bluuebunny/crossref_metadata_2025 huggingface dataset:
Separate Effects of Sodium on Germination in Saline–Sodic and Alkaline Forms at Different Concentrations
Authors: Hitti Yasmeen , MacPherson Sarah , Lefsrud Mark
Published: March 2023

Salinity negatively impacts crop productivity, yet neutral and alkali salt stresses are not often differentiated. To investigate these abiotic stresses separately, saline and alkaline solutions with identical concentrations of sodium (12 mM, 24 mM and 49 mM) were used to compare the seed germination, viability and biomass of four crop species. Commercial buffers containing NaOH were diluted to generate alkaline solutions. The sodic solutions tested contained the neutral salt NaCl. Romaine lettuce, tomato, beet, and radish were seeded and grown hydroponically for 14 days. A rapid germination was observed for alkaline solutions when compared to saline–sodic solutions. The highest plant viability recorded (90.0%) was for the alkaline solution, containing 12 mM Na+, and for the control treatment. Plant viability, with a value of 49 mM Na+ in saline–sodic and alkaline solutions, was the lowest (50.0% and 40.8% respectively), and tomato plants did not germinate. EC values were higher for the saline–sodic solutions than the alkaline solutions, yielding greater fresh mass per plant for all species, with the exception of beets grown in alkaline solution, with a value of 24 mM Na+. The fresh mass of romaine lettuce grown in the 24 mM Na+ saline–sodic solution was significantly greater than romaine lettuce grown in the alkaline solution with the same sodium concentration.
Artificial Grassland Had Higher Water Use Efficiency in Year with Less Precipitation in the Agro-Pastoral Ecotone
Authors: Zhao Kun , Qu Yan , Wang Deping , Liu Zhongkuan , Rong Yuping
Published: March 2023

Improving plant water use efficiency is a key strategy for the utilization of regional limited water resources as well as the sustainable development of agriculture industry. To investigate the effects of different land use types on plant water use efficiency and their mechanisms, a randomized block experiment was designed in the agro-pastoral ecotone of northern China during 2020–2021. The differences in dry matter accumulation, evapotranspiration, soil physical and chemical properties, soil water storage and water use efficiency and their relationships among cropland, natural grassland and artificial grassland were studied. The results show that: In 2020, the dry matter accumulation and water use efficiency of cropland were significantly higher than those of artificial and natural grassland. In 2021, dry matter accumulation and water use efficiency of artificial grassland increased significantly from 364.79 g·m−2 and 24.92 kg·ha−1·mm−1 to 1037.14 g·m−2 and 50.82 kg·ha−1·mm−1, respectively, which were significantly higher than cropland and natural grassland. The evapotranspiration of three land use types showed an increasing trend in two years. The main reason affecting the difference of water use efficiency was that land use type affected soil moisture and soil nutrients, and then changed the dry matter accumulation and evapotranspiration of plants. During the study period, the water use efficiency of artificial grassland was higher in years with less precipitation. Therefore, expanding the planted area of artificial grassland may be one of the effective ways to promote the full utilization of regional water resources.
Pipeline to Design Inbred Lines and F1 Hybrids of Leaf Chicory (Radicchio) Using Male Sterility and Genotyping-by-Sequencing
Authors: Scariolo Francesco , Palumbo Fabio , Farinati Silvia , Barcaccia Gianni
Published: March 2023

Chicory, a horticultural crop cultivated worldwide, presents many botanical varieties and local biotypes. Among these, cultivars of the Italian radicchio group of the pure species Cichorium intybus L. and its interspecific hybrids with Cichorium endivia L.—as the “Red of Chioggia” biotype—includes several phenotypes. This study uses a pipeline to address the marker-assisted breeding of F1 hybrids: it presents the genotyping-by-sequencing results of four elite inbred lines using a RADseq approach and an original molecular assay based on CAPS markers for screening mutants with nuclear male sterility in the radicchio of Chioggia. A total of 2953 SNP-carrying RADtags were identified and used to compute the actual estimates of homozygosity and overall genetic similarity and uniformity of the populations, as well as to determine their genetic distinctiveness and differentiation. Molecular data were further used to investigate the genomic distribution of the RADtags among the two Cichorium species, allowing their mapping in 1131 and 1071 coding sequences in chicory and endive, respectively. Paralleling this, an assay to screen the genotype at the male sterility locus Cims-1 was developed to discriminate wild-type and mutant alleles of the causative gene myb80-like. Moreover, a RADtag mapped close to this genomic region proved the potential application of this method for future marker-assisted selection tools. Finally, after combining the genotype information of the core collection, the best 10 individuals from each inbred line were selected to compute the observed genetic similarity as a measure of uniformity as well as the expected homozygosity and heterozygosity estimates scorable by the putative progenies derived from selfing (pollen parent) and full-sibling (seed parent) or pair-wise crossing (F1 hybrids). This predictive approach was conducted as a pilot study to understand the potential application of RADseq in the fine tuning of molecular marker-assisted breeding strategies aimed at the development of inbred lines and F1 hybrids in leaf chicory.
Nanobacterial Cellulose from Kombucha Fermentation as a Potential Protective Carrier of Lactobacillus plantarum under Simulated Gastrointestinal Tract Conditions
Authors: Charoenrak Sonthirat , Charumanee Suporn , Sirisa-ard Panee , Bovonsombut Sittisin , Kumdhitiahutsawakul Ladapa , Kiatkarun Suwalee , Pathom-Aree Wasu , Chitov Thararat , Bovonsombut Sakunnee
Published: March 2023

