bluuebunny/crossref_metadata_2025 huggingface dataset:
Inflammatory Potential of Diet Is Associated with Biomarkers Levels of Inflammation and Cognitive Function among Postmenopausal Women
Authors: Skoczek-Rubińska Aleksandra , Muzsik-Kazimierska Agata , Chmurzynska Agata , Jamka Małgorzata , Walkowiak Jarosław , Bajerska Joanna
Published: July 2021

In postmenopausal women (PW), estrogen depletion may predispose to cognitive decline through an increased risk of chronic inflammation. Unhealthy diets also appear to have an impact on the cognitive health of these women. The aim of this study was to investigate the association between inflammatory potential of the diet, levels of inflammatory biomarkers, and cognitive function in PW. In a population of 222 PW, energy intake-adjusted Dietary Inflammatory Index (E-DII) was used to assess the dietary inflammatory potential. Cognitive function was estimated using the Polish version of Mini-Mental State Examination (MMSE), corrected by age and educational level. Selected biochemical inflammatory markers (C-reactive protein, CRP; interleukin-6, IL-6; and tumor necrosis factor alpha, TNF-α) were measured by ELISA tests. PW with an anti-inflammatory diet (first tercile) had significantly higher MMSE, while BMI, percentage fat mass and TNFα concentration were significantly lower compared to those with the most proinflammatory diets (third tercile). Women with cognitive impairment had significantly higher IL-6 concentrations (4.1 (0.8) pg/mL vs. 2.5 (0.2) pg/mL, p = 0.004), and were less educated (12.7 (0.7) years vs. 14.1 (0.2) years, p = 0.03) and less physically active compared to cognitively normal women. PW with the most proinflammatory diets had increased odds of cognitive impairment compared to those with the most anti-inflammatory diets, even after adjustment (OR = 11.10, 95% confidence level; 95%CI: 2.22; 55.56; p = 0.002). Each one-point increase in E-DII (as a continuous value) was also associated with 1.55-times greater odds of cognitive impairment (95%Cl: 1.19; 2.02 p = 0.003) in this population. Dietary inflammation may increase the risk of cognitive impairment in PW, but future studies should include a more sensitive battery of tests to assess cognitive function in this population. Implementation of an anti-inflammatory dietary pattern in PW may help prevent cognitive decline.
Presence and Levels of Galactosyllactoses and Other Oligosaccharides in Human Milk and Their Variation during Lactation and According to Maternal Phenotype
Authors: Eussen Simone R. B. M. , Mank Marko , Kottler Robert , Hoffmann Xenia-Katharina , Behne Alexander , Rapp Erdmann , Stahl Bernd , Mearin M. Luisa , Koletzko Berthold
Published: July 2021

Among the human milk oligosaccharides (HMOS), the galactosyllactoses (GLs) are only limitedly studied. This study aims to describe the presence and relative levels of HMOS, including GLs, in human milk (HM) according to maternal Secretor and Lewis (SeLe) phenotype and lactation stage. Relative levels of 19 HMOS were measured in 715 HM samples collected in the first 4 months postpartum from 371 donors participating in the PreventCD study. From a subset of 24 Dutch women (171 HM samples), samples were collected monthly up to 12 months postpartum and were additionally analyzed for relative and absolute levels of β6′-GL, β3′-GL and α3′-GL. Maternal SeLe phenotype or HM group was assigned based on the presence of specific fucosylated HMOS. Most HMOS, including β6′- and β3′-GL, were present in the vast majority (≥75%) of HM samples, whereas others (e.g., LNDFH II, 2′-F-LNH and α3′-GL) only occurred in a low number (<25%) of samples. Clear differences were observed between the presence and relative levels of the HMOS according to the maternal phenotype and lactation stage. Absolute concentrations of β6′-GL and β3′-GL were higher in HM group IV samples compared to samples of the other three HM groups. β3′-GL was also higher in HM group II samples compared to HM group I samples. β3′-GL and β6′-GL were stable over lactation stages. In conclusion, presence and levels of HMOS vary according to HM group and lactation stage. Not all HMOS behave similarly: some HMOS depend strongly on maternal phenotype and/or lactation stage, whereas others do not. β3′-GL and β6′-GL were present in low concentrations in over 75% of the analyzed HM samples and showed differences between HM groups, but not between the lactation stages.
Discovery and Characterization of a Novel MASTL Inhibitor MKI-2 Targeting MASTL-PP2A in Breast Cancer Cells and Oocytes
Authors: Kang Minsung , Kim Chijung , Leem Jiyeon , Kim Ye-hyun , Kwon Young-ju , Yoon Yi Na , Chae Chong Hak , Ahn Jiyeon , Jung Kwan-Young , Oh Jeong Su , Kim Jae-Sung
Published: July 2021

