bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Crosslinking Kinetics of UV-Transparent Ethylene-Vinyl Acetate Copolymer and Polyolefin Elastomer Encapsulants
Authors: Wallner Gernot M. , Adothu Baloji , Pugstaller Robert , Costa Francis R. , Mallick Sudhanshu
Published: April 2022

Encapsulants based on ethylene-vinyl acetate copolymers (EVA) or polyolefin elastomers (POE) are essential for glass or photovoltaic module laminates. To improve their multi-functional property profile and their durability, the encapsulants are frequently peroxide crosslinked. The crosslinking kinetics are affected by the macromolecular structure and the formulation with stabilizers such as phenolic antioxidants, hindered amine light stabilizers or aromatic ultraviolet (UV) absorbers. The main objective of this study was to implement temperature-rise and isothermal dynamic mechanical analysis (DMA) approaches in torsional mode and to assess and compare the crosslinking kinetics of novel UV-transparent encapsulants based on EVA and POE. The gelation time was evaluated from the crossover of the storage and loss shear modulus. While the investigated EVA and POE encapsulants revealed quite similar activation energy values of 155 kJ/moles, the storage modulus and complex viscosity in the rubbery state were significantly higher for EVA. Moreover, the gelation of the polar EVA grade was about four times faster than for the less polar POE encapsulant. Accordingly, the curing reaction of POE was retarded up to a factor of 1.6 to achieve a progress of crosslinking of 95%. Hence, distinct differences in the crosslinking kinetics of the UV-transparent EVA and POE grades were ascertained, which is highly relevant for the lamination of modules.
Modulation of Chitosan-TPP Nanoparticle Properties for Plasmid DNA Vaccines Delivery
Authors: Nunes Renato , Serra Ana Sofia , Simaite Aiva , Sousa Ângela
Published: April 2022

Nucleic acid vaccines have become a revolutionary technology to give a fast, safe, cost-effective and efficient response against viral infections, such as SARS-CoV-2 or Human papillomavirus (HPV). However, to ensure their effectiveness, the development of adequate methods to protect, carry, and deliver nucleic acids is fundamental. In this work, nanoparticles (NPs) of chitosan (CS)-tripolyphosphate (TPP)-plasmid DNA (pDNA) were thoroughly modulated and characterized, by measuring the charge and size through dynamic light scattering (DLS) and morphology by scanning electron microscopy (SEM). Stability, cytotoxicity and cellular uptake of NPs were also evaluated. Finally, the effect of polyplexes on the expression of HPV E7 antigen in human fibroblast and RAW cells was investigated through polymerase chain reaction (PCR) and real-time PCR. The results showed NPs with a spherical/oval shape, narrow size distribution <180 nm and positive zeta potentials (>20 mV) and good stability after one month of storage at 4 °C in formulation buffer or when incubated in culture medium and trypsin. In vitro studies of NPs cytotoxicity revealed that the elimination of formulation buffers led to an improvement in the rate of cell viability. The E7 antigen transcription was also increased for NPs obtained with high pDNA concentration (60 μg/mL). The analyzed CS-TPP-pDNA polyplexes can offer a promising vehicle for nucleic acid vaccines, not only in the prevention or treatment of viral infections, but also to fight emergent and future pathogens.
Current Development and Future Perspective on Natural Jute Fibers and Their Biocomposites
Authors: Shahinur Sweety , Sayeed M. M. Alamgir , Hasan Mahbub , Sayem Abu Sadat Muhammad , Haider Julfikar , Ura Sharifu
Published: April 2022

The increasing trend of the use of synthetic products may result in an increased level of pollution affecting both the environment and living organisms. Therefore, from the sustainability point of view, natural, renewable and biodegradable materials are urgently needed to replace environmentally harmful synthetic materials. Jute, one of the natural fibers, plays a vital role in developing composite materials that showed potential in a variety of applications such as household, automotive and medical appliances. This paper first reviews the characterization and performance of jute fibers. Subsequently, the main focus is shifted towards research advancements in enhancing physical, mechanical, thermal and tribological properties of the polymeric materials (i.e., synthetic or biobased and thermoplastic or thermoset plastic) reinforced with jute fibers in a variety of forms such as particle, short fiber or woven fabric. It is understood that the physio-mechanical properties of jute-polymer composites largely vary based on the fiber processing and treatment, fiber shape and/or size, fabrication processes, fiber volume fraction, layering sequence within the matrix, interaction of the fiber with the matrix and the matrix materials used. Furthermore, the emerging research on jute fiber, such as nanomaterials from jute, bioplastic packaging, heavy metal absorption, electronics, energy device or medical applications and development of jute fiber composites with 3D printing, is explored. Finally, the key challenges for jute and its derivative products in gaining commercial successes have been highlighted and potential future directions are discussed.
Development and Applications of Hydrogel-Based Triboelectric Nanogenerators: A Mini-Review
Authors: Wang Sheng-Ji , Jing Xin , Mi Hao-Yang , Chen Zhuo , Zou Jian , Liu Zi-Hao , Feng Pei-Yong , Liu Yuejun , Zhang Zhi , Shang Yinghui
Published: April 2022

