bluuebunny/crossref_metadata_2025 huggingface dataset:
Therapies Targeting Epigenetic Alterations in Acute Kidney Injury-to-Chronic Kidney Disease Transition
Authors: Tanemoto Fumiaki , Mimura Imari
Published: January 2022

Acute kidney injury (AKI) was previously thought to be a merely transient event; however, recent epidemiological evidence supports the existence of a causal relationship between AKI episodes and subsequent progression to chronic kidney disease (CKD). Although the pathophysiology of this AKI-to-CKD transition is not fully understood, it is mediated by the interplay among multiple components of the kidney including tubular epithelial cells, endothelial cells, pericytes, inflammatory cells, and myofibroblasts. Epigenetic alterations including histone modification, DNA methylation, non-coding RNAs, and chromatin conformational changes, are also expected to be largely involved in the pathophysiology as a “memory” of the initial injury that can persist and predispose to chronic progression of fibrosis. Each epigenetic modification has a great potential as a therapeutic target of AKI-to-CKD transition; timely and target-specific epigenetic interventions to the various temporal stages of AKI-to-CKD transition will be the key to future therapeutic applications in clinical practice. This review elaborates on the latest knowledge of each mechanism and the currently available therapeutic agents that target epigenetic modification in the context of AKI-to-CKD transition. Further studies will elucidate more detailed mechanisms and novel therapeutic targets of AKI-to-CKD transition.
Prediction of Drug Targets for Specific Diseases Leveraging Gene Perturbation Data: A Machine Learning Approach
Authors: Zhao Kai , Shi Yujia , So Hon-Cheong
Published: January 2022

Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles from gene perturbations. We present a novel computational approach for drug target discovery based on machine learning (ML) models. ML models are first trained on drug-induced expression profiles with outcomes defined as whether the drug treats the studied disease. The goal is to “learn” the expression patterns associated with treatment. Then, the fitted ML models were applied to expression profiles from gene perturbations (overexpression (OE)/knockdown (KD)). We prioritized targets based on predicted probabilities from the ML model, which reflects treatment potential. The methodology was applied to predict targets for hypertension, diabetes mellitus (DM), rheumatoid arthritis (RA), and schizophrenia (SCZ). We validated our approach by evaluating whether the identified targets may ‘re-discover’ known drug targets from an external database (OpenTargets). Indeed, we found evidence of significant enrichment across all diseases under study. A further literature search revealed that many candidates were supported by previous studies. For example, we predicted PSMB8 inhibition to be associated with the treatment of RA, which was supported by a study showing that PSMB8 inhibitors (PR-957) ameliorated experimental RA in mice. In conclusion, we propose a new ML approach to integrate the expression profiles from drugs and gene perturbations and validated the framework. Our approach is flexible and may provide an independent source of information when prioritizing drug targets.
The Use of Bioactive Compounds in Hyperglycemia- and Amyloid Fibrils-Induced Toxicity in Type 2 Diabetes and Alzheimer’s Disease
Authors: Lupaescu Ancuta-Veronica , Iavorschi Monica , Covasa Mihai
Published: January 2022

It has become increasingly apparent that defective insulin signaling may increase the risk for developing Alzheimer’s disease (AD), influence neurodegeneration through promotion of amyloid formation or by increasing inflammatory responses to intraneuronal β-amyloid. Recent work has demonstrated that hyperglycemia is linked to cognitive decline, with elevated levels of glucose causing oxidative stress in vulnerable tissues such as the brain. The ability of β-amyloid peptide to form β-sheet-rich aggregates and induce apoptosis has made amyloid fibrils a leading target for the development of novel pharmacotherapies used in managing and treatment of neuropathological conditions such as AD-related cognitive decline. Additionally, deposits of β-sheets folded amylin, a glucose homeostasis regulator, are also present in diabetic patients. Thus, therapeutic compounds capable of reducing intracellular protein aggregation in models of neurodegenerative disorders may prove useful in ameliorating type 2 diabetes mellitus symptoms. Furthermore, both diabetes and neurodegenerative conditions, such as AD, are characterized by chronic inflammatory responses accompanied by the presence of dysregulated inflammatory biomarkers. This review presents current evidence describing the role of various small bioactive molecules known to ameliorate amyloidosis and subsequent effects in prevention and development of diabetes and AD. It also highlights the potential efficacy of peptide–drug conjugates capable of targeting intracellular targets.
Trends in the Prescription of Strong Opioids for Chronic Non-Cancer Pain in Primary Care in Catalonia: Opicat-Padris-Project
Authors: Perelló-Bratescu Aina , Dürsteler Christian , Álvarez-Carrera Maria Asunción , Granés Laura , Kostov Belchin , Sisó-Almirall Antoni
Published: January 2022