Kombucha bacterial cellulose (KBC), a by-product of kombucha fermentation, can be used as a biomaterial for microbial immobilization. In this study, we investigated the properties of KBC produced from green tea kombucha fermentation on days 7, 14, and 30 and its potential as a protective carrier of Lactobacillus plantarum, a representative beneficial bacteria. The highest KBC yield (6.5%) was obtained on day 30. Scanning electron microscopy showed the development and changes in the fibrous structure of the KBC over time. They had crystallinity indices of 90–95%, crystallite sizes of 5.36–5.98 nm, and are identified as type I cellulose according to X-ray diffraction analysis. The 30-day KBC had the highest surface area of 19.91 m2/g, which was measured using the Brunauer–Emmett–Teller method. This was used to immobilize L. plantarum TISTR 541 cells using the adsorption–incubation method, by which 16.20 log CFU/g of immobilized cells was achieved. The amount of immobilized L. plantarum decreased to 7.98 log CFU/g after freeze-drying and to 2.94 log CFU/g after being exposed to simulated gastrointestinal tract conditions (HCl pH 2.0 and 0.3% bile salt), whereas the non-immobilized culture was not detected. This indicated its potential as a protective carrier to deliver beneficial bacteria to the gastrointestinal tract.
Fracture Load of Mesio–Occluso–Distal Composite Restorations Performed with Different Reinforcement Techniques: An In Vitro Study
Authors: Albar Nassreen , Khayat Waad
Published: March 2023

Background: Mesio–occluso–distal (MOD) cavity preparations are often fragile due to the amount of tooth and carious structure removed. MOD cavities can often fracture if left unsupported. Aim: The study investigated the maximum fracture load of mesi–occluso–distal cavities restored using direct composite resin restorations with various reinforcement techniques. Method: Seventy-two freshly extracted, intact human posterior teeth were disinfected, checked, and prepared according to predetermined standards for mesio–occluso–distal cavity design (MOD). The teeth were assigned randomly into six groups. The first group was the control group restored conventionally with a nanohybrid composite resin (Group I). The other five groups were restored with a nanohybrid composite resin reinforced with different techniques: the ACTIVA BioACTIVE-Restorative and -Liner as a dentin substitute and layered with a nanohybrid composite (Group II); the everX Posterior composite resin layered with a nanohybrid composite (Group III); polyethylene fibers called “Ribbond” placed on both axial walls and the floor of the cavity, and layered with a nanohybrid composite (Group IV); polyethylene fibers placed on both axial walls and the floor of the cavity, and layered with the ACTIVA BioACTIVE-Restorative and -Liner as a dentin substitute and nanohybrid composite (Group V); and polyethylene fibers placed on both axial walls and the floor of the cavity and layered with the everX posterior composite resin and nanohybrid composite (Group VI). All teeth were subjected to thermocycling to simulate the oral environment. The maximum load was measured using a universal testing machine. Results: The highest maximum load was exhibited by Group III with the everX posterior composite resin, followed by Group IV, Group VI, Group I, Group II, and Group V. A statistically significant difference was demonstrated between groups (p = 0.0023). When adjusting for multiple comparisons, there were statistical differences specific to comparisons between Group III versus I, Group III versus II, Group IV versus II, and Group V versus III. Conclusions: Within the limitations of the current study, it can be concluded that a higher maximum load resistance can be achieved (statistically significant) when reinforcing nanohybrid composite resin MOD restorations with everX Posterior.
Immobilization of Hyperthermostable Carboxylesterase EstD9 from Anoxybacillus geothermalis D9 onto Polymer Material and Its Physicochemical Properties
Authors: Johan Ummie Umaiera Mohd. , Rahman Raja Noor Zaliha Raja Abd. , Kamarudin Nor Hafizah Ahmad , Latip Wahhida , Ali Mohd Shukuri Mohamad
Published: March 2023

Carboxylesterase has much to offer in the context of environmentally friendly and sustainable alternatives. However, due to the unstable properties of the enzyme in its free state, its application is severely limited. The present study aimed to immobilize hyperthermostable carboxylesterase from Anoxybacillus geothermalis D9 with improved stability and reusability. In this study, Seplite LX120 was chosen as the matrix for immobilizing EstD9 by adsorption. Fourier-transform infrared (FT-IR) spectroscopy verified the binding of EstD9 to the support. According to SEM imaging, the support surface was densely covered with the enzyme, indicating successful enzyme immobilization. BET analysis of the adsorption isotherm revealed reduction of the total surface area and pore volume of the Seplite LX120 after immobilization. The immobilized EstD9 showed broad thermal stability (10–100 °C) and pH tolerance (pH 6–9), with optimal temperature and pH of 80 °C and pH 7, respectively. Additionally, the immobilized EstD9 demonstrated improved stability towards a variety of 25% (v/v) organic solvents, with acetonitrile exhibiting the highest relative activity (281.04%). The bound enzyme exhibited better storage stability than the free enzyme, with more than 70% of residual activity being maintained over 11 weeks. Through immobilization, EstD9 can be reused for up to seven cycles. This study demonstrates the improvement of the operational stability and properties of the immobilized enzyme for better practical applications.
Parametrical Function Describing Influences of the Redistribution of Incorporated Oil for Rupture Process Reconstruction in Rubber
Authors: Datta Sanjoy , Stoček Radek , Harea Evghenii
Published: March 2023

