bluuebunny/crossref_metadata_2025 huggingface dataset:
RT-PCR Testing of Organ Culture Medium for Corneal Storage Fails to Detect SARS-CoV-2 Infection Due to Lack of Viral Replication
Authors: Müller Lisa , Ostermann Philipp Niklas , Schaal Heiner , Salla Sabine , Timm Jörg , Geerling Gerd , Menzel-Severing Johannes
Published: January 2022

Concerns of possible transmission of SARS-CoV-2 from donors to patients by corneal transplantation have caused a decline in corneal transplantations. Graft culture media are routinely tested for infectious risks, but it is unclear whether this constitutes a viable means to avoid transmitting SARS-CoV-2 via keratoplasty. We found that SARS-CoV-2 RNA was not present in the medium after seven days of organ culture of corneas from donors (n = 4), who were SARS-CoV-2-positive upon tissue procurement. These medium samples showed no presence of viral RNA. To pursue this question under controlled conditions and further exclude the possibility of productive infection in corneal grafts, we inoculated corneoscleral discs from healthy donors (n = 8) with infectious SARS-CoV-2 and performed PCR testing of the culture medium at various time points. After seven days of culture, we also tested for SARS-CoV-2 RNA within the inoculated corneal tissue. The medium from tissue samples inoculated with SARS-CoV-2 showed no increase in viral RNA, which may indicate lack of viral replication in these corneal grafts. SARS-CoV-2-RNA was, however, detected on or in corneal tissue seven days after inoculation. Our data suggest that corneal grafts may not be permissive for replication of SARS-CoV-2 and demonstrates that PCR testing of culture media cannot safely exclude that tissue has been exposed to SARS-CoV-2. It also demonstrates the difficulty to differentiate between virus adherence and virus replication by PCR testing in SARS-CoV-2 exposed tissue.
Discovery, Development, Inventions and Patent Review of Fexinidazole: The First All-Oral Therapy for Human African Trypanosomiasis
Authors: Imran Mohd , Khan Shah Alam , Alshammari Mohammed Kanan , Alqahtani Ashwaq Muiedh , Alanazi Turkiah Abdullah , Kamal Mehnaz , Jawaid Talha , Ghoneim Mohammed M. , Alshehri Sultan , Shakeel Faiyaz
Published: January 2022

Human African trypanosomiasis (HAT or ‘sleeping sickness’) is a neglected tropical disease. If untreated, it is always fatal and leads to death. A few treatments are available for HAT, but most of them require a skilled professional, which increases the financial burden on the patient. Recently, fexinidazole (FEX) has been approved by the European Medicine Agency (EMA) and the United States Food and Drug Administration (USFDA) as the first all-oral therapy for the treatment of stage-1 (hemolymphatic) as well as stage-2 (meningoencephalitic) of HAT. Before the FEX approval, there were separate treatments for stage-1 and stage-2 of HAT. This study reviews the discovery, development timeline, inventions, and patent literature of FEX. It was first approved by EMA and USFDA in 2018 and 2021, respectively. FEX was also added to the World Health Organization’s list of essential drugs in 2019. The patent literature search revealed many types of patents/patent applications (compound, salt, process, method of treatment, drug combinations, and compositions) related to FEX, which have been summarized in this article. The authors foresee a great scope to develop more inventions based on FEX (novel salts, polymorphs, drug conjugates, cyclodextrin complex, etc.) for the treatment of many protozoal diseases (Leishmaniasis and Chagas disease), inflammatory diseases, and other microbial infections. New combinations of FEX with other treatments of HAT may also provide fruitful results. This review might be useful to the scientists working on the HAT and other neglected diseases to develop novel inventions and innovations of therapeutic relevance.
The Hitchhiker’s Guide to Human Therapeutic Nanoparticle Development
Authors: Ramos Thelvia I. , Villacis-Aguirre Carlos A. , López-Aguilar Katherine V. , Santiago Padilla Leandro , Altamirano Claudia , Toledo Jorge R. , Santiago Vispo Nelson
Published: January 2022

Nanomedicine plays an essential role in developing new therapies through novel drug delivery systems, diagnostic and imaging systems, vaccine development, antibacterial tools, and high-throughput screening. One of the most promising drug delivery systems are nanoparticles, which can be designed with various compositions, sizes, shapes, and surface modifications. These nanosystems have improved therapeutic profiles, increased bioavailability, and reduced the toxicity of the product they carry. However, the clinical translation of nanomedicines requires a thorough understanding of their properties to avoid problems with the most questioned aspect of nanosystems: safety. The particular physicochemical properties of nano-drugs lead to the need for additional safety, quality, and efficacy testing. Consequently, challenges arise during the physicochemical characterization, the production process, in vitro characterization, in vivo characterization, and the clinical stages of development of these biopharmaceuticals. The lack of a specific regulatory framework for nanoformulations has caused significant gaps in the requirements needed to be successful during their approval, especially with tests that demonstrate their safety and efficacy. Researchers face many difficulties in establishing evidence to extrapolate results from one level of development to another, for example, from an in vitro demonstration phase to an in vivo demonstration phase. Additional guidance is required to cover the particularities of this type of product, as some challenges in the regulatory framework do not allow for an accurate assessment of NPs with sufficient evidence of clinical success. This work aims to identify current regulatory issues during the implementation of nanoparticle assays and describe the major challenges that researchers have faced when exposing a new formulation. We further reflect on the current regulatory standards required for the approval of these biopharmaceuticals and the requirements demanded by the regulatory agencies. Our work will provide helpful information to improve the success of nanomedicines by compiling the challenges described in the literature that support the development of this novel encapsulation system. We propose a step-by-step approach through the different stages of the development of nanoformulations, from their design to the clinical stage, exemplifying the different challenges and the measures taken by the regulatory agencies to respond to these challenges.
Engineered Full Thickness Electrospun Scaffold for Esophageal Tissue Regeneration: From In Vitro to In Vivo Approach
Authors: Pisani Silvia , Croce Stefania , Mauramati Simone , Marmonti Marta , Cobianchi Lorenzo , Herman Irene , Dorati Rossella , Avanzini Maria Antonietta , Genta Ida , Benazzo Marco , Conti Bice
Published: January 2022

