bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Ocean Sub-Surface Processes in Tropical Cyclone Phailin Using a Coupled Modeling Framework: Sensitivity to Ocean Conditions
Authors: Chakraborty Tapajyoti , Pattnaik Sandeep , Baisya Himadri , Vishwakarma Vijay
Published: August 2022

The present study is aimed to investigate sub-surface ocean processes and their contribution to the intensification of a tropical cyclone (TC) from a coupled-modeling perspective. The Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model was employed to simulate TC Phailin, which originated over the Bay of Bengal and made landfall on the eastern coast of India in October 2013. Three sub-surface ocean condition datasets—viz., (a) the European Centre for Medium-Range Weather Forecast (ECMWF) Ocean Reanalysis, (b) the Climate Forecast System Version 2 (CFSV2) Operational Analysis, and (c) the Hybrid Coordinate Ocean Model (HYCOM) Reanalysis datasets—were used for the initial and boundary conditions for the oceanic component of the coupled model in three different simulations of TC Phailin. All the simulations showed a delay in intensification compared to the observation, and ECMWF simulated the most intensified TC. CFSV2 simulated a deeper mixed layer (ML) and higher mixing, which hindered the intensification. Furthermore, higher entrainment of cold water in the ML led to cold water reaching the surface and, consequently, decreased sea surface temperature, which acted as negative feedback in the intensification of the storm in the cases of CFSV2 and HYCOM. ECMWF realistically simulated the interactions of the TC with a cold-core eddy before landfall. A sudden increase in ML heat content, the addition of heat in the ML due to entrainment, and the prevention of cold water reaching the surface were indicative of the breaking of the barrier layer (BL) in ECMWF, which was further corroborated by the spatial distribution of BL thickness in the simulation. This acted as positive feedback in the intensification of the TC. The findings of this study strongly suggest that not only the incorporation of physical oceanic sub-surface processes in the modeling of TCs but also the proper representation of prevailing mesoscale features and ocean sub-surface temperature, salinity, and current profiles in datasets is essential for realistic simulations of TCs.
Retrospective Survival Analysis of Cats with Feline Infectious Peritonitis Treated with Polyprenyl Immunostimulant That Survived over 365 Days
Authors: Černá Petra , Ayoob Ashley , Baylor Caroline , Champagne Erin , Hazanow Sandra , Heidel Robert E. , Wirth Kimberly , Legendre Alfred M. , Gunn-Moore Danièlle A.
Published: August 2022

Feline infectious peritonitis (FIP) remains a major diagnostic and treatment challenge in feline medicine. An ineffective immune response is an important component of FIP pathophysiology; hence treatment with an immune stimulant such as Polyprenyl Immunostimulant™ (PI), which enhances cell-mediated immunity by upregulating the innate immune response via Toll-like receptors, is a rational approach. Records of cats with FIP treated with PI orally for over 365 days were retrospectively studied. Of these cats (n = 174), records were obtained for n = 103 cats with appropriate clinical signs and clinical pathology. Of these, n = 29 had FIP confirmed by immunohistochemistry (IHC) or reverse transcription polymerase-chain-reaction (RT-PCR). Most of the cats (25/29; 86%) had non-effusive FIP, and only 4/29 cats (14%) had effusive FIP. The mean survival time (MST) was 2927 days (eight years); with 55% of the cats (16/29) still being alive at the time data collection, and 45% (13/29) having died. A persistently low hematocrit plus low albumin:globulin (A:G) ratio, despite treatment, was a negative prognostic indicator. It took a mean of ~182 days and ~375 days, respectively, for anemia and low A:G ratio to resolve in the cats that presented with these laboratory changes. This study shows that PI is beneficial in the treatment of FIP, and more studies are needed to establish the best protocols of use.
Cancer Immunotherapy and Delivery System: An Update
Authors: Yang Ming , Olaoba Olamide Tosin , Zhang Chunye , Kimchi Eric T. , Staveley-O’Carroll Kevin F. , Li Guangfu
Published: August 2022

With an understanding of immunity in the tumor microenvironment, immunotherapy turns out to be a powerful tool in the clinic to treat many cancers. The strategies applied in cancer immunotherapy mainly include blockade of immune checkpoints, adoptive transfer of engineered cells, such as T cells, natural killer cells, and macrophages, cytokine therapy, cancer vaccines, and oncolytic virotherapy. Many factors, such as product price, off-target side effects, immunosuppressive tumor microenvironment, and cancer cell heterogeneity, affect the treatment efficacy of immunotherapies against cancers. In addition, some treatments, such as chimeric antigen receptor (CAR) T cell therapy, are more effective in treating patients with lymphoma, leukemia, and multiple myeloma rather than solid tumors. To improve the efficacy of targeted immunotherapy and reduce off-target effects, delivery systems for immunotherapies have been developed in past decades using tools such as nanoparticles, hydrogel matrix, and implantable scaffolds. This review first summarizes the currently common immunotherapies and their limitations. It then synopsizes the relative delivery systems that can be applied to improve treatment efficacy and minimize side effects. The challenges, frontiers, and prospects for applying these delivery systems in cancer immunotherapy are also discussed. Finally, the application of these approaches in clinical trials is reviewed.
The Lattice Geometry of Walsh-Function-Based Adaptive Optics
Authors: Hu Qi , Xiao Yuyao , Cui Jiahe , Turcotte Raphaël , Booth Martin J.
Published: August 2022