The present work is focused on finding (i) the tearing energy at rupture and (ii) the redistribution of incorporated paraffin oil on the ruptured surfaces as functions of (a) the initial oil concentration and (b) the speed of deformation to the total rupture in a uniaxially induced deformation to rupture on an initially homogeneously oil incorporated styrene butadiene rubber (SBR) matrix. The aim is to understand the deforming speed of the rupture by calculating the concentration of the redistributed oil after rupture using infrared (IR) spectroscopy in an advanced continuation of a previously published work. The redistribution of the oil after tensile rupture for samples that have three different initial oil concentrations with a control sample that has no initial oil has been studied at three defined deformation speeds of rupture along with a cryo-ruptured sample. Single-edge notched tensile (SENT) specimens were used in the study. Parametric fittings of data at different deformation speeds were used to relate the concentration of the initial oil against the concentration of the redistributed oil. The novelty of this work is in the use of a simple IR spectroscopic method to reconstruct a fractographic process to rupture in relation to the speed of the deformation to rupture.
Shielding Performance of Electromagnetic Shielding Fabric Implanted with “Split-Ring Resonator”
Authors: Liu Zhe , Duan Jin , Wang Xiuchen
Published: March 2023

The electromagnetic shielding (EMS) fabric is an important electromagnetic protection product, which is widely applied in various fields. The improvement of its shielding effectiveness (SE) has always been the focus of research. This article proposes to implant a metamaterial structure of a “split-ring resonator (SRR)” in the EMS fabrics, so that the fabric not only maintains the porous and lightweight characteristics, but also obtains the SE improvement. With the help of the invisible embroidery technology, stainless-steel filaments were used to implant hexagonal SRRs inside the fabric. The effectiveness and influencing factors of the SRR implantation were described by testing the SE of the fabric and analyzing the experimental results. It was concluded that the SRR implantation inside the fabric can effectively improve the SE of the fabric. For the stainless-steel EMS fabric, the increase amplitude of the SE reached between 6 dB and 15 dB in most frequency bands. The overall SE of the fabric showed a decrease trend with the reduction of the outer diameter of the SRR. The decrease trend was sometimes fast and sometimes slow. The decreasing amplitudes were different in various frequency ranges. The number of embroidery threads had a certain effect on the SE of the fabric. When other parameters remained unchanged, the increase of the diameter of the embroidery thread resulted in the increase of the SE of the fabric. However, the overall improvement was not significant. Finally, this article also points out that other influencing factors of the SRR need to be explored, and the failure phenomenon may occur under certain situations. The proposed method has the advantages of the simple process, convenient design, no pore formation, SE improvement retaining the original porous characteristics of the fabric. This paper provides a new idea for the design, production, and development of new EMS fabrics.
Two-Step Purification and Partial Characterization of Keratinolytic Proteases from Feather Meal Bioconversion by Bacillus sp. P45
Authors: Lemes Ailton Cesar , Gautério Gabrielle Victoria , Rosa Cezar Augusto da , Brandelli Adriano , Kalil Susana Juliano
Published: March 2023

This study aimed to purify and partially characterize a keratinolytic protease produced by Bacillus sp. P45 through bioconversion of feather meal. Crude protease extract was purified using a sequence of an aqueous two-phase system (ATPS) in large volume systems (10, 50, and 500 g) to increase obtaining purified enzyme, followed by a diafiltration (DF) step. Purified protease was characterized in terms of protein profile analysis by SDS-PAGE, optimum temperature and pH, thermal deactivation kinetics at different temperatures and pH, and performance in the presence of several salts (NaCl, CaCl2, MnCl2, CaO, C8H5KO4, MgSO4, CuSO4, ZnSO4, and FeCl3) and organic solvents (acetone, ethanol, methanol, acetic acid, diethyl ether, and formaldehyde). ATPS with high capacities resulted in purer protease extract without compromising purity and yields, reaching a purification factor up to 2.6-fold and 6.7-fold in first and second ATPS, respectively, and 4.0-fold in the DF process. Recoveries were up to 79% in both ATPS and reached 84.3% after the DF step. The electrophoretic analysis demonstrated a 25–28 kDa band related to keratinolytic protease. The purified protease’s optimum temperature and pH were 55 °C and 7.5, respectively. The deactivation energy (Ed) value was 118.0 kJ/mol, while D (decimal reduction time) and z (temperature interval required to reduce the D value in one log cycle) values ranged from 6.7 to 237.3 min and from 13.6 to 18.8 °C, respectively. Salts such as CaCl2, CaO, C8H5KO4, and MgSO4 increased the protease activity, while all organic solvents caused its decrease. The results are useful for future studies about ATPS scale-up for enzyme purification and protease application in different industrial processes.
Efficiency Measurement Using Data Envelopment Analysis (DEA) in Public Healthcare: Research Trends from 2017 to 2022
Authors: Jung Sungwook , Son Jiyoon , Kim Changhee , Chung Kyunghwa
Published: March 2023