In chronic non-cancer pain (CNCP), evidence of the effectiveness of strong opioids (SO) is very limited. Despite this, their use is increasingly common. To examine SO prescriptions, we designed a descriptive, longitudinal, retrospective population-based study, including patients aged ≥15 years prescribed SO for ≥3 months continuously in 2013–2017 for CNCP in primary care in Catalonia. Of the 22,691 patients included, 17,509 (77.2%) were women, 10,585 (46.6%) were aged >80 years, and most had incomes of <€18,000 per year. The most common diagnoses were musculoskeletal diseases and psychiatric disorders. There was a predominance of transdermal fentanyl in the defined daily dose (DDD) per thousand inhabitants/day, with the greatest increase for tapentadol (312% increase). There was an increase of 66.89% in total DDD per thousand inhabitants/day for SO between 2013 (0.737) and 2017 (1.230). The mean daily oral morphine equivalent dose/day dispensed for all drugs was 83.09 mg. Transdermal fentanyl and immediate transmucosal release were the largest cost components. In conclusion, there was a sustained increase in the prescription of SO for CNCP, at high doses, and in mainly elderly patients, predominantly low-income women. The new SO are displacing other drugs.
The Anticancer Ruthenium Compound BOLD-100 Targets Glycolysis and Generates a Metabolic Vulnerability towards Glucose Deprivation
Authors: Baier Dina , Schoenhacker-Alte Beatrix , Rusz Mate , Pirker Christine , Mohr Thomas , Mendrina Theresa , Kirchhofer Dominik , Meier-Menches Samuel M. , Hohenwallner Katharina , Schaier Martin , Rampler Evelyn , Koellensperger Gunda , Heffeter Petra , Keppler Bernhard , Berger Walter
Published: January 2022

Cellular energy metabolism is reprogrammed in cancer to fuel proliferation. In oncological therapy, treatment resistance remains an obstacle and is frequently linked to metabolic perturbations. Identifying metabolic changes as vulnerabilities opens up novel approaches for the prevention or targeting of acquired therapy resistance. Insights into metabolic alterations underlying ruthenium-based chemotherapy resistance remain widely elusive. In this study, colon cancer HCT116 and pancreatic cancer Capan-1 cells were selected for resistance against the clinically evaluated ruthenium complex sodium trans-[tetrachlorobis(1H-indazole)ruthenate(III)] (BOLD-100). Gene expression profiling identified transcriptional deregulation of carbohydrate metabolism as a response to BOLD-100 and in resistance against the drug. Mechanistically, acquired BOLD-100 resistance is linked to elevated glucose uptake and an increased lysosomal compartment, based on a defect in downstream autophagy execution. Congruently, metabolomics suggested stronger glycolytic activity, in agreement with the distinct hypersensitivity of BOLD-100-resistant cells to 2-deoxy-d-glucose (2-DG). In resistant cells, 2-DG induced stronger metabolic perturbations associated with ER stress induction and cytoplasmic lysosome deregulation. The combination with 2-DG enhanced BOLD-100 activity against HCT116 and Capan-1 cells and reverted acquired BOLD-100 resistance by synergistic cell death induction and autophagy disturbance. This newly identified enhanced glycolytic activity as a metabolic vulnerability in BOLD-100 resistance suggests the targeting of glycolysis as a promising strategy to support BOLD-100 anticancer activity.
Vine Cane Compounds to Prevent Skin Cells Aging through Solid Lipid Nanoparticles
Authors: Pereira Adriana , Ramalho Maria João , Silva Renata , Silva Vera , Marques-Oliveira Rita , Silva Ana Catarina , Pereira Maria Carmo , Loureiro Joana A.
Published: January 2022

The long lifespan of the world’s population has been raising interest in the research for new solutions to delay the aging process. With the aim of skin aging prevention, solid lipid nanoparticles (SLNs) were developed in this work for the encapsulation of three lipophilic natural compounds extracted from vine cane—epigallocatechin gallate (EGCG), resveratrol and myricetin. The developed loaded-SLNs proved to be stable, maintaining their adequate physicochemical characteristics for 30 days. In addition, the loaded-SLNs formulations exhibited high encapsulation efficiencies and loading capacities and high intracellular antioxidant activity. The mixture of EGCG-loaded SLNs with resveratrol-loaded SLNs proved to have the highest protection against induced oxidative stress. The in vitro cytotoxicity of the loaded SLNs was also evaluated, showing that the developed formulations are biocompatible for concentrations up to 50 µg/mL and could be safe for use in cosmetics. The encapsulation of EGCG, resveratrol and myricetin in SLNs seems to be a suitable strategy for the delivery of these antioxidants to the skin, improving their bioavailability.
EGFR-Targeted Photodynamic Therapy
Authors: Ulfo Luca , Costantini Paolo Emidio , Di Giosia Matteo , Danielli Alberto , Calvaresi Matteo
Published: January 2022

The epidermal growth factor receptor (EGFR) plays a pivotal role in the proliferation and metastatization of cancer cells. Aberrancies in the expression and activation of EGFR are hallmarks of many human malignancies. As such, EGFR-targeted therapies hold significant potential for the cure of cancers. In recent years, photodynamic therapy (PDT) has gained increased interest as a non-invasive cancer treatment. In PDT, a photosensitizer is excited by light to produce reactive oxygen species, resulting in local cytotoxicity. One of the critical aspects of PDT is to selectively transport enough photosensitizers to the tumors environment. Accordingly, an increasing number of strategies have been devised to foster EGFR-targeted PDT. Herein, we review the recent nanobiotechnological advancements that combine the promise of PDT with EGFR-targeted molecular cancer therapy. We recapitulate the chemistry of the sensitizers and their modes of action in PDT, and summarize the advantages and pitfalls of different targeting moieties, highlighting future perspectives for EGFR-targeted photodynamic treatment of cancer.
Model-Based Equivalent Dose Optimization to Develop New Donepezil Patch Formulation
Authors: Jung Woojin , Jung Heeyoon , Vu Ngoc-Anh Thi , Kim Gwan-Young , Kim Gyoung-Won , Chae Jung-woo , Kim Taeheon , Yun Hwi-yeol
Published: January 2022

