bluuebunny/crossref_metadata_2025 huggingface dataset:
A Nano-Cleaning Fluid for Downhole Casing Cleaning
Authors: Song Hanxuan , Ye Yan , Zhang Zhen , Wang Shuang , Zhou Tong , Guo Jixiang , Zhang Shiling
Published: March 2023

In drilling and completion projects, sludge is formed as a byproduct when barite and oil are mixed, and later sticks to the casing. This phenomenon has caused a delay in drilling progress, and increased exploration and development costs. Since nano-emulsions have low interfacial surface tension, wetting, and reversal capabilities, this study used nano-emulsions with a particle size of about 14 nm to prepare a cleaning fluid system. This system enhances stability through the network structure in the fiber-reinforced system, and prepares a set of nano-cleaning fluids with adjustable density for ultra-deep wells. The effective viscosity of the nano-cleaning fluid reaches 11 mPa·s, and the system is stable for up to 8 h. In addition, this research independently developed an indoor evaluation instrument. Based on on-site parameters, the performance of the nano-cleaning fluid was evaluated from multiple angles by heating to 150 °C and pressurizing to 3.0 Mpa to simulate downhole temperature and pressure. The evaluation results show that the viscosity and shear value of the nano-cleaning fluid system is greatly affected by the fiber content, and the cleaning efficiency is greatly affected by the concentration of the nano-emulsion. Curve fitting shows that the average processing efficiency could reach 60–85% within 25 min and the cleaning efficiency has a linear relationship with time. The cleaning efficiency has a linear relationship with time, where R2 = 0.98335. The nano-cleaning fluid enables the deconstruction and carrying of the sludge attached to the well wall, which accomplishes the purpose of downhole cleaning.
Nanostructured Conducting Polymers and Their Applications in Energy Storage Devices
Authors: del Valle M. A. , Gacitúa M. A. , Hernández F. , Luengo M. , Hernández L. A.
Published: March 2023

Due to the energy requirements for various human activities, and the need for a substantial change in the energy matrix, it is important to research and design new materials that allow the availability of appropriate technologies. In this sense, together with proposals that advocate a reduction in the conversion, storage, and feeding of clean energies, such as fuel cells and electrochemical capacitors energy consumption, there is an approach that is based on the development of better applications for and batteries. An alternative to commonly used inorganic materials is conducting polymers (CP). Strategies based on the formation of composite materials and nanostructures allow outstanding performances in electrochemical energy storage devices such as those mentioned. Particularly, the nanostructuring of CP stands out because, in the last two decades, there has been an important evolution in the design of various types of nanostructures, with a strong focus on their synergistic combination with other types of materials. This bibliographic compilation reviews state of the art in this area, with a special focus on how nanostructured CP would contribute to the search for new materials for the development of energy storage devices, based mainly on the morphology they present and on their versatility to be combined with other materials, which allows notable improvements in aspects such as reduction in ionic diffusion trajectories and electronic transport, optimization of spaces for ion penetration, a greater number of electrochemically active sites and better stability in charge/discharge cycles.
Physicochemical Characterization, Biocompatibility, and Antibacterial Properties of CMC/PVA/Calendula officinalis Films for Biomedical Applications
Authors: Huang Wen-Hsin , Hung Chia-Yi , Chiang Pao-Chang , Lee Hsiang , Lin I-Ting , Lai Pin-Chuang , Chan Ya-Hui , Feng Sheng-Wei
Published: March 2023

This study reports a carboxymethyl cellulose (CMC)/polyvinyl alcohol (PVA) composite film that incorporates Calendula officinalis (CO) extract for biomedical applications. The morphological, physical, mechanical, hydrophilic, biological, and antibacterial properties of CMC/PVA composite films with various CO concentrations (0.1%, 1%, 2.5%, 4%, and 5%) are fully investigated using different experiments. The surface morphology and structure of the composite films are significantly affected by higher CO concentrations. X-ray diffraction (XRD) and Fourier transform infrared spectrometry (FTIR) analyses confirm the structural interactions among CMC, PVA, and CO. After CO is incorporated, the tensile strength and elongation upon the breaking of the films decrease significantly. The addition of CO significantly reduces the ultimate tensile strength of the composite films from 42.8 to 13.2 MPa. Furthermore, by increasing the concentration of CO to 0.75%, the contact angle is decreased from 15.8° to 10.9°. The MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] assay reveals that the CMC/PVA/CO-2.5% and CMC/PVA/CO-4% composite films are non-cytotoxic to human skin fibroblast cells, which is favorable for cell proliferation. Remarkably, 2.5% and 4% CO incorporation significantly improve the inhibition ability of the CMC/PVA composite films against Staphylococcus aureus and Escherichia coli. In summary, CMC/PVA composite films containing 2.5% CO exhibit the functional properties for wound healing and biomedical engineering applications.
Chemical and Mechanical Characterization of Unprecedented Transparent Epoxy–Nanomica Composites—New Model Insights for Mechanical Properties
Authors: Ongaro Greta , Pontefisso Alessandro , Zeni Elena , Lanero Francesco , Famengo Alessia , Zorzi Federico , Zaccariotto Mirco , Galvanetto Ugo , Fiorentin Pietro , Gobbo Renato , Bertani Roberta , Sgarbossa Paolo
Published: March 2023