Although microtubule-associated serine/threonine kinase-like (MASTL) is a promising target for selective anticancer treatment, MASTL inhibitors with nano range potency and antitumor efficacy have not been reported. Here, we report a novel potent and selective MASTL inhibitor MASTL kinase inhibitor-2 (MKI-2) identified in silico through a drug discovery program. Our data showed that MKI-2 inhibited recombinant MASTL activity and cellular MASTL activity with IC50 values of 37.44 nM and 142.7 nM, respectively, in breast cancer cells. In addition, MKI-2 inhibited MASTL kinase rather than other AGC kinases, such as ROCK1, AKT1, PKACα, and p70S6K. Furthermore, MKI-2 exerted various antitumor activities by inducing mitotic catastrophe resulting from the modulation of the MASTL-PP2A axis in breast cancer cells. The MKI-2 treatment showed phenocopies with MASTL-null oocyte in mouse oocytes, which were used as a model to validate MKI-2 activity. Therefore, our study provided a new potent and selective MASTL inhibitor MKI-2 targeting the oncogenic MAST-PP2A axis in breast cancer cells.
Tumor-Targeted Fluorescent Proteinoid Nanocapsules Encapsulating Synergistic Drugs for Personalized Cancer Therapy
Authors: Itzhaki Ella , Hadad Elad , Moskovits Neta , Stemmer Salomon M. , Margel Shlomo
Published: July 2021

Personalized cancer treatment based on specific mutations offers targeted therapy and is preferred over “standard” chemotherapy. Proteinoid polymers produced by thermal step-growth polymerization of amino acids may form nanocapsules (NCs) that encapsulate drugs overcoming miscibility problems and allowing passive targeted delivery with reduced side effects. The arginine-glycine-glutamic acid (RGD) sequence is known for its preferential attraction to αvβ3 integrin, which is highly expressed on neovascular endothelial cells that support tumor growth. Here, tumor-targeted RGD-based proteinoid NCs entrapping a synergistic combination of Palbociclib (Pal) and Alpelisib (Alp) were synthesized by self-assembly to induce the reduction of tumor cell growth in different types of cancers. The diameters of the hollow and drug encapsulating poly(RGD) NCs were 34 ± 5 and 22 ± 3 nm, respectively; thereby, their drug targeted efficiency is due to both passive and active targeting. The encapsulation yield of Pal and Alp was 70 and 90%, respectively. In vitro experiments with A549, MCF7 and HCT116 human cancer cells demonstrate a synergistic effect of Pal and Alp, controlled release and dose dependence. Preliminary results in a 3D tumor spheroid model with cells derived from patient-derived xenografts of colon cancer illustrate disassembly of spheroids, indicating that the NCs have therapeutic potential.
Ac-EAZY! Towards GMP-Compliant Module Syntheses of 225Ac-Labeled Peptides for Clinical Application
Authors: Pretze Marc , Kunkel Falk , Runge Roswitha , Freudenberg Robert , Braune Anja , Hartmann Holger , Schwarz Uwe , Brogsitter Claudia , Kotzerke Jörg
Published: July 2021

The application of 225Ac (half-life T1/2 = 9.92 d) dramatically reduces the activity used for peptide receptor radionuclide therapy by a factor of 1000 in comparison to 90Y, 177Lu or 188Re while maintaining the therapeutic outcome. Additionally, the range of alpha particles of 225Ac and its daughter nuclides in tissue is much lower (47–85 μm for alpha energies Eα = 5.8–8.4 MeV), which results in a very precise dose deposition within the tumor. DOTA-conjugated commercially available peptides used for endoradiotherapy, which can readily be labeled with 177Lu or 90Y, can also accommodate 225Ac. The benefits are lower doses in normal tissue for the patient, dose reduction of the employees and environment and less shielding material. The low availability of 225Ac activity is preventing its application in clinical practice. Overcoming this barrier would open a broad field of 225Ac therapy. Independent which production pathway of 225Ac proves the most feasible, the use of automated synthesis and feasible and reproducible patient doses are needed. The Modular-Lab EAZY is one example of a GMP-compliant system, and the cassettes used for synthesis are small. Therefore, also the waste after the synthesis can be minimized. In this work, two different automated setups with different purification systems are presented. In its final configuration, three masterbatches were performed on the ML EAZY for DOTA-TATE and PSMA-I&T, respectively, fulfilling all quality criteria with final radiochemical yields of 80–90% for the 225Ac-labeled peptides.
Nanoemulsions: A Review on the Conceptualization of Treatment for Psoriasis Using a ‘Green’ Surfactant with Low-Energy Emulsification Method
Authors: Dinshaw Ignatius Julian , Ahmad Noraini , Salim Norazlinaliza , Leo Bey Fen
Published: July 2021