Donepezil patch was developed to replace the original oral formulation. To accurately describe the pharmacokinetics of donepezil and investigate compatible doses between two formulations, a population pharmacokinetic model for oral and transdermal patches was built based on a clinical study. Plasma donepezil levels were analyzed via liquid chromatography/tandem mass spectrometry. Non-compartmental analyses were performed to derive the initial parameters for compartmental analyses. Compartmental analysis (CA) was performed with NLME software NONMEM assisted by Perl-speaks-NONMEM, and R. Model evaluation was proceeded via visual predictive checks (VPC), goodness-of-fit (GOF) plotting, and bootstrap method. The bioequivalence test was based on a 2 × 2 crossover design, and parameters of AUC and Cmax were considered. We found that a two-compartment model featuring two transit compartments accurately describes the pharmacokinetics of nine subjects administered in oral, as well as of the patch-dosed subjects. Through evaluation, the model was proven to be sufficiently accurate and suitable for further bioequivalence tests. Based on the bioequivalence test, 114 mg/101.3 cm2–146 mg/129.8 cm2 of donepezil patch per week was equivalent to 10 mg PO donepezil per day. In conclusion, the pharmacokinetic model was successfully developed, and acceptable parameters were estimated. However, the size calculated by an equivalent dose of donepezil patch could be rather large. Further optimization in formulation needs to be performed to find appropriate usability in clinical situations.
High-Performance Liquid Chromatography–Mass Spectrometry Analysis of Glycoalkaloids from Underexploited Solanum Species and Their Acetylcholinesterase Inhibition Activity
Authors: Popova Inna , Sell Belinda , Pillai Syamkumar Sivasankara , Kuhl Joseph , Dandurand Louise-Marie
Published: January 2022

Solanum glycoalkaloids are gaining increased scientific attention due to their bioactive potential in the defense of plants against pests and pathogens. The comprehensive glycoalkaloid profiling from the leaves, stems, and roots of seven underexploited Solanum species (S. caripense, S. melanocerasum, S. muricatum, S. nigrum, S. quitoense, S. retroflexum, and S. sisymbriifolium) was conducted using high-performance liquid chromatography–time-of-flight mass spectrometry. A total of 51 glycoalkaloids were shared among the studied Solanum species, with concentrations ranging from 7 to 5.63 × 105 ng g−1. Based on the glycoalkaloid composition, plants were separated into two clusters, Cluster 1 (S. melanocerasum, S. nigrum, and S. retroflexum) and Cluster 2 (S. caripense, S. muricatum, S. quitoense, and S. sisymbriifolium). The inhibition activity of glycoalkaloid extracts on acetylcholinesterase showed a half-maximal inhibitory concentration (IC50), ranging from 0.4 (S. nigrum stems) to 344.9 µg mL−1 (S. sisymbriifolium leaves), that was not directly correlated to the total glycoalkaloid contents. This suggests that the composition of glycoalkaloids in the plant extract, rather than the total concentration, is a driver of biological activity. The study provides a framework for the bioprospecting of underexploited Solanum species for exploring bioactive glycoalkaloids and other compounds with potential pesticidal activities for the development of green bioformulation. This is the first comprehensive report on the glycoalkaloid profiles of S. retroflexum.
Silencing Phytoene Desaturase Causes Alteration in Monoterpene Volatiles Belonging to the Methylerythritol Phosphate Pathway
Authors: Killiny Nabil
Published: January 2022

Volatile organic compounds (VOCs) are a large group of lipophilic hydrocarbon compounds derived from different biosynthetic pathways in plants. VOCs are produced and released from plants as a defense mechanism against biotic and abiotic stresses. They are involved in communication with the surrounding environment including plant-to-plant interactions and attracting or repelling insects. In citrus, phytoene desaturase (PDS), a precursor of the carotenoid biosynthetic pathway has been silenced using the Citrus tristeza virus-induced gene silencing technique. Silencing PDS resulted in a reduction of carotenoid contents and in the photobleaching phenotype in leaves. Interestingly, the strength of the phenotype was varied within the plants due to the unequal distribution of virus particles. Using solid-phase microextraction (SPME), fibers released VOCs from leaves with gradient degrees of the photobleaching phenotype were collected and analyzed in gas chromatography-mass spectrophotometry (GC-MS). Overall, 47 VOCs belonging to 12 chemically distinguished groups were detected and identified using authentic standards. Simple linear regression showed that monoterpenes belonging to methylerythritol phosphate (MEP) were significantly corrected with the degrees of photobleaching (carotenoid content). Both carotenoids and MEP biosynthetic pathways occurred in the plastid. Thus, we provide preliminary evidence for a potential role of carotenoids in supporting the MEP pathway and/or the production of monoterpenes.
Adhesive-Free Adhesion between Plasma-Treated Glass-Cloth-Containing Polytetrafluoroethylene (GC–PTFE) and Stainless Steel: Comparison between GC–PTFE and Pure PTFE
Authors: Nishino Misa , Okazaki Yuki , Seto Yosuke , Uehara Tsuyoshi , Endo Katsuyoshi , Yamamura Kazuya , Ohkubo Yuji
Published: January 2022