Two nanomicas of similar composition, containing muscovite and quartz, but with different particle size distributions, have been used to prepare transparent epoxy nanocomposites. Their homogeneous dispersion, due to the nano-size, was achieved even without being organically modified, and no aggregation of the nanoparticles was observed, thus maximizing the specific interface between matrix and nanofiller. No exfoliation or intercalation has been observed by XRD, despite the significant dispersion of the filler in the matrix which produced nanocomposites with a loss in transparency in the visible domain of less than 10% in the presence of 1% wt and 3% wt of mica fillers. The presence of micas does not affect the thermal behavior of the nanocomposites, which remains similar to that of the neat epoxy resin. The mechanical characterization of the epoxy resin composites revealed an increased Young’s modulus, whereas tensile strength was reduced. A peridynamics-based representative volume element approach has been implemented to estimate the effective Young’s modulus of the nanomodified materials. The results obtained through this homogenization procedure have been used as input for the analysis of the nanocomposite fracture toughness, which has been carried out by a classical continuum mechanics–peridynamics coupling approach. Comparison with the experimental data confirms the capability of the peridynamics-based strategies to properly model the effective Young’s modulus and fracture toughness of epoxy-resin nanocomposites. Finally, the new mica-based composites exhibit high values of volume resistivity, thus being excellent candidates as insulating materials.
Life Cycle Assessment of Functionalized Bionanocompounds with Ice Nucleation Protein for Freezing Applications
Authors: Fuentes Olga P. , Osma Johann F.
Published: March 2023

The objective of this study was to assess the effectiveness of functionalized bionanocompounds with ice nucleation protein (INP) as a novel approach for freezing applications in terms of how much energy is used during each step of freezing when water bionanocompound solutions were compared with pure water. According to the results of the manufacturing analysis, water required 28 times less energy than the silica + INA bionanocompound and 14 times less than the magnetite + INA bionanocompound. These findings showed that water used the least energy during the manufacturing process. In order to determine the associated environmental implications, an analysis of the operating stage was also conducted, taking the defrosting time of each bionanocompound during a 4 h work cycle into account. Our results showed that bionanocompounds may substantially reduce the environmental effects by achieving a 91% reduction in the impact after their use during all four work cycles in the operation stage. Additionally, given the energy and raw materials needed in this process, this improvement was more significant than at the manufacturing stage. The results from both stages indicated that, when compared with water, the magnetite + INA bionanocompound and the silica + INA bionanocompound would save an estimated 7% and 47% of total energy, respectively. The study’s findings also demonstrated the great potential for using bionanocompounds in freezing applications to reduce the effects on the environment and human health.
Electrochemically Stable Rechargeable Lithium–Sulfur Batteries Equipped with an Electrospun Polyacrylonitrile Nanofiber Film
Authors: Chiu Li-Ling , Chung Sheng-Heng
Published: March 2023

The high theoretical charge-storage capacity and energy density of lithium–sulfur batteries make them a promising next-generation energy-storage system. However, liquid polysulfides are highly soluble in the electrolytes used in lithium–sulfur batteries, which results in irreversible loss of their active materials and rapid capacity degradation. In this study, we adopt the widely applied electrospinning method to fabricate an electrospun polyacrylonitrile film containing non-nanoporous fibers bearing continuous electrolyte tunnels and demonstrate that this serves as an effective separator in lithium–sulfur batteries. This polyacrylonitrile film exhibits high mechanical strength and supports a stable lithium stripping and plating reaction that persists for 1000 h, thereby protecting a lithium-metal electrode. The polyacrylonitrile film also enables a polysulfide cathode to attain high sulfur loadings (4–16 mg cm−2) and superior performance from C/20 to 1C with a long cycle life (200 cycles). The high reaction capability and stability of the polysulfide cathode result from the high polysulfide retention and smooth lithium-ion diffusion of the polyacrylonitrile film, which endows the lithium–sulfur cells with high areal capacities (7.0–8.6 mA·h cm−2) and energy densities (14.7–18.1 mW·h cm−2).
MCDM Model for Evaluating and Selecting the Optimal Facility Layout Design: A Case Study on Railcar Manufacturing
Authors: Nenzhelele Tshifhiwa , Trimble John Alfred , Swanepoel Jan Andriaan , Kanakana-Katumba Mukondeleli Grace
Published: March 2023

