single factor experiment.
Strategic Slum Upgrading and Redevelopment Action Plan for Jammu City
Authors: Farooq Majid , Mushtaq Fayma , Meraj Gowhar , Singh Suraj Kumar , Kanga Shruti , Gupta Ankita , Kumar Pankaj , Singh Deepak , Avtar Ram
Published: December 2022

Rapid urbanization has led to the emergence of slums in many developing and industrialized nations. It degrades the quality of life and burdens the urban amenities resulting in uneven distribution of slums. The majority of people in the developing world live in squatter settlements and these random gatherings disrupt the economic and social developmental plans of the concerned country. No suitable planning framework has been created for replicability on a considerable scale, despite the fact that slum upgrading is acquiring worldwide importance as a political issue. In recent years Jammu City has witnessed high population growth rates resulting in an uneven provision of urban amenities and a surge in slum areas. This paper focuses on a method-based approach using Management Information System (MIS) and Geographic Information System (GIS) for upgrading slums and recommends a planning outline using the approach formulated by the Government of India under the scheme named “Rajiv Awas Yojna” (RAY). The aim of this study is to assess the status of slums, propose redevelopment plans, and highlight the roles of different planning agencies to accomplish the redevelopment goals. The study concludes by postulating several recommendations for upgrading slums and formulating a framework that can be used in other similar areas for development.
Proposed Methodology for Accuracy Improvement of LOD1 3D Building Models Created Based on Stereo Pléiades Satellite Imagery
Authors: Breaban Ana-Ioana , Oniga Valeria-Ersilia , Chirila Constantin , Loghin Ana-Maria , Pfeifer Norbert , Macovei Mihaela , Nicuta Precul Alina-Mihaela
Published: December 2022

Three-dimensional city models play an important role for a large number of applications in urban environments, and thus it is of high interest to create them automatically, accurately and in a cost-effective manner. This paper presents a new methodology for point cloud accuracy improvement to generate terrain topographic models and 3D building modeling with the Open Geospatial Consortium (OGC) CityGML standard, level of detail 1 (LOD1), using very high-resolution (VHR) satellite images. In that context, a number of steps are given attention (which are often (in the literature) not considered in detail), including the local geoid and the role of the digital terrain model (DTM) in the dense image matching process. The quality of the resulting models is analyzed thoroughly. For this objective, two stereo Pléiades 1 satellite images over Iasi city were acquired in September 2016, and 142 points were measured in situ by global navigation satellite system real-time kinematic positioning (GNSS-RTK) technology. First, the quasigeoid surface resulting from EGG2008 regional gravimetric model was corrected based on data from GNSS and leveling measurements using a four-parameter transformation, and the ellipsoidal heights of the 142 GNSS-RTK points were corrected based on the local quasigeoid surface. The DTM of the study area was created based on low-resolution airborne laser scanner (LR ALS) point clouds that have been filtered using the robust filter algorithm and a mask for buildings, and the ellipsoidal heights were also corrected with the local quasigeoid surface, resulting in a standard deviation of 37.3 cm for 50 levelling points and 28.1 cm for the 142 GNSS-RTK points. For the point cloud generation, two scenarios were considered: (1) no DTM and ground control points (GCPs) with uncorrected ellipsoidal heights resulting in an RMS difference (Z) for the 64 GCPs and 78 ChPs of 69.8 cm and (2) with LR ALS-DTM and GCPs with corrected ellipsoidal height values resulting in an RMS difference (Z) of 60.9 cm. The LOD1 models of 1550 buildings from the Iasi city center were created based on Pléiades-DSM point clouds (corrected and not corrected) and existing building sub-footprints, with four methods for the derivation of the building roof elevations, resulting in a standard deviation of 1.6 m against high-resolution (HR) ALS point cloud in the case of the best scenario. The proposed method for height extraction and reconstruction of the city structure performed the best compared with other studies on multiple satellite stereo imagery.
Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data
Authors: Wang Jinyue , Liu Jing , Li Longhui
Published: December 2022