Acquired congenital esophageal malformations, such as malignant esophageal cancer, require esophagectomy resulting in full thickness resection, which cannot be left untreated. The proposed approach is a polymeric full-thickness scaffold engineered with mesenchymal stem cells (MSCs) to promote and speed up the regeneration process, ensuring adequate support and esophageal tissue reconstruction and avoiding the use of autologous conduits. Copolymers poly-L-lactide-co-poly-ε-caprolactone (PLA-PCL) 70:30 and 85:15 ratio were chosen to prepare electrospun tubular scaffolds. Electrospinning apparatus equipped with two different types of tubular mandrels: cylindrical (∅ 10 mm) and asymmetrical (∅ 10 mm and ∅ 8 mm) were used. Tubular scaffolds underwent morphological, mechanical (uniaxial tensile stress) and biological (MTT and Dapi staining) characterization. Asymmetric tubular geometry resulted in the best properties and was selected for in vivo surgical implantation. Anesthetized pigs underwent full thickness circumferential resection of the mid-lower thoracic esophagus, followed by implantation of the asymmetric scaffold. Preliminary in vivo results demonstrated that detached stitch suture achieved better results in terms of animal welfare and scaffold integration; thus, it is to be preferred to continuous suture.
Encapsulation, Release, and Cytotoxicity of Doxorubicin Loaded in Liposomes, Micelles, and Metal-Organic Frameworks: A Review
Authors: Ibrahim Mihad , Abuwatfa Waad H. , Awad Nahid S. , Sabouni Rana , Husseini Ghaleb A.
Published: January 2022

Doxorubicin (DOX) is one of the most widely used anthracycline anticancer drugs due to its high efficacy and evident antitumoral activity on several cancer types. However, its effective utilization is hindered by the adverse side effects associated with its administration, the detriment to the patients’ quality of life, and general toxicity to healthy fast-dividing cells. Thus, delivering DOX to the tumor site encapsulated inside nanocarrier-based systems is an area of research that has garnered colossal interest in targeted medicine. Nanoparticles can be used as vehicles for the localized delivery and release of DOX, decreasing the effects on neighboring healthy cells and providing more control over the drug’s release and distribution. This review presents an overview of DOX-based nanocarrier delivery systems, covering loading methods, release rate, and the cytotoxicity of liposomal, micellar, and metal organic frameworks (MOFs) platforms.
Dabigatran Acylglucuronide, the Major Metabolite of Dabigatran, Shows a Weaker Anticoagulant Effect than Dabigatran
Authors: Kim Jong-Min , Noh Jihyeon , Park Jin-Woo , Chung Hyewon , Kim Kyoung-Ah , Park Seung Bin , Lee Jun-Seok , Park Ji-Young
Published: January 2022

Dabigatran (DAB) is an orally administered thrombin inhibitor. Both DAB and its main metabolite dabigatran acylglucuronide (DABG) have established anticoagulant effects. Here, we aimed to compare the relative anticoagulant effects of DABG and DAB in humans. Anticoagulant effects of DAB and DABG were measured in vitro using a thrombin generation assay. Additionally, their effects on other coagulation assays including PT, aPTT, TT, and fibrinogen were compared. Both DAB and DABG showed inhibitory effects on thrombin generation in a dose-dependent manner, but DABG exhibited a weaker inhibitory effect than that of DAB. The IC50 values of DAB and DABG on thrombin generation AUC were 134.1 ng/mL and 281.9 ng/mL, respectively. DABG also exhibited weaker anticoagulant effects than DAB on PT, aPTT, and TT. The results of the present study indicate that the anticoagulant effect of DABG, a main active DAB metabolite, is weaker than that of DAB.
Case Report of an Interprofessional Intervention to Improve Quality of Life for a Fluid-Limited Patient
Authors: Cox Jennifer L. , Simpson Maree Donna
Published: January 2022

This was a case of an 81-year-old female, an amputee, who presented at hospital with a fractured neck of femur after a fall in the nursing home. The patient was being treated for several complex chronic conditions for which 30 regular medicines were prescribed and 100 tablets were being taken per day. The patient was fluid limited to 1500 mL per day but the need to swallow such a high number of tablets meant that there was no fluid allowance available for any other drinks, not even a cup of tea. In the nursing home, the patient had multiple prescribers, not all from the one surgery. The pharmacist conducted a multifaceted review of the patient’s medication and lifestyle factors. Working collaboratively with the wider health care team, the intervention was able to reduce the number of medications and improve the patient’s quality of life through improving the effectiveness of other lifestyle factors. This case not only showcases pharmacist interventions but also the synergistic benefit of interprofessional working with patients with chronic and complex conditions. This is arguably more critical in rural or remote areas where there is commonly a paucity of most health practitioners, health assistants and technicians.
Effect of Inoculation with Arbuscular Mycorrhizal Fungi and Fungicide Application on the Secondary Metabolism of Solanum tuberosum Leaves
Authors: Fritz Valentina , Tereucán Gonzalo , Santander Christian , Contreras Boris , Cornejo Pablo , Ferreira Paulo Ademar Avelar , Ruiz Antonieta
Published: January 2022

