bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Evaluation of an e-Book for Bone Health and Osteoporosis Education in Adolescents
Authors: Mohd Azmi Nur Filzah Insyirah , Aznul Hisham Muhammad Hafiz , Jamil Nor Aini
Published: April 2023

Achieving optimum peak bone mass during adolescence is crucial for lifetime bone health. This study is aimed at developing and assessing an e-book designed for adolescent bone health knowledge and osteoporosis education. A needs assessment was conducted among 43 adolescents, aged 13–16 years, living in urban areas in Malaysia to determine their needs and preference for health educational material. The researchers also searched for relevant guidelines and articles regarding adolescent bone health. Subsequently, an e-book was developed based on the needs assessment and literature search. Five expert panelists (mean work experience = 11.3 years) validated the e-book contents and assessed its understandability and actionability using the Patient Educational Materials Assessment Tool for Audio-Visual Material (PEMAT-A/V). The internet (72.1%), parents (44.2%), television (41.9%), and teachers (39.5%) were the top four sources of health information among the respondents. Magazines (4.6%) and newspapers (11.6%) were the least preferred resources. Most adolescents were interested in cartoon-themed educational materials, and they perceived that including a short video, quiz, and infographic in the educational material would make it much more interactive for users. The developed e-book includes seven infographic chapters, a link to a quiz, and a summary video. The topics cover basic information on bones and the formation and resorption processes, osteoporosis and its risk factors, key nutrients for bone health (calcium and vitamin D), along with their sources and recommended amounts, physical activity and exercise for bone health, and tips for healthy lifestyle practices for bone health. All chapters and the video were rated with a median score of 100% for understandability and actionability, respectively. Some of the comments received from evaluators included that the e-book made good use of infographics, was easy to understand and interesting, and contained well-organized content. Some suggestions for improvement included adding take-home messages relevant to the topic, using colors to highlight keywords, and narrating all points presented in the video. Overall, the newly developed e-book on adolescent bone health was highly rated by expert panelists. However, the acceptance and effectiveness of the e-book in increasing bone health and osteoporosis knowledge among adolescents are yet to be evaluated. The e-book could be used as one of the educational tools to promote bone health in adolescents.
Assessment of the Use of Food Supplements by Military Personnel: Study Protocol and Results
Authors: Pravst Igor , Lavriša Živa , Hristov Hristo , Hribar Maša , Krušič Sanja , Žmitek Katja , Kušar Anita , Zdešar Kotnik Katja , Golja Petra , Čibej Andlovec Anja , Pograjc Larisa
Published: April 2023

Due to their specific mode of operation, military personnel are challenged physically as well as mentally. In most countries, the use of food supplements by military personnel is not regulated, and a high prevalence of supplementation is expected. However, data on this are scarce or very limited, without insights into the importance of supplementation for the intake of bioactive substances. Our goal was, therefore, to develop a study protocol to enable an assessment of the prevalence of using food supplements and an estimate of the contribution of supplementation practices to the dietary intake of specific nutrients and other compounds. The protocol was tested in a study of Slovene Armed Forces (SAF) personnel. Data were collected using an anonymous questionnaire in a sample of 470 participants from different military units—about half from the barracks located across the country, and the other half returning from military operations abroad. To provide meaningful results, we recorded the use of food supplements and functional foods available in single-sized portions (i.e., energy drinks, protein bars, etc.). Altogether, 68% of the participants reported supplementation, most commonly with vitamin, mineral, and protein supplements. Military rank, participation status in military operations, and physical activity were the main determinants of the specific supplements used. Surprisingly, a lower prevalence of overall and protein supplementation was observed in subjects returning from military operations abroad (62 vs. 74%) than in personnel stationed in barracks across Slovenia; however, the frequency of the use of energy drinks and caffeine supplements was higher in this population (25 vs. 11%). The study design allowed for estimations of the daily intake of supplemented bioactive compounds. We describe the challenges and approaches used in the study to support similar studies in the future and within other populations.
CD163 Monoclonal Antibody Modified Polymer Prodrug Nanoparticles for Targeting Tumor-Associated Macrophages (TAMs) to Enhance Anti-Tumor Effects
Authors: Yang Zun , Li Haijiao , Zhang Wenrui , Zhang Mingzu , He Jinlin , Yu Zepeng , Sun Xingwei , Ni Peihong
Published: April 2023