With the shifting healthcare environment, the importance of public healthcare systems is being emphasized, and the efficiency of public healthcare systems has become a critical research agenda. We reviewed recent research on the efficiency of public healthcare systems using DEA, which is one of the leading methods for efficiency analysis. Through a systematic review, we investigated research trends in terms of research purposes, specific DEA techniques, input/output factors used for models, etc. Based on the review results, future research directions are suggested. The results of this paper provide valuable information and guidelines for future DEA research on public healthcare systems.
Experimental and Simulation Study of the Latest HFC/HFO and Blend of Refrigerants in Vapour Compression Refrigeration System as an Alternative of R134a
Authors: Prasad Uma Shankar , Mishra Radhey Shyam , Das Ranadip Kumar , Soni Hargovind
Published: March 2023

Experimental and simulation investigation of the performance and characteristics of different refrigerants and blends of refrigerants is carried out to replace the existing refrigerant R134a for a vapour compression refrigeration system. The performance of VCRS systems was improved by several researchers by introducing the concept of mixing the family of refrigerants with low GWP in the working circuit. This research paper presents the performance results of different refrigerants and blends of refrigerants that can replace the R134a it is also an attempt to cover the mechanism and possible combination of different blends of refrigerants to improve the effectiveness as well as efficiency of the refrigeration system. Detailed analysis of different parameters of heat transfer and predictions of low-GWP refrigerants, including the HFO (hydro fluoro-olefin) class and the HC (hydrocarbon) class through energy and exergy analysis of commercial refrigerants such as R134a is performed. Results are obtained by using an experimental test rig and the input parameters of the experiments are kept the same with the simulation software (CYCLE_D-HX 2.0) and validated with the results to replace R134a.
Vehicle Recognition Based on Region Growth of Relative Tension and Similarity Measurement of Side Projection Profile of Vehicle Body
Authors: Zheng Mingxue , Wu Huayi
Published: March 2023

Current vehicle recognition methods are less concerned simultaneously with: (1) the scale difference between vehicles and other objects in urban city; and (2) the impact of physical characteristics of vehicles. Based on the region growth of relative tension, a method for measuring the similarity of side projection profile of a vehicle’s body is proposed for recognizing vehicles. First, region growth of relative tension is used to divide 3D point clouds into a series of spatial regions. Point clouds in these regions are projected to a 2D plane. Then, relevant 2D features are extracted, including side projection profile of vehicle body and sizes of vehicles. Screening by these relevant features, part of these regions, and point clouds inside them which conforms to the similarity measurement conditions of vehicles are selected. Quantitative evaluations on the selected data set show that the proposed algorithm achieves a recall, precision, and F-score of 0.837, 0.979, and 0.902, respectively, in recognizing vehicles. Comparative studies demonstrate the superior performance of the proposed algorithm.
Wavelength Calibration for the LIBS Spectra of the Zhurong Mars Rover
Authors: Zhang Yizhong , Ren Xin , Chen Zhaopeng , Chen Wangli , Zhang Zhenqiang , Liu Xiangfeng , Xu Weiming , Liu Jianjun , Li Chunlai
Published: March 2023

China’s first Mars rover, Zhurong, landed on the southern region of Utopia Planitia, Mars, on 14 May 2021 (UTC). Zhurong is equipped with the Mars Surface Composition Detection Package (MarSCoDe), which analyzes the Martian surface’s material composition. Composed of laser-induced breakdown spectroscopy (LIBS), short-wave infrared spectroscopy (SWIR), and a microimaging camera, MarsCoDe can work at a distance of 1.6–7 m to analyze element abundance and the mineralogy of targets on the Martian surface. Analysis shows that the wavelengths of MarSCoDe onboard LIBS spectra acquired within the same probe period will have different degrees of drift, leading to deviation in qualitative and quantitative elemental analysis. This paper finds that the spectrum drift follows a quadratic function relationship with the CCD temperature of the MarSCoDe spectrometer, based on which a wavelength calibration method is established. According to the function, the drift of a certain channel is calculated by the corresponding CCD temperature, and then the wavelength of the spectrum is calibrated by the drift. The accuracy of this calibration method for the position of peak wavelength in the LIBS spectrum can reach about 1/5 of the apparatus spectral width, and the cross-validation analysis using a norite standard sample shows that it is comparable to the wavelength calibration accuracy of the ChemCam onboard data product.
Acquisition and Processing Data from UAVs in the Process of Generating 3D Models for Solar Potential Analysis
Authors: Mitka Bartosz , Klapa Przemysław , Pióro Piotr
Published: March 2023