Psoriasis is a skin disease that is not lethal and does not spread through bodily contact. However, this seemingly harmless condition can lead to a loss of confidence and social stigmatization due to a persons’ flawed appearance. The conventional methods of psoriasis treatment include taking in systemic drugs to inhibit immunoresponses within the body or applying topical drugs onto the surface of the skin to inhibit cell proliferation. Topical methods are favored as they pose lesser side effects compared to the systemic methods. However, the side effects from systemic drugs and low bioavailability of topical drugs are the limitations to the treatment. The use of nanotechnology in this field has enhanced drug loading capacity and reduced dosage size. In this review, biosurfactants were introduced as a ‘greener’ alternative to their synthetic counterparts. Glycolipid biosurfactants are specifically suited for anti-psoriatic application due to their characteristic skin-enhancing qualities. The selection of a suitable oil phase can also contribute to the anti-psoriatic effect as some oils have skin-healing properties. The review covers the pathogenic pathway of psoriasis, conventional treatments, and prospective ingredients to be used as components in the nanoemulsion formulation. Furthermore, an insight into the state-of-the-art methods used in formulating nanoemulsions and their progression to low-energy methods are also elaborated in detail.
Two Novel PET Radiopharmaceuticals for Endothelial Vascular Cell Adhesion Molecule-1 (VCAM-1) Targeting
Authors: Pastorino Sara , Baldassari Sara , Ailuno Giorgia , Zuccari Guendalina , Drava Giuliana , Petretto Andrea , Cossu Vanessa , Marini Cecilia , Alfei Silvana , Florio Tullio , Sambuceti Gianmario , Caviglioli Gabriele
Published: July 2021

Atherosclerosis is a chronic progressive disease involving inflammatory events, such as the overexpression of adhesion molecules including the endothelial Vascular Cell Adhesion Molecule-1 (VCAM-1). VCAM-1 is rapidly overexpressed in the first stages of atherosclerosis, thus representing a promising target for early atheroma detection. Two novel Positron Emission Tomography (PET) radiopharmaceuticals (MacroP and NAMP), based on the VCAM-1-binding peptide having sequence VHPKQHRGGSKGC, were synthesized and characterized. MacroP is derived from the direct conjugation of a DOTA derivative with the peptide, while NAMP is a biotin derivative conceived to be employed in a three-step pretargeting system, involving the use of a double-chelating derivative of DOTA. The identity of the newly synthesized radiopharmaceuticals was confirmed by mass spectrometry and, after radiolabeling with 68Ga, both showed high radiochemical purity; in vitro tests on human umbilical vein endothelial cells evidenced their VCAM-1 binding ability, with higher radioactive uptake in the case of NAMP. Moreover, NAMP might also be employed in a theranostic approach in association with functionalized biotinylated nanoparticles.
A Morphology-Based Model to Describe the Low-Temperature Impact Behaviour of Rubber-Toughened Polypropylene
Authors: Deblieck Rudy , Remerie Klaas , Van den Fonteyne Winke , Boerakker Mark
Published: July 2021

The roles of the rubber particle size, the rubber particle size distribution and the constitutive behaviour of the isotactic polypropylene matrix have been studied by combining the Lazerri–Bucknall energy criterion for cavitation with the Van der Sanden–Meier–Tervoort ligament model adapted for impact conditions. It is concluded that an optimised morphology offers great potential to achieve enhanced mechanical properties with far less rubber and hence achieve a superior stiffness/toughness/processing balance.
Colorimetric Sensing of Amoxicillin Facilitated by Molecularly Imprinted Polymers
Authors: Lowdon Joseph W , Diliën Hanne , van Grinsven Bart , Eersels Kasper , Cleij Thomas J.
Published: July 2021

The scope of the presented research orientates itself towards the development of a Molecularly Imprinted Polymer (MIP)-based dye displacement assay for the colorimetric detection of the antibiotic amoxicillin in aqueous medium. With this in mind, the initial development of an MIP capable of such a task sets focus on monolithic bulk polymerization to assess monomer/crosslinker combinations that have potential towards the binding of amoxicillin. The best performing composition (based on specificity and binding capacity) is utilized in the synthesis of MIP particles by emulsion polymerization, yielding particles that prove to be more homogenous in size and morphology compared to that of the crushed monolithic MIP, which is an essential trait when it comes to the accuracy of the resulting assay. The specificity and selectivity of the emulsion MIP proceeds to be highlighted, demonstrating a higher affinity towards amoxicillin compared to other compounds of the aminopenicillin class (ampicillin and cloxacillin). Conversion of the polymeric receptor is then undertaken, identifying a suitable dye for the displacement assay by means of binding experiments with malachite green, crystal violet, and mordant orange. Once identified, the optimal dye is then loaded onto the synthetic receptor, and the displaceability of the dye deduced by means of a dose response experiment. Alongside the sensitivity, the selectivity of the assay is scrutinized against cloxacillin and ampicillin. Yielding a dye displacement assay that can be used (semi-)quantitatively in a rapid manner.
Synthesis and Antimicrobial Properties of Highly Cross-Linked pH-Sensitive Hydrogels through Gamma Radiation
Authors: Bustamante-Torres Moises , Pino-Ramos Victor H. , Romero-Fierro David , Hidalgo-Bonilla Sandra P. , Magaña Héctor , Bucio Emilio
Published: July 2021

