bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Drude-Type Response of Photocarriers in Fe-Doped β-Ga2O3 Crystal
Authors: Jiang Hao , Wang Ke , Murakami Hironaru , Tonouchi Masayoshi
Published: April 2022

Beta gallium oxide, β-Ga2O3, is one of the promising ultrawide bandgap semiconductors with a monoclinic (C2/m) β-phase structure showing strong anisotropic properties. To improve the performance of these devices, more optical characterization is required. Here, the anisotropic carrier dynamics in optically excited (010) oriented Fe-doped β-Ga2O3 was studied by terahertz time-domain spectroscopy. An 800 nm continuous-wave light source was employed to excite carriers from Fe acceptors to the conduction band and to probe an anisotropic interaction with the THz field. The complex THz conductivities fitted with the Drude and Drude–Smith models revealed that the optically excited carriers behave as nearly free carriers along the a-axis, whereas those along the c-axis show a non-Drude type response. The estimated mobility for the c-axis agrees with the reported values, whereas the results suggest much higher mobility along the a-axis.
Intraspecific Diversity in Aquatic Ecosystems: Comparison between Spirodela polyrhiza and Lemna minor in Natural Populations of Duckweed
Authors: Bog Manuela , Appenroth Klaus-Juergen , Schneider Philipp , Sree K. Sowjanya
Published: April 2022

Samples of two duckweed species, Spirodela polyrhiza and Lemna minor, were collected around small ponds and investigated concerning the question of whether natural populations of duckweeds constitute a single clone, or whether clonal diversity exists. Amplified fragment length polymorphism was used as a molecular method to distinguish clones of the same species. Possible intraspecific diversity was evaluated by average-linkage clustering. The main criterion to distinguish one clone from another was the 95% significance level of the Jaccard dissimilarity index for replicated samples. Within natural populations of L. minor, significant intraspecific genetic differences were detected. In each of the three small ponds harbouring populations of L. minor, based on twelve samples, between four and nine distinct clones were detected. Natural populations of L. minor consist of a mixture of several clones representing intraspecific biodiversity in an aquatic ecosystem. Moreover, identical distinct clones were discovered in more than one pond, located at a distance of 1 km and 2.4 km from each other. Evidently, fronds of L. minor were transported between these different ponds. The genetic differences for S. polyrhiza, however, were below the error-threshold of the method within a pond to detect distinct clones, but were pronounced between samples of two different ponds.
Investigation of the Warpage of a High-Density Polyethylene Pallet by Plastic Injection Compression Molding: Part I—Numerical Approach
Authors: Cheng Chun-Der , Liao Yi-Ling , Tsai Hsi-Hsun
Published: April 2022

Many challenges are associated with the injection compression molding process for producing a half-pallet (1320 mm × 1110 mm × 75 mm, length × width × height), which is butt-welded to another one for enhancing its strength. This pooled high-density polyethylene (HDPE) pallet is able to endure the impacts of a heavy load and a low ambient temperature. Reducing the warpage of a half-pallet is, therefore, essential for reducing the residual internal stress within the welded portions. An advanced Moldex3D package helps to detail the temperature distribution and warpage of a half-pallet. The pre-setting molding parameters from a mass-production factory produce half-pallets with worse flatness. In this investigation on using appropriate cooling water temperatures within the core and cavity plates of the mold, the numerical results show that the warpage of the top surface of the half-pallet was 11.549 mm, low warpage with respect to this large-scale pallet. Furthermore, the compression speed of 50–60 mm/s may have produced a low flatness of the half-pallet in this study.
Facile Synthesis of Hydrogel-Based Ion-Exchange Resins for Nitrite/Nitrate Removal and Studies of Adsorption Behavior
Authors: Dharmapriya Thakshila Nadeeshani , Shih Hsin-Yin , Huang Po-Jung
Published: April 2022

This research aimed to create facile, reusable, hydrogel-based anion exchange resins that have been modified with two different amines to test their ability to adsorb nitrate and nitrite in water using batch and continuous systems. In the batch experiment, maximum adsorption capacities of nitrate and nitrite onto poly (ethylene glycol) diacrylate methacryloxyethyltrimethyl ammonium chloride (PEGDA-MTAC) and poly (ethylene glycol) diacrylate 2-aminoethyl methacrylate hydrochloride (PEGDA-AMHC) adsorbents can be obtained as 13.51 and 13.16 mg NO3−-N/g sorbent; and 12.36 and 10.99 mg NO2−-N/g sorbent respectively through the Langmuir isotherm model. After 15 adsorption/desorption cycles, PEGDA-MTAC and PEGDA-AMHC retained nitrate adsorption efficiencies of 94.71% and 83.02% and nitrite adsorption efficiencies of 97.38% and 81.15% respectively. In a column experiment, modified adsorbents demonstrated adsorption efficiencies greater than 45% after being recycled five times. Proposed hydrogel-based adsorbents can be more effective than several types of carbon-based sorbents for nitrate and nitrite removal in water and have benefits such as reduced waste generation, cost-effectiveness, and a facile synthesis method.
A Review on Green Synthesis of TiO2 NPs: Photocatalysis and Antimicrobial Applications
Authors: Verma Vishal , Al-Dossari Mawaheb , Singh Jagpreet , Rawat Mohit , Kordy Mohamed G. M. , Shaban Mohamed
Published: April 2022