In potato (Solanum tuberosum) crops, the use of fungicides to control some diseases is widespread; however, it has been reported that this practice can modify the potato polyphenolic content, and new strategies oriented to the potato defense system are necessary. One alternative is the use of arbuscular mycorrhizal fungi (AMF) to improve the defense mechanisms of plants. In this study, phenolic profiles and antioxidant activities in leaves of three potato genotypes (CB2011-509, CB2011-104, and VR808) were evaluated in crops inoculated with three AMF strains (Claroideoglomus claroideum, Claroideoglomus lamellosum, and Fumneliformis mosseae) and with AMF in combination with the use of two commercial fungicides (MONCUT [M] and ReflectXtra [R]). Eight phenolic compounds were detected, mainly hydroxycinnamic acids (HCAD) and flavonols, in samples where the highest concentrations of HCAD were obtained, 5-caffeoylquinic acid was the most abundant phenolic. The antioxidant activity was higher using the cupric reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP) methods. The association of AMF with plants had benefits on the secondary metabolism; however, the response differed according to genotype. The different combinations of potato genotypes, AMF strain, and fungicide modified the content of phenolic compounds in leaves in different ways; the treatment using C. lamellosum and ReflectXtra was the ideal combination for the genotypes analyzed here, with the higher antioxidant response, which supports the further technological evaluation of efficient AMF strains and fungicides in potato crops.
Study on the Role of Salicylic Acid in Watermelon-Resistant Fusarium Wilt under Different Growth Conditions
Authors: Zhu Feiying , Wang Zhiwei , Su Wenjun , Tong Jianhua , Fang Yong , Luo Zhengliang , Yuan Fan , Xiang Jing , Chen Xi , Wang Ruozhong
Published: January 2022

Background: Fusarium wilt disease is leading threat to watermelon yield and quality. Different cultivation cropping systems have been reported as safe and efficient methods to control watermelon Fusarium wilt. However, the role of salicylic acid (SA) in watermelon resistance to Fusarium wilt in these different cultivation systems remains unknown. Methods: in this experiment, we used RNA-seq and qRT-PCR to study the effect of SA biosynthesis on improving watermelon health, demonstrating how it may be responsible for Fusarium wilt resistance under continuous monocropping and oilseed rape rotation systems. Results: the results revealed that the expression of the CIPALs genes was key to SA accumulation in watermelon roots. We observed that the NPR family genes may play different roles in responding to the SA signal. Differentially expressed NPRs and WRKYs may interact with other phytohormones, leading to the amelioration of watermelon Fusarium wilt. Conclusions: further understanding of gene expression patterns will pave the way for interventions that effectively control the disease.
Advanced Characterisation of Soft Polymers under Cyclic Loading in Context of Engine Mounts
Authors: Gejguš Tomáš , Schröder Jonas , Loos Klara , Lion Alexander , Johlitz Michael
Published: January 2022

The experimental investigation of viscoelastic behavior of cyclically loaded elastomeric components with respect to the time and the frequency domain is critical for industrial applications. Moreover, the validation of this behavior through numerical simulations as part of the concept of virtual prototypes is equally important. Experiments, combined measurements and test setups for samples as well as for rubber-metal components are presented and evaluated with regard to their industrial application. For application in electric vehicles with relevant excitation frequencies substantially higher than by conventional drive trains, high-frequency dynamic stiffness measurements are performed up to 3000 Hz on a newly developed test bench for elastomeric samples and components. The new test bench is compared with the standard dynamic measurement method for characterization of soft polymers. A significant difference between the measured dynamic stiffness values, caused by internal resonance of the bushing, is presented. This effect has a direct impact on the acoustic behavior of the vehicle and goes undetected by conventional measurement methods due to their lower frequency range. Furthermore, for application in vehicles with internal combustion engine, where the mechanical excitation amplitudes are significantly larger than by vehicles with electric engines, a new concept for the identification of viscoelastic material parameters that is suitable for the representation of large periodic deformations under consideration of energy dissipation is described. This dissipated energy causes self-heating of the polymer and leads to the precocious aging and failure of the elastomeric component. The validation of this concept is carried out thermally and mechanically on specimen and component level. Using the approaches developed in this work, the behavior of cyclically loaded elastomeric engine mounts in different applications can be simulated to reduce the time spent and save on the costs necessary for the production of prototypes.
A NIR-Light-Driven Twisted and Coiled Polymer Actuator with a PEDOT-Tos/Nylon-6 Composite for Durable and Remotely Controllable Artificial Muscle
Authors: Hwang Inwook , Mun Seongcheol , Shin Hyungcheol , Yun Sungryul
Published: January 2022

