bluuebunny/crossref_metadata_2025 huggingface dataset:
NMR, LC-MS Characterization of Rydingia michauxii Extracts, Identification of Natural Products Acting as Modulators of LDLR and PCSK9
Authors: Sut Stefania , Tahmasebi Aminallah , Ferri Nicola , Ferrarese Irene , Rossi Ilaria , Panighel Giovanni , Lupo Maria Giovanna , Maggi Filippo , Karami Akbar , Dall’Acqua Stefano
Published: March 2022

Rydingia michauxii (Briq.) Scheen and V.A.Albert (Lamiaceae) is used in Iranian traditional medicine to treat malaria, diabetes, hyperlipidemia, rheumatism and cardiovascular diseases. NMR and LC-DAD-MSn analyses were used to establish extract composition and phenylethanoid, flavonoid glycosides, lignans, labdane diterpenes and iridoids were identified and quantified. The main constituents were isolated, and structures were elucidated based on NMR, polarimetric and MS measurements. A new natural compound, ent-labda-8(17),13-dien-18-glucopyranosyl ester-15,16-olide is described here. The effects of ent-labda-8(17),13-dien-18-oic acid-15,16-olide (1), ent-labda-8(17),13-dien-18-glucopyranosyl es-ter-15,16-olide (2), antirrhinoside (3), echinacoside (4), verbascoside (5), and apigenin 6,8-di-C-glucoside (6), on the low-density lipoprotein receptor (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9), were studied in the human hepatocarcinoma cell line Huh7. Among the six constituents, (3) showed the strongest induction of the LDLR (3.7 ± 2.2 fold vs. control) and PCSK9 (3.2 ± 1.5 fold vs. control) at a concentration of 50 µM. The in vitro observations indicated a potential lipid lowering activity of (3) with a statin-like mechanism of action.
Polydopamine-Coated Magnetic Iron Oxide Nanoparticles: From Design to Applications
Authors: Siciliano Giulia , Monteduro Anna Grazia , Turco Antonio , Primiceri Elisabetta , Rizzato Silvia , Depalo Nicoletta , Curri Maria Lucia , Maruccio Giuseppe
Published: March 2022

Magnetic iron oxide nanoparticles have been extensively investigated due to their applications in various fields such as biomedicine, sensing, and environmental remediation. However, they need to be coated with a suitable material in order to make them biocompatible and to add new functionalities on their surface. This review is intended to give a comprehensive overview of recent advantages and applications of iron oxide nanoparticles coated by polydopamine film. The synthesis method of magnetic nanoparticles, their functionalization with bioinspired materials and (in particular) with polydopamine are discussed. Finally, some interesting applications of polydopamine-coated magnetic iron oxide nanoparticles will be pointed out.
Enhancement of Casimir Friction between Graphene-Covered Topological Insulator
Authors: Yu Ting , Luo Rong , Wang Tongbiao , Zhang Dejian , Liu Wenxing , Yu Tianbao , Liao Qinghua
Published: March 2022

Casimir friction is theoretically studied between graphene-covered undoped bismuth selenide (Bi2Se3) in detail. In the graphene/Bi2Se3 composite structure, the coupling of the hyperbolic phonon polaritons supported by Bi2Se3 with the surface plasmons supported by graphene can lead to the hybrid surface plasmon–phonon polaritons (SPPPs). Compared with that between undoped Bi2Se3, Casimir friction can be enhanced by more than one order of magnitude due to the contribution of SPPPs. It is found that the chemical potential that can be used to modulate the optical characteristic of SPPPs plays an important role in Casimir friction. In addition, the Casimir friction between doped Bi2Se3 is also studied. The friction coefficient between doped Bi2Se3 can even be larger than that between graphene-covered undoped Bi2Se3 for suitable chemical potential due to the contribution of unusual electron surface states. The results obtained in this work are not only beneficial to the study of Casimir frictions but also extend the research ranges of topological insulators.
Effects of Isocaloric Fructose Restriction on Ceramide Levels in Children with Obesity and Cardiometabolic Risk: Relation to Hepatic De Novo Lipogenesis and Insulin Sensitivity
Authors: Olson Emily , Suh Jung H. , Schwarz Jean-Marc , Noworolski Susan M. , Jones Grace M. , Barber John R. , Erkin-Cakmak Ayca , Mulligan Kathleen , Lustig Robert H. , Mietus-Snyder Michele
Published: March 2022

Sugar intake, particularly fructose, is implicated as a factor contributing to insulin resistance via hepatic de novo lipogenesis (DNL). A nine-day fructose reduction trial, controlling for other dietary factors and weight, in children with obesity and metabolic syndrome, decreased DNL and mitigated cardiometabolic risk (CMR) biomarkers. Ceramides are bioactive sphingolipids whose dysregulated metabolism contribute to lipotoxicity, insulin resistance, and CMR. We evaluated the effect of fructose reduction on ceramides and correlations between changes observed and changes in traditional CMR biomarkers in this cohort. Analyses were completed on data from 43 participants. Mean weight decreased (−0.9 ± 1.1 kg). The majority of total and subspecies ceramide levels also decreased significantly, including dihydroceramides, deoxyceramides and ceramide-1-phoshates. Change in each primary ceramide species correlated negatively with composite insulin sensitivity index (CISI). Change in deoxyceramides positively correlated with change in DNL. These results suggest that ceramides decrease in response to dietary fructose restriction, negatively correlate with insulin sensitivity, and may represent an intermediary link between hepatic DNL, insulin resistance, and CMR.
Determinants of Suboptimal Gestational Weight Gain among Antenatal Women Residing in the Highest Gross Domestic Product (GDP) Region of Malaysia
Authors: Nurul-Farehah Shahrir , Rohana Abdul Jalil , Hamid Noor Aman , Daud Zaiton , Asis Siti Harirotul Hamrok
Published: March 2022

