bluuebunny/crossref_metadata_2025 huggingface dataset:
In Situ Preparation of Tannic Acid-Modified Poly(N-isopropylacrylamide) Hydrogel Coatings for Boosting Cell Response
Authors: Xu Jufei , Liu Xiangzhe , Liang Pengpeng , Yuan Hailong , Yang Tianyou
Published: April 2024

The improvement of the capability of poly(N-isopropylacrylamide) (PNIPAAm) hydrogel coating in cell adhesion and detachment is critical to efficiently prepare cell sheets applied in cellular therapies and tissue engineering. To enhance cell response on the surface, the amine group-modified PNIPAAm (PNIPAAm-APTES) nanohydrogels were synthesized and deposited spontaneously on tannic acid (TA)-modified polyethylene (PE) plates. Subsequently, TA was introduced onto PNIPAAm-APTES nanohydrogels to fabricate coatings composed of TA-modified PNIPAAm-APTES (PNIPAAm-APTES-TA). Characterization techniques, including TEM, SEM, XPS, and UV-Vis spectroscopy, confirmed the effective deposition of hydrogels of PNIPAAm as well as the morphologies, content of chemical bonding-TA, and stability of various coatings. Importantly, the porous hydrogel coatings exhibited superhydrophilicity at 20 °C and thermo-responsive behavior. The fluorescence measurement demonstrated that the coating’s stability effectively regulated protein behavior, influencing cell response. Notably, cell response tests revealed that even without precise control over the chain length/thickness of PNIPAAm during synthesis, the coatings enhanced cell adhesion and detachment, facilitating efficient cell culture. This work represented a novel and facile approach to preparing bioactive PNIPAAm for cell culture.
Non-Invasive Delivery of Negatively Charged Nanobodies by Anodal Iontophoresis: When Electroosmosis Dominates Electromigration
Authors: Sahraoui Phedra Firdaws , Vadas Oscar , Kalia Yogeshvar N.
Published: April 2024

Iontophoresis enables the non-invasive transdermal delivery of moderately-sized proteins and the needle-free cutaneous delivery of antibodies. However, simple descriptors of protein characteristics cannot accurately predict the feasibility of iontophoretic transport. This study investigated the cathodal and anodal iontophoretic transport of the negatively charged M7D12H nanobody and a series of negatively charged variants with single amino acid substitutions. Surprisingly, M7D12H and its variants were only delivered transdermally by anodal iontophoresis. In contrast, transdermal permeation after cathodal iontophoresis and passive diffusion was <LOQ. The anodal iontophoretic delivery of these negatively charged proteins was achieved because electroosmosis was the dominant electrotransport mechanism. Cutaneous deposition after the anodal iontophoresis of M7D12HWT (wild type), and the R54E and K65E variants, was statistically superior to that after cathodal iontophoresis (6.07 ± 2.11, 9.22 ± 0.80, and 14.45 ± 3.45 μg/cm2, versus 1.12 ± 0.30, 0.72 ± 0.27, and 0.46 ± 0.07 µg/cm2, respectively). This was not the case for S102E, where cutaneous deposition after anodal and cathodal iontophoresis was 11.89 ± 0.87 and 8.33 ± 2.62 µg/cm2, respectively; thus, a single amino acid substitution appeared to be sufficient to impact the iontophoretic transport of a 17.5 kDa protein. Visualization studies using immunofluorescent labeling showed that skin transport of M7D12HWT was achieved via the intercellular and follicular routes.
Comprehensive Therapeutic Approaches to Tuberculous Meningitis: Pharmacokinetics, Combined Dosing, and Advanced Intrathecal Therapies
Authors: Madadi Ahmad Khalid , Sohn Moon-Jun
Published: April 2024

Tuberculous meningitis (TBM) presents a critical neurologic emergency characterized by high mortality and morbidity rates, necessitating immediate therapeutic intervention, often ahead of definitive microbiological and molecular diagnoses. The primary hurdle in effective TBM treatment is the blood–brain barrier (BBB), which significantly restricts the delivery of anti-tuberculous medications to the central nervous system (CNS), leading to subtherapeutic drug levels and poor treatment outcomes. The standard regimen for initial TBM treatment frequently falls short, followed by adverse side effects, vasculitis, and hydrocephalus, driving the condition toward a refractory state. To overcome this obstacle, intrathecal (IT) sustained release of anti-TB medication emerges as a promising approach. This method enables a steady, uninterrupted, and prolonged release of medication directly into the cerebrospinal fluid (CSF), thus preventing systemic side effects by limiting drug exposure to the rest of the body. Our review diligently investigates the existing literature and treatment methodologies, aiming to highlight their shortcomings. As part of our enhanced strategy for sustained IT anti-TB delivery, we particularly seek to explore the utilization of nanoparticle-infused hydrogels containing isoniazid (INH) and rifampicin (RIF), alongside osmotic pump usage, as innovative treatments for TBM. This comprehensive review delineates an optimized framework for the management of TBM, including an integrated approach that combines pharmacokinetic insights, concomitant drug administration strategies, and the latest advancements in IT and intraventricular (IVT) therapy for CNS infections. By proposing a multifaceted treatment strategy, this analysis aims to enhance the clinical outcomes for TBM patients, highlighting the critical role of targeted drug delivery in overcoming the formidable challenges presented by the blood–brain barrier and the complex pathophysiology of TBM.
Transport of Non-Steroidal Anti-Inflammatory Drugs across an Oral Mucosa Epithelium In Vitro Model
Authors: Lin Grace C. , Friedl Heinz-Peter , Grabner Sarah , Gerhartl Anna , Neuhaus Winfried
Published: April 2024

Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most prescribed drugs to treat pain or fever. However, oral administration of NSAIDs is frequently associated with adverse effects due to their inhibitory effect on the constitutively expressed cyclooxygenase enzyme 1 (COX-1) in, for instance, the gastrointestinal tract. A systemic delivery, such as a buccal delivery, of NSAIDs would be beneficial and additionally has the advantage of a non-invasive administration route, especially favourable for children or the elderly. To investigate the transport of NSAIDs across the buccal mucosa and determine their potential for buccal therapeutic usage, celecoxib, diclofenac, ibuprofen and piroxicam were tested using an established oral mucosa Transwell® model based on human cell line TR146. Carboxyfluorescein and diazepam were applied as internal paracellular and transcellular marker molecule, respectively. Calculated permeability coefficients revealed a transport ranking of ibuprofen > piroxicam > diclofenac > celecoxib. Transporter protein inhibitor verapamil increased the permeability for ibuprofen, piroxicam and celecoxib, whereas probenecid increased the permeability for all tested NSAIDs. Furthermore, influence of local inflammation of the buccal mucosa on the transport of NSAIDs was mimicked by treating cells with a cytokine mixture of TNF-α, IL-1ß and IFN-γ followed by transport studies with ibuprofen (+ probenecid). Cellular response to pro-inflammatory stimuli was confirmed by upregulation of cytokine targets at the mRNA level, increased secreted cytokine levels and a significant decrease in the paracellular barrier. Permeability of ibuprofen was increased across cell layers treated with cytokines, while addition of probenecid increased permeability of ibuprofen in controls, but not across cell layers treated with cytokines. In summary, the suitability of the in vitro oral mucosa model to measure NSAID transport rankings was demonstrated, and the involvement of transporter proteins was confirmed; an inflammation model was established, and increased NSAID transport upon inflammation was measured.
The Enjoyment of Being Had: The Aesthetics of Masquerade in The Confidence-Man
Authors: Godley J. Asher
Published: April 2024

Impostors, confidence artists, and artful deceivers seem to have achieved a strange kind of popularity and even prestige in our contemporary political landscape, for reasons that remain elusive, especially given how harmful and socially unwanted such behaviors ostensibly are. Herman Melville’s 1857 novel, The Confidence-Man: His Masquerade, helps us shift our perspective on this seemingly irrational phenomenon because it points out how being susceptible to dupery is linked to the enjoyment of fiction itself. This insight also highlights the importance of epistemological failure in the recent “return to aesthetics” in literary studies, where the positive dimension of unconsciously “willing one’s dupery” directly links aesthetic form to politics. The logic that connects aesthetics to unconscious enjoyment is then elaborated in the work of psychoanalytic thinkers such as Sigmund Freud, Jacques Lacan, Helene Deutsch and others to raise particular questions about how and why the enjoyment of being duped has been associated with feminine sexuality. Reading Melville’s novel while considering psychoanalytic concepts such as the “as if” personality, imposture, and interpassivity illuminates how confidence games play upon the ruses of sexuality, which have profound implications for why the public remains in thrall to the workings of known deceivers.
Evaluating Guayule (Parthenium argentatum A. Gray) Germplasm Grown in Spain: Rubber and Resin along Three Production Cycles
Authors: Jara Francisco Miguel , García-Martínez María de las Mercedes , López-Córcoles Horacio , Carrión María Engracia , Zalacain Amaya , Carmona Manuel
Published: April 2024

Rubber and resin are potentially important products of guayule (Parthenium argentatum A. Gray) that can assure the profitability of this crop as an agricultural alternative for the semi-arid areas of central and eastern Spain. This study analyzes, for the first time, the changes in rubber and resin production across 27 guayule accessions (traditional and modern) and along three cycles under the agroclimatic conditions of Castilla-La Mancha, simulating industrial management with a biannual harvest. The rubber content (% of dry mass) increased from 4.2% in one-year-old plants to 6.6% in two-year-old plants, but decreased after harvesting. Contrastingly, the rubber yield doubled in contiguous sampling, reaching a mean of 303.6 kg ha−1, with a maximum yield of 341.2 kg ha−1 after the first harvest. Three patterns of rubber production were established based on the production periods. A similar analysis was performed for resin production, which was heterogeneous across accessions belonging to the same rubber groups. In this case, three independent groups were established to classify the resin accumulation profiles following the same criteria of production periods. Here, we demonstrate that biannual harvesting has the potential to enhance rubber accumulation in summer, although more research is needed for its adaption to current harvesting techniques in this area.
Assessment of Allelopathic Potential of Cotton Chromosome Substitution Lines
Authors: Segbefia Worlanyo , Singh Varsha , Fuller Mary Gracen , Yue Ziming , Souza Fernanda Reolon de , Tseng Te Ming
Published: April 2024