Tumor-associated macrophages (TAMs)-based immunotherapy is a promising strategy. Since TAMs are mainly composed of M2-type macrophages, they have a promoting effect on tumor growth, invasion, and metastasis. M2-type macrophages contain a specific receptor CD163 on their surface, providing a prerequisite for active targeting to TAMs. In this study, we prepared CD163 monoclonal antibody modified doxorubicin-polymer prodrug nanoparticles (abbreviated as mAb-CD163-PDNPs) with pH responsiveness and targeted delivery. First, DOX was bonded with the aldehyde group of a copolymer by Schiff base reaction to form an amphiphilic polymer prodrug, which could self-assemble into nanoparticles in the aqueous solution. Then, mAb-CD163-PDNPs were generated through a “Click” reaction between the azide group on the surface of the prodrug nanoparticles and dibenzocyclocytyl-coupled CD163 monoclonal antibody (mAb-CD163-DBCO). The structure and assembly morphology of the prodrug and nanoparticles were characterized by 1H NMR, MALDI-TOF MS, FT-IR UV-vis spectroscopy, and dynamic light scattering (DLS). In vitro drug release behavior, cytotoxicity, and cell uptake were also investigated. The results show that the prodrug nanoparticles have regular morphology and stable structure, especially mAb-CD163-PDNPs, which can actively target TAMs at tumor sites, respond to the acidic environment in tumor cells, and release drugs. While depleting TAMs, mAb-CD163-PDNPs can actively enrich drugs at the tumor site and have a strong inhibitory effect on TAMs and tumor cells. The result of the in vivo test also shows a good therapeutic effect, with a tumor inhibition rate of 81%. This strategy of delivering anticancer drugs in TAMs provides a new way to develop targeted drugs for immunotherapy of malignant tumors.
Formulation and Characterization of Epalrestat-Loaded Polysorbate 60 Cationic Niosomes for Ocular Delivery
Authors: Kattar Axel , Quelle-Regaldie Ana , Sánchez Laura , Concheiro Angel , Alvarez-Lorenzo Carmen
Published: April 2023

The aim of this work was to develop niosomes for the ocular delivery of epalrestat, a drug that inhibits the polyol pathway and protects diabetic eyes from damage linked to sorbitol production and accumulation. Cationic niosomes were made using polysorbate 60, cholesterol, and 1,2-di-O-octadecenyl-3-trimethylammonium propane. The niosomes were characterized using dynamic light scattering, zeta-potential, and transmission electron microscopy to determine their size (80 nm; polydispersity index 0.3 to 0.5), charge (−23 to +40 mV), and shape (spherical). The encapsulation efficiency (99.76%) and the release (75% drug release over 20 days) were measured with dialysis. The ocular irritability potential (non-irritating) was measured using the Hen’s Egg Test on the Chorioallantoic Membrane model, and the blood glucose levels (on par with positive control) were measured using the gluc-HET model. The toxicity of the niosomes (non-toxic) was monitored using a zebrafish embryo model. Finally, corneal and scleral permeation was assessed with the help of Franz diffusion cells and confirmed with Raman spectroscopy. Niosomal permeation was higher than an unencapsulated drug in the sclera, and accumulation in tissues was confirmed with Raman. The prepared niosomes show promise to encapsulate and carry epalrestat through the eye to meet the need for controlled drug systems to treat the diabetic eye.
Spectra of a Bragg Microresonator Filled with a Graphene-Containing Medium
Authors: Fedorova Irina V. , Eliseeva Svetlana V. , Sementsov Dmitrij I.
Published: April 2023

Transmission spectra of a symmetric microresonator structure, with dielectric Bragg mirrors, are obtained. The working cavity of the structure is partially filled by a layer of a quarter-wave thickness of finely layered “graphene–semiconductor” medium, with material parameters controlled by external electric and magnetic fields. It is shown, that the transformation of the spectra is achieved both by changing the energy state of the graphene layers and by changing the external magnetic field. The spectral characteristics for the inverted and doped states of graphene layers are established.
High Efficiency and High Stability for SHG in an Nd:YVO4 Laser with a KTP Intracavity and Q-Switching through Harmonic Modulation
Authors: Afanador Delgado Samuel Mardoqueo , García López Juan Hugo , Reátegui Rider Jaimes , Aboites Vicente , Echenausía Monroy José Luis , Huerta Cuellar Guillermo
Published: April 2023

In this paper, the stabilization and high efficiency of an unstable Second Harmonic Generation (SHG) of an Nd:YVO4 laser with a KTP intracavity is demonstrated. By using a passive Q-switching crystal (Cr4+:YAG) and a parametric modulation method (harmonic modulation), the stabilization of the laser is reached. An harmonic modulation was applied to the pumping of the Nd:YVO4-KTP laser to control the amplitude and frequency of the laser emission. The results were characterized by using power spectra analysis, optical spectrum, bifurcation diagrams, and temporal series of the laser intensity. The promising application of this green light source is materialized when such light is necessary for high-density optics, such as in the treatment materials industry or in some aesthetic applications.
On the Suitability of Phosphonate-Containing Polyamidoamines as Cotton Flame Retardants
Authors: Beduini Alessandro , Albanese Domenico , Carosio Federico , Manfredi Amedea , Ranucci Elisabetta , Ferruti Paolo , Alongi Jenny
Published: April 2023