UAVs have recently become a very popular tool for acquiring geospatial data. Photographs, films, images, and results of measurements of various sensors from them constitute source material for generating, among other things, photographic documentation, visualisation of places and objects, cartographic materials and 3D models. These models are not only material for the visualisation of objects but are also source material for spatial analysis, including the assessment and analyses of the solar potential of buildings. This research aims to benchmark the feasibility of using UAV-derived data acquired from three sensors, namely the DJI Zenmuse P1 camera, the Share PSDK102S v2 multi-lens camera and the DJI Zenmuse L1 laser scanner. The data from these were acquired for the construction of comprehensive and reliable 3D models, which will form the basis for generating solar potential maps. Various sensors, data storage formats, and geospatial data processing capabilities are analysed to determine the most optimal and efficient solution for providing accurate, complete and reliable 3D models of places and objects for the construction of solar potential maps. In this paper, the authors prepare a compilation of the results of the studies from different measurement combinations and analyse the strengths and weaknesses of the different solutions, as well as the integration of the results for an optimal 3D model, which was used to perform solar potential analyses for the selected built-up area. The results of the study show that the parameters for assessing the quality of a 3D model can be statistical parameters that determine the coplanarity of roof slope points (i.e., standard deviation, distances from the plane, and RMS value). The completeness of the model is defined as the percentage of the recorded area by sensors to the total area of the model.
A Traffic-Aware Fair MAC Protocol for Layered Data Collection Oriented Underwater Acoustic Sensor Networks
Authors: Yang Sidan , Liu Xuan , Su Yishan
Published: March 2023

Underwater acoustic channels are characterized by long propagation delay, limited available bandwidth and high energy costs. These unique characteristics bring challenges to design media access control (MAC) protocol for underwater acoustic sensor networks (UASNs). Especially in data-collection-oriented UASNs, data generated at underwater nodes are transmitted hop-by-hop to the sink node. The traffic loads undertaken by nodes of different depths are different. However, most existing MAC protocols do not consider the traffic load imbalance in data-collection-oriented UASNs, resulting in unfairness in how the nodes transmit their own generated data. In this paper, we propose a novel traffic-aware fair MAC protocol for layered data-collection-oriented UASNs, called TF-MAC. TF-MAC accesses a medium by assigning time slots of different lengths to each layer via different traffic loads to achieve traffic fairness of nodes. To improve throughput and avoid collision in the network, an overlapping time slot division mechanism for different layers and multi-channel allocation scheme within each single layer is employed. Considering the time-varying traffic loads of the nodes, an adaptive packet length algorithm is proposed by taking advantage of the spatial-temporal uncertainty of underwater channels. A sea experiment was conducted to prove the spatial-temporal uncertainty of UASNs, which provides a feasibility basis for the proposed algorithm. Simulation results show that TF-MAC can greatly improve the network performance in terms of throughput, delay, energy consumption, and fairness in the layered data-collection-oriented UASNs.
Causes and Impacts of Decreasing Chlorophyll-a in Tibet Plateau Lakes during 1986–2021 Based on Landsat Image Inversion
Authors: Pang Shuyu , Zhu Liping , Liu Chong , Ju Jianting
Published: March 2023

Lake chlorophyll-a (Chl-a) is one of the important components of the lake ecosystem. Numerous studies have analyzed Chl-a in ocean and inland water ecosystems under pressures from climate change and anthropogenic activities. However, little research has been conducted on lake Chl-a variations in the Tibet Plateau (TP) because of its harsh environment and limited opportunities for in situ data monitoring. Here, we combined 95 in situ measured lake Chl-a concentration data points and the Landsat reflection spectrum to establish an inversion model of Chl-a concentration. For this, we retrieved the mean annual Chl-a concentration in the past 35 years (1986–2021) of 318 lakes with an area of > 10 km2 in the TP using the backpropagation (BP) neural network prediction method. Meteorological and hydrological data, measured water quality parameters, and glacier change in the lake basin, along with geographic information system (GIS) technology and spatial statistical analysis, were used to elucidate the driving factors of the Chl-a concentration changes in the TP lakes. The results showed that the mean annual Chl-a in the 318 lakes displayed an overall decrease during 1986–2021 (−0.03 μg/L/y), but 63%, 32%, and 5% of the total number exhibited no significant change, significant decrease, and significant increase, respectively. After a slight increase during 1986–1995 (0.05 μg/L/y), the mean annual lake Chl-a significantly decreased during 1996–2004 (−0.18 μg/L/y). Further, it decreased slightly during 2005–2021 (−0.02 μg/L/y). The mean annual lake Chl-a concentration was significantly negatively correlated with precipitation (R2 = 0.48, p < 0.01), air temperature (R2 = 0.31, p < 0.01), lake surface water temperature (LSWT) (R2 = 0.51, p < 0.01), lake area (R2 = 0.42, p < 0.01), and lake water volume change (R2 = 0.77, p < 0.01). The Chl-a concentration of non-glacial-meltwater-fed lakes were higher than those of glacial-meltwater-fed lakes, except during higher precipitation periods. Our results shed light on the impacts of climate change on Chl-a variation in the TP lakes and lay the foundation for understanding the changes in the TP lake ecosystem.
Rediscovering the Lost Roman Landscape in the Southern Trieste Karst (North-Eastern Italy): Road Network, Land Divisions, Rural Buildings and New Hints on the Avesica Road Station
Authors: Bernardini Federico
Published: March 2023