Facility layout in a manufacturing system is a complex production activity because decisions on layout design are influenced by numerous, ambiguous, and competing factors. This study proposes a method for determining and choosing an ideal layout using a hybridized Fuzzy Analytic Hierarchy Process (F-AHP) with the Fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (F-TOPSIS). The F-AHP is used, in this case, because of its ability to generate design criteria weight. The railcar industrial case study results indicate that the developed model can effectively lead to selection of the most suitable facility layout design. The Discrete Event Simulation model is used to evaluate the performance of the suggested layout concepts with the purpose of determining quantitative criteria for use when selecting the most optimal concept by the proposed Fuzzy AHP-TOPSIS model. The proposed methodology demonstrated that a framework is a logical way to solve problems. The proposed Fuzzy AHP-TOPSIS methodology is capable of selecting the best layout concept based on the set decision criteria. Layout concept three was the best in terms of the closeness coefficient, which was more than 0.9 for both batching and non-batching processing.
Authentication of Coffee Blends by 16-O-Methylcafestol Quantification Using NMR Spectroscopy
Authors: Lin Ya-Tze , We You-Lun , Kao Ya-Min , Tseng Su-Hsiang , Wang Der-Yuan , Chen Shin-Yu
Published: March 2023

In 2019, a coffee chain in Taiwan was found to be mixing relatively cheap Robusta beans into products marketed as 100% Arabica. Many studies show 16-OMC is a remarkable marker to distinguish Robusta from Arabica beans, and nuclear magnetic resonance (NMR) is a convenient and efficient technique for 16-OMC quantification. Here, a 500 MHz NMR was employed to determine the content of 16-OMC in coffee for adulterate evaluation. A total of 118 samples were analyzed including products from the coffee chain, raw materials (single coffee beans), and other commercial products. The contents of 16-OMC in single Robusta beans were between 1005.55 and 3208.32 mg/kg and were absent from single Arabica beans. The surveillance results indicate that 17 out of 47 blend products claiming to contain 100% Arabica had 16-OMC quantifications in the range of 155.74–784.60 mg/kg. Furthermore, all 17 products were produced by the same coffee chain. We confirmed that coffee chain adulterated Arabica with Robusta in parts of their products, which claimed to include 100% Arabica. Moreover, this work highlights the free form of 16-OMC was esterified by coffee instantly. The decomposition products of 16-OMC were observed obviously in green Robusta while the mechanisms remain unclear. Future research should focus more on these aspects to further increase our understanding of these mechanisms.
A Critical Evaluation of Recent Studies on Packed-Bed Bioreactors for Solid-State Fermentation
Authors: Mitchell David Alexander , Ruiz Héctor A. , Krieger Nadia
Published: March 2023

Packed-bed bioreactors are often used for aerobic solid-state fermentation, since the forced aeration supplies O2 and removes metabolic heat from the bed. Motivated by the potential for applications in biorefineries, we review studies conducted on packed-bed bioreactors over the last decade, evaluating the insights these studies provide into how large-scale packed beds should be designed and operated. Many studies have used low superficial air velocities and suffer from preferential airflow, such that parts of the bed are not properly aerated. Moreover, some studies have proposed ineffective strategies, such as reversing the direction of the airflow or introducing air through perforated pipes within the bed. Additionally, many studies have used narrow water-jacketed packed-bed bioreactors, but these bioreactors do not reflect heat removal in wide large-scale packed beds, in which heat removal through the side walls makes a minor contribution. Finally, we conclude that, although some attention has been given to characterizing the porosities, water sorption isotherms and volumetric heat and mass transfer coefficients of substrate beds, this work needs to be extended to cover a wider range of solid substrates, and work needs to be done to characterize how these bed properties change due to microbial growth.
Characterization of a Gliding Arc Igniter from an Equilibrium Stage to a Non–Equilibrium Stage Using a Coupled 3D–0D Approach
Authors: Li Zhenyang , Zhu Yifei , Pan Di , Cheng Xinyao
Published: March 2023

A gliding arc plasma source designed for high efficient ignition has been studied with the help of numerical simulation and experiments. A coupled 3D–0D approach has been proposed to model the gliding arc from ignition (the equilibrium stage) to extinguish (the non–equilibrium stage). The model takes the measured discharge morphology, voltage, current, and velocity as inputs, and has been validated by comparing the calculated temperature with experimental results from an independent group. The temporal evolution of the temperature as well as active species, and the effective penetration length of the gliding arc has been studied; the influence of the gliding arc-based plasma igniter on the ignition delay time of a premixed pentane-air gas has also been theoretically analyzed.
Kinetic Aspects of Suzuki Cross-Coupling Using Ligandless Pd Nanoparticles Embedded in Aromatic Polymeric Matrix
Authors: Sapunov Valentin N. , Nikoshvili Linda Z. , Bakhvalova Elena S. , Sulman Mikhail G. , Matveeva Valentina G.
Published: March 2023