Weed interference consistently poses a significant agronomic challenge in cotton production, leading to unfavorable direct and indirect consequences. Consequently, the predominant strategy employed to manage weeds is the application of synthetic herbicides. However, this extensive reliance has resulted in the development of herbicide-resistant weed populations due to the prolonged use of a single herbicide and the lack of rotation. This project focused on identifying weed-suppressive cotton chromosome substitution (CS) lines. These CS lines closely resemble the parent TM-1, an upland cotton derivative (Gossypium hirsutum). Each CS line carries a single chromosome or chromosome arm exchanged from G. barbadense, G. tomentosum, or G. mustelinum within the TM-1 background. In a greenhouse experiment utilizing a stepwise approach, five CS lines, along with two conventional varieties (Enlist and UA48) and the parent line (TM1), were assessed to determine their potential for suppressing Palmer amaranth growth. The plant height was measured 7, 14, and 21 days after establishment, and the chlorophyll content was measured 21 days after establishment. The results revealed varying levels of chlorophyll reduction in Palmer amaranth, with the Enlist variety displaying the lowest reduction (32%) and TM-1 exhibiting the highest (78%). Within 14 days of establishment, the CS lines T26lo, BNTN 1-15, and T11sh demonstrated substantial suppression of Palmer amaranth height, with reductions of 79, 70, and 71%, respectively. Conversely, Enlist displayed the least effective performance among the CS lines. Moreover, CS22, CS49, CS50, CS34, UA48, and CS23 displayed a decreasing trend in reducing Palmer amaranth height from 14 to 21 days after establishment. This research demonstrates the inherent herbicidal attributes within cotton CS lines against Palmer amaranth. In light of the versatile applications of cotton fibers and the unique characteristics of the G. hirsutum genome, this study investigates the potential of specific cotton lines in enhancing weed management practices. By elucidating the implications of our findings, we aim to contribute to promoting sustainability and developing alternatives to synthetic herbicides in agricultural systems.
Mechanical Behaviour of As-Manufactured and Repaired Aligned Discontinuous Basalt Fibre-Reinforced Vitrimer Composites
Authors: Messmer Leon L. , Kandemir Ali , Yavuz Burak Ogun , Longana Marco L. , Hamerton Ian
Published: April 2024

The aim of this research is to investigate basalt as a natural mineral-based fibre together with a vitrimeric resin as a sustainable alternative to standard composite materials. Vitrimers combine the properties of thermoset and thermoplastic polymers, enabling the repair of specimens and hence prolonging the lifetime of the composite material. The micro-mechanical characteristics between the basalt fibres and the vitrimer resin are reported and shown to match those of a standard Skyflex K51 epoxy resin. Discontinuous (4 mm) basalt fibres were employed to produce aligned discontinuous fibre-reinforced composites (ADFRCs) using the high-performance discontinuous fibre (HiPerDiF) technology. The mechanical characteristics of the laminates were investigated through tensile testing and the fracture zones were analysed under a scanning electron microscope. By normalising the results by their respective fibre volume fraction, it was discovered that the vitrimer–basalt ADFRCs exhibited, on average, a 4% higher strength and a 25% higher stiffness compared to their basalt epoxy counterparts. The repair potential of the vitrimer ADFRC specimens was explored during low-temperature compression repair. Two approaches were tested using double-sided local- and full-patch repair. Both successfully recovered a significant amount of their prime strength. In conclusion, the potential of the sustainable vitrimer–basalt composite is shown by its competitive mechanical performance. Combining this with the manufacturing flexibility, repair potential, and recyclability of the material, the vitrimer–basalt composite seems to be a competitive alternative to standard glass epoxies.
A Comparative Study of Micromechanical Analysis Models for Determining the Effective Properties of Out-of-Autoclave Carbon Fiber–Epoxy Composites
Authors: Kim Young Cheol , Jang Hong-Kyu , Joo Geunsu , Kim Ji Hoon
Published: April 2024

This study aims to critically assess different micromechanical analysis models applied to carbon-fiber-reinforced plastic (CFRP) composites, employing micromechanics-based homogenization to accurately predict their effective properties. The paper begins with the simplest Voigt and Reuss models and progresses to more sophisticated micromechanics-based models, including the Mori–Tanaka and Method of Cells (MOC) models. It provides a critical review of the areas in which these micromechanics-based models are effective and analyses of their limitations. The numerical analysis results were confirmed through finite element simulations of the periodic representative volume element (RVE). Furthermore, the effective properties predicted by these micromechanics-based models were validated via experiments conducted on IM7/5320-1 composite material with a fiber volume fraction of 0.62.
Comparative Analysis of Physicochemical and Functional Properties of Pectin from Extracted Dragon Fruit Waste by Different Techniques
Authors: Du Huimin , Olawuyi Ibukunoluwa Fola , Said Nurul Saadah , Lee Won-Young
Published: April 2024