The design of new polymeric systems for antimicrobial drug release focused on medical/surgical procedures is of great interest in the biomedical area due to the high prevalence of bacterial infections in patients with wounds or burns. For this reason, in this work, we present a new design of pH-sensitive hydrogels copolymerized by a graft polymerization method (gamma rays), intended for localized prophylactic release of ciprofloxacin and silver nanoparticles (AgNPs) for potential topical bacterial infections. The synthesized hydrogels were copolymerized from acrylic acid (AAc) and agar. Cross-linked hydrogel film formation depended on monomer concentrations and the degree of radiation used (Cobalt-60). The obtained hydrogel films were characterized by attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and mechanical testing. The swelling of the hydrogels was evidenced by the influence of their pH-sensitiveness. The hydrogel was loaded with antimicrobial agents (AgNPs or ciprofloxacin), and their related activity was evaluated. Finally, the antimicrobial activity of biocidal-loaded hydrogel was tested against Escherichia coli (E. coli) and methicillin-resistant Staphylococcus aureus (MRSA) on in vitro conditions.
A DFT Study on the Interaction of Doped Carbon Nanotubes with H2S, SO2 and Thiophene
Authors: Tavakol Hossein , Haghshenas Hamed
Published: July 2021

The interactions of simple and Al-, B-, N-, S-, P-, and Si-doped carbon nanotubes with three sulfur-containing molecules (H2S, SO2, and thiophene) were investigated to assess their adsorption potencies and sensor abilities. The DFT method was used to calculate the adsorption energies and natural bond orbitals parameters. In addition, population analyses were performed to calculate the energy gaps and reactivity parameters. The results showed an exothermic interaction of H2S, SO2, and thiophene with simple and doped carbon nanotubes, while the maximum negative adsorption energies belong to Al- and B-containing complexes. Furthermore, evaluation of second-order perturbation energies (obtained from natural bond orbitals calculations) confirmed that the highest energies were related to B- and Al-containing intramolecular interactions. The results revealed the favorability of adsorption of SO2 by nanotubes (B- and Al-doped carbon nanotubes, in particular) compared with the other examined adsorbates.
Quantitative Investigation of Radiometric Interactions between Snowfall, Snow Cover, and Cloud Liquid Water over Land
Authors: Takbiri Zeinab , Milani Lisa , Guilloteau Clement , Foufoula-Georgiou Efi
Published: July 2021

Falling snow alters its own microwave signatures when it begins to accumulate on the ground, making retrieval of snowfall challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual observations by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over shallow snow cover (snow water equivalent (SWE) ≤100 kg m−2) and low values of cloud liquid water path (LWP 100–150 g m−2), the scattering of light snowfall (intensities ≤0.5 mm h−1) is detectable only at frequency 166 GHz, while for higher snowfall rates, the signal can also be detected at 89 GHz. However, when SWE exceeds 200 kg m−2 and the LWP is greater than 100–150 g m−2, the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 than 166 GHz. The results also reveal that over high latitudes above 60°N where the SWE is greater than 200 kg m−2 and LWP is lower than 100–150 g m−2, the snowfall microwave signal could not be detected with GPM without considering a priori data about SWE and LWP. Our findings provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.
A Regional Model for Predicting Tropospheric Delay and Weighted Mean Temperature in China Based on GRAPES_MESO Forecasting Products
Authors: Cao Liying , Zhang Bao , Li Junyu , Yao Yibin , Liu Lilong , Ran Qishun , Xiong Zhaohui
Published: July 2021

Accurate tropospheric delay (TD) and weighted mean temperature (Tm) are important for Global Navigation Satellite System (GNSS) positioning and GNSS meteorology. For this purpose, plenty of empirical models have been built to provide estimates of TD and Tm. However, these models cannot resolve TD and Tm variations at synoptic timescales since they only model the average annual, semi-annual, and/or daily variations. As a result, the existed empirical models cannot perform well under extreme weather conditions. To address this limitation, we propose to estimate Zenith Hydrostatic Delay (ZHD), Zenith Wet Delay (ZWD), and Tm directly from the stratified numerical weather forecasting products of the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_MESO) of China. The GRAPES_MESO forecasting data has a temporal resolution of 3 h, which provides the opportunity to resolve the synoptic variation. However, it is found that the estimated ZWD and Tm exhibit apparent systematic deviation from in situ observation-based estimates, which is due to the inherent biases in the GRAPES_MESO data. To solve this problem, we propose to correct these biases using a linear model and a spherical cap harmonic model. The estimates after correction are termed as the “CTropGrid” products. When validated by the radiosonde data, the CTropGrid product has biases of 1.5 mm, −0.7 mm, and −0.1 K, and Root Mean Square (RMS) error of 8.9 mm, 20.2 mm, and 1.5 K for ZHD, ZWD, and Tm. Compared to the widely used GPT2w model, the CTropGrid products have improved the accuracies of ZHD, ZWD, and Tm by 11.9%, 55.6%, and 60.5% in terms of RMS. When validating the Zenith Tropospheric Delay (ZTD) products (the sum of ZHD and ZWD) using the IGS ZTD data, the CTropGrid ZTD has a bias of −0.7 mm and an RMS of 35.8 mm, which is 22.7% better than the GPT2w model in terms of RMS. Besides the accuracy improvements, the CTropGrid products well model the synoptic-scale variations of ZHD, ZWD, and Tm. Compared to the existing empirical models that only capture the tidal (seasonal and/or diurnal) variations, the CTropGrid products capture well the non-tidal variations of ZHD, ZWD, and Tm, which enhances the tropospheric delay corrections and GNSS water vapor monitoring at synoptic timescales. Therefore, the CTropGrid product is an important progress in GNSS positioning and GNSS meteorology.
Change Capsule Network for Optical Remote Sensing Image Change Detection
Authors: Xu Quanfu , Chen Keming , Zhou Guangyao , Sun Xian
Published: July 2021