An interdisciplinary study of the ancient landscape of the Trieste Karst (north-eastern Italy) is presented in this paper. Airborne Laser Scanning (ALS) has been applied to obtain high-resolution topography of the 25 km2 investigated area in order to identify potential archaeological anomalies. The ALS-derived high-resolution Digital Terrain Models have been visualized and managed using QGIS and Relief Visualization Toolbox. Possible archaeological anomalies have been verified through field surveys and interpreted using a multidisciplinary approach mainly based on the collection of associated archaeological materials and geomorphological and stratigraphic evidence. From a methodological perspective, the elaboration and study of ALS-derived images, and in particular the local relief model visualization, combined with the collection of Roman shoe hobnails, have proven to be effective approaches for the certain identification and dating of Roman roads in karst environments. The obtained results have revealed an almost completely unknown Roman landscape: the investigated area was crossed by important public roads, whose layout has been accurately reconstructed for a total length of over 10 km, and occupied by large country estates, sometimes enclosed within boundary walls perfectly fitting the Roman land division grid. One of the identified buildings could correspond to a road station, perhaps the Avesica known from ancient itinerary documents—i.e., the itinerarium Antonini Augusti—due to its position and proximity to a major road junction.
Evaluating Simulated Microphysics of Stratiform and Convective Precipitation in a Squall Line Event Using Polarimetric Radar Observations
Authors: Sun Yuting , Zhou Zhimin , Gao Qingjiu , Li Hongli , Wang Minghuan
Published: March 2023

Recent upgrades to China’s radar network now allow for polarimetric measurements of convective systems in central China, providing an effective data set with which to evaluate the microphysics schemes employed in local squall line simulations. We compared polarimetric radar variables derived by Weather Research and Forecasting (WRF) and radar forward models and the corresponding hydrometeor species with radar observations and retrievals for a severe squall line observed over central China on 16 March 2022. Two microphysics schemes were tested and were able to accurately depict the contrast between convective and stratiform regions in terms of the drop size distribution (DSD) and reproduce the classical polarimetric signatures of the observed differential reflectivity (ZDR) and specific differential phase (KDP) columns. However, for the convective region, the simulated DSDs in both schemes exhibited lower proportions of large drops and lower liquid water content; by contrast, for the stratiform region, the proportion of large drops was found to be too high in the Morrison (MORR) scheme. The underprediction of ice-phase processes in the convective region, particularly the riming processes associated with graupel and hail, was likely responsible for the bias toward large raindrops at low levels. In the stratiform region, raindrop evaporation in the WRF Double-Moment 6-Class (WDM6) scheme, which partially offsets the overestimation of ice-phase processes, produced ground DSDs that more closely matched the observational data, and did not exhibit the overly strong warm-rain collisional growth processes of MORR.
A Two-Stage Multi-Agent EV Charging Coordination Scheme for Maximizing Grid Performance and Customer Satisfaction
Authors: Amin Adil , Mahmood Anzar , Khan Ahsan Raza , Arshad Kamran , Assaleh Khaled , Zoha Ahmed
Published: March 2023

Advancements in technology and awareness of energy conservation and environmental protection have increased the adoption rate of electric vehicles (EVs). The rapidly increasing adoption of EVs may affect grid operation adversely. However, the increased integration of EVs, if managed appropriately, can positively impact the performance of the electrical network in terms of power losses, voltage deviations and transformer overloads. This paper presents a two-stage multi-agent-based scheme for the coordinated charging scheduling of EVs. The first stage uses particle swarm optimization (PSO) at the distribution network operator (DNO) level to determine the optimal power allocation among the participating EV aggregator agents to minimize power losses and voltage deviations, whereas the second stage at the EV aggregator agents level employs a genetic algorithm (GA) to align the charging activities to achieve customers’ charging satisfaction in terms of minimum charging cost and waiting time. The proposed method is implemented on the IEEE-33 bus network connected with low-voltage nodes. The coordinated charging plan is executed with the time of use (ToU) and real-time pricing (RTP) schemes, considering EVs’ random arrival and departure with two penetration levels. The simulations show promising results in terms of network performance and overall customer charging satisfaction.
Linear Interval Approximation of Sensor Characteristics with Inflection Points
Authors: Marinov Marin B. , Nikolov Nikolay , Dimitrov Slav , Ganev Borislav , Nikolov Georgi T. , Stoyanova Yana , Todorov Todor , Kochev Lachezar
Published: March 2023