In recent years, with the appearance of the triboelectric nanogenerator (TENG), there has been a wave of research on small energy harvesting devices and self-powered wearable electronics. Hydrogels—as conductive materials with excellent tensile properties—have been widely focused on by researchers, which encouraged the development of the hydrogel-based TENGs (H-TENGs) that use the hydrogel as an electrode. Due to the great feasibility of adjusting the conductivity and mechanical property as well as the microstructure of the hydrogels, many H-TENGs with excellent performance have emerged, some of which are capable of excellent outputting ability with an output voltage of 992 V, and self-healing performance which can spontaneously heal within 1 min without any external stimuli. Although there are numerous studies on H-TENGs with excellent performance, a comprehensive review paper that systematically correlates hydrogels’ properties to TENGs is still absent. Therefore, in this review, we aim to provide a panoramic overview of the working principle as well as the preparation strategies that significantly affect the properties of H-TENGs. We review hydrogel classification categories such as their network composition and their potential applications on sensing and energy harvesting, and in biomedical fields. Moreover, the challenges faced by the H-TENGs are also discussed, and relative future development of the H-TENGs are also provided to address them. The booming growth of H-TENGs not only broadens the applications of hydrogels into new areas, but also provides a novel alternative for the sustainable power sources.
Material Removal Optimization Strategy of 3D Block Cutting Based on Geometric Computation Method
Authors: Shao Hui , Liu Qimeng , Gao Zhiwei
Published: April 2022

During the material removal stage in stone rough processing, milling type has been widely explored, which, however, may cause time and material consumption, as well as substantial stress for the environment. To improve the material removal rate and waste reuse rate in the rough processing stage for three-dimensional stone products with a special shape, in this paper, circular saw disc cutting is explored to cut a convex polyhedron out of a blank box, which approaches a target product. Unlike milling optimization, this problem cannot be well solved by mathematical methods, which have to be solved by geometrical methods instead. An automatic block cutting strategy is proposed intuitively by considering a series of geometrical optimization approaches for the first time. To obtain a big removal block, constructing cutting planes based on convex vertices is uniquely proposed. Specifically, the removal vertices (the maximum thickness of material removal) are searched based on the octree algorithm, and the cutting plane is constructed based on this thickness to guarantee a relatively big removal block. Moreover, to minimize the cutting time, the geometrical characteristics of the intersecting convex polygon of the cutting plane with the convex polyhedron are analyzed, accompanied by the constraints of the guillotine cutting mode. The optimization algorithm determining the cutting path is presented with a feed direction accompanied by the shortest cutting stroke, which confirms the shortest cutting time. From the big removal block and shortest cutting time, the suboptimal solution of the average material removal rate (the ratio of material removal volume to cutting time) is generated. Finally, the simulation is carried out on a blank box to approach a bounding sphere both on MATLAB and the Vericut platform. In this case study, for the removal of 85% of material with 19 cuts, the proposed cutting strategy achieves five times higher the average material removal rate than that of one higher milling capacity case.
RecSys Pertaining to Research Information with Collaborative Filtering Methods: Characteristics and Challenges
Authors: Azeroual Otmane , Koltay Tibor
Published: April 2022

Recommendation (recommender) systems have played an increasingly important role in both research and industry in recent years. In the area of publication data, for example, there is a strong need to help people find the right research information through recommendations and scientific reports. The difference between search engines and recommendation systems is that search engines help us find something we already know, while recommendation systems are more likely to help us find new items. An essential function of recommendation systems is to support users in their decision making. Recommendation systems are information systems that can be categorized into decision support systems, as long as they are used for decision making and are intended to support people instead of replacing them. This paper deals with recommendation systems for research information, especially publication data. We discuss and analyze the challenges and peculiarities of implementing recommender systems for the scientific exchange of research information. For this purpose, data mining techniques are examined and a concept for a recommendation system for research information is developed. Our aim is to investigate to what extent a recommendation system based on a collaborative filtering approach with cookies is possible. The data source is publication data extracted from cookies in the Web of Science database. The results of our investigation show that a collaborative filtering process is suitable for publication data and that recommendations can be generated with user information. In addition, we have seen that collaborative filtering is an important element that can solve a practical problem by sifting through large amounts of dynamically generated information to provide users with personalized content and services.
Dizang and the Three Kings: Constructing Buddhist Hell by Imitating the Bureaucratic System in the Tang Dynasty
Authors: Jiang Xiao
Published: April 2022