Nanotechnology is a fast-expanding area with a wide range of applications in science, engineering, health, pharmacy, and other fields. Nanoparticles (NPs) are frequently prepared via a variety of physical and chemical processes. Simpler, sustainable, and cost-effective green synthesis technologies have recently been developed. The synthesis of titanium dioxide nanoparticles (TiO2 NPs) in a green/sustainable manner has gotten a lot of interest in the previous quarter. Bioactive components present in organisms such as plants and bacteria facilitate the bio-reduction and capping processes. The biogenic synthesis of TiO2 NPs, as well as the different synthesis methods and mechanistic perspectives, are discussed in this review. A range of natural reducing agents including proteins, enzymes, phytochemicals, and others, are involved in the synthesis of TiO2 NPs. The physics of antibacterial and photocatalysis applications were also thoroughly discussed. Finally, we provide an overview of current research and future concerns in biologically mediated TiO2 nanostructures-based feasible platforms for industrial applications.
Using a Fiber Bragg Grating Sensor to Measure Residual Strain in the Vacuum-Assisted Resin Transfer Molding Process
Authors: Luo Guang-Min , Liou Guang-Yen , Xiao Hong-Zhe
Published: April 2022

Vinyl ester (VE) resin has strong environmental tolerance and is the matrix commonly used in the composite materials of fiber-reinforced plastics (FRP). VE resin is often combined with glass fiber in different maritime structures, such as wind turbine blades, spinner cases, and nacelle cases. However, VE resin exhibits exothermic reactions and shrinkage during curing, which often generates residual strain in large structures and those with a high stacking number. This study explored the exothermic reaction and shrinkage of VE resin and glass fiber during the vacuum-assisted resin transfer molding process, as measured using a fiber Bragg grating sensor. The experiment results verified the relationship between the stacking number and residual strain shrinkage. In addition, the symmetric laminate method was used to prevent the bending–twisting coupling effect and subsequent warping deformation of the FRP laminated plate during curing. The experiment results also verified that the bottom layers of the FRP laminated plates produced using VE resin were closer to the mold, and exhibited more shrinkage as the stacking number increased. In addition, this study discovered that during the experiment, the symmetry layer of the FRP laminated plate had a higher exothermic temperature than the bottom layer as a result of the symmetry layer’s ineffective heat dissipation. Therefore, the curing shrinkage of the symmetry layer resin was measured. The experiment results indicated that if the stacking number was between 10 and 30, the residual strain shrinkage of the symmetry layer was greater than that of the surface layer. However, because of the symmetric laminate, the residual strain of the symmetry layer did not increase when the temperature increased. Therefore, the greatest residual strain occurred at the surface of the bottom layer of the laminated plate with a stacking number of 40.
Thermal and Calorimetric Investigations of Some Phosphorus-Modified Chain Growth Polymers 1: Polymethyl Methacrylate
Authors: Arun Malavika , Bigger Stephen , Guerrieri Maurice , Joseph Paul , Tretsiakova-McNally Svetlana
Published: April 2022

The thermal and calorimetric characterizations of polymethyl methacrylate-based polymers are reported in this paper. The modifying groups incorporated the phosphorus atom in various chemical environments, including oxidation states of III, or V. Both additive and reactive strategies were employed, where the loading of phosphorus was kept at 2 wt% in all cases. The plaques, obtained through the bulk polymerization route, were subjected to a variety of spectroscopic, thermal and combustion techniques. The results showed that the different modifying groups exerted varying nature, degrees and modes of combustion behaviors, which also included in some cases an additive, and even an antagonistic effect. In the case of covalently-bound phosphonate groups, early cracking of the pendent ester moieties was shown to produce phosphoric acid species, which in turn can act in the condensed phase. For the additives, such as phosphine and phosphine oxide, limited vapor-phase inhibition can be assumed to be operative.
Mathematical Description of the RAFT Copolymerization of Styrene and Glycidyl Methacrylate Using the Terminal Model
Authors: Tenorio-López José Alfredo , Benvenuta-Tapia Juan José , García-Navarro Norma , Vivaldo-Lima Eduardo , Champagne Pascale , Saldívar-Guerra Enrique
Published: April 2022