Dragon fruit peel, often discarded, is a valuable source of commercial pectin. This study investigates different extraction methods, including cold-water (CW), hot-water (HW), ultrasound (US), and novel enzyme extraction (xylanase: EZX), to extract pectins from dragon fruit peel and compare their characteristics. The pectin yield ranged from 10.93% to 20.22%, with significant variations in physicochemical properties across methods (p < 0.05). FTIR analysis revealed that extraction methods did not alter the primary structural configuration of the pectins. However, molecular weights (Mws) varied significantly, from 0.84 to 1.21 × 103 kDa, and the degree of esterification varied from 46.82% to 51.79% (p < 0.05). Monosaccharide analysis identified both homogalacturonan (HG) and rhamnogalacturonan-I (RG-I) pectic configurations in all pectins, predominantly comprising galacturonic acid (77.21–83.12 %mol) and rhamnose (8.11–9.51 %mol), alongside minor side-chain sugars. These properties significantly influenced pectin functionalities. In the aqueous state, a higher Mw impacted viscosity and emulsification performance, while a lower Mw enhanced antioxidant activities and promoted the prebiotic function of pectin (Lactis brevies growth). This study highlights the impact of extraction methods on dragon fruit peel pectin functionalities and their structure–function relationship, providing valuable insights into predicting dragon fruit peel’s potential as a food-grade ingredient in various products.
Novel Photothermal Graphene-Based Hydrogels in Biomedical Applications
Authors: Croitoru Alexa-Maria , Ficai Denisa , Ficai Anton
Published: April 2024

In the last decade, photothermal therapy (PTT) has attracted tremendous attention because it is non-invasive, shows high efficiency and antibacterial activity, and minimizes drug side effects. Previous studies demonstrated that PTT can effectively inhibit the growth of bacteria and promotes cell proliferation, accelerating wound healing and tissue regeneration. Among different NIR-responsive biomaterials, graphene-based hydrogels with photothermal properties are considered as the best candidates for biomedical applications, due to their excellent properties. This review summarizes the current advances in the development of innovative graphene-based hydrogels for PTT-based biomedical applications. Also, the information about photothermal properties and the potential applications of graphene-based hydrogels in biomedical therapies are provided. These findings provide a great potential for supporting their applications in photothermal biomedicine.
Metal-Assisted Injection Spinning of Ultra Strong Fibers from Megamolecular LC Polysaccharides
Authors: Ali Mohammad Asif , Singh Maninder , Zhang Shuo , Kaneko Daisaku , Okajima Maiko Kaneko , Kaneko Tatsuo
Published: April 2024

The molecular orientation of liquid crystalline (LC) hydrogels has the potential to induce a range of functionalities that can deliver great mechanical strength. Sacran is a supergiant LC polysaccharide isolated from the cyanobacterium Aphanothece sacrum with a high amount of anionic functional groups such as sulfates and carboxylates. In this article, ultra-strong sacran hydrogels and their dried fibers were produced by cross-linking under injection flow with trivalent metal ions such as Al3+, Cr3+, Fe3+, In3+, and rare-earth metal ions such Er3+ and Sr3+. Crossed-polarizing microscopy and X-ray diffraction imaging revealed a uniaxial molecular orientation in the LC gel fiber, resulting in outstanding mechanical characteristics.
Recent Advances in Polymers Bearing Activated Esters for the Synthesis of Glycopolymers by Postpolymerization Modification
Authors: Tanaka Tomonari
Published: April 2024

Glycopolymers are functional polymers with saccharide moieties on their side chains and are attractive candidates for biomaterials. Postpolymerization modification can be employed for the synthesis of glycopolymers. Activated esters are useful in various fields, including polymer chemistry and biochemistry, because of their high reactivity and ease of reaction. In particular, the formation of amide bonds caused by the reaction of activated esters with amino groups is of high synthetic chemical value owing to its high selectivity. It has been employed in the synthesis of various functional polymers, including glycopolymers. This paper reviews the recent advances in polymers bearing activated esters for the synthesis of glycopolymers by postpolymerization modification. The development of polymers bearing hydrophobic and hydrophilic activated esters is described. Although water-soluble activated esters are generally unstable and hydrolyzed in water, novel polymer backbones bearing water-soluble activated esters are stable and useful for postpolymerization modification for synthesizing glycopolymers in water. Dual postpolymerization modification can be employed to modify polymer side chains using two different molecules. Thiolactone and glycine propargyl esters on the polymer backbone are described as activated esters for dual postpolymerization modification.
Reflecting on Evil and the Devil in Pentecostal Theodicy
Authors: Nel Marius
Published: April 2024