The Buddhist ideas and practices of hell were bureaucratized in medieval China. The cult of Dizang and the Ten Kings of Hell was popular from the late Tang Dynasty onward. However, the concept of the Three Kings of Hell (King Yama 閻羅王, the Magistrate of Mount Tai 泰山府君, and the Great Spirit of the Five Paths 五道大神) appeared before that of the Ten Kings and has long been ignored. This article aimed to make a textual comparison of the descriptions of Dizang and the Three Kings in the literature with the bureaucratic system of the Three Departments (sansheng zhi 三省制), which was the central government system during the Tang Dynasty, where the Three Departments performed their respective functions. There are several structural and functional parallels between the underworldly afterlife and the political bureaucracies of the world. The workings of the system in hell changed in texts from different periods, showing the evolution of the Three Departments system during the Tang Dynasty. This case study demonstrated that the system of Dizang and the Three Kings of Hell were constructed based on the official system used in human society and that the underworld was reinterpreted as a bureaucratic system similar to the temporal one.
Muslim YouTubers in Turkey and the Authoritarian Male Gaze on YouTube
Authors: Çelebioğlu Esma
Published: April 2022

The increased digitalization in today’s world, including social interactions online, as well as digital practices and performances, has a significant impact on the identity formation of youth and reflects their self-representation in society and the global world. This article examines how gender identities shape online representations of religious youth in Turkey. To this end, this study particularly focuses on young Muslim YouTubers whose religious identity appears either as a part of their images (i.e., veiled women/hijabi YouTubers) or through the contents they create (Muslim male YouTubers). Presenting similarities and divergences between online representations of Muslim YouTubers, this study sheds light on how Muslim youth express religiosity as a part of their online identities through the digital content they create. Furthermore, this analysis explores different modes of utilization of YouTube by young female and male Muslims as manifested through their videos. Following Schiffer’s categorization of the functionality of objects, I will argue that socialization and individuality are highly prioritized in the contents created by hijabi YouTubers. At the same time, an ideological and authoritarian perspective becomes prominent among the YouTube videos created by Muslim male YouTubers in Turkey.
Who Is My Neighbor? Developing a Pedagogical Tool for Teaching Environmental Preaching and Ethics in Online and Hybrid Courses
Authors: Schade Leah D.
Published: April 2022

As theological education has moved increasingly to online and hybrid settings (both by choice and by pandemic necessity), practical theologians committed to teaching ecological theological education must navigate a paradox. How do we teach about interconnectivity and interdependence between the human and other-than-human inhabitants of a particular place when our classrooms are in disembodied digital spaces? This article examines a case study of a pedagogical tool developed by the author called the “Who Is My Neighbor” Mapping Exercise that enables students to explore and articulate how they conceptualize themselves and their faith communities embedded within their larger ecological contexts. This paper assesses the use of the mapping exercise in four different course contexts: three online and one hybrid online–immersion course. The author provides an overview of each of the four course contexts in which the tool was used, includes descriptions of how students engaged the tool, and assesses its effectiveness. The author uses three types of criteria for assessment of the pedagogical exercise: student feedback, level of competence demonstrated in student assignments (sermons, worship services, teaching events), and personal observations, particularly around the differences between online and onsite contexts. The author suggests that the mapping exercise is a tool that can be used by others teaching practical theology to help students understand their relationships within Creation and their communities, critically engage environmental justice issues, and apply what they learn to their ministry contexts.
Leverage, Growth Opportunities, and Credit Risk: Evidence from Italian Innovative SMEs
Authors: Manelli Alberto , Pace Roberta , Leone Maria
Published: April 2022

The link between leverage and growth opportunities has been a topic issue in corporate finance for many years. The present paper aims to investigate the link between credit risk, leverage, and growth opportunities in a sample of Italian innovative small-and-medium enterprises (SMEs), given the lack of empirical literature on the subject. The results of the WLS model confirm the relationship between investments, leverage, and credit risk highlighted by the literature—in particular, a negative relationship emerges between credit risk and investments and between leverage and investments, while the analysis reveals a positive relationship between investments and liquidity. Furthermore, in consideration of the significant economic differences existing between the regional macro-areas into which Italy is divided, the firms were classified by geographical areas. The results show that the northeast area is the region characterised by the most reliable and significant results. The paper is organised as follows: Introduction provides a review of the theoretical and empirical literature on the link between leverage, investments, and growth opportunities and on credit risk; Materials and Methods explain the model; Results explain the WLS regression; Discussions contain the main finding of the analysis; Conclusions summarize the study.
Practicality and Robustness of Tree Species Identification Using UAV RGB Image and Deep Learning in Temperate Forest in Japan
Authors: Onishi Masanori , Watanabe Shuntaro , Nakashima Tadashi , Ise Takeshi
Published: April 2022