In this study, the effect of plasma treatment on glass-cloth-containing polytetrafluoroethylene (GC–PTFE) was investigated. Previous plasma studies investigated pure PTFE (which does not contain glass cloth) but not GC–PTFE. The effect of Ar + H2O plasma treatment on GC–PTFE was investigated. The Ar + H2O plasma-treated GC–PTFE sheets were thermally compressed to stainless steel (SUS304) foils without using adhesive, and the GC–PTFE/SUS304 adhesion strengths were measured using a 90° peel test. The adhesion strength increased with the increase in the plasma treatment time (0.8 and 1.0 N/mm at 20 s and 300 s, respectively). Thus, strong adhesion between GC–PTFE/SUS304 was achieved without adhesive. This improvement in the adhesion properties of GC–PTFE can be attributed to the generation of oxygen-containing functional groups and the decrease in the surface roughness of the samples. Thereafter, the adhesion properties of GC–PTFE and pure PTFE were compared. Because, unlike pure PTFE, GC–PTFE has no weak boundary layer, GC–PTFE exhibited better adhesion properties than pure PTFE under short plasma treatment times.
Effect of Graphite Filler Type on the Thermal Conductivity and Mechanical Behavior of Polysulfone-Based Composites
Authors: Mohammad Hussam , Stepashkin Andrey A. , Tcherdyntsev Victor V.
Published: January 2022

The goal of this study was to create a high-filled composite material based on polysulfone using various graphite materials. Composite material based on graphite-filled polysulfone was prepared using a solution method which allows the achievement of a high content of fillers up to 70 wt.%. Alongside the analysis of the morphology and structure, the thermal conductivity and mechanical properties of the composites obtained were studied. Structural analysis shows how the type of filler affects the structure of the composites with the appearance of pores in all samples which also has a noticeable effect on composites’ properties. In terms of thermal conductivity, the results show that using natural graphite as a filler gives the best results in thermal conductivity compared to artificial and expanded graphite, with the reduction of thermal conductivity while increasing temperature. Flexural tests show that using artificial graphite as a filler gives the composite material the best mechanical load transfer compared to natural or expanded graphite.
K+-Responsive Crown Ether-Based Amphiphilic Copolymer: Synthesis and Application in the Release of Drugs and Au Nanoparticles
Authors: Wang Xiao , Zheng Xianghong , Liu Xinyu , Zeng Birong , Xu Yiting , Yuan Conghui , Dai Lizong
Published: January 2022

Due to unique chelating and macrocyclic effects, crown ether compounds exhibit wide application prospects. They could be introduced into amphiphilic copolymers to provide new trigger mode for drug delivery. In this work, new amphiphilic random polymers of poly(lipoic acid-methacrylate-co-poly(ethylene glycol) methyl ether methacrylate-co-N-isopropylacrylamide-co-benzo-18-crown-6-methacrylamide (abbrev. PLENB) containing a crown ether ring and disulphide bond were synthesized via RAFT polymerization. Using the solvent evaporation method, the PLENB micelles were formed and then used to load substances, such as doxorubicin hydrochloride (DOX) and gold nanoparticles. The results showed that PLENB exhibited a variety of lowest critical solution temperature (LCST) in response to the presence of different ions, such as K+, Na+ and Mg2+. In particular, the addition of 150 mM K+ increased the LCST of PLENB from 31 to 37 °C and induced the release of DOX from the PLENB@DOX assemblies with a release rate of 99.84% within 12 h under 37 °C. However, Na+ and Mg2+ ions could not initiate the same response. Furthermore, K+ ions drove the disassembly of gold aggregates from the PLENB-SH@Au assemblies to achieve the transport of Au NPs, which is helpful to construct a K+-triggered carrier system.
Interpolymer Complexes of Poly(methacryloyloxyethyl phosphorylcholine) and Polyacids
Authors: Nekrasova Tatiana , Nazarova Olga , Vlasova Elena , Fischer Andrei , Zolotova Yuliya , Bezrukova Marina , Panarin Evgeniy
Published: January 2022

It has been shown that macromolecules of poly(methacryloyloxyethyl phosphorylcholine) can form hydrogen bonded interpolymer complexes with homo- and copolymers of carboxylic acids and with poly(vinylphosphonic) acid in aqueous solutions. Polarized luminescence and IR spectroscopy were applied in the investigation. Nanosecond relaxation times characterizing the mobility of the chain fragments for the initial luminescent labeled polymers were determined and their changes by a factor of 2–50 were established during the formation of an interpolymer complex. Hydrogen bonds play a dominant role in the formation of these complexes. Hydrophobic interactions serve as an additional stabilizing factor. It is established that poly(methacryloyloxyethyl phosphorylcholine)/poly(vinylphosphonic acid) complex forms a looser structure in comparison with those for polycarboxylic acids as result of electrostatic repulsion between charged groups.
Enhancement of the Mechanical, Self-Healing and Pollutant Adsorption Properties of Mortar Reinforced with Empty Fruit Bunches and Shell Chars of Oil Palm
Authors: Hermawan Dede , Budiman Ismail , Febrianto Fauzi , Subyakto Subyakto , Pari Gustan , Ghozali Muhammad , Bahtiar Effendi , Sutiawan Jajang , Azevedo Afonso
Published: January 2022