During the last decades, palladium nanoparticles (Pd(0) NPs) and Pd(II) compounds were shown to be attractive catalysts for fine organic synthesis. Nanostructured Pd(0) or Pd(II) catalysts have a relatively low environmental impact, but, at the same time, they are indispensable for such processes as Suzuki cross-coupling. This paper describes the preparation of Pd(0) or Pd(II) supported/embedded in hyper-cross-linked polystyrene (HPS) and compares their activity in Suzuki cross-coupling between phenylboronic acid and 4-bromoanisole. Obviously, the palladium charge (Pd(0) ↔ Pd(II)) changes continuously during the reaction catalytic cycle. It would seem that the use of the starting palladium in the form of Pd(0) or Pd(II) should not affect the reaction’s kinetic laws for both catalysts, but their special individuality is manifested between them. Nanoparticulate Pd(0) catalysts are stable during the reaction. In contrast, catalysts based on Pd(II) are extremely active in the initial period of the reaction, but then the “hot form” of the catalyst is rapidly converted into the form of Pd(0), whose activity is identical to that of the preliminarily reduced catalyst. This work discusses the possible nature of this phenomenon. A mathematical model for Suzuki cross-coupling reaction was suggested that was able to adequately describe experimental data. The level of reliability (R2) of the correlation between the experimental and calculated data was R2 = 0.97–0.99.
Isolation, Structural Elucidation, In Vitro Anti-α-Glucosidase, Anti-β-Secretase, and In Silico Studies of Bioactive Compound Isolated from Syzygium cumini L.
Authors: Mujawah Adil , Rauf Abdur , Bawazeer Sami , Wadood Abdul , Hemeg Hassan A. , Bawazeer Saud
Published: March 2023

Diabetes is one of the main health issues worldwide because of its lifetime duration. To overcome this health problem, the current study was conducted. This investigation aims to explore the α-glucosidase and β-secretase potential of extract/fractions and pure isolated compounds of Syzygium cumini bark. The chloroform extract of Syzygium cumini bark was subjected to chromatographic analysis to yield compound 1. The structure of isolated phytochemical (1) was conducted using advanced spectroscopic analysis. Among test extracts, the chloroform fraction exhibited a significant effect against α-glucosidase with a % activity of 86.20% and an IC50 of 77.09 µM, while the isolated compound exhibited a promising effect with a % activity of 91.54 and an IC50 value of 17.54 μM. The extract/fractions and isolated compound 1 also showed promising effects against the β-secretase enzyme, having % effects of 83.21 and 91.54% with IC50 values of 318.76 and 17.54 μM, respectively. The extract/fractions and compound 1 were found to possess promising inhibitory activity against α-glucosidase and β-secretase. This research project opens a new avenue for research into detailed chemical and biological studies on Syzygium cumini to isolate bioactive enzyme inhibitors. Furthermore, the isolated compound 1 friedelin was docked into the active site of β-secretase and α-glucosidase. The molecular docking was assessed using molecular docking via the MOE-Dock tool. The docking results showed good docking scores of −6.84 and −6.46 when docked against β-secretase and α-glucosidase, respectively, and strong interactions.
An App-Based Recommender System Based on Contrasting Automobiles
Authors: Liu Hsiu-Wen , Wu Jei-Zheng , Wu Fang-Lin
Published: March 2023

Product recommendation systems are essential for enhancing customer experience, and integrating them with mobile apps is crucial for improving usability and fostering user engagement. This study proposes a hybrid approach that utilizes comparative facts from pairwise comparison data and comparison lists, with association rules as the method to formulate the recommendation system. The study employs a dataset from the New-Cars Database app, comprising 30,867 vehicle comparisons made by 5327 users across 40 car brands and 870 cars from 30 January 2015 to 2 April 2015. Two metrics are developed to measure the system’s output under varying support and confidence thresholds. The findings suggest that adjusting the support and confidence values can improve the breadth and depth of product recommendations. In addition, the unit of analysis can affect the recommendation system’s output, with comparison lists supplementing and expanding the exploration of potential outcomes. The proposed hybrid approach aims to provide more reliable and comprehensive product recommendations by combining both approaches and has implications for both academic and managerial contexts by facilitating the development of effective recommendation systems.
Optimization and Intensification of Bioactive Components and Antioxidant Activity of Extracts from Date Fruit (Phoenix dactylifera L.) Using Pulsed Electric Fields (PEF) Technology and Thermal Processing
Authors: Souli Ikbel , Chaira Nizar , Jemni Monia , Tlahig Samir , Ferchichi Ali , Lanoisellé Jean-Louis
Published: March 2023

The objective of this study was to assess the impact of pulsed electric field (PEF) treatment on the extraction of polyphenolics and antioxidant activity from downgraded date palm fruits. The PEF pretreatments (frequency: 30 Hz, time: 50 μs, pulse number: 240, the electric field strengths were found to be 1, 2, and 2.5 kV.cm−1, and methanol (50%) and temperatures (20, 40, 50 °C)) were optimized and applied before extraction to produce an extract of date fruits with a high content of bioactive compounds. The extracts obtained immediately after pretreatments were analyzed for total polyphenolic content, antioxidant activity, and phenolic profiles. The results revealed that the PEF-assisted extracts at 2.5 kV.cm−1 at T50 °C exhibited higher polyphenol content (+27%) and antioxidant activity (+31%) and notably improved phenolic profiles compared to untreated extracts. PEF treatment processing significantly enhanced the bioactive components and antioxidant activities of date fruits over time, regardless of the treatment applied and the extraction’s temperature. Hence, the application of PEF combined with thermal processing can be an appropriate alternative treatment for a better extractability of bioactive compounds from fruit of dates and food byproducts. These biomolecules could be consumed as new food technology, incorporated as food additives, and nutraceuticals products.
Religiosity and Misanthropy across the Racial and Ethnic Divide
Authors: Valente Rubia R. , Smith Ryan A.
Published: March 2023