We show that there is an intrinsic link between the use of Walsh aberration modes in adaptive optics (AO) and the mathematics of lattices. The discrete and binary nature of these modes means that there are infinite combinations of Walsh mode coefficients that can optimally correct the same aberration. Finding such a correction is hence a poorly conditioned optimisation problem that can be difficult to solve. This can be mitigated by confining the AO correction space defined in Walsh mode coefficients to the fundamental Voronoi cell of a lattice. By restricting the correction space in this way, one can ensure there is only one set of Walsh coefficients that corresponds to the optimum correction aberration. This property is used to enable the design of efficient estimation algorithms to solve the inverse problem of finding correction aberrations from a sequence of measurements in a wavefront sensorless AO system. The benefit of this approach is illustrated using a neural-network-based estimator.
Isotope and Spin Effects Induced by Compression of Paramagnetic Molecules
Authors: Barashkova Irene , Breslavskaya Natalia , Wasserman Luybov , Buchachenko Anatoly
Published: August 2022

The zero-point energies (ZPEs) of paramagnetic molecules, free and compressed in a C59N paramagnetic cage, were computed. The excess of energy acquired by molecules under compression depended on the deuterium and tritium isotopes which ranged from 6–8 kcal/mol for H2+ to 1.0–1.5 kcal/mol for HO• and HO2. The differences in the ZPEs of compressed isotopic molecules resulted in large deuterium and tritium isotope effects which differed for singlet and triplet spin states. The hyperfine coupling (HFC) constants for protons and 17O nuclei decreased under compression, confirming the leakage of the unpaired π-electron from the central oxygen atom of guest molecules into the system of π-electrons of the cage, and its distribution over 60 atoms of the C59N. The latter seems to be the reason why the nitrogen-14 HFCs for C59N remain almost unchanged upon encapsulation of guest molecules. The singlet-triplet splitting is shown to depend on the Coulomb interaction, which controls the sign of the exchange potential. The importance of compression effects on the functioning of enzymes as molecular compressing devices is discussed.
Development of an Effective Sonotrode Based Extraction Technique for the Recovery of Phenolic Compounds with Antioxidant Activities in Cherimoya Leaves
Authors: Martín-García Beatriz , Aznar-Ramos María José , Verardo Vito , Gómez-Caravaca Ana María
Published: August 2022

The leaves of Annona cherimola Mill (cherimoya) are a potential source of phenolic compounds that have been shown to have beneficial properties. Therefore, this study focuses on establishing an ultrasonic-assisted extraction of phenolic compounds in cherimoya leaves using a sonotrode. For that purpose, a Box-Behnken design based on a response surface methodology (RSM) was used to optimize factors, such as amplitude, extraction time and solvent composition to obtain the maximum content of phenolic compounds by HPLC-MS and the maximum in-vitro antioxidant activity by DPPH, ABTS and FRAP assays in ‘Fino de Jete’ cherimoya leaves. The optimal conditions were 70% amplitude, 10 min and 40:60 ethanol/water (EtOH/H2O) (v/v). The results obtained under these optimum conditions by using a sonotrode were compared with those from an ultrasonic bath; briefly, recovery of phenolic compounds by sonotrode was 2.3 times higher than a bath. Therefore, these optimal conditions were applied to different varieties ‘Campas’, ‘Fino de Jete’ and ‘Negrito Joven’ harvested in the Tropical Coast of Granada (Spain). A total of 39 phenolic compounds were determined in these cherimoya leaf extracts, 24 phenolic compounds by HPLC-MS and 15 proanthocianidins by HPLC-FLD. 5-p-coumaroylquinic acid, lathyroside-7-O-α-l-rhamnopyranoside and quercetin hexose acetate were first identified in cherimoya leaves. The most concentrated phenolic compounds were the flavonoids, such as rutin and quercetin hexoside and proanthocyanidins including monomers. Almost no significant differences in the phenolic content in these cultivars were found (11–13 mg/g d.w. for phenolic compounds and 11–20 mg/g d.w. for proanthocyanidins). In addition, sonotrode ultrasonic-assisted extraction has been shown to be an efficient extraction technique in the phenolic recovery from cherimoya leaves that could be implemented on an industrial scale.
Evaluation of Growth Characteristics and Biological Activities of ‘Dachul’, a Hybrid Medicinal Plant of Atractylodes macrocephala × Atractylodes japonica, under Different Artificial Light Sources
Authors: Hwang Myeong Ha , Seo Ji Won , Park Byung Jun , Han Kyeong Jae , Lee Jae Geun , Kim Na Young , Kim Myong Jo , Seong Eun Soo
Published: August 2022

