bluuebunny/crossref_metadata_2025 huggingface dataset:
Critical Review of Lipid-Based Nanoparticles as Carriers of Neuroprotective Drugs and Extracts
Authors: Fernandes Filipe , Dias-Teixeira Mónica , Delerue-Matos Cristina , Grosso Clara
Published: February 2021

The biggest obstacle to the treatment of diseases that affect the central nervous system (CNS) is the passage of drugs across the blood-brain barrier (BBB), a physical barrier that regulates the entry of substances into the brain and ensures the homeostasis of the CNS. This review summarizes current research on lipid-based nanoparticles for the nanoencapsulation of neuroprotective compounds. A survey of studies on nanoemulsions (NEs), nanoliposomes/nanophytosomes and solid lipid nanoparticles (SLNs)/nanostructured lipid carriers (NLCs) was carried out and is discussed herein, with particular emphasis upon their unique characteristics, the most important parameters influencing the formulation of each one, and examples of neuroprotective compounds/extracts nanoencapsulated using these nanoparticles. Gastrointestinal absorption is also discussed, as it may pose some obstacles for the absorption of free and nanoencapsulated neuroprotective compounds into the bloodstream, consequently hampering drug concentration in the brain. The transport mechanisms through which compounds or nanoparticles may cross BBB into the brain parenchyma, and the potential to increase drug bioavailability, are also discussed. Additionally, factors contributing to BBB disruption and neurodegeneration are described. Finally, the advantages of, and obstacles to, conventional and unconventional routes of administration to deliver nanoencapsulated neuroprotective drugs to the brain are also discussed, taking into account the avoidance of first-pass metabolism, onset of action, ability to bypass the BBB and concentration of the drug in the brain.
On the Origin of Reduced Cytotoxicity of Germanium-Doped Diamond-Like Carbon: Role of Top Surface Composition and Bonding
Authors: Zemek Josef , Jiricek Petr , Houdkova Jana , Ledinsky Martin , Jelinek Miroslav , Kocourek Tomas
Published: February 2021

This work attempts to understand the behaviour of Ge-induced cytotoxicity of germanium-doped hydrogen-free diamond-like carbon (DLC) films recently thoroughly studied and published by Jelinek et al. At a low doping level, the films showed no cytotoxicity, while at a higher doping level, the films were found to exhibit medium to high cytotoxicity. We demonstrate, using surface-sensitive methods—two-angle X-ray-induced core-level photoelectron spectroscopy (ARXPS) and Low Energy Ion Scattering (LEIS) spectroscopy, that at a low doping level, the layers are capped by a carbon film which impedes the contact of Ge species with tissue. For higher Ge content in the DLC films, oxidized Ge species are located at the top surface of the layers, provoking cytotoxicity. The present results indicate no threshold for Ge concentration in cell culture substrate to avoid a severe toxic reaction.
The Relationship between Food Security Status and Fruit and Vegetable Intake during the COVID-19 Pandemic
Authors: Litton Michelle M. , Beavers Alyssa W.
Published: February 2021

The coronavirus disease 2019 (COVID-19) pandemic has drastically altered food shopping behaviors, and the resulting economic recession has caused a spike in food insecurity. Since food insecurity is associated with poor diet, especially low intake of fruits and vegetables, food-insecure individuals may disproportionately experience negative health impacts related to poor diet during the pandemic. To assess the relationship between food security status and fruit and vegetable intake during the COVID-19 pandemic, we conducted an online survey of adult residents of the US state of Michigan in June of 2020. Among the 484 survey respondents, 36.2% were classified as food-insecure. Food-insecure respondents consumed fruits and vegetables fewer times per day than food-secure respondents and were more likely to report decreasing their consumption of any type of fruits and vegetables (total, fresh, frozen, and canned) since the pandemic started. For those who reduced their purchase of fresh fruit and vegetable, reasons included poor quality, poor availability, high price, reduced store trips, and concerns of contamination. These findings highlight the need for adequate food assistance during the COVID-19 pandemic and in future pandemics, as well as public health messages that promote healthy eating.
Vitamin D and Lung Outcomes in Elderly COVID-19 Patients
Authors: Sulli Alberto , Gotelli Emanuele , Casabella Andrea , Paolino Sabrina , Pizzorni Carmen , Alessandri Elisa , Grosso Marco , Ferone Diego , Smith Vanessa , Cutolo Maurizio
Published: February 2021