A novel polyamidoamine (M-PCASS) bearing a disulfide group and two phosphonate groups per repeat unit was obtained by reacting N,N′-methylenebisacrylamide with a purposely designed bis-sec-amine monomer, namely, tetraethyl(((disulfanediylbis(ethane-2,1-diyl))bis(azanediyl))bis(ethane-2,1-diyl))bis(phosphonate) (PCASS). The aim was to ascertain whether the introduction of phosphonate groups, well-known for inducing cotton charring in the repeat unit of a disulfide-containing PAA, increased its already remarkable flame retardant efficacy for cotton. The performance of M-PCASS was evaluated by different combustion tests, choosing M-CYSS, a polyamidoamine containing a disulfide group but no phosphonate groups, as a benchmark. In horizontal flame spread tests (HFSTs), M-PCASS was a more effective flame retardant than M-CYSS at lower add-ons with no afterglow. In vertical flame spread tests, the only effect was afterglow suppression with no self-extinguishment even at add-ons higher than in HFSTs. In oxygen-consumption cone calorimetry tests, M-PCASS decreased the heat release rate peak of cotton by 16%, the CO2 emission by 50%, and the smoke release by 83%, leaving a 10% residue to be compared with a negligible residue for untreated cotton. Overall, the set of results obtained envisage that the newly synthesized phosphonate-containing PAA M-PCASS may be suitable for specific applications as flame retardant, where smoke suppression or reduction of total gas released is a key requirement.
Silk/Polyamidoamine Membranes for Removing Chromium VI from Water
Authors: Ferruti Paolo , Alongi Jenny , Barabani Emanuele , Manfredi Amedea , Ranucci Elisabetta
Published: April 2023

Polyamidoamine hydrogels prepared by the radical post-polymerization of α,ω-bisacrylamide-terminated M-AGM oligomers, in turn obtained by the polyaddition of 4-aminobutylguanidine with N,N’-methylenebisacrylamide, were reinforced with raw silk fibers, which can establish covalent bonds with the polyamidoamine matrix via reaction of the amine groups in the lysine residues with the acrylamide terminals of the M-AGM oligomer. Silk/M-AGM membranes were prepared by impregnating silk mats with M-AGM aqueous solutions and subsequent crosslinking by UV irradiation. The guanidine pendants of the M-AGM units imparted the ability to form strong but reversible interactions with oxyanions, including the highly toxic chromate ions. The potential of the silk/M-AGM membranes to purify Cr(VI)-contaminated water down to the drinkability level, that is, below 50 ppb, was tested by performing sorption experiments both in static (Cr(VI) concentration 20–2.5 ppm) and flow conditions (Cr(VI) concentration 10–1 ppm). After static sorption experiments, the Cr(VI)-loaded silk/M-AGM membranes could easily be regenerated via treatment with a 1 M sodium hydroxide solution. Dynamic tests performed using two stacked membranes and a 1 ppm Cr(VI) aqueous solution reduced Cr(VI) concentration down to 4 ppb. Remarkably, the use of renewable sources, the environmentally friendly preparation process, and the goal achieved meet eco-design requirements.
Stabilization and Valorization of Beer Bagasse to Obtain Bioplastics
Authors: Castro-Criado Daniel , Abdullah Johar Amin Ahmed , Romero Alberto , Jiménez-Rosado Mercedes
Published: April 2023

Beer bagasse is a residue produced in large quantities, though it is undervalued in the industry. Its high protein and polysaccharide content make it attractive for use in sectors such as the manufacture of bioplastics. However, its high water content makes it necessary to stabilize it before being considered as a raw material. The main objective of this work was to evaluate the stabilization of beer bagasse and the production of bioplastics from it. In this sense, different drying methods (freeze-drying and heat treatment at 45 and 105 °C) were studied. The bagasse was also characterized physicochemically to evaluate its potential. In addition, bagasse was used in combination with glycerol (plasticizer) to make bioplastics by injection molding, analyzing their mechanical properties, water absorption capacity and biodegradability. The results showed the great potential of bagasse, presenting a high content of proteins (18–20%) and polysaccharides (60–67%) after its stabilization, with freeze-drying being the most suitable method to avoid its denaturation. Bioplastics present appropriate properties for use in applications such as horticulture and agriculture.
Green Preparation of Lightweight, High-Strength Cellulose-Based Foam and Evaluation of Its Adsorption Properties
Authors: Zhou Yongxing , Yin Wenbo , Guo Yuliang , Qin Chenni , Qin Yizheng , Liu Yang
Published: April 2023

In recent years, the application scope of most cellulose-based foams is limited due to their low adsorbability and poor recyclability. In this study, a green solvent is used to extract and dissolve cellulose, and the structural stability of the solid foam is enhanced by adding a secondary liquid via the capillary foam technology, and the strength of the solid foam is improved. In addition, the effects of the addition of different gelatin concentrations on the micro-morphology, crystal structure, mechanical properties, adsorption, and recyclability of the cellulose-based foam are investigated. The results show that the cellulose-based foam structure becomes compact, the crystallinity is decreased, the disorder is increased, and the mechanical properties are improved, but its circulation capacity is decreased. When the volume fraction of gelatin is 2.4%, the mechanical properties of foam are the best. The stress of the foam is 55.746 kPa at 60% deformation, and the adsorption capacity reaches 57.061 g/g. The results can serve as a reference for the preparation of highly stable cellulose-based solid foams with excellent adsorption properties.
Hybrid Steel/NSM/GFRP System Versus GFRP Wrapping for Upgrading RC Wall-like Columns
Authors: Elsanadedy Hussein , Abbas Husain , Siddiqui Nadeem , Almusallam Tarek , Al-Salloum Yousef
Published: April 2023