In this paper, we proposed a novel light-driven polymer actuator that could produce remotely controllable tensile stroke in response to near infrared (NIR) light. The light-driven polymer actuator was composed of a twisted and coiled nylon-6 fiber (TCN) and a thin poly(3,4-ethylenedioxythiophene) doped with p-toluenesulfonate (PEDOT-Tos) layer. By adopting dip-coating methodology with thermal polymerization process, we constructed a thin and uniform PEDOT-Tos layer on the surface of the three-dimensional TCN structure. Thanks to the PEDOT-Tos layer with excellent NIR light absorption characteristic, the NIR light illumination via a small LEDs array allowed the multiple PEDOT-Tos coated TCN actuators to be photo-thermally heated to a fairly consistent temperature and to simultaneously produce a contractile strain that could be modulated as high as 8.7% with light power. The actuation performance was reversible without any significant hysteresis and highly durable during 3000 cyclic operations via repetitive control of the LEDs. Together with its simple structure and facile fabrication, the light-driven actuator can lead to technical advances in artificial muscles due to its attractive benefits from remote controllability without complex coupled instruments and electromagnetic interference.
The Reduction in the Deformation of HDPE Composites Using Self-Lubricating Fillers in an Aqueous Environment
Authors: Liu Chuanbo , Liu Shutian , Dong Conglin , Yuan Chengqing , Bai Xiuqin
Published: January 2022

Reducing the deformation of polymer matrix materials can decrease the fluctuation of coefficient of friction (COF), and friction-induced vibration and its amplitudes. HDPE composites with T-ZnOw as a fixed strengthening filler were modified with the addition of Si3N4 particles at different concentrations. The COFs, wear rates, micro-morphologies, and friction-induced vibrations were obtained by conducting sliding tests against carbon steel balls in an aqueous environment at a low velocity and high load. The mechanism of the reduction in frictional fluctuation due to the addition of Si3N4 particles was revealed through the frictional responses. The results demonstrated that 4 wt% addition of Si3N4 in HDPE can enhance the strain–stress property and improve the lubrication by forming a lubricating film. Therefore, the surface deformation and the fluctuations of COFs and its vibrations were reduced. The aggregation phenomenon and reduced strain–stress response at a high concentration of Si3N4 disrupted the positive fluctuating reduction, and resulted in a rough surface with severe tearing and cracking deformations. Additionally, it led to fluctuating wear behaviors with high COF and vibrations. The results obtained in this study can elucidate the effects of adding Si3N4 particles to enhance lubrication in polymer composites. Additionally, the results provide a new research method for designing and manufacturing polymer-based composites with low friction-induced fluctuations.
Carbon-Nano Fibers Yield Improvement with Iodinated Electrospun PVA/Silver Nanoparticle as Precursor via One-Step Synthesis at Low Temperature
Authors: Gea Saharman , Attaurrazaq Boy , Situmorang Suhut Alexander , Piliang Averroes Fazlur Rahman , Hendrana Sunit , Goutianos Stergios
Published: January 2022

High temperature is required in carbon fiber synthesis in the carbonization step. However, direct high-temperature heating without the presence of additive materials would affect the yield and structure of carbon fibers produced. Thus, this study aims to synthesize carbon fibers from poly-vinyl alcohol (PVA), as the precursor and reducing agent, using silver nanoparticles (SNP) from silver nitrate (AgNO3) as additives. The pre-treatment of PVA was performed in three steps, i.e., mixing PVA/AgNO3, electrospinning, and iodination. The interaction of PVA and AgNO3 was assessed by FTIR, and SEM was used to characterize the electro-spun fibers prior and after iodination; Raman spectrophotometer was carried out to confirm the yield of carbon fibers. There was reduction in oxygen groups (3000–3800 cm−1) and emergence of –C=O (1100 cm−1) and –C=C– (1627 cm−1) functional groups, indicating formation of carbon layers. Based on the DT/GA results, the silver nanoparticles reduce the need of high temperature with optimum carbonization at 350 °C and lead to the formation of more regular graphene layers. Graphene layers with a size distribution of 0.438 nm and well-organized structures were successfully formed, and the Raman shifting showed higher intensities of G and G’ bands in the presence of Ag. Based on DT/GA results, the yield of carbon fibers with iodinated PVA fibers and SNP as additive had higher rates around 800 µg/min, reaching 33% at 500 °C. Thus, it is demonstrated that iodinated PVA/AgNO3 samples can significantly improve carbon fiber yield at low temperatures.
Screen Printing of pH-Responsive Dye to Textile
Authors: Gorjanc Marija , Gerl Ana , Kert Mateja
Published: January 2022

The development of pH-responsive textile sensors has attracted much interest in recent decades. Therefore, the aim of this study was to show that screen printing could be one of the possible techniques for development of pH-responsive textile. Several parameters that could influence the pH sensitivity and responsivity of a screen-printed textile with bromocresol green dye were studied, such as textile substrate (cotton, polyamide), printing paste composition, and type of fixation (heat and steaming). The change in mechanical and physical properties of the printed fabrics was tested according to the valid ISO, EN, or ASTM standards. The responsiveness of the printed samples to different pH values with the change in colour was evaluated spectrophotometrically. In addition, the colour fastness of the printed textiles to rubbing, washing, and light was also investigated. The results show that the textile responsiveness to pH change was successfully developed by flat screen-printing technique, which proves that the printing process could be one of the methods for the application of indicator dye to textiles. The application of the printing paste to cotton and polyamide fabrics resulted in an expected change in the mechanical and physical properties of the fabrics studied. The responsiveness of printed fabrics to the change of pH value depends on the type of fibres, the strength of dye–fibre interactions, and the wettability of the fabric with buffer solutions. The colour fastness of the printed fabrics to dry and wet rubbing is excellent. Printed polyamide fabric is more resistant to washing than printed cotton fabric. Both printed fabrics have poor colour fastness to light.
Influence of Xanthan Gum Addition on the Short- and Long-Term Retrogradation of Corn Starches of Various Amylose Content
Authors: Krystyjan Magdalena , Dobosz-Kobędza Anna , Sikora Marek , Baranowska Hanna Maria
Published: January 2022