The popularity of smart sensors and the Internet of Things (IoT) is growing in various fields and applications. Both collect and transfer data to networks. However, due to limited resources, deploying IoT in real-world applications can be challenging. Most of the algorithmic solutions proposed so far to address these challenges were based on linear interval approximations and were developed for resource-constrained microcontroller architectures, i.e., they need buffering of the sensor data and either have a runtime dependency on the segment length or require the sensor inverse response to be analytically known in advance. Our present work proposed a new algorithm for the piecewise-linear approximation of differentiable sensor characteristics with varying algebraic curvature, maintaining the low fixed computational complexity as well as reduced memory requirements, as demonstrated in a test concerning the linearization of the inverse sensor characteristic of type K thermocouple. As before, our error-minimization approach solved the two problems of finding the inverse sensor characteristic and its linearization simultaneously while minimizing the number of points needed to support the characteristic.
Computer Vision Applications in Intelligent Transportation Systems: A Survey
Authors: Dilek Esma , Dener Murat
Published: March 2023

As technology continues to develop, computer vision (CV) applications are becoming increasingly widespread in the intelligent transportation systems (ITS) context. These applications are developed to improve the efficiency of transportation systems, increase their level of intelligence, and enhance traffic safety. Advances in CV play an important role in solving problems in the fields of traffic monitoring and control, incident detection and management, road usage pricing, and road condition monitoring, among many others, by providing more effective methods. This survey examines CV applications in the literature, the machine learning and deep learning methods used in ITS applications, the applicability of computer vision applications in ITS contexts, the advantages these technologies offer and the difficulties they present, and future research areas and trends, with the goal of increasing the effectiveness, efficiency, and safety level of ITS. The present review, which brings together research from various sources, aims to show how computer vision techniques can help transportation systems to become smarter by presenting a holistic picture of the literature on different CV applications in the ITS context.
Engineering of Advanced Materials for High Magnetic Field Sensing: A Review
Authors: Žurauskienė Nerija
Published: March 2023

Advanced scientific and industrial equipment requires magnetic field sensors with decreased dimensions while keeping high sensitivity in a wide range of magnetic fields and temperatures. However, there is a lack of commercial sensors for measurements of high magnetic fields, from ∼1 T up to megagauss. Therefore, the search for advanced materials and the engineering of nanostructures exhibiting extraordinary properties or new phenomena for high magnetic field sensing applications is of great importance. The main focus of this review is the investigation of thin films, nanostructures and two-dimensional (2D) materials exhibiting non-saturating magnetoresistance up to high magnetic fields. Results of the review showed how tuning of the nanostructure and chemical composition of thin polycrystalline ferromagnetic oxide films (manganites) can result in a remarkable colossal magnetoresistance up to megagauss. Moreover, by introducing some structural disorder in different classes of materials, such as non-stoichiometric silver chalcogenides, narrow band gap semiconductors, and 2D materials such as graphene and transition metal dichalcogenides, the possibility to increase the linear magnetoresistive response range up to very strong magnetic fields (50 T and more) and over a large range of temperatures was demonstrated. Approaches for the tailoring of the magnetoresistive properties of these materials and nanostructures for high magnetic field sensor applications were discussed and future perspectives were outlined.
Blending Approach Preparation of PVA-g-PMA Films with Embedded “Green” Synthesized Silver Nanoparticles for Acetone Optical Detection
Authors: Lazarova Katerina , Christova Darinka , Karashanova Daniela , Georgieva Biliana , Marovska Gergana , Slavov Anton , Babeva Tsvetanka
Published: March 2023

The blending approach (also known as the ex-situ approach) was used for the deposition of thin composite films comprising poly(vinyl alcohol-graft-methyl acrylate) (PVA-g-PMA) and silver nanoparticles (AgNPs). Firstly, the copolymer aqueous dispersion was synthesized through the redox polymerization of methyl acrylate (MA) on poly(vinyl alcohol) (PVA) using ammonium cerium (IV) nitrate as the initiator. Then, AgNPs were synthesized through a “green” method using the water extract of lavender based on by-products of the essential oil industry, and then they were blended with the polymer. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) were used to determine nanoparticle size, along with their stability over time in suspension, during the 30-day period. Thin films of the PVA-g-PMA copolymer, with different AgNP volume fractions varying between 0.008 and 0.260%, were deposited via the spin-coating method on Si substrates, and their optical properties were explored. UV-VIS-NIR spectroscopy and non-linear curve fitting were used for the determination of the refractive index, extinction coefficient, and thickness of the films, while photoluminescence measurements at room temperature were conducted for studying the emission of the films. The concentration dependence of film thickness was observed and showed that thickness increased linearly from 31 nm to 75 nm when the nanoparticles’ weight content increased from 0.3 wt% to 2.3 wt%. The sensing properties toward acetone vapors were tested in a controlled atmosphere by measuring reflectance spectra before and during exposure to the analyte molecules in the same film spot; the swelling degree of films was calculated and compared to the corresponding undoped samples. It was shown that the concentration of AgNPs of 1.2 wt% in the films is optimal for the enhancement of the sensing response toward acetone. The influence of AgNPs on the films’ properties was revealed and discussed.
An Electro-Oculogram (EOG) Sensor’s Ability to Detect Driver Hypovigilance Using Machine Learning
Authors: Murugan Suganiya , Sivakumar Pradeep Kumar , Kavitha C. , Harichandran Anandhi , Lai Wen-Cheng
Published: March 2023