Reinforced concrete (RC) wall-like columns are commonly employed in structures in Saudi Arabia. These columns are preferred by architects owing to their minimum projection in the usable space. However, they often need strengthening due to several reasons, such as the addition of more stories and increasing the live load as a result of changing the usage of the building. This research aimed to obtain the best scheme for the axial strengthening of RC wall-like columns. The challenge in this research is to develop strengthening schemes for RC wall-like columns, which are favored by architects. Accordingly, these schemes were designed so that the dimensions of the column cross-section are not increased. In this regard, six wall-like columns were experimentally examined in the event of axial compression with zero eccentricity. Two specimens were not retrofitted to be used as control columns, whereas four specimens were retrofitted with four schemes. The first scheme incorporated traditional glass fiber-reinforced polymer (GFRP) wrapping, while the second one utilized GFRP wrapping combined with steel plates. The last two schemes involved the addition of near-surface mounted (NSM) steel bars combined with GFRP wrapping and steel plates. The strengthened specimens were compared with regard to axial stiffness, maximum load, and dissipated energy. Besides column testing, two analytical approaches were suggested for computing the axial capacity of tested columns. Moreover, finite element (FE) analysis was performed for evaluating the axial load versus displacement response of tested columns. As an outcome of the study, the best strengthening scheme was proposed to be used by practicing engineers for axial upgrading of wall-like columns.
Thermal Stability and Non-Isothermal Kinetic Analysis of Ethylene–Propylene–Diene Rubber Composite
Authors: Alfannakh Huda , Alnaim Nisrin , Ibrahim Sobhy S.
Published: April 2023

The purpose of this study was to investigate the thermal stability and the decomposition kinetics of ethylene–propylene–diene monomer (EPDM) composite samples loaded with and without lead powder (50, 100, and 200 phr lead) using thermogravimetric analysis (TGA). TGA was carried out at different heating rates (5, 10, 20, and 30 °C/min) under inert conditions in the temperature range of 50–650 °C. Lead addition did not significantly change the onset temperature or peak position corresponding to the maximum decomposition rate of the first derivative of the TGA curve (DTGA) (onset at about 455 °C and Tm at about 475 °C). Peak separation for the DTGA curves indicated that the main decomposition region for EPDM, the host rubber, overlapped the main decomposition region for volatile components. The decomposition activation energy (Ea) and pre-exponent factor (A) were estimated using the Friedman (FM), Kissinger–Akahira–Sunose (KAS), and Flynn–Wall–Ozawa (FWO) iso-conversional methods. Average activation energy values of around 231, 230, and 223 kJ/mol were obtained for the EPDM host composite using the FM, FWO, and KAS methods, respectively. For a sample loaded with 100 phr lead, the average activation energy values obtained via the same three methods were 150, 159, and 155 kJ/mole, respectively. The results obtained from the three methods were compared with results obtained using the Kissinger and Augis–Bennett/Boswell methods, and strong convergence was found among the results of the five methods. A significant change in the entropy of the sample was detected with the addition of lead powder. For the KAS method, the change in entropy, ΔS, was −3.7 for EPDM host rubber and −90 for a sample loaded with 100 phr lead, α = 0.5.
Folic Acid Adjustive Polydopamine Organic Nanoparticles Based Fluorescent Probe for the Selective Detection of Mercury Ions
Authors: Chen Lijuan , Chen Changchang , Yan Yehan , Yang Linlin , Liu Renyong , Zhang Jiajia , Zhang Xin , Xie Chenggen
Published: April 2023

Polydopamine fluorescent organic nanomaterials present unique physicochemical and biological properties, which have great potential application in bio-imaging and chemical sensors. Here, folic acid (FA) adjustive polydopamine (PDA) fluorescent organic nanoparticles (FA-PDA FONs) were prepared by a facile one-pot self-polymerization strategy using dopamine (DA) and FA as precursors under mild conditions. The as-prepared FA-PDA FONs had an average size of 1.9 ± 0.3 nm in diameter with great aqueous dispersibility, and the FA-PDA FONs solution exhibit intense blue fluorescence under 365 nm UV lamp, and the quantum yield is ~8.27%. The FA-PDA FONs could be stable in a relatively wide pH range and high ionic strength salt solution, and the fluorescence intensities are constant. More importantly, here we developed a method for rapidly selective and sensitive detection of mercury ions (Hg2+) within 10 s using FA-PDA FONs based probe, the fluorescence intensities of FA-PDA FONs presented a great linear relationship to Hg2+ concentration, the linear range and limit of detection (LOD) were 0–18 µM and 0.18 µM, respectively. Furthermore, the feasibility of the developed Hg2+ sensor was verified by determination of Hg2+ in mineral water and tap water samples with satisfactory results.
Effects of Accelerated Aging on Thermal, Mechanical and Shape Memory Properties of Cyanate-Based Shape Memory Polymer: III Vacuum Thermal Cycling
Authors: Ping Zhongxin , Xie Fang , Gong Xiaobo , Liu Liwu , Leng Jinsong , Liu Yanju
Published: April 2023