Starch retrogradation is a complex process and in most food products is undesirable. Knowing and understanding the mechanisms and factors that influence this process may become the key to a better and innovative approach to food design. In this paper, we investigated the effect of 0%, 0.05% and 0.20% (w/w) xanthan gum (XG) addition on the short- and long-term retrogradation of 4%, 5% and 6% corn starch gels, depending on the amylose/amylopectin ratio in the starch. The changes were monitored throughout 90 days. The pasting characteristics of blends, rheological and texture analyses, as well as syneresis, revealed that XG stabilizes the starch in the short term, but it does not inhibit retrogradation caused by amylopectin. After 30 days of storage, the destabilization of the starch-hydrocolloid mixture was observed. Based on the obtained results, a probable mechanism for the retrogradation of corn starch process in the presence of xanthan gum was proposed.
Individualized Dosage Optimization for Myeloablative Conditioning before Unrelated Cord Blood Transplantation in a Diamond–Blackfan Anemia Patient with Germline RPL11 Mutation: A Case Study
Authors: Chen Rong-Long , Fang Li-Hua , Chen Liuh-Yow
Published: January 2022

Unrelated cord blood transplantation (CBT) for Diamond–Blackfan anemia (DBA), a systemic ribosomopathy affecting the disposition of conditioning agents, has resulted in outcomes inferior to those by transplantations from matched donors. We report the experience of the pharmacokinetics-guided myeloablative unrelated CBT in a DBA patient with a germline RPL11 mutation. The conditioning consisted of individualized dosing of fludarabine (based on weight and renal function with a target area under the curve (AUC) of 17.5 mg·h/L) and busulfan (based on therapeutic drug monitoring with a target AUC of 90 mg·h/L), as well as dosing and timing of thymoglobulin (based on body weight and pre-dose lymphocyte count to target pre-CBT AUC of 30.7 AU·day/mL and post-CBT AUC of 4.3 AU·day/mL, respectively). The pharmacokinetic measures resulted in a 27.5% reduction in busulfan and a 35% increase in fludarabine, as well as an over three-fold increase in thymoglobulin dosage with the start time changed to day-9 instead of day-2 compared to regular regimens. The transplantation resulted in rapid, complete, and sustained hematopoietic engraftment. The patient is now healthy over 3 years after CBT. A pharmacokinetics-guided individualized dosing strategy for conditioning might be a feasible option to improve the outcomes of DBA patients receiving unrelated myeloablative CBT.
An Artificial Neural Network Model to Predict Efficiency and Emissions of a Gasoline Engine
Authors: Yang Ruomiao , Yan Yuchao , Sun Xiaoxia , Wang Qifan , Zhang Yu , Fu Jiahong , Liu Zhentao
Published: January 2022

With global warming, and internal combustion engine emissions as the main global non-industrial emissions, how to further optimize the power performance and emissions of internal combustion engines (ICEs) has become a top priority. Since the internal combustion engine is a complex nonlinear system, it is often difficult to optimize engine performance from a certain factor of the internal combustion engine, and the various parameters of the internal combustion engine are coupled with each other and affect each other. Moreover, traditional experimental methods including 3D simulation or bench testing are very time consuming or expensive, which largely affects the development of engines and the speed of product updates. Machine learning algorithms are currently receiving a lot of attention in various fields, including the internal combustion engine field. In this study, an artificial neural network (ANN) model was built to predict three types of indicators (power, emissions, and combustion phasing) together, including 50% combustion crank angle (CA50), carbon monoxide (CO), unburned hydrocarbons (UHC), nitrogen oxides (NOx), indicated mean effective pressure (IMEP), and indicated thermal efficiency (ITE). The goal of this work was to verify that only one machine learning model can combine power, emissions, and phase metrics together for prediction. The predicted results showed that all coefficients of determination (R2) were larger than 0.97 with a relatively small RMSE, indicating that it is possible to build a predictive model with three types of parameters (power, emissions, phase) as outputs based on only one ANN model. Most importantly, when optimizing the powertrain control strategy of a hybrid vehicle, only a surrogate model can help establish the relationship between the input and output parameters of the whole engine, which is the need of the future research. Overall, this study demonstrated that it is feasible to integrate three types of combustion-related parameters in a single machine learning model.
‘The March Is Not Ended’: ‘Church’ Confronting the State over the Zimbabwean Crisis
Authors: Manyonganise Molly
Published: January 2022