This study was conducted to evaluate the effects of different artificial light sources on the growth characteristics and various biological activities of the Atractylodes macrocephala x Atractylodes japonica hybrid cv. ‘Dachul’, which is highly useful for medicinal purposes. The plant had the largest biomass with a plant height of 38.20 ± 1.95 cm when treated with microwave electrodeless light (MEL). The chlorophyll content of the plants treated with fluorescent light (FL) was 53.93 ± 1.05 SPAD and was the highest. The antioxidant effect, determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH), was the highest with 92.7 ± 0.2% in plants treated with light-emitting diode (LED)-green light. Total phenol and flavonoid contents were significantly higher with 19.7 ± 0.5 mg GAE/g and 40.2 ± 2.2 mg QE/g in the sample treated with LED-green light, respectively. For antimicrobial activity using the minimum inhibitory concentration (MIC) technique, the inhibitory ability against Escherichia coli was at 0.25 mg/mL under LED-green light treatment. The whitening activity using tyrosinase enzyme showed the highest tyrosinase inhibitory ability at 62.1 ± 1.2% of the above extract treated with MEL light. To confirm the immune activity in lipopolysaccharide (LPS)-induced RAW 264.7 cells, NO production of inflammation-related substances was measured. In addition, the inflammation-related genes iNOS (inducible nitric oxide synthase), COX-2 (cyclooxygenase-2), and TNF-α (tumor necrosis factor-α) in the same sample were confirmed using reverse transcriptase (RT)-PCR, and the result showed that gene expression was suppressed compared with that in the control group. It is expected that Dachul plants treated with LED-blue light will play an important role in enhancing intracellular anti-inflammatory activity. From these results, the effect for various biological activities appeared in a significantly diverse spectrum in response to different wavelengths of artificial light sources in Dachul.
Hepatoprotective Effect of Opuntia robusta Fruit Biocomponents in a Rat Model of Thioacetamide-Induced Liver Fibrosis
Authors: Pulido-Hornedo Nayeli Amalinalli , Ventura-Juárez Javier , Guevara-Lara Fidel , González-Ponce Herson Antonio , Sánchez-Alemán Esperanza , Buist-Homan Manon , Moshage Han , Martínez-Saldaña Ma. Consolación
Published: August 2022

Liver fibrosis is a chronic disease associated with oxidative stress that has a great impact on the population mortality. Due to their antioxidant capacity, we evaluated the protective effect of Opuntia robusta fruit (Or) on liver fibrosis. A nutraceutical characterization of Or was performed and a model of fibrosis was induced with thioacetamide (TAA) in Wistar rats. Aminotransferases, reduced glutathione (GSH) and histopathology were evaluated. Or contained 436.5 ± 57 mg of Betacyanins equivalents/L., 793 mg of catechin equivalents (CAE)/100 g for flavonoids, 1118 mg of gallic acid equivalents (GAE)/100 g for total phenols, 141.14 mg/100 g for vitamin C and 429.9 μg/100 g for vitamin E. The antioxidant capacity of Or was: 2.27 mmol of Trolox® equivalents (TE)/L (DPPH), 62.2 ± 5.0 μmol TE/g (ABTS•+), 80.2 ± 11.7 μmol TE/g (FRAP), 247.9 ± 15.6 µmol TE/g (AAPH) and 15.0% of H2O2 elimination. An increase (p < 0.05) of aminotransferases and a decrease (p < 0.05) of hepatic GSH was observed in the TAA group compared to the control and the concomitant groups. Histopathology showed changes in the normal architecture of the liver treated with TAA compared to the concomitant treatments. Or contains bioactive components with antioxidant capacity, which can reduce fibrotic liver damage.
Formulation of Fast Dissolving β-Glucan/Bilberry Juice Films for Packaging Dry Powdered Pharmaceuticals for Diabetes
Authors: Avramia Ionut , Amariei Sonia
Published: August 2022

The aim of this study was to develop fast dissolving films based on β-glucan and bilberry juice due to the bioactive potential of β-glucan and antidiabetic effect of bilberry juice. The benefit of incorporation of bioactive compounds into the films is due to the removal of unnecessary excipients and to confer protection as well as increase stability and shelf life to the packaged product. Due to the fast dissolving requirements of the European Pharmacopeia, which reduced the dissolution time from 180 to 60 s, indicating less than a minute, hygroscopic materials, such as sodium alginate and a suitable plasticizer, such as glycerin were incorporated. Moreover, the influence of ingredients and surfactants, such as soybean oil was studied in the design of fast dissolving films. Additionally, the steady state rate water vapor transmission rate (WVTR), water vapor permeability (WVP), and FT-IR spectroscopy tests were performed at high resolution to ensure the reliability of the films and composition as well as to validate the results. Our data suggest that the addition of surfactants contributed to the development of fast dissolving films without influencing the diffusion of water vapor. Low levels of WVTR and short dissolution time made from β-glucan and bilberry juice are a convenient candidate for packaging dry powdered pharmaceuticals for diabetes.
Ethnobotanical Review and Dataset Compiling on Wild and Cultivated Plants Traditionally Used as Medicinal Remedies in Italy
Authors: Monari Stefania , Ferri Maura , Salinitro Mirko , Tassoni Annalisa
Published: August 2022