Change detection based on deep learning has made great progress recently, but there are still some challenges, such as the small data size in open-labeled datasets, the different viewpoints in image pairs, and the poor similarity measures in feature pairs. To alleviate these problems, this paper presents a novel change capsule network by taking advantage of a capsule network that can better deal with the different viewpoints and can achieve satisfactory performance with small training data for optical remote sensing image change detection. First, two identical non-shared weight capsule networks are designed to extract the vector-based features of image pairs. Second, the unchanged region reconstruction module is adopted to keep the feature space of the unchanged region more consistent. Third, vector cosine and vector difference are utilized to compare the vector-based features in a capsule network efficiently, which can enlarge the separability between the changed pixels and the unchanged pixels. Finally, a binary change map can be produced by analyzing both the vector cosine and vector difference. From the unchanged region reconstruction module and the vector cosine and vector difference module, the extracted feature pairs in a change capsule network are more comparable and separable. Moreover, to test the effectiveness of the proposed change capsule network in dealing with the different viewpoints in multi-temporal images, we collect a new change detection dataset from a taken-over Al Udeid Air Basee (AUAB) using Google Earth. The results of the experiments carried out on the AUAB dataset show that a change capsule network can better deal with the different viewpoints and can improve the comparability and separability of feature pairs. Furthermore, a comparison of the experimental results carried out on the AUAB dataset and SZTAKI AirChange Benchmark Set demonstrates the effectiveness and superiority of the proposed method.
Using Discrete-Point LiDAR to Classify Tree Species in the Riparian Pacific Northwest, USA
Authors: Tatum Julia , Wallin David
Published: July 2021

Practical methods for tree species identification are important for both land management and scientific inquiry. LiDAR has been widely used for species mapping due to its ability to characterize 3D structure, but in structurally complex Pacific Northwest forests, additional research is needed. To address this need and to determine the feasibility of species modeling in such forests, we compared six approaches using five algorithms available in R’s lidR package and Trimble’s eCognition software to determine which approach most consistently identified individual trees across a heterogenous riparian landscape. We then classified segments into Douglas fir (Pseudotsuga menziesii), black cottonwood (Populus balsamifera ssp. trichocarpa), and red alder (Alnus rubra). Classification accuracies based on the best-performing segmentation method were 91%, 92%, and 84%, respectively. To our knowledge, this is the first study to investigate tree species modeling from LiDAR in a natural Pacific Northwest forest, and the first to model Pacific Northwest species at the landscape scale. Our results suggest that LiDAR alone may provide enough information on tree species to be useful to land managers in limited applications, even under structurally challenging conditions. With slight changes to the modeling approach, even higher accuracies may be possible.
Oilseed Rape (Brassica napus L.) Phenology Estimation by Averaged Stokes-Related Parameters
Authors: Zhang Wangfei , Zhang Yongxin , Yang Yue , Chen Erxue
Published: July 2021

Accurate and timely knowledge of crop phenology assists in planning and/or triggering appropriate farming activities. The multiple Polarimetric Synthetic Aperture Radar (PolSAR) technique shows great potential in crop phenology retrieval for its characterizations, such as short revisit time, all-weather monitoring and sensitivity to vegetation structure. This study aims to explore the potential of averaged Stokes-related parameters derived from multiple PolSAR data in oilseed rape phenology identification. In this study, the averaged Stokes-related parameters were first computed by two different wave polarimetric states. Then, the two groups of averaged Stokes-related parameters were generated and applied for analyzing averaged Stokes-related parameter sensitivity to oilseed rape phenology changes. At last, decision tree (DT) algorithms trained using 60% of the data were used for oilseed rape phenological stage classification. Four Stokes parameters (g0, g1, g2 and g3) and eight sub parameters (degree of polarization m, entropy H, ellipticity angle χ, orientation angle φ, degree of linear polarization Dolp, degree of circular polarization Docp, linear polarization ratio Lpr and circular polarization ratio Cpr) were extracted from a multi-temporal RADARSAT-2 dataset acquired during the whole oilseed rape growth cycle in 2013. Their sensitivities to oilseed rape phenology were analyzed versus five main rape phenology stages. In two groups (two different wave polarimetric states) of this study, g0, g1, g2, g3, m, H, Dolp and Lpr showed high sensitivity to oilseed rape growth stages while χ, φ, Docp and Cpr showed good performance for phenology classification in previous studies, which were quite noisy during the whole oilseed rape growth circle and showed unobvious sensitivity to the crop’s phenology change. The DT algorithms performed well in oilseed rape phenological stage identification. The results were verified at the parcel level with left 40% of the point dataset. Five phenology intervals of oilseed rape were identified with no more than three parameters by simple but robust decision tree algorithm groups. The identified phenology stages agree well with the ground measurements; the overall identification accuracies were 71.18% and 79.71%, respectively. For each growth stage, the best performance occurred at stage S1 with the accuracy of 95.65% for Group 1 and 94.23% for Group 2, and the worst performance occurred at stage S3 and S5 with the values around 60%. Most of the classification errors may resulted from the indistinguishability of S3 and S5 using Stokes-related parameters.
Exposure of Loggerhead Sea Turtle Nests to Waves in the Florida Panhandle
Authors: Ware Matthew , Ceriani Simona , Long Joseph , Fuentes Mariana
Published: July 2021