This study aims to produce mortar through the addition of oil palm shells (OPS)-activated charcoal and oil palm empty fruit bunch (OPEFB) hydrochar, which has high mechanical properties, self-healing crack capabilities, and pollutant adsorption abilities. The cracking of mortar and other cementitious materials is essential in anticipating and reducing building damages and ages due to various reasons, such as chemical reactions, foundation movements, climatic changes, and environmental stresses. This leads to the creation of self-healing mortar, which is produced by adding reductive crack size materials to form calcium carbonate (CaCO3) and silicate hydrate (3CaO.2SiO2.2H2O, CSH). One of these materials is known as activated charcoal, which is obtained from oil palm shells (OPS) and oil palm empty fruit bunches (OPEFB) fibres. This is because the OPS-activated charcoal minimizes crack sizes and functions as a gaseous pollutant absorber. In this study, activated charcoal was used as fine aggregate to substitute a part of the utilized sand. This indicated that the utilized content varied between 1–3 wt.% cement. Also, the mortar samples were tested after 28 days of cure, including the mechanical properties and gaseous pollutant adsorption abilities. Based on this study, the crack recovery test was also performed at specific forces and wet/dry cycles, respectively, indicating that the mortar with the addition of 3% activated charcoal showed the best characteristics. Using 3% of the cement weight, OPEFB hydrochar subsequently varied at 1, 2, and 3% of the mortar volume, respectively. Therefore, the mortar with 3 and 1% of OPS-activated charcoal and OPEFB hydrochar had the best properties, based on mechanical, self-healing, and pollutant adsorption abilities.
Fast Evaluation and Comparison of the Energy Performances of Elastomers from Relative Energy Stored Identification under Mechanical Loadings
Authors: Le Cam Jean-Benoît
Published: January 2022

The way in which elastomers use mechanical energy to deform provides information about their mechanical performance in situations that require substantial characterization in terms of test time and cost. This is especially true since it is usually necessary to explore many chemical compositions to obtain the most relevant one. This paper presents a simple and fast approach to characterizing the mechanical and energy behavior of elastomers, that is, how they use the mechanical energy brought to them. The methodology consists of performing one uniaxial cyclic tensile test with a simultaneous temperature measurement. The temperature measurement at the specimen surface is processed with the heat diffusion equation to reconstruct the heat source fields, which in fact amounts to surface calorimetry. Then, the part of the energy involved in the mechanical hysteresis loop that is not converted into heat can be identified and a quantity γse is introduced for evaluating the energy performance of the materials. This quantity is defined as an energy ratio and assesses the ability of the material to store and release a certain amount of mechanical energy through reversible microstructure changes. Therefore, it quantifies the relative energy that is not used to damage the material, for example to propagate cracks, and that is not dissipated as heat. In this paper, different crystallizable materials have been considered, filled and unfilled. This approach opens many perspectives to discriminate, in an accelerated way, the factors affecting these energetic performances of elastomers, at the first order are obviously the formulation, the aging and the mechanical loading. In addition, such an approach is well adapted to better characterize the elastocaloric effects in elastomeric materials.
Synthesis and Characterizations of Eco-Friendly Organosolv Lignin-Based Polyurethane Coating Films for the Coating Industry
Authors: Bergamasco Sara , Tamantini Swati , Zikeli Florian , Vinciguerra Vittorio , Scarascia Mugnozza Giuseppe , Romagnoli Manuela
Published: January 2022

Three different formulations of bio-based polyurethane (PU), varying the weight ratio between Organosolv lignin and a commercial isocyanate, were synthesized. The coating formulations were characterized by SEM, pyrolysis-GC/MS, FTIR spectroscopy and FTIR mapping, which confirmed the successful formation of urethane bonds between commercial isocyanate and hydroxyl groups deriving from lignin. The coatings were applied on beech wood samples to measure color and contact angles, and eventually FTIR mapping of the coated wood samples was performed. FTIR mapping is an interesting tool to monitor the distribution of PU chemical bonds on the coating surface and to evaluate the homogeneity of the applied coating films. Increasing the lignin content of the PU coatings results in more red-yellow and darker tones, while the commercial PU coating is transparent. For a higher lignin concentration, the solid content as well as the weight gain of the applied coatings increase. A higher percentage of lignin in the prepared PU formulations leads to superficial cracks and therefore higher coating permeability compared to the commercial PU, but the prepared lignin-based PU coating still makes a raw wood surface significantly more hydrophobic. Apparently, additives such as film-formers with low surface tension to counteract cracks’ formation are necessary to improve the performance of lignin-based PU coatings.
Synthesis of a Novel Water-Soluble Polymer Complexant Phosphorylated Chitosan for Rare Earth Complexation
Authors: Chen Yuxin , Chen Yujuan , Lu Dandan , Qiu Yunren
Published: January 2022

Combining the characteristics of rare earth extractants and water-soluble polymer complexants, a novel complexant phosphorylated chitosan (PCS) was synthesized by Kabachnik–Fields reaction with alkalized chitosan, dimethyl phosphonate, and formaldehyde as raw materials and toluene-4-sulfonic acid monohydrate (TsOH) as catalyst. The complexation properties of PCS and poly (acrylic acid) sodium (PAAS) for lanthanum ions in the solution were compared at the same pH and room temperature. In addition, the frontier molecular orbital energies of polymer–La complexes were calculated by the density functional theory method, which confirmed the complexation properties of the polymers to rare earths. The results indicate that the PCS has better water solubility compared with chitosan and good complex ability to rare earths, which can be used for rare earth separation by the complexation–ultrafiltration process.
Analysis of Fe(II)-Ni(II) Electrochemical Reduction Process and Electrodeposition of FeNi Films
Authors: Qi Yanling , He Chenchen , Zhang Run , Wang Wei
Published: January 2022