Background and aim: Vitamin D deficiency is frequently reported in patients with SARS-CoV-2 infection. The aim of this study was to correlate the 25OH-Vitamin D serum concentrations with clinical parameters of lung involvement, in elderly patients hospitalized for SARS-CoV-2 infection. Methods: Sixty-five consecutive COVID-19 patients (mean age 76 ± 13 years) and sixty-five sex- and age-matched control subjects (CNT) were analyzed. The following clinical parameters, including comorbidities, were collected at admission: type of pulmonary involvement, respiratory parameters (PaO2, SO2, PaCO2, PaO2/FiO2), laboratory parameters (including 25OH-vitamin D, D-dimer, C-reactive protein). Results: Significantly lower vitamin D serum levels were found in COVID-19 patients than in CNT (median 7.9 vs. 16.3 ng/mL, p = 0.001). Interestingly, a statistically significant positive correlation was observed between vitamin D serum levels and PaO2 (p = 0.03), SO2 (p = 0.05), PaO2/FiO2 (p = 0.02), while a statistically significant negative correlation was found between vitamin D serum levels and D-dimer (p = 0.04), C-reactive protein (p = 0.04) and percentage of O2 in a venturi mask (p = 0.04). A negative correlation was also observed between vitamin D serum levels and severity of radiologic pulmonary involvement, evaluated by computed tomography: in particular, vitamin D was found significantly lower in COVID-19 patients with either multiple lung consolidations (p = 0.0001) or diffuse/severe interstitial lung involvement than in those with mild involvement (p = 0.05). Finally, significantly lower vitamin D serum levels were found in the elderly COVID-19 patients who died during hospitalization, compared to those who survived (median 3.0 vs. 8.4 ng/mL, p = 0.046). Conclusions: This study confirms that 25OH-vitamin D serum deficiency is associated with more severe lung involvement, longer disease duration and risk of death, in elderly COVID-19 patients. The detection of low vitamin D levels also in younger COVID-19 patients with less comorbidities further suggests vitamin D deficiency as crucial risk factor at any age.
Cross-Sectional Associations between Mothers and Children’s Breakfast Routine—The Feel4Diabetes-Study
Authors: Giménez-Legarre Natalia , Santaliestra-Pasías Alba , Cardon Greet , Imre Rurik , Iotova Violeta , Kivelä Jemina , Liatis Stavros , Makrilakis Konstantinos , Mavrogianni Christina , Milenkovic Tatjana , Nánási Anna , Tankova Tsvetalina , Timpel Patrick , Willems Ruben , Manios Yannis , Moreno Luis ,   on behalf of the Feel4Diabetes-Study Group
Published: February 2021

Positive influences of family members have been associated with a high probability of children’s daily breakfast consumption. Therefore, the aim of this study was to scrutinize the association of breakfast routines between mothers and their children. The baseline data of the Feel4Diabetes-study was obtained in 9760 children (49.05% boys)–mother pairs in six European countries. A parental self-reported questionnaire gauging the frequency of breakfast consumption and of breakfast´ foods and beverages consumption was used. Agreement in routines of mothers and their children’s breakfast consumption was analyzed in sex-specific crosstabs. The relationship of breakfast routine and food groups’ consumption between mothers and their children was assessed with analysis of covariance. The highest proportion of children who always consumed breakfast were those whose mothers always consumed it. Children consuming breakfast regularly had a higher intake of milk or unsweetened dairy products and all kind of cereal products (low fiber and whole-grain) than occasional breakfast consumers (p < 0.05). The strong similarity between mothers and children suggests a transfer of breakfast routine from mothers to their children, as a high proportion of children who usually consume breakfast were from mothers also consuming breakfast. All breakfast foods and beverages consumption frequencies were similar between children and their mothers.
Deteriorated Dietary Patterns with Regards to Health and Environmental Sustainability among Hungarian Roma Are Not Differentiated from Those of the General Population
Authors: Llanaj Erand , Vincze Ferenc , Kósa Zsigmond , Bárdos Helga , Diószegi Judit , Sándor János , Ádány Róza
Published: February 2021

Nutritional epidemiology studies on Roma people are scarce and, to date, their nutrient-based dietary patterns with regards to both healthy and sustainable dietary considerations have never been reported. We report, for the first time, adherence to healthy and sustainable dietary patterns using scoring and regression models, based on recommendations defined by the World Health Organization, in the Dietary Approaches to Stop Hypertension (DASH) study and the EAT-Lancet report, as well as dietary quality based on Dietary Inflammatory Index (DII) among the Hungarian Roma (HR) population living in North East Hungary, with Hungarian general (HG) adults as reference. Data were obtained from a complex, comparative health survey involving dietary assessment, structured questionnaire-based interview, physical and laboratory examinations on 359 HG and 344 HR subjects in Northeast Hungary. Poisson regressions were fit to models that included DASH, EAT, DII and Healthy Diet Indicator as dependent variables to assess the influence of ethnicity on healthy and sustainable nutrient-based patterns. Adjusted models controlled for all relevant covariates using the residual method indicated poor dietary quality with regards to the selected dietary patterns. These associations were not ethnicity-sensitive, except for DII, where Roma ethnicity was linked to a decrease of DII score (β = −0.455, 95%CI: −0.720; −0.191, p < 0.05). Currently, HR dietary patterns appear to be relatively unhealthy and unsustainable, rendering them vulnerable to elevated risk of ill-health. Nevertheless, their dietary patterns did not strongly differ from HG, which may contribute to Hungarians being one of the most obese and malnourished nations in Europe. Further prospective research on the potential public and environmental health effects of these findings is warranted.
Chemosensory Function in Burning Mouth Syndrome a Comparative Cross-Sectional Study
Authors: López-Jornet Pia , Collado Yolanda , Zambudio Alfonso , Pons-Fuster Eduardo , Castillo Felipe Candela , Tvarijonaviciute Asta
Published: February 2021