Identifying tree species from the air has long been desired for forest management. Recently, combination of UAV RGB image and deep learning has shown high performance for tree identification in limited conditions. In this study, we evaluated the practicality and robustness of the tree identification system using UAVs and deep learning. We sampled training and test data from three sites in temperate forests in Japan. The objective tree species ranged across 56 species, including dead trees and gaps. When we evaluated the model performance on the dataset obtained from the same time and same tree crowns as the training dataset, it yielded a Kappa score of 0.97, and 0.72, respectively, for the performance on the dataset obtained from the same time but with different tree crowns. When we evaluated the dataset obtained from different times and sites from the training dataset, which is the same condition as the practical one, the Kappa scores decreased to 0.47. Though coniferous trees and representative species of stands showed a certain stable performance regarding identification, some misclassifications occurred between: (1) trees that belong to phylogenetically close species, (2) tree species with similar leaf shapes, and (3) tree species that prefer the same environment. Furthermore, tree types such as coniferous and broadleaved or evergreen and deciduous do not always guarantee common features between the different trees belonging to the tree type. Our findings promote the practicalization of identification systems using UAV RGB images and deep learning.
Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models
Authors: Yang Zhizhou , Zou Lei , Xia Jun , Qiao Yunfeng , Cai Diwen
Published: April 2022

Urban water quality is facing strongly adverse degradation in rapidly developing areas. However, there exists a huge challenge to estimating the inner features and predicting the variation of long-term water quality due to the lack of related monitoring data and the complexity of urban water systems. Fortunately, multi-remote sensing data, such as nighttime light and evapotranspiration (ET), provide scientific data support and reasonably reveal the variation mechanisms. Here, we develop an integrated decomposition-reclassification-prediction method for water quality by integrating the CEEMDN method, the RF method mothed, and the genetic algorithm-support vector machine model (GA-SVM). The degression of the long-term water quality was decomposed and reclassified into three different frequency terms, i.e., high-frequency, low-frequency, and trend terms, to reveal the inner mechanism and dynamics in the CEEMDAN method. The RF method was then used to identify the teleconnection and the significance of the selected driving factors. More importantly, the GA-SVM model was designed with two types of model schemes, which were the data-driven model (GA-SVMd) and the integrated CEEMDAN-GA-SVM model (defined as GA-SVMc model), in order to predict urban water quality. Results revealed that the high-frequency terms for NH3-N and TN had a major contribution to the water quality and were mainly dominated by hydrometeorological factors such as ET, rainfall, and the dynamics of the lake water table. The trend terms revealed that the water quality continuously deteriorated during the study period; the terms were mainly regulated by the land use and land cover (LULC), land metrics, population, and yearly rainfall. The predicting results confirmed that the integrated GA-SVMc model had better performance than single data-driven models (such as the GA-SVM model). Our study supports that the integrated method reveals variation rules in water quality and provides early warning and guidance for reducing the water pollutant concentration.
Detection of Periodic Disturbances in LOFAR Calibration Solutions
Authors: Beser Katarzyna , Mevius Maaijke , Grzesiak Marcin , Rothkaehl Hanna
Published: April 2022

The Earth’s ionosphere is a highly variable medium on a wide range of spatio-temporal scales. The responsiveness of plasma to the geomagnetic field and its changes gives rise to anisotropy, which may introduce wave-like characteristics while scanning the ionosphere with a line-of-sight towards a radio source. Previous studies of LOw Frequency ARray (LOFAR) calibration phase solutions report that the estimated beta parameter of a structure function calculated over 6–8 h of astronomical observation timespan has a range of values from 1.6 to 2.0, with an average of 1.89. Such difference between the observations could result from transient wave-like disturbances within the data. This study aims to present a method of signal processing of ionospheric calibration datasets that allows the extraction of a transient wave-like signal and discuss its possible origin. We use complex Morlet wavelet analysis applied to two 8 h observations corresponding to very quiet geomagnetic conditions. We find a wave-like signal in the interferometric Total Electron Content data even during periods of no geomagnetic activity. We suggest it results from the relative velocity changes between the LOFAR line-of-sight and a convection pattern in the ionospheric F layer. Establishing the relationship between quiet time ionosphere, geomagnetic field changes and LOFAR’s calibration solutions may prove beneficial to determination of the dominant signals in the more disturbed conditions, which we leave for future study.
Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model
Authors: Du Dandan , Zheng Chaolei , Jia Li , Chen Qiting , Jiang Min , Hu Guangcheng , Lu Jing
Published: April 2022