The systematic study of misanthropy, the lack of trust in humanity, has proliferated over the last 30 years. One prominent line of research details racial and ethnic disparities in levels of misanthropy, but pays little attention to the role of religiosity, while another focuses attention on religiosity and its impact on levels of misanthropy, with only scant attention to the role of race and ethnicity. Little attempt has been made to synthesize these two strands of literature to address an important unanswered question: Does the association between religiosity and misanthropy vary by racial and ethnic group? To answer this question, we pooled data from the General Social Survey (GSS, 2000–2018). Among other things, we find stark racial differences between Blacks and Whites in terms of the effect of religiosity on misanthropy. Blacks and Latinos who attend religious services weekly (social religiosity) have significantly higher levels of misanthropy than others, while Whites who attend weekly services are less likely to be misanthropic. An important takeaway is that service attendance (a type of social capital) is associated with feelings of misanthropy for all groups (albeit in opposite directions for Blacks and Latinos versus Whites), rather than personal acts of prayer (individual religiosity). When it comes to misanthropy, we conclude that religion works differently for minorities compared with Whites. We discuss the implications of our findings for future research.
Turks versus the West: Civilizational Populism in Turkey’s Ruling Coalition
Authors: Bacik Gokhan , Seker Serkan
Published: March 2023

Civilizational populism is readily observable in Turkish politics. This study analyzes how the ruling political parties in Turkey (Islamist JDP and ultra-nationalist NAP) reframe extant civilizational ideas into a populist format to reproduce civilizational populism for ideological and pragmatic reasons. The research implements a two-level analysis of civilizational populism. On the first level, the article reveals the intellectual origins of the ideas on civilizations. On the second level, it analyses how these ideas are used by political actors in constructing populist civilizational discourse in daily politics. This methodological approach to civilizational populism shows that politicians use old ideas that are well-known by their supporters while framing them as their populist narrative. Thus, civilizational populism occurs in Turkey as a continuity. This study finds out that (i) Civilizational populism is a salient phenomenon proving how Islam and nationalism are socially and politically coded as friendly categories in Turkey; (ii) Political actors are the agents of populism but not the inventors of the many ideas they instrumentalize; (iii) Civilizational populism in Turkey is constructed on an anti-Western narrative which is essentialist and culturalist. Consequently, the article reveals that the culturist and essentialist critique levelled by other civilizations at Western political actors can be levelled similarly at the Muslim political elite.
Energy Efficiency of a Wheeled Bio-Inspired Hexapod Walking Robot in Sloping Terrain
Authors: Žák Marek , Rozman Jaroslav , Zbořil František V.
Published: March 2023

Multi-legged robots, such as hexapods, have great potential to navigate challenging terrain. However, their design and control are usually much more complex and energy-demanding compared to wheeled robots. This paper presents a wheeled six-legged robot with five degrees of freedom, that is able to move on a flat surface using wheels and switch to gait in rugged terrain, which reduces energy consumption. The novel joint configuration mimics the structure of insect limbs and allows our robot to overcome difficult terrain. The wheels reduce energy consumption when moving on flat terrain and the trochanter joint reduces energy consumption when moving on slopes, extending the operating time and range of the robot. The results of experiments on sloping terrain are presented. It was confirmed that the use of the trochanter joint can lead to a reduction in energy consumption when moving in sloping terrain.
G-reqs, a New Model Proposal for Capturing and Managing In Situ Data Requirements: First Results in the Context of the Group on Earth Observations
Authors: Maso Joan , Brobia Alba , Voidrot Marie-Francoise , Zabala Alaitz , Serral Ivette
Published: March 2023

In the field of Earth observation, the importance of in situ data was recognized by the Group on Earth Observations (GEO) in the Canberra Declaration in 2019. The GEO community focuses on three global priority engagement areas: the United Nations 2030 Agenda for Sustainable Development, the Paris Agreement, and the Sendai Framework for Disaster Risk Reduction. While efforts have been made by GEO to open and disseminate in situ data, GEO did not have a general way to capture in situ data user requirements and drive the data provider efforts to meet the goals of its three global priorities. We present a requirements data model that first formalizes the collection of user requirements motivated by user-driven needs. Then, the user requirements can be grouped by essential variable and an analysis can derive product requirements and parameters for new or existing products. The work was inspired by thematic initiatives, such as OSCAR, from WMO, OSAAP (formerly COURL and NOSA) from NOAA, and the Copernicus In Situ Component Information System. The presented solution focuses on requirements for all applications of Earth observation in situ data. We present initial developments and testing of the data model and discuss the steps that GEO should take to implement a requirements database that is connected to actual data in the GEOSS platform and propose some recommendations on how to articulate it.
Remote 3D Displacement Sensing for Large Structures with Stereo Digital Image Correlation
Authors: Feng Weiwu , Li Qiang , Du Wenxue , Zhang Dongsheng
Published: March 2023