Wave wash-over poses a significant threat to sea turtle nests, with sustained exposure to waves potentially resulting in embryonic mortality and altered hatchling locomotor function, size, and sex ratios. Identifying where and under what conditions wave exposure becomes a problem, and deciding what action(s) to take (if any), is a common issue for sea turtle managers. To determine the exposure of sea turtle nests to waves and identify potential impacts to hatchling productivity, we integrated a geographic information system with remote sensing and wave runup modeling across 40 nesting beaches used by the Northern Gulf of Mexico Loggerhead Recovery Unit. Our models indicate that, on average, approximately 50% of the available beach area and 34% of nesting locations per nesting beach face a significant risk of wave exposure, particularly during tropical storms. Field data from beaches in the Florida Panhandle show that 42.3% of all nest locations reported wave exposure, which resulted in a 45% and 46% decline in hatching and emergence success, respectively, relative to their undisturbed counterparts. Historical nesting frequency at each beach and modeled exposure to waves were considered to identify priority locations with high nesting density which either experience low risk of wave exposure, as these are good candidates for protection as refugia for sustained hatchling production, or which have high wave exposure where efforts to reduce impacts are most warranted. Nine beaches in the eastern Florida Panhandle were identified as priority sites for future efforts such as habitat protection or research and development of management strategies. This modeling exercise offers a flexible approach for a threat assessment integration into research and management questions relevant to sea turtle conservation, as well as for other beach species and human uses of the coastal environment.
A Multi-Task Network with Distance–Mask–Boundary Consistency Constraints for Building Extraction from Aerial Images
Authors: Shi Furong , Zhang Tong
Published: July 2021

Deep-learning technologies, especially convolutional neural networks (CNNs), have achieved great success in building extraction from areal images. However, shape details are often lost during the down-sampling process, which results in discontinuous segmentation or inaccurate segmentation boundary. In order to compensate for the loss of shape information, two shape-related auxiliary tasks (i.e., boundary prediction and distance estimation) were jointly learned with building segmentation task in our proposed network. Meanwhile, two consistency constraint losses were designed based on the multi-task network to exploit the duality between the mask prediction and two shape-related information predictions. Specifically, an atrous spatial pyramid pooling (ASPP) module was appended to the top of the encoder of a U-shaped network to obtain multi-scale features. Based on the multi-scale features, one regression loss and two classification losses were used for predicting the distance-transform map, segmentation, and boundary. Two inter-task consistency-loss functions were constructed to ensure the consistency between distance maps and masks, and the consistency between masks and boundary maps. Experimental results on three public aerial image data sets showed that our method achieved superior performance over the recent state-of-the-art models.
Research on Self-Balancing System of Autonomous Vehicles Based on Queuing Theory
Authors: Li Huanping , Wang Jian , Bai Guopeng , Hu Xiaowei
Published: July 2021

In order to explore the changes that autonomous vehicles on the road would bring to the current traffic and make full use of the intelligent features of autonomous vehicles, the article defines a self-balancing system of autonomous vehicles. Based on queuing theory and stochastic process, the self-balancing system model with self-balancing characteristics is established to balance the utilization rate of autonomous vehicles under the conditions of ensuring demand and avoiding an uneven distribution of vehicle resources in the road network. The performance indicators of the system are calculated by the MVA (Mean Value Analysis) method. The analysis results show that the self-balancing process could reduce the average waiting time of customers significantly in the system, alleviate the service pressure while ensuring travel demand, fundamentally solve the phenomenon of concentrated idleness after the use of vehicles in the current traffic, maximize the use of the mobile vehicles in the system, and realize the self-balancing of the traffic network while reducing environmental pollution and saving energy.
Molecularly Imprinted Polymers for Dispersive (Micro)Solid Phase Extraction: A Review
Authors: Jayasinghe G. D. Thilini Madurangika , Moreda-Piñeiro Antonio
Published: July 2021

The review describes the development of batch solid phase extraction procedures based on dispersive (micro)solid phase extraction with molecularly imprinted polymers (MIPs) and magnetic MIPs (MMIPs). Advantages and disadvantages of the various MIPs for dispersive solid phase extraction and dispersive (micro)solid phase extraction are discussed. In addition, an effort has also been made to condense the information regarding MMIPs since there are a great variety of supports (magnetite and magnetite composites with carbon nanotubes, graphene oxide, or organic metal framework) and magnetite surface functionalization mechanisms for enhancing MIP synthesis, including reversible addition-fragmentation chain-transfer (RAFT) polymerization. Finally, drawbacks and future prospects for improving molecularly imprinted (micro)solid phase extraction (MIMSPE) are also appraised.
Bounded Rationality, Social Capital and Technology Adoption in Family Farming: Evidence from Cocoa-Tree Crops in Ivory Coast
Authors: Cordaro Francesco , Desdoigts Alain
Published: July 2021