Most Pentecostals, at least in the global South, believe that Satan and his demonic forces are responsible for much of the carnage and suffering that characterise life on earth. The broader context of the discourse is the challenge theodicy poses to Christian believers: if God is almighty and good, why do believers, just like unbelievers, suffer while living on earth? This paper aims to discuss Pentecostals’ response: they blame evil as Satan’s strategy to oppose God. They reason that his main goal is to handicap and double-cross creation because God threw him and his followers from heaven following his rebellion against the divine order. Thus, Satan is portrayed as the instigator of the first human couple, tempting them to sin, with all future generations implied by their choice and cursing human beings with a sinful nature at birth. Demonic forces employ human sinful nature to realise their ultimate goal, to separate humankind from the Creator by tempting them to sin while also threatening the rest of creation. This article investigates the Pentecostal theology of demonic forces in explaining the challenges posed by theodicy by comparing it to biblical data, using grammatical-historical exegesis and a comparative literature survey to evaluate their biblical grounding. It concludes that Pentecostals’ belief in such forces are justified if the the New Testament narratives are accepted as divine revelation. However, some Pentecostal speculations about demons’ origins, scope and reach are not biblically justified and complicates the response to theodicy, such as the origin of evil and its relation to human beings.
The Contemporary Shamanic Healing: A Case Study of the Daur Shamanic River Spirit lʊs Ritual
Authors: Sa Minna
Published: April 2024

In traditional shamanism, the sacred mission and responsibility of a shaman is to provide healing and salvation for individuals. Today, with continuous advancements in science, technology, and medical expertise, the content and methods of shamanic healing are quietly evolving, alongside the upholding and preservation of traditional beliefs. The case study of the Daur shamanic lʊs (river spirit) ritual in this paper discusses the concepts of actual disease and virtual disease in contemporary Daur shamanism. By briefly describing the key processes of this ceremony, including the involvement of shaman spirits and the main elements of divine songs, this paper analyzes the characteristics and functions of the modern-day Daur shaman river spirit ceremony. During the ritual dedicated to lʊs, Daur shamans perform symbolic ceremonies while receiving oracles from their spiritual guides. The ceremony itself incorporates various unique healing techniques such as dʊməl, tærmit, xʊræ- xʊræ, arʃan, altəŋ sʊlʊ; kʊtʊr bʊjin, taboo, etc. These distinctive methods aim to achieve preventive healing as well as realistic healing on both the individual and collective levels. In summary, the lʊs ritual itself serves as a transformative process that encompasses diverse forms of healing through its ceremonial practices.
Religion and Loneliness: Investigating Different Aspects of Religion and Dimensions of Loneliness
Authors: Gemar Adam
Published: April 2024

This study explores the relationship between religiosity, spirituality, and loneliness in the United States, using the 2018 General Social Survey to assess their interactions against a backdrop of declining traditional religious affiliation and a rise in “spiritual but not religious” identification. It examines religion and spirituality’s capacity to counteract loneliness, a condition with significant health implications. The analysis uncovers complex relationships between aspects of religious life and loneliness, showing no mitigating role of spirituality when controlling for other factors, with complex and varied negative relationships of religious service attendance and self-rate religiosity to different aspects of loneliness. Yet, any potentially protective effect of religion varies, with minority religious groups reporting feelings of increased loneliness. These findings underscore religion and spirituality’s nuanced roles in emotional well-being, indicating that their benefits (or not) against loneliness are complex, varied, and depend on the aspect of religion or loneliness observed, along with non-religious factors. The paper contributes to the literature on societal loneliness, changing religious and spiritual engagements, and highlighting the need for a comprehensive approach to explore the role of religion and spirituality in understanding loneliness specifically, and personal and social well-being more generally.
Risk Management in the Area of Bitcoin Market Development: Example from the USA
Authors: Janjua Laeeq Razzak , Gigauri Iza , Wójcik-Czerniawska Agnieszka , Pohulak-Żołędowska Elżbieta
Published: April 2024

This paper explores the relationship between Bitcoin returns, the consumer price index, and economic policy uncertainty. Employing the QARDL method, this study examines both short- and long-term dynamics between macroeconomic factors and Bitcoin returns. Our analysis of monthly time series data from January 2011 to November 2023 reveals that volatile US economic policy indicators, such as high economic policy uncertainty, volatile inflation, and rising interest rates, have recently exerted a negative impact on Bitcoin returns. This study shows that these results are true not only for traditional money but also for cryptocurrencies such as Bitcoin, despite their cardinal features. Its decentralized nature, indicating that it has no physical representation, is not tied to any authority or national economy and relies on a complex algorithm to track transactions. Further, it yields volatile returns that depend on macroeconomic indicators.
Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach
Authors: Tian Tian , Yang Kunde , Wu Fei-Yun , Zhang Ying
Published: April 2024