Driving safely is crucial to avoid death, injuries, or financial losses that can be sustained in an accident. Thus, a driver’s physical state should be monitored to prevent accidents, rather than vehicle-based or behavioral measurements, and provide reliable information in this regard. Electrocardiography (ECG), electroencephalography (EEG), electrooculography (EOG), and surface electromyography (sEMG) signals are used to monitor a driver’s physical state during a drive. The purpose of this study was to detect driver hypovigilance (drowsiness, fatigue, as well as visual and cognitive inattention) using signals collected from 10 drivers while they were driving. EOG signals from the driver were preprocessed to remove noise, and 17 features were extracted. ANOVA (analysis of variance) was used to select statistically significant features that were then loaded into a machine learning algorithm. We then reduced the features by using principal component analysis (PCA) and trained three classifiers: support vector machine (SVM), k-nearest neighbor (KNN), and ensemble. A maximum accuracy of 98.7% was obtained for the classification of normal and cognitive classes under the category of two-class detection. Upon considering hypovigilance states as five-class, a maximum accuracy of 90.9% was achieved. In this case, the number of detection classes increased, resulting in a reduction in the accuracy of detecting more driver states. However, with the possibility of incorrect identification and the presence of issues, the ensemble classifier’s performance produced an enhanced accuracy when compared to others.
Monitoring Land Degradation Dynamics to Support Landscape Restoration Actions in Remote Areas of the Mediterranean Basin (Murcia Region, Spain)
Authors: Gabriele Marzia , Brumana Raffaella
Published: March 2023

This study aims to develop a workflow methodology for collecting substantial amounts of Earth Observation data to investigate the effectiveness of landscape restoration actions and support the implementation of the Above Ground Carbon Capture indicator of the Ecosystem Restoration Camps (ERC) Soil Framework. To achieve this objective, the study will utilize the Google Earth Engine API within R (rGEE) to monitor the Normalized Difference Vegetation Index (NDVI). The results of this study will provide a common scalable reference for ERC camps globally, with a specific focus on Camp Altiplano, the first European ERC located in Murcia, Southern Spain. The coding workflow has effectively acquired almost 12 TB of data for analyzing MODIS/006/MOD13Q1 NDVI over a 20-year span. Additionally, the average retrieval of image collections has yielded 120 GB of data for the COPERNICUS/S2_SR 2017 vegetation growing season and 350 GB of data for the COPERNICUS/S2_SR 2022 vegetation winter season. Based on these results, it is reasonable to asseverate that cloud computing platforms like GEE will enable the monitoring and documentation of regenerative techniques to achieve unprecedented levels. The findings will be shared on a predictive platform called Restor, which will contribute to the development of a global ecosystem restoration model.
Exploring the Effects of LED-Based Visible Light Communication on Reading and Color Perception in Indoor Environments: An Experimental Study
Authors: Caputo Stefano , Mucchi Lorenzo , Comparetto Regina , D’Antoni Vittoria , Farini Alessandro , Orsi Valentina , Baldanzi Elisabetta
Published: March 2023

Visible light communications (VLC) is a technology that enables the transmission of digital information with a light source. VLC is nowadays seen as a promising technology for indoor applications, helping WiFi to handle the spectrum crunch. Possible indoor applications range from Internet connection at home/office to multimedia content delivery in a museum. Despite the vast interest of researchers in both theoretical analysis and experimentation on VLC technology, no studies have been carried out on the human perceptions of objects illuminated by VLC-based lamps. It is important to define if a VLC lamp decreases the reading capability or modifies the color perception in order to make VLC a technology appropriate for everyday life use. This paper describes the results of psychophysical tests on humans to define if VLC lamps modify the perception of colors or the reading speed. The results of the reading speed test showed a 0.97 correlation coefficient between tests with and without VLC modulated light, leading us to conclude that there is no difference in the reading speed capability with and without VLC-modulated light. The results of the color perception test showed a Fisher exact test p-value of 0.2351, showing that the perception of color is not influenced by the presence of the VLC modulated light.
IoT and Deep Learning-Based Farmer Safety System
Authors: Adhitya Yudhi , Mulyani Grathya Sri , Köppen Mario , Leu Jenq-Shiou
Published: March 2023

Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, receive training, and work in a safe environment. With the wearable device as an Internet of Things (IoT) subsystem, the device can read sensor data as well as compute and send information. We investigated the validation and simulation dataset to determine whether accidents occurred with farmers by applying the Hierarchical Temporal Memory (HTM) classifier with each dataset input from the quaternion feature that represents 3D rotation. The performance metrics analysis showed a significant 88.00% accuracy, precision of 0.99, recall of 0.04, F_Score of 0.09, average Mean Square Error (MSE) of 5.10, Mean Absolute Error (MAE) of 0.19, and a Root Mean Squared Error (RMSE) of 1.51 for the validation dataset, 54.00% accuracy, precision of 0.97, recall of 0.50, F_Score of 0.66, MSE = 0.06, MAE = 3.24, and = 1.51 for the Farming-Pack motion capture (mocap) dataset. The computational framework with wearable device technology connected to ubiquitous systems, as well as statistical results, demonstrate that our proposed method is feasible and effective in solving the problem’s constraints in a time series dataset that is acceptable and usable in a real rural farming environment for optimal solutions.