Solar photovoltaic (PV) power generation is a vital renewable energy to achieve carbon neutrality. Previous studies which explored mapping PV using open satellite data mainly focus in remote areas. However, the complexity of land cover types can bring much difficulty in PV identification. This study investigated detecting PV in diverse landscapes using freely accessible remote sensing data, aiming to evaluate the transferability of PV detection between rural and urbanized coastal area. We developed a random forest-based PV classifier on Google Earth Engine in two provinces of China. Various features including Sentinel-2 reflectance, Sentinel-1 polarization, spectral indices and their corresponding textures were constructed. Thereafter, features with high permutation importance were retained. Three classification schemes with different training and test samples were, respectively, conducted. Finally, the VIIRS nighttime light data were utilized to refine the initial results. Manually collected samples and existing PV database were used to evaluate the accuracy of our method. The results revealed that the top three important features in detecting PV were the sum average texture of three bands (NDBI, VV, and VH). We found the classifier trained in highly urbanized coastal landscape with multiple PV types was more transferable (OA = 97.24%, kappa = 0.94), whereas the classifier trained in rural landscape with simple PV types was erroneous when applied vice versa (OA = 68.84%, kappa = 0.44). The highest accuracy was achieved when using training samples from both regions as expected (OA = 98.90%, kappa = 0.98). Our method recalled more than 94% PV in most existing databases. In particular, our method has a stronger detection ability of PV installed above water surface, which is often missing in existing PV databases. From this study, we found two main types of errors in mapping PV, including the bare rocks and mountain shadows in natural landscapes and the roofing polyethylene materials in urban settlements. In conclusion, the PV classifier trained in highly urbanized coastal landscapes with multiple PV types is more accurate than the classifier trained in rural landscapes. The VIIRS nighttime light data contribute greatly to remove PV detection errors caused by bare rocks and mountain shadows. The finding in our study can provide reference values for future large area PV monitoring.
High-Sensitivity Slot-Loaded Microstrip Patch Antenna for Sensing Microliter-Volume Liquid Chemicals with High Relative Permittivity and High Loss Tangent
Authors: Yeo Junho , Lee Jong-Ig
Published: December 2022

This paper proposes a microwave sensor based on a high-sensitivity slot-loaded rectangular microstrip patch antenna (MPA) for measuring microliter-volume liquid chemicals with high relative permittivity and high loss tangent. A rectangular single-ring complementary split ring resonator (SR-CSRR) slot with a bottom-edge center split (BCS) was inserted along the upper radiating edge of the patch to enhance the relative permittivity sensitivity of the MPA. The first resonant frequency of the proposed SR-CSRR-BCS slot-loaded MPA showed the highest sensitivity compared to the resonant frequencies of the MPAs with other commonly used slots for varying the relative permittivity of the planar substrate type material under test from 1 to 10 when placed above the patch. After designing the scaled SR-CSRR-BCS slot-loaded MPA with the unloaded first resonant frequency at 2.5 GHz, a hollow acrylic cylindrical liquid container with an inner volume of approximately 18.6 μL was placed at the top-edge center of the SR-CSRR-BCS slot to achieve maximum sensitivity. A quarter-wavelength transformer was applied between the patch and the feed line of the MPA to improve the impedance mismatch that occurs when liquid chemicals with a high loss tangent are placed in the container. Water, methanol, and ethanol were carefully selected for test liquids to cover a broad range of relative permittivity and high loss tangents. The proposed SR-CSRR-BCS slot-loaded MPA was designed and fabricated on a 0.76 mm-thick RF-35 substrate, and a reference RS-loaded MPA was designed and fabricated for comparison. The shift in the first resonant frequency of the input reflection coefficient characteristic was used for the sensitivity comparison, and the container was filled with 15 μL of the liquids at 25 °C. The measured sensitivity (%) of the proposed SR-CSRR-BCS slot-loaded MPA for water was 0.45%, which was higher than other antenna-based microwave sensors in the literature.
An Efficient Pest Detection Framework with a Medium-Scale Benchmark to Increase the Agricultural Productivity
Authors: Aladhadh Suliman , Habib Shabana , Islam Muhammad , Aloraini Mohammed , Aladhadh Mohammed , Al-Rawashdeh Hazim Saleh
Published: December 2022