Shape memory polymers (SMPs) with intelligent deformability have shown great potential in the field of aerospace, and the research on their adaptability to space environments has far-reaching significance. Chemically cross-linked cyanate-based SMPs (SMCR) with excellent resistance to vacuum thermal cycling were obtained by adding polyethylene glycol (PEG) with linear polymer chains to the cyanate cross-linked network. The low reactivity of PEG overcame the shortcomings of high brittleness and poor deformability while endowing cyanate resin with excellent shape memory properties. The SMCR with a glass transition temperature of 205.8 °C exhibited good stability after vacuum thermal cycling. The SMCR maintained a stable morphology and chemical composition after repeated high–low temperature cycle treatments. The SMCR matrix was purified by vacuum thermal cycling, which resulted in an increase in its initial thermal decomposition temperature by 10–17 °C. The continuous vacuum high and low temperature relaxation of the vacuum thermal cycling increased the cross-linking degree of the SMCR, which improved the mechanical properties and thermodynamic properties of SMCR: the tensile strength of SMCR was increased by about 14.5%, the average elastic modulus was greater than 1.83 GPa, and the glass transition temperature increased by 5–10 °C. Furthermore, the shape memory properties of SMCR after vacuum thermal cycling treatment were well maintained due to the stable triazine ring formed by the cross-linking of cyanate resin. This revealed that our developed SMCR had good resistance to vacuum thermal cycling and thus may be a good candidate for aerospace engineering.
Magneto-Mechanical and Thermal Properties of Nd-Fe-B-Epoxy-Bonded Composite Materials
Authors: Grujić Aleksandar , Nedeljković Dragutin , Stajić-Trošić Jasna , Stijepović Mirko Z. , Alnouri Sabla , Perišić Srdjan
Published: April 2023

Polymer-bonded magnets are a class of composite material that combines the magnetic properties of metal particles and the molding possibility of a polymeric matrix. This class of materials has shown huge potential for various applications in industry and engineering. Traditional research in this field has so far mainly focused on mechanical, electrical or magnetic properties of the composite, or on particle size and distribution. This examination of synthesized Nd-Fe-B-epoxy composite materials includes the mutual comparison of impact toughness, fatigue, and the structural, thermal, dynamic-mechanical, and magnetic behavior of materials with different content of magnetic Nd-Fe-B particles, in a wide range from 5 to 95 wt.%. This paper tests the influence of the Nd-Fe-B content on impacting the toughness of the composite material, as this relationship has not been tested before. The results show that impact toughness decreases, while magnetic properties increase, along with increasing content of Nd-Fe-B. Based on the observed trends, selected samples have been analyzed in terms of crack growth rate behavior. Analysis of the fracture surface morphology reveals the formation of a stable and homogeneous composite material. The synthesis route, the applied methods of characterization and analysis, and the comparison of the obtained results can provide a composite material with optimum properties for a specific purpose.
The Titles of the High Priest of Jerusalem in the Pre-Hasmonean Period
Authors: Nihan Christophe
Published: April 2023

This article studies the main titles documented for the high priest of Jerusalem in the Hebrew Bible as well as in a few other sources from the Persian and Hellenistic periods. In dialogue with recent scholarship on the topic, particularly an important article by Noam Mizrahi it argues that the title הכהן הגדול (ha-kohēn ha-gādôl), “high” or “great priest” probably originates in the late monarchic period (seventh century BCE), but only became the standard designation for the high priest during the fifth century BCE. An alternative title, כהן הראש (kohēn ha-ro’š), “head” or “chief” priest, was introduced in Chronicles and other writings in order to designate the high priests of the preexilic period specifically. Finally, a third title, המשיח (ha-kohēn ha-māšîaḥ), “the anointed priest”, was used for some time in priestly circles as part of a bid to transfer a key royal attribute (anointment) to the high priest of Jerusalem, but was eventually replaced with the more standard designation הכהן הגדול.
A Fine-Grained Ship-Radiated Noise Recognition System Using Deep Hybrid Neural Networks with Multi-Scale Features
Authors: Liu Shuai , Fu Xiaomei , Xu Hong , Zhang Jiali , Zhang Anmin , Zhou Qingji , Zhang Hao
Published: April 2023

Fine-grained ship-radiated noise recognition methods of different specific ships are in demand for maritime traffic safety and general security. Due to the high background noise and complex transmission channels in the marine environment, the accurate identification of ship radiation noise becomes quite complicated. Existing ship-radiated noise-based recognition systems still have some shortcomings, such as the imperfection of ship-radiated noise feature extraction and recognition algorithms, which lead to distinguishing only the type of ships rather than identifying the specific vessel. To address these issues, we propose a fine-grained ship-radiated noise recognition system that utilizes multi-scale features from the amplitude–frequency–time domain and incorporates a multi-scale feature adaptive generalized network (MFAGNet). In the feature extraction process, to cope with highly non-stationary and non-linear noise signals, the improved Hilbert–Huang transform algorithm applies the permutation entropy-based signal decomposition to perform effective decomposition analysis. Subsequently, six learnable amplitude–time–frequency features are extracted by using six-order decomposed signals, which contain more comprehensive information on the original ship-radiated noise. In the recognition process, MFAGNet is designed by applying unique combinations of one-dimensional convolutional neural networks (1D CNN) and long short-term memory (LSTM) networks. This architecture obtains regional high-level information and aggregate temporal characteristics to enhance the capability to focus on time–frequency information. The experimental results show that MFAGNet is better than other baseline methods and achieves a total accuracy of 98.89% in recognizing 12 different specific noises from ShipsEar. Additionally, other datasets are utilized to validate the universality of the method, which achieves the classification accuracy of 98.90% in four common types of ships. Therefore, the proposed method can efficiently and accurately extract the features of ship-radiated noises. These results suggest that our proposed method, as a novel underwater acoustic recognition technology, is effective for different underwater acoustic signals.
SSANet: An Adaptive Spectral–Spatial Attention Autoencoder Network for Hyperspectral Unmixing
Authors: Wang Jie , Xu Jindong , Chong Qianpeng , Liu Zhaowei , Yan Weiqing , Xing Haihua , Xing Qianguo , Ni Mengying
Published: April 2023