A mathematical model for the kinetics, composition and molar mass development of the bulk reversible addition-fragmentation chain transfer (RAFT) copolymerization of glycidyl methacrylate (GMA) and styrene (St), at several GMA molar feed fractions at 103 °C, in the presence of 2-cyano isopropyl dodecyl trithiocarbonate as the RAFT agent and 1,1′-azobis(cyclohexane carbonitrile), as the initiator, is presented. The copolymerization proceeded in a controlled manner and dispersities of the copolymers remained narrow even at high conversions. Experimental data and calculated profiles of conversion versus time, composition versus conversion and molar mass development for the RAFT copolymerization of St and GMA agreed well for all conditions tested, including high-conversion regions. The kinetic rate constants associated with the RAFT- related reactions and diffusion-controlled parameters were properly estimated using a weighted nonlinear multivariable regression procedure. The mathematical model developed in this study may be used as an aid in the design and upscaling of industrial RAFT polymerization processes.
Setting MRP Parameters and Optimizing the Production Planning Process
Authors: Malindzakova Marcela , Garaj Patrik , Trpčevská Jarmila , Malindzak Dusan
Published: April 2022

This article describes a methodical framework that combines two specific methods of Lean management, namely the ABC method and the MRP planning method. The article further argues that combining the ABC inventory method with subsequent MRP planning is beneficial if the combination is implemented in practice. To demonstrate the benefits, the framework is tested using a case study company. The presented case-study problem is to reduce the number of changeover downtimes in the environment of an engineering production company. The researched company deals with the problem of setting up production lines in a way to minimize the number of downtimes within one work shift. Within the solution, four possible variants of the production plan are presented. By combining the ABC and MRP methods, up to four changeovers can be saved, which in financial terms represents a saving of about EUR 450,000 per year.
Synchronous or Not? The Timing of the Younger Dryas and Greenland Stadial-1 Reviewed Using Tephrochronology
Authors: Larsson Simon A. , Kylander Malin E. , Sannel A. Britta K. , Hammarlund Dan
Published: April 2022

The exact spatial and temporal behaviour of rapid climate shifts during the Last Glacial–Interglacial Transition are still not entirely understood. In order to investigate these events, it is necessary to have detailed palaeoenvironmental reconstructions at geographically spread study sites combined with reliable correlations between them. Tephrochronology, i.e., using volcanic ash deposits in geological archives as a dating and correlation tool, offers opportunities to examine the timing of events across wider regional scales. This study aims to review the posited asynchrony of the Younger Dryas stadial in comparison with Greenland Stadial-1 by correlating new proxy data from southernmost Sweden to previous palaeoclimate reconstructions in Europe based on the presence of the Hässeldalen Tephra, the Vedde Ash, and the Laacher See Tephra. μ-XRF core-scanning data were projected using a recently published age–depth model based on these tephras and several radiocarbon dates, and compared to previous findings, including by adapting previous chronologies to the recently proposed earlier date of the Laacher See Tephra (13,006 ± 9 cal. a BP). Although the results to some extent support the idea of a more synchronous Younger Dryas event than previously assumed, this issue requires further high-resolution proxy studies to overcome limitations of temporal precision.
British Quaker Aid to Spanish Republican Exiles in Concentration Camps in the South of France (1939–1940)
Authors: Palfreeman Linda
Published: April 2022

When a failed military coup provoked civil war in Spain in July 1936, British Quakers were among the first t respond to the tremendous need for humanitarian aid among the civilian population. They distributed food and clothing, set up canteens and hospitals, provided schooling and workshops, and organized the evacuation of children from war zones. Then, in January 1939, when the Spanish Republic finally succumbed to the might of the rebel forces, the Quakers accompanied thousands of refugees in their flight towards the French border. This became known as ‘la retirada’ (the Retreat). Once in French territory, the refugees were herded into improvised internment camps. These were simply vast open spaces on the beaches encircled by barbed wire, with no shelter, no latrines and barely any food. Quakers were the first to obtain permits to access the camps in order to alleviate the suffering and deprivation found there. They distributed not only the most basic aid such as food and clothing, but also pencils and notebooks, as well as tools and materials of all kinds to work with. Thus, in characteristic fashion, they provided people with the means by which they could help themselves.
Excavating the Hall of Dreams: The Inventions of “Fine Art” and “Religion” in Japan
Authors: Storm Jason Ānanda Josephson
Published: April 2022

Setting out from Okakura Kakuzō and Ernest Fenollosa’s famous “discovery” of the Yumedono Kannon, this article will trace the contested construction of the categories of “religion” (shūkyō) and “fine art” (bijutsu) in Meiji Japan. In religious studies circles, it has become commonplace to think of “religion” as the only disciplinary master category with issues. However, not only was “religion” invented in Japan, but “fine art” was invented there too. Indeed, categories from “culture” to “society” to “politics” have similar issues. Attending to these will help refocus crucial debates away from an obsession with translation and onto more fundamental issues about “cultural categories” as such. This paper will advance the debate by explaining the attendant constructions of “religion” and “fine art” as process social kinds. In doing so, it will showcase the museum and the temple as central sites of materialized disputation over global categories and their local instantiation. It will show how assimilation to the world-system in the long nineteenth century was a complex multi-generational process of negotiation and contestation, producing new hybrid spaces, returns, transformations, and innovations that then reflected back on global systems, changing them in subtle but profound ways.
The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot
Authors: Duivon Askan , Kirsch Pino , Mauboussin Boris , Mougard Gabriel , Woszczyk Jakub , Sanfilippo Filippo
Published: April 2022