Taste and smell are considered to be functions that contribute to the maintenance of good nutritional status. The present study evaluates taste and smell function in patients with burning mouth syndrome (BMS) versus a control group. A cross-sectional study was made of 36 consecutive patients with BMS and 56 healthy patients. Smell was assessed using the Sniffin’ Sticks test, while taste was evaluated with Taste Strips. Oral quality of life was assessed with the Oral Health Impact Profile-14 (OHIP-14), and the severity of dry mouth with the Thompson Xerostomia Inventory. The patients with BMS had a mean age of 60.4 ± 10.5 years, while the controls had a mean age of 61.3 ± 19 years. No significant differences in smell were recorded between the two groups. In contrast, significant differences in taste function were observed between the patients with BMS and the controls. In the patients with BMS, 44.4% suffered taste alterations compared with the 3.4% healthy controls. Further studies in such patients are needed to allow improved management of the chemosensory problems, mouth dryness, and oral health-related quality of life in BMS.
Molecular Diversity of Giardia duodenalis, Cryptosporidium spp., and Blastocystis sp. in Symptomatic and Asymptomatic Schoolchildren in Zambézia Province (Mozambique)
Authors: Muadica Aly S. , Köster Pamela C. , Dashti Alejandro , Bailo Begoña , Hernández-de-Mingo Marta , Balasegaram Sooria , Carmena David
Published: February 2021

Infections by the protist enteroparasites Giardia duodenalis, Cryptosporidium spp., and, to a much lesser extent, Blastocystis sp. are common causes of childhood diarrhoea in low-income countries. This molecular epidemiological study assesses the frequency and molecular diversity of these pathogens in faecal samples from asymptomatic schoolchildren (n = 807) and symptomatic children seeking medical attention (n = 286) in Zambézia province, Mozambique. Detection and molecular characterisation of pathogens was conducted by polymerase chain reaction (PCR)-based methods coupled with Sanger sequencing. Giardia duodenalis was the most prevalent enteric parasite found [41.7%, 95% confidence interval (CI): 38.8–44.7%], followed by Blastocystis sp. (14.1%, 95% CI: 12.1–16.3%), and Cryptosporidium spp. (1.6%, 95% CI: 0.9–2.5%). Sequence analyses revealed the presence of assemblages A (7.0%, 3/43) and B (88.4%, 38/43) within G. duodenalis-positive children. Four Cryptosporidium species were detected, including C. hominis (30.8%; 4/13), C. parvum (30.8%, 4/13), C. felis (30.8%, 4/13), and C. viatorum (7.6%, 1/13). Four Blastocystis subtypes were also identified including ST1 (22.7%; 35/154), ST2 (22.7%; 35/154), ST3 (45.5%; 70/154), and ST4 (9.1%; 14/154). Most of the genotyped samples were from asymptomatic children. This is the first report of C. viatorum and Blastocystis ST4 in Mozambique. Molecular data indicate that anthropic and zoonotic transmission (the latter at an unknown rate) are important spread pathways of diarrhoea-causing pathogens in Mozambique.
A Robust Bioassay of the Human Bradykinin B2 Receptor That Extends Molecular and Cellular Studies: The Isolated Umbilical Vein
Authors: Marceau François , Bachelard Hélène
Published: February 2021

Bradykinin (BK) has various physiological and pathological roles. Medicinal chemistry efforts targeted toward the widely expressed BK B2 receptor (B2R), a G-protein-coupled receptor, were primarily aimed at developing antagonists. The only B2R antagonist in clinical use is the peptide icatibant, approved to abort attacks of hereditary angioedema. However, the anti-inflammatory applications of B2R antagonists are potentially wider. Furthermore, the B2R antagonists notoriously exhibit species-specific pharmacological profiles. Classical smooth muscle contractility assays are exploited over a time scale of several hours and support determining potency, competitiveness, residual agonist activity, specificity, and reversibility of pharmacological agents. The contractility assay based on the isolated human umbilical vein, expressing B2R at physiological density, was introduced when investigating the first non-peptide B2R antagonist (WIN 64338). Small ligand molecules characterized using the assay include the exquisitely potent competitive antagonist, Pharvaris Compound 3 or the partial agonist Fujisawa Compound 47a. The umbilical vein assay is also useful to verify pharmacologic properties of special peptide B2R ligands, such as the carboxypeptidase-activated latent agonists and fluorescent probes. Furthermore, the proposed agonist effect of tissue kallikrein on the B2R has been disproved using the vein. This assay stands in between cellular and molecular pharmacology and in vivo studies.
Design, Synthesis, and Biological Evaluation of a Series of 5- and 7-Hydroxycoumarin Derivatives as 5-HT1A Serotonin Receptor Antagonists
Authors: Ostrowska Kinga , Leśniak Anna , Czarnocka Zuzanna , Chmiel Jagoda , Bujalska-Zadrożny Magdalena , Trzaskowski Bartosz
Published: February 2021

We have designed and synthesized a series of 60 new 5- and 7-hydroxycoumarin derivatives bearing the piperazine moiety with the expected binding to 5-HT1A and 5-HT2A receptors. Molecular docking of all investigated compounds revealed subnanomolar estimates of 5-HT1AR Ki for three ligands and 5-HT2AR Ki for one ligand as well as numerous low nanomolar estimates of Ki for both receptors. Intrigued by these results we synthesized all 60 new derivatives using microwave-assisted protocols. We show that three new compounds show a relatively high antagonistic activity against the 5HT1A receptor, although lower than the reference compound WAY-100635. These compounds also showed relatively low binding affinities to the 5-HT2A receptor. We also provide a detailed structure–activity analysis of this series of compounds and compare it with previously obtained results for an exhaustive series of coumarin derivatives.
Effects of Red and White Ginseng Preparations on Electrical Activity of the Brain in Elderly Subjects: A Randomized, Double-Blind, Placebo-Controlled, Three-Armed Cross-Over Study
Authors: Dimpfel Wilfried , Mariage Pierre-Antoine , Panossian Alexander G.
Published: February 2021