Suboptimal gestational weight gain has been associated with adverse perinatal and maternal outcomes, including increased risk of non-communicable diseases later in life. This study aimed to determine the proportion and determinants of suboptimal GWG. A cross-sectional study was conducted among 475 pregnant women in Selangor between January and March 2020. The study included all pregnant women at their second or third trimester who fulfilled the inclusion and exclusion criteria. A multistage sampling was applied. The GWG adequacy was based on recommendations from the Institute of Medicine (2009). Multinomial logistic regressions were used for data analysis. Out of the 475 respondents, 224 (47.2%) pregnant women had inadequate GWG, 142 (29.9%) had adequate GWG, and 109 (22.9%) had excessive GWG. Multinomial logistic regression showed that having diabetes in pregnancy (AdjOR 2.24, 95% CI: 1.31, 3.83, p = 0.003), middle (M40) monthly household income (AdjOR 2.33, 95% CI: 1.09, 4.96, p = 0.029), low (B40) monthly household income (AdjOR 2.22, 95% CI: 1.07, 4.72, p = 0.039), and an obese pre-pregnancy BMI (AdjOR 2.77, 95% CI: 1.43, 5.35, p = 0.002) were significantly associated with inadequate GWG. Overweight (AdjOR 5.18, 95% CI: 2.52, 10.62, p < 0.001) and obese pre-pregnancy BMIs (AdjOR 17.95, 95% CI: 8.13, 36.95, p < 0.001) were significantly associated with excessive GWG. Improving maternal and perinatal outcomes requires targeted interventions focusing on these modifiable determinants.
Targeting Cardiovascular Diseases by Flavonols: An Update
Authors: Kozłowska Aleksandra , Szostak-Węgierek Dorota
Published: March 2022

Flavonols are one of the most plentiful flavonoid subclasses found in natural products and are extensively used as dietary supplements. Numerous in vitro and in vivo studies have shown the cardioprotective properties of flavonols, especially quercetin. This group of substances exerts positive impacts primarily due to their antiatherogenic, antithrombotic, and antioxidant activities. The potential of flavonols to promote vasodilation and regulation of apoptotic processes in the endothelium are other beneficial effects on the cardiovascular system. Despite promising experimental findings, randomized controlled trials and meta-analyses have yielded inconsistent results on the influence of these substances on human cardiovascular parameters. Thus, this review aims to summarize the most recent clinical data on the intake of these substances and their effects on the cardiovascular system. The present study will help clinicians and other healthcare workers understand the value of flavonol supplementation in both subjects at risk for cardiovascular disease and patients with cardiovascular diseases.
Calcium, Magnesium, and Zinc Supplementation during Pregnancy: The Additive Value of Micronutrients on Maternal Immune Response after SARS-CoV-2 Infection
Authors: Citu Ioana Mihaela , Citu Cosmin , Margan Madalin-Marius , Craina Marius , Neamtu Radu , Gorun Oana Maria , Burlea Bogdan , Bratosin Felix , Rosca Ovidiu , Grigoras Mirela Loredana , Motoc Andrei , Malita Daniel , Neagoe Octavian , Gorun Florin
Published: March 2022

Magnesium may contribute to the immune response during and after SARS-CoV-2 infection by acting as a cofactor for immunoglobulin production and other processes required for T and B cell activity. Considering magnesium as a recommended dietary supplement during pregnancy and the possible role of magnesium deficiency in COVID-19 and its complications, the current study sought to determine the effect of magnesium and magnesium-containing nutritional supplements on the immune response following SARS-CoV-2 infection in pregnant women, as well as to observe differences in pregnancy outcomes based on the supplements taken during pregnancy. The study followed a cross-sectional design, where patients with a history of SARS-CoV-2 infection during their pregnancy were surveyed for their preferences in nutritional supplementation and their profile compared with existing records from the institutional database. A cohort of 448 pregnant women with COVID-19 during 22 months of the pandemic was assembled, out of which 13.6% took a magnesium-only supplement, and 16.5% supplemented their diet with a combination of calcium, magnesium, and zinc. Around 60% of patients in the no-supplementation group had the SARS-CoV-2 anti-RBD lower than 500 U/mL, compared with 50% in those who took magnesium-based supplements. A quantity of magnesium >450 mg in the taken supplements determined higher levels of antibody titers after COVID-19. Low magnesium dosage (<450 mg) was an independent risk factor for a weak immune response (OR-1.25, p-value = 0.003). The observed findings suggest supplementing the nutritional intake of pregnant women with magnesium-based supplements to determine higher levels of SARS-CoV-2 anti-RBD antibodies, although causality remains unclear.
Pan-Phosphodiesterase Inhibitors Attenuate TGF-β-Induced Pro-Fibrotic Phenotype in Alveolar Epithelial Type II Cells by Downregulating Smad-2 Phosphorylation
Authors: Wójcik-Pszczoła Katarzyna , Chłoń-Rzepa Grażyna , Jankowska Agnieszka , Ferreira Bruno , Koczurkiewicz-Adamczyk Paulina , Pękala Elżbieta , Wyska Elżbieta , Pociecha Krzysztof , Gosens Reinoud
Published: March 2022