Over the centuries, wild plants have constituted the main food ingredients and traditional medicine in rural communities. In the last decades, thousands of ethnobotanical studies have been conducted, with the aim of documenting the traditional knowledge on wild and cultivated plants both for food and therapeutic purposes. In the present work, 75 published papers related to Italian ethnobotanical knowledge on wild and cultivated plants traditionally used for medical purposes were analyzed and data on 1117 different species organized in the first dataset to target medicinal applications only. For each plant species, the Italian region of use, plant organs, mode of preparation, specific pathological group of application, citation index, and use index were listed. The different therapeutic applications were subdivided into nine main pathological groups according to the targeted human apparatus. Overall, the cited species with highest number of uses were related to the treatment of the digestive system and skin-ears-eyes-hair diseases, followed by diseases of the genito-urinary and respiratory systems. The 13 most relevant species were identified on the basis of their citation and use indexes. The present review on Italian medicinal flora aims to provide valuable information on wild and cultivated species, which are potential sources of plant-based therapeutic remedies, to preserve and reevaluate endangered traditional folk knowledge.
Development of a Decision Support System for the Management of Mummy Berry Disease in Northwestern Washington
Authors: Cucak Mladen , Harteveld Dalphy O. C. , Wasko DeVetter Lisa , Peever Tobin L. , Moral Rafael de Andrade , Mattupalli Chakradhar
Published: August 2022

Mummy berry, caused by Monilinia vaccinii-corymbosi, is the most important disease of the northern highbush blueberry (Vaccinium corymbosum L.) in North America and can cause up to 70% yield losses in affected fields. A key event in the mummy berry disease cycle is the primary infection phase where ascospores are released by apothecia that infect emerging floral and vegetative tissues. Current management of mummy berry disease in northwestern Washington is predominantly reliant on the prevention of primary infections through prophylactic, calendar-based fungicide spray applications early in the growing season. To improve the understanding of risk during these periods and to help tailor management strategies, we developed a decision support system (DSS) based on field records spanning over five seasons and four locations in northwestern Washington. Environmental conditions across the region were highly uniform but different dynamics of apothecial development were observed under high- and low-management regimes. Based on our analysis, we suggest basing the initial iteration of the DSS on two sub-models. The first sub-model predicts the onset of apothecia based on chill-unit accumulation under high- and low-management regimes, and the second predicts primary infection risk, which provides opportunities to improve the timing of fungicide applications. The synoptic DSS proposed here is based on the current biological knowledge of the pathosystem and available data for the northwestern Washington region. We provide the analysis and the DSS implementation and evaluation as an open-source repository, providing opportunities for further improvements. Finally, we provide suggestions for future research and the operational efforts needed for improving the utility and accuracy of the mummy berry DSS.
Using Trait-Based Methods to Study the Response of Grassland to Fertilization in the Grassland in Semiarid Areas in the Loess Plateau of China
Authors: Yang Yuting , Chen Zhifei , Xu Bingcheng , Wei Jiaqi , Zhu Xiaoxu , Yao Hongbin , Wen Zhongming
Published: August 2022

Grassland is the dominant vegetation type in the Loess Plateau, and grassland productivity and processes are limited by nitrogen (N) and phosphorus (P). Studies have shown that productivity would change following fertilization in the grassland. The response of productivity to fertilization mainly depends on the dominant species traits. Trait-based methods provide a useful tool for explaining the variations in grassland productivity following fertilization. However, the relative contribution of plant functional traits to grassland productivity under N and P addition in the Loess Plateau is not clear. We measured aboveground biomass (AGB) and leaf N content (LN), leaf P content (LP), leaf N/P ratio (LN/P), specific leaf area (SLA), leaf tissue density (LTD), leaf dry matter content (LDMC), and maximum plant height (Hmax) to study how these plant functional traits regulate the relative biomass of different species and grassland productivity following fertilization. Our results showed, that under different nutrient addition levels, the linkages between plant functional traits and the relative biomass of different species were different. Community AGB was positively related to community−weighted mean LN (CWM_LN), CWM_LN/P, CWM_SLA, and CWM_Hmax, but negatively related to CWM_LTD and CWM_LDMC. Dominant species traits largely determined grassland productivity, in line with the mass ratio hypothesis. These findings further highlight the close linkages between community-level functional traits and grassland productivity. Our study contributes to the mechanisms underlying biodiversity–ecosystem function relationships and has significance for guiding semiarid grassland management.
Mercury Phytotoxicity and Tolerance in Three Wild Plants during Germination and Seedling Development
Authors: Kalinhoff Carolina , Calderón Norma-Thalia
Published: August 2022