Background: Recently, the superior efficacy of hydroponically cultivated red ginseng preparation HRG80® compared to wild growing white ginseng (WG) in preventing stress-induced symptoms related to the daily work situation of healthy subjects was reported. The aim of this study was to compare the effects of HRG80®, WG, and placebo on the electrical activity in the brain of elderly human subjects during relaxation and mental challenges. Methods: Changes in the electroencephalogram (EEG) frequency ranges of 17 different brain regions were measured after single and repeated administration of HRG80®, WG, and placebo across a four-week randomized, double-blind, placebo-controlled three-armed cross-over trial. Results: Both red and white ginseng preparations had a strong impact on brain activity, with different effects on various brain regions depending on the mental load during relaxation and cognitive tasks associated with memory, attention, and mental performance. Both ginseng preparations exhibited significant effects on spectral powers compared to placebo, reflecting an activating action. The spectral changes in the quantitative EEG induced by HRG80® indicated an improvement in mood as well as calming effects, evidenced by the modulation of β2 waves, representing changes in GABA-ergic neurotransmission. HRG80® attenuated δ/θ powers during relaxation, suggesting the potential improvement of pathologically enhanced spectral power in aging. Conclusion: The results of this study suggest that both hydroponically cultivated red and wild growing white ginseng have similar beneficial effects on the cognitive functions of elderly subjects, as reflected by electric brain activity, but their modes of action on the brain are different.
Understanding Carrier Performance in Low-Dose Dry Powder Inhalation: An In Vitro–In Silico Approach
Authors: Pinto Joana T. , Cachola Inês , F. Pinto João , Paudel Amrit
Published: February 2021

The use of physiologically based pharmacokinetic (PBPK) models to support drug product development has become increasingly popular. The in vitro characterization of the materials of the formulation provides valuable descriptors for the in silico prediction of the drug’s pharmacokinetic profile. Thus, the application of an in vitro–in silico framework can be decisive towards the prediction of the in vivo performance of a new medicine. By applying such an approach, this work aimed to derive mechanistic based insights into the potential impact of carrier particles and powder bulk properties on the in vivo performance of a lactose-based dry powder inhaler (DPI). For this, a PBPK model was developed using salbutamol sulphate (SS) as a model drug and the in vitro performance of its low-dose blends (2% w/w) with different types of lactose particles was investigated using different DPI types (capsule versus reservoir) at distinct airflows. Likewise, the influence of various carrier’s particle and bulk properties, device type and airflow were investigated in silico. Results showed that for the capsule-based device, low-dose blends of SS had a better performance, when smaller carrier particles (Dv0.5 ≈ 50 μm) with about 10% of fines were used. This resulted in a better predicted bioavailability of the drug for all the tested airflows. For the reservoir type DPI, the mean particle size (Dv0.5) was identified as the critical parameter impacting performance. Shear cell and air permeability or compressibility measurements, particle size distribution by pressure titration and the tensile strength of the selected lactose carrier powders were found useful to generate descriptors that could anticipate the potential in vivo performance of the tested DPI blends.
Hepatocellular-Targeted mRNA Delivery Using Functionalized Selenium Nanoparticles In Vitro
Authors: Singh Dhireshan , Singh Moganavelli
Published: February 2021

Selenium’s (Se) chemopreventative and therapeutic properties have attracted attention in nanomedicine. Se nanoparticles (SeNPs) retain these properties of Se while possessing lower toxicity and higher bioavailability, potentiating their use in gene delivery. This study aimed to formulate SeNPs for efficient binding and targeted delivery of FLuc-mRNA to hepatocellular carcinoma cells (HepG2) in vitro. The colorectal adenocarcinoma (Caco-2) and normal human embryonic kidney (HEK293) cells that do not have the asialoorosomucoid receptor (ASGPR) were utilized for comparison. SeNPs were functionalized with chitosan (CS), polyethylene glycol (PEG), and lactobionic acid (LA) for ASGPR targeting on HepG2 cells. Nanoparticles (NPs) and their mRNA-nanocomplexes were characterized by Fourier transform infra-red (FTIR) and UV-vis spectroscopy, transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Gel and fluorescence-based assays assessed the NP’s ability to bind and protect FLuc-mRNA. Cytotoxicity was determined using the -(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay, while transgene expression was evaluated using the luciferase reporter gene assay. All NPs appeared spherical with sizes ranging 57.2–130.0 nm and zeta potentials 14.9–31.4 mV. NPs bound, compacted, and protected the mRNA from nuclease digestion and showed negligible cytotoxicity in vitro. Targeted gene expression was highest in the HepG2 cells using the LA targeted NPs. These NPs portend to be efficient nanocarriers of nucleic acids and warrant further investigation.
The Response of the Associations of Grass and Epichloë Endophytes to the Increased Content of Heavy Metals in the Soil
Authors: Wiewióra Barbara , Żurek Grzegorz
Published: February 2021