The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from a control standpoint, the accurate identification of push-points and reliable determination of feasible contact reaction forces are required. This is difficult to achieve with rigidly actuated robots because of the lack of compliance. As a possible solution to this challenge, our research group recently presented Serpens, a low-cost, open-source, and highly compliant multi-purpose modular snake robot with a series elastic actuator (SEA). In this paper, we propose a new prototyping iteration for our snake robot to achieve a more dependable design. The following three contributions are outlined in this work as a whole: the remodelling of the elastic joint with the addition of a damper element; a refreshed design for the screw-less assembly mechanism that can now withstand higher transverse forces; the re-design of the joint module with an improved reorganisation of the internal hardware components to facilitate heat dissipation and to accommodate a larger battery with easier access. The Robot Operating System (ROS) serves as the foundation for the software architecture. The possibility of applying machine learning approaches is considered. The results of preliminary simulations are provided.
A Remotely Sensed Framework for Spatially-Detailed Dryland Soil Organic Matter Mapping: Coupled Cross-Wavelet Transform with Fractional Vegetation and Soil-Related Endmember Time Series
Authors: Sun Qiangqiang , Zhang Ping , Jiao Xin , Lun Fei , Dong Shiwei , Lin Xin , Li Xiangyu , Sun Danfeng
Published: April 2022

Soil organic matter (SOM) plays pivotal roles in characterizing dryland structure and function; however, remotely sensed spatially-detailed SOM mapping in these regions remains a challenge. Various digital soil mapping approaches based on either single-period remote sensing or spectral indices in other ecosystems usually produce inaccurate, poorly constrained estimates of dryland SOM. Here, a framework for spatially-detailed SOM mapping was proposed based on cross-wavelet transform (XWT) that exploits ecologically meaningful features from intra-annual fractional vegetation and soil-related endmember records. In this framework, paired green vegetation (GV) and soil-related endmembers (i.e., dark surface (DA), saline land (SA), sand land (SL)) sequences were adopted to extract 30 XWT features in temporally and spatially continuous domains of cross-wavelet spectrum. We then selected representative features as exploratory covariates for SOM mapping, integrated with four state-of-the-art machine learning approaches, i.e., ridge regression (RR), least squares-support vector machines (LS-SVM), random forests (RF), and gradient boosted regression trees (GBRT). The results reported that SOM maps from 13 coupled filtered XWT features and four machine learning approaches were consistent with soil-landscape knowledge, as evidenced by a spatially-detailed gradient from oasis to barren. This framework also presented more accurate and reliable results than arithmetically averaged features of intra-annual endmembers and existing datasets. Among the four approaches, both RF and GBRT were more appropriate in the XWT-based framework, showing superior accuracy, robustness, and lower uncertainty. The XWT synthetically characterized soil fertility from the consecutive structure of intra-annual vegetation and soil-related endmember sequences. Therefore, the proposed framework improved the understanding of SOM and land degradation neutrality, potentially leading to more sustainable management of dryland systems.
Assessment of Ecosystem Services Supply and Demand (Mis)matches for Urban Ecological Management: A Case Study in the Zhengzhou–Kaifeng–Luoyang Cities
Authors: Xue Dong , Wang Zhaojun , Li Yuan , Liu Mengxue , Wei Hejie
Published: April 2022

Accurate supply and demand matching of ecosystem services (ESs) is important for managing regional ecosystems. On the basis of remote-sensing, meteorological, and socio-economic data, we mapped the supply, demand, and matching status of four ESs (i.e., water production, carbon sequestration, food supply, and soil conservation) using biophysical models and the ArcGIS spatial analysis module within the Zhengzhou–Kaifeng–Luoyang (ZKL) urban agglomeration in 2018. Four-quadrant analysis was employed to identify the spatial matching types of supply-demand relationships within the study region. The results are as follows. The supply-demand ratios of different ESs in the cell scale exhibit different spatial characteristics because of major influencing factors, including the natural environment (e.g., precipitation and temperature) and social development (e.g., urbanization level). Analysis of the supply-demand imbalances of the four ESs indicates that water production is deficient across the entire research area, whereas the whole research area’s carbon sequestration, food supply, and soil conversation are in the surplus state. Regarding the spatial matching types for supply and demand of the four ecosystem services, water production is dominated by the “low–low (low supply and low demand)” type. Carbon sequestration is dominated by the “low–low” and “high–low (high supply and low demand)” types. The “low–low” type dominates food supply and soil conservation. Due to the severity of the deficit in water production, all districts and counties in the ZKL urban agglomeration are identified as areas requiring ecological conservation, ecological restoration, or ecological improvement. Development guidance strategies and planning suggestions are proposed in different ecological areas. These policies could also be applied in other similar urban agglomerations.
Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation
Authors: Lopes Francis M. , Dutra Emanuel , Trigo Isabel F.
Published: April 2022