The effects of boric acid and ammonium sulfate on the electrochemical reduction process of Fe(II) Ni(II) were studied. A series of FeNi thin films were prepared by electrodeposition with different current density and Fe(II) concentration in solution. Linear sweep voltammetry (LSV) results show that the reduction current of Fe(II) is higher than that of Ni(II) at the same concentration of Fe(II) and Ni(II) as well as the same electrodeposition parameters. Adding H3BO3 to Fe(II) Ni(II) solution is beneficial to obtain brighter and compact coating, and adding (NH4)2SO4 is beneficial to obtain higher reduction current density. Energy dispersive X-Ray spectroscopy (EDS) results show that the current density has a significant and nonlinear effect on the Fe content in FeNi thin films. The highest Fe content is obtained at a current density of 25 A∙cm−2. SEM results show that the surface morphology of FeNi films is controlled by the content of Ni and Fe in the films. With increasing Fe content in the film, the morphology of the film changes from smooth and compact to spherical bulge and eventually to smooth again. X-ray diffraction (XRD) results show that the structure of FeNi films is controlled by the content of Ni and Fe in the film. With increasing of Fe content in the film, the structure of the film changes from FCC (111) phase dominant to BCC (110) phase dominant. The average grain size of FeNi films does not change with solution composition and current density. The results of magnetic properties show that the saturation magnetization Ms is proportional to the Fe content in the films, and the maximum value of Ms appears at the highest Fe content. The coercivity Hc is almost independent of Fe content in the films and does not change with solution composition and current density.
Dilemmas of Religious Education, Freedom of Religion and Education in Cyprus
Authors: Latif Dilek
Published: January 2022

The boundaries between secularism, democracy, pluralism, and religious diversity cannot easily be demarcated. Bringing democratic and secular values together with religious pluralism, accommodating different religious communities, and acknowledging individual rights is a great challenge for many societies. In parallel, religious education (RE) in state schools has been a controversial and unresolved issue. On both sides of Cyprus, RE is organized in a mono-confessional way: while the Christian Orthodox content of RE is linked with Greek national identity in the Greek Cypriot South, Sunni Islamic RE is linked with the Turkish national identity in the Turkish Cypriot North. On both sides of the island, the compulsory and mono-confessional characters of RE, as well as the national curricula and textbooks that are used, are a source of conflict. Within this context, this article explores the way RE (Orthodox Christian, Sunni Islamic) is organized in Cyprus and to what extent this may lead to an infringement of the freedom of religion and freedom of education.
The Effect of Religious Beliefs and Attitudes in Intrinsic and Extrinsic Optimism and Pessimism in Players of Games of Chance
Authors: Mónico Lisete S. , Alferes Valentim R.
Published: January 2022

Games of chance usually make people feel a whirlwind of emotions, especially in gambling. While those games depend more on luck than on individuals’ skills, optimism should be a distinctive feature. Considering the classic literature of the effects of religiosity on risk behaviors, the issue of the influence of religiosity on optimism in players of games of chance has been less studied, especially when we considered optimism as a multidimensional concept comprising intrinsic and extrinsic optimism and pessimism. Aims: To analyze the effect of religious beliefs and attitudes in optimism and pessimism dimensions in players of games of chance and gambling. Method: The sample consists of 271 recurring players of games of chance and gambling, who answered a questionnaire composed of measures of religious beliefs and attitudes, optimism, pessimism, and estimates of future occurrences, evidencing good psychometric properties. Results: Players are moderately religious and more optimistic than pessimistic, estimating a chance of 36% of highly unlikely desirable events. The structural model showed an overall influence of religious beliefs and attitudes higher on optimism (R2 = 44%) than on pessimism (R2 = 5%). However, the distinction between intrinsic and extrinsic optimism has shown that the players anchor their optimism in different kinds of beliefs. Extrinsic desirable events, like winning the lottery, were more predicted by religious beliefs and attitudes in comparison with intrinsic desirable events. Inversely, religious beliefs and attitudes tend to predict more intrinsic pessimism in comparison with intrinsic optimism. Conclusions: Optimism is not a one-dimensional construct, should be analyzed considering the dichotomies of optimism/pessimism and intrinsic/extrinsic. In recurring players of games of chance and gambling, religious beliefs and attitudes predicted more optimism than pessimism, being more associated with extrinsic than intrinsic desirable events. More intrinsically pessimistic players seem to recur to religiosity to anchor their positive expectations.
Creating Demand and Creating Knowledge Communities: Myanmar/Burmese Buddhist Women, Monk Teachers, and the Shaping of Transnational Teachings
Authors: Saruya Rachelle
Published: January 2022