Convolutional neural-network-based autoencoders, which can integrate the spatial correlation between pixels well, have been broadly used for hyperspectral unmixing and obtained excellent performance. Nevertheless, these methods are hindered in their performance by the fact that they treat all spectral bands and spatial information equally in the unmixing procedure. In this article, we propose an adaptive spectral–spatial attention autoencoder network, called SSANet, to solve the mixing pixel problem of the hyperspectral image. First, we design an adaptive spectral–spatial attention module, which refines spectral–spatial features by sequentially superimposing the spectral attention module and spatial attention module. The spectral attention module is built to select useful spectral bands, and the spatial attention module is designed to filter spatial information. Second, SSANet exploits the geometric properties of endmembers in the hyperspectral image while considering abundance sparsity. We significantly improve the endmember and abundance results by introducing minimum volume and sparsity regularization terms into the loss function. We evaluate the proposed SSANet on one synthetic dataset and four real hyperspectral scenes, i.e., Samson, Jasper Ridge, Houston, and Urban. The results indicate that the proposed SSANet achieved competitive unmixing results compared with several conventional and advanced unmixing approaches with respect to the root mean square error and spectral angle distance.
Range-Doppler Based Moving Target Image Trace Analysis Method in Circular SAR
Authors: Shen Wenjie , Wang Yanping , Lin Yun , Li Yang , Jiang Wen , Hong Wen
Published: April 2023

The single channel Circular Synthetic Aperture Radar (CSAR) has the advantage of continuous surveillance of a fixed scene of interest, which can provide high frame rate image sequences to detect ground moving targets. Recent image-sequence-based CSAR moving target detection methods utilize the fact that the target signal moves fast in the image sequence. Knowledge of the target’s image trace(moving trace in the image sequence, which is equal to a target signature’s morphology in a full aperture CSAR image) can help design better detection methods. However, previous signature morphology studies are based on linear track geometry assumptions, which cannot handle CSAR’s nonlinear track. Hence, this paper proposes a new image trace method based on the range-Doppler principle. The proposed method can deduct the exact analytic function of an arbitrary moving target’s image trace in CSAR. The method assumes radar operates in side-looking mode and that the target moves on the ground plane. It combines the range-Doppler equations(i.e., iso-range and iso-Doppler relation) and Cartesian transformation between the ground and radar coordinate system to obtain the parametric functions of the image trace. Based on the method, three types of target motion (including linear and nonlinear motion) are analyzed. The proposed method is validated with both simulated and real data.
Driving Mechanism of Differentiation in Urban Thermal Environment during Rapid Urbanization
Authors: Ji Yifeng , Peng You , Li Zhitao , Li Jiang , Liu Shaobo , Cai Xiaoxi , Yin Yicheng , Feng Tao
Published: April 2023

To achieve sustainable urban development, it is essential to gain insight into the spatial and temporal differentiation characteristics and the driving mechanisms of the urban thermal environment (UTE). As urbanization continues to accelerate, human activity and landscape configuration and composition interact to complicate the UTE. However, the differences in UTE-driven mechanisms at different stages of urbanization remain unclear. In this study, the UTE of Shenyang was measured quantitatively by using the land surface temperature (LST). The spatial and temporal differentiation characteristics were chronologically studied using the standard deviation ellipse (SDE) and hotspot analysis (Getis–Ord Gi*). Then, the relationship between human activities, landscape composition and landscape configuration and LST was explored in a hierarchical manner by applying the geographical detector. The results show that the UTE in Shenyang continues to deteriorate with rapid urbanization, with significant spatial and temporal differentiation characteristics. The class-level landscape configuration is more important than that at the landscape level when studying UTE-driven mechanisms. At the class level, the increased area and abundance of cropland can effectively reduce LST, while those of impervious surfaces can increase LST. At the landscape level, LST is mainly influenced by landscape composition and human activities. Due to rapid urbanization, the nonlinear relationship between most drivers and LST shifts to near-linear. In the later stage of urbanization, more attention needs to be paid to the effect of the interaction of drivers on LST. At the class level, the interaction between landscape configuration indices for impervious surfaces, cropland and water significantly influenced LST. At the landscape level, the interactions among the normalized difference building index (NDBI) and other selected factors are significant. The findings of this study can contribute to the development of urban planning strategies to optimize the UTE for different stages of urbanization.
A Cross-View Image Matching Method with Feature Enhancement
Authors: Rao Ziyu , Lu Jun , Li Chuan , Guo Haitao
Published: April 2023