By examining plant responses to heavy metal stress during the early stages of the life cycle, we can predict their tolerance and survival in polluted areas as well as their potential for bioremediation. The objective of our study was to evaluate the effect of exposure to mercury (Hg) on the germination and in vitro development of three plant species: Bidens pilosa, Taraxacum officinale (Asteraceae), and Heliocarpus americanus (Malvaceae). These are wild ecotypes adapted to local edaphoclimatic conditions in southern Ecuador, an area which has been historically affected by artisanal and small-scale gold mining (SSGM). For comparison, we additionally used a known Hg-tolerant plant, Lactuca sativa (Asteraceae). We tested biorelevant concentrations of Hg, equivalent to those occurring in soils affected by SSGM, i.e., up to 4.0 mg/L of Hg. The relative inhibitory effects of the treatments (0.6, 2.0, and 4.0 mg/L of Hg) on the germination percentage were most evident in T. officinale, followed by B. pilosa, while L. sativa and H. americanus were not affected. In terms of the time needed to reach 50% germination (T50), B. pilosa exposed to higher concentrations of Hg showed an increase in T50, while H. americanus showed a significant reduction compared to the control treatment. The reduction in radicle length at 4.0 mg/L Hg compared to the control was more evident in L. sativa (86%) than in B. pilosa (55.3%) and H. americanus (31.5%). We concluded that, in a scenario of Hg contamination in the evaluated concentration range, the grass B. pilosa and the tree H. americanus could have a higher probability of establishment and survival.
Investigations on Temperatures of the Flat Insert Mold Cavity Using VCRHCS with CFD Simulation
Authors: Wang Rong-Tsu , Wang Jung-Chang , Chen Sih-Li
Published: August 2022

This paper adopted transient CFD (Computational Fluid Dynamics) simulation analysis with an experimental method for designing and surveying the quick and uniform rise in the temperature of the plastics into the insert mold cavity. Plastic injection molding utilizing VCRHCS (Vapor Chamber for Rapid Heating and Cooling System) favorably decreased the defects of crystalline plastic goods’ welding lines, enhancing the tensile intensity and lowering the weakness of welding lines of a plastic matter. The vapor chamber (VC) possessed a rapid uniform temperature identity, which was embedded between the heating unit and the mold cavity. The results show that the tensile strength of the plastic specimen increased above 8%, and the depths of the welding line (V-gap) decreased by 24 times (from 12 μm to 0.5 μm). The VCRHCS plastic injection molding procedure can constructively diminish the development time for novel related products, as described in this paper.
Electrocrystallization of Calcium Oxalate on Electrospun PCL Fibers Loaded with Phytic Acid as a Template
Authors: Arce Tatiana Zegers , Yazdani-Pedram Mehrdad , Neira-Carrillo Andrónico
Published: August 2022

Crystallization occurs widely in living organisms where different organs could associate with the calcification process, such as the formation of calcium oxalate (CaOx) calculi in the urinary tract. However, the pathogenesis and the role of an inhibitor in the pathological processes involved in urolithiasis is poorly understood. Therefore, the use of phytic acid (PA) as an inhibitor for the organic fibrillar matrix is a novel approach to inhibit the formation of pathological CaOx crystals. Herein, electrospun polymer fiber meshes of polycaprolactone (PCL) with random (R) and aligned (A) fiber orientations containing PA were prepared by electrospinning, and their role as a 3D organic template in in vitro CaOx crystallization was investigated. CaOx crystals were generated on conductive tin indium oxide (ITO)-modified glass with R-PCL and A-PCL fibers in the presence of PA through an electrocrystallization (EC) procedure. This study provides a simple electrochemical approach to evaluate the role of PA as an inhibitor in the nucleation of pathological CaOx crystals. The resulting CaOx crystals were analyzed by chrono-potentiometry, optical microscopy (OM), scanning electron microscopy (SEM), and X-ray diffraction (XRD). We found that PA and the fiber orientations are key factors in the nucleation and crystal growth of CaOx, achieving the stabilization of healthy CaOx crystal and the inhibition of the pathological crystal form.
Life Extension Technologies and Pregnancy: Practical and Theological Considerations
Authors: Renaud Myriam
Published: August 2022

As biotechnologies emerge that halt or slow aging, what significance will these have for pregnancy? I argue in favor of life extension technologies based on their benefit for cis-gendered women who wish to become pregnant. After age 27, fertility decreases, and risks associated with pregnancies increase. At the same time, women’s twenties and thirties are often key years in their working life. If aging is stopped or slowed, women can delay pregnancy past those years. Though Martin Luther may seem an unlikely resource for theological reflection on this issue, his biblical commentaries on pregnancy lend support for these technologies. Luther emphasized how the pregnant Mary, though of lowly status, was essential to the embodiment of God and a testament to the blessings God may visit upon anyone. Luther also emphasized how Eve and other pregnant women help advance God’s promise to sustain God’s creation of humankind. I acknowledge that lengthening the window of fertility could exacerbate overpopulation on the Earth but show that solutions typically advanced, such as John K. Davis’ “Forced Choice” proposal, almost always rely on controlling women’s bodily autonomy and must be rejected. I also show that fears of a Malthusian crisis are likely not only overblown but incorrect given predicted declines in fertility rates.
Plant Biomass Conversion to Vehicle Liquid Fuel as a Path to Sustainability
Authors: Ketov Aleksandr , Sliusar Natalia , Tsybina Anna , Ketov Iurii , Chudinov Sergei , Krasnovskikh Marina , Bosnic Vladimir
Published: August 2022