The Zimbabwean crisis has been on-going since the year 2000. The various ecumenical bodies of the church in Zimbabwe have been voicing their concerns to the state through meetings and pastoral letters. While the church has been touted as a critical player in conflict resolution and peacebuilding, concerns about the church have been raised. One of these has been the issue of a divided organization that has failed to speak with one voice. With the coming into power of the so called ‘Second Republic’, hopes were raised that the state would be willing to have the crisis resolved. However, the crisis has just worsened, and the church has again been forced to break its silence. The purpose of this paper is to analyse the pastoral letter that was issued by the Zimbabwe Catholic Bishops Conference on 14 August 2020, titled ‘The March is not Ended’, which sought to respond to the crisis in Zimbabwe. The paper seeks to establish what religious groups can achieve in the event that they set aside their differences for the common good in conflict situations. Data for the paper were gathered through the issued pastoral letter, as well as the responses to it on online media.
Ancillary Data Uncertainties within the SeaDAS Uncertainty Budget for Ocean Colour Retrievals
Authors: De Vis Pieter , Mélin Frédéric , Hunt Samuel E. , Morrone Rosalinda , Sinclair Morven , Bell Bill
Published: January 2022

Atmospheric corrections introduce uncertainties in bottom-of-atmosphere Ocean Colour (OC) products. In this paper, we analyse the uncertainty budget of the SeaDAS atmospheric correction algorithm. A metrological approach is followed, where each of the error sources are identified in an uncertainty tree diagram and briefly discussed. Atmospheric correction algorithms depend on ancillary variables (such as meteorological properties and column densities of gases), yet the uncertainties in these variables were not studied previously in detail. To analyse these uncertainties for the first time, the spread in the ERA5 ensemble is used as an estimate for the uncertainty in the ancillary data, which is then propagated to uncertainties in remote sensing reflectances using a Monte Carlo approach and the SeaDAS atmospheric correction algorithm. In an example data set, wind speed and relative humidity are found to be the main contributors (among the ancillary parameters) to the remote sensing reflectance uncertainties.
Wetland Vegetation Classification through Multi-Dimensional Feature Time Series Remote Sensing Images Using Mahalanobis Distance-Based Dynamic Time Warping
Authors: Li Huayu , Wan Jianhua , Liu Shanwei , Sheng Hui , Xu Mingming
Published: January 2022

Efficient methodologies for vegetation-type mapping are significant for wetland’s management practices and monitoring. Nowadays, dynamic time warping (DTW) based on remote sensing time series has been successfully applied to vegetation classification. However, most of the previous related studies only focused on Normalized Difference Vegetation Index (NDVI) time series while ignoring multiple features in each period image. In order to further improve the accuracy of wetland vegetation classification, Mahalanobis Distance-based Dynamic Time Warping (MDDTW) using multi-dimensional feature time series was employed in this research. This method extends the traditional DTW algorithm based on single-dimensional features to multi-dimensional features and solves the problem of calculating similarity distance between multi-dimensional feature time series. Vegetation classification experiments were carried out in the Yellow River Delta (YRD). Compared with different classification methods, the results show that the K-Nearest Neighbors (KNN) algorithm based on MDDTW (KNN-MDDTW) has achieved better classification accuracy; the overall accuracy is more than 90%, and kappa is more than 0.9.
Extraction of Landslide Information Based on Object-Oriented Approach and Cause Analysis in Shuicheng, China
Authors: Han Yunfei , Wang Ping , Zheng Yongguo , Yasir Muhammad , Xu Chunmei , Nazir Shah , Hossain Md Sakaouth , Ullah Saleem , Khan Sulaiman
Published: January 2022

In China, landslides are abundant, widespread, and regular, destroying villages and agriculture and sometimes posing a threat to people’s lives. The question of how to rapidly detect and attain landslide data is a significant topic of research, yet traditional measurement using medium-resolution remote sensing data is problematic. Object-oriented categorization is utilized in this research to extract landside data from high-resolution GF-1 and Sentinel-2 data. Data preprocessing begins with orthophoto correction, image matching, and data fusion, followed by band enhancement, which comprises band synthesis, principal component analysis, and filtering, and finally landside extraction using an object-oriented technique. The impact of geology, lithology, rainfall, and human activities on the occurrence of landslides in the study area is explored utilizing DEM data, visualization tools, remote sensing interpretation map, and other associated data. The studies are conducted in Shuicheng County, Guizhou Province, China, with a segmentation scale of 25 pixels and 14 classification feature parameters. Following that, the landslide mass is extracted and categorization findings of nearby characteristics are acquired. Finally, the destructiveness of the landslide is determined by comparing the results of object-oriented classification before and after the landslide. With a Kappa coefficient of 0.76 and a landslide extraction accuracy of 79.8%, the overall classification accuracy is 87%. Combined with the geological structure, rock lithology, spatial location, landslide occurrence process, elevation of the study area, precipitation and the impact of human activities, the causes of the landslide are discussed and analyzed. The early warning of other unknown landslides can be obtained by analyzing the features of the aforementioned components.
Insect-Equivalent Radar Cross-Section Model Based on Field Experimental Results of Body Length and Orientation Extraction
Authors: Wang Rui , Kou Xiao , Cui Kai , Mao Huafeng , Wang Shuaihang , Sun Zhuoran , Li Weidong , Li Yunlong , Hu Cheng
Published: January 2022