Channel estimation in Underwater Acoustic Communication (UAC) faces significant challenges due to the non-Gaussian, impulsive noise in ocean environments and the inherent high dimensionality of the estimation task. This paper introduces a robust channel estimation algorithm by solving an l1−l1 optimization problem via the Alternating Direction Method of Multipliers (ADMM), effectively exploiting channel sparsity and addressing impulsive noise outliers. A non-monotone backtracking line search strategy is also developed to improve the convergence behavior. The proposed algorithm is low in complexity and has robust performance. Simulation results show that it exhibits a small performance deterioration of less than 1 dB for Channel Impulse Response (CIR) estimation in impulsive noise environments, nearly matching its performance under Additive White Gaussian Noise (AWGN) conditions. For Delay-Doppler (DD) doubly spread channel estimation, it maintains Bit Error Rate (BER) performance comparable to using ground truth channel information in both AWGN and impulsive noise environments. At-sea experimental validations for channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems further underscore the fast convergence speed and high estimation accuracy of the proposed method.
Observation Analysis and Numerical Simulation of the Urban Barrier Effect on Thunderstorm Organization
Authors: Shi Tao , Yang Yuanjian , Lu Gaopeng , Wen Xiangcheng , Liu Lei , Qi Ping
Published: April 2024

The urban underlying surface may affect the thunderstorm process. However, current research on this phenomenon is still in its infancy. This paper aimed to analyze the influence of the urban underlying surface on the evolution of thunderstorm organization through ground observation and numerical simulation. The results indicated that when the thunderstorm system with strong synoptic conditions passed through the built-up area of Beijing, it exhibited obvious bifurcation and detour. The dynamic field of near-surface cold pools could serve as diagnostic indicators for understanding how the urban underlying surface affects the thunderstorm process. The large-scale compact-rise clusters in the city center could alter the movement direction and path of the cold pool outflow, thereby influencing the thunderstorm organization process. In addition to the spatial configuration of the building complex, the city size might also be an important factor influencing the thunderstorm process. This study might provide a fundamental foundation and technical support for predicting and assessing urban thunderstorm disasters.
A Deep Learning Localization Method for Acoustic Source via Improved Input Features and Network Structure
Authors: Sun Dajun , Fu Xiaoying , Teng Tingting
Published: April 2024

Shallow water passive source localization is an essential problem in underwater detection and localization. Traditional matched-field processing (MFP) methods are sensitive to environment mismatches. Many neural network localization methods still have room for improvement in accuracy if they are further adjusted to underwater acoustic characteristics. To address these problems, we propose a deep learning localization method via improved input features and network structure, which can effectively estimate the depth and the closest point of approach (CPA) range of the acoustic source. Firstly, we put forward a feature preprocessing scheme to enhance the localization accuracy and robustness. Secondly, we design a deep learning network structure to improve the localization accuracy further. Finally, we propose a method of visualizing the network to optimize the estimated localization results. Simulations show that the accuracy of the proposed method is better than other compared features and network structures, and the robustness is significantly better than that of the MFP methods. Experimental results further prove the effectiveness of the proposed method.
Automated Camera Pose Generation for High-Resolution 3D Reconstruction of Bridges by Unmanned Aerial Vehicles
Authors: Jung Jan Thomas , Merkle Dominik , Reiterer Alexander
Published: April 2024

This work explores the possibility of automating the aerial survey of bridges to generate high-resolution images necessary for digital damage inspection. High-quality unmanned aerial vehicle (UAV) based 3D reconstruction of bridges is an important step towards autonomous infrastructure inspection. However, the calculation of optimal camera poses remains challenging due to the complex structure of bridges and is therefore often conducted manually. This process is time-consuming and can lead to quality losses. Research in this field to automate this process is yet sparse and often requires high informative models of the bridge as the base for calculations, which are not given widely. Therefore, this paper proposes an automated camera pose calculation method solely based on an easily accessible polygon mesh of the bridge. For safe operation, point cloud data of the environment are used for automated ground detection and obstacle avoidance including vegetation. First, an initial set of camera poses is generated based on a voxelized mesh created in respect to the quality requirements for 3D reconstruction using defined camera specification. Thereafter, camera poses not fulfilling safety distances are removed and specific camera poses are added to increase local coverage quality. Evaluations of three bridges show that for diverse bridge types, near-complete coverage was achieved. Due to the low computational effort of the voxel approach, the runtime was kept to a minimum, even for large bridges. The subsequent algorithm is able to find alternative camera poses even in areas where the optimal pose could not be placed due to obstacles.
A Concrete Core Void Imaging Approach and Parameter Analysis of Concrete-Filled Steel Tube Members Using Travel Time Tomography: Multi-Physics Simulations and Experimental Studies
Authors: Zheng Wenting , Xu Bin , Xia Zongjun , Wang Jiang , Liu Jingliang , Yao Yudi , Wang Yifei
Published: April 2024

Concrete-filled steel tube (CFST) members have been widely used in civil engineering due to their advanced mechanical properties. However, internal defects such as the concrete core voids and interface debonding in CFST structures are likely to weaken their load-carrying capacity and stiffness, which affects the safety and serviceability. Visualizing the inner defects of the concrete cores in CFST members is a critical requirement and a challenging task due to the obvious difference in the material mechanical parameters of the concrete core and steel tube in CFST members. In this study, a curved ray theory-based travel time tomography (TTT) with a least square iterative linear inversion algorithm is first introduced to quantitatively identify and visualize the sizes and positions of the concrete core voids in CFST members. Secondly, a numerical investigation of the influence of different parameters on the inversion algorithm for the defect imaging of CFST members, including the effects of the model weighting matrix, weighting factor and grid size on the void’s imaging quality and accuracy, is carried out. Finally, an experimental study on six CFST specimens with mimicked concrete core void defects is performed in a laboratory and the mimicked defects are visualized. The results demonstrate that TTT can identify the sizes and positions of the concrete core void defects in CFST members efficiently with the use of optimal parameters.
A Feedback Active Control Approach to Road Noise Based on a Single Microphone Sensor to Improve Automotive Cabin Sound Comfort
Authors: Liu Hao , Lee Jaecheon
Published: April 2024