Insect pests and crop diseases are considered the major problems for agricultural production, due to the severity and extent of their occurrence causing significant crop losses. To increase agricultural production, it is significant to protect the crop from harmful pests which is possible via soft computing techniques. The soft computing techniques are based on traditional machine and deep learning-based approaches. However, in the traditional methods, the selection of manual feature extraction mechanisms is ineffective, inefficient, and time-consuming, while deep learning techniques are computationally expensive and require a large amount of training data. In this paper, we propose an efficient pest detection method that accurately localized the pests and classify them according to their desired class label. In the proposed work, we modify the YOLOv5s model in several ways such as extending the cross stage partial network (CSP) module, improving the select kernel (SK) in the attention module, and modifying the multiscale feature extraction mechanism, which plays a significant role in the detection and classification of small and large sizes of pest in an image. To validate the model performance, we develop a medium-scale pest detection dataset that includes the five most harmful pests for agriculture products that are ants, grasshopper, palm weevils, shield bugs, and wasps. To check the model’s effectiveness, we compare the results of the proposed model with several variations of the YOLOv5 model, where the proposed model achieved the best results in the experiments. Thus, the proposed model has the potential to be applied in real-world applications and further motivate research on pest detection to increase agriculture production.
Carbon Dioxide Monitoring inside an Australian Brewery Using an Internet-of-Things Sensor Network
Authors: Hawchar Amer , Ould Solomon , Bennett Nick S.
Published: December 2022

Maintaining a high standard of indoor air quality (IAQ) is vital to ensuring good human health. The concentration of CO2 in air is a good proxy for IAQ, while high levels of CO2 have been shown to cause cognitive or physiological impairment. Work environments that generate CO2 as an inherent part of their business present a unique and significant risk in terms of poor IAQ. Craft breweries generate CO2 and, unlike larger breweries, often lack the technology to capture and re-use the fermentation CO2 for beer carbonation. The purpose of this study is to demonstrate that the venting of fermentation CO2 and the unintentional venting of CO2 during the filling of CO2 storage tanks can cause the indoor CO2 levels to rise significantly. This is shown by monitoring CO2 levels inside an Australian craft brewery using a newly developed system containing three Internet of Things (IoT) sensor nodes positioned strategically in different sections of the brewery. The maximum CO2 level recorded was in excess of 18,000 ppm, with the maximum time period levels exceeding 1000 and 10,000 ppm being equivalent to 425 and 26 min, respectively. The identification of differences in measured CO2 at different times and locations throughout the brewery reveals that a single hard-wired CO2 sensor may be inadequate to support IAQ monitoring. For this purpose, a network of portable or wearable CO2 sensor nodes may be most suitable. The battery life of the sensors is a key consideration, and the current sensor battery life is too short. Low-power sensors and communication protocols are recommended for this task.
An Adaptive Refinement Scheme for Depth Estimation Networks
Authors: Alizadeh Naeini Amin , Sheikholeslami Mohammad Moein , Sohn Gunho
Published: December 2022