In this paper, we allege that the hypothesis in favor of bounded rationality is a plausible explanation when it comes to better understanding the sluggish pace of adoption of best available tree crop farming techniques in poor small-scale rural communities. Our research builds on data collection and analysis of cocoa farming in Ivory Coast. Firstly, we find that the cognitive scarcity under which smallholder farmers make their decisions, in particular, satisficing behavior and fast and frugal heuristics, outweigh the scarcity of financial and human resources. Secondly, we show that the structure of the environment measured through various dimensions of social capital influences human rationality and decision-making. On the one hand, the greater smallholder farmers’ civic capital (solidarity, reciprocity, trustworthiness, cooperation), the more likely they are to modify their farming practices (p < 0.05) and, more specifically, to exchange information, learn, and eventually revise these practices. On the other hand, the greater the number of organizations the farmers participate in, the greater the probability of modifying their practices (p < 0.01). Information about farming techniques disseminates through weak bridging ties built within agricultural organizations (e.g., cooperatives, extension services) rather than through strong bonding ties between family or diaspora members.
Discrete Element Simulation Analysis of Biaxial Mechanical Properties of Concrete with Large-Size Recycled Aggregate
Authors: Li Tan , Xiao Jianzhuang
Published: July 2021

Concrete made with large-size recycled aggregates is a new kind of recycled concrete, where the size of the recycled aggregate used is 25–80 mm, which is generally three times that of conventional aggregate. Thus, its composition and mechanical properties are different from that of conventional recycled concrete and can be applied in large-volume structures. In this study, recycled aggregate generated in two stages with randomly distributed gravels and mortar was used to replace the conventional recycled aggregate model, to observe the internal stress state and cracking of the large-size recycled aggregate. This paper also investigated the mechanical properties, such as the compressive strength, crack morphology, and stress–strain curve, of concrete with large-size recycled aggregates under different confining pressures and recycled aggregate incorporation ratios. Through this research, it was found that when compared with conventional concrete, under the confining pressure, the strength of large-size recycled aggregate concrete did not decrease significantly at the same stress state, moreover, the stiffness was increased. Confining pressure has a significant influence on the strength of large-size recycled aggregate cocrete.
Effect of Activating Solution Modulus on the Synthesis of Sustainable Geopolymer Binders Using Spent Oil Bleaching Earths as Precursor
Authors: Delgado-Plana P. , Rodríguez-Expósito A. , Bueno-Rodríguez S. , Pérez-Villarejo L. , Tobaldi D. M. , Labrincha J. A. , Eliche-Quesada D.
Published: July 2021

The valorization of spent oil bleaching earths (SOBE) is crucial for the protection of the environment and the reuse of resources. In this research, alkali-activated binders were manufactured at room temperature using SOBE as a precursor by varying the mass ratio between the activating solutions of sodium silicate (Na2SiO3) and 6 M sodium hydroxide (NaOH) (activating solution modulus) (Na2SiO3/NaOH ratio = 1/1; 1/2; 1/3; 1/4) to investigate the influence on the technological properties of the materials. This process intends to evaluate the potential of SOBE, heat-treated at 550 °C (1 h), as a precursor of the reaction (source of aluminosilicates). Samples produced with higher amounts of sodium silicate developed a denser structure, with lower porosity and a higher amount of geopolymer gel. Maximum flexural (8.35 MPa) and compressive (28.4 MPa) strengths of samples cured at room temperature for 28 days were obtained with a Na2SiO3/NaOH mass ratio of 1/1. The study demonstrates that SOBE waste can be used as a precursor in the manufacture of geopolymer binders that show a good compromise between physical, mechanical and thermally insulating characteristics.
Multilevel Antecedents of Organizational Speed: The Exemplary Case of a Small Italian R&D Organization
Authors: Agostini Lara , Nosella Anna
Published: July 2021

The COVID-19 outbreak has compelled many organizations to adapt to a rapidly changing environment. In this context, the aim of this article is to unveil how a small R&D organization has been able to rapidly take advantage of the opportunities offered by the COVID-19 outbreak and to understand the factors that have enabled organizational speed. Results of the qualitative analysis of this exemplary single case show that a combination of factors at the individual level (i.e., characteristics of the CEO and collaborators), organizational level (i.e., structure, resources, operative systems and processes, culture), and partner level (i.e., characteristics of the partner portfolio) is required to go through a very fast recognition–decision–execution process.
Myths and Issues about Sustainable Living
Authors: Butters Chris
Published: July 2021

There are many common misconceptions about sustainable living. These hinder both an understanding of the benefits, and broader acceptance of sustainable solutions. Professionals within sustainability know of many good project examples, but these are still little known amongst the broader public; and in many countries hardly at all. Four such misconceptions or “myths” are briefly described, and then countered by a selection of examples. Most of these have been extensively studied and are arguably largely success stories, covering many aspects of ecological, economic and social sustainability. Four points are then noted which whilst not new, demand increased attention: an integrated view of city and countryside; the still underrated role of dynamics and process; social science insights into consumption and sociotechnical change; and emerging questions about sustainability in dense settlements, i.e., urbanity in general. This paper thus argues for a synthesis perspective; some quite new research perspectives are emerging. The paper is based on the literature as well as over 25 years of professional experience, visits, workshops and in-depth exchanges with most of the projects presented. Whilst remaining attentive to obstacles, weaknesses and challenges, a key task is to achieve wider dissemination of “the good news” about sustainable settlements and living.
Development of the Animal Conservation Digital Learning Aids and Assessments through the Industry-University Collaborative Course
Authors: Chen Yu-Horng
Published: July 2021