Satellite-based models have been widely used to estimate gross primary production (GPP) of terrestrial ecosystems. Although they have many advantages for mapping spatiotemporal variations of regional or global GPP, the performance in agroecosystems is relatively poor. In this study, a light-use-efficiency model for cropland GPP estimation, named EF-LUE, driven by remote sensing data, was developed by integrating evaporative fraction (EF) as limiting factor accounting for soil water availability. Model parameters were optimized first using CO2 flux measurements by eddy covariance system from flux tower sites, and the optimized parameters were further spatially extrapolated according to climate zones for global cropland GPP estimation in 2001–2019. The major forcing datasets include the fraction of absorbed photosynthetically active radiation (FAPAR) data from the Copernicus Global Land Service System (CGLS) GEOV2 dataset, EF from the ETMonitor model, and meteorological forcing variables from ERA5 data. The EF-LUE model was first evaluated at flux tower site-level, and the results suggested that the proposed EF-LUE model and the LUE model without using water availability limiting factor, both driven by flux tower meteorology data, explained 82% and 74% of the temporal variations of GPP across crop sites, respectively. The overall KGE increased from 0.73 to 0.83, NSE increased from 0.73 to 0.81, and RMSE decreased from 2.87 to 2.39 g C m−2 d−1 in the estimated GPP after integrating EF in the LUE model. These improvements may be largely attributed to parameters optimized for different climatic zones and incorporating water availability limiting factor expressed by EF into the light-use-efficiency model. At global scale, the verification by GPP measurements from cropland flux tower sites showed that GPP estimated by the EF-LUE model driven by ERA5 reanalysis meteorological data and EF from ETMonitor had overall the highest R2, KGE, and NSE and the smallest RMSE over the four existing GPP datasets (MOD17 GPP, revised EC-LUE GPP, GOSIF GPP and PML-V2 GPP). The global GPP from the EF-LUE model could capture the significant negative GPP anomalies during drought or heat-wave events, indicating its ability to express the impacts of the water stress on cropland GPP.
Ground-Based MAX-DOAS Measurements of Tropospheric Aerosols, NO2, and HCHO Distributions in the Urban Environment of Shanghai, China
Authors: Wang Haoyue , Wei Wanlin , Che Huizheng , Tang Xiao , Bian Jianchun , Yu Ke , Wang Weiguo
Published: April 2022

Aerosol extinction profiles at 550 nm were retrieved by applying multi-axis differential optical absorption spectroscopy (MAX-DOAS) and lookup table. Then the tropospheric NO2 and HCHO vertical column densities were retrieved using a two-step method from 28 July to 5 August of 2015 in Shanghai. The retrieved results were compared with the satellite products, and then their diurnal variation was observed. A consistency check was performed before the inversion to obtain a correction factor. Based on the sensitivity of geometric angles to oxygen dimer air mass factor (O4 AMF, AMF is the ratio of the slanted column density to the vertical column density), the parameterization scheme of geometric angles in the lookup table is optimized. The results show that the aerosol increased significantly in the afternoon. The diurnal variation of tropospheric NO2 and HCHO vertical column densities (VCDs) are bimodal and unimodal patterns respectively, and their values are higher than those of GOME-2 and OMI satellite products. A process of aerosol reduction and recovery are related to ground particulates and meteorological elements. The chemical sensitivity of local ozone production also has a clear diurnal variation.
Slot Antennas Integrated into 3D Knitted Fabrics: 5.8 GHz and 24 GHz ISM Bands
Authors: Cupal Miroslav , Raida Zbynek
Published: April 2022

In the paper, a 3D knitted fabric is used for the design of a circularly polarized textile-integrated antenna. The role of the radiating element is played by a circular slot etched into the conductive top wall of a textile-integrated waveguide. Inside the circular slot, a cross slot rotated for about 45° is etched to excite the circular polarization. The polarization of the antenna can be changed by the rotation of the cross slot. The antenna has a patch-like radiation pattern, and the gain is about 5.3 dBi. The textile-integrated feeder of the antenna is manufactured by screen printing conductive surfaces and sewing side walls with conductive threads. The antenna was developed for ISM bands 5.8 GHz and 24 GHz. The operation frequency 24 GHz is the highest frequency of operation for which the textile-integrated waveguide antenna has been manufactured.
A Taper-in-Taper Structured Interferometric Optical Fiber Sensor for Cu2+ ion Detection
Authors: Gong Zidan , Lei Yisong , Wang Ziwen , Zhang Jie , Sun Zeji , Li Yuyao , Huang Jianhao , Chan Chichiu , Ouyang Xia
Published: April 2022

Copper ion is closely associated with the ecosystem and human health, and even a little excessive dose in drinking water may result in a range of health problems. However, it remains challenging to produce a highly sensitive, reliable, cost-effective and electromagnetic-interference interference-immune device to detect Cu2+ ion in drinking water. In this paper, a taper-in-taper fiber sensor was fabricated with high sensitivity by mode-mode interference and deposited polyelectrolyte layers for Cu2+ detection. We propose a new structure which forms a secondary taper in the middle of the single-mode fiber through two-arc discharge. Experimental results show that the newly developed fiber sensor possesses a sensitivity of 2741 nm/RIU in refractive index (RI), exhibits 3.7 times sensitivity enhancement when compared with traditional tapered fiber sensors. To apply this sensor in copper ions detection, the results present that when the concentration of Cu2+ is 0–0.1 mM, the sensitivity could reach 78.03 nm/mM. The taper-in-taper fiber sensor exhibits high sensitivity with good stability and mechanical strength which has great potential to be applied in the detection of low Cu2+ ions in some specific environments such as drinking water.
Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics—Part 2: Accuracy
Authors: Pagnon David , Domalain Mathieu , Reveret Lionel
Published: April 2022