Tire–road noise deteriorates the sound quality of a vehicle’s interior and affects the driving safety and comfort. Obtaining low interior noise is a challenge for passenger car manufacturers. Traditional passive noise control (PNC) is efficient for canceling high frequency noise but not useful for low frequency noise, while active noise control (ANC), according to the residual error signal, can generate an anti-noise signal to reduce the original noise. Most research has focused on improving the control effect for a feedforward ANC system. However, this paper emphasizes a feedback ANC system based on a signal microphone sensor. There are two main contributions in this study to improve automotive cabin sound comfort. One is that the algorithm of the feedback ANC system using a single microphone sensor without a reference noise signal is proposed based on the Filtered-x Least Mean Square method. The other is that the algorithm applies additive random noise online to estimate the secondary path model. A simulation was implemented based on measured real road noise data, and the simulation results indicate that the proposed feedback ANC system with the single microphone sensor can effectively attenuate road noise. This study shows the feasibility of applying a feedback ANC system in automobiles to increase the cabin sound quality.
Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs
Authors: Takahashi Karin , Ueno Hitoshi
Published: April 2024

Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasive and non-restrictive monitoring of vital signs, including the heart rate and respiration, to detect changes in the health status of several elderly individuals. A ballistocardiogram with a piezoelectric sensor was tested using seven individuals. The frequency spectra of the biosignals acquired from the piezoelectric sensors exhibited multiple peaks corresponding to the harmonics originating from the heartbeat. We aimed for individual identification based on the shapes of these peaks as the recognition criteria. The results of individual identification using deep learning techniques revealed good identification proficiency. Altogether, the monitoring system integrated with piezoelectric sensors showed good potential as a personal identification system for identifying individuals with abnormal biological signals.
Optimal Design and Development of Magnetic Field Detection Sensor for AC Power Cable
Authors: Liu Yong , Xin Yuepeng , Huang Youcong , Du Boxue , Huang Xingwang , Su Jingang
Published: April 2024

The state detection of power cables is very important to ensure the reliability of the power supply. Traditional sensors are mostly based on electric field detection. The operation is complex, and its efficiency needs to be improved. This paper optimizes the design and development of the magnetic field detection sensor for AC power cables. First, through the establishment of the magnetic field sensor model, it is determined that permalloy is the material of the magnetic core, the optimal aspect ratio of the magnetic core is 20, and the ratio of coil length to core length is 0.3. Second, the coil-simulation model is established, and it is determined that the optimal number of turns of the coil is 11,000 turns, the diameter of the enameled copper wire is 0.08 mm, and the equivalent magnetic field noise of the sensor is 0.06 pT. Finally, the amplifying circuit based on negative magnetic flux feedback is designed, the sensor is assembled, and the experimental circuit is built for the sensitivity test. The results show that the sensitivity of the magnetic field sensor is 327.6 mV/μT. The sensor designed in this paper has the advantages of small size, high sensitivity, ease of carry, and high reliability.
Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data
Authors: Tan Tan-Hsu , Tian Jia-Hong , Sharma Alok Kumar , Liu Shing-Hong , Huang Yung-Fa
Published: April 2024

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user’s quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU). Initially, radar sensor data are used to generate information related to time and frequency responses using short-time Fourier transform (STFT). Subsequently, the magnitudes and phase values are calculated and fed into the 1D-CNN and Bi-GRU models to extract spatial and temporal features for subsequent model training and activity recognition. Additionally, we propose a simple cross-channel operation (CCO) to facilitate the exchange of magnitude and phase features between parallel convolutional layers. An open dataset collected through radar, named Rad-HAR, is employed for model training and performance evaluation. Experimental results demonstrate that the proposed 1D-CNN+CCO-BiGRU model demonstrated superior performance, achieving an impressive accuracy rate of 98.2%. This outperformance of existing systems with the radar sensor underscores the proposed model’s potential applicability in real-world scenarios, marking a significant advancement in the field of HAR within the IoT framework.
An Intelligent Thermal Compensation System Using Edge Computing for Machine Tools
Authors: Kristiani Endah , Wang Lu-Yan , Liu Jung-Chun , Huang Cheng-Kai , Wei Shih-Jie , Yang Chao-Tung
Published: April 2024