The importance of Abhidhamma (higher doctrine) in Myanmar Buddhist society is well known. However, it is only within the last century that this doctrine has become more accessible to the laity, and specifically to women devotees. Today, women make up the majority of monks’ devotees in the country. Indeed, as this article argues, a major role in increasing the Abhidhamma’s importance and visibility in Burmese society has been played by women. Although monks such as Ledi Sayadaw (1846–1923) reworked the teachings to make them more accessible to the laity, laywomen seem to have played an active role in creating a “demand” for learning the more difficult Buddhist teachings that were previously only available to monastic elites. It may be difficult to find individual female authors or references to women in texts written by monks during the earlier part of the colonial era, yet we can find examples of women displaying agency as part of larger groups. This fact complicates the notion of individual agency that is usually focused on in current research. During the colonial era, a considerable number of literate women were part of a “growing reading public,” and I argue that Burmese laywomen created a “demand” for learning Buddhist doctrine, with monks then creating a “supply”. My suspicions grew regarding women’s “demand” for learning, from multi-sited ethnographic fieldwork carried out in Myanmar at a village monastery near Meiktila in 2014, and at a suburban house monastery in the San Francisco Bay Area during various visits beginning in 2010. I found that after observing the same teaching monk in both places that one woman student was responsible for creating these “knowledge communities” after creating a “demand” to learn the Abhidhamma. I was also able to learn how this monk’s doctrinal content and pedagogical methods of his teaching practice had been impacted not only by the different teaching environments, but also by the female students at the two sites.
Beyond the Global Mufti: Religious Authority as Political Action
Authors: Belhaj Abdessamad
Published: January 2022

The International Union of Muslim Scholars, headquartered in Qatar, is an organisation of Muslim jurists founded in 2004 by Yūsuf al-Qaraḍāwī and led today by Aḥmad al-Raysūnī. Despite its importance in the current religious-political discourse in the Muslim world and beyond, this organisation received little attention from scholars, and no study to date has been dedicated to examine its claims and practices of authority. The central thesis of this paper is that the jurists of IUMS are religious and political authorities who: 1. embrace a wide range of “umma” issues, which allow IUMS to appear as the “authentic” and “autonomous” “guardian” of Islam; 2. play a role in international relations (ranging from Chad to China) as “supporters” of particular political actions; 3. negotiate a new type of religious authority embodied by the scholar-activist who emerged as a reaction to the deep religious and political transformations in the Sunni world. To conduct this case study, I approached IUMS from the perspective of sociology of religion (with a focus on the problem of authority) and relied on qualitative methods of analysis (contextualisation, descriptive discourse analysis, in particular), inspecting the local context of IUMS in Qatar as well the global context of umma politics, and using Arabic sources available on its website.
Can I Pay at Purgatory? The Negative Impact of the Purgatory Ethic in Islamic Societies: Theoretical and Empirical Evidence
Authors: Al-Issa Riyad Salim , Krauss Steven Eric , Roslan Samsilah , Abdullah Haslinda
Published: January 2022

The psychological and social effects of the doctrine of purgatory (temporary afterlife punishment) have not received sufficient attention from sociologists. Temporary afterlife punishment (TAP) is any kind of ‘temporary’ torment a person believes they will receive after death as a result of one’s sins, before admission into heaven/paradise. Investigating the effects of TAP beliefs can help to understand their social impact on contemporary Islamic societies. Drawing on related research on the Protestant ethic hypothesis, and self-control theory, the present study theorized the negative psychological and social impact of TAP. We argue that the effect of the Predestination doctrine on pro-sociality is best attributed to the Protestant denial of belief in TAP, and that the positive impact of afterlife punishment beliefs on self-control and prosocial behavior decreases with belief in TAP. To test these hypotheses, we first developed the Temporary Afterlife Punishment Expectations (TAPE) scale and examined the relationship between TAPE and self-control, rule-breaking ability, and integrity (as an indicator of prosocial behavior). Data were collected from Muslim youth in two countries (Jordan N = 605 and Malaysia N = 303). Exploratory and confirmatory factor analyses of the Jordanian data support the construct validity of the TAPE scale. In line with our hypotheses, path analysis results supported the negative effects of TAPE on self-control, rule-breaking ability, and integrity. Replicating the study with the Malaysian sample led to similar results. Future research directions are recommended.
Transformer for Tree Counting in Aerial Images
Authors: Chen Guang , Shang Yi
Published: January 2022

The number of trees and their spatial distribution are key information for forest management. In recent years, deep learning-based approaches have been proposed and shown promising results in lowering the expensive labor cost of a forest inventory. In this paper, we propose a new efficient deep learning model called density transformer or DENT for automatic tree counting from aerial images. The architecture of DENT contains a multi-receptive field convolutional neural network to extract visual feature representation from local patches and their wide context, a transformer encoder to transfer contextual information across correlated positions, a density map generator to generate spatial distribution map of trees, and a fast tree counter to estimate the number of trees in each input image. We compare DENT with a variety of state-of-art methods, including one-stage and two-stage, anchor-based and anchor-free deep neural detectors, and different types of fully convolutional regressors for density estimation. The methods are evaluated on a new large dataset we built and an existing cross-site dataset. DENT achieves top accuracy on both datasets, significantly outperforming most of the other methods. We have released our new dataset, called Yosemite Tree Dataset, containing a 10 km2 rectangular study area with around 100k trees annotated, as a benchmark for public access.
3MRS: An Effective Coarse-to-Fine Matching Method for Multimodal Remote Sensing Imagery
Authors: Fan Zhongli , Liu Yuxian , Liu Yuxuan , Zhang Li , Zhang Junjun , Sun Yushan , Ai Haibin
Published: January 2022