The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m−2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.
Modeling the CO2+ Ultraviolet Doublet Emission from Mars with a Multi-Instrument MAVEN Data Set
Authors: Li Zichuan , Niu Dandan , Gu Hao , Wu Xiaoshu , Huang Yingying , Zhong Jiahao , Cui Jun
Published: April 2022

With the aid of a multi-instrument data set gathered by the Mars Atmosphere and Volatile Evolution (MAVEN) during ten selected periods, we make detailed calculations of the CO2+ Ultraviolet Doublet (UVD) emission brightness profiles which are then compared to the Imaging Ultraviolet Spectrometer limb observations. Our calculations confirm that the photoionization of atmospheric CO2 is the predominant process driving CO2+ UVD emission at high altitudes, whereas the photoelectron impact ionization of CO2 becomes more important at low altitudes. The data–model comparisons show good agreement near and above the emission peak at around 120 km with an intensity of 27–45 kR. A special case is found for period 3 coincident with a regional dust storm during which the peak altitude rose by 20 km. Of particular interest is the significant discrepancy below the peak, which is likely associated with the uncertainties in either atmospheric density or incident solar irradiance. A detailed investigation suggests that the latter uncertainty is more likely responsible for such a discrepancy, in that the solar irradiance shortward of a wavelength threshold below 30 nm should be adjusted to achieve reasonable data–model agreement over the entire altitude range. This result highlights the necessity to improve the accuracy of any solar irradiance model used for planetary aeronomical studies.
On the Potential for Remote Observations of Coastal Morphodynamics from Surf-Cameras
Authors: Conlin Matthew , Adams Peter , Palmsten Margaret
Published: April 2022

Recreational surf-cameras (surfcams) are ubiquitous along many coastlines, and yet are a largely untapped source of coastal morphodynamic observations. Surfcams offer broad spatial coverage and flexibility in data collection, but a method to remotely acquire ground control points (GCPs) and initial camera parameter approximations is necessary to better leverage this existing infrastructure to make quantitative measurements. This study examines the efficacy of remotely monitoring coastal morphodynamics from surfcams at two sites on the Atlantic coast of Florida, U.S.A., by leveraging freely available airborne lidar observations to acquire remote-GCPs and open-source web tools for camera parameter approximations, ignoring lens distortion. Intrinsic and extrinsic camera parameters are determined using a modified space resection procedure, wherein parameters are determined using iterative adjustment while fitting to remote-GCPs and initial camera parameter approximations derived from justified assumptions and Google Earth. This procedure is completed using the open-source Surf-Camera Remote Calibration Tool (SurfRCaT). The results indicate root mean squared horizontal reprojection errors at the two cameras of 3.43 m and 6.48 m. Only immobile hard structures such as piers, jetties, and boulders are suitable as remote-GCPs, and the spatial distribution of available points is a likely reason for the higher accuracy at one camera relative to the other. Additionally, lens distortion is not considered in this work. This is another important source of error and including it in the methodology is highlighted as a useful avenue for future work. Additional factors, such as initial camera parameter approximation accuracy, likely play a role as well. This work illustrates that, provided there is sufficient remote-GCP availability and small lens distortion, remote video monitoring of coastal areas with existing surfcams could provide a usable source of coastal morphodynamic observations. This is further explored with a shoreline change analysis from the higher-accuracy camera. It was found that only the largest (>6 m) magnitude shoreline changes exceed the observational uncertainty driven by shoreline mapping error and reprojection error, indicating that remotely calibrated surfcams can provide observations of seasonal or storm-driven signals.
Improving the Forecasting of Winter Wheat Yields in Northern China with Machine Learning–Dynamical Hybrid Subseasonal-to-Seasonal Ensemble Prediction
Authors: Cao Junjun , Wang Huijing , Li Jinxiao , Tian Qun , Niyogi Dev
Published: April 2022