The rapid development of civilization increases the area of land exposed to the accumulation of toxic compounds, including heavy metals, both in water and soil. Endophytic fungi associated with many species of grasses are related to the resistance of plants to biotic and abiotic stresses, which include heavy metals. This paper reviews different aspects of symbiotic interactions between grass species and fungal endophytes from the genera Epichloë with special attention paid to the elevated concentration of heavy metals in growing substrates. The evidence shows the high resistance variation of plant endophyte symbiosis on the heavy metals in soil outcome. The fungal endophytes confer high heavy metal tolerance, which is the key feature in its practical application with their host plants, i.e., grasses in phytoremediation.
Thermodynamic Modeling and Validation of the Temperature Influence in Ternary Phase Polymer Systems
Authors: Romay Marta , Diban Nazely , Urtiaga Ane
Published: February 2021

The effect of the temperature, as a process variable in the fabrication of polymeric membranes by the non-solvent induced phase separation (NIPS) technique, has been scarcely studied. In the present work, we studied the influence of temperature, working at 293, 313 and 333 K, on the experimental binodal curves of four ternary systems composed of PVDF and PES as the polymers, DMAc and NMP as the solvents and water as the non-solvent. The increase of the temperature caused an increase on the solubility gap of the ternary system, as expected. The shift of the binodal curve with the temperature was more evident in PVDF systems than in PES systems indicating the influence of the rubbery or glassy state of the polymer on the thermodynamics of phase separation. As a novelty, the present work has introduced the temperature influence on the Flory–Huggins model to fit the experimental cloud points. Binary interaction parameters were calculated as a function of the temperature: (i) non-solvent/solvent (g12) expressions with UNIFAC-Dortmund methodology and (ii) non-solvent/polymer (χ13) and solvent/polymer (χ23) using Hansen solubility parameters. Additionally, the effect of the ternary interaction term was not negligible in the model. Estimated ternary interaction parameters (χ123) presented a linear relation with temperature and negative values, indicating that the solubility of the polymers in mixtures of solvent/non-solvent was higher than expected for single binary interaction. Finally, PES ternary systems exhibited higher influence of the ternary interaction parameter than PVDF systems.
Effect of Neutralizer on Transparency of Nucleating Agent-Containing Polypropylene
Authors: Iwasaki Shohei , Uchiyama Yohei , Tenma Miwa , Yamaguchi Masayuki
Published: February 2021

The effects of neutralizer species on the transparency of injection-molded plates were studied using isotactic polypropylene (PP) containing a crystal nucleating agent—i.e., 1,3:2,4-bis-o-(4-methylbenzylidene)-d-sorbitol (MDBS). A plate containing lithium stearate (StLi) was more transparent than one containing calcium stearate (StCa) when the MDBS content was 0.1 wt. %. The addition of StLi accelerated the formation of MDBS fibers and the crystallization of PP. However, when the MDBS content was 1.0 wt. %, StCa improved the transparency more effectively than StLi. These results indicate that the combination of an appropriate amount of MDBS and the correct neutralizer species is critical for enhancing the transparency of injection-molded PP plates.
Gradient 3D Printed PLA Scaffolds on Biomedical Titanium: Mechanical Evaluation and Biocompatibility
Authors: Portan Diana V. , Ntoulias Christos , Mantzouranis Georgios , Fortis Athanassios P. , Deligianni Despina D. , Polyzos Demosthenes , Kostopoulos Vassilis
Published: February 2021

The goal of the present investigation was to find a solution to crucial engineering aspects related to the elaboration of multi-layered tissue-biomimicking composites. 3D printing technology was used to manufacture single-layered and gradient multi-layered 3D porous scaffolds made of poly-lactic acid (PLA). The scaffolds manufacturing process was optimized after adjusting key printing parameters. The scaffolds with 60 μm side length (square-shaped pores) showed increased stiffness values comparing to the other specimens. A silicone adhesive has been further used to join biomedical titanium plates, and the PLA scaffolds; in addition, titania nanotubes (TNTs were produced on the titanium for improved adhesion. The titanium-PLA scaffold single lap joints were evaluated in micro-tensile testing. The electrochemical processing of the titanium surface resulted in a 248% increase of the ultimate strength in the overlap area for dry specimens and 40% increase for specimens immersed in simulated body fluid. Finally, the biocompatibility of the produced scaffolds was evaluated with primary cell populations obtained after isolation from bone residual tissue. The manufactured scaffolds present promising features for applications in orthopedic implantology and are worth further.
Geometry Analysis and Microhardness Prediction of Nickel-Based Laser Cladding Layer on the Surface of H13 Steel
Authors: Yao Fangping , Fang Lijin , Chen Xiang
Published: February 2021

In order to improve the resistance to thermal fatigue and wear resistance of H13 hot-working tool steel, a nickel-based composite coating was prepared on its surface by laser cladding technology. The relationship was studied between the main processing parameters and the size of the cladding layer such as height and width. Based on the orthogonal polynomial regression method, the relationships were modeled mathematically between laser power, scanning speed, powder feeding voltage and microhardness. This model was proved to be able to predict the laser power and powder feeding voltage under 1100 Hv microhardness.
An Accurate Geocoding Method for GB-SAR Images Based on Solution Space Search and Its Application in Landslide Monitoring
Authors: Cai Jialun , Jia Hongguo , Liu Guoxiang , Zhang Bo , Liu Qiao , Fu Yin , Wang Xiaowen , Zhang Rui
Published: February 2021