Two-dimensional deep-learning pose estimation algorithms can suffer from biases in joint pose localizations, which are reflected in triangulated coordinates, and then in 3D joint angle estimation. Pose2Sim, our robust markerless kinematics workflow, comes with a physically consistent OpenSim skeletal model, meant to mitigate these errors. Its accuracy was concurrently validated against a reference marker-based method. Lower-limb joint angles were estimated over three tasks (walking, running, and cycling) performed multiple times by one participant. When averaged over all joint angles, the coefficient of multiple correlation (CMC) remained above 0.9 in the sagittal plane, except for the hip in running, which suffered from a systematic 15° offset (CMC = 0.65), and for the ankle in cycling, which was partially occluded (CMC = 0.75). When averaged over all joint angles and all degrees of freedom, mean errors were 3.0°, 4.1°, and 4.0°, in walking, running, and cycling, respectively; and range of motion errors were 2.7°, 2.3°, and 4.3°, respectively. Given the magnitude of error traditionally reported in joint angles computed from a marker-based optoelectronic system, Pose2Sim is deemed accurate enough for the analysis of lower-body kinematics in walking, cycling, and running.
The Influence of Optical Alignment Error on Compression Coding Superresolution Imaging
Authors: Wang Chao , Xing Siyuan , Xu Miao , Shi Haodong , Wu Xingkai , Fu Qiang , Jiang Huilin
Published: April 2022

Superresolution (SR) imaging technology based on compression coding has always been considered as the key to break through the geometric resolution of the detector. In addition to factors such as the reconstruction algorithm and mounting platform vibrations, the impact of inherent errors in the optical system itself on the reconstruction results of SR imaging is also obvious. To address this issue, a study on the design of the SR optical system and the influence of optical alignment errors on SR imaging was conducted. The design of the SR optical system based on digital micro-mirror device (DMD) for long-wave infrared wavelength was completed, and an athermal analysis of the system was carried out. The design results showed that the SR optical system has good imaging quality in the operating temperature range. The imaging model of the DMD SR imaging optical system is established according to the designed SR optical system. We investigated the influence of various alignment errors, including decenter, tilt, lens interval error and defocus, on the imaging properties of the SR optical system. Various random combinations of alignment errors were introduced into the optical system, respectively, and the SR reconstructed image quality of the imaging system was analyzed using the inverse sensitivity method to obtain the tolerance limits when the system was assembled. Finally, the effectiveness of the method to obtain the alignment tolerance limit of the compression coding SR imaging optical system was verified through a desktop demonstration experiment.
Detecting the Presence of Intrusive Drilling in Secure Transport Containers Using Non-Contact Millimeter-Wave Radar
Authors: Wagner Samuel , Alkasimi Ahmad , Pham Anh-Vu
Published: April 2022

We employ a 77–81 GHz frequency-modulated continuous-wave (FMCW) millimeter-wave radar to sense anomalous vibrations during vehicle transport at highway speeds for the first time. Secure metallic containers can be breached during transport by means of drilling into their sidewalls but detecting a drilling signature is difficult because the large vibrations of transport drown out the small vibrations of drilling. For the first time, we demonstrate that it is possible to use a non-contact millimeter-wave radar sensor to detect this micron-scale intrusive drilling while highway-speed vehicle movement shakes the container. With the millimeter-wave radar monitoring the microdoppler signature of the container’s vibrating walls, we create a novel signal-processing pipeline consisting of range–angle tracking, time–frequency analysis, horizontal stripe image convolution, and principal component analysis to create a robust and powerful detection statistic to alarm if drilling is present. To support this pipeline, we develop a statistical model combining the vibrating container and the random vibrations induced by vehicle movement to explore the robustness of the sensor’s detection capabilities. The presented results strongly support the inclusion of a millimeter-wave radar vibration sensor into a transport security system.
Vision-Based Defect Inspection and Condition Assessment for Sewer Pipes: A Comprehensive Survey
Authors: Li Yanfen , Wang Hanxiang , Dang L. Minh , Song Hyoung-Kyu , Moon Hyeonjoon
Published: April 2022