Biofuel such as linseed oil has an energy potential of 48.8 MJ/kg, which is much lower than fossil diesel fuel 57.14 MJ/kg. Existing biofuels need to increase the energy potential for use in traditional engines. Moreover, biofuel production demands cheap feedstock, for example, sawdust. The present paper shows that the technology to synthesize high-energy liquid vehicle fuels with a gross calorific value up to 53.6 MJ/kg from renewable sources of plant origin is possible. Slow pyrolysis was used to produce high-energy biofuel from sawdust and linseed oil. The proposed approach will allow not only to preserve the existing high-tech energy sources of high unit capacity based on the combustion of liquid fuels, but also to make the transition to reducing the carbon footprint and, in the future, to carbon neutrality by replacing fossil carbon of liquid hydrocarbon fuels with the carbon produced from biomass.
Attention-Based Multi-Level Feature Fusion for Object Detection in Remote Sensing Images
Authors: Dong Xiaohu , Qin Yao , Gao Yinghui , Fu Ruigang , Liu Songlin , Ye Yuanxin
Published: August 2022

We study the problem of object detection in remote sensing images. As a simple but effective feature extractor, Feature Pyramid Network (FPN) has been widely used in several generic vision tasks. However, it still faces some challenges when used for remote sensing object detection, as the objects in remote sensing images usually exhibit variable shapes, orientations, and sizes. To this end, we propose a dedicated object detector based on the FPN architecture to achieve accurate object detection in remote sensing images. Specifically, considering the variable shapes and orientations of remote sensing objects, we first replace the original lateral connections of FPN with Deformable Convolution Lateral Connection Modules (DCLCMs), each of which includes a 3×3 deformable convolution to generate feature maps with deformable receptive fields. Additionally, we further introduce several Attention-based Multi-Level Feature Fusion Modules (A-MLFFMs) to integrate the multi-level outputs of FPN adaptively, further enabling multi-scale object detection. Extensive experimental results on the DIOR dataset demonstrated the state-of-the-art performance achieved by the proposed method, with the highest mean Average Precision (mAP) of 73.6%.
Hierarchical Classification of Soybean in the Brazilian Savanna Based on Harmonized Landsat Sentinel Data
Authors: Parreiras Taya , Bolfe Édson , Chaves Michel , Sanches Ieda , Sano Edson , Victoria Daniel , Bettiol Giovana , Vicente Luiz
Published: August 2022

The Brazilian Savanna presents a complex agricultural dynamic and cloud cover issues; therefore, there is a need for new strategies for more detailed agricultural monitoring. Using a hierarchical classification system, we explored the Harmonized Landsat Sentinel-2 (HLS) dataset to detect soybean in western Bahia, Brazil. Multispectral bands (MS) and vegetation indices (VIs) from October 2021 to March 2022 were used as variables to feed Random Forest models, and the performances of the complete HLS time-series, HLSS30 (harmonized Sentinel), HLSL30 (harmonized Landsat), and Landsat 8 OLI (L8) were compared. At Level 1 (agricultural areas × native vegetation), HLS, HLSS30, and L8 produced identical models using MS + VIs, with 0.959 overall accuracies (OA) and Kappa of 0.917. At Level 2 (annual crops × perennial crops × pasturelands), HLS and L8 achieved an OA of 0.935 and Kappa > 0.89 using only VIs. At Level 3 (soybean × other annual crops), the HLS MS + VIs model achieved the best performance, with OA of 0.913 and Kappa of 0.808. Our results demonstrated the potential of the new HLS dataset for medium-resolution mapping initiatives at the crop level, which can impact decision-making processes involving large-scale soybean production and agricultural sustainability.
Complex-Valued Multi-Scale Fully Convolutional Network with Stacked-Dilated Convolution for PolSAR Image Classification
Authors: Xie Wen , Jiao Licheng , Hua Wenqiang
Published: August 2022

Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is designed for pixel-to-pixel tasks, has obtained enormous success in semantic segmentation. Therefore, effectively using the FCN model combined with polarimetric characteristics for PolSAR image classification is quite promising. This paper proposes a novel FCN model by adopting complex-valued domain stacked-dilated convolution (CV-SDFCN). Firstly, a stacked-dilated convolution layer with different dilation rates is constructed to capture multi-scale features of PolSAR image; meanwhile, the sharing weight is employed to reduce the calculation burden. Unfortunately, the labeled training samples of PolSAR image are usually limited. Then, the encoder–decoder structure of the original FCN is reconstructed with a U-net model. Finally, in view of the significance of the phase information for PolSAR images, the proposed model is trained in the complex-valued domain rather than the real-valued domain. The experiment results show that the classification performance of the proposed method is better than several state-of-the-art PolSAR image classification methods.
Comparative Evaluation of a Newly Developed Trunk-Based Tree Detection/Localization Strategy on Leaf-Off LiDAR Point Clouds with Varying Characteristics
Authors: Zhou Tian , dos Santos Renato César , Liu Jidong , Lin Yi-Chun , Fei William Changhao , Fei Songlin , Habib Ayman
Published: August 2022