Migratory insects constitute a valuable component of atmospheric and terrestrial biomass, and their migratory behavior provides abundant information for insect management and ecological effect assessment. Effective monitoring of migratory insects contributes to the evaluation and forecasting of catastrophic migration events, such as pest outbreaks. With a large-scale monitoring technique using S-band weather radar, the insect density is estimated based on the linear relationship between radar reflectivity and the average radar cross-section (RCS) of the insects. However, the average RCS model neglects the morphological and observation parameters of the insects, which reduces the estimation accuracy. In this paper, we established an insect-equivalent RCS model based on the joint probability distribution of “body length–incident angle”. Then, we observed and extracted the morphological and observational parameters of the migratory insects by conducting a 69-day field experiment, using a Ku-band fully polarimetric entomological radar, in Dongying, Shandong Province, China. Finally, combined with the experimental results and the simulated scattering characteristics of individual insects with different body lengths, the typical insect-equivalent RCS model was established. The RCS of the model fluctuates between 0.233 mm2 and 0.514 mm2, with different incident angles. Our results lay a data foundation for the quantitative analysis of insects by weather radar.
On the Processing of Dual-Channel Receiving Signals of the LuTan-1 SAR System
Authors: Lin Haoyu , Deng Yunkai , Zhang Heng , Liu Dacheng , Liang Da , Fang Tingzhu , Wang Robert
Published: January 2022

LuTan-1 (LT-1) is an innovative spaceborne radar Earth observation mission including two satellites equipped with synthetic aperture radar (SAR) which will be launched in 2022. Active phased array antennas that can be divided into two physical channels are equipped on each satellite. The signal can be transmitted through the full antenna without broadening and recorded by each channel. Therefore, two methods can be used to preprocess the dual-channel receiving signals, referred to as dual-channel echo reconstruction and dual-channel echo synthesis. The former is inherited from the traditional high-resolution wide-swath mode and the latter is a method that takes coherent superposition as the reference. This paper researches the impacts of the two methods in system performance and imaging quality. Principles and theoretical models are firstly given. Furthermore, the system performance under the “L1A_SM_S” working mode of the LT-1 is simulated to compare the differences between the two methods, which mainly focuses on azimuth ambiguity-to-signal ratio, noise equivalent sigma zero, and the performance of block adaptive quantization. Afterwards, the test data acquired by the ground validation system of the LT-1 are used for the hardware-in-the-loop simulation to demonstrate the imaging quality between the two methods. Finally, a quantitative comparison is given.
A Scalable Computing Resources System for Remote Sensing Big Data Processing Using GeoPySpark Based on Spark on K8s
Authors: Guo Jifu , Huang Chunlin , Hou Jinliang
Published: January 2022

As a result of Earth observation (EO) entering the era of big data, a significant challenge relating to by the storage, analysis, and visualization of a massive amount of remote sensing (RS) data must be addressed. In this paper, we proposed a novel scalable computing resources system to achieve high-speed processing of RS big data in a parallel distributed architecture. To reduce data movement among computing nodes, the Hadoop Distributed File System (HDFS) is established on nodes of K8s, which are also used for computing. In the process of RS data analysis, we innovatively use the tile-oriented programming model instead of the traditional strip-oriented or pixel-oriented approach to better implement parallel computing in a Spark on Kubernetes (K8s) cluster. A large RS raster layer can be abstracted as a user-defined tile format of any size, so that a whole computing task can be divided into multiple distributed parallel tasks. The computing resources applied by users would be immediately assigned in the Spark on K8s cluster by simply configuring and initializing SparkContext through a web-based Jupyter notebook console. Users can easily query, write, or visualize data in any box size from the catalog module in GeoPySpark. In summary, the system proposed in this study can provide a distributed scalable resources system for assembling big data storage, parallel computing, and real-time visualization.
Physical and Biochemical Responses to Sequential Tropical Cyclones in the Arabian Sea
Authors: Wang Tongyu , Chen Fajin , Zhang Shuwen , Pan Jiayi , Devlin Adam T. , Ning Hao , Zeng Weiqiang
Published: January 2022

The upper-ocean physical and biochemical responses to sequential tropical cyclones (TCs) Kyarr and Maha in the Arabian Sea (AS) were investigated using data from satellites and Bio-Argo floats. Corresponding to slow and strong sequential TCs, two cooling processes and two short chlorophyll a (chl-a) blooms occurred on the sea surface, separated by 6–7 days, and three cold eddies appeared near the TC paths, with sea surface temperatures dropping more than 6 °C. Phytoplankton blooms occurred near cold eddies e1, e2, and e3, with chl-a concentrations reaching 12.76, 23.09, and 16.51 mg/m3, respectively. The depth-integrated chl-a analysis confirmed that the first chl-a enhancement was related to the redistribution of chl-a associated with TC-induced Ekman pumping and vertical mixing at the base of the mixed layer post-TC Kyarr. The subsequent, more pronounced chl-a bloom occurred due to the net growth of phytoplankton, as nutrient-rich cold waters were brought into the euphotic layer through Ekman pumping, entrainment, and eddy pumping post-TC Maha. Upwelling (vertical mixing) was the dominant process allowing the resupply of nutrients near (on the right side of) the TC path. The results derived from a biogeochemistry model indicated that the chl-a evolution was consistent with the observations recorded on Bio-Argo floats. This study suggests that in sequential TC-induced phytoplankton blooms, the redistribution of chl-a is a major mechanism for the first bloom, when high chl-a concentrations occur in the subsurface layer, whereas the second bloom is fueled by nutrients supplied from the deep layer.
DA-IMRN: Dual-Attention-Guided Interactive Multi-Scale Residual Network for Hyperspectral Image Classification
Authors: Zou Liang , Zhang Zhifan , Du Haijia , Lei Meng , Xue Yong , Wang Z. Jane
Published: January 2022