Due to the advantages of economics, safety, and efficiency, vision-based analysis techniques have recently gained conspicuous advancements, enabling them to be extensively applied for autonomous constructions. Although numerous studies regarding the defect inspection and condition assessment in underground sewer pipelines have presently emerged, we still lack a thorough and comprehensive survey of the latest developments. This survey presents a systematical taxonomy of diverse sewer inspection algorithms, which are sorted into three categories that include defect classification, defect detection, and defect segmentation. After reviewing the related sewer defect inspection studies for the past 22 years, the main research trends are organized and discussed in detail according to the proposed technical taxonomy. In addition, different datasets and the evaluation metrics used in the cited literature are described and explained. Furthermore, the performances of the state-of-the-art methods are reported from the aspects of processing accuracy and speed.
An Efficient Defocus Blur Segmentation Scheme Based on Hybrid LTP and PCNN
Authors: Basar Sadia , Waheed Abdul , Ali Mushtaq , Zahid Saleem , Zareei Mahdi , Biswal Rajesh Roshan
Published: April 2022

The defocus or motion effect in images is one of the main reasons for the blurry regions in digital images. It can affect the image artifacts up to some extent. However, there is a need for automatic defocus segmentation to separate blurred and sharp regions to extract the information about defocus-blur objects in some specific areas, for example, scene enhancement and object detection or recognition in defocus-blur images. The existence of defocus-blur segmentation algorithms is less prominent in noise and also costly for designing metric maps of local clarity. In this research, the authors propose a novel and robust defocus-blur segmentation scheme consisting of a Local Ternary Pattern (LTP) measured alongside Pulse Coupled Neural Network (PCNN) technique. The proposed scheme segments the blur region from blurred fragments in the image scene to resolve the limitations mentioned above of the existing defocus segmentation methods. It is noticed that the extracted fusion of upper and lower patterns of proposed sharpness-measure yields more noticeable results in terms of regions and edges compared to referenced algorithms. Besides, the suggested parameters in the proposed descriptor can be flexible to modify for performing numerous settings. To test the proposed scheme’s effectiveness, it is experimentally compared with eight referenced techniques along with a defocus-blur dataset of 1000 semi blurred images of numerous categories. The model adopted various evaluation metrics comprised of Precision, recall, and F1-Score, which improved the efficiency and accuracy of the proposed scheme. Moreover, the proposed scheme used some other flavors of evaluation parameters, e.g., Accuracy, Matthews Correlation-Coefficient (MCC), Dice-Similarity-Coefficient (DSC), and Specificity for ensuring provable evaluation results. Furthermore, the fuzzy-logic-based ranking approach of Evaluation Based on Distance from Average Solution (EDAS) module is also observed in the promising integrity analysis of the defocus blur segmentation and also in minimizing the time complexity.
Reciprocal Relationship between Parents’ School- and Home-Based Involvement and Children’s Reading Achievement during the First Year of Elementary School
Authors: Bonanati Sabrina , Rubach Charlott
Published: April 2022

Reading is an essential competence students learn in school. One question is how parents can support their children and their reading competence, particularly at the beginning of elementary school. Guided by this question, this study investigated the longitudinally reciprocal relationship between parental school- and home-based involvement with children’s reading competence. We also tested whether school- and home-based involvement mediated the relationship between structural context variables (e.g., migration background) and reading competence. A total of 254 parent–child dyads answered a questionnaire at two measurement points, i.e., at the beginning and the end of the first grade in elementary school. Home-based involvement and reading competence were negatively, reciprocally related to each other. Furthermore, we found a negative association between reading competence at the beginning of grade 1 and the relative change in school-based involvement at the end of grade 1. No mediation effects of school- and home-based involvement in the relation between structural context variables and reading competence were found. This paper provides a deeper understanding of the complex interrelations of the family–school partnership during the first school year.
Multicomponent Intervention Associated with Improved Emotional and Cognitive Outcomes of Marginalized Unemployed Youth of Latin America
Authors: Crespo-Andrade Cristina , Trueba Ana Francisca , Garcés María Sol , Pluck Graham
Published: April 2022

Mass migration and people seeking political refuge are critical social issues facing Latin America. Ecuador has the largest population of recognized refugees in the region. Youths from a migration background have an increased risk of becoming NEET (Young people not in employment, education, or training). Such youths struggle more with mental health problems than non-NEET peers. Being a refugee, NEET further increases the risk of having mental health problems and may be linked to lower cognitive functioning, which could maintain exclusion and unemployment. This intervention study was performed with a group of young people of different nationalities who were refugees or belonged to other vulnerable groups attending a six-week employability-support intervention in Ecuador. In order to assess the impact of the intervention, a range of measures of executive cognitive function, mental health, and the potential for positive change were used. We found that post-intervention, the group reported significantly less psychological distress and better self-esteem, self-efficacy, and cognitive response inhibition than before the intervention. We conclude that multicomponent interventions may effectively improve the psychological functioning of vulnerable NEET groups in the Latin American context.
Comparative Research and Critical Child Protection Studies
Authors: Parton Nigel Ashmore
Published: April 2022