LiDAR data acquired by various platforms provide unprecedented data for forest inventory and management. Among its applications, individual tree detection and segmentation are critical and prerequisite steps for deriving forest structural metrics, especially at the stand level. Although there are various tree detection and localization approaches, a comparative analysis of their performance on LiDAR data with different characteristics remains to be explored. In this study, a new trunk-based tree detection and localization approach (namely, height-difference-based) is proposed and compared to two state-of-the-art strategies—DBSCAN-based and height/density-based approaches. Leaf-off LiDAR data from two unmanned aerial vehicles (UAVs) and Geiger mode system with different point densities, geometric accuracies, and environmental complexities were used to evaluate the performance of these approaches in a forest plantation. The results from the UAV datasets suggest that DBSCAN-based and height/density-based approaches perform well in tree detection (F1 score > 0.99) and localization (with an accuracy of 0.1 m for point clouds with high geometric accuracy) after fine-tuning the model thresholds; however, the processing time of the latter is much shorter. Even though our new height-difference-based approach introduces more false positives, it obtains a high tree detection rate from UAV datasets without fine-tuning model thresholds. However, due to the limitations of the algorithm, the tree localization accuracy is worse than that of the other two approaches. On the other hand, the results from the Geiger mode dataset with low point density show that the performance of all approaches dramatically deteriorates. Among them, the proposed height-difference-based approach results in the greatest number of true positives and highest F1 score, making it the most suitable approach for low-density point clouds without the need for parameter/threshold fine-tuning.
Investigation on Vertical Position and Sound Velocity Variation for GNSS/Acoustic Seafloor Geodetic Calibration Based on Moving Survey Data
Authors: Shan Rui , Liu Huimin , Zhao Shuang , Li Haojun
Published: August 2022

The accuracy of GNSS/Acoustic seafloor geodetic calibration is greatly influenced by the temporal variation of sound velocity, especially in the vertical direction. Aiming at correcting of the unknown parameters related to both the positions and the sound velocity, this paper proposes a step-by-step inversion scheme based on moving survey data. The proposed method firstly estimates the horizontal normalized travel time delay with sound ray tracing strategy and then computes the horizontal position with circle line observations. We reconstructed an inversion scheme for extracting the surface sound velocity disturbance (SSVD) and corrected the vertical position from cross line data. The SSVD is decomposed into a sum of different period disturbances, and a new SSVD is reconstructed by combining the long period disturbance and short period disturbance. The proposed algorithm is verified by the South China Sea experiment for GNSS/Acoustic seafloor geodetic calibration. The results demonstrate that the new method can take the effects of sound velocity variation into consideration and improve the precision of the vertical position, which is superior to the least squares (LS), the single-difference LS for seafloor geodetic calibration.
Sar2color: Learning Imaging Characteristics of SAR Images for SAR-to-Optical Transformation
Authors: Guo Zhe , Guo Haojie , Liu Xuewen , Zhou Weijie , Wang Yi , Fan Yangyu
Published: August 2022

Optical images are rich in spectral information, but difficult to acquire under all-weather conditions, while SAR images can overcome adverse meteorological conditions, but geometric distortion and speckle noise will reduce the quality of SAR images and thus make image interpretation more challenging. Therefore, transforming SAR images to optical images to assist SAR image interpretation will bring opportunities for SAR image application. With the advancement of deep learning technology, the ability of SAR-to-optical transformation has been greatly improved. However, most of the current mainstream transformation methods do not consider the imaging characteristics of SAR images, and there will be failures such as noisy color spots and regional landform deformation in the generated optical images. Moreover, since the SAR image itself does not contain color information, there also exist many color errors in these results. Aiming at the above problems, Sar2color, an end-to-end general SAR-to-optical transformation model, is proposed based on a conditional generative adversarial network (CGAN). The model uses DCT residual block to reduce the effect of coherent speckle noise on the generated optical images, and constructs the Light atrous spatial pyramid pooling (Light-ASPP) module to mitigate the negative effect of geometric distortion on the generation of optical images. These two designs ensure the precision of texture details when the SAR image is transformed into an optical image, and use the correct color memory block (CCMB) to improve the color accuracy of transformation results. Towards the Sar2color model, we have carried out evaluations on the homologous heterogeneous SAR image and optical image pairing dataset SEN1-2. The experimental results show that, compared with other mainstream transformation models, Sar2color achieves the state-of-the-art effect on all three objective and one subjective evaluation metrics. Furthermore, we have carried out various ablation experiments, and the results show the effectiveness of each designed module of Sar2color.
Advances in the Quality of Global Soil Moisture Products: A Review
Authors: Liu Yangxiaoyue , Yang Yaping
Published: August 2022

Soil moisture is a crucial component of land–atmosphere interaction systems. It has a decisive effect on evapotranspiration and photosynthesis, which then notably impacts the land surface water cycle, energy transfer, and material exchange. Thus, soil moisture is usually treated as an indispensable parameter in studies that focus on drought monitoring, climate change, hydrology, and ecology. After consistent efforts for approximately half a century, great advances in soil moisture retrieval from in situ measurements, remote sensing, and reanalysis approaches have been achieved. The quality of soil moisture estimates, including spatial coverage, temporal span, spatial resolution, time resolution, time latency, and data precision, has been remarkably and steadily improved. This review outlines the recently developed techniques and algorithms used to estimate and improve the quality of soil moisture estimates. Moreover, the characteristics of each estimation approach and the main application fields of soil moisture are summarized. The future prospects of soil moisture estimation trends are highlighted to address research directions in the context of increasingly comprehensive application requirements.
Comparing Object-Based and Pixel-Based Methods for Local Climate Zones Mapping with Multi-Source Data
Authors: Yan Ziyun , Ma Lei , He Weiqiang , Zhou Liang , Lu Heng , Liu Gang , Huang Guoan
Published: August 2022