Airway remodeling is a pathological process that accompanies many chronic lung diseases. One of the important players in this process are epithelial cells, which under the influence of pro-inflammatory and pro-fibrotic factors present in the airway niche, actively participate in the remodeling process by increasing extracellular matrix secretion, acquiring migration properties, and overproducing pro-fibrotic transducers. Here, we investigated the effect of three new 8-arylalkylamino- and 8-alkoxy-1,3-dimethyl-2,6-dioxo-1,2,3,6-tetrahydro-7H-purin-7-yl-N-(5-(tert-butyl)-2-hydroxyphenyl)butanamides (1, 2, and 3), representing prominent pan-phosphodiesterase (pan-PDE) inhibitors on transforming growth factor type β (TGF-β)-induced alveolar epithelial type II cells (A549 cell line) of a pro-fibrotic phenotype. Our results demonstrate for the first time the strong activity of pan-PDE inhibitors in the prevention of TGF-β-induced mesenchymal markers’ expression and A549 cells’ migration. We also showed an increased p-CREB and decreased p-Smad-2 phosphorylation in TGF-β-induced A549 cells treated with 1, 2, and 3 derivatives, thereby confirming a pan-PDE inhibitor mesenchymal phenotype reducing effect in alveolar epithelial type II cells via suppression of the canonical Smad signaling pathway. Our observations confirmed that PDE inhibitors, and especially those active against various isoforms involved in the airway remodeling, constitute an interesting group of compounds modulating the pro-fibrotic response of epithelial cells.
A Protein-Based, Long-Acting HIV-1 Fusion Inhibitor with an Improved Pharmacokinetic Profile
Authors: Xu Wei , Cong Zhe , Duan Qianyu , Wang Qian , Su Shan , Wang Rui , Lu Lu , Xue Jing , Jiang Shibo
Published: March 2022

Recently, a series of highly effective peptide- or protein-based HIV fusion inhibitors have been identified. However, due to their short half-life, their clinical application is limited. Therefore, the development of long-acting HIV fusion inhibitors is urgently needed. Here, we designed and constructed a protein-based, long-acting HIV fusion inhibitor, termed FLT (FN3-L35-T1144), consisting of a monobody, FN3, which contains an albumin-binding domain (ABD), a 35-mer linker (L35), and a peptide-based HIV fusion inhibitor, T1144. We found that FLT bound, via its FN3 component, with human serum albumin (HSA) in a reversible manner, thus maintaining the high efficiency of T1144 against infection by both HIV-1 IIIB (X4) and Bal (R5) strains with IC50 of 11.6 nM and 15.3 nM, respectively, and remarkably prolonging the half-life of T1144 (~27 h in SD rats). This approach affords protein-based HIV fusion inhibitors with much longer half-life compared to enfuvirtide, a peptide-based HIV fusion inhibitor approved for use in clinics. Therefore, FLT is a promising candidate as a new protein-based anti-HIV drug with an improved pharmacokinetic profile.
Formulation and Evaluation of Hybrid Niosomal In Situ Gel for Intravesical Co-Delivery of Curcumin and Gentamicin Sulfate
Authors: Gugleva Viliana , Michailova Victoria , Mihaylova Rositsa , Momekov Georgi , Zaharieva Maya Margaritova , Najdenski Hristo , Petrov Petar , Rangelov Stanislav , Forys Aleksander , Trzebicka Barbara , Momekova Denitsa
Published: March 2022

The current study describes the elaboration of a hybrid drug delivery platform for an intravesical application based on curcumin/gentamicin sulfate simultaneously loaded niosomes incorporated into thermosensitive in situ gels. Series of niosomes were elaborated via the thin film hydration method, evaluating the impact of non-ionic surfactants’, cholesterol’s, and curcumin’s concentration. The formulation composed of equimolar ratio of Span 60, Tween 60, and 30 mol% cholesterol was selected as the optimal composition, due to the high entrapment efficiency values obtained for both drugs, and appropriate physicochemical parameters (morphology, size, PDI, and zeta potential), therefore, was further incorporated into Poloxamers (407/188) and Poloxamers and chitosan based in situ gels. The developed hybrid systems were characterized with sol to gel transition in the physiological range, suitable rheological and gelling characteristics. In addition, the formed gel structure at physiological temperatures determines the retarded dissolution of both drugs (vs. niosomal suspension) and sustained release profile. The conducted microbial studies of selected niosomal in situ gels revealed the occurrence of a synergetic effect of the two compounds when simultaneously loaded. The findings indicate that the elaborated thermosensitive niosomal in situ gels can be considered as a feasible platform for intravesical drug delivery.
Photoelectrochemical Energy Conversion over 2D Materials
Authors: Raza Ali , Zhang Xinyu , Ali Sarfraz , Cao Changhai , Rafi Arslan Ahmed , Li Gao
Published: March 2022