Subseasonal-to-seasonal (S2S) prediction of winter wheat yields is crucial for farmers and decision-makers to reduce yield losses and ensure food security. Recently, numerous researchers have utilized machine learning (ML) methods to predict crop yield, using observational climate variables and satellite data. Meanwhile, some studies also illustrated the potential of state-of-the-art dynamical atmospheric prediction in crop yield forecasting. However, the potential of coupling both methods has not been fully explored. Herein, we aimed to establish a skilled ML–dynamical hybrid model for crop yield forecasting (MHCF v1.0), which hybridizes ML and a global dynamical atmospheric prediction system, and applied it to northern China at the S2S time scale. In this study, we adopted three mainstream machining learning algorithms (XGBoost, RF, and SVR) and the multiple linear regression (MLR) model, and three major datasets, including satellite data from MOD13C1, observational climate data from CRU, and S2S atmospheric prediction data from IAP CAS, used to predict winter wheat yield from 2005 to 2014, at the grid level. We found that, among the four models examined in this work, XGBoost reached the highest skill with the S2S prediction as inputs, scoring R2 of 0.85 and RMSE of 0.78 t/ha 3–4 months, leading the winter wheat harvest. Moreover, the results demonstrated that crop yield forecasting with S2S dynamical predictions generally outperforms that with observational climate data. Our findings highlighted that the coupling of ML and S2S dynamical atmospheric prediction provided a useful tool for yield forecasting, which could guide agricultural practices, policy-making and agricultural insurance.
Identifying the Factors behind Climate Diversification and Refugial Capacity in Mountain Landscapes: The Key Role of Forests
Authors: Hoffrén Raúl , Miranda Héctor , Pizarro Manuel , Tejero Pablo , García María B.
Published: April 2022

Recent studies have shown the importance of small-scale climate diversification and climate microrefugia for organisms to escape or suffer less from the impact of current climate change. These situations are common in topographically complex terrains like mountains, where many climate-forcing factors vary at a fine spatial resolution. We investigated this effect in a high roughness area of a southern European range (the Pyrenees), with the aid of a network of miniaturized temperature and relative humidity sensors distributed across 2100 m of elevation difference. We modeled the minimum (Tn) and maximum (Tx) temperatures above- and below-ground, and maximum vapor pressure deficit (VPDmax), as a function of several topographic and vegetation variables derived from ALS-LiDAR data and Landsat series. Microclimatic models had a good fit, working better in soil than in air, and for Tn than for Tx. Topographic variables (including elevation) had a larger effect on above-ground Tn, and vegetation variables on Tx. Forest canopy had a significant effect not only on the spatial diversity of microclimatic metrics but also on their refugial capacity, either stabilizing thermal ranges or offsetting free-air extreme temperatures and VPDmax. Our integrative approach provided an overview of microclimatic differences between air and soil, forests and open areas, and highlighted the importance of preserving and managing forests to mitigate the impacts of climate change on biodiversity. Remote-sensing can provide essential tools to detect areas that accumulate different factors extensively promoting refugial capacity, which should be prioritized based on their high resilience.
The Maraichine Cattle Breed Supports Breeders and Researchers in the Atlantic Coastal Marshlands
Authors: Roche Bénédicte , Farruggia Anne , Pousin Marc , Riga Paul , Chataigner Claude , Boutifard Vincent , Prieur Michel , Roux Pierre , Cooke Andrew S. , Rivero M. Jordana
Published: April 2022

The Maraichine breed of cattle originates from the Loire region of France and has been under a conservation programme since 1986. This programme links the conservation of the breed with the conservation of its traditional environment of wet grasslands. In this case report, we describe the different steps of this programme, each of which had its own successes and challenges. We also describe how, throughout this process, researchers have been involved in the generation and dissemination of information covering areas such as stakeholder perspectives, animal performance, and socio-economics. Under the conservation programme, the Maraichine population has expanded in both size and scale. Simultaneously, stakeholder perspectives have also developed, continually shifting the balance between the productivity, conservation, and maintenance of heritage traits. The conservation programme also provided the opportunity to utilise the breed’s desirable traits, such as easy calving and disease resistance. Whilst the carcasses are not necessarily as valuable as those of other breeds, farmers have implemented novel economic practices to capitalise on market opportunities. Today, Maraichine cattle and Maraichine breeders offer researchers the opportunity to deepen and enrich our knowledge on sustainable ruminant livestock farming systems.
Machine Learning in Injection Molding: An Industry 4.0 Method of Quality Prediction
Authors: Párizs Richárd Dominik , Török Dániel , Ageyeva Tatyana , Kovács József Gábor
Published: April 2022

One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging. Machine learning (ML) algorithms can be the solution, as they work in multidimensional spaces by learning the structure of datasets. In this study, we used four ML algorithms (kNN, naïve Bayes, linear discriminant analysis, and decision tree) and compared their effectiveness in predicting the quality of multi-cavity injection molding. We used pressure-based quality indexes (features) as inputs for the classification algorithms. We proved that all the examined ML algorithms adequately predict quality in injection molding even with very little training data. We found that the decision tree algorithm was the most accurate one, with a computational time of only 8–10 s. The average performance of the decision tree algorithm exceeded 90%, even for very little training data. We also demonstrated that feature selection does not significantly affect the accuracy of the decision tree algorithm.
Nanoporous Cauliflower-like Pd-Loaded Functionalized Carbon Nanotubes as an Enzyme-Free Electrocatalyst for Glucose Sensing at Neutral pH: Mechanism Study
Authors: Ghanam Abdelghani , Haddour Naoufel , Mohammadi Hasna , Amine Aziz , Sabac Andrei , Buret François
Published: April 2022