The work performance of stereo digital image correlation (stereo-DIC) technologies, especially the operating accuracy and reliability in field applications, is not fully understood. In this study, the key technologies of the field remote 3D displacement sensing of civil structures based on stereo-DIC have been proposed. An image correlation algorithm is incorporated in improving the matching accuracy of control points. An adaptive stereo-DIC extrinsic parameter calibration method is developed by fusing epipolar-geometry-based and homography-based methods. Furthermore, a reliable reference frame that does not require artificial markers is established based on Euclidean transformation, which facilitates in-plane and out-of-plane displacement monitoring for civil structures. Moreover, a camera motion correction is introduced by considering background points according to the camera motion model. With an experiment, the feasibility and accuracy of the proposed system are validated. Moreover, the system is applied to sense the dynamic operating displacement of a 2 MW wind turbine’s blades. The results show the potential capability of the proposed stereo-DIC system in remote capturing the full-field 3D dynamic responses and health status of large-scale structures.
Monitoring Land Use/Land Cover and Landscape Pattern Changes at a Local Scale: A Case Study of Pyongyang, North Korea
Authors: Piao Yong , Xiao Yi , Ma Fengdi , Park Sangjin , Lee Dongkun , Mo Yongwon , Jeong Seunggyu , Hwang Injae , Kim Yujin
Published: March 2023

One method of understanding landscape pattern changes is through an understanding of land use/land cover (LULC) changes, which are closely related to landscape pattern changes. Previous studies have monitored LULC changes across North Korea but did not consider landscape changes at a local scale. Using multiple LULC products to construct sample points, the LULC was classified using a random-forest algorithm and Landsat satellite dataset. The overall accuracy of the classification was 97.66 ± 1.36%, and the Kappa coefficient was 0.95 ± 0.03. Based on the classification results, landscape indices were used to quantify and monitor landscape pattern changes. The results showed that, from 2000 to 2020, there was an increasing trend in built-up and forest areas in Pyongyang, while cropland showed a decreasing trend, and landscape fragmentation increased. However, urban expansion was not the main factor affecting fragmentation. The main factors were forest recovery and cropland reduction, leading to an increase in landscape fragmentation in Pyongyang.
An Overview of Emergency Communication Networks
Authors: Wang Qian , Li Wenfeng , Yu Zheqi , Abbasi Qammer , Imran Muhammad , Ansari Shuja , Sambo Yusuf , Wu Liwen , Li Qiang , Zhu Tong
Published: March 2023

In recent years, major natural disasters and public safety accidents have frequently occurred worldwide. In order to deal with various disasters and accidents using rapidly deployable, reliable, efficient, and stable emergency communication networks, all countries in the world are strengthening and improving emergency communication network construction and related technology research. Motivated by these situations, in this paper, we provide a state-of-the-art survey of the current situation and development of emergency communication networks. In this detailed investigation, our primary focus is the extensive discussion of emergency communication network technology, including satellite networks, ad hoc networks, cellular networks, and wireless private networks. Then, we explore and analyze the networks currently applied in emergency rescue, such as the 370M narrowband private network, broadband cluster network, and 5G constellation plan. We propose a broadband-narrowband integrated emergency communication network to provide an effective solution for visual dispatch of emergency rescue services. The main findings derived from the comprehensive survey on the emergency communication network are then summarized, and possible research challenges are noted. Lastly, we complete this survey by shedding new light on future directions for the emergency communication network. In the future, the emergency network will develop in the direction of intelligence, integration, popularization, and lower cost, and space-air-ground-sea integrated networks. This survey provides a reference basis for the construction of networks to mitigate major natural disasters and public safety accidents.
Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season
Authors: Buthelezi Siphiwokuhle , Mutanga Onisimo , Sibanda Mbulisi , Odindi John , Clulow Alistair D. , Chimonyo Vimbayi G. P. , Mabhaudhi Tafadzwanashe
Published: March 2023

Maize (Zea Mays) is one of the most valuable food crops in sub-Saharan Africa and is a critical component of local, national and regional economies. Whereas over 50% of maize production in the region is produced by smallholder farmers, spatially explicit information on smallholder farm maize production, which is necessary for optimizing productivity, remains scarce due to a lack of appropriate technologies. Maize leaf area index (LAI) is closely related to and influences its canopy physiological processes, which closely relate to its productivity. Hence, understanding maize LAI is critical in assessing maize crop productivity. Unmanned Aerial Vehicle (UAV) imagery in concert with vegetation indices (VIs) obtained at high spatial resolution provides appropriate technologies for determining maize LAI at a farm scale. Five DJI Matrice 300 UAV images were acquired during the maize growing season, and 57 vegetation indices (VIs) were generated from the derived images. Maize LAI samples were collected across the growing season, a Random Forest (RF) regression ensemble based on UAV spectral data and the collected maize LAI samples was used to estimate maize LAI. The results showed that the optimal stage for estimating maize LAI using UAV-derived VIs in concert with the RF ensemble was during the vegetative stage (V8–V10) with an RMSE of 0.15 and an R2 of 0.91 (RRMSE = 8%). The findings also showed that UAV-derived traditional, red edge-based and new VIs could reliably predict maize LAI across the growing season with an R2 of 0.89–0.93, an RMSE of 0.15–0.65 m2/m2 and an RRMSE of 8.13–19.61%. The blue, red edge and NIR sections of the electromagnetic spectrum were critical in predicting maize LAI. Furthermore, combining traditional, red edge-based and new VIs was useful in attaining high LAI estimation accuracies. These results are a step towards achieving robust, efficient and spatially explicit monitoring frameworks for sub-Saharan African smallholder farm productivity.
Sentinel-2 MSI Observations of Water Clarity in Inland Waters across Hainan Island and Implications for SDG 6.3.2 Evaluation
Authors: Qiu Ruiting , Wang Shenglei , Shi Jiankang , Shen Wei , Zhang Wenzhi , Zhang Fangfang , Li Junsheng
Published: March 2023