The solar motivated photoelectrochemical (PEC), used in water splitting systems, shows superior talent in converting solar energy in the form of cleaning and in sustaining a chemical energy evolution. PEC systems present by integrating a photoelectrode, which involves light-harvesting to absorb solar energy, thereby introducing an interlayer for the transformation of photogenerated electrons and holes, along with a co-catalyst to trigger oxidation and reduce the chemical reactions. In this review, we describe a variety of two-dimensional (2D) layered photoanodes and photocathodes, such as graphitic carbon nitrides, transition metal dichalcogenides, layered double hydroxides, MXenes, and co-catalysts for the assembly of combined photoelectrodes belonging to oxygen evolution and/or hydrogen evolution chemical reactions. The basic principles of PEC water splitting associated with physicochemical possessions relating to photoelectrodes unified with catalytic chemical reactions have been investigated. Additionally, the mechanisms attributing to a relationship with 2D photoelectrodes have been incorporated as a supplementary discussion. The improvement strategies, which include the construction of heterostructures, surface functionalization, and formations of heterojunctions, have also been discussed. The issues and challenges relevant to the field have been acknowledged for facilitating future research, indicating optimized conversion activity corresponding to PEC water splitting.
Understanding In Vivo Chromatic Aberrations in Pseudophakic Eyes Using on Bench and Computational Approaches
Authors: Vinas-Pena Maria , de Castro Alberto , Dorronsoro Carlos , Gonzalez-Ramos Ana , Redzovic Suad , Willet Nicolas , Garzon Nuria , Marcos Susana
Published: March 2022

Diffractive multifocal intraocular lenses (IOLs) modulate chromatic aberration and reduce it at certain distances due to interactions between the refractive and diffractive chromatic components. However, the extent to which computer modeling and on bench measurements of IOL chromatic aberration translate to chromatic aberration in patients implanted with these multifocal IOLs (MIOLs) is not yet fully understood. In this study, we compare the chromatic difference of focus and longitudinal chromatic aberrations in pseudophakic patients implanted with different IOL designs (monofocal and trifocal IOLs) and materials (hydrophobic and hydrophilic), and compared them with predictions from computer eye models and on bench measurements with the same IOLs. Patient data consisted of results from 63 pseudophakic eyes reported in four different studies and obtained psychophysically in the visual testing channel of a custom-developed polychromatic adaptive optics system. Computational predictions were obtained using ray tracing on computer eye models, and modulation transfer function (MTF) on bench measurements on physical eye models. We found that LCA (in vivo/simulated) for far vision was 1.37 ± 0.08 D/1.19 D for monofocal hydrophobic, 1.21 ± 0.08 D/0.88 D for monofocal hydrophilic, 0.99 ± 0.06 D/1.19 D for MIOL hydrophobic, and 0.82 ± 0.05 D/0.88 D for MIOL hydrophilic. For intermediate and near vision, LCA (in vivo/simulated) was 0.67 ± 0.10 D/0.75 D and 0.23 ± 0.08 D/0.19 D for MIOL hydrophobic and 0.27 ± 0.15 D/0.38 D and 0.15 ± 0.15 D/−0.13 D for MIOL hydrophilic, respectively. In conclusion, computational ray tracing and on bench measurements allowed for evaluating in vivo chromatic aberration with different materials and designs for multifocal diffractive intraocular lenses.
Design and Evaluation of a Polymer Support Fluid in a Soil–Rock Mixture
Authors: Ying Chunye , Hu Xinli , Xia Peng , Zhang Haiyan
Published: March 2022

Soil–rock mixtures are commonly encountered in the construction of bored piles. Conventional bentonite support fluids have disadvantages, such as more significant environmental impacts, more complex mixing, bigger site footprint, weaker foundation performance, and overall low economies. The present study conducted a comprehensive investigation of partially hydrolyzed polyacrylamide (PHPA) polymer fluids, an alternative to bentonite ones, to drill into a soil-limestone mixture. The fluid flow pattern, aging behavior, and the influence of finer silty clay on polymer fluid were explored. The test results showed that polymer fluids were reasonably well fitted to the power-law model and were a good alternative to the conventional bentonite ones. In terms of their aging behavior, the remaining active viscosity of the polymer was at least 70% after a prolonged aging time of up to 30 days, showing the effective on-site use of polymer fluids. The mixing of silty clay significantly reduced the apparent viscosity of polymer fluids, with 10% silty clay causing a viscosity reduction of 76%, indicating the importance of fluid control in drilling these materials. A polymer formula, water + 0.08%PHPA + 0.1~0.5%Na2CO3, was proposed and was verified by drilling into a soil–limestone mixture. The polymer fluids led to small radial displacements around the boreholes with a high drilling quality. This work would be helpful for consultants and contractors designing and constructing bored piles in soil and rock mixtures utilizing polymer fluids.
Environmental Consequences of Rubber Crumb Application: Soil and Water Pollution
Authors: Fořt Jan , Kobetičová Klára , Böhm Martin , Podlesný Jan , Jelínková Veronika , Vachtlová Martina , Bureš Filip , Černý Robert
Published: March 2022