Most cross-view image matching algorithms focus on designing network structures with excellent performance, ignoring the content information of the image. At the same time, there are non-fixed targets such as cars, ships, and pedestrians in ground perspective images and aerial perspective images. Differences in perspective, direction, and scale cause serious interference with the cross-view matching process. This paper proposes a cross-view image matching method with feature enhancement, which first transforms the empty image to generate a transformation image aligned with the ground–aerial image domain to establish a preliminary geometric correspondence between the ground-space image. Then, the rich feature information of the deep network and the edge information of the cross-convolution layer are used to establish the feature correspondence between the ground-space images. The feature fusion module enhances the tolerance of the network model to scale differences, improving the interference problem of transient non-fixed targets on the matching performance in the images. Finally, the maximum pooling and feature aggregation strategies are adopted to aggregate local features with obvious distinguishability into global features to complete the accurate matching between ground images. The experimental results show that the proposed method has good advance and high accuracy on CVUSA, which is commonly used in public datasets, reaching 92.23%, 98.47%, and 99.74% on the top 1, top 5 and top 10 indicators, respectively, outperforming the original method in the dataset with a limited field of view and image center, better completing the cross-perspective image matching task.
An Indoor Fingerprint Positioning Algorithm Based on WKNN and Improved XGBoost
Authors: Lu Haizhao , Zhang Lieping , Chen Hongyuan , Zhang Shenglan , Wang Shoufeng , Peng Huihao , Zou Jianchu
Published: April 2023

Considering the low indoor positioning accuracy and poor positioning stability of traditional machine-learning algorithms, an indoor-fingerprint-positioning algorithm based on weighted k-nearest neighbors (WKNN) and extreme gradient boosting (XGBoost) was proposed in this study. Firstly, the outliers in the dataset of established fingerprints were removed by Gaussian filtering to enhance the data reliability. Secondly, the sample set was divided into a training set and a test set, followed by modeling using the XGBoost algorithm with the received signal strength data at each access point (AP) in the training set as the feature, and the coordinates as the label. Meanwhile, such parameters as the learning rate in the XGBoost algorithm were dynamically adjusted via the genetic algorithm (GA), and the optimal value was searched based on a fitness function. Then, the nearest neighbor set searched by the WKNN algorithm was introduced into the XGBoost model, and the final predicted coordinates were acquired after weighted fusion. As indicated in the experimental results, the average positioning error of the proposed algorithm is 1.22 m, which is 20.26–45.58% lower than that of traditional indoor positioning algorithms. In addition, the cumulative distribution function (CDF) curve can converge faster, reflecting better positioning performance.
Application-Layer Time Synchronization and Data Alignment Method for Multichannel Biosignal Sensors Using BLE Protocol
Authors: Li Jianan , Quintin Eric , Wang He , McDonald Benjamin E. , Farrell Todd R. , Huang Xinming , Clancy Edward A.
Published: April 2023

Wearable wireless biomedical sensors have emerged as a rapidly growing research field. For many biomedical signals, multiple sensors distributed about the body without local wired connections are required. However, designing multisite systems at low cost with low latency and high precision time synchronization of acquired data is an unsolved problem. Current solutions use custom wireless protocols or extra hardware for synchronization, forming custom systems with high power consumption that prohibit migration between commercial microcontrollers. We aimed to develop a better solution. We successfully developed a low-latency, Bluetooth low energy (BLE)-based data alignment method, implemented in the BLE application layer, making it transferable between manufacturer devices. The time synchronization method was tested on two commercial BLE platforms by inputting common sinusoidal input signals (over a range of frequencies) to evaluate time alignment performance between two independent peripheral nodes. Our best time synchronization and data alignment method achieved absolute time differences of 69 ± 71 μs for a Texas Instruments (TI) platform and 477 ± 490 μs for a Nordic platform. Their 95th percentile absolute errors were more comparable—under 1.8 ms for each. Our method is transferable between commercial microcontrollers and is sufficient for many biomedical applications.
A Magnetic Levitation System for Range/Sensitivity-Tunable Measurement of Density
Authors: Yu Junhui , Li Donghai , Zhu Chengxian , Ouyang Qiran , Miao Chunyang , Yu Haidong
Published: April 2023

Magnetic levitation (MagLev) is a promising density-based analytical technique with numerous applications. Several MagLev structures with different levels of sensitivity and range have been studied. However, these MagLev structures can seldom satisfy the different performance requirements simultaneously, such as high sensitivity, wide measurement range, and easy operation, which have prevented them from being widely used. In this work, a tunable MagLev system was developed. It is confirmed by numerical simulation and experiments that this system possesses a high resolution down to 10−7 g/cm3 or even higher compared to the existing systems. Meanwhile, the resolution and range of this tunable system can be adjusted to meet different requirements of measurement. More importantly, this system can be operated simply and conveniently. This bundle of characteristics demonstrates that the novel tunable MagLev system could be handily applied in various density-based analyses on demand, which would greatly expand the ability of MagLev technology.
Micro-Leakage Image Recognition Method for Internal Detection in Small, Buried Gas Pipelines
Authors: Zhao Yuxin , Su Zhong , Zhao Hui
Published: April 2023