Although ground-based synthetic aperture radar (GB-SAR) interferometry has a very high precision with respect to deformation monitoring, it is difficult to match the fan-shaped grid coordinates with the local topography in the geographical space because of the slant range projection imaging mode of the radar. To accurately identify the deformation target and its position, high-accuracy geocoding of the GB-SAR images must be performed to transform them from the two-dimensional plane coordinate system to the three-dimensional (3D) local coordinate system. To overcome difficulties of traditional methods with respect to the selection of control points in GB-SAR images in a complex scattering environment, a high-resolution digital surface model obtained by unmanned aerial vehicle (UAV) aerial photogrammetry was used to establish a high-accuracy GB-SAR coordinate transformation model. An accurate GB-SAR image geocoding method based on solution space search was proposed. Based on this method, three modules are used for geocoding: framework for the unification of coordinate elements, transformation model, and solution space search of the minimum Euclidean distance. By applying this method to the Laoguanjingtai landslide monitoring experiment on Hailuogou Glacier, a subpixel geocoding accuracy was realized. The effectiveness and accuracy of the proposed method were verified by contrastive analysis and error assessment. The method proposed in this study can be applied for accurate 3D interpretation and analysis of the spatiotemporal characteristic in GB-SAR deformation monitoring and should be popularized.
A Wavelength-Resolution SAR Change Detection Method Based on Image Stack through Robust Principal Component Analysis
Authors: Ramos Lucas P. , Campos Alexandre B. , Schwartz Christofer , Duarte Leonardo T. , Alves Dimas I. , Pettersson Mats I. , Vu Viet T. , Machado Renato
Published: February 2021

Recently, it was demonstrated that low-frequency wavelength-resolution synthetic aperture radar (SAR) images could be considered to follow an additive mixing model due to their backscatter characteristics. This simplification allows for the use of source separation methods, such as robust principal component analysis (RPCA) via principal component pursuit (PCP), for detecting changes in those images. In this manuscript, a change detection method for wavelength-resolution SAR images based on image stack through RPCA is proposed. The method aims to explore both the temporal and flight heading diversity of a set of wavelength-resolution multitemporal SAR images in order to detect concealed targets in forestry areas. A heuristic based on three rules for better exploring the RPCA results is introduced, and a new configurable parameter for false alarm reduction based on the analysis of image windows is proposed. The method is evaluated using real data obtained from measurements of the ultrawideband (UWB) very high-frequency (VHF) SAR system CARABAS-II. Experiments for stacks of four and seven reference images are conducted, and the use of reference images acquired with different flight headings is explored. The results indicate that a gain in performance can be achieved by using large image stacks containing, at least, one image of each possible flight heading of the data set, which can result in a probability of detection (PD) above 99% for a false alarm rate (FAR) as low as one false alarm per three square kilometers. Furthermore, it is demonstrated that high PD and low FAR can be achieved, also considering images from similar flight headings as reference images.
Fusion of GF and MODIS Data for Regional-Scale Grassland Community Classification with EVI2 Time-Series and Phenological Features
Authors: Wu Zhenjiang , Zhang Jiahua , Deng Fan , Zhang Sha , Zhang Da , Xun Lan , Javed Tehseen , Liu Guizhen , Liu Dan , Ji Mengfei
Published: February 2021

Satellite-borne multispectral data are suitable for regional-scale grassland community classification owing to comprehensive coverage. However, the spectral similarity of different communities makes it challenging to distinguish them based on a single multispectral data. To address this issue, we proposed a support vector machine (SVM)–based method integrating multispectral data, two-band enhanced vegetation index (EVI2) time-series, and phenological features extracted from Chinese GaoFen (GF)-1/6 satellite with (16 m) spatial and (2 d) temporal resolution. To obtain cloud-free images, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) algorithm was employed in this study. By using the algorithm on the coarse cloudless images at the same or similar time as the fine images with cloud cover, the cloudless fine images were obtained, and the cloudless EVI2 time-series and phenological features were generated. The developed method was applied to identify grassland communities in Ordos, China. The results show that the Caragana pumila Pojark, Caragana davazamcii Sanchir and Salix schwerinii E. L. Wolf grassland, the Potaninia mongolica Maxim, Ammopiptanthus mongolicus S. H. Cheng and Tetraena mongolica Maxim grassland, the Caryopteris mongholica Bunge and Artemisia ordosica Krasch grassland, the Calligonum mongolicum Turcz grassland, and the Stipa breviflora Griseb and Stipa bungeana Trin grassland are distinguished with an overall accuracy of 87.25%. The results highlight that, compared to multispectral data only, the addition of EVI2 time-series and phenological features improves the classification accuracy by 9.63% and 14.7%, respectively, and even by 27.36% when these two features are combined together, and indicate the advantage of the fine images in this study, compared to 500 m moderate-resolution imaging spectroradiometer (MODIS) data, which are commonly used for grassland classification at regional scale, while using 16 m GF data suggests a 23.96% increase in classification accuracy with the same extracted features. This study indicates that the proposed method is suitable for regional-scale grassland community classification.
A Regional Zenith Tropospheric Delay (ZTD) Model Based on GPT3 and ANN
Authors: Yang Fei , Guo Jiming , Zhang Chaoyang , Li Yitao , Li Jun
Published: February 2021