End-of-life tires are utilized for various purposes, including sports pitches and playground surfaces. However, several substances used at the manufacture of tires can be a source of concerns related to human health or environment’s adverse effects. In this context, it is necessary to map whether this approach has the desired effect in a broader relation. While the negative effects on human health were investigated thoroughly and legislation is currently being revisited, the impact on aquatic or soil organisms has not been sufficiently studied. The present study deals with the exposure of freshwater and soil organisms to rubber crumb using the analysis of heavy metal and polycyclic aromatic hydrocarbon concentrations. The obtained results refer to substantial concerns related to freshwater contamination specifically, since the increased concentrations of zinc (7 mg·L−1) and polycyclic aromatic hydrocarbons (58 mg·kg−1) inhibit the growth of freshwater organisms, Desmodesmus subspicatus, and Lemna minor in particular. The performed test with soil organisms points to substantial concerns associated with the mortality of earthworms as well. The acquired knowledge can be perceived as a roadmap to a consistent approach in the implementation of the circular economy, which brings with it a number of so far insufficiently described problems.
Intervention Program to Reduce Religious Prejudice in Education Settings: A Scoping Review
Authors: Tondok Marselius Sampe , Suryanto Suryanto , Ardi Rahkman
Published: March 2022

In a plural society, education has an important role in preparing students to be able to live together with differences, including religious differences. Based on the contact hypothesis theory, various intervention programs have been carried out to overcome religious prejudice. This study aims to explore the concept, form, and impact of the interfaith intervention program in reducing religious prejudice in the context of education. The method used was a scoping review following the PRISMA-ScR protocol. Articles were searched online from the SAGE, Science Direct, Scopus, and Web of Science databases. There were six journal articles in the period 2012–2021 that were included based on the inclusion and exclusion criteria set. The results of this scoping review synthesized concepts, forms, and impacts, as well as research methods related to interfaith intervention programs to reduce religious prejudice in the education settings. We discussed the implications and directions for further research in research for the design, implementation, and evaluation of intergroup contact-based learning in education settings, especially higher education.
Simulating River/Lake–Groundwater Exchanges in Arid River Basins: An Improvement Constrained by Lake Surface Area Dynamics and Evapotranspiration
Authors: Vasilevskiy Peter , Wang Ping , Pozdniakov Sergey , Wang Tianye , Zhang Yichi , Zhang Xuejing , Yu Jingjie
Published: March 2022

Surface water–groundwater interactions in arid zones are characterized by water exchange processes in a complex system comprising intermittent streams/terminal lakes, shallow aquifers, riparian zone evapotranspiration, and groundwater withdrawal. Notable challenges arise when simulating such hydrological systems; for example, field observations are scarce, and hydrogeological parameters exhibit considerable spatial heterogeneity. To reduce the simulation uncertainties, in addition to groundwater head and river discharge measurements, we adopted remote sensing-based evapotranspiration data and lake area dynamics as known conditions to calibrate the model. We chose the Ejina Basin, located in the lower reaches of the Heihe River Basin in arid northwest China, as the study area to validate our modelling approach. The hydrological system of this basin is characterized by intensive, spatiotemporally variable surface water–groundwater interactions. The areas of the terminal lakes into which all river runoff flows vary significantly depending on the ratio between river runoff and lake evaporation. Simulation results with a monthly time step from 2000 to 2017 indicate that river leakage accounted for approximately 61% of the total river runoff. Our study shows that for areas where surface water and groundwater observations are sparse, combining remote sensing product data of surface water areas and evapotranspiration can effectively reduce the uncertainty in coupled surface water and groundwater simulations.
Comparing Fire Extent and Severity Mapping between Sentinel 2 and Landsat 8 Satellite Sensors
Authors: White Laura A. , Gibson Rebecca K.
Published: March 2022

Mapping of fire extent and severity across broad landscapes and timeframes using remote sensing approaches is valuable to inform ecological research, biodiversity conservation and fire management. Compiling imagery from various satellite sensors can assist in long-term fire history mapping; however, inherent sensor differences need to be considered. The New South Wales Fire Extent and Severity Mapping (FESM) program uses imagery from Sentinel and Landsat satellites, along with supervised classification algorithms, to produce state-wide fire maps over recent decades. In this study, we compared FESM outputs from Sentinel 2 and Landsat 8 sensors, which have different spatial and spectral resolutions. We undertook independent accuracy assessments of both Sentinel 2 and Landsat 8 sensor algorithms using high-resolution aerial imagery from eight training fires. We also compared the FESM outputs from both sensors across 27 case study fires. We compared the mapped areas of fire severity classes between outputs and assessed the classification agreement at random sampling points. Our independent accuracy assessment demonstrated very similar levels of accuracy for both sensor algorithms. We also found that there was substantial agreement between the outputs from the two sensors. Agreement on the extent of burnt versus unburnt areas was very high, and the severity classification of burnt areas was typically either in agreement between the sensors or in disagreement by only one severity class (e.g., low and moderate severity or high and extreme severity). Differences between outputs are likely partly due to differences in sensor resolution (10 m and 30 m pixel sizes for Sentinel 2 and Landsat 8, respectively) and may be influenced by landscape complexity, such as terrain roughness and foliage cover. Overall, this study supports the combined use of both sensors in remote sensing applications for fire extent and severity mapping.
Omega-KA-Net: A SAR Ground Moving Target Imaging Network Based on Trainable Omega-K Algorithm and Sparse Optimization
Authors: Zhang Hongwei , Ni Jiacheng , Xiong Shichao , Luo Ying , Zhang Qun
Published: March 2022