Freshwater on islands represents a precious resource and highly vulnerable ecosystem. For monitoring freshwater, satellite remote sensing is efficient and has large-scale application. This study proposed a modified model of the quasi-analytical algorithm (ZSD-QAAv6m) to retrieve the water clarity of inland waters (>1 km2) across Hainan Island, China using Sentinel-2 multispectral instrument data. By adjusting the threshold of Rrs(665), the proposed model could accurately estimate water clarity with diverse optical properties on the island and avoid underestimation in moderately clear waters. Based upon this, the first spatiotemporal analysis of recent water clarity in Hainan Island was conducted. The results show that lake water clarity in the central region was generally higher (with average value of 1.4 m) than that of coastal regions (with average value of 1.2 m). Seasonally, the water clarity during the wet season was usually lower than that in the dry season, with average values of 1.1 m and 1.3 m across the island respectively. From 2017 to 2021, the proportion of water bodies with water clarity > 0.5 m increased from 60% to 100%. The overall spatial pattern of water clarity was correlated to the regional vegetation cover in Hainan Island, with higher clarity associated with higher vegetation cover in the central regions. The seasonal variation of water clarity may be attributed to heavy rainfall and runoff during the wet season; while the distinct annual variation may be benefited from the strengthened surface water protections in Hainan Province in recent years. This study provides a practical approach for evaluating the SDG 6.3.2 indicator in Hainan Island using remote sensed water clarity as a comprehensive water quality indicator and the findings could facilitate the island’s water resource management and conservation.
Synapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network
Authors: Seok Hyunho , Son Shihoon , Jathar Sagar Bhaurao , Lee Jaewon , Kim Taesung
Published: March 2023

Memristors mimic synaptic functions in advanced electronics and image sensors, thereby enabling brain-inspired neuromorphic computing to overcome the limitations of the von Neumann architecture. As computing operations based on von Neumann hardware rely on continuous memory transport between processing units and memory, fundamental limitations arise in terms of power consumption and integration density. In biological synapses, chemical stimulation induces information transfer from the pre- to the post-neuron. The memristor operates as resistive random-access memory (RRAM) and is incorporated into the hardware for neuromorphic computing. Hardware composed of synaptic memristor arrays is expected to lead to further breakthroughs owing to their biomimetic in-memory processing capabilities, low power consumption, and amenability to integration; these aspects satisfy the upcoming demands of artificial intelligence for higher computational loads. Among the tremendous efforts toward achieving human-brain-like electronics, layered 2D materials have demonstrated significant potential owing to their outstanding electronic and physical properties, facile integration with other materials, and low-power computing. This review discusses the memristive characteristics of various 2D materials (heterostructures, defect-engineered materials, and alloy materials) used in neuromorphic computing for image segregation or pattern recognition. Neuromorphic computing, the most powerful artificial networks for complicated image processing and recognition, represent a breakthrough in artificial intelligence owing to their enhanced performance and lower power consumption compared with von Neumann architectures. A hardware-implemented CNN with weight control based on synaptic memristor arrays is expected to be a promising candidate for future electronics in society, offering a solution based on non-von Neumann hardware. This emerging paradigm changes the computing algorithm using entirely hardware-connected edge computing and deep neural networks.
Uncontrolled Two-Step Iterative Calibration Algorithm for Lidar–IMU System
Authors: Yin Shilun , Xie Donghai , Fu Yibo , Wang Zhibo , Zhong Ruofei
Published: March 2023

Calibration of sensors is critical for the precise functioning of lidar–IMU systems. However, the accuracy of the system can be compromised if motion distortion is not considered. This study proposes a novel uncontrolled two-step iterative calibration algorithm that eliminates motion distortion and improves the accuracy of lidar–IMU systems. Initially, the algorithm corrects the distortion of rotational motion by matching the original inter-frame point cloud. Then, the point cloud is further matched with IMU after the prediction of attitude. The algorithm performs iterative motion distortion correction and rotation matrix calculation to obtain high-precision calibration results. In comparison with existing algorithms, the proposed algorithm boasts high accuracy, robustness, and efficiency. This high-precision calibration result can benefit a wide range of acquisition platforms, including handheld, unmanned ground vehicle (UGV), and backpack lidar–IMU systems.
Working Mode Recognition of Non-Specific Radar Based on ResNet-SVM Learning Framework
Authors: Pan Jifei , Xiong Jingwei , Zhuo Yihong
Published: March 2023