This paper focuses on the use of smart manufacturing in lathe-cutting tool machines, which can experience thermal deformation during long-term processing, leading to displacement errors in the cutting head and damage to the final product. This study uses time-series thermal compensation to develop a predictive system for thermal displacement in machine tools, which is applicable in the industry using edge computing technology. Two experiments were carried out to optimize the temperature prediction models and predict the displacement of five axes at the temperature points. First, an examination is conducted to determine possible variances in time-series data. This analysis is based on the data obtained for the changes in time, speed, torque, and temperature at various locations of the machine tool. Using the viable machine-learning models determined, the study then examines various cutting settings, temperature points, and machine speeds to forecast the future five-axis displacement. Second, to verify the precision of the models created in the initial phase, other time-series models are examined and trained in the subsequent phase, and their effectiveness is compared to the models acquired in the first phase. This work also included training seven models of WNN, LSTNet, TPA-LSTM, XGBoost, BiLSTM, CNN, and GA-LSTM. The study found that the GA-LSTM model outperforms the other three best models of the LSTM, GRU, and XGBoost models with an average precision greater than 90%. Based on the analysis of training time and model precision, the study concluded that a system using LSTM, GRU, and XGBoost should be designed and applied for thermal compensation using edge devices such as the Raspberry Pi.
A Survey of Techniques for Discovering, Using, and Paying for Third-Party IoT Sensors
Authors: Dawod Anas , Georgakopoulos Dimitrios , Jayaraman Prem Prakash , Nirmalathas Ampalavanapillai
Published: April 2024

The Internet of Things (IoT) includes billions of sensors and actuators (which we refer to as IoT devices) that harvest data from the physical world and send it via the Internet to IoT applications to provide smart IoT services and products. Deploying, managing, and maintaining IoT devices for the exclusive use of an individual IoT application is inefficient and involves significant costs and effort that often outweigh the benefits. On the other hand, enabling large numbers of IoT applications to share available third-party IoT devices, which are deployed and maintained independently by a variety of IoT device providers, reduces IoT application development costs, time, and effort. To achieve a positive cost/benefit ratio, there is a need to support the sharing of third-party IoT devices globally by providing effective IoT device discovery, use, and pay between IoT applications and third-party IoT devices. A solution for global IoT device sharing must be the following: (1) scalable to support a vast number of third-party IoT devices, (2) interoperable to deal with the heterogeneity of IoT devices and their data, and (3) IoT-owned, i.e., not owned by a specific individual or organization. This paper surveys existing techniques that support discovering, using, and paying for third-party IoT devices. To ensure that this survey is comprehensive, this paper presents our methodology, which is inspired by Systematic Literature Network Analysis (SLNA), combining the Systematic Literature Review (SLR) methodology with Citation Network Analysis (CNA). Finally, this paper outlines the research gaps and directions for novel research to realize global IoT device sharing.
Strengths Perspective: How Social Work Students Use Mindfulness as a Self-Care Strategy
Authors: Evans Rosalind , Hawley-Bernardez Alicia , Gibbons Greg
Published: April 2024

(1) Background: As helping professionals, social workers are more susceptible to compassion fatigue, vicarious trauma, and burnout due to regular exposure to clients’ trauma, traumatic situations, and heavy caseloads. Social work students also face similar experiences during their field placement as they prepare to enter the profession. In addition, stress, a significant factor affecting academic performance, is prevalent among social work students. Prolonged stress can lead to chronic health conditions, emphasizing the need to develop effective stress management practice techniques. (2) Objective: To examine the impact of a four-week mindfulness strengths-perspective synchronous series and the impact on social work students’ personal strengths, self-care, stress, and coping strategies. (3) Methods: The purpose of this study was to examine social work students’ experiences with using mindfulness from a strengths perspective. Twenty-three (n = 23) social work students participated in a four-week synchronous mindfulness series that incorporated a strengths perspective, focusing on stress reduction and self-care practices. The series consisted of weekly mindfulness activities and writing prompts, concluding with a focus group in the final week. A thematic analysis was utilized to identify key themes. (4) Results: The researchers identified six themes: consistency and commitment, affirmations and self-love, a caring community, mindfulness strategies, physical restoration, and enrichment and learning. (5) Conclusion: Students were able to develop a better understanding of self-care and the benefits of taking time to incorporate practices for their health and wellness.
Sustainable Media and Green Innovation: The Impact of Sustainable Atmosphere and Environmental Regulation on Manufacturing Enterprises
Authors: Yang Yifan , Liu Hongda
Published: April 2024

This study proposes a research framework for media attention towards green innovation of manufacturing enterprises based on the theory of stakeholders and legitimacy. We examine the potential effect of media attention on the manufacturing industry and make a multidimensional heterogeneity analysis with a sample of Chinese manufacturing enterprises during 2011–2019. Our results show an inverted U-shaped relationship between various attentions of media and green innovation. We find that the early attention of the media can expand the green innovation ability of manufacturing enterprises. However, the excessive attention of the media later may decrease the green behavior of enterprises. The legitimacy pressure of media attention on enterprises helps enterprises carry out green innovation and reduce false green innovation activities. In addition, the sustainable construction, environmental regulations, and sustainable social atmosphere focused on by the media will have a positive effect on the green innovation of enterprises. We suggest that recognizing the importance and potential power of sustainable media, environmental regulations, and sustainable atmosphere in green technology is a key component of the ecological inclusive path to promote the achievement of sustainable development goals.