The ground moving target (GMT) is defocused due to unknown motion parameters in synthetic aperture radar (SAR) imaging. Although the conventional Omega-K algorithm (Omega-KA) has been proven to be applicable for GMT imaging, its disadvantages are slow imaging speed, obvious sidelobe interference, and high computational complexity. To solve the above problems, a SAR-GMT imaging network is proposed based on trainable Omega-KA and sparse optimization. Specifically, we propose a two-dimensional (2-D) sparse imaging model deducted from the Omega-KA focusing process. Then, a recurrent neural network (RNN) based on an iterative optimization algorithm is built to learn the trainable parameters of Omega-KA by an off-line supervised training method, and the solving process of the sparse imaging model is mapped to each layer of the RNN. The proposed trainable Omega-KA network (Omega-KA-net) forms a new GMT imaging method that can be applied to high-quality imaging under down-sampling and a low signal to noise ratio (SNR) while saving the imaging time substantially. The experiments of simulation data and measured data demonstrate that the Omega-KA-net is superior to the conventional algorithms in terms of GMT imaging quality and time.
Mapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysis
Authors: Ouyang Linke , Wu Caiyan , Li Junxiang , Liu Yuhan , Wang Meng , Han Ji , Song Conghe , Yu Qian , Haase Dagmar
Published: March 2022

The impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions.
Data-Driven Joint Beam Selection and Power Allocation for Multiple Target Tracking
Authors: Shi Yuchun , Zheng Hao , Li  Kang
Published: March 2022

For the problem of joint beam selection and power allocation (JBSPA) for multiple target tracking (MTT), existing works tend to allocate resources only considering the MTT performance at the current tracking time instant. However, in this way, it cannot guarantee the long-term MTT performance in the future. If the JBSPA not only considers the tracking performance at the current tracking time instant but also at the future tracking time instant, the allocation results are theoretically able to enhance the long-term tracking performance and the robustness of tracking. Motivated by this, the JBSPA is formulated as a model-free Markov decision process (MDP) problem, and solved with a data-driven method in this article, i.e., deep reinforcement learning (DRL). With DRL, the optimal policy is given by learning from the massive interacting data of the DRL agent and environment. In addition, in order to ensure the information prediction performance of target state in maneuvering target scenarios, a data-driven method is developed based on Long-short term memory (LSTM) incorporating the Gaussian mixture model (GMM), which is called LSTM-GMM for short. This method can realize the state prediction by learning the regularity of nonlinear state transitions of maneuvering targets, where the GMM is used to describe the target motion uncertainty in LSTM. Simulation results have shown the effectiveness of the proposed method.
Toward Realigning Automatic Speaker Verification in the Era of COVID-19
Authors: Khan Awais , Javed Ali , Malik Khalid Mahmood , Raza Muhammad Anas , Ryan James , Saudagar Abdul Khader Jilani , Malik Hafiz
Published: March 2022

The use of face masks has increased dramatically since the COVID-19 pandemic started in order to to curb the spread of the disease. Additionally, breakthrough infections caused by the Delta and Omicron variants have further increased the importance of wearing a face mask, even for vaccinated individuals. However, the use of face masks also induces attenuation in speech signals, and this change may impact speech processing technologies, e.g., automated speaker verification (ASV) and speech to text conversion. In this paper we examine Automatic Speaker Verification (ASV) systems against the speech samples in the presence of three different types of face mask: surgical, cloth, and filtered N95, and analyze the impact on acoustics and other factors. In addition, we explore the effect of different microphones, and distance from the microphone, and the impact of face masks when speakers use ASV systems in real-world scenarios. Our analysis shows a significant deterioration in performance when an ASV system encounters different face masks, microphones, and variable distance between the subject and microphone. To address this problem, this paper proposes a novel framework to overcome performance degradation in these scenarios by realigning the ASV system. The novelty of the proposed ASV framework is as follows: first, we propose a fused feature descriptor by concatenating the novel Ternary Deviated overlapping Patterns (TDoP), Mel Frequency Cepstral Coefficients (MFCC), and Gammatone Cepstral Coefficients (GTCC), which are used by both the ensemble learning-based ASV and anomaly detection system in the proposed ASV architecture. Second, this paper proposes an anomaly detection model for identifying vocal samples produced in the presence of face masks. Next, it presents a Peak Norm (PN) filter to approximate the signal of the speaker without a face mask in order to boost the accuracy of ASV systems. Finally, the features of filtered samples utilizing the PN filter and samples without face masks are passed to the proposed ASV to test for improved accuracy. The proposed ASV system achieved an accuracy of 0.99 and 0.92, respectively, on samples recorded without a face mask and with different face masks. Although the use of face masks affects the ASV system, the PN filtering solution overcomes this deficiency up to 4%. Similarly, when exposed to different microphones and distances, the PN approach enhanced system accuracy by up to 7% and 9%, respectively. The results demonstrate the effectiveness of the presented framework against an in-house prepared, diverse Multi Speaker Face Masks (MSFM) dataset, (IRB No. FY2021-83), consisting of samples of subjects taken with a variety of face masks and microphones, and from different distances.
Acoustic Emission Signal Fault Diagnosis Based on Compressed Sensing for RV Reducer
Authors: Yang Jianwei , Liu Chang , Xu Qitong , Tai Jinyi
Published: March 2022