This article argues that two interrelated factors have played important roles in the emergence of academic analyses of child protection policies and practices: the evidence of growing strains and crises in child protection systems over the last forty years; and the development of comparative research on different systems. The latter has demonstrated that child protection policies and practices vary between different countries such that the differences could not be explained by differences in the nature of child maltreatment in the different societies—other political, social, and cultural factors were at play. This paper outlines the nature of these key developments and the conceptual frameworks which have emerged to explain the differences. A significant positive outcome is that such conceptual frameworks can be drawn upon for furthering our analyses of different policies, practices and systems and their possible reform and improvement.
Mixed-Race Ancestry ≠ Multiracial Identification: The Role Racial Discrimination, Linked Fate, and Skin Tone Have on the Racial Identification of People with Mixed-Race Ancestry
Authors: Gonlin Vanessa
Published: April 2022

Mixed-race identification may be complex, in that people with mixed-race ancestry may or may not identify as multiracial. Social experiences, such as experiencing racial discrimination, believing that your fate is connected with specific racialized others, and personal characteristics, such as skin color, all have been theorized to play a role in identification. The Mixed-Race Ancestry Survey (2019) conducted on Mechanical Turk allows me to ask unique questions with a large enough sample of this understudied population to disaggregate by racial ancestries. Only people with mixed-race ancestry are included in this study, but respondents may identify mono- or multiracially. Binary logistic regression models reveal that increased linked fate with a specific racial group is associated with greater odds of racially identifying, at least in part, with that group (e.g., among Asians, greater linked fate with Asians is associated with greater odds of identifying as mono- or multiracially Asian). Increased linked fate with multiracials as a group is also connected to greater odds of identifying as multiracial. In addition, personally experiencing racial discrimination is associated with a greater likelihood of identifying as Black and slightly lower odds of identifying as White or as Latinx. Finally, as skin tone darkens the odds of identifying as Black increase three-fold and the odds of identifying as multiracial increase by 1.3 times. I discuss these findings by racial ancestry groups, noting that being aware of having mixed-race ancestry does not in and of itself predict multiracial identification. Rather, in a social structure that uplifts Whiteness, feeling linked fate, experiencing discrimination, and having darker skin tone are important predictors of identification. These findings highlight the mechanisms connected to racial identification for a population that may feel tied to multiple racial groups and is navigating identification within a White-centric nation.
Health Crisis and the Dual Reflexivity of Knowledge
Authors: Bernardeau-Moreau Denis
Published: April 2022

Although successive pandemic episodes adversely affect populations and it remains difficult to assess their long-term extent and impact, they may, paradoxically, have a positive effect. In fact, they can promote awareness by reviving a form of reflexivity with respect to public health, economic and social policies, and by driving in-depth reflection on the measures that must be taken to limit the current and future imbalances caused by human activity. Habermas emphasises that the reflexive “push” is no longer just a matter for experts; it is also collective, historical, and political, in the sense that it involves citizens who intend to weigh in on the debate and make their voices and wishes heard by policy-makers and economic actors. Reflecting upon the ethics of responsibility (Weber) is therefore essential. If we are to follow Giddens and Habermas’ thinking, this reflexivity represents an integral part of the modern age. Our intention, in this article, is to show how major events, beyond an initial period of shock, can help to awake different levels of reflexivity in individuals.
A Model for Engaging Students, Faculty, and Communities in Social Action through a Community-Based Curriculum and Admissions Process—A Case Study of the Honors Living-Learning Community at Rutgers University—Newark
Authors: Santana Engelbert , du Plessis Davy , Eatman Timothy
Published: April 2022

The Honors Living-Learning Community (HLLC) at Rutgers University–Newark (RU-N) pushes the boundaries of academia’s possibilities by placing community-engaged scholarship as a critical pillar of student success. Established in 2015, the HLLC is pursuing its triumvirate rallying call—“revolutionizing honors, cultivating talent, and engaging communities”. The HLLC brings together dynamic students passionate about social justice issues, Rutgers University-Newark faculty and staff, and community partners aiming to tackle some of the nation’s most urgent social issues. Pivoting on a curriculum structured around what it means to be a local citizen in a global world, the HLLC brings students and faculty members from every school and college at Rutgers-Newark together with community-based partners to operationalize authentic experiential learning. With its emphasis on social action and issues of inequality, the HLLC brings together the academic sphere and community-based organizations to design and implement projects and courses that promote social justice in the community and enact ameliorative changes based on shared passions and mutual interests. Through a multimodal approach grounded in literature and best practices, the HLLC is built intentionally from the ground up on high-impact practices for student success and the principles of full participation. This paper highlights the HLLC’s efforts to engage students and community members through community-engaged courses and programs to address issues such as inequity. Furthermore, the authors offer a model that actively moves beyond theory to practice-based initiatives within an honor’s academic context. Examples of the HLLC’s initiatives are presented to enhance the discourse around collective knowledge building and community-engaged research by highlighting student and community partner-led initiatives. Given the HLLC’s resolve to develop a national model, the paper dedicates special attention to pedagogy and programs.