The fusion of image data from multiple sensors is crucial for many applications. However, there are significant nonlinear intensity deformations between images from different kinds of sensors, leading to matching failure. To address this need, this paper proposes an effective coarse-to-fine matching method for multimodal remote sensing images (3MRS). In the coarse matching stage, feature points are first detected on a maximum moment map calculated with a phase congruency model. Then, feature description is conducted using an index map constructed by finding the index of the maximum value in all orientations of convolved images obtained using a set of log-Gabor filters. At last, several matches are built through image matching and outlier removal, which can be used to estimate a reliable affine transformation model between the images. In the stage of fine matching, we develop a novel template matching method based on the log-Gabor convolution image sequence and match the template features with a 3D phase correlation matching strategy, given that the initial correspondences are achieved with the estimated transformation. Results show that compared with SIFT, and three state-of-the-art methods designed for multimodal image matching, PSO-SIFT, HAPCG, and RIFT, only 3MRS successfully matched all six types of multimodal remote sensing image pairs: optical–optical, optical–infrared, optical–depth, optical–map, optical–SAR, and day–night, with each including ten different image pairs. On average, the number of correct matches (NCM) of 3MRS was 164.47, 123.91, 4.88, and 4.33 times that of SIFT, PSO-SIFT, HAPCG, and RIFT for the successfully matched image pairs of each method. In terms of accuracy, the root-mean-square error of correct matches for 3MRS, SIFT, PSO-SIFT, HAPCG, and RIFT are 1.47, 1.98, 1.79, 2.83, and 2.45 pixels, respectively, revealing that 3MRS got the highest accuracy. Even though the total running time of 3MRS was the longest, the efficiency for obtaining one correct match is the highest considering the most significant number of matches. The source code of 3MRS and the experimental datasets and detailed results are publicly available.
Assessment and Inter-Comparison of Multi-Source High Spatial Resolution Evapotranspiration Products over Lancang–Mekong River Basin, Southeast Asia
Authors: Chen Houbing , Gnanamoorthy Palingamoorthy , Chen Yaoliang , Mansaray Lamin R. , Song Qinghai , Liao Kuo , Shi Aoni , Feng Ganlin , Sun Chenna
Published: January 2022

Evapotranspiration (ET) plays a crucial role in water balance within the global hydrological cycle. Timely assessment of ET products can provide the scientific basis for quantitative analysis of hydrological cycle processes and water resources assessment. In this paper, four high spatial resolution remote sensing ET products—the Moderate-resolution Imaging Spectroradiometer global terrestrial evapotranspiration product (MOD16), the ET product based on Penman–Monteith–Leuning equation version 2 (PML-V2), the ET product based on the Breathing Earth System Simulator (BESS) and the ET product of the Global LAnd Surface Satellite (GLASS)—were firstly assessed using the eddy covariance (EC) of different vegetation types in the Lancang–Mekong River Basin (LMRB). To fully assess the performances of these four products, spatiotemporal inter-comparisons and literature comparisons were also conducted across different climatic zones. The results are summarized as follows: (1) MOD16 does not perform well as compared to the other three products, with its Root Mean Square Error (RMSE) being higher than GLASS, PML-V2 and BESS, which are approximately 0.47 mm/8-day, 0.66 mm/8-day, and 0.90 mm/8-day, respectively; (2) the performance of each product varies across different vegetation types, and even within the same climate zone. PML-V2 performs best in evergreen broadleaf forests, BESS performs best in deciduous broadleaf forests and croplands, and GLASS performs best in shrubs, grasslands and mixed vegetation; (3) each product can well reflect the spatial difference brought by topography, climate and vegetation over the entire basin but all four ET products do not show either a consistent temporal trend or a uniform spatial distribution; (4) ET ranges of these four products over LMRB are consistent with previous literature in evergreen broadleaf forests, deciduous broadleaf forests, needleleaf forests and mixed forests in other regions with the same climate zones, but they show great differences in croplands, grasslands and shrubs. This study will contribute to improving our understanding of these four ET products in the different climatic zones and vegetation types over LMRB.
Meta-Pixel-Driven Embeddable Discriminative Target and Background Dictionary Pair Learning for Hyperspectral Target Detection
Authors: Guo Tan , Luo Fulin , Fang Leyuan , Zhang Bob
Published: January 2022

In hyperspectral target detection, the spectral high-dimensionality, variability, and heterogeneity will pose great challenges to the accurate characterizations of the target and background. To alleviate the problems, we propose a Meta-pixel-driven Embeddable Discriminative target and background Dictionary Pair (MEDDP) learning model by combining low-dimensional embeddable subspace projection and the discriminative target and background dictionary pair learning. In MEDDP, the meta-pixel set is built by taking the merits of homogeneous superpixel segmentation and the local manifold affinity structures, which can significantly reduce the influence of spectral variability and find the most typical and informative prototype spectral signature. Afterward, an embeddable discriminative dictionary pair learning model is established to learn a target and background dictionary pair based on the structural incoherent constraint with embeddable subspace projection. The proposed joint learning strategy can reduce the high-dimensional redundant information and simultaneously enhance the discrimination and compactness of the target and background dictionaries. The proposed MEDDP model is solved by an iterative and alternate optimization algorithm and applied with the meta-pixel-level target detection method. Experimental results on four benchmark HSI datasets indicate that the proposed method can consistently yield promising performance in comparison with some state-of-the-art target detectors.