The rotate vector (RV) reducer has a complex structure and highly coupled internal components. Acoustic emission (AE) signal, which is more sensitive to a weak fault, is selected for fault diagnosis of the RV reducer. The high sampling frequency and big data are the challenges for AE signal store and analysis. This study combines compressed sensing (CS) and convolutional neural networks. As a result, data redundancy is significantly reduced while retaining most of the information, and the analysis efficiency is improved. Firstly, the time-domain AE signal was projected into the compression domain to obtain the compression signal; then, the wavelet packet decomposition in the compressed domain was performed to obtain the information of each frequency band. Next, the frequency band information was sent into the input layer of the multi-channel convolutional layer, and the energy pooling layer mines the energy characteristics of each frequency band. Finally, the softmax classifier was used to classify and predict different fault types of RV reducers. The self-fabricated RV reducer experimental platform was used to verify the proposed method. The experimental results show that the proposed method can effectively extract the fault features in the AE signal of the RV reducer, improve the efficiency of signal processing and analysis, and achieve the accurate classification of RV reducer faults.
AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms
Authors: Convertino Victor A. , Techentin Robert W. , Poole Ruth J. , Dacy Ashley C. , Carlson Ashli N. , Cardin Sylvain , Haider Clifton R. , Holmes III David R. , Wiggins Chad C. , Joyner Michael J. , Curry Timothy B. , Inan Omer T.
Published: March 2022

The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability of two machine learning (ML) algorithms based on real-time feature analysis of arterial waveforms obtained from a non-invasive continuous blood pressure system (Finometer®) signal to predict the onset of decompensated shock: the compensatory reserve index (CRI) and the compensatory reserve metric (CRM). One hundred ninety-one healthy volunteers underwent progressive simulated hemorrhage using lower body negative pressure (LBNP). The least squares means and standard deviations for each measure were assessed by LBNP level and stratified by tolerance status (high vs. low tolerance to central hypovolemia). Generalized Linear Mixed Models were used to perform repeated measures logistic regression analysis by regressing the onset of decompensated shock on CRI and CRM. Sensitivity and specificity were assessed by calculation of receiver-operating characteristic (ROC) area under the curve (AUC) for CRI and CRM. Values for CRI and CRM were not distinguishable across levels of LBNP independent of LBNP tolerance classification, with CRM ROC AUC (0.9268) being statistically similar (p = 0.134) to CRI ROC AUC (0.9164). Both CRI and CRM ML algorithms displayed discriminative ability to predict decompensated shock to include individual subjects with varying levels of tolerance to central hypovolemia. Arterial waveform feature analysis provides a highly sensitive and specific monitoring approach for the detection of ongoing hemorrhage, particularly for those patients at greatest risk for early onset of decompensated shock and requirement for implementation of life-saving interventions.
Review and Analysis of Technical Designs of Rear Underrun Protective Devices (RUPDs) in Terms of Regulatory Compliance
Authors: Gidlewski Mirosław , Jackowski Jerzy , Posuniak Paweł
Published: March 2022

The Rear Underrun Protective Device (RUPD) is a basic means to prevent a passenger car from running under the rear of a motor truck (also referred to as heavy goods vehicle or HGV) or a trailer in the case of a rear-end collision and thus to reduce deformations of the car’s passenger compartment (“survival space”). In many publications dealing with such devices, the increasing of RUPD stiffness by applying innovative design solutions or using high-strength materials has been considered; in some designs, additional RUPD components are introduced to absorb the impact energy. In this paper, a review of the RUPD designs is presented and some of them are analyzed, where their characteristics that are essential for the compliance with normative market requirements are indicated. Results of the authors’ research on the selection of an energy absorber incorporated in the rear impact guard bar of an HGV are presented as well.
Development of a Smartphone-Integrated Reflective Scatterometer for Bacterial Identification
Authors: Doh Iyll-Joon , Dowden Brianna , Patsekin Valery , Rajwa Bartek , Robinson J. Paul , Bae Euiwon
Published: March 2022