The local climate zones (LCZs) system, a standard framework characterizing urban form and environment, effectively promotes urban remote sensing research, especially urban heat island (UHI) research. However, whether mapping with objects is more advantageous than with pixels in LCZ mapping remains uncertain. This study aims to compare object-based and pixel-based LCZ mapping with multi-source data in detail. By comparing the object-based method with the pixel-based method in 50 and 100 m, respectively, we found that the object-based method performed better with overall accuracy (OA) higher at approximately 2% and 5%, respectively. In per-class analysis, the object-based method showed a clear advantage in the land cover types and competitive performance in built types while LCZ2, LCZ5, and LCZ6 performed better with the pixel-based method in 50 m. We further employed correlation-based feature selection (CFS) to evaluate feature importance in the object-based paradigm, finding that building height (BH), sky view factor (SVF), building surface fraction (BSF), permeable surface fraction (PSF), and land use exhibited high selection frequency while image bands were scarcely selected. In summary, we concluded that the object-based method is capable of LCZ mapping and performs better than the pixel-based method under the same training condition unless in under-segmentation cases.
Human–Robot Collaboration in Industrial Automation: Sensors and Algorithms
Authors: Schmitz Anne
Published: August 2022

Technology is changing the manufacturing world [...]
Big Girls Don’t Cry: An Assessment of Research Units’ Leadership and Gender Distribution in Higher Education Institutions
Authors: Morais Ricardo , Fernandes Clara E. , Piñeiro-Naval Valeriano
Published: August 2022

Academia is often pointed out as a challenging environment to evolve in, especially for women. Whilst women perform in multidisciplinary settings, studies point out still-existing gender gaps in academia, especially in positions of power. This study looks at decision-making positions in Higher Education Institutions (HEIs), specifically in Portuguese academic research. Furthermore, we seek to understand if research roles are distributed equally gender-wise among cohorts in research units, as well as if deans’ genders are a factor of influence in such role attributions. We will look at the research roles in academia, particularly research units fostered by HEIs, to observe gender distribution based on total cohorts. Using univariate and bivariate tests, our research aims to assess gender distribution in leading research roles in public and private institutions. We take the specific case of Portugal; therefore, we cannot extrapolate the results to other countries. However, outcomes point out resisting differences in fields of research and coordination and role distribution among R&D units, as well as in fundamental relations between power positions in academia and research.
Density Pattern of Flare-Horned Markhor (Capra falconeri) in Northern Pakistan
Authors: Ahmad Shakeel , Rehman Ejaz Ur , Ali Hussain , Din Nazakat , Haider Jibran , Din Jaffar Ud , Nawaz Muhammad Ali
Published: August 2022

Wild ungulates play vital roles in maintaining a balanced ecosystem through herbivory and are also an important determinant of carnivores’ density. The flare-horned markhor (Capra falconeri) is a threatened wild goat distributed across the mountain ranges of Pakistan, India, Afghanistan, Russia, Turkmenistan, Uzbekistan, and Tajikistan. The remote terrain and fragmented population limit our understanding of the population ecology of markhor, though knowledge of the target species population is vital for making informed management decisions. Therefore, the current study was designed to determine the markhor population across their range in Northern Pakistan and to evaluate the efforts made by the government and non-government organizations for the conservation of markhor. Double-observer surveys were conducted during 2019–2021 in nine major watersheds of Khyber Pakhtunkhwa and Gilgit-Baltistan covering an area of 4664 km2. Secondary data were collected for unassessed areas to gain a holistic overview of the markhor population and density in the region. Results revealed a markhor population of 7579, with a density of 0.30 animals per km2 in Northern Pakistan. Our analysis of the double-observer data through the Bayesian behavioral capture–recapture model estimated a population of 5993 individuals (95% CI) of markhor across nine study sites, with a density of 1.28 animals per km2. A review of secondary data revealed that a population of about 1586 was present in the un-surveyed area (20,033.33 km2), with a density of 0.08 per km2. A total of 146 groups of markhor were counted, with a mean group size of 23 (3–58) individuals. There were 109 males and 108 young per 100 females in the population. Among 1936 recorded males, Class I males accounted for 27.74%, followed by Class II (26.45%), Class IV (trophy-size) (23.40%), and Class III (22.42%). The overall detection probability was recorded as 0.87 and 0.68 for the first observer and second observer, respectively. Compared with the past reports, the population of markhor in Northern Pakistan appears to be increasing, particularly in protected areas (PAs) such as national parks and community-controlled hunting areas (CCHAs). Conservation programs, notably trophy hunting and PA networks, appear to be vital in sustaining markhor populations in parts of the species range. We recommend expansion in such programs in the markhor range in order to maintain a viable population of this majestic wild goat in the region.