Deep learning has proved to be a breakthrough in depth generation. However, the generalization ability of deep networks is still limited, and they cannot maintain a satisfactory performance on some inputs. By addressing a similar problem in the segmentation field, a feature backpropagating refinement scheme (f-BRS) has been proposed to refine predictions in the inference time. f-BRS adapts an intermediate activation function to each input by using user clicks as sparse labels. Given the similarity between user clicks and sparse depth maps, this paper aims to extend the application of f-BRS to depth prediction. Our experiments show that f-BRS, fused with a depth estimation baseline, is trapped in local optima, and fails to improve the network predictions. To resolve that, we propose a double-stage adaptive refinement scheme (DARS). In the first stage, a Delaunay-based correction module significantly improves the depth generated by a baseline network. In the second stage, a particle swarm optimizer (PSO) delineates the estimation through fine-tuning f-BRS parameters—that is, scales and biases. DARS is evaluated on an outdoor benchmark, KITTI, and an indoor benchmark, NYUv2, while for both, the network is pre-trained on KITTI. The proposed scheme was effective on both datasets.
Single Camera-Based Dual-Channel Near-Infrared Fluorescence Imaging system
Authors: Choi Janghoon , Shin Jun-Geun , Tak Yoon-Oh , Seo Youngseok , Eom Jonghyun
Published: December 2022

In this study, we propose a single camera-based dual-channel near-infrared (NIR) fluorescence imaging system that produces color and dual-channel NIR fluorescence images in real time. To simultaneously acquire color and dual-channel NIR fluorescence images of two fluorescent agents, three cameras and additional optical parts are generally used. As a result, the volume of the image acquisition unit increases, interfering with movements during surgical procedures and increasing production costs. In the system herein proposed, instead of using three cameras, we set a single camera equipped with two image sensors that can simultaneously acquire color and single-channel NIR fluorescence images, thus reducing the volume of the image acquisition unit. The single-channel NIR fluorescence images were time-divided into two channels by synchronizing the camera and two excitation lasers, and the noise caused by the crosstalk effect between the two fluorescent agents was removed through image processing. To evaluate the performance of the system, experiments were conducted for the two fluorescent agents to measure the sensitivity, crosstalk effect, and signal-to-background ratio. The compactness of the resulting image acquisition unit alleviates the inconvenient movement obstruction of previous devices during clinical and animal surgery and reduces the complexity and costs of the manufacturing process, which may facilitate the dissemination of this type of system.
Numerical Model Driving Multi-Domain Information Transfer Method for Bearing Fault Diagnosis
Authors: Zhang Long , Zhang Hao , Xiao Qian , Zhao Lijuan , Hu Yanqing , Liu Haoyang , Qiao Yu
Published: December 2022

Given the complexity of the application scenarios of rolling bearing and the severe scarcity of fault samples, a solution to the issue of fault diagnosis under varying working conditions along with the absence of fault samples is required. A numerical model-driven cross-domain fault diagnosis method targeting variable working conditions is proposed based on the cross-Domain Nuisance Attribute Projection (cDNAP). Firstly, the simulation datasets consisting of multiple fault types under variable working conditions are constructed to solve the problem of incomplete fault samples. Secondly, the simulation datasets are expanded by means of generating adversarial network to ensure sufficient samples for subsequent model training. Finally, cDNAP is used to obtain the cross-domain simulation projection matrix, which eliminates the variance in the distribution of measured and simulated sample features under varying working conditions. The experimental results of cross-domain for variable working conditions show that the diagnostic accuracy reaches up to 99%. Compared with DANN, DSAN, and DAAN domain adversarial neural networks, the proposed method performs better in bearing fault diagnosis.
Modified Triple-Tuned Bandpass Filter with Two Concurrently Tuned Transmission Zeros
Authors: Magnuski Mirosław , Noga Artur , Surma Maciej , Wójcik Dariusz
Published: December 2022

In this paper, a modified triple-tuned microstrip bandpass filter is presented. The filter consists of inductively cross-coupled resonators tuned with varactors. The application of the additional source-load couplings together with resonator branch swapping results in two transmission zeros tuned concurrently with operating frequency. These transmission zeros placed on both sides of the passband significantly increase slope steepness in transition bands. The example filter tuned from 0.36 to 0.78 GHz and controlled by a single voltage was manufactured and validated by measurements. It has a constant fractional bandwidth of 11%, low in-band insertion loss ranging from 1.8 to 2.5 dB, and out-of-band attenuation up to 5 GHz without parasitic passbands. The obtained filter parameters made it useful for preselector networks.
High Temperature Measurement with Low Cost, VCSEL-Based, Interrogation System Using Femtosecond Bragg Gratings
Authors: Markowski Konrad , Bojarczuk Juliusz , Araszkiewicz Piotr , Ciftci Jakub , Ignaciuk Adam , Gąska Michał
Published: December 2022