The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS positioning and navigation and GNSS meteorology. Establishing a stable and reliable ZTD model is one of the interests in GNSS research. In this study, we proposed a regional ZTD model that makes full use of the ZTD calculated from regional GNSS data and the corresponding ZTD estimated by global pressure and temperature 3 (GPT3) model, adopting the artificial neutral network (ANN) to construct the correlation between ZTD derived from GPT3 and GNSS observations. The experiments in Hong Kong using Satellite Positioning Reference Station Network (SatRet) were conducted and three statistical values, i.e., bias, root mean square error (RMSE), and compound relative error (CRE) were adopted for our comparisons. Numerical results showed that the proposed model outperformed the parameter ZTD model (Saastamoinen model) and the empirical ZTD model (GPT3 model), with an approximately 56%/52% and 52%/37% RMSE improvement in the internal and external accuracy verification, respectively. Moreover, the proposed method effectively improved the systematic deviation of GPT3 model and achieved better ZTD estimation in both rainy and rainless conditions.
Mars3DNet: CNN-Based High-Resolution 3D Reconstruction of the Martian Surface from Single Images
Authors: Chen Zeyu , Wu Bo , Liu Wai Chung
Published: February 2021

Three-dimensional (3D) surface models, e.g., digital elevation models (DEMs), are important for planetary exploration missions and scientific research. Current DEMs of the Martian surface are mainly generated by laser altimetry or photogrammetry, which have respective limitations. Laser altimetry cannot produce high-resolution DEMs; photogrammetry requires stereo images, but high-resolution stereo images of Mars are rare. An alternative is the convolutional neural network (CNN) technique, which implicitly learns features by assigning corresponding inputs and outputs. In recent years, CNNs have exhibited promising performance in the 3D reconstruction of close-range scenes. In this paper, we present a CNN-based algorithm that is capable of generating DEMs from single images; the DEMs have the same resolutions as the input images. An existing low-resolution DEM is used to provide global information. Synthetic and real data, including context camera (CTX) images and DEMs from stereo High-Resolution Imaging Science Experiment (HiRISE) images, are used as training data. The performance of the proposed method is evaluated using single CTX images of representative landforms on Mars, and the generated DEMs are compared with those obtained from stereo HiRISE images. The experimental results show promising performance of the proposed method. The topographic details are well reconstructed, and the geometric accuracies achieve root-mean-square error (RMSE) values ranging from 2.1 m to 12.2 m (approximately 0.5 to 2 pixels in the image space). The experimental results show that the proposed CNN-based method has great potential for 3D surface reconstruction in planetary applications.
Normalized Difference Vegetation Index Temporal Responses to Temperature and Precipitation in Arid Rangelands
Authors: Sanz Ernesto , Saa-Requejo Antonio , Díaz-Ambrona Carlos H. , Ruiz-Ramos Margarita , Rodríguez Alfredo , Iglesias Eva , Esteve Paloma , Soriano Bárbara , Tarquis Ana M.
Published: February 2021

Rangeland degradation caused by increasing misuses remains a global concern. Rangelands have a remarkable spatiotemporal heterogeneity, making them suitable to be monitored with remote sensing. Among the remotely sensed vegetation indices, Normalized Difference Vegetation Index (NDVI) is most used in ecology and agriculture. In this paper, we research the relationship of NDVI with temperature, precipitation, and Aridity Index (AI) in four different arid rangeland areas in Spain’s southeast. We focus on the interphase variability, studying time series from 2002 to 2019 with regression analysis and lagged correlation at two different spatial resolutions (500 × 500 and 250 × 250 m2) to understand NDVI response to meteorological variables. Intraseasonal phases were defined based on NDVI patterns. Strong correlation with temperature was reported in phases with high precipitations. The correlation between NDVI and meteorological series showed a time lag effect depending on the area, phase, and variable observed. Differences were found between the two resolutions, showing a stronger relationship with the finer one. Land uses and management affected the NDVI dynamics heavily strongly linked to temperature and water availability. The relationship between AI and NDVI clustered the areas in two groups. The intraphases variability is a crucial aspect of NDVI dynamics, particularly in arid regions.
Unsupervised Machine Learning on Domes in the Lunar Gardner Region: Implications for Dome Classification and Local Magmatic Activities on the Moon
Authors: Chen Yuchao , Huang Qian , Zhao Jiannan , Hu Xiangyun
Published: February 2021

Lunar volcanic domes are essential windows into the local magmatic activities on the Moon. Classification of domes is a useful way to figure out the relationship between dome appearances and formation processes. Previous studies of dome classification were manually or semi-automatically carried out either qualitatively or quantitively. We applied an unsupervised machine-learning method to domes that are annularly or radially distributed around Gardner, a unique central-vent volcano located in the northern part of the Mare Tranquillitatis. High-resolution lunar imaging and spectral data were used to extract morphometric and spectral properties of domes in both the Gardner volcano and its surrounding region in the Mare Tranquillitatis. An integrated robust Fuzzy C-Means clustering algorithm was performed on 120 combinations of five morphometric (diameter, area, height, surface volume, and slope) and two elemental features (FeO and TiO2 contents) to find the optimum combination. Rheological features of domes and their dike formation parameters were calculated for dome-forming lava explanations. Results show that diameter, area, surface volume, and slope are the selected optimum features for dome clustering. 54 studied domes can be grouped into four dome clusters (DC1 to DC4). DC1 domes are relatively small, steep, and close to the Gardner volcano, with forming lavas of high viscosities and low effusion rates, representing the latest Eratosthenian dome formation stage of the Gardner volcano. Domes of DC2 to DC4 are relatively large, smooth, and widely distributed, with forming lavas of low viscosities and high effusion rates, representing magmatic activities varying from Imbrian to Eratosthenian in the northern Mare Tranquillitatis. The integrated algorithm provides a new and independent way to figure out the representative properties of lunar domes and helps us further clarify the relationship between dome clusters and local magma activities of the Moon.
Multisensor and Multiresolution Remote Sensing Image Classification through a Causal Hierarchical Markov Framework and Decision Tree Ensembles
Authors: Pastorino Martina , Montaldo Alessandro , Fronda Luca , Hedhli Ihsen , Moser Gabriele , Serpico Sebastiano B. , Zerubia Josiane
Published: February 2021