In this work, we propose a novel functionalized carbon nanotube (f-CNT) supporting nanoporous cauliflower-like Pd nanostructures (PdNS) as an enzyme-free interface for glucose electrooxidation reaction (GOR) in a neutral medium (pH 7.4). The novelty resides in preparing the PdNS/f-CNT biomimetic nanocatalyst using a cost-effective and straightforward method, which consists of drop-casting well-dispersed f-CNTs over the Screen-printed carbon electrode (SPCE) surface, followed by the electrodeposition of PdNS. Several parameters affecting the morphology, structure, and catalytic properties toward the GOR of the PdNS catalyst, such as the PdCl2 precursor concentration and electrodeposition conditions, were investigated during this work. The electrochemical behavior of the PdNS/f-CNT/SPCE toward GOR was investigated through Cyclic Voltammetry (CV), Linear Sweep Voltammetry (LSV), and amperometry. There was also a good correlation between the morphology, structure, and electrocatalytic activity of the PdNS electrocatalyst. Furthermore, the LSV response and potential-pH diagram for the palladium–water system have enabled the proposal for a mechanism of this GOR. The proposed mechanism would be beneficial, as the basis, to achieve the highest catalytic activity by selecting the suitable potential range. Under the optimal conditions, the PdNS/f-CNT/SPCE-based biomimetic sensor presented a wide linear range (1–41 mM) with a sensitivity of 9.3 µA cm−2 mM−1 and a detection limit of 95 µM (S/N = 3) toward glucose at a detection potential of +300 mV vs. a saturated calomel electrode. Furthermore, because of the fascinating features such as fast response, low cost, reusability, and poison-free characteristics, the as-proposed electrocatalyst could be of great interest in both detection systems (glucose sensors) and direct glucose fuel cells.
Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery
Authors: Li Xiuhua , Ba Yuxuan , Zhang Muqing , Nong Mengling , Yang Ce , Zhang Shimin
Published: April 2022

Sugarcane is the main industrial crop for sugar production, and its growth status is closely related to fertilizer, water, and light input. Unmanned aerial vehicle (UAV)-based multispectral imagery is widely used for high-throughput phenotyping, since it can rapidly predict crop vigor at field scale. This study focused on the potential of drone multispectral images in predicting canopy nitrogen concentration (CNC) and irrigation levels for sugarcane. An experiment was carried out in a sugarcane field with three irrigation levels and five fertilizer levels. Multispectral images at an altitude of 40 m were acquired during the elongating stage. Partial least square (PLS), backpropagation neural network (BPNN), and extreme learning machine (ELM) were adopted to establish CNC prediction models based on various combinations of band reflectance and vegetation indices. The simple ratio pigment index (SRPI), normalized pigment chlorophyll index (NPCI), and normalized green-blue difference index (NGBDI) were selected as model inputs due to their higher grey relational degree with the CNC and lower correlation between one another. The PLS model based on the five-band reflectance and the three vegetation indices achieved the best accuracy (Rv = 0.79, RMSEv = 0.11). Support vector machine (SVM) and BPNN were then used to classify the irrigation levels based on five spectral features which had high correlations with irrigation levels. SVM reached a higher accuracy of 80.6%. The results of this study demonstrated that high resolution multispectral images could provide effective information for CNC prediction and water irrigation level recognition for sugarcane crop.
Ship Segmentation and Georeferencing from Static Oblique View Images
Authors: Carrillo-Perez Borja , Barnes Sarah , Stephan Maurice
Published: April 2022

Camera systems support the rapid assessment of ship traffic at ports, allowing for a better perspective of the maritime situation. However, optimal ship monitoring requires a level of automation that allows personnel to keep track of relevant variables in the maritime situation in an understandable and visualisable format. It therefore becomes important to have real-time recognition of ships present at the infrastructure, with their class and geographic position presented to the maritime situational awareness operator. This work presents a novel dataset, ShipSG, for the segmentation and georeferencing of ships in maritime monitoring scenes with a static oblique view. Moreover, an exploration of four instance segmentation methods, with a focus on robust (Mask-RCNN, DetectoRS) and real-time performances (YOLACT, Centermask-Lite) and their generalisation to other existing maritime datasets, is shown. Lastly, a method for georeferencing ship masks is proposed. This includes an automatic calculation of the pixel of the segmented ship to be georeferenced and the use of a homography to transform this pixel to geographic coordinates. DetectoRS provided the highest ship segmentation mAP of 0.747. The fastest segmentation method was Centermask-Lite, with 40.96 FPS. The accuracy of our georeferencing method was (22 ± 10) m for ships detected within a 400 m range, and (53 ± 24) m for ships over 400 m away from the camera.
A Systematic Review of Industrial Exoskeletons for Injury Prevention: Efficacy Evaluation Metrics, Target Tasks, and Supported Body Postures
Authors: Golabchi Ali , Chao Andrew , Tavakoli Mahdi
Published: April 2022