In this article, a cost-effective and fast interrogating system for wide temperature measurement with Fiber Bragg Gratings is presented. The system consists of a Vertical Cavity Surface Emitting Laser (VCSEL) with a High Contrast Grating (HCG)-based cavity that allows for the fast tuning of the output wavelength. The work focuses on methods of bypassing the limitations of the used VCSEL laser, especially its relatively narrow tuning range. Moreover, an error analysis is provided by means of the VCSEL temperature instability and its influence on the system performance. A simple proof of concept of the measurement system is shown, where two femtosecond Bragg gratings were used to measure temperature in the range of 25 to 800 °C. In addition, an exemplary simulation of a system with sapphire Bragg gratings is provided, where we propose multiplexation in the wavelength and reflectance domains. The presented concept can be further used to measure a wide range of temperatures with scanning frequencies up to hundreds of kHz.
A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
Authors: Batty Taran , Ehrampoosh Armin , Shirinzadeh Bijan , Zhong Yongmin , Smith Julian
Published: December 2022

In recent years, robotic minimally invasive surgery has transformed many types of surgical procedures and improved their outcomes. Implementing effective haptic feedback into a teleoperated robotic surgical system presents a significant challenge due to the trade-off between transparency and stability caused by system communication time delays. In this paper, these time delays are mitigated by implementing an environment estimation and force prediction methodology into an experimental robotic minimally invasive surgical system. At the slave, an exponentially weighted recursive least squares (EWRLS) algorithm estimates the respective parameters of the Kelvin–Voigt (KV) and Hunt–Crossley (HC) force models. The master then provides force feedback by interacting with a virtual environment via the estimated parameters. Palpation experiments were conducted with the slave in contact with polyurethane foam during human-in-the-loop teleoperation. The experimental results indicated that the prediction RMSE of error between predicted master force feedback and measured slave force was reduced to 0.076 N for the Hunt–Crossley virtual environment, compared to 0.356 N for the Kelvin–Voigt virtual environment and 0.560 N for the direct force feedback methodology. The results also demonstrated that the HC force model is well suited to provide accurate haptic feedback, particularly when there is a delay between the master and slave kinematics. Furthermore, a haptic feedback approach that incorporates environment estimation and force prediction improve transparency during teleoperation. In conclusion, the proposed bilateral master–slave robotic system has the potential to provide transparent and stable haptic feedback to the surgeon in surgical robotics procedures.
Recent Developments in Emerging Contaminants Determination and Treatment Technologies
Authors: Bashir Mohammed J. K. , Mojiri Amin
Published: December 2022

The most fundamental need, which all people must have to maintain their life, is access to clean water [...]
The Relationship between Family Milieu and Music Education
Authors: Szűcs Tímea
Published: December 2022

Our study aimed to map the family milieu of 21st-century music students. With the help of the applied social science methods, we studied what patterns facilitated children’s music education and whether there were objectively justifiable differences in the socioeconomic status of music students and non-musical students. In our survey, we used a quantitative method in the form of paper-based, self-administered questionnaires. We sampled eighth-grade students of elementary art schools in several county seats that had a long history of teaching (n = 270) and eighth-grade students in several elementary schools (n = 285) as a control group. We assumed that students learning music are children of families with higher cultural capital, mostly with backgrounds in music education, who consider extracurricular activities investments. We tested our hypothesis using SPSS program, the methods included logistic regression and cluster analysis. Our results prove the existence of differences in the socioeconomic status of music and non-music students.