In order to resolve the problem that the sample of image for internal detection of DN100 buried gas pipeline microleakage is single and difficult to identify, a recognition method of microleakage image of the pipeline internal detection robot is proposed. First, nongenerative data augmentation is used to expand the microleakage images of gas pipelines. Secondly, a generative data augmentation network, Deep Convolutional Wasserstein Generative Adversarial Networks (DCWGANs), is designed to generate microleakage images with different features for detection in the pipeline of gas pipelines to achieve sample diversity of microleakage images of gas pipelines. Then, a bi-directional feature pyramid network (BiFPN) is introduced into You Only Look Once (YOLOv5) to retain more deep feature information by adding cross-scale connecting lines in the feature fusion structure; finally, a small target detection layer is constructed in YOLOv5 so that more shallow feature information can be retained to achieve small-scale leak point recognition. The experimental results show that the precision of this method for microleak identification is 95.04%, the recall rate is 94.86%, the mAP value is 96.31%, and the minimum size of identifiable leaks is 1 mm.
Sensor Management Method of Giving Priority to Confirmed Identified Targets
Authors: Ding Chunshan , Li Chunguo
Published: April 2023

The optimization objective function of sensor management for target identification is commonly established based on information theory indicators such as information gain, discrimination, discrimination gain, and quadratic entropy, which can control the sensors to reduce the overall uncertainty of all targets to be identified but ignores the speed of target being confirmed as identified. Therefore, inspired by the maximum posterior criterion of target identification and the target identification confirmation mechanism, we study a sensor management method that preferentially allocates resources to identifiable targets. Firstly, in the distributed target identification framework based on Bayesian theory, an improved identification probability prediction method that provides feedback the global identification results to local classifiers is proposed, which can improve the accuracy of identification probability prediction. Secondly, an effective sensor management function based on information entropy and expected confidence level is proposed to optimize the identification uncertainty itself rather than its variation, which can increase the priority of targets that satisfy the desired confidence level. In the end, the sensor management for target identification is modeled as a sensor allocation problem, and the optimization objective function based on the effective function is constructed, which can improve the target identification speed. The experimental results show that the correct identification rate of the proposed method is comparable to the methods based on information gain, discrimination, discrimination gain, and quadratic entropy in different scenarios, but the average time to confirm the identification is the shortest.
Use, Validity and Reliability of Inertial Movement Units in Volleyball: Systematic Review of the Scientific Literature
Authors: Villarejo-García Diego Hernán , Moreno-Villanueva Adrián , Soler-López Alejandro , Reche-Soto Pedro , Pino-Ortega José
Published: April 2023

The use of inertial devices in sport has become increasingly common. The aim of this study was to examine the validity and reliability of multiple devices for measuring jump height in volleyball. The search was carried out in four databases (PubMed, Scopus, Web of Sciences and SPORTDiscus) using keywords and Boolean operators. Twenty-one studies were selected that met the established selection criteria. The studies focused on determining the validity and reliability of IMUs (52.38%), on controlling and quantifying external load (28.57%) and on describing differences between playing positions (19.05%). Indoor volleyball was the modality in which IMUs have been used the most. The most evaluated population was elite, adult and senior athletes. The IMUs were used both in training and in competition, evaluating mainly the amount of jump, the height of the jumps and some biomechanical aspects. Criteria and good validity values for jump counting are established. The reliability of the devices and the evidence is contradictory. IMUs are devices used in volleyball to count and measure vertical displacements and/or compare these measurements with the playing position, training or to determine the external load of the athletes. It has good validity measures, although inter-measurement reliability needs to be improved. Further studies are suggested to position IMUs as measuring instruments to analyze jumping and sport performance of players and teams.
Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug–Food Interactions from Chemical Structures
Authors: Kha Quang-Hien , Le Viet-Huan , Hung Truong Nguyen Khanh , Nguyen Ngan Thi Kim , Le Nguyen Quoc Khanh
Published: April 2023

Possible drug–food constituent interactions (DFIs) could change the intended efficiency of particular therapeutics in medical practice. The increasing number of multiple-drug prescriptions leads to the rise of drug–drug interactions (DDIs) and DFIs. These adverse interactions lead to other implications, e.g., the decline in medicament’s effect, the withdrawals of various medications, and harmful impacts on the patients’ health. However, the importance of DFIs remains underestimated, as the number of studies on these topics is constrained. Recently, scientists have applied artificial intelligence-based models to study DFIs. However, there were still some limitations in data mining, input, and detailed annotations. This study proposed a novel prediction model to address the limitations of previous studies. In detail, we extracted 70,477 food compounds from the FooDB database and 13,580 drugs from the DrugBank database. We extracted 3780 features from each drug–food compound pair. The optimal model was eXtreme Gradient Boosting (XGBoost). We also validated the performance of our model on one external test set from a previous study which contained 1922 DFIs. Finally, we applied our model to recommend whether a drug should or should not be taken with some food compounds based on their interactions. The model can provide highly accurate and clinically relevant recommendations, especially for DFIs that may cause severe adverse events and even death. Our proposed model can contribute to developing more robust predictive models to help patients, under the supervision and consultants of physicians, avoid DFI adverse effects in combining drugs and foods for therapy.