Industrial workplaces expose workers to a high risk of injuries such as Work-related Musculoskeletal Disorders (WMSDs). Exoskeletons are wearable robotic technologies that can be used to reduce the loads exerted on the body’s joints and reduce the occurrence of WMSDs. However, current studies show that the deployment of industrial exoskeletons is still limited, and widespread adoption depends on different factors, including efficacy evaluation metrics, target tasks, and supported body postures. Given that exoskeletons are not yet adopted to their full potential, we propose a review based on these three evaluation dimensions that guides researchers and practitioners in properly evaluating and selecting exoskeletons and using them effectively in workplaces. Specifically, evaluating an exoskeleton needs to incorporate: (1) efficacy evaluation metrics based on both subjective (e.g., user perception) and objective (e.g., physiological measurements from sensors) measures, (2) target tasks (e.g., manual material handling and the use of tools), and (3) the body postures adopted (e.g., squatting and stooping). This framework is meant to guide the implementation and assessment of exoskeletons and provide recommendations addressing potential challenges in the adoption of industrial exoskeletons. The ultimate goal is to use the framework to enhance the acceptance and adoption of exoskeletons and to minimize future WMSDs in industrial workplaces.
A Localized Transient-Based Fault Location Scheme for Distribution Systems
Authors: Bayati Navid , Mortensen Lasse Kappel , Savaghebi Mehdi , Shaker Hamid Reza
Published: April 2022

Many distribution systems have several branches with only one protection system at the upstream system. This characteristic degrades the performance of traditional fault location schemes. In this paper, a localized fault location method based on the transient behavior of fault currents by using local data is proposed. The proposed scheme uses only local current and the voltage of the upstream overcurrent relay as input data of the fault location scheme. The formulation considers fault resistance, loads, and different fault locations. Furthermore, due to the usage of transient fault current data, the proposed method locates the fault within several milliseconds with a suitable range of error. To validate the effectiveness of this method, field measurement data, obtained from a real distribution system in East Jutland, Denmark operated by Dinel A/S, are used, and extensive real-time simulations are performed. The results prove that the proposed method locates different types of faults within an appropriate time and error, which can improve the maintenance and reliability of distribution systems.
Augmented Reality for Human–Robot Collaboration and Cooperation in Industrial Applications: A Systematic Literature Review
Authors: Costa Gabriel de Moura , Petry Marcelo Roberto , Moreira António Paulo
Published: April 2022

With the continuously growing usage of collaborative robots in industry, the need for achieving a seamless human–robot interaction has also increased, considering that it is a key factor towards reaching a more flexible, effective, and efficient production line. As a prominent and prospective tool to support the human operator to understand and interact with robots, Augmented Reality (AR) has been employed in numerous human–robot collaborative and cooperative industrial applications. Therefore, this systematic literature review critically appraises 32 papers’ published between 2016 and 2021 to identify the main employed AR technologies, outline the current state of the art of augmented reality for human–robot collaboration and cooperation, and point out future developments for this research field. Results suggest that this is still an expanding research field, especially with the advent of recent advancements regarding head-mounted displays (HMDs). Moreover, projector-based and HMDs developed approaches are showing promising positive influences over operator-related aspects such as performance, task awareness, and safety feeling, even though HMDs need further maturation in ergonomic aspects. Further research should focus on large-scale assessment of the proposed solutions in industrial environments, involving the solution’s target audience, and on establishing standards and guidelines for developing AR assistance systems.
Selective Detection of Liquid Viscosity Using Acoustic Plate Waves with In-Plane Polarization
Authors: Anisimkin Vladimir , Shamsutdinova Elizaveta , Li Peng , Wang Bin , Zhu Feng , Qian Zhenghua , Kuznetsova Iren
Published: April 2022

Using plates of weak piezoeletcric crystal (quartz) loaded with various liquids, it is shown that along with common modes, whose sensitivity towards different liquid parameters comparable with each other, there are some uncommon modes, whose amplitude responses towards viscosity η are much larger than towards temperature T and electric conductivity σ. The search of the modes with the selective properties is accomplished by varying plate thickness h, crystal orientation, wave length λ, and mode order n. It is found that all modes possessing the property are characterized by small surface-normal displacement, avoiding wave radiation into adjacent liquid, large in-plane displacements, enhancing viscous coupling the modes and liquids, and small electro-mechanical constant, reducing electro-acoustic interaction. Basing on the modes, the sensor prototypes with selective operation are developed and tested for η from 1 to 1500 cP, σ from 0 to 1.2 S/m, and t from 0 to 55 °C. Because of operation at ultrasonic frequency (tens MHz) the prototypes have different sensitivities in various η-ranges: 0.3 dB/cP for 1–20 cP, 0.12 dB/cP for 20–100 cP, and 0.015 dB/cP for 100–1500 cP. Viscosity responses of the prototypes become comparable with their electric outputs only for η < 2 cP. Temperature responses are almost zero in air, but when plate is coated with liquid they increase depending on liquid properties, allowing measurements of the temperature dependence of the liquid viscosity.