Due to the rapid changes caused by globalization and internationalization, this study focused on achieving Sustainable Development Goals (SDGs) 4 and 15 via specific digital learning materials—animal conservation apps—particularly designed for enlarging primary school pupils’ knowledge of biodiversity and conservation of natural habitats, and promoting sustainable development and lifelong learning abilities. Through a collaboration with Taipei Zoo, this study recruited 37 undergraduates who took the Learning Design and Practice course to develop the digital learning-assisted materials, namely animal conservation apps and assessment tools that suited the digital learning materials. In the initiative stage of the course, the undergraduates were required to work as a team and to learn in a group by observing and experiencing the model apps provided in the class. The provided apps were developed in compliance with the ADDIE model. In the middle stage of the course, each team was asked to develop their team app and assessment tools following the ADDIE model. In the final stage, each team’s design results were evaluated based on the digital learning material scale and core competency test evaluation: art domain. The results show that the undergraduates were able to integrate the expertise they gained in the course to developing high-quality digital learning materials. According to the educational professionals’ evaluation, the assessment tools designed by the undergraduates scored high marks.
Crowdsourcing Research for Social Insights into Smart Cities Applications and Services
Authors: Alhalabi Wadee , Lytras Miltiadis , Aljohani Nada
Published: July 2021

The evolution in knowledge management and crowdsourcing research provides new data-processing capabilities. The availability of both structured and unstructured open data formats offers unforeseen opportunities for analytics processing and advanced decision-making. However, social sciences research is facing advanced, complicated social challenges and problems. The focus of this study is to analyze the contribution of crowdsourcing techniques to the promotion of advanced social sciences research, exploiting open data available from the geographical positioning system (GPS) to analyze human behavior. In our study, we present the conceptual design of a device that, with the help of a global positioning system-data collection device (GPS-DCD), associates behavioral aspects of human life with place. The main contribution of this study is to integrate research in computer science and information systems with that in social science. The prototype system summarized in this work, proves the capacity of crowdsourcing and big data research to facilitate aggregation of microcontent related to human behavior toward improved quality of life and well-being in modern smart cities. Various ethical issues are also discussed to promote the scientific debate on this matter. Our study shows the capacity of emerging technologies to deal with social challenges. This kind of research will gain increased momentum in the future due to the availability of big data and new business models for social platforms.
Analyzing the Basic Properties and Environmental Footprint Reduction Effects of Highly Sulfated Calcium Silicate Cement
Authors: Kim Hyeon-Soo , Kim Ik , Yang Wan-hee , Moon Soo-Young , Lee Ji-Young
Published: July 2021

In South Korea, efforts to reduce carbon dioxide emissions and environmental impacts from the perspective of life cycle assessment (LCA) are important because of the implementation of zero-energy building certification for public buildings and the promotion of net-zero policy. Therefore, it is critical to develop cement alternatives with low embodied energy and less environmental impact. In this study, the applicability of “highly sulfated calcium silicate cement (HSCSC),” an eco-friendly binder developed by our research team, was investigated. Its basic properties and environmental footprint reduction effects were examined in comparison with ordinary Portland cement (OPC) and Portland blast furnace slag cement (PBSC). The environmental impacts of the HSCSC were analyzed using the LCA method. The results confirmed that HSCSC can be considered an excellent alternative to conventional OPC or PBSC in certain areas as an eco-friendly binder that can reduce carbon dioxide emissions and environmental impacts. Moreover, compared to OPC and PBSC, the probability of HSCSC affecting the human body is extremely low. The results of this study may contribute to the development and practical use of cements that minimize climate impacts, as well as improve the efficacy of future research on embodied energy saving.
Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels
Authors: Bardarov Nikolai , Todorov Vladislav , Christoff Nicole
Published: July 2021

The need to identify wood by its anatomical features requires a detailed analysis of all the elements that make it up. This is a significant problem of structural wood science, the most general and complete solution of which is yet to be sought. In recent years, increasing attention has been paid to the use of computer vision methods to automate processes such as the detection, identification, and classification of different tissues and different tree species. The more successful use of these methods in wood anatomy requires a more precise and comprehensive definition of the anatomical elements, according to their geometric and topological characteristics. In this article, we conduct a detailed analysis of the limits of variation of the location and grouping of vessels in the observed microscopic samples. The present development offers criteria and quantitative indicators for defining the terms shape, location, and group of wood tissues. It is proposed to differentiate the quantitative indicators of the vessels depending on their geometric and topological characteristics. Thus, with the help of computer vision technics, it will be possible to establish topological characteristics of wood vessels, the extraction of which would be used to develop an algorithm for the automatic classification of tree species.