In this paper, a hierarchical probabilistic graphical model is proposed to tackle joint classification of multiresolution and multisensor remote sensing images of the same scene. This problem is crucial in the study of satellite imagery and jointly involves multiresolution and multisensor image fusion. The proposed framework consists of a hierarchical Markov model with a quadtree structure to model information contained in different spatial scales, a planar Markov model to account for contextual spatial information at each resolution, and decision tree ensembles for pixelwise modeling. This probabilistic graphical model and its topology are especially fit for application to very high resolution (VHR) image data. The theoretical properties of the proposed model are analyzed: the causality of the whole framework is mathematically proved, granting the use of time-efficient inference algorithms such as the marginal posterior mode criterion, which is non-iterative when applied to quadtree structures. This is mostly advantageous for classification methods linked to multiresolution tasks formulated on hierarchical Markov models. Within the proposed framework, two multimodal classification algorithms are developed, that incorporate Markov mesh and spatial Markov chain concepts. The results obtained in the experimental validation conducted with two datasets containing VHR multispectral, panchromatic, and radar satellite images, verify the effectiveness of the proposed framework. The proposed approach is also compared to previous methods that are based on alternate strategies for multimodal fusion.
Multi-Path and Group-Loss-Based Network for Speech Emotion Recognition in Multi-Domain Datasets
Authors: Noh Kyoung Ju , Jeong Chi Yoon , Lim Jiyoun , Chung Seungeun , Kim Gague , Lim Jeong Mook , Jeong Hyuntae
Published: February 2021

Speech emotion recognition (SER) is a natural method of recognizing individual emotions in everyday life. To distribute SER models to real-world applications, some key challenges must be overcome, such as the lack of datasets tagged with emotion labels and the weak generalization of the SER model for an unseen target domain. This study proposes a multi-path and group-loss-based network (MPGLN) for SER to support multi-domain adaptation. The proposed model includes a bidirectional long short-term memory-based temporal feature generator and a transferred feature extractor from the pre-trained VGG-like audio classification model (VGGish), and it learns simultaneously based on multiple losses according to the association of emotion labels in the discrete and dimensional models. For the evaluation of the MPGLN SER as applied to multi-cultural domain datasets, the Korean Emotional Speech Database (KESD), including KESDy18 and KESDy19, is constructed, and the English-speaking Interactive Emotional Dyadic Motion Capture database (IEMOCAP) is used. The evaluation of multi-domain adaptation and domain generalization showed 3.7% and 3.5% improvements, respectively, of the F1 score when comparing the performance of MPGLN SER with a baseline SER model that uses a temporal feature generator. We show that the MPGLN SER efficiently supports multi-domain adaptation and reinforces model generalization.
Intelligent Technology to Enhance Policing and Public Accountability
Authors:   Brazilian Federal Highway Police, Fortaleza/CE, Brazil, Aloísio Vieira Lira Neto ,   University of Fortaleza, Fortaleza/CE, Brazil
Published: February 2021

In view of the situation of violence faced in Brazil, several actors, from the most diverse areas of knowledge, have been dedicated to studying, analyzing and proposing solutions for public security. The great challenge of much of what is produced is to combine theory with practice. In addition, the fact that we do not have State policies, but Government policies contribute significantly to the lack of long-term studies. Discontinuities, whether due to the ineffectiveness of what is proposed, or due to cultural and organizational changes in crime, preclude a cycle of planning, execution, evaluation and correction. This brings us to the first observation of modern public security: volatility. Thus, it is impossible to imagine modern management without the use of technology for the quick and assertive analysis of the problems faced. In this sense, the use of the intelligence, strategy, and technology triad becomes essential for accurate monitoring of these changes, providing guidelines and subsidies for the modernization of public security management and security and policing matrix. Given these statements, the present study has the general objective of presenting the Policy to Combat the Mobility of Crime and its effects on the Public Security of the State of Cear[Pleaseinsert“PrerenderUnicode–˝intopreamble] (Brazil), referring to the period from 2017 to 2019. Through an empirical analysis, statistical data were collected to present a direct scenario of the implementation and the results achieved and present the theoretical relationship between the actions and the results, thus providing an exploratory depth of the facts and their impacts. In order to show the positive results achieved, a quantitative and qualitative method was used to correlate aspects and concepts in the large area of the humanities with practical policing and technological applications. As a result of the implementation of the Combating the Mobility of Crime, the State of Cear[Pleaseinsert“PrerenderUnicode–˝intopreamble] managed to place the number of robberies and homicides among the lowest rates of the decade, gaining national prominence of strategy and technology employed. Thus, the Policy to Combat the Mobility of Crime changed the policing matrix, allowing greater efficiency of the resources used and better monitoring the indicators.