We present a smartphone-based bacterial colony phenotyping instrument using a reflective elastic light scattering (ELS) pattern and the resolving power of the new instrument. The reflectance-type device can acquire ELS patterns of colonies on highly opaque media as well as optically dense colonies. The novel instrument was built using a smartphone interface and a 532 nm diode laser, and these essential optical components made it a cost-effective and portable device. When a coherent and collimated light source illuminated a bacterial colony, a reflective ELS pattern was created on the screen and captured by the smartphone camera. The collected patterns whose shapes were determined by the colony morphology were then processed and analyzed to extract distinctive features for bacterial identification. For validation purposes, the reflective ELS patterns of five bacteria grown on opaque growth media were measured with the proposed instrument and utilized for the classification. Cross-validation was performed to evaluate the classification, and the result showed an accuracy above 94% for differentiating colonies of E. coli, K. pneumoniae, L. innocua, S. enteritidis, and S. aureus.
Word Embedding Distribution Propagation Graph Network for Few-Shot Learning
Authors: Zhu Chaoran , Wang Ling , Han Cheng
Published: March 2022

Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an obvious distinction between artificial intelligence and humans. In the FSL domain, most graph neural networks (GNNs) focus on transferring labeled sample information to an unlabeled query sample, ignoring the important role of semantic information during the classification process. Our proposed method embeds semantic information of classes into a GNN, creating a word embedding distribution propagation graph network (WPGN) for FSL. We merge the attention mechanism with our backbone network, use the Mahalanobis distance to calculate the similarity of classes, select the Funnel ReLU (FReLU) function as the activation function of the Transform layer, and update the point graph and word embedding distribution graph. In extensive experiments on FSL benchmarks, compared with the baseline model, the accuracy of the WPGN on the 5-way-1/2/5 shot tasks increased by 9.03, 4.56, and 4.15%, respectively.
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry
Authors: Cimarelli Claudio , Bavle Hriday , Sanchez-Lopez Jose Luis , Voos Holger
Published: March 2022

Unsupervised learning for monocular camera motion and 3D scene understanding has gained popularity over traditional methods, which rely on epipolar geometry or non-linear optimization. Notably, deep learning can overcome many issues of monocular vision, such as perceptual aliasing, low-textured areas, scale drift, and degenerate motions. In addition, concerning supervised learning, we can fully leverage video stream data without the need for depth or motion labels. However, in this work, we note that rotational motion can limit the accuracy of the unsupervised pose networks more than the translational component. Therefore, we present RAUM-VO, an approach based on a model-free epipolar constraint for frame-to-frame motion estimation (F2F) to adjust the rotation during training and online inference. To this end, we match 2D keypoints between consecutive frames using pre-trained deep networks, Superpoint and Superglue, while training a network for depth and pose estimation using an unsupervised training protocol. Then, we adjust the predicted rotation with the motion estimated by F2F using the 2D matches and initializing the solver with the pose network prediction. Ultimately, RAUM-VO shows a considerable accuracy improvement compared to other unsupervised pose networks on the KITTI dataset, while reducing the complexity of other hybrid or traditional approaches and achieving comparable state-of-the-art results.
Force-Sensitive Interface Engineering in Flexible Pressure Sensors: A Review
Authors: Tai Guojun , Wei Dapeng , Su Min , Li Pei , Xie Lei , Yang Jun
Published: March 2022

Flexible pressure sensors have received extensive attention in recent years due to their great importance in intelligent electronic devices. In order to improve the sensing performance of flexible pressure sensors, researchers are committed to making improvements in device materials, force-sensitive interfaces, and device structures. This paper focuses on the force-sensitive interface engineering of the device, which listing the main preparation methods of various force-sensitive interface microstructures and describing their respective advantages and disadvantages from the working mechanisms and practical applications of the flexible pressure sensor. What is more, the device structures of the flexible pressure sensor are investigated with the regular and irregular force-sensitive interface and accordingly the influences of different device structures on the performance are discussed. Finally, we not only summarize diverse practical applications of the existing flexible pressure sensors controlled by the force-sensitive interface but also briefly discuss some existing problems and future prospects of how to improve the device performance through the adjustment of the force-sensitive interface.
Estimation with Heisenberg-Scaling Sensitivity of a Single Parameter Distributed in an Arbitrary Linear Optical Network
Authors: Triggiani Danilo , Tamma Vincenzo
Published: March 2022

Quantum sensing and quantum metrology propose schemes for the estimation of physical properties, such as lengths, time intervals, and temperatures, achieving enhanced levels of precision beyond the possibilities of classical strategies. However, such an enhanced sensitivity usually comes at a price: the use of probes in highly fragile states, the need to adaptively optimise the estimation schemes to the value of the unknown property we want to estimate, and the limited working range, are some examples of challenges which prevent quantum sensing protocols to be practical for applications. This work reviews two feasible estimation schemes which address these challenges, employing easily realisable resources, i.e., squeezed light, and achieve the desired quantum enhancement of the precision, namely the Heisenberg-scaling sensitivity. In more detail, it is here shown how to overcome, in the estimation of any parameter affecting in a distributed manner multiple components of an arbitrary M-channel linear optical network, the need to iteratively optimise the network. In particular, we show that this is possible with a single-step adaptation of the network based only on a prior knowledge of the parameter achievable through a “classical” shot-noise limited estimation strategy. Furthermore, homodyne measurements with only one detector allow us to achieve Heisenberg-limited estimation of the parameter. We further demonstrate that one can avoid the use of any auxiliary network at the price of simultaneously employing multiple detectors.