Mode recognition is a basic task to interpret the behavior of multi-functional radar. The existing methods need to train complex and huge neural networks to improve the recognition ability, and it is difficult to deal with the mismatch between the training set and the test set. In this paper, a learning framework based on residual neural network (ResNet) and support vector machine (SVM) is designed, to solve the problem of mode recognition for non-specific radar, called multi-source joint recognition framework (MSJR). The key idea of the framework is to embed the prior knowledge of radar mode into the machine learning model, and combine the manual intervention and automatic extraction of features. The model can purposefully learn the feature representation of the signal on the working mode, which weakens the impact brought by the mismatch between training and test data. In order to solve the problem of difficult recognition under signal defect conditions, a two-stage cascade training method is designed, to give full play to the data representation ability of ResNet and the high-dimensional feature classification ability of SVM. Experiments show that the average recognition rate of the proposed model, with embedded radar knowledge, is improved by 33.7% compared with the purely data-driven model. Compared with other similar state-of-the-art reported models, such as AlexNet, VGGNet, LeNet, ResNet, and ConvNet, the recognition rate is increased by 12%. Under the condition of 0–35% leaky pulses in the independent test set, MSJR still has a recognition rate of more than 90%, which also proves its effectiveness and robustness in the recognition of unknown signals with similar semantic characteristics.
Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers
Authors: Frej Damian , Grabski Paweł , Jurecki Rafał S. , Szumska Emilia M.
Published: March 2023

A vehicle’s longitudinal acceleration is a parameter often used for determining vehicle motion dynamics. This parameter can also be used to evaluate driver behavior and passenger comfort analysis. The paper presents the results of longitudinal acceleration tests of city buses and coaches recorded during rapid acceleration and braking maneuvers. The presented test results demonstrate that longitudinal acceleration is significantly affected by road conditions and surface type. In addition, the paper presents the values of longitudinal accelerations of city buses and coaches during their regular operation. These results were obtained on the basis of registration of vehicle traffic parameters in a continuous and long-term manner. The test results showed that the maximum deceleration values recorded during the tests of city buses and coaches in real traffic conditions were much lower than the maximum deceleration values found during sudden braking maneuvers. This proves that the tested drivers in real conditions did not have to use sudden braking. The maximum positive acceleration values recorded in acceleration maneuvers were slightly higher than the acceleration values logged during the rapid acceleration tests on the track.
A Wearable Insole System to Measure Plantar Pressure and Shear for People with Diabetes
Authors: Tang Jinghua , Bader Dan L. , Moser David , Parker Daniel J. , Forghany Saeed , Nester Christopher J. , Jiang Liudi
Published: March 2023

Pressure coupled with shear stresses are the critical external factors for diabetic foot ulceration assessment and prevention. To date, a wearable system capable of measuring in-shoe multi-directional stresses for out-of-lab analysis has been elusive. The lack of an insole system capable of measuring plantar pressure and shear hinders the development of an effective foot ulcer prevention solution that could be potentially used in a daily living environment. This study reports the development of a first-of-its-kind sensorised insole system and its evaluation in laboratory settings and on human participants, indicating its potential as a wearable technology to be used in real-world applications. Laboratory evaluation revealed that the linearity error and accuracy error of the sensorised insole system were up to 3% and 5%, respectively. When evaluated on a healthy participant, change in footwear resulted in approximately 20%, 75% and 82% change in pressure, medial–lateral and anterior–posterior shear stress, respectively. When evaluated on diabetic participants, no notable difference in peak plantar pressure, as a result of wearing the sensorised insole, was measured. The preliminary results showed that the performance of the sensorised insole system is comparable to previously reported research devices. The system has adequate sensitivity to assist footwear assessment relevant to foot ulcer prevention and is safe to use for people with diabetes. The reported insole system presents the potential to help assess diabetic foot ulceration risk in a daily living environment underpinned by wearable pressure and shear sensing technologies.
Electromagnetic Wave Absorption in the Human Head: A Virtual Sensor Based on a Deep-Learning Model
Authors: Di Barba Paolo , Januszkiewicz Łukasz , Kawecki Jarosław , Mognaschi Maria Evelina
Published: March 2023

Determining the amount of electromagnetic wave energy absorbed by the human body is an important issue in the analysis of wireless systems. Typically, numerical methods based on Maxwell’s equations and numerical models of the body are used for this purpose. This approach is time-consuming, especially in the case of high frequencies, for which a fine discretization of the model should be used. In this paper, the surrogate model of electromagnetic wave absorption in human body, utilizing Deep-Learning, is proposed. In particular, a family of data from finite-difference time-domain analyses makes it possible to train a Convolutional Neural Network (CNN), in view of recovering the average and maximum power density in the cross-section region of the human head at the frequency of 3.5 GHz. The developed method allows for quick determination of the average and maximum power density for the area of the entire head and eyeball areas. The results obtained in this way are similar to those obtained by the method based on Maxwell’s equations.