Deep learning-based fusion of spectral-spatial information is increasingly dominant for hyperspectral image (HSI) classification. However, due to insufficient samples, current feature fusion methods often neglect joint interactions. In this paper, to further improve the classification accuracy, we propose a dual-attention-guided interactive multi-scale residual network (DA-IMRN) to explore the joint spectral-spatial information and assign pixel-wise labels for HSIs without information leakage. In DA-IMRN, two branches focusing on spatial and spectral information separately are employed for feature extraction. A bidirectional-attention mechanism is employed to guide the interactive feature learning between two branches and promote refined feature maps. In addition, we extract deep multi-scale features corresponding to multiple receptive fields from limited samples via a multi-scale spectral/spatial residual block, to improve classification performance. Experimental results on three benchmark datasets (i.e., Salinas Valley, Pavia University, and Indian Pines) support that attention-guided multi-scale feature learning can effectively explore the joint spectral-spatial information. The proposed method outperforms state-of-the-art methods with the overall accuracy of 91.26%, 93.33%, and 82.38%, and the average accuracy of 94.22%, 89.61%, and 80.35%, respectively.
Efficient Instance Segmentation Paradigm for Interpreting SAR and Optical Images
Authors: Fan Fan , Zeng Xiangfeng , Wei Shunjun , Zhang Hao , Tang Dianhua , Shi Jun , Zhang Xiaoling
Published: January 2022

Instance segmentation in remote sensing images is challenging due to the object-level discrimination and pixel-level segmentation for the objects. In remote sensing applications, instance segmentation adopts the instance-aware mask, rather than horizontal bounding box and oriented bounding box in object detection, or category-aware mask in semantic segmentation, to interpret the objects with the boundaries. Despite these distinct advantages, versatile instance segmentation methods are still to be discovered for remote sensing images. In this paper, an efficient instance segmentation paradigm (EISP) for interpreting the synthetic aperture radar (SAR) and optical images is proposed. EISP mainly consists of the Swin Transformer to construct the hierarchical features of SAR and optical images, the context information flow (CIF) for interweaving the semantic features from the bounding box branch to mask branch, and the confluent loss function for refining the predicted masks. Experimental conclusions can be drawn on the PSeg-SSDD (Polygon Segmentation—SAR Ship Detection Dataset) and NWPU VHR-10 instance segmentation dataset (optical dataset): (1) Swin-L, CIF, and confluent loss function in EISP acts on the whole instance segmentation utility; (2) EISP* exceeds vanilla mask R-CNN 4.2% AP value on PSeg-SSDD and 11.2% AP on NWPU VHR-10 instance segmentation dataset; (3) The poorly segmented masks, false alarms, missing segmentations, and aliasing masks can be avoided to a great extent for EISP* in segmenting the SAR and optical images; (4) EISP* achieves the highest instance segmentation AP value compared to the state-of-the-art instance segmentation methods.
Microwave Brightness Temperature (MBT) Background in Bayan Har Block, Qinghai-Tibet Plateau and Its Importance in Searching for Seismic MBT Anomalies
Authors: Qi Yuan , Wu Lixin , Ding Yifan , Liu Yingjia , Wang Xiao , Mao Wenfei
Published: January 2022

The abnormal behaviors of microwave brightness temperature (MBT) before and after some strong inland earthquakes have been studied for more than 15 years, but the normal features of MBT background in the investigated regions still lack essential attention. This study focused on the extremely seismically active Bayan Har block on the Qinghai-Tibet Plateau in China, and revealed the spatiotemporal variations of monthly mean background and monthly standard deviation (STD) of MBT by using data of 10.65 and 89 GHz from AMSR-2 instrument. In terms of space, the results revealed that the MBT backgrounds at the two frequencies both basically exhibited a negative correlation with regional altitude but were more pronounce at high frequency. They also showed different response characteristics to the properties of soil and vegetation. In terms of time, the low-frequency background exhibited a complex month-to-month variation, with auxiliary data suggesting a joint contribution of surface soil moisture (SSM) and seasonal temperature; while the high-frequency background presented good agreement only with the variation in surface temperature. Meanwhile, the monthly STD of MBT was discovered being affected by SSM at the low-frequency and by snowfall events at the high-frequency. By employing MBT data of 10.65 GHz from AMSR-E and AMSR-2 sensors, the spatiotemporal evolutions of MBT anomalies before, during and after the Ms 7.1 Yushu earthquake on 13 April 2010 and the Ms 7.4 Maduo earthquake on 21 May 2021 were obtained referring to dynamic monthly mean background. A typical strip-shaped positive MBT anomaly just covering the Bayan Har block was found occurring prior to the two earthquakes, and the time series of average MBT anomaly inside the block was analyzed by using multiple datasets. The typical abnormal MBT strip was discriminated being independent of non-seismic factors and regarded as a possible precursor for both earthquakes. This research uncovered the normal features of MBT background and demonstrated the common characteristics of MBT anomalies preceding two strike-slip earthquakes inside the Bayan Har block. It has instructive significance for studying, understanding and searching for seismic MBT anomalies on Qinghai-Tibet Plateau.